U.S. Department
of Commerce
Volume 102
Number 1
January 2004
Fishery
Bulletin
U.S. Department
of Commerce
Donaid L. Evans
Secretary
National Oceanic
and Atmospheric
Administration
Vice Admiral
Conrad C. Lautenbacher Jr.,
USN (ret.)
Under Secretary for
Oceans and Atmosphere
National Marine
Fisheries Service
William T. Hogarth
Assistant Administrator
for Fisheries
.^TOFCo.
X
K1^ /
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U.S. Department
of Commerce
Seattle, Washington
Volume 102
Number 1
January 2004
Fishery
Bulletin
Contents
ary
MAR 5 2004
The conclusions and opinions expressed
in Fisher)' Bulletin are solely those of the
authors and do not represent the official
position of the National Marine Fisher-
ies Service (NOAA) or any other agency
or institution.
The National Marine Fisheries Service
(NMFS) does not approve, recommend, or
endorse any proprietary product or pro-
prietary material mentioned in this pub-
lication. No reference shall be made to
NMFS. or to this publication furnished by
NMFS, in any advertising or sales pro-
motion which would indicate or imply
that NMFS approves, recommends, or
endorses any proprietary product or pro-
prietary material mentioned herein, or
which has as its purpose an intent to
cause directly or indirectly the advertised
product to be used or purchased because
of this NMFS publication.
Articles
1-13 Alonzo, Suzanne H., and Marc Mangel
The effects of size-selective fisheries on the stock dynamics of
and sperm limitation in sex-changing fish
14-24 Baba, Katsuhisa, Toshifumi Kawajiri,
Yasuhiro Kuwahara, and Shigeru Nakao
An environmentally based growth model that uses finite
difference calculus with maximum likelihood method:
its application to the brackish water bivalve
Corbicula /aponica in Lake Abashiri, Japan
25-46 Brodeur, Rick D., Joseph P. Fisher, David J. Teel,
Robert L. Emmett, Edmundo Casillas,
and Todd W. Miller
Juvenile salmomd distribution, growth, condition, origin,
and environmental and species associations
in the Northern California Current
47-62 Garcia-Rodrfguez, Francisco J.,
and David Aurioles-Gamboa
Spatial and temporal variation in the diet of the
California sea lion (Zalophus californianus)
in the Gulf of California, Mexico
63-77 Jung, Sukgeun, and Edward D. Houde
Recruitment and spawning-stock biomass distribution
of bay anchovy (Anchoa mitchilli) in Chesapeake Bay
78-93 Kellison, Todd G., and David B. Eggleston
Coupling ecology and economy: modeling
optimal release scenarios for summer flounder
(Paralichthys dentatus) stock enhancement
94-107 Kritzer, Jacob P.
Sex-specific growth and mortality, spawning season,
and female maturation of the stripey bass
(Lut/anus carponotatus) on the Great Barrrier Reef
Fishery Bulletin 102(1)
108-117 Orr, Anthony J., Adria S. Banks, Steve Mellman, Harriet R. Huber,
Robert L. DeLong, and Robin F. Brown
Examination of the foraging habits of Pacific harbor seal (Phoca vitulina richardsi) to describe their use
of the Umpqua River, Oregon, and their predation on salmonids
Companion paper with Purcell et al., see "Notes" below.
118-126 Park, Wongyu, R. Ian Perry, and Sung Yun Hong
Larval development of the sidestriped shrimp (Pandalopsis dispar Rathbun) (Crustacea, Decapoda, Pandahdae)
reared in the laboratory
127-141 Pearson, Donald E., and Franklin R. Shaw
Sources of age determination errors for sablefish (Anop/opoma fimbria)
142-155 Powell, Allyn B., Robin T. Cheshire, Elisabeth H. Laban, James Colvocoresses, Patrick O Donnell,
and Marie Davidian
Growth, mortality, and hatchdate distributions of larval and juvenile spotted seatrout (Cynoscion nebulosus) in
Florida Bay, Everglades National Park
156-167 Santana, Francisco M., and Rosangela Lessa
Age determination and growth of the night shark (Carcharhinus signatus) off the northeastern Brazilian coast
168-178 Smith, Keith R„ David A. Somerton, Mei-Sun Yang, and Daniel G. Nichol
Distribution and biology of prowfish (Zaprora silenus) in the northeast Pacific
179-195 Ward, Peter, Ransom A. Myers, and Wade Blanchard
Fish lost at sea: the effect of soak time on pelagic longlme catches
196-206 Watanabe, Chikako, and Akihiko Yatsu
Effects of density-dependence and sea surface temperature on interannual variation in length-at-age
of chub mackerel (Scomber japonicus) in the Kuroshio-Oyashio area during 1970-1997
Notes
207-212 Llanos-Rivera, Alejandra, and Leonardo R. Castro
Latitudinal and seasonal egg-size variation of the anchoveta (Engrauhs nngens) off the Chilean coast
213-220 Purcell, Maureen, Greg Mackey, Eric LaHood, Harriet Huber, and Linda Park
Molecular methods for the genetic identification of salmonid prey from Pacific harbor seal
(.Phoca vitulina richardsi) scat
Companion paper with Orr et al., see "Articles" above.
221-229 Weng, Kevin C, and Barbara A. Block
Diel vertical migration of the bigeye thresher shark (Alopias superciliosus), a species possessing
orbital retia mirabilia
231 Subscription form
Abstract— Fisheries models have tradi-
tionally focused on patterns of growth,
fecundity, and survival offish. However,
reproductive rates are the outcome of
a variety of interconnected factors
such as life-history strategies, mating
patterns, population sex ratio, social
interactions, and individual fecundity
and fertility. Behaviorally appropriate
models are necessary to understand
stock dynamics and predict the success
of management strategies. Protogynous
sex-changing fish present a challenge
for management because size-selective
fisheries can drastically reduce repro-
ductive rates. We present a general
framework using an individual-based
simulation model to determine the
effect, of life-history pattern, sperm
production, mating system, and man-
agement strategy on stock dynamics.
We apply this general approach to the
specific question of how size-selective
fisheries that remove mainly males
will impact the stock dynamics of a
protogynous population with fixed
sex change compared to an otherwise
identical dioecious population. In
this dioecious population, we kept all
aspects of the stock constant except
for the pattern of sex determination
(i.e. whether the species changes sex
or is dioecious). Protogynous stocks
with fixed sex change are predicted to
be very sensitive to the size-selective
fishing pattern. If all male size classes
are fished, protogynous populations are
predicted to crash even at relatively low
fishing mortality. When some male size
classes escape fishing, we predict that
the mean population size of sex-chang-
ing stocks will decrease proportionally
less than the mean population size of
dioecious species experiencing the same
fishing mortality. For protogynous spe-
cies, spawning-per-recruit measures
that ignore fertilization rates are not
good indicators of the impact of fishing
on the population. Decreased mating
aggregation size is predicted to lead to
an increased effect of sperm limitation
at constant fishing mortality and effort.
Marine protected areas have the poten-
tial to mitigate some effects of fishing
on sperm limitation in sex-changing
populations.
Manuscript approved for publication
23 July 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull 102:1-13(2004).
The effects of size-selective fisheries
on the stock dynamics of and sperm limitation
in sex-changing fish
Suzanne H. Aionzo
Institute of Marine Sciences and the Center lor Stock Assessment Research (CSTAR)
University of California Santa Cruz
1156 High Street
Santa Cruz, California 95064
E-mail address shalonzoiS'ucscedu
Marc Mangel
Department of Applied Mathematics and Statistics
Jack Baskin School of Engineering and the Center for Stock Assessment Research (CSTAR)
University of California Santa Cruz
1156 High Street
Santa Cruz, California 95064
Fisheries models are generally used
to predict the impact of fishing on
stock dynamics and yield (Quinn and
Deriso, 1999; Haddon, 2001). Classic
models have focused mainly on growth,
fecundity, and survival of species, with-
out considering the impact of mating
patterns on reproduction, survival,
and recruitment. It is now recognized
that life-history strategies and mating
behavior will affect stock dynamics.
Even so, general quantitative predic-
tions regarding the effect of specific
life-history patterns on fished popula-
tions are limited and further theory is
needed (Levin and Grimes. 2002). It
is likely that management strategies
taking into account a species' reproduc-
tive behavior will greatly improve our
ability to manage stocks (e.g. Beets and
Friedlander, 1999). We would also like
to know when the mating behavior and
reproductive strategies of a stock will
be worth investigating and when tradi-
tional management techniques will be
sufficient. For example, in a manage-
ment context, how do sex-changing
stocks differ from separate-sex species?
Here, we take an initial step toward
generating a theory of the combined
effect of life history and mating pat-
terns on stock dynamics by focusing
on the potential for and effect of sperm
limitation in a protogynous (female to
male) sex-changing stock. We focus
on protogyny for this article because
numerous protogynous species are com-
mercially important, namely red porgy
{Pagrus pagrus), gag grouper iMyc-
teroperca microlepis), and California
sheephead iSemicossyphus pulcher).
Sex-changing fish present a unique
challenge for management because size-
selective fisheries have the potential to
drastically reduce reproductive rates
and population size at levels of fishing
that would not pose a problem for dioe-
cious (separate-sex) species (Huntsman
and Schaaf, 1994; Armsworth, 2001; Fu
et al., 2001). On the other hand, pro-
togynous stocks may be less sensitive
to the removal of large individuals if
females are not fished and fertilization
rates remain high. Many commercially
important species are known to change
sex (Bannerot et al., 1987; Shapiro,
1987; Coleman et al., 1996; Brule et al.,
1999; Adams et al., 2000; Armsworth,
2001; Fu et al., 2001). Previous models
have shown that sex-changing fish may
be vulnerable to fishing (Bannerot et
al., 1987; Huntsman and Schaaf, 1994;
Armsworth, 2001; Fu et al.. 2001).
Complications arise because the ef-
fect of fishing on a sex-changing spe-
cies is mediated by many aspects of
their reproductive biology, such as sex
ratio, size-dependent fecundity, spawn-
ing aggregation size, and reproductive
skew. Furthermore, patterns of sex
change have cascading effects on the
sex ratio, social interactions, population
Fishery Bulletin 102(1)
fecundity, and male sperm production — all of which can
affect stock dynamics. Thus, we cannot treat sex change as
an isolated aspect of a species. Instead, we must consider
sex change within the context of the mating system and
the life history of the species to make general predictions.
Behaviorally appropriate models are required to gener-
ate constructive qualitative and quantitative theory. Past
theory has indicated that sex-changing populations exhibit
stock dynamics that often differ from those of dioecious
populations (Bannerot et al., 1987; Huntsman and Schaaf,
1994; Armsworth, 2001; Fu et al, 2001 ). Furthermore, pro-
togynous stocks are predicted to be sensitive to fishing pat-
tern and may exhibit nonlinear dynamics that could lead
to population crashes (Armsworth, 2001). However, it is not
known which aspects of the mating behavior and life his-
tory pattern of sex-changing stocks drive these differences.
Here we focus on comparing a protogynous stock with an
otherwise identical dioecious population to determine the
effect of mating aggregation size, fertilization rates, and
life history pattern on stock dynamics.
Size-selective (or age-selective) fisheries can impact a
species through a decrease in spawning stock biomass, in
general and through the removal of highly fecund larger
and older individuals, in particular (Sadovy, 2001). How-
ever, in protogynous species, fisheries that preferentially
remove large males can also change the population sex
ratio; however, the exact effect of fishing pressure on stock
dynamics in a protogynous species is complex. At one
extreme, the complete removal of males from the popula-
tion would cause a stock to crash, potentially making sex-
changing species more vulnerable than dioecious species
in the face of high fishing pressures. At the other extreme,
sex-changing species may be less affected by size-selective
fisheries if female fecundity limits recruitment and males
are not removed in such numbers as to reduce mating
or fertilization rates. Currently, there is no theory that
predicts the potential for sperm limitation in protogynous
stocks as a function of gamete production, fertilization
rates, and mating pattern.
It has been suggested that marine reserves may be a vi-
able management option for species where highly fecund
older individuals are critical to reproduction (Levin and
Grimes, 2002). However, no theory exists that can predict
the impact of marine reserves on stock dynamics in sex-
changing species. We consider the impact of a no-take
marine reserve on the stock dynamics. We compare the
effect of setting aside 0-30% of the spawning population
in a reserve. We assume that larval production is exported
from within the reserve to the rest of the population and
determine whether the reserve can mediate some of the ef-
fects of fishing outside the reserve because this represents
the optimal scenario for marine reserves. We also compare
mean catch rates in the presence and absence of a reserve
as a function of fishing mortality.
Spawning-per-recruit (SPR) measures are often used to
estimate the impact of fishing on a stock (Parkes, 2000;
Jennings et al., 2001). Ideally, a spawning-per-recruit mea-
sure would keep track of per-recruit production of larvae
or eggs (Jennings et al., 2001). However, spawning stock
biomass per recruit (SSBR) is commonly used to estimate
the reproductive output per recruit at different intensities
of fishing. One assumes that the biomass of mature fish is
linearly related to reproductive output, which may be the
case when egg production limits biomass and fecundity in-
creases linearly with biomass. In protogynous stocks, over-
fishing of males alone may decrease fertilization rates and
hence reproductive output without affecting either female
biomass or egg production. Thus, in protogynous stocks or
sex-selective fisheries, classic measures of spawning per re-
cruit may misrepresent the impact of fishing on the stock's
reproduction and hence population stability (Punt et al.,
1993). We examine a variety of per-recruit measures and
determine their ability to predict changes due to exploita-
tion in mean population size.
In this study, we describe a general approach using sex-
and size-dependent individual-based simulation models
that predict reproduction, size distribution, and sex ratio
in fished populations as a function of mating system and
sex-change pattern. We examine the case where sex change
occurs at a specific size threshold. We recognize that plastic
and socially mediated sex-change patterns have been ob-
served, and our results will apply only to species with fixed
sex change. We explore the impact of mating aggregation
size, sperm production, and asymptotic fertilization rates
on the predicted stock dynamics in the presence of exploita-
tion. We make predictions regarding the effects of fishing
on population size, reproduction, sex ratio, size distribu-
tion, and fertilization rates. We also compare our results
to previous work and discuss future directions.
Methods
We used an individual-based simulation to predict the size
distribution, individual and population fecundity, popula-
tion sex ratio, fertilization rate, and population size as a
function of fishing mortality (Fig. 1). Individuals vary in
age, size, sex, and mating site. Population size varies as a
function of baseline survival, fishing mortality, reproduc-
tion, and larval recruitment. Reproduction depends on the
pattern of sex change, mating system, sex ratio, mating site,
and fecundity (or fertility) of individual males and females.
For each annual time period, we determined individual
survival, the size and age of these individuals in the next
time period, and the total production of surviving offspring
by those individuals. Initial analyses showed that a station-
ary size, sex, and age distribution is found within approxi-
mately 50 time periods and is independent of the initial
population conditions. Thus, we simulated 100 time periods
prior to examining the impact of fishing on stock dynamics
to ensure that the population had already reached the sta-
tionary size and sex distribution for that scenario and set
of parameters. We then examined the model for 100 repro-
ductive seasons in the presence of fishing with a constant
mean fishing mortality. Because a number of elements of
the model were stochastic, we examined 20 simulations for
each scenario and set of parameter values. Initial analyses
indicated that 20 simulations were more than sufficient to
lead to low variability in the key measures of interest. We
assumed that reproduction occurs at the level of the mating
Alonzo and Mangel: The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish 3
group at different reproductive sites. Individual sur-
vival, maturation, sex change, and mating site were
determined stochastically as described below.
Fishing and adult survival
We assumed that adult survival is density indepen-
dent but depends on fishing selectivity, fishing mor-
tality, and baseline adult mortality in the absence of
fishing. For simplicity, we assumed that age and size do
not affect nonfishing adult mortality p.A. We assumed
that the fishery is size selective; we let L represent fish
size, F represent annual fishing mortality, Lf represent
the size at which there is 50% chance an individual of
that size will be taken, and r represent the steepness
of the selectivity pattern. Then fishing selectivity per
size class siL) is given by
siD-
l + exp-HL-L,))
and adult annual survival becomes
cr(L) = exp(-/iA-Fs(L))
(1)
(2)
We assumed that fishing does not differentially
affect the sexes independent of size. We recognize,
however, that for some species this may not be the
case. We also assumed that fishing occurs each year
prior to reproduction and can represent either pulse or
continuous fishing with an annual mortality F. We let
N it) represent the number of individuals in age class
a at time t so that population size N(t)= Sa Na(t).
Population dynamics
We assumed that the number of larvae that enter the popu-
lation is determined by the production of fertilized eggs Pit)
and the probability that those larvae will survive to recruit.
Pit) is determined by the adult fecundity and fertilization
rates described below. For computational tractability, we
also assumed that a population ceiling Nmax exists (Mangel
and Tier, 1993, 1994 ). However, we chose NmBX large enough
that the stable population size was below the ceiling. Larval
survival has both density-independent and density-depen-
dent components (e.g. Cowen et al., 2000; Sale, 2002). We
used a Beverton-Holt recruitment function to determine
larval survival to the next age class (Quinn and Deriso,
1999; Jennings et al., 2001). Larvae represented the zero-
age class N0(t) and thus the number of larvae surviving to
recruit in any year t is given by
Nnit) = (oPit))/(l+pPit)) if (ctP(t))/(l+pP(t))
+JjNjt)<Nmax
(3)
AT0(*) = max| 0,Nmax-^Na(t) | if (aPlt))/(l+ pPit))
MATING SITES
Adult survival determined by baseline mortality and fishing pattern
Reproduction determined by group fecundity and fertility
No migration between mating sites
Density-dependent and
density-independent
larval survival
Recruitment random
across mating sites
Figure 1
Structure and population dynamics of the individual-based
model. We assumed that all mating sites contribute to a single
larval pool.
where a gives density-independent survival; and /3 deter-
mines the strength of the density-dependence in the larval
phase. In this function, we used the number of fertilized
eggs produced, Pit), rather than spawning stock size. We
selected parameter values for larval survival that allowed
the mean population size to be stationary near the ceiling
in the absence of fishing. We assumed a single larval pool
and that larvae recruit to mating sites at random (Fig. 1).
The population was open between mating sites and we
were simulating the entire stock. Thus, there was no emi-
gration to or immigration from outside populations.
Growth dynamics
We assumed that all larvae enter the population at the
same size, L0. We assumed that growth is deterministic
and independent of sex or reproductive status. We used a
discrete time version of the von Bertalanffy growth equa-
tion (Beverton, 1987, 1992) to determine growth between
age classes of surviving adults in which Lmf represents the
asymptotic size and k is the growth rate. Then an indi-
vidual of length Lit) at time t will grow in the next time
period to size Lit+1) as follows:
Z,(f+l) = Llnf(l + exp(-fc)) + L(f>exp(-A).
(4)
Mating system
We assumed that reproduction occurs at the level of the
mating group, and we examined the effect of varying mating
group size and the number of mating sites. We assumed
Fishery Bulletin 102(1)
that juveniles and adults exhibit site fidelity but that larvae
settle randomly among mating sites. We also assumed that
the population carrying capacity is split equally among the
mating sites and that the total capacity of all mating sites
exceeds the maximum population size in the absence of fish-
ing as determined by adult mortality and the recruitment
function. Therefore, mating sites do not limit recruitment
but may affect reproductive rates. We examined three cases:
1 ) the entire population mates at one site (one mating site
with up to 1000 individuals); 2) a few large mating groups
exist ( 10 sites with a maximum of 100 individuals per site);
and 3) many small mating aggregations exist (20 mating
sites with a maximum of 50 individuals per site). For sim-
plicity, we assumed that within a mating site, individuals
mate in proportion to their fertility and fecundity. Therefore,
large males and females have higher expected reproductive
success. However, we assumed that all males that are large
enough to change sex have a chance of reproducing propor-
tional to their fertility. This is equivalent to assuming that
females exhibit a mate choice threshold I Janetos, 1980) that
has evolved with the size-at-sex change and that females
have an equal probability of mating with males above this
size threshold. However, a large male mating advantage
clearly still exists. We also assumed that fishing mortality
remains constant as mating aggregation size varies. Thus,
we assumed that fishing effort per site does not increase as
the number of mating sites decreases. An alternative would
be to assume that total fishing mortality increases as the
number of mating aggregations decreases.
Maturity
The probability that an individual matures pm(L) is deter-
mined by size. Once an individual matures, she remains
female until sex change (see below). We let Lm represent
the length at which 50% of the individuals will have
matured.
EiL)=aLh,
(7)
P,JL)-
1
where a and b are constants.
Once an individual has changed sex (as determined by
the sex change rule described above) sperm production (in
millions) S(L) is given by
S{L)=cLd ,
(8)
l + exp(-q(L- Lm
(5)
where c and d are constants.
Size-dependent fecundity has been measured in many
fish species (e.g. Gunderson, 1997). A general allometric
relationship between sperm production and size has not
been established. Therefore, we assumed that male gamete
production increases with size at the same rate as that for
females ib=d). We also assumed that males produce many
more sperm at any body length than females produce
eggs. Clearly, other possible patterns exist. We examined
the case where males produce from 102 to 106 sperm for
every egg produced by a female. In the pelagic spawning
wrasse (Thalassoma bifasciatum ), large males release ap-
proximately 1000 times more sperm than females release
eggs (Schultz and Warner, 1991; Warner et al., 1995).
We used recently published data on sperm production
and fertilization rates in the bluehead wrasse (Thalas-
soma bifasciatum) to generate a biologically appropriate
fertilization function for our model (Warner et al., 1995;
Petersen et al., 2001). It is critical to consider a biologically
appropriate form for the function to express fertilization
rates when considering the potential for sperm limitation.
The probability an egg will be fertilized is an increasing
function of the number of sperm available for that mat-
ing (Fig. 2). The number of eggs released per mating also
affects the fertilization rate (Fig. 2). For simplicity, we cal-
culated the average expected fertilization rate per mating
site based on the total production of sperm and eggs at the
site. We let S represent the number of sperm released (in
millions) and £ the number of eggs released at each mating
site. We assumed that the proportion of eggs fertilized per
mating site pF is given by
where q determines the steepness of the probability
function.
Sex change
The probability of sex change, pciL), is a logistic function
of absolute size L
P,.(L) =
l + exp(-p(L-L, ))
(6)
where Lr represents the size at which 50% of the indi-
viduals will change sex from female to male and p is a
constant.
Reproduction
We assumed that female fecundity E(L) depends on indi-
vidual size according to the allometric relationship
Pf
l + iisE + X)S
(9)
where k and % are constants fitted to the data.
The number of eggs fertilized per group is ph-E and the
total production of fertilized eggs. Pit), is the sum of the
number of eggs fertilized in all mating groups.
Measures of spawning stock biomass per recruit
To measure the impact of fishing on stock dynamics, we
computed the total spawning stock biomass per recruit
starting from the beginning of fishing for the next 50
years. We used the generally recognized pattern that
fish wet weight tends to be approximately proportional
to the cube offish length (Gunderson, 1997) to convert
fish length, L, into relative biomass, B(L)~L\ Then we
calculated total female and male spawning stock biomass
Alonzo and Mangel: The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish
per recruit (SSBR). We also kept track of the
total fecundity (egg production per recruit I,
fertility (sperm production per recruit), and
eggs fertilized per recruit.
Marine reserves
^=150 (about 60 females)
OS-
'S 0.6
■s 0.4
02
We examined the effect of no-take marine
reserves on the predicted stock dynamics by
comparing the stock dynamics in the presence
and absence of reserves. Without a reserve,
individuals at all mating sites are subject to
fishing. In the presence of a no-take marine
reserve, we "protect" a percentage of the
mating sites (and thus the population) from
fishing. We examined cases in which 09c, 10%,
20%, and 30% of mating sites were protected
from fishing. We assumed that the population
is completely open among mating sites. Thus,
eggs produced from all mating sites enter one
larval pool and recruitment occurs randomly
between mating sites. Clearly other possibili-
ties exist and could be considered in future analyses, but
this case represents a reasonable baseline situation to con-
sider because many marine fish have pelagic larval phases.
We also recognize that these analyses ignore the effect of
interactions between species within the reserve on stock
dynamics. We examined two situations. In the first case,
reduced fishing effort occurs when mean fishing mortality
is decreased in the presence of reserves because fishing
mortality (F) at the unprotected sites remains the same as
before the reserve. In the second case, the redistribution of
fishing effort occurs when mean fishing mortality across all
sites remains the same because fishing mortality increases
at the unprotected sites.
Comparison of sex-changing stocks and dioecious stocks
Ideally, we would like to distinguish the effects of sex change
in isolation from the confounding effects of mating pattern,
sex ratio, survival, growth, and population fecundity on
stock dynamics. To differentiate whether sex change in iso-
lation or other aspects of the mating system determine the
predicted stock dynamics, we also examined a version of the
model described above for a population where sex is fixed
at birth. In this dioecious population, we keep all aspects
of the stock constant except for the pattern of sex determi-
nation (whether the species changes sex or is dioecious).
One would generally expect a dioecious population with
no differences between the sexes in mortality to exhibit a
50:50 sex ratio ( Fisher, 1930; Trivers, 1972; Charnov, 1982 ).
However, we wanted to control for all differences between
the dioecious and protogynous stocks other than the sex-
determination pattern. Therefore, we considered the same
sex ratio at maturity (0.67=the proportion of adults that
are female) as found in the sex-changing population in the
absence of fishing. Assuming no sex-specific differences in
survival to maturity, this is the same as assuming a 0.67
sex ratio at birth. In this model, individuals remain one sex
(determined randomly at birth) throughout their lifetime.
Km=1750 (about 700 females)
K>750 (about 300 females)
5.000
10.000
1 5.000
20,000
Sperm number (S)
(in millions, about 1 to 100 males)
Figure 2
Fertilization rate as a function of the number of eggs and sperm per mating
site. The saturation parameter Km=\E+x is taken from Equation 9.
Fishing is size but not sex selective. We assumed that males
mature at the same size as females.
Parameter values
We used previous research on California sheephead (Lab-
ridae, Semicossyphus pulcher), a commercially important
sex-changing fish, to provide evolutionarily and ecologi-
cally reasonable parameters for the model. Although the
growth, survival, and reproduction of this species have
been studied, less is known about the factors that induce
sex change and mating behavior. In this species, sex change
occurs at approximately 30 cm although the exact pattern
varies among populations (Warner, 1975; Cowen, 1990). It
is not known whether sex change is fixed or socially medi-
ated. Because nothing is known about fertilization rates in
the California sheephead, we generated k and y <Eq. 9) by
fitting a line through the estimated values of Km for small
and large bluehead wrasse females as a function of their
mean egg production (see Table 1 and Fig. 2; Warner et
al., 1995; Petersen et al., 2001). For parameter values and
sensitivity analyses see Table 1.
Results
We present the average across 20 simulations of the mean
population measures of the last 50 years for each simula-
tion. The variation around the mean in all measures con-
sidered was very low (hundredths of a percent of the mean
or less). For the spawning per recruit (SPR) measures we
give the mean value across the first 50 years of fishing to
ensure that the entire cohort had died before the end of the
simulation. When the ratio of sperm to eggs is 104 to 106,
a single male can fertilize all of the eggs in the population.
When the ratio of sperm to eggs is 102, sperm limitation
occurs even in the absence of fishing. Therefore, we present
results for the case where the ratio of sperm to eggs is 103
Fishery Bulletin 102(1)
Table 1
The following parameters were used in the model.
Parameter
Baseline values
Definition and source
Growth
*
0.05
growth rate (based on Cowen, 1990)
*W
90 cm
asymptotic size (based on Cowen, 1990)
h
8 cm
larval size at recruitment
Population
N
max
1000
maximum population size
V-A
0.35
adult mortality (based on Cowen, 19901
a
0.0001
density-independent larval mortality
P
a/(l-exp(-
-H»
))N
,,^3.33x10--)
larval recruitment function parameter (see text)
Fishing
r
1 (0.1)
steepness of selectivity curve
Lf
30 (25,35)
length at which 509? chance a fish will be removed
F
0-3
fishing mortality
Reproduction
a
7.04
constant in the fecundity relationship (Warner, 1975)
6
2.95
exponent in the fecundity relationship (Warner, 1975)
c
10-3a (10-
2a,
10"
4Q)
constant in the sperm production function (measured in millions
of sperm)
d
b
exponent in the fertility relationship (Warner, 1975)
K
0.000003
slope of fertilization function parameter
X
0.09
intercept of fertilization function parameter (based on Peterson
et al., 2001) see text for details
Maturity
Lm
20 cm
length at which 507c offish mature (Warner, 1975; Cowen. 1990)
Q
1
shape parameter in the maturity function
Sex change
h
30 cm
length at which 50% offish change sex (Warner, 1975; Cowen. 1990)
P
1
shape parameter in the sex change function
and fertilization rates are 100% in the absence of fishing,
but the population must have multiple males for high fer-
tilization rates. For all the results presented in our study
we assumed a fixed sex-change pattern, mating among
males and females at each site proportional to gamete
production, and larval export among mating sites. We also
assumed, unless otherwise noted, a sharp size-selective
fishing pattern (r=l) and that the probability of sex change
and removal of sex-changing fish by the fishery are cen-
tered at the same mean size or Lj=Lc. Clearly, the results
presented in our study may not apply to cases where these
assumptions are not met.
General patterns predicted by the model
First, we examined the general effect of fishing mortality
on the sex-changing stock for the case when one mating
site exists. When Lf= Lc, eggs produced per recruit decrease
only slightly with fishing mortality (e.g. a 3% drop as fish-
ing mortality increased from 0 to 3, Fig. 3A). However, the
mean number of eggs fertilized (both total and per recruit)
decreases sharply as fishing mortality increases (e.g. a 30%
drop as fishing mortality increased from 0 to 3, Fig. 3A).
The number of recruits per year decreases as well. As fish-
ing mortality increases, male spawning stock biomass per
recruit decreases dramatically, whereas changes in female
spawning stock biomass would be practically undetectable
(90% drop for male SSBR, compared with a 3% drop for
female SSBR as F increases from 0 to 3, Fig. 3B). Because of
the drop in male SSBR, total spawning stock biomass (males
and females) per recruit also decreases as fishing mortal-
ity increases. Sperm production per recruit is predicted to
decrease with increasing fishing mortality (Fig. 3C).
Sensitivity of stock dynamics to fishing pattern
In general, mean population size decreases as fishing pres-
sure increases (Fig. 4A). The adult sex ratio (measured as
Alonzo and Mangel: The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish
the percentage of mature individuals that are female) also
increases as fishing mortality increases (Fig. 4B) and the
mean size of adults in the population decreases. These pat-
terns depend on fishing being size selective, which causes a
disproportional take of males. If the size-selectivity of the
fishery targeted smaller size classes (L<LC), a decline in
annual biomass removed by the fishery is predicted with
increasing F and the stock is predicted to crash at a rela-
tively low fishing mortality (Fig. 4C). If the fishery is less
selective (r=0.1, L,=LC), the population is also predicted
to crash for most fishing mortalities. Thus, allowing some
proportion of mature males to consistently escape fishing
is critical even at low fishing mortality. As fishing mortality
increases, the predicted biomass removed by the fishery
increases with diminishing returns ( Fig. 4C ). When Lf=Lc,
the biomass removed by the fishery does not continue to
increase with F because all males above the size at sex
change are being removed by the fishery. In this case, the
males in the population are essentially breeding only once
before they are taken by the fishery. For the range of fish-
ing mortality considered, we did not observe a decline in
biomass taken with increasing F unless L<Lt. or r=0.1. If
more size classes are allowed to escape fishing (Lf>Lc), the
general patterns remain the same, but for the same fishing
mortality (.F), the effect of fishing on the population is less
(Fig. 4). Female biomass does not decrease much with fish-
ing mortality when Lf=Lc even though some females are
removed by the fishery because the probability of a female
changing sex is the probability of it being fished. Therefore,
female loss due to the fishery affects male biomass rather
than female biomass in the population.
Sperm limitation and production
The removal of large males from the population is pre-
dicted to cause sperm limitation and decreased fertiliza-
tion rates (Fig. 3, A and C), leading to a decrease in mean
population size (Fig. 4A). The degree to which the fertiliza-
tion rate and thus the population size decreases depends
to a great extent on the pattern of sperm production
and fertilization. We assumed that only a few males are
needed to fertilize the eggs of many females (Fig. 2). We
also assumed that per-capita reproduction and recruitment
are high even at a low population size (Barrowman and
Myers, 2000). Thus, protogynous populations with lower
sperm production or fertilization rates would experience
greater effects from fishing than predicted in the present
study. Similarly, populations with lower production or sur-
vival would experience larger decreases in population size
even with the same level of sperm limitation and fishing.
In general, however, the removal of males alone from a pro-
togynous population with a fixed sex change is predicted to
cause decreased fertilization rates and lower mean popula-
tion size even when the fertilization rate function is asymp-
totic and individual male sperm production is high.
Mating aggregation size
As mating aggregation size decreased and fishing mortality
and effort remained constant, the effect of fishing on the pop-
Eggs produced
1 1.5 2
Fishing mortality (F)
Figure 3
Spawning-per-recruit measures. Results are presented for
the sex-changing stock with one mating site when L^= Lc
and r=l. Means across 20 simulations are given. For details
see the general text.
ulation increased. As described above, we assumed that fish-
ing effort would not be concentrated on the few large mating
aggregations and thus increase total fishing mortality. The
sex ratio, mean size, mean fecundity, and mean fertility all
remained the same across different mating aggregation
sizes with constant fishing mortality. However, the mean
fertilization rate and number of fertilized eggs per recruit
decreased with mating group size ( Fig. 5 ) even though male
biomass and SSBR remained the same. Both predicted
mean population size and biomass taken decreased as fish-
ing mortality increased (Fig. 5). This pattern was generated
by sperm limitation in small mating groups. Smaller groups
have higher probabilities that sperm production within the
group will not be sufficient to fertilize the eggs produced
within the mating group. Small mating aggregations may
not only be sperm limited but also be male limited and fail
to reproduce completely; populations with small group sizes
(50 individuals or less) were predicted to become extinct in
Fishery Bulletin 102(1)
5-25% of the simulations as fishing mortality (F) increased
from 0 to 1. The impact of mating group size on stock dynam-
ics is thus predicted to be nonlinear. A threshold mating
aggregation size appeared to exist below which sperm limi-
tation and reproductive failure become common.
Spawning-per-recruit measures
For size-selective fishing, the spawning stock biomass per
recruit of females is not predicted to decrease significantly
with increased fishing mortality as long as some male size
classes escape fishing (Lr>Lv). However, male biomass per
recruit and sperm production per recruit are both predicted
to decrease. Although egg production is not predicted to
900
800
A
L,>LC
CD
n 700
to
^\ L,=LC
<= 600 J
o
'ra 500 "
3
g- 400 "
Q.
c 300 "
ra
| 200 '
\l,<lc
100
0
i
0
0.5 1 1.5 2 2.5 3
1 ,
B
L,=LC
x ratio
male)
o o c
-g 03 CO
<n •£ ° 6 '
g .2 0.5 •
ra o 0.4 .
3 Q.
o. 2 0.3 .
P a.
0- — 0.2 .
0.1 ■
\l,<lc
o
0
0.5 1 1.5 2 2.5 3
600.000
C
L,=LC
iomass
the fishery
o o
o o
o o
o o
■o >,
ra £? 300.000
D T3
a a>
c >
< ° 200.000
CD
100,000
U/<
0
0
0.5 1 15 2 2.5 3
Fishing mortality (F)
Figure 4
The effect of size-s
ilect ive fishing on stock dynamics. We present
results for the sex-changing stock with one mating site when
r=l. Means across
20 simulations are given. For details see the
general text.
decrease with increasing size-selective fishing pressure,
the number of fertilized eggs is predicted to decrease.
When all male size classes are fished iL.>Lc), the stock
is predicted to crash and therefore clearly female biomass
and egg production are predicted to decrease with fishing
mortality. In general, the predicted decrease in mean popu-
lation size and reproduction is driven for the most part by
decreased sperm production and consequently a reduction
in the number of eggs fertilized per recruit. The relation-
ships between fishing pressure and the classic spawning-
per-recruit measures do not indicate the true effect that
fishing is predicted to have on the protogynous population
(Fig. 6). When Lf>Lc, female spawning stock biomass per
recruit and eggs produced per recruit showed almost no
effect of fishing on the population, even as mean
population size decreased. Because of the size-selec-
tive fishing pattern, total and male biomass per recruit
decreased with fishing mortality and decreasing mean
population size. However, male and total biomass per
recruit did not reflect the increased effect of fishing on
populations with smaller mating aggregations. The
production of fertilized eggs per recruit decreased with
increased fishing pressure and decreased more sharply
for smaller mating aggregations. Only the number of
fertilized eggs per recruit could assess the predicted
effect of fishing on the protogynous population. Thus,
classic SPR measures were predicted to fail in the
presence of sperm limitation to assess the impact of
fishing on a protogynous stock.
Marine reserves and fishery management
In the situation considered in this study, the pattern
of fishing is more important to stock dynamics than
the presence of marine reserves. We assumed a size-
selectivity that allowed on average 50% of individuals
of sex-changing size to escape the fishing gear. Thus,
although the sex ratio does increase (become more
female) by 20-40%, all males are not lost from the
population (when Lfs.Lt. and r=l ). If fishing selectivity
occurs at a smaller size, then the effects on the popula-
tion are predicted to be much greater and the protogy-
nous stock would suddenly become more affected than
the dioecious population. For example, at L^=25 cm the
protogynous stock is predicted to crash whenever F^l.
This occurs not because of a reduction in the produc-
tion of eggs but rather because of a failure to fertilize
the eggs produced by surviving females. When males
of all size classes are fished, populations can become
male limited and fertilization rates drop drastically. A
decrease in the production of fertilized eggs can lead to
a decrease in female biomass, but it is the removal of
males rather than females that causes this decline.
When fishing effort is not redistributed after the
formation of a reserve, the impact of fishing on the
mean population size and SPR measures is predicted
to decrease (e.g. Fig. 7A). However, if fishing effort is
redistributed among unprotected areas, the benefit
of the reserves to the protogynous stock decreases
(Fig. 8A). Protecting some sites allows large males to
Alonzo and Mangel: The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish 9
escape fishing and thus increases the pro-
duction of fertilized eggs at the population
level. However, yield decreased proportion-
ally to the percentage of sites protected by
the reserve unless fishing effort is redis-
tributed among the remaining sites. We as-
sumed that fish do not move between sites
after the larval stage, and thus larger and
older individuals do not leave the reserve
and become exposed to fishing. Although this
assumption is clearly appropriate for some
species, it is important to realize that the dy-
namics and predictions would differ for more
closed populations or migratory species. For
the fishing pattern and biological scenario
examined in this study, marine reserves are
not predicted to increase biomass available
to the fishery (Figs. 7B and 8B).
Dynamics of dioecious versus protogynous
stocks
In the dioecious stock with a single ran-
domly mating aggregation, both male and
female biomass per recruit and fecundity
or fertility per recruit are predicted to
decrease as fishing mortality increases ( Fig.
6). Because both egg production and sperm
production decrease with increased fishing
pressure in the dioecious stock, the number
of eggs fertilized per recruit did not differ
much from the other SPR measures. Thus,
SSBR and eggs per recruit also indicated the
impact of fishing on the stock in dioecious
stocks with large mating aggregations. The
percent drop in population size and fertil-
ized egg production is predicted to be much
greater in dioecious species and occurred
more quickly than in the sex-changing
stock because of a reduction in overall
population fecundity even in the absence of
decreased fertilization rates. However, dioe-
cious stocks are predicted to exhibit larger
mean population size for the same fishing
mortality and to support a larger fishery
because of the additional egg production of
large fecund females. At very small mating
aggregations, sperm limitation is predicted
even in the dioecious stock and fertilized
eggs per recruit become a better indicator
of stock dynamics in the presence of fishing.
Dioecious stocks are also predicted to benefit
from marine no-take reserves through the
protection of large fecund females ( Fig. 7 ).
Discussion
In this study we developed a general frame-
work that examines the consequences to
0.95
0.9
0.85
Egg production
(per recruit)
Fertilized eggs
(per recruit)
Mean population
size
Figure 5
Mating aggregation size affects the response to fishing. Large (one large
mating aggregation ) and small ( 10 smaller mating aggregations I situations
are compared. Percent change in the presence of fishing (from F=0 to F=l>
in egg production per recruit, mean fertilized egg production per recruit, and
mean population size are given. Total population fecundity and mean body
size are lower for the smaller mating aggregations.
PROTOGYNOUS POPULATION
1 1
F=3
Eggs produced
F=0
r& S
0.9-
0.8-
Eggs fertilized _n
.a
St'
»■"
0.7-
a® x
o
Eggs produced
and fertilized
DIOECIOUS POPULATION
0.6-
0.5.
ft
ti
*
0.4
F=3
F=0
600 650 700 750 800 850 900 950
Mean population size
Figure 6
Spawning-per-recruit (SPR) measures in a protogynous (squares) and dioe-
cious (triangles) stock: Mean egg production per recruit (filled) and mean
fertilized eggs per recruit (open) are shown for a randomly mating popula-
tion with one large mating group. Error bars indicate the standard error of
the mean. For the dioecious population, the two SPR measures overlap.
10
Fishery Bulletin 102(1)
fisheries management of a behaviorally and evolution-
ary reasonable life-history and sex-change pattern. We
based our assumptions and parameter values on patterns
observed in natural populations that have presumably
evolved given the life history tradeoffs and expected repro-
ductive success associated with these behaviors. However,
we made various assumptions that affect the predicted
patterns such as a fixed sex-change pattern, male mating
success proportional to sperm production, and a very resil-
ient recruitment function. Despite these assumptions, a
number of general patterns emerge.
Life-history pattern is important but not sufficient
to predict stock dynamics
In general, we predicted that a protogynous stock with
fixed sex change will respond to the same fishing pressure
o
o ^
fl
Q.— '
°> S3,
-= cr>
X
<D
0) Q
0.75
0.5 ■
0.25
Protogynous
t- C\J
Dioecious
B
E
g
a
600,000-
500,000'
400,000-
300,000-
200,000-
100.000
Protogynous
Dioecious
Figure 7
The effect of marine reserves on protogynous and dioecious popula-
tions when fishing effort is decreased (case 1 1. 1 A) Percent change
in the presence of fishing CF=1) in the production of fertilized eggs
compared to in the absence of fishing. ( B) Annual biomass removed
by the fisheries varies with marine reserve and sex-change pat-
tern. Numbers shown are for 10 mating sites when F=l.
differently than an otherwise identical dioecious stock.
Understanding the life history of the population is clearly
important to our understanding of stock dynamics. How-
ever, it is not possible to classify protogynous stocks simply
as more or less sensitive to fishing. The differences between
dioecious and sex-changing fish are relatively complex, and
it is not the case that one life history is expected to be more
or less vulnerable to fishing. Although the sex change and
fishing pattern are important, they must be seen in the
context of the mating system, reproductive behavior, and
population dynamics of the species. If no male size classes
escape fishing, then the sex-changing population will be
much more sensitive to fishing and may crash even at low
fishing mortality. When some male size classes escape fish-
ing, an identical dioecious stock is predicted to experience
a greater decrease in mean population size than the pro-
togynous population. However, the protogynous species is
predicted to be much more sensitive to mating aggre-
gation size and sperm limitation. Protogynous stocks
are predicted to benefit from marine protected areas
at high levels of fishing mortality where sperm limi-
tation is common at fished mating sites. In contrast,
the dioecious stock is predicted to derive a greater
benefit of marine reserves even at low fishing mortal-
ity because of the protection of large fecund females
( Fig. 7 ). Although the sex-changing population is pre-
dicted to be less sensitive to fishing mortality overall,
it is clearly very important to understand the exact
details of the sex-change pattern and the size-selec-
tivity of fishing in relation to sex change. It will also
be important to understand the mating system and
patterns of fertilization success and sperm produc-
tion in males when managing a protogynous stock.
Given the sensitivity of the sex-changing stock to the
size-selective pattern of fishing, we recommend the
precautionary approach of keeping fishing mortality
sufficiently low so that some males of all size classes
always escape fishing (Fig. 4C). Clearly, protogynous
stocks cannot be managed as if they were dioecious.
Sperm limitation and mating aggregation size affect
stock dynamics
The removal of large males from the population can
cause sperm limitation, decreased fertilization rates,
and decreased population size even in a resilient spe-
cies with high sperm production. Sperm limitation
will increase as mating group size decreases. In the
present model, even small males produced relatively
large amounts of sperm. If males are removed, popu-
lations with lower sperm production are predicted to
be more sensitive to the removal of large fertile males.
Our assumption of fertilization rates determined by
total egg and sperm production per mating site will,
if anything, have underestimated the potential for
sperm limitation. Other mating systems and repro-
ductive behaviors could lead to greater sperm limita-
tion than predicted in our study For example, species
that have not evolved under sperm competition should
be more affected by the removal of large males than
Alonzo and Mangel: The effects of size-selective fisheries on the stock dynamics of and sperm limitation in sex-changing fish
species with sperm competition because of decreased
allocation to sperm production. Pair spawning among
individuals could also lead to decreased fertilization
rates. Reproductive behaviors often found in sex-
changing species, such as territoriality, female choice,
resource-defense polygyny, and mate monopolization,
all lead to skewed reproductive success for males and
could further decrease fertilization rates. Sperm limita-
tion is predicted to occur, and an understanding of such
factors as fertilization rate, sperm production, mating
skew, and mating group size will increase our ability to
understand and predict stock dynamics.
Traditional spawning-per-recruit measures can fail
in the presence of sperm limitation
Although problems exist with traditional spawning-
per-recruit measures in general (Parkes, 2000), they
are especially problematic for sex-changing stocks. In
the dioecious stock, the relationship between female
and total spawning stock biomass per recruit exhibits a
roughly linear relationship with population size. In the
sex-changing stock, female fecundity does not reflect
the changes in mean population size. Although total or
male spawning stock biomass per recruit did decrease
with decreased population size, the fit between these
measures will depend greatly on the size-dependent
sperm production of males, mating aggregation size,
and other factors determining the potential for sperm
limitation. Male or total spawning stock biomass
per recruit alone cannot predict sperm limitation
and thus will fail to predict the potential population
crashes that may result. We conclude that any mea-
sure of spawning per recruit in a sex-changing species
that does not consider sperm limitation and reduced
fertilization rates has the potential to underestimate
the impact of fishing on the population. The number
of eggs produced or female spawning stock biomass
can remain relatively unchanged in the face of high
fishing mortality even as the population is predicted
to decline. However, the failure of classic spawning-
per-recruit measures in the presence of declines due
to sperm limitation or decreased fertilization rate will
not be limited to protogynous stocks. Although sperm
production patterns and fertilization rates are not known
for many commercially important species, this information
can be collected to develop a general sense of how sperm
production depends on individual size. We also have a
general sense of the factors that are expected to affect fer-
tilization rates (Birkhead and Moller, 1998) and these can
be easily studied in any species where spawning grounds
are accessible to researchers. It is clear that new manage-
ment measures must be developed for sex-changing species
that consider the potential for sperm limitation because
biomass alone may miss the potential for rapid population
crashes. One purpose of theory is to tell us what we need
to know more about and to stimulate further research. Our
results clearly indicate that we need to know more about
sperm production and fertilization rates when managing
protogynous stocks.
"P V
<= s
- oi
-^ <D
CD CD
0.75
0.5
& 0.25
i- c\j
Protogynous
Dioecious
B
600,000
500.000
400.000
300.000
200,000
100,000
Protogynous
Dioecious
Figure 8
The effect of marine reserves on protogynous and dioecious
populations when fishing effort is redistributed (case 2). iAi
Percent change in the presence of fishing iF=ll in the produc-
tion of fertilized eggs compared to percent change in the absence
of fishing. (Bl Annual biomass removed by the fisheries varies
with marine reserve and sex-change pattern. Numbers shown
are for 10 mating sites when F=l.
Marine reserves and size-selective fishing can be used
to manage protogynous stocks
Marine reserves clearly have the potential to decrease the
impact of fishing on populations. Large highly fecund or
fertile individuals may be protected from size-selective
fisheries. However, the benefits of a marine reserve will
be significantly decreased if fishing effort is simply redis-
tributed to unprotected sites (Figs. 7 and 8; Guenette and
Pitcher, 1999; Apostolaki et al„ 2002). It is usually rec-
ognized that the larval export and import dynamics will
be crucial to whether reserves increase mean population
size. We predict that the degree to which stocks respond
to no-take reserves will also depend on their life-history
pattern, mating system, and size-dependent fecundity
and fertility. The protection of large and fecund (or fertile)
12
Fishery Bulletin 102(1)
fish will certainly increase reproduction and decrease the
impact of fishing on the population. However, the benefit of
marine reserves will be much greater in populations where
larger or older individuals play a key role in reproduction.
Given the predicted extreme sensitivity of the protogynous
population to the pattern of size-selective fishing, marine
protected areas could represent a precautionary manage-
ment strategy to ensure that some males are not subject
to fishing mortality.
A comprehensive approach to stock dynamics
Managing fishing on stocks of sex-changing fish will require
considering the sex-change pattern. However, one must also
consider the sex change pattern within the context of the
mating system. Although the pattern of sex determination
does affect the stock dynamics, simple statements regard-
ing whether dioecious or sex-changing populations are
more sensitive to fishing are not possible. The differences
among dioecious and sex-changing stocks are complex, and
the management of these stocks will depend as much on
their mating system, the type of fishing strategies used
to capture them, and mating aggregation size as on the
sex determination pattern. Classic SPR measures cannot
measure sperm limitation and reduced fertilization rates,
and thus will not always measure or predict the impact of
fishing mortality on the population. Rather than relying
on measures of spawning stock biomass per recruit alone,
management groups should also monitor protogynous sex-
changing stocks for a reduction in fertilization rates
Acknowledgments
We thank Phil Levin, Alec McCall, Steve Ralston, and Bob
Warner for their comments on an earlier version of this
manuscript. This research was supported by National Sci-
ence Foundation grant IBN-01 10506 to Suzanne Alonzo
and the Center for Stock Assessment Research (CSTAR).
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14
Abstract— We present a growth analy-
sis model that combines large amounts
of environmental data with limited
amounts of biological data and apply it
to Corbicula japonica. The model uses
the maximum-likelihood method with
the Akaike information criterion, which
provides an objective criterion for model
selection. An adequate distribution for
describing a single cohort is selected
from available probability density func-
tions, which are expressed by location
and scale parameters. Daily relative
increase rates of the location parameter
are expressed by a multivariate logistic
function with environmental factors
for each day and categorical variables
indicating animal ages as independent
variables. Daily relative increase rates
of the scale parameter are expressed by
an equation describing the relationship
with the daily relative increase rate of
the location parameter. Corbicula
japonica grows to a modal shell length
of 0.7 mm during the first year in Lake
Abashiri. Compared with the attain-
able maximum size of about 30 mm,
the growth of juveniles is extremely
slow because their growth is less sus-
ceptible to environmental factors until
the second winter. The extremely slow
growth in Lake Abashiri could be a
geographical genetic variation within
C. japon ica .
An environmentally based growth model
that uses finite difference calculus
with maximum likelihood method:
its application to the brackish water bivalve
Corbicula japonica in Lake Abashiri, Japan
Katsuhisa Baba
Hokkaido Hakodate Fisheries Experiment Station
1-2-66, Yunokawa, Hakodate
Hokkaido 042-0932, Japan
E-mail address babak@fjshexp pref.hokkaido.jp
Toshifumi Kawajiri
Nishiabashin Fisheries Cooperative Association
1-7-1, Oomagan, Abashiri
Hokkaido 093-0045, Japan
Yasuhiro Kuwahara
Hokkaido Abashiri Fisheries Experiment Station
31, Masuura, Abashiri
Hokkaido 099-3119, Japan.
Shigeru Nakao
Graduate School of Fisheries Sciences
Hokaido University
3-1-1, Minato, Hakodate
Hokkaido 041-8611, Japan
Manuscript approved for publication
14 August 2003 by Scientific Editor
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:14-24 (2004).
Extreme fluctuations, both short-term
and seasonal, in food availability (e.g.
phytoplankton density ) make it difficult
to determine relationships between
the growth of filter-feeding bivalves
and environmental factors (Bayne,
19931. However, it is becoming easier
to acquire large amounts of environ-
mental data through the use of data
loggers, submersible fluorometers, or
remote-sensing satellites, which enable
environmental monitoring at daily or
subdaily intervals. The development
of these devices could solve difficulties
in data collection. However, analytical
methods that combine large amounts
of environmental data with limited
amounts of biological data (e.g. shell
length) are not yet well developed.
We present an environmentally based
growth model that combines such
unbalanced data sets. This model is
useful in elucidating relationships
between environmental factors and
growth of filter feeders from field data.
Complex box models, such as eco-
physiological models, can derive the
relationships between environmental
factors and the growth of filter-feeding
bivalves (Campbell and Newell, 1998;
Grant and Bacher, 1998; Scholten and
Smaal, 1998). These models are useful
for estimating impacts of cultivated
species on an ecosystem or the carrying
capacity of a species (or both) (Dame,
1993; Heral, 1993; Grant et al„ 1993).
They are suitable for animals that have
been widely studied, such as Mytilus
edulis, because they are derived by
integrating a huge amount of ecophysi-
ological knowledge acquired mainly
from laboratory experiments. However,
extrapolation of such knowledge to
natural conditions is still controver-
sial (Jorgensen, 1996; Bayne, 1998).
Our model treats complicated eco-
Baba et al.: An environmentally based growth model for |uvenile Corbicula japonica
15
physiological processes as a black box; we constructed the
model directly from fluctuations in environmental factors
and growth rates. Our approach is reasonable for animals
for which ecophysiological knowledge is limited, especially
when the main purpose of investigation is to derive the
relationships between environment and growth.
We applied the model to a single cohort of Corbicula
japonica juveniles spawned in August 1997. We did not
consider any bias caused by adjacent cohorts because C.
japonica failed to spawn in 1995, 1996, and 1998 in Lake
Abashiri owing to low water temperatures during the
spawning season (Baba et al., 1999). Such investigations
provide important basic information, such as the shape of
the distribution of a single cohort, and the relationship
between growth rate and expansion rate of size variation
in a single cohort.
Corbicula spp. are harvested commercially in Japan. The
annual catch ranged from 19,000 to 27,000 metric tons in
1996 to 2000 ( Ministry of Agriculture, Forestry and Fisher-
ies1), of which C. japonica was the main species. Corbicula
japonica is distributed in brackish lakes and tidal flats of
rivers from the south of Japan to the south of Sakhalin
(Kafanov, 1991), is a dominant macrozoobenthos in these
lakes, and has important roles in bioturbation and energy
flow (Nakamura et al., 1988; Yamamuro and Koike, 1993).
Juvenile C. japonica growth is fast in southern habitats.
Their spats collected in Lake Shinji, which lies in the south-
ern part of its range, grow to a mean shell length of around
6.7 mm in natural conditions by the first winter ( Yamane et
al.2). In northern habitats, growth is also believed to be fast;
Utoh ( 1981 ) reported that mean shell length at the first an-
nual mark was around 5.7 mm in Lake Abashiri. In Utoh's
study differences between the shell lengths at the first an-
nual marks and the shell lengths of individuals aged to be
one year were also reported. The purposes of the present
study are to elucidate juvenile growth and its relationship
to environmental factors in Lake Abashiri.
Materials and methods
Overview of the model
Our model expresses relative growth rate for C. japonica by
a sigmoid function with environmental factors and animal
ages as independent variables. Modeling processes in gen-
eral follow five steps: 1) Shell lengths of a single cohort are
summarized by an adequate probability density function,
which is expressed by a location parameter and a scale
parameter; 2 ) Daily relative increase rate of the location
1 Ministry of Agriculture, Forestry and Fisheries. 1996-
2002. Statistics on fisheries and water culture production.
Association of Agriculture and Forestry. 1-2-1 Kasumigaseki,
Chiyoda, Tokyo 100-0013. Japan.
2 Yamane, K., M. Nakamura, T. Kiyokawa, H. Fukui, and E.
Shigemoto. 1999. Experiment on the artificial spat collec-
tion. Bull. Shimane Pref. Fish. Exp. Stn., p. 232-234. Unpubl.
rep. Shimane Prefectural Fisheries Experimental Station,
25-1 Setogashima, Hamada, Shimane 697-0051, Japan. |In
Japanese.]
parameter (dRIRL) is approximated by a sigmoid function
with environmental factors and animal ages as indepen-
dent variables; 3) Daily relative increase rate of the scale
parameter is approximated by a simple function with the
dRIRL as an independent variable; 4) The model is opti-
mized by a maximum likelihood method; and 5) The best
model is selected by Akaike information criterion (AIC).
The AIC is an information-theoretic criterion extended
from Fisher's likelihood theory and is useful for simulta-
neous comparison of models (Akaike, 1973; Burnham and
Anderson, 1998).
Study site and sampling method
To collect juveniles of C japonica spawned in August 1997,
sediments were sampled with a 0.05-m2 Smith-Mclntyre
grab once or twice a month from September 1997 to July
1999 at a depth of 3.5-4.0 m in Lake Abashiri (Fig. 1). The
habitat of C. japonica is restricted to areas shallower than
6-m depth because the deeper area, the lower stratum of
the lake, is covered by anoxic polyhaline water. We assumed
that the selectivity of the sampling gear on C. japonica
juveniles was negligible because the gear grabs the juve-
niles with the sediment. Because the magnitude of spawn-
ing in 1997 was relatively small (Baba et al., 1999), we
selected a sampling site where we found abundant settled
juveniles in our preliminary investigations. Samples could
not be obtained during winter because of ice cover. Sedi-
ments were washed with tap water on 2- mm and 0.125-
mm mesh sieves from September 1997 to October 1998,
and on 4.75-mm and 0.125-mm mesh sieves from April
to July 1999. To separate the juveniles from the retained
sediments, we treated the sediments with zinc chloride
solution as described by Sellmer (1956). Then we sorted
the juveniles under a binocular microscope. Identification
of the cohort spawned in 1997 was quite easy because C.
japonica failed to spawn in 1995, 1996, and 1998 owing to
low water temperatures during the spawning season ( Baba
et al., 1999). We considered all the individuals that passed
through the larger-mesh sieves and that were retained on
the smaller-mesh sieve as the 1997 cohort. Shell lengths
were measured under a profile projector (V-12, Nikon Ltd.,
Chiyoda, Tokyo) at 50x magnification with a digital caliper
(Digimatic caliper, Mitsutoyo Ltd., Kawasaki, Kanagawa),
which has a 0.02-mm precision.
Environmental factors
Values for water temperature (°C), water fluorescence
(fluorescence equivalent to uranin density, ug/L). salinity
(psu, practical salinity unit), and turbidity (equivalent to
kaolin density, ppm) were obtained for 0.1-m intervals
from unpublished data at the Abashiri Local Office of
the Hokkaido Development Bureau.3 The variables were
measured by a submersible fluorometer (Memory Chloro-
tec, ACL-1180-OK, Alec Electronics Ltd., Kobe, Hyogo) at
four sites in Lake Abashiri at intervals of about one week
( Fig. 1 ). The average values of each variable between the
depths of 1 m and 6 m were used for later analyses. Values
between the measured dates were interpolated linearly
16
Fishery Bulletin 102(1)
E14CT E142
N44
N42°
Lake Abashiri
Figure 1
Location of sampling site for Corbicula japonica juveniles in Lake Abashiri. Japan (#i. Envi-
ronmental factors — water temperature, water fluorescence, salinity, and turbidity — were
measured at four sites, designated by ©■
for subsequent analysis with the environmentally based
growth model. The water fluorescence reflects the density
of phytoplankton.
Model structure
Modeling the distribution of a single sample Normal
distribution is usually used to describe a single cohort in
fishes and aquatic invertebrates (e.g. Pauly, 1987; Founier
and Sibert, 1990; Yamakawa and Matsumiya, 1997). How-
ever, an adequate function to describe a single cohort of
each animal should be selected to avoid biases caused
by any inadequacies of the function. Probability density
functions of many distributions are applicable for that
purpose, and the appropriate can be selected among easily
calculable functions to ensure convergence of the model.
Characteristics of many distributions are well described
by Evans et al. (1993). We used two distributions: normal
distribution and largest extreme value distribution. The
normal distribution is symmetric. The largest extreme
value distribution is asymmetric with a longer tail toward
the larger side. These are expressed by a location param-
eter and a scale parameter.
To use all the information inherent in data, parameters
of the distribution functions are estimated from raw data
(e.g. lengths I, not from summarized data such as length fre-
quency. This estimation method is described by Sakamoto
et al. ( 1983 1. The most adequate distribution is selected by
AIC. Log-likelihood functions of the distributions take the
following forms:
Normal distribution
1
logeLm)rmal(a,b) = £log(. T=!=exp[-(/,-a)2/2&2] , (1)
(2)
3 Abashiri Local Office of the Hokkaido Development Bureau.
2-6-1 Shinmachi, Abashiri, Hokkaido 093-0046, Japan.
Largest extreme value distribution
log,. L,argt-Ja,b) = £log,.{< 1/ 6)exp[-(/, -a) lb]
x expj- exp[-( /, - a ) / b]\\ ,
where n = number of data;
/, = length of (th individual;
a = location parameter; and
b = scale parameter.
The location parameter is a mean in the normal distri-
bution. The location parameter is a mode in the largest
extreme distributions. The scale parameter is a standard
deviation in the normal distribution.
The AIC is calculated by
AIC = -2 log tma.ximum likelihood) + 2m. (3)
where m = number of parameters to be estimated.
The model with the minimum AIC is the best model. A
difference of more than 1 or 2 is regarded as significant in
terms of AIC (Sakamoto et al., 1983).
Modeling the change in the location Values of the location
and scale parameters usually increase with the growth of
an animal. The relative increase rate in a certain time step
is defined as
Baba et al.: An environmentally based growth model for juvenile Corbicula /aponica
17
r,=(P,
Pi-i)IPi=v
(4)
where rt = relative increase rate of a parameter in the /th
time step; and
Pl = parameter value after the /th time step.
Relationships between the parameter value and the rela-
tive increase rate of the parameter can be expressed by
P, = P(,( !+/-,)
P2=Pia+r2) = P0(l+r1Kl + r2)
P3=P2(l+r3) = P0(l + r1)(l + 7-2)(l + r!)
(5)
P.=P0fl(1+r')"
where P(l = parameter value at the first sampling;
P, = parameter value after the /'th time step; and
ri = relative increase rate of the parameter in the
/th time step.
We used one day as the time step in this study In our envi-
ronmentally based growth model, we assumed that the
daily relative increase rate of location parameter (dRIRL)
depends on the age of the animal and on environmental
factors for each day. Sigmoid functions that take values
between 0 and a certain maximum are empirically appro-
priate for expressing the relationships between the dRIRL
and independent variables, especially for measures such as
shell length that do not show negative growth. Therefore,
using categorical variables indicating animal ages and envi-
ronmental factors for each day as independent variables, we
express the dRIRL by the multivariate logistic function
related because the dRIRS is larger when the dRIRL is
larger. Therefore, we estimated the dRIRS from an equa-
tion expressing the relationship to the dRIRL. We tested
two functions,
Yl + Y2Si (7l+/2S, >0)
0 (yi + 72s, <0)
and
t, =
0
s, - 7i > 0)
(s, -/, <0)
(7)
(8)
where ti = dRIRS on the /th day from the first sampling;
Yv Yz = coefficients of the equations; and
Sj = dRIRL on the /th day from the first sampling.
Model estimation
Likelihood function The location and scale parameters
at the first sampling (o0 and fe0), the coefficients of Equa-
tion 6 (smax, a, and pk), and the coefficients of Equations 7
and 8 (y-j and y2) are estimated as values that maximize
total log-likelihood. The total log-likelihood is evaluated
by the adequate probability density function selected in
the first step. The log-likelihood functions take the follow-
ing forms:
Normal distribution
log, L„ormal (aQ,b„, smax , a j , pk , yv y2)
= X2>g* -Arexp[-(Z<7i-a,)/242]
2nb
(9)
Largest extreme value distribution
s, =smax/ 1 + exp
2>a+£ab*
(61
where si = dRIRL on the /th day from the first sampling;
smax = potential maximum dRIRL of the animal;
a., Pk = coefficients of each independent variable;
A = categorical variable ( a dummy variable indi-
cating animal ages ) that takes the value 1
orO;
Ekl = the kt\\ environmental factor on the /th day
from the first sampling;
nA = number of age categories; and
nE = number of environmental factors.
The categorical variable takes the value of 1 when the
animal is the category, otherwise it takes 0. The multivari-
ate logistic function with smax = 1 is used for logistic regres-
sions (Sokal and Rohlf, 1995). A method of giving a value to
the categorical variable is described by Zar ( 1999).
Modeling the change in scale The daily relative increase
rate of scale parameter (dRIRS) and dRIRL must be cor-
loge-L,argcs/o0,fe0,smax,a,,^„71,)'2)
N nq
=XZ1°g«{(1/Vexp[-^-«,>/4]
xexp{-exp[-(Z9i-<59)/feJU,
(10)
where a0, 60 = values of the location and scale param-
eters, respectively, at the first sampling;
smax> aj> Pk = coefficients of Equation 6;
Yvy2 - coefficients of Equations 7 and 8;
N = number of samplings;
nq = number of data at the qth sampling;
aq = location parameter at the qth sampling
estimated by Equation 5 (r,=s, );
bq = scale parameter at the qth sampling esti-
mated by Equation 5 (r~^); and
/ = length of the /th individual at the <?th
sampling.
AIC is used to select significant environmental factors,
the age categorization, and the equation to express the
18
Fishery Bulletin 102(1)
relationship between dRIRL and dRIRS, i.e. Equation 7
or 8.
Confidence intervals To evaluate uncertainties of coef-
ficient values and model selection, we estimated the 95r/f
confidence intervals of all coefficients — i.e. a0, b0, smax, a-,
jik, yj, and y2 — based on profile likelihood. For example, the
95% confidence interval of a,, — a,
-was estimated as an
interval that suffices in the following equation:
2\ max log,. L(a0,b0, smax , a , , ft , y1 , y, )
max log,. U d0 , 4, smBX, aJt ft, yu y2
K=a096)}<^(0.05),
(11)
where .v^lO.OS) = value of a chi-squared distribution at an
upper probability of 0.05 with one degree
of freedom, i.e. 3.84.
The characteristics of the interval are explained by
Burnham and Anderson ( 1998).
We used Microsoft Excel (Microsoft Corp., Redmond, WA)
as the analysis platform, and Solver (Microsoft Corp., Red-
mond, WA) as the nonlinear optimization tool.
Model selection
We used three procedures for model selection to achieve
the best model. First, we constructed an a priori set of base
models based on biological variables; then we selected the
best base model. Fixation of the base model drastically
decreases possible candidate models to be tested. To test all
possible combinations of independent variables and model
forms is quite impractical. Second, we excluded insignificant
factors from the best base model. Third, we checked the sig-
nificance of environmental factors that were not included in
the base models. If one was significant, we included it in the
best base model. All of these procedures were performed by
AIC. The construction of the a priori set of candidate models
is partially subjective, but it is an important part of the
model construction (Burnham and Anderson, 1998).
Seasonal growth in bivalves is influenced by water
temperature and food supply (Bayne and Newell, 1983).
The growth rate of Corbicula fluminea changes with age
(McMahon, 1983). Therefore, we constructed base models
combining water temperature, water fluorescence, and
categorical variables indicating age for the independent
variables of Equation 6. We tested two types of categoriza-
tion of age. The first segregates ages based on real age, i.e.
two categories: 0+ or 1+. The second segregates ages in rela-
tion to winter, i.e. three categories: before the first winter,
from the first to the second winter, and after the second
winter. For the real-age categorization, age was segregated
based on 1 September, because the spawning season was
in August 1997. For the winter-base age categorization, we
segregated ages based on 1 January. No biases should have
occurred because of the segregation date of the winter base
categorization and because the growth of C.japonica is neg-
ligible during winter. Four base models were constructed
0.2 "
g
a
0.1 --
0.0 -i
Largest extreme
value distribution
Normal distribution
L.
-+-
0
1 2
Shell length (mm)
Figure 2
Two distributions fitted by the maximum-
likelihood method to the shell lengths of Cor-
bicula japonica juveniles spawned in 1997 and
sampled on 22 April 1999. Raw data are shown
by +. The shell length composition is shown by
the histogram.
combining the two types of age categorization and two types
of equations expressing the relationship between the dRIRL
and the dRIRS, i.e. Equations 7 or 8. We selected the best
base model by AIC.
To check the significance of each environmental factor
and age categorization, we removed the independent vari-
ables one by one from the best base model and re-optimized
the model. When the model was significantly improved by
the removal in terms of AIC, the effect of the variable was
insignificant on the model; therefore we excluded it.
To check the significance of salinity and turbidity, which
were not included in the base models, we included them
one at a time into the best base model and re-optimized the
model. When the model was improved by the inclusion, the
effect of the variable was significant on the model; therefore
we included it.
Results
Modeling the distribution of a single sample
The largest extreme value distribution was the best in
terms of AIC except for data sampled on 13 May 1998
(results are not shown). The exception is due probably
to the small sample size (rc=38) on that date. The largest
extreme value distribution was therefore used to evaluate
likelihood in later analyses: we selected Equation 10 from
Equations 9 and 10. The result of fitting the two distri-
butions to the shell lengths sampled on 22 April 1999 is
shown in Figure 2 as a representative example. The largest
extreme value distribution is apparently better than the
normal distribution for describing the single cohort of C.
japonica spawned in 1997.
Baba et al.: An environmentally based growth model for |uvenile Corbicu/a /aponica
19
Table 1
Values of location and scale parameters at the first sampling, coefficients, log-likelihood, and AIC of models constructed based on
the largest extreme value distribution. The best AIC among four base models ( models 1-4 ) is enclosed by a single line. The best AIC
of all models is enclosed by a double line. dRIRL = daily relative increase rate of location parameter, dRIRS = daily relative increase
rate of scale parameter. Temp. = water temperature, WF = water fluorescence, Sal. = salinity, Turb. = turbidity, CI = before the first
winter, C2 = from the first to the second winter, C3 = after the second winter.
Model
no.
Parameters
at 1st
sampling
Max.
dRIRL
Age categorization
Environmen
tal factors
Expressing relationship
between dRIRS
and dRIRL
Log-L
Al A2
a j a2
A3
«3
Temp.
ft
WF
ft
Sal.
ft
Turb
ft
AIC
ao
^0
smax
)'i
y2 Eq. no
1
0.299
0.040
0.012
0+ 1 +
-62.6 -23.7
0.16
2.61
0.0000
1.686
7
850.4
-1682.9
2
3
4
0.297
0.299
0.299
0.040
0.042
0.042
0.011
0.011
0.011
-56.1 -22.1
0.20
0.61
0.65
2.44
0.41
0.42
0.0001
-0.0076
0.0034
0.887
2.902
0.760
8
7
8
852.3
950.4
952.2
-1686.5
ci C2
C3
-16.8 -16.7
-17.5 -17.6
-9.1
-9.6
-1880.9
-1884.4
4.1
4.2
0.299
0.297
0.042
0.038
0.011
0.005
-18.3' -10.0
127.9 -26.8'
0.68
0.34
0.44
4.15
0.0034
0.0000
0.760
0.895
8
8
952.2
735.0
-1886.3
-1451.9
4.3
0.295
0.037
0.008
-47.3 -16.3
-8.8
1.47
0.0033
0.766
8
848.9
-1679.9
4.4
0.299
0.041
0.013
-4.9 -8.9
-4.9
0.40
0.0020
0.806
8
909.6
-1801.1
4.5
0.299
0.042
0.011
-16.7'
-9.1
0.62
0.42
-0.25
0.0033
0.762
8
952.4
-1884.8
4.6
0.299
0.042
0.011
-18.5'
-10.2
0.68
0.44
0.007
0.0034
0.760
8
952.2
-1884.4
1 One common coefficient was used for the two categorical
/ariables.
Model selection and application
Model 4 was the best in terms of AIC among four base
models (Table 1, models 1-4); ages were categorized in
relation to winter; and the relationship between dRIRL
and dRIRS was expressed by Equation 8.
Four models were made by removing each independent
variable from model 4 (Table 1, models 4.1 to 4.4). The effect
of one age categorization — segregation of ages between the
first and second winters — was insignificant on the model,
because the model was significantly improved by its re-
moval in terms of AIC. The effects of the other independent
variables were significant on the model, because the model
was significantly worse by their removal in terms of AIC.
The effects of salinity and turbidity were insignificant on
the model, because adding each variable made the model
significantly worse in terms of AIC (Table 1, models 4.5 and
4.6). Consequently, model 4. 1 was the best model to describe
the relationships among environmental factors, ages, and
growth of C. japonica juveniles spawned in 1997.
The coefficient value for age categorization of before the
second winter (-18.3) is much smaller than that of after the
second winter (-10.0) (Table 1). This difference suggests
that the growth response of C. japonica juveniles is much
less susceptible to environmental factors before the second
winter than after.
Peaks of the dRIRL corresponded with peaks of water
fluorescence, when the water temperature was warmer
than about 10°C, especially before the second winter (Fig. 3,
B and C). Therefore, food supply is the most influential fac-
tor when the water temperature is above about 10°C. The
slow growth or no growth during winter is due to the low
water temperatures. The dRIRL reached a plateau after 30
May 1999. This was due to two factors: water fluorescence
was relatively intense after 30 May 1999 (Fig. 3B); and the
growth response of C. japonica to the environmental factors
was more susceptible after the second winter than before.
The confidence limits of all the coefficients seem to be
reasonably estimated by the profile likelihood method
(Table 2). These results also guarantee the convergence of
the model because the model was frequently optimized to
seek each confidence limit with different starting values.
We repeated the optimization at least 20 times to seek each
confidence limit. On other models, we also confirmed the
convergences as well.
The largest extreme value distributions estimated by
model 4.1 fitted the shell lengths of C. japonica juveniles
very well (Fig. 4).
Discussion
Model formulation and application
Largest extreme value distribution is apparently better
than normal distribution to describe the single cohort of
C. japonica that spawned in 1997. This distribution has a
mode and a longer tail toward the larger side. If the shell
20
Fishery Bulletin 102(1)
± 0.02
£ 0.01
rr
D
5
4
3 "
2 "
1 "
0
fc-
^ >
fiO ;
M
4^%,
-^— Turbidity
-•— Salinity
-■
40 -
1/ \
20- l"'"l I
■ 1 1
1
~wj
Mode (estimated by model 4.1)
90% confidence interval (estimated by
model 4.1)
° Mode (sample)
Date
Figure 3
Environmental fluctuations and prediction of the growth oiCorbiculajapon-
ica juveniles spawned in 1997 in Lake Abashiri by the best model (Model 4.1
in Tablel). (Al Insignificant environmental factors (factors excluded in the
model selection), turbidity (equivalent to kaolin density, ppmi and salinity
(psu, practical salinity unitl. (Bl Significant environmental factors (factors
included in the model selection I, temperature (°C) and water fluorescence
(equivalent to uranin density, /'g/L>. (Cl Daily relative increase rate of loca-
tion parameter (dRIRLl and daily relative increase rate of scale parameter
(dRIRS) estimated by the model. (Di Growth of Corbicula japonica; verti-
cal bars represent 90% confidence intervals for the shell lengths of the
samples.
length distribution becomes asymmetric during growth,
skcwness of the distribution would increase according
to growth. However, there is no correlation between the
skewness and the means of the shell lengths. Therefore, we
thought that the shell length distribution of the cohort was
already asymmetric just after settlement. Such a distribu-
tion might be influenced by fluctuations in larval settle-
ment during the spawning season; and larval settlement
would be influenced by fluctuations in larval supply from
the water column. During the spawning season of 1997.
the average planktonic larval density gradually increased
from 26 ind/m3 on 25 July to a maximum of 603 ind/m3 on
Baba et al.: An environmentally based growth model for |uvenile Corbicula japonica
21
Table 2
95% confidence limits of location and scale parameters at the first sampling and coefficients of the best model constructed based
on the largest extreme value distribution (models 4.1 in Table 1) estimated by profile likelihood method. dRIRL = daily relative
increase rate of location parameter. dRIRS = daily relative increase rate of scale parameter. Temp. = water temperature, WF =
water fluorescence, Sal. = salinity, Turb. = turbidity.
Parameters
at 1st
sampling
Max.
dRIRL
Age categorization
Environmental factors
Expressing
relationship
between dRIRS
and dRIRL
A,
a,
a.
Temp.
ft
WF
ft
Sal.
ft
Turb.
ft
Lower 95 %
Upper 95 %
0.294
0.304
0.039
0.045
0.010 -26.6'
0.013 -11.5'
-14.6
-6.4
0.41
1.00
0.27
0.64
0.0027
0.0039
0.734
0.793
1 One common coefficient for the two categorical variables.
13 August. Then it sharply decreased to 3 ind/m3 on 19
August (Baba et al., 1999). Such a pattern of larval-density
fluctuation might have caused the asymmetric distribution
of shell lengths of the settled juveniles. Another possible
factor that influenced the shapes of the shell length distri-
butions and the relationship between dRIRL and dRIRS
is size-dependent mortality, e.g. predations and fisheries.
Size-dependent mortality has been reported in several
marine bivalves (e.g. Nakaoka, 1996). Potential predators
of C.japonica are fishes, such as Japanese dace (Tribolo-
don hakonensis) (also known as big-scaled Pacific redfin,
FAO), Pacific redfin (Tribolodon brandtii), common carp
(Cyprinus carpio), and the So-iny mullet (Liza haemato-
cheila ) (Kawasaki4). In our study, the size-dependent mor-
tality was negligible because the range of the shell lengths
observed in this study was very narrow.
The shape of the distribution to describe a single cohort
should be determined from the data. In contrast, single
cohorts are usually separated from multicohort data by as-
suming a normal distribution of lengths in a single cohort
(e.g. Fournier and Sibert, 1990). Therefore, it is possible
that multicohort analysis done without selection of an
adequate distribution to describe a single cohort causes
substantial bias in estimations of various stock features
of animal populations, such as age composition, growth,
mortality, and recruitment. In our preliminary analyses,
we also tested smallest extreme value distribution, inverse
Gaussian distribution, and lognormal distribution. The in-
verse Gaussian distribution was the best for two samples;
the lognormal distribution, was the best for two samples;
the largest extreme value distribution was the best for ten
samples. Therefore, it is reasonable to select the largest ex-
treme value distribution. We selected a single distribution
for our analyses, otherwise a discontinuous point would
have appeared in the growth curve.
Relatively large confidence intervals were obtained in
the coefficients of the linear component of Equation 6, i.e.
a , and /3;, (Table 2). The relatively large confidence inter-
vals may indicate that the number of estimated coefficients
is somewhat larger than the number of samplings. There-
fore, to estimate these coefficients more precisely, we may
need to investigate more cohorts spawned in other years
in future investigations.
Growth of C. japonica
We identified extremely slow growth in C. japonica juve-
niles, which grew to a modal shell length of 0.7 mm during
the first year in Lake Abashiri, which lies at 43.7°N. Spats
of C. japonica collected from 1992 to 1997 in Lake Shinji,
which lies at 35.5°N, grew to a mean shell length of 6.7
mm in natural conditions by the first winter (Yamane et
al.2). Using environmental factors measured in Lake Shinji
from 1990 to 1998 at monthly intervals (Seike5), we simu-
lated the growth of C. japonica with model 4.1. Corbicula
japonica grew to a mean shell length of 1.4 mm (standard
error, 0.37 ) by the first winter in the simulations. Therefore,
the large difference in juvenile growth between the two
habitats cannot be explained by environmental differences
because the results of the simulation were apparently an
underestimate. We think that the extremely slow growth
of the juveniles (prolonged phase of meiobenthic develop-
ment ) in Lake Abashiri is probably a geographical varia-
tion, which is genetically determined, within C. japonica.
However, there remains a possibility that the juvenile
growth differences depend on other environmental factors
not measured in this study. Therefore, the geographical
4 Kawasaki, K. 1997. Lagoon structure and fish produc-
tion in Ogawara-ko Lagoon. /;; Final reports on fisheries in
Ogawara-ko Lagoon (Tohoku Construction Corporation ed.),
p. 4-33. Unpubl. rep. Construction Office for Takasegawa
General Development of Tohoku Regional Construction Bureau,
3 Ishido, Hachinohe, Aomori 039-1165, Japan.
6 Seike, Y. 1990-98. Gobiusu: monthly report of water quality
in Lake Shinji and Lake Nakaumi. Unpubl. rep. Faculty of
Science and Engineering. Shimane University, 1060 Nishi-
kawatsu, Matsue, Shimane 690-0S23, Japan.
22
Fishery Bulletin 102(1)
10 Sep 1997; mode: 0.30mm,
scale: 0.04, n=341
13 May 1998; mode: 0.41mm,
scale: 0.06, n=38
11 Jun 1998; mode: 0.51 mm,
scale: 0.12, n=292
10 Jul 1998; mode: 0.57mm.
scale: 0.10, n=610
13 Aug 1998; mode: 0.64mm,
scale: 0.12. n=456
1 1 Sep 1998; mode: 0.70mm.
scale: 0.17, n=202
14 Oct 1998; mode: 0.76mm.
scale: 0.17. n=162
0.0
22 Apr 1999; mode: 0.74mm.
scale: 0.15, n=265
+ +
13 May 1999; mode: 0.81mm,
scale: 0.20. n=241
0.2 t
t
H
0.1
00
28 Jul 1999; mode: 2.14mm,
scale: 1.06, n=63
^#T>fffi^^
3456 0123456
Shell length (mm)
Figure 4
Shell-length compositions of a single cohort of Corbicula japonica spawned in 1997. The raw data
(shell lengths) are shown by +. The largest extreme value distribution estimated by the best model
( model 4. 1 in Table 1 1 is shown by a solid line. The largest extreme value distribution independently
fitted by the maximum likelihood method is shown by a dashed line. The sampling date and values
of location parameter I mode) and scale parameter independently fitted by the maximum likelihood
method are shown in each panel.
variation should be validated by reciprocal transplanta-
tions or laboratory experiments (or both) in future inves-
tigations. Prolonged phases of meiobenthic development
have been reported in some marine bivalves (Nakaoka,
1992; Harvey and Gage, 1995). However, a prolonged phase
of meiobenthic development as a geographical variation is
rarely reported.
In many species of bivalve, populations from higher lati-
tudes have a slower initial growth rate; but longevity and ul-
timate size in these populations are frequently greater than
at lower latitudes (Newell, 1964; Seed, 1980). The extremely
slow growth of C. japonica juveniles in Lake Abashiri may be
an extreme example of this phenomenon. In Lake Abashiri,
C. japonica failed to spawn in ten out of 21 years for which
Baba et al
An environmentally based growth model for juvenile Corbicu/a japonica
23
data were available because of low water temperatures dur-
ing the summer spawning season (Baba et al., 1999). This
means that a long life span is essential to sustain popula-
tions of C. japonica in northern habitats. We think that a
long life span is the ultimate factor for the extremely slow
growth rate of C. japonica juveniles in Lake Abashiri.
The growth response of C. japonica juveniles is much less
susceptible to environmental factors before the second win-
ter than after and is the proximate factor for an extremely
slow growth rate. Nuculoma tenuis, a detritus feeder, de-
velops its palp proboscides, its feeding apparatus, during
the prolonged phase of meiobenthic development (Harvey
and Gage, 1995). The change of growth susceptibility to en-
vironmental factors in young ages may suggest that some
functional morphological changes occur in C. japonica, also
a filter feeder. In our preliminary analyses, we could not
find a better model when we used different values of smax
in Equation 6 between ages instead of categorical variables
indicating ages. Therefore, we conclude that the difference
in growth rates between ages is not due to a difference in
potential maximum growth rate, at least in the range of the
shell length observed in our study. When our model is ap-
plied to a wider range of the shell lengths or other species,
it is best to examine the age dependence of smax.
Acknowledgments
We express our thanks to T Kato, Vice-Head of the River
Improvement Section in the Abashiri Local Office of the
Hokkaido Development Bureau, for providing environmen-
tal data on Lake Abashiri. We also thank the reviewers of
Fishery Bulletin for providing helpful suggestions on our
manuscript.
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25
Abstract— Information is summarized
on juvenile salmonid distribution, size,
condition, growth, stock origin, and
species and environmental associations
from June and August 2000 GLOBEC
cruises with particular emphasis on
differences related to the regions north
and south of Cape Blanco off Southern
Oregon. Juvenile salmon were more
abundant during the August cruise as
compared to the June cruise and were
mainly distributed northward from
Cape Blanco. There were distinct differ-
ences in distribution patterns between
salmon species: chinook salmon were
found close inshore in cooler water all
along the coast and coho salmon were
rarely found south of Cape Blanco. Dis-
tance offshore and temperature were
the dominant explanatory variables
related to coho and chinook salmon
distribution. The nekton assemblages
differed significantly between cruises.
The June cruise was dominated by juve-
nile rockfishes, rex sole, and sablefish,
which were almost completely absent
in August. The forage fish community
during June comprised Pacific herring
and whitebait smelt north of Cape
Blanco and surf smelt south of Cape
Blanco. The fish community in August
was dominated by Pacific sardines and
highly migratory pelagic species. Esti-
mated growth rates of juvenile coho
salmon were higher in the GLOBEC
study area than in areas farther north.
An unusually high percentage of coho
salmon in the study area were preco-
cious males. Significant differences in
growth and condition of juvenile coho
salmon indicated different oceano-
graphic environments north and south
of Cape Blanco. The condition index
was higher in juvenile coho salmon to
the north but no significant differences
were found for yearling chinook salmon.
Genetic mixed stock analysis indicated
that during June, most of the chinook
salmon in our sample originated from
rivers along the central coast of Oregon.
In August, chinook salmon sampled
south of Cape Blanco were largely from
southern Oregon and northern Cali-
fornia; whereas most chinook salmon
north of Cape Blanco were from the
Central Valley in California.
Manuscript approved for publication
30 June 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull 102:25-46 (2004).
Juvenile salmonid distribution, growth, condition,
origin, and environmental and species associations
in the Northern California Current*
Rick D. Brodeur
Northwest Fisheries Science Center
National Marine Fisheries Service, NOAA
2030 S. Marine Science Drive
Newport, Oregon 97365
E-mail address: Rick-Brodeuriffinoaa-gov
Joseph P. Fisher
College of Ocean and Atmospheric Sciences
Oregon State University
Corvallis, Oregon 97331
David J. Teel
Northwest Fisheries Science Center
National Marine Fisheries Service, NOAA
Seattle, Washington 98112
Robert L. Emmett
Northwest Fisheries Science Center
National Marine Fisheries Service, NOAA
2030 S Marine Science Drive
Newport, Oregon 97365
Edmundo Casillas
Northwest Fisheries Science Center
National Marine Fisheries Service, NOAA
Seattle, Washington 98112
Todd W. Miller
Cooperative Institute for Marine Resources
Studies
Oregon State University
Newport, Oregon 97365
The need to understand the direct
and indirect linkages between oceano-
graphic conditions and salmon sur-
vival in the marine environment has
increased with the listing of many
West Coast salmon stocks as threat-
ened or endangered. Recent studies
have shown that long-term changes
in climate affect oceanic structure and
produce abrupt differences in salmon
marine survival and returns (Francis
and Hare, 1994: Mantua et al., 19971. A
major regime shift in the subarctic and
California Current ecosystems during
the late 1970s may have been a factor
in reducing ocean survival of salmon in
the Pacific Northwest and in increas-
ing marine survival in Alaska ( Hare et
al., 1999). Fluctuations in mortality of
salmon in the freshwater and marine
environments have been shown to be
almost equally significant sources of
annual salmonid recruitment variability
( Bradford, 1995 ). Unlike in the freshwa-
ter environment, the physical and bio-
logical mechanisms and factors in the
marine environment that cause mor-
tality of salmon are largely unknown.
Predation, inter- and intraspecific
competition, food availability, smolt
quality and health, and physical ocean
conditions likely influence survival of
salmon in the marine environment.
Thus, increasing our understanding of
nearshore ocean environments, their
linkages to oceanographic conditions,
and the role they play in salmonid
survival, could provide management
options for increasing adult returns.
Characterization of the space-time vari-
ability of the environmental conditions
that smolts encounter when they enter
the nearshore ocean, and the eventual
survival of these smolts will allow us to
identify which biotic and abiotic ocean
conditions are correlated with various
ocean survival levels.
Many anadromous salmonid popula-
tions along the west coast of the United
States have declined over the last few
decades (Nehlsen et al., 1991), and most
stocks show a regional north-south pat-
tern in degree of extinction risk (Kope
and Wainwright, 1998). This pattern
suggests that both marine habitat con-
ditions and mesoscale climate patterns
affect salmonid population status (e.g.
Lawson, 1993). A dramatic example is
the population trend of coho salmon
(Oncorhynchus kisutch) along the Or-
egon coast. Populations along the coast
north of Cape Blanco (43°N) have exhib-
; Contribution number 364 of the U.S.
GLOBEC program. NEP Office, Oregon
State University, Corvallis. OR.
26
Fishery Bulletin 102(1)
ited a strong decline in size and survival in the mid-1990s;
whereas populations south of Cape Blanco have not shown
this trend (Lewis1). This finding suggests that these two
populations have experienced different ocean conditions.
The quality of the marine habitat (in terms of habitat
complexity, prey density, and temperature) undoubt-
edly influences fish growth and condition. Growth and
indices of condition can be used as measures of habitat
quality for juvenile salmon and to identify essential links
between oceanographic conditions and survival of salmon
populations during the critical juvenile life history phase.
Measures such as growth (growth rate, size variation, and
allometric relationships) (Lorenzen, 1996; McGurk, 1996)
and accumulation of energetic reserves used in growth and
sustenance during the low-productivity winter periods
have been used previously to characterize habitat quality
and to describe how it ultimately affects the individual and
the population (Perry etal., 1996; Paul and Willette, 1997).
Environmental factors are known to affect growth, repro-
duction, survival, and ultimately population recruitment
(Hinch et al., 1995; Marschall and Crowder, 1995; Fried-
land and Haas, 1996). As such, fish condition, growth rate,
and size in the pre-adult stages are parameters that can be
used to identify the influence of natural and anthropogenic
ocean conditions on marine survival.
Much of our current knowledge of the dominant nekton
of the pelagic ecosystem off the coasts of Oregon and Wash-
ington is derived from a series of 17 cruises conducted by
Oregon State University (OSU) from 1979 to 1985. These
collections, consisting of >900 quantitative purse seine sets
in the northern California Current, were made to examine
geographic distributions and temporal trends of the domi-
nant nekton and how these relate to physical and biotic
conditions at the time of capture. The primary purpose
of these cruises was to collect data for assessment of the
abundance, distribution, growth, migration, and ecology of
juvenile salmon in coastal waters. Data on the distribution,
migration and growth of juvenile salmon from these cruises
have been summarized in Fisher and Pearcy (1988; 1995).
Pearcy and Fisher ( 1988, 1990), and Pearcy ( 1992). Analy-
sis of the nonsalmonid data includes studies on their abun-
dance and distribution (Brodeur and Pearcy, 1986; Emmett
and Brodeur, 2000), feeding habits (Brodeur et al., 1987)
and interannual variability in relation to oceanographic
conditions (Brodeur and Pearcy, 1992). In addition, the
distribution of juvenile salmon (mainly coho and chinook
salmon [O. tshawytscha}) has been studied more recently
as a component of a multiyear Columbia River Plume study
(Emmett and Brodeur, 2000; Teel et al., 2003; Brodeur et
al., 2003). However, all these cruises extended only as far
south as Cape Blanco, with the exception of one cruise (July
1984), which extended as far south as Eureka, California,
but included only a few collections south of Cape Blanco
(Pearcy and Fisher, 1990). Thus, the region south of Cape
Blanco is almost completely unknown in terms of juvenile
1 Lewis, M. A. 2002. Stock assessment of anadromous salmo-
nids 2001. Monitoring program report OPSW-ODFW-2002-04,
57 p. Oregon Dept. Fish Wildlife, Portland. OR 97207.
salmon distribution, pelagic nekton, and biological ocean-
ography in general, despite being an area of very strong
upwelling and high productivity. Also, the fine-scale dis-
tribution of juvenile salmon in relation to environmental
variables has not been studied in any detail.
The California Current is not homogeneous but rather
can be divided into distinct subunits or regions, each with
its own physical and biological characteristics (U.S. GLO-
BEC, 1994). A break between the northernmost two regions
occurs at Cape Blanco, where the equatorward upwelling
jet veers sharply off the shelf and into the California Cur-
rent (Barth et al., 2000). The upwelling zone north of the
cape is narrow, extending out about 30 km, whereas south
of Cape Blanco, it can extend up to 100 km offshore. This
area also appears to represent a faunal break for some zoo-
plankton communities (McGowan et al., 1999; Peterson and
Keister, 2002) and is a break point for alternative salmon
migration strategies (Weitkamp et al., 1995; Weitkamp and
Neely, 2002).
During the summer of 2000, we conducted broad-scale
sampling and fine-scale process studies from central Or-
egon to northern California to examine the distribution
of juvenile salmon and associated species in relation to
environmental conditions. This was one component of a
multidisciplinary U.S. Global Ocean Ecosystem Dynamics
(GLOBEC) Northeast Pacific study examining the north-
ern California Current ranging in scope from the physics
up to the top trophic levels (Batchelder et al., 2002). We
were interested in examining the distribution of juvenile
salmon north and south of Cape Blanco, the origin of these
fish, and any regional differences in growth and condition
of salmon across the range of sampling. Evidence exists
that the physical conditions and the associated biota are
different within this geographical scale. Thus, analyses of
the relationship between oceanographic conditions and the
response of resident biota can provide insights into the
linkages associated with physical and biological processes
that shape the biological community, and in particular,
those associated with salmon recruitment.
Methods
Field surveys
Surveys were conducted over two time periods — early
summer (29 May-18 June, 2000) and late summer (28
July-15 August, 2000). Each survey consisted of a meso-
scale grid along designated GLOBEC transects that had
been monitored for several years and by fine-scale pro-
cess sampling at stations of interest based on features
observed in the physical environment (fronts or eddies)
or by acoustic sampling conducted by two accompanying
oceanographic vessels (RV Wecoma and RV New Horizon).
Further details on the physical and biological conditions
occurring at the time of our sampling have been reported
by Batchelder et al. (2002).
For the mesoscale survey, stations were established at
1, 5, 10, 15, 20, 25 and 30 nautical miles from shore on
each of five transects. Inclement weather, particularly
Brodeur et al.: Distribution, growth, condition, origin, and associations of |uvenile salmonids
27
during the first cruise, prevented us from sampling all
the stations along each transect. At each station, a Nordic
264 rope trawl built by Nor'Eastern Trawl Systems, Inc.
(Bainbridge Island, WA) was towed in surface waters by
a chartered fishing vessel (FV Sea Eagle) at a speed of 6
km/h. This rope trawl has a maximum mouth opening of
approximately 30 m x 18 m. Mesh sizes ranged from 162.6
cm in the throat of the trawl near the jib lines to 8.9 cm in
the codend. To maintain catches of small fish and squid, a
6.1-m long, 0.8-cm mesh knotless liner was sewn into the
codend. All tows were 30 minutes in duration. All fish and
squid caught were counted and measured at sea. After fork
length (FL) was measured to the nearest mm, all juvenile
salmon were immediately frozen for later determinations
of growth, condition, food habits, genetic analysis, and as-
sessment of pathological condition.
The physical and biological environment was monitored
and sampled at each station immediately prior to setting
the trawl. A CTD (conductivity, temperature, and depth)
cast was made with a Sea-Bird SBE 19 Seacat profiler to
100 m at deep stations or within 10 m of the bottom at
shallow stations. Chlorophyll and nutrient samples were
collected from 3 m depth with a Niskin water sampler. A
neuston tow with a 1-m2 mouth containing 333-,(im mesh
net was towed for 5 minutes out of the wake of the vessel
at each station. General Oceanics flow meters were placed
inside the net to measure the amount of water sampled.
Additional details on the analysis of these neuston trawls
are available in Reese et al.2
Condition and growth analysis
Each salmonid was remeasured (FL to the nearest mm)
and weighed (to the nearest 0.1 g) in the laboratory. A por-
tion of hepatic and muscle tissue was excised, placed in
individual capsules, frozen in liquid nitrogen, and stored
at -80°C until analyzed. The bioenergetic health of juve-
nile salmon was evaluated by assessing changes in water
content (as a surrogate measure of fat accumulation) of
liver and muscle to estimate dry tissue weight. The water
content was determined by drying tissue samples to a con-
stant weight at 105°C. The accumulation of energy reserves
during the growth season ( energy reserves of salmon in
August in relation to salmon collected in June) that would
enhance survival of juveniles during the winter when food
availability is lower was also measured. The condition of
juvenile salmon was assessed by examining weight residu-
als (by using either the wet weight or dry weight) derived
from the allometric relationship between length and weight
of individual juvenile salmon after logarithmic transforma-
tion (Jakob et al., 1996) of salmon captured in June and
August. Wet-weight residuals are representative of the
traditional condition index of animals and are a reflection
2 Reese, D.C., T.W.Miller, and R.D. Brodeur. 2003. Community
structure of neustonic zooplankton in the northern California
Current in relation to oceanographic conditions. 22 p. Unpubl.
manuscript. Northwest Fisheries Science Center, NMFS. 2030
S. Marine Science Drive, Newport, OR 97365.
of somatic tissue growth. Dry-weight residuals are respon-
sive to accumulation of fat stores and are a reflection of the
bioenergetic health of the individual animal (Sutton et al.,
2000; Post and Parkinson, 2001).
To contrast growth characteristics during 2000 in differ-
ent latitudinal ranges of the California Current, we com-
pared ocean growth rates of juvenile coho salmon south
and north of Cape Blanco in the GLOBEC study area,
and in the area from Newport, Oregon, north to northern
Washington. The physical and biological characteristics of
these three regions of the coastal ocean differ greatly (U.S.
GLOBEC, 1994), and these differences may impact the dis-
tribution and abundance of prey of juvenile salmonids and
therefore may also affect salmonid growth. Data north of
Newport, Oregon, were collected during a separate study of
the Columbia River plume and the adjacent coastal ocean
(hereafter called the "plume study") using the same trawl
and a similar sampling strategy as in the GLOBEC study
(see Emmett and Brodeur [2000] and Teel et al. [2003] for
details).
Scales were examined from 45 juvenile coho salmon
caught during the June and August 2000 GLOBEC
cruises and 252 juvenile coho salmon caught during the
2000 plume cruises. The scales were mounted on gummed
cards from which acetate impressions were made. Using
a video camera attached to a compound microscope and
Optimas® imaging software (vers. 5.1, Optimas Inc., Se-
attle, WA) we measured the distance (scale radius) along
the anterior-posterior axis of each scale from the focus
(F) to the ocean entry mark (OE) and to the scale margin
(Fig. 1). The fork-length of each fish at the time of ocean
entry (FL0E) was estimated from the scale radius (SR0E)
at ocean entry using the Fraser and Lee back-calculation
method (Ricker, 1992):
FL„
(FL- 36.07)
SR
xSRof. +36.07,
where FL = length at capture;
SR = scale radius at capture; and
36.07 = the intercept from a regression of SR on FL
for juvenile coho salmon caught in the ocean
(Fig. 2A).
In an analogous fashion, fish weight at time of ocean entry
(Wr0£) was back-calculated f
length at ocean entry (FL0E):
(Wt0E) was back-calculated from the estimated fish fork
\ni Wt0E) =
(ln(Wr 1 + 12.633)
ln(FL)
xln(FLr,F 1-12.633,
where Wt = weight at capture; and
-12.633 = the intercept from a linear regression of
ln(Wr) on ln(FL) for juvenile coho salmon
caught in the ocean (Fig. 2B).
The growth rate in FL,
(FL-FL0E)lAd,
28
Fishery Bulletin 102(1)
Figure 1
Scale from a 352-mm FL male juvenile coho salmon
(Oncorhynchus kisutch) caught during the August 2000
GLOBEC cruise showing the axis of measurement (black
line), the focus (F), the mark of ocean entry (OE), and the
scale margin (SM).
and the instantaneous growth rate in weight:
G = (MWt)-MWt0E))/M,
where Ad = estimated days between ocean entry and cap-
ture, were estimated for each salmon.
The meaning of the instantaneous growth rate G can be
stated as follows: if salmon growth is exponential between
ocean entry and capture, then
Wt
Wt„
and at any instant the fish's weight increases at the rate of
G of its body weight per day. G can be multiplied by 100 to
give the instantaneous growth rate in terms of percentage
of body weight per day.
Although the dates of ocean entry of individual lish
were unknown, seaward migration of coho salmon smolts
in California, Oregon, and Washington rivers occurs mainly
between mid-April and mid-June, and there is no consis-
tent latitudinal trend in timing of the migration ( Weitkamp
et al., 1995). Peak downstream migration of coho salmon
smolts was between mid-May and very early June in the
Columbia River estuary, 1978-83 (Dawley et al., 1985),
and in the lower Trinity River, California, 1997-2000 (US-
A FL (mm) vs scale radius (mm)
GM Regression: FL = 152.22 SR +36.07
r2 = 0.94, n=370
1 2
Scales radius (mm)
B Wt(g)vs FL(mm)
In(WI) = 3.2273'ln(FL) - 12 6329
or Wt(g) = 3.263x1 (T5 FL(mm)32273
n=1018V = 0.99
s
— 5
In (FL)
Figure 2
(A) Regression of fork length (FL) on scale radius and. 'Bi
regression of ln(WY) on ln(FL) for juvenile coho salmon {On-
corhynchus kisutch) caught during the May 1998-September
2000 Columbia River plume study.
FWS3). In 2000, peak downstream migration of mainly
nonhatchery coho salmon smolts at 13 monitoring sites in
coastal Oregon rivers north of Cape Blanco occurred from
April 2 to May 20; median peak migration occurred 26 April
( Solazzi et al.4) From the information available on timing of
seaward migration of coho salmon smolts. we used an ocean
entry date of 15 May when calculating Ad and estimating
ocean growth rates of unmarked coho salmon from scales.
In addition to estimating growth rates of juvenile
coho salmon from scales, we also estimated instantaneous
growth rates in weight between hatchery release and cap-
ture in the ocean of 28 coded-wire-tagged (CWT) juvenile
coho salmon:
USFWS (U.S. Fish and Wildlife Service). 2001. Juvenile sal-
monid monitoring on the mainstem Klamath River at Big Bar
and mainstem Trinity River at Willow Creek, 1997-2000, 106 p.
Annual report of the Klamath River Fisheries Assessment Pro-
gram. Areata Fish and Wildlife Office, Areata, CA 9552 1 .
Solazzi, M.F., S.L.Johnson, B.Miller, and T.Dalton. 2002. Sal-
monid life-cvele monitoring project 2001. Monitoring program
report OPSW-ODFW-2002-2, 25 p. Oregon Dept. Fish and
Wildlife, Portland. OR 97207.
Brodeur et al.: Distribution, growth, condition, origin, and associations of juvenile salmonids
29
G = (MWt)-MWtR))/M,
where Wt = weight of the CWT fish at capture;
WtR = the average weight of fish in the CWT group
at time of release; and
Ad = days between hatchery release and capture
in the ocean.
Estimated growth rates of these CWT fish, of known release
date and known average release weight were used to vali-
date the growth rates estimated from scale analysis
Our analysis of the growth of chinook salmon based on
scale characteristics is not far enough advanced to report
in this article. We plan to present these data in a later
article.
Contribution of hatchery coho salmon to catches
The total numbers, percentages of marked fish ( any exter-
nal fin clips or internal tags) and grand average weights
of hatchery coho salmon smolts released in 2000 are sum-
marized for different release regions in Appendix Table 1.
These data were used to compare the estimated average
weights of fish at time of ocean entry (from scale analy-
sis ) with the average weights of hatchery fish at time of
release, and also to estimate the proportions of hatchery
coho salmon in our catches. We calculated the expected
percentage (E%) of marked fish in each catch if 100% of
the fish were hatchery fish:
E%
X*.*4,
where i?, = the proportional contribution of region i to the
catch (this paper for the GLOBEC catches,
and from Teel et al., 2003 for the plume study
catches); and
A, = the percentage of hatchery fish that were
marked in region i ( from Appendix Table 1 ).
The percentage of hatchery fish in each catch sample (H%)
was then estimated as
0%
H% = — xlOO,
E%
where OcA = observed percentage of marked fish.
Genetic analysis
The freshwater origins of juvenile chinook and coho salmon
and steelhead (O. my kiss) were studied by using standard
methods of genetic mixed stock analysis (Milner et al.,
1985; Pella and Milner, 1987). According to the methods
described by Aebersold et al. (1987), samples of eye, liver,
heart, and skeletal muscle were extracted from frozen whole
juvenile salmon and analyzed with horizontal starch-gel
protein electrophoresis. Data from previous studies char-
acterizing genetic (allozyme) differences among spawning
populations in California and the Pacific Northwest were
then used as baseline data to estimate the stock composi-
tions of our ocean caught mixed-stock samples. Baselines
consisted of 32 gene loci and 116 populations for chinook
salmon (Teel et al.5), 58 loci and 49 populations for coho
salmon (Teel et al., 2003), and 55 loci and 57 populations
for steelhead (Busby et al., 1996). Estimates of stock com-
positions were made by using the maximum likelihood
procedures described by Pella and Milner (1987) and the
Statistical Package for Analyzing Mixtures (Debevec et al.,
2000). Estimates of individual baseline populations were
then summed to estimate contributions of regional stock
groups. Precision of the stock composition estimates was
estimated by bootstrapping the estimates 100 times with
resampling of the baseline and mixture genetic data as
described in Pella and Milner (1987).
Habitat and assemblage analysis
The raw numbers offish and squid caught from each trawl
were converted to densities based on the volume filtered
per trawl to standardize for differences in effort between
tows. Density contours of juvenile salmon and other nekton
were produced using specialized graphics programs. We
then tested whether the habitat associations of the domi-
nant salmonids were significantly different from the total
habitat sampled by following the methods outlined in Perry
and Smith ( 1994). This procedure involved comparing the
cumulative distributions of salmon catch with observed
environmental conditions (temperature, salinity, chloro-
phyll-a at one meter, water depth, and neuston displace-
ment volume). We performed 5000 randomizations of the
data and used the Cramer-von Mises test statistic recom-
mended by Syrjala ( 1996) as being robust to the effects of
inordinately large catches.
To explore the relationship between juvenile salmon and
other fish species and environmental variables, we used
several types of multivariate analyses (McCune and Grace,
2002 ). Original data from each of the two cruises formed
complimentary species and environmental matrices. The
June and August cruises were analyzed individually to
look at spatial patterns of species composition in relation to
environmental gradients (Gauch, 1982). To avoid spurious
effects of rare species, we excluded species from the data
matrix that had a frequency of occurrence of less than 10%
of the possible occurrences for each cruise (McCune and
Grace, 2002). To minimize the effect of very large catches,
the data were log transformed. Stations with no species
present were eliminated from the data set to allow for anal-
ysis of sample units in species space. Data transformations
and their effects on the summary statistics were examined
prior to analysis. Analyses of data were performed by using
PC-ORD version 4.28 (McCune and Mefford, 1999).
Agglomerative hierarchical cluster analysis (AHCA)
using the Bray-Curtis dissimilarity measure and Wards
Teel, D. J„ P. A. Crane. C. M. Guthrie, III, A. R. Marshall. D.
M. Van Doornik, W. D. Templin, N. V. Varnavskaya, and L. W.
Seeb. 1999. Comprehensive allozyme database discriminates
chinook salmon from around the Pacific Rim. (NPAFC docu-
ment 440), 25 p. Alaska Department of Fish and Game, Divi-
sion of Commercial Fisheries, 333 Raspberry Road, Ancorage, AK
99518.
30
Fishery Bulletin 102(1)
linkage function was applied to arrange the nekton spe-
cies assemblages and stations into cluster groups. The
cutoff level to form optimal groups within the species
and station dendrograms was based on several criteria: 1)
biological meaning; 2) significance tests of groups using
a multi-response permutation procedure (MRPP); and 3i
comparison of cutoff level MRPP results with those groups
obtained from one cutoff level below and above the level of
interest. A nonparametric procedure, MRPP compares the
a priori groupings from AHCA and tests the hypothesis
of no difference between the groups. For cluster analysis
of stations, indicator species analysis (ISA) was used to
determine nekton species strongly associated with indi-
vidual groups. ISA assigns indicator values to each spe-
cies according to relative abundance and frequency, then
tests the significance (Monte-Carlo permutation test) of
the highest species-specific indicator value assigned to a
particular group.
Nonmetric multidimensional scaling (NMS; Kruskal,
1964) was used to ordinate sample units in species space
and to compare station cluster groups to environmental
gradients. NMS was chosen for this analysis because it is
robust to data that are non-normal and that have high
numbers of zeros. Initial runs of NMS from both cruise da-
tasets resulted in three-dimensional solutions. Subsequent
reapplication of NMS using a three-dimensional solution
(Sorensen distance, 400 maximum iterations, and 40 runs
with real data) was applied for the final ordinations. To
examine the environmental or station factors associated
with each NMS axis that may have affected the distribu-
tion of the dominant taxa, we correlated the NMS station
and species scores to a suite of environmental variables
including water depth, distance offshore, latitude, surface
temperature, surface salinity, chlorophyll-a concentration,
and neuston zooplankton settled volumes. Pearson and
Kendall correlations with each ordination axis were used
to measure strength and direction of individual species and
environmental parameters.
Results
Distribution of juvenile salmon and other species
We collected a total of 18,852 nekton individuals: two ceph-
alopod, one agnathan, two elasmobranch, and 57 fish taxa
from 163 surface trawls (see Table 1 for scientific names
of all species). With the exception of market squid in June
and blue shark in August, most of the nonteleost nekton
occurred in only a few collections. Substantially fewer fish
were caught in the June cruise than in the August cruise,
but the diversity was much higher in the June cruise. The
catch in June was dominated by forage fishes such as
Pacific herring, surf and whitebait smelt, and juvenile rock-
fishes, sablefish, and flatfishes. Salmonids, mainly juvenile
chinook and coho salmon and steelhead, comprised a rela-
tively minor proportion of the catches (only 114 juvenile
salmonids; 1.9 % of the total).
The August cruise was dominated by several large
catches of Pacific sardine (Table 1 ). Jack mackerel was the
most common nonsalmonid caught. Many of the juvenile
fish taxa caught during the June cruise were absent during
the August cruise; those that did occur ( sablefish. rex sole)
were much lower in abundance. Mesopelagic fishes of the
family Bathylagidae and Myctophidae were collected only
during the August cruise, mainly because of the inclusion
of more offshore stations and occasional collections during
nondaylight hours. As in the earlier cruise, salmonids com-
prised a relatively minor percentage of the catch (3.19f ) but
were more common and abundant during this survey.
Juvenile chinook salmon were broadly distributed lati-
tudinally during both cruises, but their distribution was
mainly restricted to nearshore stations within the 100-m
isobath (Fig. 3). Coho salmon juveniles were more common
north of Cape Blanco during both cruises and were found
generally farther offshore than chinook salmon juveniles
(Fig. 3). In contrast, steelhead juveniles were found mainly
south of Cape Blanco, especially in June, but their zonal
distribution overlapped that of coho salmon juveniles.
Size and condition of juvenile salmon
Fork length of yearling chinook salmon averaged 227 ±42
mm FL in June and 230 ±30 mm FL in August and aver-
aged 135 ±12 mm FL for subyearling chinook salmon in
August, whereas juvenile coho salmon averaged 162 ±32
mm FL in June and 286 ±46 mm FL in August ( Table 2 ). No
significant differences in fork length of juvenile chinook or
coho salmon north or south of Cape Blanco were evident.
Juvenile coho salmon weighed significantly more on a
wet-weight basis for a given fork length in the region north
of Cape Blanco compared to juveniles captured south of
Cape Blanco (Fig. 4). This pattern was also similar and
significant when evaluated on a dry-weight basis (bioen-
ergetic growth). Although the stock composition in the two
regions could account for some of these differences, the
growth responses likely reflect habitat-specific features in
the region north of Cape Blanco that benefit coho salmon.
No difference in condition of yearling chinook salmon cap-
tured north or south of Cape Blanco, on either a wet- or dry-
weight basis, was evident (Fig. 4). Information regarding
size and condition of subyearling chinook salmon are not
presented because few subyearling chinook salmon were
caught in June and all but one subyearling chinook salmon
in August were caught in the region south of Cape Blanco,
OR. Insufficient subyearling chinook salmon were avail-
able for an analysis comparable to that done for yearling
chinook and coho salmon.
Proportions of wild and hatchery coho salmon
Most of the juvenile coho salmon caught during the plume
study north of Newport, Oregon, originated in hatcher-
ies (Table 3). In June and September 2000 we estimated
that wild fish comprised only W9i and 25r< . respectively,
of the catch. Wild fish, however, comprised a proportion-
ally much higher percentage of the catch of coho salmon
in the GLOBEC study area in June north of Cape Blanco
(67$ I, and in August south of Cape Blanco (619! I, than in
the plume study area farther to the north. Most jacks and
Brodeur et al.: Distribution, growth, condition, origin, and associations of |uvenile salmonids
31
Table 1
Phylogenetic listing of nekton catch in numerical composition, frequency of occurrence
(F.O.) and size
range cau
ght for each cruise.
(j) indicates juvenile stage; (a) adult. ML =
mantle length, TL = total length.
FL = fork length, SL = standard length (
in mm).
Class and Family
Common name
June (84 stations)
August (79 stations)
Scientific name
dumber
F.O.
Size range
Number
F.O.
Size range
Cephalopoda
Onychoteuthidae
Pacific clubhook
squid
Onychoteuthis
borealijaponicus
19
6
21-80 ML
302
6
21-227 ML
Loliginidae
Market squid
Loligo opalescens
301
14
33-122 ML
1
1
35 ML
Agnatha
Petromyzontidae
Pacific lamprey
Lampetra tridentata
1
1
625 TL
Chondrichthyes
Alopiidae
Thresher shark
Alopias vulpinus
1
1
36-576 TL
Carcharhinidae
Blue shark
Prionace glauca
18
10
1300-1660 TL
Osteichthyes
Xenocongridae
Eel leptocephalus
Thalassenchelys coheni
3
1
214-243 TL
2
2
260-305 TL
Clupeidae
Pacific herring
Clupea pallasi
1022
9
127-195 FL
Pacific sardine
Sardinops sagax
7
2
237-260 FL
10,327
15
178-290 FL
Engraulididae
Northern anchovy
Engraulis mordax
49
12
148-165 FL
Salmonidae
Chinook salmon (j,a)
Oncorhynchus
tshawytscha
56
18
121-780 FL
252
26
109-910 FL
Coho salmon (j,a)
Oncorhynchus kisutch
35
15
122-580 FL
111
25
210-736 FL
Cutthroat trout (j,a)
Oncorhynchus clarki
1
1
186 FL
3
3
258-341 FL
Steelhead trout (j,a)
Oncorhynchus mykiss
22
8
176-284 FL
36
13
261-430 FL
Osmeridae
Smelt (j)
Osmeridae
14
4
37-52 SL
74
5
31-50 SL
Surf smelt
Hypomesus pretiosus
846
8
128-184 FL
351
7
140-187 FL
Whitebait smelt
Allosmerus elongatus
946
6
60-114 FL
79
3
76-132 FL
Bathylagidae
Popeye blacksmelt
Bathylagus ochotensis
1
1
76 SL
Paralepidae
Slender barracudina
Lestidium ringens
3
1
72-76 SL
Myctophidae
Northern lampfish
Stenobrachius leucopsarus
96
4
14-70 SL
Bigfin lanterfish
Symbolophorus californiensis
61
4
89-102 SL
Blue laternfish
Tarletonbeama crenularis
10
3
33-87 SL
Gadidae
Gadid(j)
Gadidae
10
3
42-58 SL
13
3
53-57 SL
Pacific cod 1 j )
Gadus macrocephalus
23
1
38-60 SL
Pacific tomcod ( j )
Microgadus proximus
6
4
35-55 SL
8
2
49-80 SL
Scomberesocidae
Pacific saury
Cololabis saira
26
1
182-229 FL
66
6
131-194 FL
Atherinidae
Jacksmelt
Atherinopsis californiensis
1
1
302 FL
Trachipteridae
King-of-the-salmon (j )
Trachipterus altivelis
2
2
71-270 SL
12
2
40-83 SL
Gasterosteidae
Threespine stickleback
Gasterosteus aculeatus
1
1
60 SL
Scorpaenidae
Pacific ocean perch (j )
Sebastes alutus
1
1
33 SL
Darkblotched rockfish (j
Sebastes crameri
154
14
29-54 SL
1
1
53 SL
Yellowtail rockfish (j)
Sebastes flavidus
1350
24
20-63 SL
1
1
18 SL
Shortbelly rockfish (j )
Sebastes jordani
1
1
37 SL
Black rockfish (j,a)
Sebastes melanops
1
1
30 SL
1
1
335 FL
Bocaccio (j )
Sebastes paucispinis
20
5
21-36 SL
Canary rockfish (j )
Sebastes pinniger
27
5
22-39 SL
Bank rockfish (j )
Sebastes rufus
8
1
16-28 SL
Stripetail rockfish (j)
Sebastes saxicola
13
3
32-37 SL
Hexagrammidae
Lingcod (j)
Ophiodon elongatus
20
9
76-81 FL
Anoplopomatidae
Sablefish (j )
Anoplopoma fimbria
182
14
55-136 FL
4
2
173-241 FL
continued
32
Fishery Bulletin 102(1)
Table 1 (continued)
Class and Family
Common name
Scientific name
June (84 stations)
August 179 stations)
Number
F.O.
Size range
Number
F.O.
Size range
Cottidae
Irish lord Ij)
Hemilepidotus spp.
2
1
38-40 FL
Cabezon (j )
Scorpeanichthys
marmoratus
12
7
33-38 SL
Pacific staghorn
sculpin
Leptocottus armatus
1
1
180 TL
Agonidae
Sturgeon poacher (j)
Podothecus acipenserinus
1
1
80 TL
Cyclopteridae
Pacific spiny
lumpsucker
Eumierotremus orbis
1
1
253 TL
Carangidae
Jack mackerel
Trachurus symmetricus
111
3
364-583 FL
839
20
227-589 FL
Bramidae
Pacific pomfret
Brama japonica
5
2
387-434 FL
Anarhichadidae
Wolf-eel (j)
Anarrhichthys ocellatus
15
13
215-555 TL
8
7
442-582 TL
Ammodytidae
Pacific sandlance
Ammodytes hexapterus
4
4
45-82 SL
Zaprodidae
Prowfish (j)
Zaprora silenus
1
1
68 SL
Scombridae
Chub mackerel
Scomber japonicus
74
6
266-421 FL
Centrolophidae
Medusafish
Icichthys lockingtoni
3
3
37-50 SL
8
6
87-129 FL
Bothidae
Sanddabs (j)
Citharichthys spp.
23
13
35-43 SL
3
2
269-288 TL
Pacific sanddab (j )
Citharichthys sordidus
32
4
32^4 SL
Speckled sanddab (j )
Citharichthys stigmaeus
60
10
30-43 SL
Pleuronectidae
Dover sole (j)
Microstomas pacificus
2
2
40-50 SL
3
1
27-34 SL
Sand sole (j)
Psettichthys melanostictus
3
3
22-39 SL
Slender sole (j)
Eopsetta exilis
1
1
66 SL
Starry flounder
Platichthys stellatus
2
1
349-399 TL
Curlfin sole (j)
Pleuronichthys decurrens
5
3
25-31 SL
English sole
Parophrys vetulus
1
1
303 TL
Rex sole (j )
Errex zachirus
581
12
34-79 SL
48
11
44-70 SL
Molidae
Ocean sunfish
Mola mola
1
1
620 TL
Total
5974
12,878
about one half of the nonjacks caught north of Cape Blanco
in August were hatchery fish.
Two factors, however, may have lead to inaccuracies in
estimation of hatchery-wild ratios of coho salmon in the
GLOBEC study area. First, because of low sample sizes,
the data were pooled from both June and August catches
for the genetic stock analysis; therefore we do not know the
proportional contributions of the different release areas
to the catches in either month alone. Second, all the fish
released from Klamath River and Trinity River hatcheries
had been clipped on the maxillary. We were unaware that
the maxillary clip was being used, did not look for it, and
consequently may have classified fish with this mark as
unmarked. Therefore, the proportion of hatchery fish in
the catch of coho salmon during GLOBEC may have been
higher than is shown in Table 3.
Age and growth of juvenile coho salmon
Forty-three percent (24 of 56) of the juvenile coho salmon
caught during the August GLOBEC cruise were preco-
cious males ("jacks") according to the testes-weight to
body-weight criteria of Pearcy and Fisher ( 1988). This is a
much higher percentage of jacks than found among juve-
nile fish caught in September 2000 in the plume study off
Oregon and Washington, where only 4.5% offish (6 of 132)
were precocious males or females according to the same
criteria. Because the jacks were considerably larger than
the nonjacks, average growth rates of the two groups were
reported separately.
Estimated average growth rates in FL between ocean
entry and capture were higher for fish caught in the
August 2000 GLOBEC cruises (1.56-2.22 mm/d) than
for fish caught in any other cruises (Table 3). The fish
caught in August 2000 were also larger when they entered
the ocean (average 170- 178 mm FL) than fish caught in
other cruises (averagel54-160 mm FL). Average growth
rate of jacks from north of Cape Blanco (2.22 mm/d), was
significantly higher (/-test, P<0.05) than growth rates of
nonjacks (1.56-1.67 mm/d). Growth rates of nonjacks north
and south of Cape Blanco were not significantly different la-
test, P<0.05). The combination of large size at ocean entry
Brodeur et al.: Distribution, growth, condition, origin, and associations of juvenile salmonids
33
45.0
44.5
44.0
43.5
43.0
42.5
42.0
41.5
Newport
Chinook
>
0
1 to
5
0
6 to
150
Coho
A
1 10
5
A
6 to
150
J
Oregon
r California
45.0
44.5
44.0
43.5
43.0
42.5
42.0
41.5
125.5
125.0
124.5
124,0
123.5 125.5
Longitude (W)
125.0
124.5
124.0
123.5
Figure 3
Catch distribution for juvenile coho (Oncorhynchus kisutch) and chinook salmon (O. tshawytscha)
for the (A) June and (B) August cruise overlaid on surface temperature contours. Plus signs are
stations sampled where no salmon were caught.
and favorable conditions for growth in the ocean probably
contributed to the very high percentage of jack coho salmon
in August 2000 in the GLOBEC study area.
Estimated average growth rates between ocean entry and
capture of juvenile coho salmon were higher in the GLOBEC
area than in the plume study area U-tests, P<0.05). For fish
caught in June, average growth rate was 1.06 mm/d and 0.63
mm/d in the GLOBEC and plume study areas, respectively.
For fish caught in August or September, average growth
rate was 1.57-2.22 mm/d in the GLOBEC study area and
1.17 mm/d plume in the study area (Table 3). The higher
growth rates of coho salmon caught in the GLOBEC study
area suggests that in 2000 conditions for growth were bet-
ter there than those in the plume study area farther north
off Oregon and Washington. Average instantaneous growth
rates in weight were also higher (/-tests, P<0.05) for the
fish caught in the June and August 2000 GLOBEC cruises
(2.0 and 2.1-2.8% body wt/d, respectively) than for the fish
caught in the June and September 2000 plume study cruises
(1.2 and 1.7 % body wt/d, respectively; Table 4A).
In addition, the average condition index (CI) of juve-
nile coho salmon in June was significantly higher (/-test,
P=0.03) in the GLOBEC study area (1.12, n=32, SD=0.087)
than in the plume study area (1.07, n=245, SD=0.117).
Similarly, the average CI of nonjack juvenile coho salmon
was higher (/-test, P=0.002) in August in the GLOBEC
study area (1.24, n=32, SD=0.096) than in September in
the plume study area (1.18, n=132, SD=0.100). Both the
high instantaneous growth rates in weight and the high
CI of juvenile coho salmon caught in the GLOBEC study
area suggest that conditions for growth of coho salmon in
this area were very good in 2000. Growth rates estimated
from the few CWT fish caught during these cruises (Table
4B) were similar to, and help validate, the growth rates
estimated from scales (Table 4A).
Average weights at time of ocean entry back-calculated
from scales for coho salmon caught in June in the GLOBEC
area and in all months in the plume study area (Table 4A)
were slightly higher than the average weights of hatchery
coho salmon at time of release (Appendix Table 1). For ex-
ample, in the plume study area, average back calculated
weights at ocean entry ranged from 37.5 g to 42.4 g (Table
4A) — slightly higher than the expected average weights
at release of about 32-33 g based on the stock composi-
34
Fishery Bulletin 102(1)
Table 2
Summary of mean, standard deviation, and range of FL measured in the field, weight measured in the laboratory, and condition
index (CI) of subyearling (age 0.0) and yearling (age 1.0) chinook salmon and yearling (age 1.0) coho salmon caught during the June
and August cruises north (N) and south (S) of Cape Blanco (latitude 42.837°). Precocious coho salmon are indicated with a "J".
Field FL (mm)
Laboratory
weight (g)
C.I.
(wtx 105/ FL3 )
n
Mean
SD
Range
Mean
SD
Range
Mean
SD
Chinook (age 0.0)
June (N)
1
121
—
—
18
—
—
1.04
—
August (N)
1
172
—
—
70
—
—
1.37
—
August (S)
125
134
12
109-175
28
9
12-70
1.10
0.08
Chinook (age 1.0)
June (N)
27
229
42
144-280
178
91
33-306
1.32
0.10
June(S)
1
174
—
—
67
—
—
1.28
—
August (N)
54
229
26
187-318
164
72
80-468
1.32
0.09
August (S)
35
231
35
190-349
176
94
80-535
1.32
0.07
Coho (age 1.0)
June (N)
30
161
33
122-276
56
51
19-292
1.13
0.08
June (S)
2
172
0
172-172
49
1
48-49
0.95
0.01
August (N-J)
24
365
31
310-415
690
209
375-1198
1.38
0.12
August (N)
24
285
51
210-385
326
188
97-766
1.26
0.10
August (S)
8
293
33
239-334
308
103
157-433
1.19
0.05
Table 3
Catch, percentage of the catch that was marked, estimated percentage of hatchery origin, size of scale sample, FL at ocean entry
(OE) back calculated from scales, FL at capture, and estimated growth rate in FL while in the ocean for juvenile coho salmon
caught during the 2000 GLOBEC and Columbia River plume studies. All length data are from the scale sample only. An ocean entry
date of 15 May was used when calculating growth rate in FL.
Cruise
Catch
(n)
Marked
Estimated % Scale sample
hatchery origin (n)
Back-
calculated FL
at OE (mm)
mean (SD)
FL at capture
(mm)
Growth rate
(mm/d)
mean (SD)
mean(SD)
GLOBEC
June 2000
32
32%
33% 11
155 (29.0)
177(42.3)
1.06(1.01)
Aug 2000
North of C.Blanco
Jacks
24
71%
74% 19
170(22.8)
370(28.1)
2.22 (0.35)
Nonjacks
24
46%
48% 9
178(21.6)
309(46.1)
1.67 (0.51)
South of C. Blanco
Nonjacks
8
38%
39% 6
178(13.0)
303 (29.3)
1.56 (0.22)
Plume study
May 2000
165
68%
76-80%; 79
157(16.5)
166(17.7)
0.97(1.15)
Jun 2000
245
76%
90% 97
160(14.5)
185(23.4)
0.63 (0.53)
Sep 2000
132
65%
75% 76
154(19.0)
305 (24.9)
1.17(0.23)
' No genetic stock analysis was available. The higher estimate assumes the same stock composition as in June,
hatchery fish were from the Columbia River.
the lower estimate
assumes that all
Brodeur et al.: Distribution, growth, condition, origin, and associations of |uvenile salmonids
35
A
0.004
0002
0
-0.002
-0.004
□ Wet Wt (Somatic Growth)
to
as -0.006
"D
■ Dry Wl (Energetic Growth)
CO
1) 0.02 -,
o
B
0.01 -
—L— H^H
-0.01 -
-0.02 -
-0.03 -
-0.04 -
-0.05 -
l
-0.06 -
-0.07 -
Cape Blanco Cape Blanco
North South
Figure 4
Wet and dry weight residuals ( + 1 standard error) for (A) yearling chinook (On-
corhynchus tshawytscha) and (B) juvenile coho salmon (O. kisutch) collected
North and South of Cape Blanco. Weight residuals are derived from the linear
relationship between fork length and wet or dry weight (log-transformed data)
of juvenile salmon captured in June and August.
tion of these catches (Teel et al., 2003) and the release
weights (Appendix Table 1). Similarly, the back-calculated
weight at ocean entry in June in the GLOBEC area (45.5 g)
was slightly higher than the expected average weight at
hatchery release (about 41 gl based on the stock compo-
sition (Table 5) and the average release weights. These
fairly small differences between back-calculated size at
ocean entry and average size at release could be due to
growth during downstream migration, selectively higher
mortality of small smolts, or a bias in the back-calculation
procedure.
However, the average back-calculated weights at time of
ocean entry offish caught in August in the GLOBEC study
area (60-69 g) were over two standard deviations above the
average weights of hatchery fish released from the Oregon
coast or northern California — the main contributors to this
catch (Appendix Table 1). These were obviously atypical
coho salmon, and the very high proportion of jacks (preco-
36
Fishery Bulletin 102(1)
Table 4
(A) Weights at ocean entry
I OE ) back-calculated from scales, weights at capture
and estimated instantaneous rates
of growth while
in the ocean iGl for juvenile coho salmon
caught during the 2000 GLOBEC and Col
umbia River plume studies.
An ocean entry
date of 15 May was used when calculating growth rate. (B) Similar data for CWT fish.
Growth rates of the CWT coho salmon were
estimated for the periods
between hatchery release and capture in the ocean.
A Cruise
;;
Back-calc. Wt. at OE (g)
Weight at capture (g)
G
mean (SD)
mean(SD)
mean (SD)
GLOBEC
June 2000
11
45.5 (26.8)
78.0(76.4)
0.020(0.015)
Aug 2000
North of C.
Blanco
Jacks
19
68.9(27.2)
719.7(200.0)
0.028 (0.005)
Nonjacks
9
59.5 (26.3)
419.2(177.2)
0.023 (0.006)
South of C.
Blanco
Nonjacks
6
60.3(12.8)
336.2 (96.2)
0.021 (0.002)
Plume study
May 2000
79
39.4 (10.8)
47.9(14.6)
0.020(0.024)
Jun 2000
97
42.4(12.5)
71.9(33.3)
0.012(0.009)
Sep 2000
75
37.5(13.7)
347.2(158.3)
0.017(0.003)
B Cruise
n
Wt. at release (g)
Wt. at capture (g)
G
mean (SD)
mean (SD)
mean (SD)
GLOBEC
Jun 2000
4
44.4(1.3)
86.6 (30.9)
0.018(0.005)
Aug 2000
3
35.6 (9.8)
395.7(215.0)
0.024(0.003)
Plume study
Jun 2000
11
28.3(4.5)
66.1(32.3)
0.012(0.005)
Sep 2000
10
33.4(10.91
392.4(283.3)
0.018(0.002)
cious, sexually developed males) among the fish was prob-
ably a consequence of their very large size at ocean entry
and their high rates of growth in the ocean.
Freshwater origins of juvenile salmonids
Allozyme data were collected from samples of 247 chinook
salmon, 88 coho salmon, and 58 steelhead. Genetic mixed
stock analyses indicated that chinook salmon in June were
predominately (54%, SD=0.18) from rivers and hatcheries
along the mid Oregon coast, an area immediately north of
Cape Blanco (Table 5, Fig. 5). In August, chinook salmon
were largely from rivers that enter the sea south of Cape
Blanco. Fish from the Sacramento and San Joaquin rivers
in northern California were estimated to comprise 90%
(SD=0.07) of the chinook salmon sampled in August north
of Cape Blanco. The largest concentration of chinook
salmon we sampled was south of Cape Blanco in August,
and these fish were mostly from rivers in southern Oregon
(539(, SD=0.10) and the Sacramento and San Joaquin
rivers (20%, SD=0.05). Chinook salmon from the Colum-
bia River Basin were also present, but were estimated
to comprise only 18% (SD=0.15) of the June sample and
8% (SD=0.05) of the August sample north of Cape Blanco.
Recoveries of hatchery chinook salmon bearing coded-wire
tags (CWT) provided direct evidence of stock origins for
ten fish, all taken in trawls north of Cape Blanco (Table
5). These data reveal that hatchery fish released from
the Umpqua River on the central Oregon coast (;;=6),
Columbia River Basin («=3) and Sacramento River (« = 1)
contributed to our sample of chinook salmon. The propor-
tion of CWT fish from the Umpqua River in our August
catch north of Cape Blanco (8%) indicated that the con-
tribution of mid Oregon coastal fish was underestimated
in the genetic analysis likely because of the small size of
the mixture sample.
Genetic estimates of coho salmon indicated that most
fish originated from coastal Oregon rivers north of Cape
Blanco (479S , SD=0.10) and from the Columbia River (13%,
SD=0.08 ) (Table 5 ). However, a substantial proportion (40r/i ,
SD=0.09) of coho salmon were from coastal rivers south of
Cape Blanco, a region that includes spawning populations
in the Rogue and Klamath rivers. Eight coho salmon in
our sample contained CWTs and showed that fish from
Brodeur et al.: Distribution, growth, condition, origin, and associations of juvenile salmonids
37
Table 5
Estimated percentage stock compositions, samples sizes, and recoveries
of coded wire tags (CWTs) for chinook and coho salmon and
steelhead sampled in trawl surveys along the Oregon and California coasts in 2000
Some of tht
major baseline stocks are given for
coastal stock groups. None of the steelhead sampled contained coded wire tags.
June (rc=35)
August (?!=157) August (n=55)
Entire
South of
North of
Study Area
Cape Blanco Cape Blanco
Chinook salmon stock group Est.
SD CWT Est.
SD CWT Est.
SD CWT
Columbia and Snake Rivers 18
0.15
2 3
0.03 8
0.05 1
North Oregon coast (Nehalem, Trask, Alsea, and Siuslaw Rivers) 0
0.00
0
0.00 0
0.00
Mid Oregon coast (Umpqua, Coquille, Sixes, and Elk Rivers) 54
0.18
3 3
0.03 1
0.02 3
South Oregon coast (Rogue. Chetco, and Winchuck Rivers) 26
0.16
53
0.10 0
0.00
Klamath and Trinity Rivers 0
0.00
14
0.07 0
0.00
North California Coast (Mad, Eel, and Mattole Rivers) 2
0.05
7
0.07 1
0.04
Sacramento and San Joaquin Rivers 0
0.00
20
0.05 90
0.07 1
June and August (rc=88)
Coho salmon stock group
Entire study area
Est.
SD CWT
Columbia River
13
0.08 2
North and Mid Oregon coast (Nehalem, Siletz, Alsea, Umpqua, and Coos Rivers)
47
0.10 5
Rogue and Klamath Rivers
40
0.09 1
North California Coast (Mad, Russian, Little, and Scott Rivers)
0
0.00
June and August (n=58)
Steelhead trout stock group
Entire study area
Est.
SD
Columbia and Snake Rivers
0
0.00
North and Mid Oregon coast (Nehalem, Siletz, Alsea, Umpqua, Coos,
and Coquille Rivers)
1
0.03
South Oregon coast (Elk, Rogue, Chetco, and Winchuck Rivers)
53
0.08
Smith, Klamath, and Trinity Rivers
0
0.00
North California Coast (Mad, Eel, and Ten Mile Rivers)
10
0.05
Sacramento and San Joaquin Rivers
14
0.05
Central and South California Coast (San Lorenzo River and Scott, Pauma,
and Gaviota Creeks
3
0.02
Unknown
19
—
hatcheries in the Umpqua River (n=5), Rogue River (n=l),
and Columbia River (n=2) were in our study area.
Genetic analysis of steelhead samples showed that a
large proportion were from the Rogue River and nearby
coastal streams (53%, SD=0.08). Steelhead from the Sacra-
mento and San Joaquin rivers (14%, SD=0.05) and north-
ern California coastal rivers (10%, SD=0.05) were also
present. Estimates for steelhead originating from rivers
north of Cape Blanco and from south of the San Francisco
Bay were near zero. Approximately 19% of the steelhead
mixture was not allocated to any source population, sug-
gesting that our baseline data for the species is incomplete.
No steelhead in our collections contained CWTs.
Species associations of juvenile salmonids and other
species
From cluster analysis of species based on station assem-
blages (Fig. 6), MRPP of both sample periods showed strong
within-group agreement (P<0.0001) at the first level (two
groups); all subsequent groups had sequentially higher
levels of within-group agreement. As a result, the cutoff
level was determined by balancing a lower percent infor-
mation remaining (<30%) in the model while retaining bio-
logically meaningful groups. For June this cutoff resided at
the second level (three groups) and for August, at the third
level (four groups ). For the June cruise, all salmonids includ-
38
Fishery Bulletin 102(1)
1
A
I
127°
i
122"
1
117"W
— 50°N
Vancouver "~-~~
Island ^fc---
B.C.
-
Pacific
Ocean
Olympic
Peninsula
Puge!
^ Sound , r" r£*\ •/
- 46"
Columbia R
-5sk^ "X Columbia R
L wA
J Snake R _
— 42"
N
-38" ^
Newport
Cape Blanco / ,-.-,
/ • Yj
Crescent City vC7
Eel R. /\\
I
s" Umpqua
Rogue R
CU
/ o> r /,
3 ) A
3 ( L-
o
\ ;o V
i
R. 1
OR
V
ID
CA
3arvJu
1 1 1
0 1 00 200 km
I
B
1 1
127- 122-
1
117"W
June
-so-N entire
study area
.^^
-
©
f|°oo
~46' August
north of
Cape Blanco
° oo
7\
-4-' W
i
August
south of
#•'-.
i
Cape Blanco
i
#
•
0 100 200 km
1 1
••
1 1
— 50* N
c
— r
132"
127°
122°
'46'June and August
entire study area
— 42"
O •
N
J_
_L
J.
Figure 5
(A) Map of study area and location of GLOBEC sampling (hatching). (B) Stock compositions of chinook salmon (Oncorhynchus
tshawytscha). Stock groups are North of Columbia River (grey), Columbia River Basin (green), north Oregon coast (pink), mid Oregon
coast (yellow), south Oregon coast (dark blue), Klamath River Basin (black), north California coast (light blue), and Central Valley
(red). (C) Stock compositions of coho salmon (O. kisutch). Stock groups are Columbia River (green), mid and north Oregon coast (dark
pink), Rogue and Klamath rivers (blue), and north California coast (orange).
Brodeur et al.: Distribution, growth, condition, origin, and associations of juvenile salmonids
39
June
100
Information remaining (%)
75 50 25
H 1 1 1 H
Coho
Chinook (a)
Wolfeel
Chinook (j)
Lmgcod
Steelhead
Sablefish
Market squid
Whitebait smelt
Pacific herring
Surf smelt
Darkblotched rockfish — ,
Yellowtail rockfish — T~
Rex sole —
Speckled sanddab —
i
August
100
r-
Information remaining (%)
75 50 25
H 1 1 1 h
i
Coho (a)
Coho (j)
Chinook (a)
Chinook (j)
Surf smelt
Steelhead
Medusafish
Pacific saury
Wolfeel
Osmeriid (j)
Blue shark
Northern anchovy
Rex sole
Chub mackerel
Pacific sardine
Jack mackerel
Figure 6
Cluster species groupings by cruise. The dashed lines indicate the cutoff levels for each
cluster group. See Table 1 for scientific names.
i>
ing steelhead were classified within the same grouping that
included several pelagic juvenile taxa, including wolf-eel,
lingcod, and sablefish (Fig. 61. Two other clusters that were
not associated with juvenile salmon included a southern
inshore group consisting of market squid. Pacific herring,
and two species of smelt and an offshore northern group
consisting primarily of juvenile rockfish and rex sole. For
the August cruise, all salmonid juveniles and adults again
clustered together in one large group with surf smelt and
medusafish ( Fig. 6 ). The remaining three groups were much
smaller and consisted primarily of offshore pelagic species.
Cluster analysis of stations based on species assem-
blages, and subsequent examination of the cutoff level us-
ing MRPP, resulted in three groupings from both sample
periods (Fig. 7). MRPP revealed strong within-group
agreement for all levels (P<0.0001); however, delineation
at three groups was based on maintaining lower percent in-
formation remaining (<30%) and still having a meaningful
level of resolution. There was some measure of geographic
separation among the three groups (Fig. 7). In June, group
A was predominantly inshore and mostly in the southern
half of the sampling area, group B was found mainly in
the middle shelf region and was more northern, and group
C was found predominantly offshore. In August, group A
consisted of only three stations, all south of Cape Blanco,
whereas groups B and C both spanned the entire shelf and
offshore region and had no particular north-south affin-
ity (Fig. 7). ISA of the groups from both sampling periods
showed that only groups A and C had indicator species
(Tables 6 and 7), whereas the intermediate groups had
none.
Ordination analyses and environmental correlates
NMS ordination of the June sampling period (Fig. 8A)
revealed most of the variance in the data: axes 1 and
40
Fishery Bulletin 102(1)
June
2000 AAAAAn] a
44.5-
□ A *
rw
44.0-
cPa A a
n nrriAAA
d
43.5-
n nriAA'fY/
•
43.0-
A \
D
AA \ (
□□ ao/
duster Groupings
42.5-
' Group A O ,
Group B A
aA
Group C [
42.0-
OnA
, , , i i , , , ,
1
42.0-
August 2000 rr D| &A
A
125.5 125.0 124.5 124.0 1235 125.5 125.0 124.5 124.0 123.5
Longitude (W)
Figure 7
Map showing locations of cluster station groupings by cruise.
Table 6
Indicator species analysis showing indicator values for dominant pelagic nekton captu
mean, standard deviations (SD), and P- values for each cluster grouping. Cluster Group
mined to be indicators of that group.
•ed in pelagic trawls during June 2000 and
B did not have any species that were deter-
Group
Species
Observed indicator
value (IV)
Indicator value IV from randomized
groups
P-value
Mean
SD
A
chinook (age 0.0 1
61.0
15.7
6.54
<0.001
A
lingcod
26.1
12.6
5.67
0.024
A
Pacific herring
71.7
12.8
5.88
<0.001
A
surf smelt
86.5
11.8
5.59
<0.001
A
whitebait smelt
31.5
10.4
5.55
0.007
A
market squid
50.8
15.0
6.20
<0.001
C
darkblotched rockfish
66.8
1 5 8
6.31
<0.001
C
rex sole
46.0
15.0
6.24
0.002
C
sablefish
31.1
16.2
6.32
0.035
C
speckled sanddab
52.5
13.4
5.94
0.001
C
yellowtail rockfish
98.8
19.0
6.30
<0.001
3 represented 31% and 237f, respectively (stress=16.3).
Temperature, depth and salinity best explained the ordi-
n;it ion of stations, representing a cross shelf gradient from
nearshore high levels of salinity to increasing temperature
and depth offshore. Ordination of August stations (Fig.
8B) represented 42' i of the variance in the data, and 23%
of the variance was loaded on axis 2 and 19% on axis 3
(stress=19.4). As with June, salinity increased toward the
coast and temperature and depth increased off the shelf.
The groups derived from the cluster analysis tended to
group together in multivariate space, with the exception
of group B in the June cruise (triangles in Fig. 8A).
Brodeur et al.: Distribution, growth, condition, origin, and associations of |uvenile salmonids
41
Table 7
Indicator Species Analysis showing indicator values for dominant pelagic nekton captured in pelagic trawls during August 2000
and mean, standard deviations (SD), and P-values for each cluster grouping. Cluster Group B did not have any species that were
determined to be indicators of that group.
Group
Species
Observed indicator
value (IV)
Indicator value IV from randomized groups
P-value
Mean
SD
A
chinook (age 1.0)
76.5
21.3
11.18
0.004
A
A
chinook (age 0.0)
surf smelt
80.4
97.9
22.1
12.4
11.62
8.21
0.003
<0.001
C
chub mackerel
33.3
12.8
8.88
0.021
C
jack mackerel
73.7
23.0
11.86
0.006
Table 8
Results of statistical tests for habitat associations between juvenile salmon and environmental or station variables from each
cruise in 2000. Fish marked by zeros indicate subyearlings and those marked with one indicate yearlings. Shown are the P-levels
for 5000 randomizations of the cumulative frequency of the habitat variable and the proportion of the standardized salmon catch
associated with each habitat observation. Results are based on the Cramer von-Mises test statistic determined from binned data
for depth and neuston biomass. Significance values <0.05 are shown in boldface.
Cruise
Jun
Aug
Taxon and age
Surface temp.
Surface salinity
1-m chlorophyll
Bottom depth
Neuston biomass
chinook (age 1.0)
0.30
0.60
0.13
0.18
0.13
coho (age 1.0)
0.33
0.48
0.21
0.17
0.31
chinook (age 0.0)
0.36
0.25
0.13
0.35
0.42
chinook (age 1.0)
0.04
<0.01
<0.01
0.02
0.29
coho (age 1.0)
0.68
0.04
0.07
0.02
0.45
There were few instances where the habitat associations
of juvenile salmon were significantly different from the
distribution of environmental variables sampled (Table 8).
None of the variables were significant for yearling chinook
and coho salmon in the June sampling (no subyearling
salmon were caught during that cruise). In August, all
the variables except neuston biomass were significant for
yearling chinook salmon. These fish were collected at cooler
temperatures, higher salinities, higher chlorophyll-o con-
centrations, and at shallower depths than have been typi-
cally recorded (Fig. 9). Coho salmonjuveniles were found in
higher salinities and shallower depths than at the sampled
habitat (Fig. 9). These results correlated with the capture
of juvenile chinook salmon and to a lesser with extent coho
salmon at nearshore stations in the upwelling zone.
Discussion
Understanding the mechanisms underlying the dynamics
of multispecies communities is one of the biggest challenges
in ecology. Most communities contain many interacting spe-
cies, each of which is likely to be affected by multiple biotic
and abiotic factors. In order to effectively characterize a
system, we need to differentiate variability resulting from
both temporal and spatial factors. Our observations took
place during two time periods of about 20 days each and
thus were not synoptic "snapshots" of the system. Indeed,
during our June sampling, conditions changed markedly
from the beginning to the end of the cruise because of the
arrival of an anomalous major southwest storm ( Batch-
elder et al., 2002), which likely completely altered the
hydrography and biology of the system. Thus, short-term
temporal variability may obscure patterns observed over
the spatial scale of our sampling.
The pelagic nekton community sampled during these
cruises was not that different from what had previously
been shown for purse seine and trawling collections off
the coast of Oregon and Washington ( Brodeur and Pearcy,
1986; Emmett and Brodeur, 2000; Brodeur et al., 2003).
The early summer nekton community was dominated by
coastal forage fishes such as smelts and Pacific herring,
but also comprised juveniles of many rockfish, sculpin,
and flatfish species. These winter-spring spawning species
eventually settle out to demersal habitats sometime in
summer (Shenker, 1988; Doyle, 1992), which may in part
explain the paucity of these taxa in the August cruise. In
contrast, the August nekton community consisted of large,
42
Fishery Bulletin 102(1)
highly migratory species such as Pacific sardines, jack
mackerel, and chub mackerel. Pacific sardine, which was
almost completely absent from the system in the 1980s, has
undergone a substantial resurgence and is now one of the
most abundant species off the coast in summer (Brodeur
et al., 2000; Emmett and Brodeur, 2000; McFarlane and
Beamish, 2001). It should be noted, however, that some of
the differences between cruises could be accounted for by
the inclusion of substantially more offshore stations during
A;
aa
REXS
SPSD
cr
A
A
A
3
A
U
STHD t
A
MASO o
WBSM
DBRF
°-,YTRF
D
cP
SABF
A
Temperature
Depth
, Salinityn n
LGCD
- <%
PHER
»*
D
d1
CHIN1
COHO
A
A
*
1
Axisl (r2=0.31)
CO
CO
X
<
B
A
A
* A
*
REXS
A
D
STHD
A
COHOA
A
D
a
coftoj
D
A
a D
-Depth
a Salinity
D
Temperature
CHINO
0
BLSH
OSMJ °
CO
CD
PSAR
CHIN1
O
o
a
o ^OEL
a
°0
CO
o
Axis 2 (r2=0.23)
Figure 8
Nonmetric multidimensional scaling (NMS) ordination
plot of stations and nekton species with environmental
parameters from June (A) and August (B) 2000 GLOBEC
cruises. Station symbols denote: onshore tO>. mid-shelf
!▲). and slope (D) groupings; Species abbreviations denote
the following taxa: CHIN 0 (chinook, age 0), CHIN 1
(chinook, age al.ll, STHD (steelhead trout). SUSM (surf
smelt), PSAU (Pacific saury), WOEL (wolf-eel juvenile),
OSM J (osmerid juvenile), REXS (rex sole, larval i, MEDF
(medusafish ), PSAR (Pacific sardine), .JAMA (jack mack-
erel), CHMA (chub mackerel), NANC (northern anchovy).
BLSH (blue shark).
the second cruise. Our results from the community analy-
ses suggest that juvenile salmon tend to co-occur with each
other and with a variety of other pelagic nekton, including
adult salmon, and that this spatial overlap varies tempo-
rally. Brodeur et al. (2003), in analyzing community struc-
ture based on previous pelagic sampling data off Oregon
and Washington, arrived at similar results. In both studies,
the geographic boundaries of the pelagic assemblages often
overlap and are not as distinct as demersal assemblages.
However, the pelagic environment is much more spatially
and temporally heterogeneous than the demersal environ-
ment, and many of the species examined in our study are
highly mobile and are likely to respond quickly to changing
conditions. Research is presently underway to examine the
trophic interactions among salmonids and with other sym-
patric nekton species in order to determine what ecological
relationships (e.g. predation, competition), if any, are occur-
ring in this system.
From the results of our sampling, we concluded that ju-
venile salmonids, with the possible exception of steelhead,
occupy the cool, high salinity, inshore upwelling regions off
the southern Oregon coast. However, particularly for the
June cruise, many of the coho and chinook salmon juveniles
collected may have recently entered the ocean with little
time to disperse offshore, so that the capture location may
not reflect true habitat preferences. Moreover, the vertical
dimensions of our trawl also precluded us from sampling
the nearshore, subtidal regions where some subyearling
chinook may reside shortly after entering the ocean.
Salmon and steelhead differed considerably in stock com-
position. The pattern for coho salmon was similar to that
of chinook salmon in that fish from sources both north and
south of Cape Blanco contributed to our catches. However,
steelhead from rivers north of Cape Blanco were absent,
presumably having migrated offshore and north shortly
after entering the sea, as shown by Pearcy et al. (1990).
Although our stock composition estimates for steelhead
should be viewed with caution because of an incomplete ge-
netic baseline and a relatively small number of samples, our
findings support Pearcy et al.'s suggestion that steelhead
from rivers south of Cape Blanco have a unique marine
distribution and reside throughout the summer in the up-
welling zone off northern California and southern Oregon.
Our study revealed seasonal shifts in the abundance and
stock composition of juvenile salmonids. Although salmo-
nids comprised small portions of the vertebrate catches of
both the June and August cruises, juvenile chinook salmon,
coho salmon, and steelhead were much more abundant
later in the summer, likely indicating that fish moving
into our study area are from shoreline or riverine habitats.
The greater abundance of chinook salmon in late summer
can be explained in part by the northern migration offish
that originated in rivers south of our study area. Chinook
salmon from the Sacramento and San Joaquin rivers in
California's Central Valley comprised substantial propor-
tions in the August catches both south (20%) and in nth
i 90' i ) of Cape Blanco. In contrast, the few chinook salmon
caught in June were mostly (549r ) from streams that en-
ter the sea immediately north of Cape Blanco such as the
Umpqua, Coquille, Sixes, and Elk rivers. Chinook salmon
Brodeur et al.: Distribution, growth, condition, origin, and associations of juvenile salmonids
43
E
o
•Chinook 1 0
Coho 1 .0
-Habitat
12 14
Water temperature (C)
j ■*"
09 -
~~, r. ..---'
OR -
, *
0
07 -
/ ■"
. ..
06 -
r- '
05 -
r'
04 -
03 ■
- - -Chinook 1 0
02 -
f J"
Coho 1 0
n 1 -
1 V
Habitat
n -
10 15
Chla concentration
1
09
08
07
06
0.5
04
03
0.2
0 1
0
31.50
J i
- - -Chinook 1 0
X '
Coho 1.0
Habitat
Y 1
^ }
# >
,'
4
ja _ _ _ J
3250 3300
Salinity (PSU)
•Chinook 1 0
-Coho 1.0
-Habitat
100 150 200
Water depth (m)
Figure 9
Cumulative distribution curves for salmon and environmental or station variables. Only the August variables that showed at least
one significant difference are included. See Table 8 for results of the statistical tests.
from these rivers are known to primarily migrate north
of our study area along the coast (Nicholas and Hankin,
1988). By August, fish from these stocks were nearly absent
from our samples. Oregon rivers south of Cape Blanco, an
area that includes the Rogue, Chetco, and Winchuck riv-
ers, produce chinook salmon with a more southerly pattern
of ocean migration (Nicholas and Hankin, 1988; Myers et
al., 1998). Chinook salmon from these rivers were found
throughout the summer and contributed 53% to our largest
catches of chinook salmon along transects south of Cape
Blanco in August.
Results from our 2000 GLOBEC cruises identified Cape
Blanco as an important breakpoint in salmonid life-his-
tory variation. Stock distributions of both juvenile salmon
and steelhead indicated that different migration patterns
of fish originating from southern and northern rivers are
evident during their early marine phase. Our August sur-
vey also revealed sharp contrasts in life-history type and
freshwater origin between the juvenile chinook salmon
population in the marine area north of Cape Blanco and
that to the south. Chinook salmon captured north of Cape
Blanco were nearly all yearlings and largely from the Sac-
ramento River drainage. Subyearlings predominated in our
catches south of Cape Blanco and included a much larger
proportion offish from coastal streams in southern Oregon
and northern California.
Comparisons of our results with similar studies conduct-
ed further north show differences in salmonid migrations
on a somewhat broader geographic scale. In several years of
sampling during the summers of 1981 through 1985 off the
central Oregon to northern Washington coast, most juvenile
chinook salmon bearing CWTs were from Columbia River
hatcheries (Pearcy and Fisher, 1990; Fisher and Pearcy,
1995). Only one tagged chinook salmon from a river south
of Cape Blanco (Klamath River) was captured. Pearcy and
Fisher also found that juvenile coho salmon were largely
from the Columbia River and that smaller contributions
were from coastal rivers north of Cape Blanco. Their find-
ings have been corroborated by more recent surveys in the
same region (Emmett and Brodeur, 2000) using genetic
44
Fishery Bulletin 102(1)
data (Teel et al., 2003). Samples from subsequent cruises
will be used to examine the persistence of such fine- and
broad-scale geographic structure in the juvenile migrations
of salmonid stocks.
A major source of error in our estimates of growth rates
of juvenile coho salmon back-calculated from scales was
uncertainty of when individual fish entered the ocean. We
used a single date of ocean entry for all fish (15 May), but
individual fish, of course, entered the ocean at different
times over the course of a month or more. Consequently,
coefficients of variation were relatively large (84—119% and
75-120% of mean growth rate in FL and weight, respec-
tively) for fish caught in May and June, when errors in es-
timated growth periods likely were large in relation to the
actual growth periods. Conversely, coefficients of variation
were relatively small ( 14-30% and 10-26% of growth rate
in FL and weight, respectively) for fish caught in August or
September, when errors in estimated growth periods likely
were small in relation to the actual growth periods. (Note
the decrease in standard deviation of mean growth rates
with month of capture in Tables 3 and 4A). Growth rates
of CWT coho salmon between hatchery release and capture
in the ocean (Table 4B) were very similar to the growth
rates of unmarked salmon estimated from scales for the
same months and areas. In addition, the growth rates of
the former group ( CWT coho salmon ) helped to validate the
growth rates of the latter group (Table 4A).
Significant differences in growth and condition of ju-
venile coho salmon indicate that different oceanographic
environments exist north and south of Cape Blanco. The
length of the fish indicated that substantial growth oc-
curred in juvenile coho salmon during the study period. As-
sessment of other growth features (condition) revealed that
juvenile coho salmon grew better north of Cape Blanco.
Because we included measurement of condition in both the
June and August period in the evaluation, changes in stock
composition, described earlier, may be partly responsible
for this observation. Although genetic stock composition
was different between months, month of sampling was not
a significant factor, suggesting that stock composition is
not likely a significant factor affecting the difference in
condition (a performance metric) of juvenile salmon north
and south of Cape Blanco.
Several lines of evidence further support the hypothesis
that areas north of Cape Blanco benefit juvenile yearling
chinook and coho salmon. There were greater numbers of
juvenile yearling chinook and coho salmon to the north of
Cape Blanco. Although our overall sampling effort was
greater north of Cape Blanco, in the mesoscale portion of
our survey designed to assess general distribution patterns,
more yearling chinook and coho salmon were captured
north of Cape Blanco. Secondly, when we evaluated the
growth rate of juvenile coho salmon in the GLOBEC region
compared to juveniles captured off northern Oregon and
Washington, juveniles from the GLOBEC region grew much
better. The similar tracking of resource (distribution and
abundance) and performance (measured in terms of either
somatic and energetic growth or growth rate) metrics for
juvenile yearling chinook salmon and coho salmon ninth
of Cape Blanco suggests that habitat quality in this region
was better. The results of this study help define the biogeo-
graphical zones for salmon growth and establish regional-
based management strategies for depleted salmon stocks.
Acknowledgments
We thank the captain and crew of the FV Sea Eagle for their
expert help in conducting the trawling operations under
sometimes adverse weather conditions. We are grateful
to Jackie Popp-Noskov, Paul Bentley, Marcia House, and
Becky Baldwin for assistance in field sampling. Donald
Van Doornik and David Kuligowski collected the genetic
data. We thank Anne Marshall for the use of unpublished
chinook salmon allele frequency data. Stephen Smith
and Alex De Robertis helped with the statistical analy-
sis. Earlier versions of this manuscript were improved
by the helpful comments of two anonymous journal
reviewers. Research was conducted as part of the
U.S. GLOBEC program and was jointly funded by the
National Science Foundation (Grant no. OCE-0002855)
and the National Oceanic and Atmospheric Administra-
tion (NOAA). We also acknowledge the Bonneville Power
Administration for funding the plume study.
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Appendix
Table 1
Summary of releases of coho salmon smolts in 2000 by region. This summary of releases of all hatchery coho salmon smolts
by region was calculated from data in the Pacific States Marine Fisheries Commission Regional Mark Information System
(http://www.rmis.org/ [accessed 5 April 2003]) and in USFWS 2001 (see Footnote 2 in the general text).
No. of release
groups
ToHl fish
Release
weight (gl
released
Marked
mean I SD )
All British Columbia
250
13,612,715
71.4',
19.6(5.7)
Washington: St. Juan de Fuca, Puget Sound, Skagit River,
Nooksack River, etc.
83
15,316,299
86 r,
29.1 (19.7)
Washington:
North of Columbia River to Cape Flattery
63
7,630,257
76 7',
31.6(5.3)
Columbia River
140
29,879,137
89.09i
32.0^ 1
Oregon Coast north of Cape Blanco
14
809,962
95.69!
41.6(7.41
Southern Oregon and Northern California: Rogue, Klamath,
and Trinity Rivers
5
745.060
99.8^'
42.1 (4.4)
' 100% of the fish released from Klamath and Trinity Rivers were clipped on the maxillary.
47
Abstract— Between June 1995 and May
1996 seven rookeries in the Gulf of Cali-
fornia were visited four times in order
to collect scat samples for studying spa-
tial and seasonal variability California
sea lion prey. The rookeries studied
were San Pedro Martir, San Esteban.
El Rasito, Los Machos, Los Cantiles.
Isla Granito, and Isla Lobos. The 1273
scat samples collected yielded 4995
otoliths (95.3%) and 247 (4.7%) cepha-
lopod beaks. Fish were found in 97.4%
of scat samples collected, cephalopods
in 11.2%, and crustaceans in 12.7%. We
identified 92 prey taxa to the species
level, 11 to genus level, and 10 to family
level, of which the most important were
Pacific cutlassfish (Trichiuruslepturus),
Pacific sardine (Sardinops caeruleus),
plainfin midshipman (Porichthys spp. ),
myctophid no. 1, northern anchovy
(Engraulis mordax). Pacific mackerel
(Scomber- japonicus), anchoveta (Ceten-
graulis mysticetus), and jack mackerel
(Trachurus symmetricus). Significant
differences were found among rooker-
ies in the occurrence of all main prey
(P<0.04), except for myctophid no. 1
(P>0.05). Temporally, significant dif-
ferences were found in the occurrence
of Pacific cutlassfish, Pacific sardine,
plainfin midshipman, northern an-
chovy, and Pacific mackerel (P<0.05).
but not in jack mackerel lx2=2.94, df=3,
P=0.40 1, myctophid no. l(;r= 1.67, df= 3,
P=0.64 ), or lanternfishes ( x2=2.08, df=3,
P=0.56). Differences were observed in
the diet and in trophic diversity among
seasons and rookeries. More evident
was the variation in diet in relation to
availability of Pacific sardine.
Spatial and temporal variation in the diet
of the California sea lion (Zalophus californianus)
in the Gulf of California, Mexico
Francisco J. Garcia-Rodriguez
David Aurioles-Gamboa
Centra Interdisciplinary de Ciencias Mannas-lnstituto Politecnico Nacional
Departamento de Biologia Manna y Pesquerias
Apdo. Postal 592
La Paz, Ba|a California Sur, Mexico
E-mail address (for F J. Garcia-Rodriguez) fjgrodriifflcibnor.mx
Manuscript approved for publication
9 October 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:47-62 (2004).
The population of the California sea
lion (Zalophus californianus), in the
Gulf of California numbers approxi-
mately 23,000 individuals, 82% of
which inhabit the northern region of
the gulf above latitude 28° (Aurioles-
Gamboa and Zavala-Gonzalez, 1994).
In this region are found the most
important reproductive areas and the
highest pup production of the Gulf.
Aurioles-Gamboa and Zavala-Gonzalez
(1994) suggested that the high con-
centration of animals in this region is
related to high abundance of pelagic
fish such as Pacific sardine (Sardinops
caeruleus) (also known as South Ameri-
can pilchard, FAO), Pacific mackerel
(Scomber japonicus). Pacific thread
herring (Opisthonema libertate), and
anchoveta (Cetengraulis mysticetus)
(Cisneros-Mata et al., 19871; Cisneros-
Mata et al., 19912; Cisneros-Mata et al.,
19973).
Despite the importance of the north-
ern gulf region, feeding studies of the
California sea lion at Gulf of California
rookeries have been few and have been
conducted at different time periods.
Researchers have studied sea lion diet
in Los Islotes (Aurioles-Gamboa et al.,
1984; Garcia-Rodriguez, 1995), Los
Cantiles (Isla Angel de la Guarda), Isla
Granito (Sanchez-Arias, 1992; Bautista-
Vega, 2000), and Isla Racito (Orta-Davi-
la, 1988). These studies have shown that
sea lions consume a variety of prey and
that differences exist between the diet
of sea lions found at different rookeries
within the Gulf of California. At Los
Islotes, the most important prey were
cusk eel (Aulopus bajacali), bigeye bass
(Pronotogrammus eos), threadfin bass
(Pronotogrammus multifasciatus), and
splitail bass (Hemanthias sp.) (Aurioles-
Gamboa et al, 1984; Garcia-Rodriguez.
1995). At Los Cantiles and Isla Granito
important prey were lanternfish (Dia-
phus sp.), northern anchovy (Engraulis
mordax). Pacific cutlassfish (Trichiurus
nitens), shoulderspot (Caelorinchus
scaphopsis), and Pacific whiting (Mer-
luccius productus) (Sanchez-Arias,
1992; Bautista-Vega, 2000), whereas at
Isla Racito, important prey were Pacific
sardine (Sardinops caeruleus). Pacific
mackerel (Scomber japonicus), grunt
(Haemulopsis spp.), rockfish (Sebastes
1 Cisneros-Mata, M. A.. J. P. Santos-Molina,
J. A. DeAnda M.,A. Sanchez-Palafox, and J.
J. Estrada. 1987. Pesqueria de sardina
en el noroeste de Mexico ( 1985/86 ). Informe
Tecnico, 79 p. Centro Regional de Inves-
tigaciones Pesqueras de Guaymas. INP.
SEPESCA. Calle 20 No. 605 Sur Col. La
Cantera. Guaymas, Son. CP. 85400.
2 Cisneros-Mata, M. A., M. O. Nevarez-
Martinez, G. Montemayor-Lopez, J.
P. Santos-Molina, and R. Morales-
Azpeitia. 1991. Pesqueria de sardina en
el Golfo de California de 1988/89-1989/90.
Informe Tecnico. 80 p. Centro Regional de
Investigaciones Pesqueras de Guaymas.
INP. SEPESCA. Calle 20 No. 605 Sur Col.
La Cantera. Guaymas, Son. CP. 85400.
3 Cisneros-Mata, M. A., M. O. Nevarez-
Martinez, M. A. Martinez-Zavala, M. L.
Anguiano-Carranza, J. P. Santos-Molina,
A. R. Godinez-Cota, and G. Montemayor-
Lopez. 1997. Diagnosis de la pesqueria
de pelagicos menores del Golfo de Califor-
nia de 1991/92 a 1995/96. Informe Tecnico,
59 p. Centro Regional de Investigaciones
Pesqueras de Guaymas. INP. SEMARNAP.
Calle 20 No. 605 Sur Col. La Cantera.
Guavmas, Son. CP. 85400.
48
Fishery Bulletin 102(1)
spp. ), and Pacific whiting (Merluccius spp. )
(Orta-Davila, 1988).
Some California sea lion prey are important
fisheries resources in Mexico. The Pacific sar-
dine, for example, is the target of a fishery be-
gun in 1967 and which, along with the northern
anchovy, contributed to most of the volume of
the catch (200,870 t during the 1995-96 season)
obtained in the Gulf (Cisneros-Mata et al.3).
The central and northern regions of the Gulf
of California harbor the greatest abundance of
sea lions and schooling fishes, such as the sar-
dine and anchovy. Because of this, knowledge of
sea lion feeding habits and their temporal and
spatial variability is relevant to understanding
the potential interaction between sea lions and
fisheries in the area (Orta-Davila, 1988; San-
chez-Arias, 1992; Bautista-Vega, 2000).
In this article, we present the results of
concurrent diet studies conducted at various
rookeries and haulout areas of sea lions in the
northern rookeries of the Gulf of California to
examine the prey consumed, and spatial and
temporal variability in their diet.
Materials and methods
32°
28°
24°
20°
16°
12°
Scat samples of California sea lions were
collected at Isla San Pedro Martir (SPM,
28°24'00"N, 112°25'3"W), Isla San Esteban
(EST, 28°42'00"N, 112°36'00"W), Isla Rasito
(RAS, 28°49'30"N, 112°59'30"W), Isla Granito
(GRA, 29°34'30"N, 113°32'15"W), Isla Lobos
(LOB, 30°02'30"N, 114°. 28'30"W), and at two
colonies of Isla Angel de la Guarda known as
Los Machos (MAC, 29°20'00"N, 113°30'00"W),
and Los Cantiles (CAN, 29°32'00"N, 113°29'00"W, Fig. 1).
The total number of California sea lions in these seven
rookeries was approximately 15,000 animals (that were
hauled out) of which about 12.2% inhabit San Pedro Martir.
34.7% San Esteban, 2.8% El Rasito, 10.0% Los Machos,
8.7%. Los Cantiles, 11.0% Isla Granito, and 20.6% Isla
Lobos (Aurioles-Gamboa and Zavala-Gonzalez, 1994). All
the animals were spread out along the shoreline of each
island, except at Isla Angel de la Guarda, where they were
clustered within two areas: Los Cantiles, on the eastern
shoreline and Los Machos on the western shoreline.
Scat samples were obtained at reproductive and non-
reproductive haulout areas between June 1995 and May
1996. At El Rasito, sampling was done only at one reproduc-
tive area; fresh and dried samples were collected (Fig. 2).
If for any reason a scat was not collected (because it was
found in pieces or in poor condition), it was destroyed and
the site was cleared to avoid collection during subsequent
trips. All fresh and dried samples collected were pooled to
represent each sampling period. We assumed that the diet
information corresponded to a time period close to the col-
lection trip, but some dried scats could have been deposited
shortly after the last collection.
Pacific
Ocean
122°
118°
114°
110°
106°
Figure 1
Map of Baja California showing location of California sea lion rook-
eries that were studied in the Gulf of California.
Scats were stored in plastic bottles and then dried
shortly thereafter to prevent decomposition offish otoliths
and other hard parts (which were used in subsequent
prey identification) until the scats could be processed at
a later date. The samples were processed by soaking in
a weak biodegradable detergent solution for 1 to 7 days
before being sifted through nested sieves of 2. 00-, 1.18-.
and 0.5-mm mesh size. Fish bones and scales, eye lenses of
fish and squid, otoliths, cephalopod beaks, and crustacean
fragments were extracted from the samples. Cephalopod
beaks were stored in 70% ethanol, and the other items were
dried and stored in vials. Sagittal otoliths and cephalopod
beaks were used to identify teleost fish and cephalopods, re-
spectively. Identifications were made by using photographs
and diagrams from Clarke (1962), Fitch ( 1966), Fitch and
Brownell (1968), and Wolff (1984), as well as voucher
specimen material from the 1) Center Interdiseiplinario
de Marinas Ciencias (CICIMAR), 2) Instituto Tecnologico
y de Estudios Superiores de Monterrey, Guaymas, 3) Los
Angeles County Museum of Natural History, California,
and 4) Centro de Investigacion Cientifica y de Educacion
Superior de Ensenada (CICESE). Baja California, Mexico.
Prey species identifed to family level were coded by using
Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Zalophus californianus
49
San Pedro Martir (SPM)
28° 24'-
HA
San Esteban (EST)
112°40' 112=38' 1 12=36' 112=34' 112=32'
J L
28=44-
28=42'
El Rasito (RAS)
Angel de la Guarda
28=49'
113=40' 113=30' 113=20' 113=10' 113=00'
I I i i i
29=30'-
r^\ «— Los Cantiles (CAN)
/ (RAyHA)
29° 20'-
A\ ^-.
29° 10-
Los Machos (MAC)\ ^
(RA y HA) ^v \
M
Isla Granito (GRA)
Isla Lobos (LOB)
113'
34'
113° 33'
i
29° 35'-
s RA
RA
ha *\y
29=34'-
30=03'.
114=29'
1
114= 28
I
| RA
K
HA -
Figure 2
Location of sites where samples of California sea lion scats were collected at each island.
RA = reproductive area; HA = haulout area.
the family name plus a sequential number. Otoliths from
prey species that were not identified to species, genus, or
family level were coded with "fish species" plus a number.
Three indices were used to describe the diet of sea lions.
Percent number (PN) represents the percentage of the
number of individuals for each prey taxon over the total
number of individuals found in all scat samples. Percent
of occurrence (PO) represents the percentage of scats hav-
ing a given prey taxon and indicates the percentage of the
population that is consuming a particular prey species. The
third index, index of importance (IIMP) incorporates PN
and PO and is defined as
IIMP,
'T ^
u
X
(1)
where xt = number of individuals of taxon z' in scatj;
X = total number of individuals from all taxa found
in scat J; and
U = total number of samples with prey.
The IIMP, developed for scat analysis (Garcfa-Rodriguez,
1999), was used to determine the importance of prey
species, their spatial and temporal variation in the diet.
50
Fishery Bulletin 102(1)
diversity of prey estimates, and measures of similarity
among rookeries. Crustaceans were not incorporated into
the IIMP index because it was not possible to quantify the
number of individuals in the samples.
We used the IIMP Index because it is less sensitive to
changes in the number of prey in an individual scat com-
pared to PN. For example, if a scat contains a single prey
taxon, the IIMP does not change regardless of the number
of individuals of that taxon, in that scat. However, as one
increases the number of individuals of a given prey taxon
in the scat, the PN will also increase for that prey. The
IIMP allows each scat to contribute an equal amount of
information, whereas PN can be dominated by a few scats
with a large number of a single prey-taxon otoliths. In this
manner the IIMP is similar to the split-sample frequency
of ocurrence (SSFO) index, developed by Olesiuk (1993),
where each scat is treated as a sampling unit and does
not assume, as does PN, that the distribution of prey hard
parts between scats is uniform. However, with the SSFO
index, each prey taxon in a given scat is given an equal
weight for that scat. If only one species occurs in a sample,
its occurrence is scored as 1, if two species occur, each oc-
currence is scored as 0.5, and so forth (Olesiuk, 1993). The
IIMP index incorporates more information than the SSFO
index, regardless of the number of individuals of each taxon
in the scat.4
Percent number (PN) was used only to show differences
between broad prey groups (fishes and cephalopods) and
PO was used to review the temporal and spatial changes
from each main prey (those with average IIMP of at least
10% at any rookery). For all estimations, a single otolith
(right or left) or single cephalopod beak (upper or lower)
represented one individual prey. We tested the hypothesis
that the occurrence of the main prey was independent of
the rookery and of the date collection using contingency
tables and an estimator of chi-square (x~) (Cortes, 1997).
Total length of the otoliths (mm) and the linear
equation obtained by Alvarado-Castillo5 were used to
estimate the length of the Pacific sardine (total length
mm=7. 41+147. 24xotolith length mm); r=0.85, n=2740).
Insufficient data did not allow estimating the size of speci-
mens from May. All estimated lengths were transformed us-
ing loglO, followed by an ANOVA among sampling periods.
The size of Pacific sardine consumed by California sea lion
was compared to those caught in the commercial fishery.
We chose to estimate the size of Pacific sardines because of
the broad information available concerning age and growth
and other aspects about the fishery and because we found
many sardine otoliths in good condition.
Spatial and temporal correlation in composition of diet
was compared by using the Spearman rank correlation co-
4 Garcfa-Rodriguez, F. J., and J. De la Cruz-Agiiero. In prep. An
index to measure the specie prey importance of California sea
lion ^Zalophus californianus) based on scat samples.
'Alvarado-Castillo, R. Unpubl. data. Departamento de
Biologia y Pesquerias, Centro Interdisciplinary de Ciencias
Marinas. Avenida IPN S/N Col. Palo Playa de Santa Rita, La
Paz, Baja California Sur, Mexico 23070.
efficient (Rs) (Fritz. 1974). Pairs of IIMP values were used
for each prey taxon in a pair of sampling events (rookeries
or sampling dates) to examine the correlation among them.
This analysis was limited to prey that had an IIMP value
of 10% or more. Cluster analysis of average IIMP data for
the seven rookeries was used to assess the similarity of
the diet among rookeries. The dendrogram for the cluster
analysis was based on relative Euclidean distances and
unweighted pair-grouping methods (UPGMA) strategy
(Ludwig and Reynolds, 1988). We included only prey that,
for at least one occasion, had IIMP values >10%.
Trophic diversity was evaluated by using diversity curves
(Hurtubia, 1973) developed from IIMP index data. For each
date and colony, the cumulative diversity was calculated for
increasing numbers of sequentially numbered (but we as-
sumed randomly deposited and collected) scat samples. The
diversity curves also allowed us to evaluate sample size
(Hurtubia, 1973; Hoffman. 1978; Magurran, 1988, Cortes,
1997) by identifying the point at which the curve flattens.
The diversity was estimated by using the Shannon index:
H'
-^P,\nPr
(2)
where H' = trophic diversity;
S = total number of prey taxa; and
Pl = IIMPr and represents the relative abundance
of taxon i obtained from each scat and pooled
from scat 1 up to the total number of scats
collected.
The values of trophic diversity were then plotted against
the number of pooled scats.
Results
Identification of prey
The 1273 scat samples collected during June 1995 through
May 1996 (Table 1) yielded fish remains in 97.4% of the
samples, cephalopod remains in 11.2%, and crustacean
remains in 12.7%. Fish and cephalopods represented
95.39; and 4.7%, respectively, of the 5242 individual prey
(excluding crustaceans). The occurrence and number
of these prey groups changed temporally and spatially
(Fig. 3). We identified 92 prey taxa to the species level, 11
to the genus level, and 10 to family level from 851 scats
(Table 2). Remaining scats had damaged prey structures
in a condition that prevented us from identifying species
to the genus or family level.
We found nine main prey with IIMP average values a 10%
(Table 3): the Pacific cutlassfish {THchiurus lepturus), the
Pacific sardine (Sardinops eaeruleus), the plainfin mid-
shipman (Porichthys spp.), myctophid no. 1, the northern
anchovy iEngraulis mordax), Pacific mackerel {Scomber
japonicus), the anchoveta (Cetengraulis mysticetus), jack
mackerel iTrachurus symmetricus), and the lanternfish
(unid. myctophid).
Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Zalophus californianus
51
Table 1
Number of scats collected at each rookery for each sampling period.
June 1995
San Pedro Martir (SPM)
SanEsteban(EST)
ElRasito(RAS)
Los Cantiles (CAN)
IslaGranito(GRAl
Los Machos (MAC)
IslaLobos(LOB)
Total
22
50
11
20
24
39
72
238
September 1995
January 1996
33
66
56
58
20
32
139
404
91
58
47
41
36
72
433
Mav 1996
29
67
25
35
19
0
23
198
Total
172
274
150
160
104
107
306
1273
Spatial and temporal variability of the main prey
The importance (IIMP) of the Pacific cutlassfish was
greater in Los Cantiles (28.4%), Isla Lobos (20.8%), and
Isla Granito (48.5%) than at other sites (Fig. 4). The Pacific
sardine was the dominant prey at Los Machos and to the
south. There was a significant correlation across the sea-
sons between Los Machos and El Rasito (r=0.998. P=0.04),
but not between Los Machos and Isla Granito U-0.602,
P=0.59). The IIMP of sardine was also correlated between
El Rasito and San Esteban (r=0.95, P=0.04). The plainfin
midshipman did not show a clear pattern, but its presence
in the diet increased northeastward from Isla Angel de la
Guarda. Lanternfishes, especially myctophid no. 1, were
the dominant prey at San Pedro Martir, San Esteban, and
El Rasito. The presence of Pacific mackerel was positively
correlated with the presence of the Pacific sardine. The
anchoveta was only found at Isla Lobos, and jack mackerel
at El Rasito, San Pedro Martir, and Isla Granito.
The changes in the PO of the main prey coincided with
the variations of the IIMP. The occurrence of Pacific cut-
lassfish. Pacific sardine, plainfin midshipman, northern
anchovy, Pacific mackerel, and jack mackerel was signifi-
cantly different (P<0.04) among rookeries. Myctophid no.
1 showed no significant difference in ocurrence <x2=11.04,
df=6, P=0.09); but when all lanternfishes were pooled,
their occurrence among rookeries was significantly differ-
ent (x2=H.13,df=6,P=0.04). We found significant temporal
differences in the occurrence of Pacific cutlassfish. Pacific
sardine, plainfin midshipman, northern anchovy, and Pa-
cific mackerel (P<0.05), but no significant differences were
found among seasons in the occurrence of jack mackerel
(*2=2.94, df=3, P=0.40), myctophid no. 1 <x2=1.67, df=3,
P=0.6428), or lanternfish <x2=2.08, df=3,P=0.5562).
Size of Pacific sardine consumed by sea lions
The estimated size of the Pacific sardine found in scat
was between 101.8 mm and 179.7 mm (mean length of
150.4 mm ±13.7 mm). Significant differences were found
among sampling periods (P=4. 79, df=2, P=0. 01 ), specifically
between June and January (Newman-Keuls test; P=0.04)
and between September and January (Newman-Keuls test;
P=0.01). The average size was 147.4 mm (±16.1 mm) in
June, 151.7 mm (±13.0 mm) in September, and 136.5 mm
( ±13.7 mm ) in January ( Fig. 5 ). A similar pattern was found
in Los Cantiles, Los Machos, and Isla Granito.
Spatial and temporal correlation in diet
We identified 25 prey taxa that had an IIMP index value
of >10% (Table 3) for a given collection. The Spearman
rank correlation coefficient of IIMP between any pair of
rookeries during June, September, January, and May was
not significant (P>0.08). There was no positive correla-
tion among any pair of sampling periods for any rookery
(P>0.14), except between January and May at San Pedro
Martir (Ps=0.64, P<0.05) and El Rasito (Ps=0.66, P<0.05)
and between January and June as well as between Janu-
ary and May at Isla Lobos (Rs=0.56, P=0.05; and Ps=0.59,
P=0.05. respectively).
The similarity in diet was related to the distance between
rookeries. A clustering for the seven rookeries was obtained
from these 25 prey taxa (Fig 6). We arbitrarily used a "cut-
off" distance of 0.3 and 0.4 on the dendrogram as reference
points for identifying clusters. The group obtained by us-
ing the first distance (0.3) showed four feeding areas: one
located in the south ( area I; San Pedro Martir, San Esteban,
and El Rasito), another in Canal de Ballenas (area II: Los
Machos) and two in the north (area III: Los Cantiles and
Isla Lobos; and area IV: Isla Granito). When the second
distance (0.4) was used, the seven rookeries grouped into
two clusters: 1) the southern region and Canal de Ballenas,
and 2) the region north of Angel de la Guarda.
Spatial and temporal variability in trophic diversity
Temporal variability in trophic diversity was evident
between the rookeries (Fig. 7). In general, two patterns
could be differentiated: one in which the diversity varied
little throughout the year and the other in which diversity
was high in January and low in September. The rookeries
San Pedro Martir and Isla Lobos showed the first pattern
and Los Machos and Isla Granito (and to a lesser extent,
San Esteban and El Rasito) showed the second pattern. In
September, when diversity was low, the dominant prey at
52
Fishery Bulletin 102(1)
100
80
60
40
20
0
100 T
80
60
40
20
0.-
Percent number
D Fishes ■ Cephalopods
JUNE 1995- MAY 1996
SPM EST RAS MAC CAN GRA LOB
□ Fishes ■ Cephalopods
JUNE 1995
100
80
60
40
20
0
100
80
60
40
20
0
100
80
60
40 ■
20
0
SPM EST RAS MAC CAN GRA LOB
■ Fishes ■ Cephalopods
SEPTEMBER 1995
SPM EST RAS MAC CAN GRA LOB
□ Fishes ■ Cephalopods
JANUARY 1996
SPM EST RAS MAC CAN GRA LOB
□ Fishes ■ Cephalopods
MAY 1996
SPM EST RAS MAC CAN GRA LOB
100
80 1
60
40 1
20
0
100'
80
60
40'
20'
0.
Percent occurrence
Q Fishes ■ Cephalopods □ Crustaceans
JUNE 1995- MAY 1996
M
XI
Jl
SPM EST RAS MAC CAN GRA LOB
□ Fishes ■ Cephalopods □ Crustaceans
JUNE 1995
n
n
^3*.
SPM EST RAS MAC CAN GRA LOB
□ Fishes ■ Cephalopods D Crustaceans
SEPTEMBER 1995
n Jl n
100,
80
60 1
40 1
20
0
SPM EST RAS MAC CAN GRA LOB
O Fishes H Cephalopods D Crustaceans
JANUARY 1996
SPM EST RAS MAC CAN GRA LOB
D Fishes I Cephalopods D Crustaceans
MAY 1996
n^Q
SPM EST RAS MAC CAN GRA LOB
Figure 3
Percent number (PNi and percent occurrence (POl index values for fishes, cephalopods, and crustaceans found in
samples of California sea lion scats collected at seven rookeries in the Gulf of California, Mexico, for all sampling
periods combined and for each sampling period.
San Esteban, El Rasito, and Los Machos was Pacific sar-
dine, whereas at Isla Granito, it was Pacific cutlassfish
(Fig. 4 1. The curves obtained for Los Cantiles showed a
clear pattern of diversity only in September, although the
trend in the January curve would suggest a higher diver-
sity in January than in September.
Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Zalophus califomianus
53
Table 2
Prey of California sea lion
identified from scat samples
collected at Isla San Pedro Martir,
Isla San Esteban, Isla El Rasito, Los
Cantiles, Isla Granito, Los Machos and Isla Lobos from June 1995 through May 1996. n ind. =
= number of individuals in
the sample;
PN = percent number; n occurr = number of occurrences
PO = percentage
of occurrence; IIMP = index of
importance.
Scientific name
Common name
n Ind.
PN
n Occurr.
PO
IIMP
Trichiurus lepturus
Pacific cutlassfish
306
5.837
128
15.041
16.392
Sardinops caeruleus
Pacific sardine
358
6.829
88
10.341
10.020
Porichthys spp.
midshipman
456
8.699
95
11.163
9.297
Myctophid no. 1
lanternfish
714
13.621
119
13.984
7.901
Engraulis mordax
northern anchovy
430
8.203
43
5.053
5.199
Scomber japonicus
Pacific mackerel
103
1.965
42
4.935
3.403
Cetengraulis mysticetus
anchoveta
410
7.821
15
1.763
2.404
Loliolopsis diomedeae
squid
77
1.469
35
4.113
2.399
Trachurus symmetricus
jack mackerel
111
2.118
41
4.818
2.273
Merluccius spp.
Pacific whiting
55
1.049
25
2.938
2.206
Pontinus spp.
scorpionfish
61
1.164
26
3.055
1.842
Enoploteuthid no. 1
squid
95
1.812
23
2.703
1.754
Caelorinchus scaphopsis
shoulderspot
65
1.240
25
2.938
1.728
Octopus sp. no. 1
octopus
24
0.458
17
1.998
1.614
Sebastes macdonaldi
Mexican rockfish
42
0.801
18
2.115
1.496
Citharichthys sp no. 1
sanddab
120
2.289
23
2.703
1.220
Fish species no. 1
—
49
0.935
25
2.938
1.153
Haemulopsis leuciscus
white grunt
176
3.357
21
2.468
1.093
Peprilus snyderi
salema butterfish
163
3.110
33
3.878
1.025
Prionotus spp.
searobin
12
0.229
9
1.058
0.855
Prionotus stephanophrys
lumptail searobin
53
1.011
14
1.645
0.814
Argentina sialis
Pacific argentine
19
0.362
13
1.528
0.754
Fish species no. 2
—
55
1.049
27
3.173
0.737
Hemanthias peruanus
splittail bass
60
1.145
22
2.585
0.602
Fish species no. 3
—
9
0.172
6
0.705
0.592
Micropogomas ectenes
slender croaker
13
0.248
9
1.058
0.547
Lepophidium spp.
cusk-eel
9
0.172
3
0.353
0.532
Fish species no. 4
—
10
0.191
3
0.353
0.511
Sebastes exsul
buccanner rockfish
15
0.286
10
1.175
0.505
Cranchiid no. 2
Squid
20
0.382
12
1.410
0.501
Haemulon flaviguttatum
yellowspotted grunt
11
0.210
3
0.353
0.468
Sela r cru men oph th aim us
bigeye scad
24
0.458
12
1.410
0.431
Fish species no. 5
—
33
0.630
19
2.233
0.384
Paralabrax sp. no. 1
sea bass
9
0.172
5
0.588
0.373
Synodus sp. no. 3
lizardfish
10
0.191
3
0.353
0.341
Lepophidium prorates
prowspine cusk-eel
5
0.095
4
0.470
0.335
Fish species no. 6
—
9
0.172
5
0.588
0.324
Synodus sp. no. 1
lizardfish
25
0.477
10
1.175
0.324
Octopus sp, no. 2
octopus
8
0.153
7
0.823
0.308
Gonatus berryi
squid
5
0.095
5
0.588
0.274
Mugil cephalus
striped mullet
1
0.019
1
0.118
0.265
Paranthias colonus
Pacific creole-fish
1
0.019
1
0.118
0.265
Batistes polylepis
finescale triggerfish
13
0.248
4
0.470
0.245
Physiculus nematopus
charcoal mora
30
0.572
12
1.410
0.244
Hemanthias spp.
sea bass
9
0.172
6
0.705
0.234
Fish species no. 7
—
10
0.191
8
0.940
0.233
Uroconger varidens
conger eel
8
0.153
5
0.588
0.189
Larimus spp.
drum
8
0.153
6
0.705
0.174
Apogon retrosella
barspot cardinalfish
5
0.095
4
0.470
0.173
Dosidicus gigas
squid
8
0.153
5
0.588
0.171
continued
54
Fishery Bulletin 102(1)
Table 2 (continued)
Scientific name
Common name
n Ind.
PN
n Occurr.
PO
IIMP
Merluccius productus
Pacific whiting
1
0.019
1
0.118
0.167
Fish species no. 8
—
2
0.038
2
0.235
0.159
Synodus sp. no. 2
lizardfish
12
0.229
5
0.588
0.132
Scorpaena sonorae
Sonora scorpionfish
2
0.038
1
0.118
0.130
Eucinostomus spp.
mojarra
13
0.248
5
0.588
0.129
Fish species no. 9
—
3
0.057
3
0.353
0.127
Cynoscion reticulatus
striped weakfish
23
0.439
7
0.823
0.124
Fish species no. 10
—
10
0.191
1
0.118
0.122
Caulolatilus affinis
bighead tilefish
4
0.076
3
0.353
0.114
Paralabrax auroguttatus
goldspotted sand bass
18
0.343
4
0.470
0.110
Fish species no. 11
—
3
0.057
2
0.235
0.102
Cranchiid no. 5
squid
1
0.019
1
0.118
0.097
Bodianus diplotaenia
mexican hogfish
1
0.019
1
0.118
0.087
Prionotus sp. no. 1
searonbin
2
0.038
2
0.235
0.087
Strongylura exilis
California needlefish
1
0.019
1
0.118
0.083
Synodus spp.
lizardfish
6
0114
5
0.588
0.146
Fish species no. 12
—
3
0.057
3
0.353
0.074
Fish species no. 13
—
2
0.038
1
0.118
0.065
Fish species no. 14
—
3
0.057
1
0.118
0.060
Fish species no. 15
—
2
0.038
1
0.118
0.058
Fish species no. 16
2
0.038
2
0.235
0.056
Porichthys sp. 1
midshipman
1
0.019
1
0.118
0.052
Fish species no. 17
—
5
0.095
3
0.353
0.049
Calamus brachysomus
Pacific porgy
5
0.095
2
0.235
0.043
Fish species no. 18
—
1
0.019
1
0.118
0.042
Fish species no. 19
—
5
0.095
2
0.235
0.041
Ophididae no. 1
—
1
0.019
1
0.118
0.040
Fish species no. 20
—
5
0.095
3
0.353
0.039
Sebastes sinesis
blackmouth rockfish
2
0.038
1
0.118
0.039
Symphurus spp.
tonguefish
3
0.057
1
0.118
0.038
Fish species no. 21
—
2
0.038
1
0.118
0.036
Pronotogrammus multifasciatus
threadfin bass
8
0.153
2
0.235
0.029
Fish species no. 22
—
2
0.038
2
0.235
0.027
Fish species no. 23
—
2
0.038
1
0.118
0.021
Orthopristis reddingi
Bronze-striped grunt
16
0.305
1
0.118
0.020
Fish species no. 24
—
2
0.038
1
0.118
0.020
Fish species no. 25
—
1
0.019
1
0.118
0.016
Cranchiidae no. 4
squid
2
0.038
2
0.235
0.014
Fish species no. 26
—
2
0.038
2
0.235
0.014
Histioteuthis heteropsis
squid
0.019
1
0.118
0.014
Scorpaenidae no. 1
—
0.019
1
0.118
0.011
Fish species no. 27
—
0.057
2
0.235
0.011
Fish species no. 28
—
0.019
1
0.118
0.010
Fish species no. 29
—
0.019
1
0.118
0.008
Cranchiidae no. 3
squid
0.019
1
0.118
0.006
Bollmannia spp.
goby
0.019
1
0.118
0.006
Fish species no. 30
—
0.019
1
0.118
0.005
Cranchiidae no. 1
squid
0.019
1
0.118
0.004
Paralabrax maculatofasciatus
spotted sand bass
0.019
1
0.118
0.003
Ophidian scrippsae
basketweave cusk-eel
0.019
1
0.118
0.003
Physiculus spp.
cod. codling, mora
2
0.038
1
0.118
0.003
Ophididae no. 2
—
4
0.076
1
0.118
0.002
Unid. Carangidae
jacks
8
0.153
3
0.353
0.141
continued
Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Za/ophus californianus
55
Table 2 (continued)
Scientific name
Common name
n Ind.
PN
n Occurr.
PO
IIMP
Unid. Engraulidae
anchovies
1
0.019
1
0.118
0.248
Unid. Haemulidae
grunts
13
0.248
11
1.293
0.509
Unid. Labridae
wrasses
1
0.019
1
0.118
0.005
Unid. Mycthophidae
lanternifishes
216
4.121
71
8.343
4.895
Unid. Ophididae
cusk-eel
2
0.038
1
0.118
0.098
Unid. Scianidae
drums
13
0.248
9
1.058
0.643
Unid. Scorpaenidae
scorpionfishes
30
0.572
18
2.115
1.078
Unid. Serranidae
sea bass
13
0.248
6
0.705
0.176
Unid. Triglidae
searobins
1
0.019
1
0.118
0.002
Unid. fishes
39
0.744
16
1.880
1.819
Unid. cephalopod
4
0.076
4
0.470
0.373
Unid. fishes (very
eroded )
381
7.268
231
27.145
Remains of cephalopods
14
1.645
Remains of crustaceans
162
19.036
Discussion
Stomach acids attack otoliths, affecting their size and
number and consequently the estimate of prey occurrence
and importance. Erosion of otoliths during digestion has
been analyzed in studies of pinnipeds in captivity. Bowen
(2000) reviewed nine studies that estimated the propor-
tion of otoliths recovered in scat samples to obtain a
prey-number correction factor (NCF). He found that NCF
is greater than 1.0 because many prey species are not
recovered in the scat samples. Additionally, the erosion
level can be significantly different among prey species
(Bowen, 2000) because of differences in the shape and
microstructure of otoliths. Therefore, estimates of biomass
based on scat analysis should be carefully interpreted
because the consumption of some prey species can be
under- or overestimated. Correction factors are needed
to compensate for differential erosion for the prey species
of each pinniped.
In this study the most important prey of California sea
lions were pelagic fish with small, thin, and fragile otoliths
(Nolf, 1993). The lanternfish also have small otoliths —
perhaps smaller than those of any other prey taxa found
in the scats. Their true importance in California sea lion
feeding may be underestimated because of erosion caused
by stomach acids (Da Silva and Neilson, 1985; Murie and
Lavigne, 1985; Jobling and Breiby, 1986; Jobling, 1987; Toll-
it et al., 1997). Similarly, the presence of cephalopods may
have been underestimated because their jaws are composed
of chitin, which is harder to digest, and frequently are re-
gurgitated (Pitcher, 1980; Hawes, 1983). However, the high
resistence to digestion of cephalopod beaks allows recovery
of them in good shape. Thus they are a good choice to use in
such diet analyses (Lowry and Carretta, 1999).
A numerical index of prey species importance may over-
or underestimate the dominance of prey species in the diet
because it does not consider the weight of the prey. For
IIMP, a numerical index that assumes a similar weight for
all prey species, the true importance of the individual large
prey in the diet can be underestimated and the importance
of individual small prey can be overestimated. This prob-
lem is also present when the PO, PN, and the SSFO index
are used because these are all based only upon the number
and occurrence of otoliths and cephalopods beaks. As when
using PN. and the SSFO, the IIMP does not work for species
that cannot be enumerated, such as crustaceans.
Given the tendencies of the trophic diversity curves, the
sample size was suitable in almost all cases. However, at
San Pedro Martir a few more samples would have been
useful to fully depict the diet. At Los Cantiles, except
during September 1995, the samplings should have been
more intense because the flattened portion of the diversity
curves are not clear. The information, therefore, that comes
from those samples could be biased. However, the number
of scats that we analyzed contained a high percentage of
the consumed species, especially the main prey.
The results of this study indicate that the California
sea lion consumed mainly fish and some crustaceans and
cephalopods. According to the PN index, fish were more
important than cephalopods in the diet of sea lions. In ad-
dition, fish were more frequent (PO) than crustacean and
cephalopods.
Crustaceans were represented in a similar manner in
scats from all rookeries. Cephalopods, however, were more
important at San Pedro Martir and San Esteban, prob-
ably because they are more common towards the southern
gulf. Species of the suborder Oegopsida, which includes
oceanic species (Roper and Young, 1975), were most com-
monly found in scats from these rookeries. Orta-Davila
(1988) and Sanchez-Arias (1992) have also noted the low
consumption of cephalopods at the northern rookeries.
Fish were the most diverse and commonly eaten prey. In
contrast to cephalopods, fish were slightly less important
in the southern region.
The availability and abundance of the various prey
resources influenced the diet of the sea lions in the Gulf
56
Fishery Bulletin 102(1)
Table 3
Prey of California sea lions having IIMP index values alO^ in at leas
t one sampling
period for seven rookeries in the Gulf of Cali-
fornia, Mexico
Blank indicate that species were
not recorded in diet; '
— " means unavailable data.
Prey species
June 1995 September 1995
January 1996
May 1996
Average
San Pedro
Engraulis mordax
29.7
2.1
0.5
8.1
Marti r
myctophid no. 1
29.0
10.5
9.0
20.5
17.3
Porichthys spp.
11.2
2.0
6.8
15.5
8.9
Prionotus stephanophrys
0.6
3.3
3.3
10.9
4.5
enopleoteuthid no.l
27.3
0.8
7.0
Sebastes macdonaldi
10.4
2.6
Haeumulopsis leuciscus
16.7
6.0
5.7
San Esteban
Trichiurus lepturus
24.9
3.4
3.0
7.8
Sardinops caeruleus
10.0
34.1
4.2
12.1
unid. Myctophidae
13.79
3.4
4.3
10.9
8.1
myctophid no. 1
2.8
11.8
8.9
18.8
10.6
enopleoteuthid no. 1
16.9
4.2
Sebastes macdonaldi
2.1
9.7
1.4
3.3
fish species no. 1
1.7
11.0
3.2
El Rasito
Porichthys spp.
26.2
4.0
2.3
8.1
unid. Myctophidae
16.4
1.5
8.1
16.4
10.6
Scomber japonicus
13.8
3.2
3.7
2.5
5.8
Pontinus spp.
11.5
5.1
4.1
10.9
7.9
Octopus sp. no. 1
11.5
2.9
7.7
5.5
myctophid no. 1
6.6
5.1
21.4
6.8
10.0
Sardinops caeruleus
1.6
40.1
0.9
7.3
12.5
Trachurus symmetricus
22.0
5.0
23.4
12.6
Caelorinchus scaphopsis
3.6
13.5
10.5
6.9
Los Machos
Sardinops caeruleus
21.0
64.1
16.8
—
34.0
Scomber japonicus
19.0
10.9
—
10.0
Merluccius spp.
15.4
8.2
—
7.9
Trichiurus lepturus
11.7
5.4
—
5.7
Sebastes macdonaldi
1.8
11.3
—
4.4
Los Cantiles
Porichthys spp.
66.7
15.5
20.6
Trichiurus lepturus
22.2
38.2
53.1
28.4
Engraulis mordax
3.7
0.4
14.3
4.6
myctophid no. 1
17.6
4.8
5.6
Sardinops caeruleus
6.8
19.0
6.5
fish species no. 3
0.9
14.3
3.8
unid. fishes
0.9
19.0
5.0
unid. Scianidae
14.3
3.6
Lepophidium spp.
14.
3.5
Lo/iolopsis diomedcav
21.1
5.3
Isla Granito
Engraulis mordax
49.3
7.8
14.3
Trichiurus lepturus
22.0
70.1
2.0
100.0
48.5
unid. myctophidae
1.7
1.1
12.6
3.9
Sardinops caeruleus
0.9
18.7
4.9
Porichthys spp.
0.5
18.2
4.6
5.8
Citharichthys sp. no. 1
21.7
5.4
Isla Lobos
Cetengraulis mysticetus
32.7
0.1
6.8
27.8
16.9
Trichiurus lepturus
25.2
27.7
15.8
14.3
20.8
Porichthys spp.
9.0
10.3
23.2
35.5
19.5
Loliolopsis diomedeae
4.9
2.2
11.6
3.5
5.6
Peprilus snyderi
23.5
5.2
7.2
Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Zalophus califomianus 57
100
80
60
SPM EST RAS MAC CAN GRA LOB
11111 Ml H
l l i 1 ^_ ^B
Trichiurus lepturus
20
« hJI L^l h^^^m.
I a 5 fe'i a i fell a i fell Si ? fell & i fell & 5 fe'i & i |
n 10 * SI 3 $ t SH to n Sl=5 to t Sin (0 t Sin to n 5 1 => to -> S
100
80
1 1 1 1 1 1
40
20
\_m i ■ J - _« : _ i
Sardinops caeruleus
■7 Q. ;r >- 1 Z Q_ Z >- 1 2 Q. z >- 1 z 0- Z >-'Z 0- Z >;! Z 0- Z >r'Z 0- z ^
3 W * S't W 3 5 ' => co =5 5 ' =^ w> ^ 5I=3 « ^ 5l=i W ^ 5' =5 w -> 5
100,
80
1 I 1 1 1 1
1 I 1 1 I 1
60
40
I ! -
Porichthys spp
20
- | ■ P- ' - ' — ^
iMI;ilil;iill;ili l;l ft i £;5 M 1;5 8l 1
100
80
60
40
20
Myctophidae no. 1
Z Cl Z >'Z 0- Z >"'z Q- Z V'z Q- Z i ' Z CL Z >' Z 0- Z b'z CL Z £
D 111 < <iD UJ < <iD HI < <|D UJ < <|D HI < <|D UJ < <|D Hi < *
=i CO 3 S1 =5 (0 ^ 5't 0) ^ SI=»W ^ S ' =? CO -» S'-> (0 -» S -> CO ->5
CD
C_>
c
a
o
Q.
1
CD
CD
ro
c
100
80
60
40
20
Myctophidae
z cl z >-'z n z v'zcl z v'z cl z >'z 0- z b'z cl z i'z cl z >
i 8 1 1;1 8 1 i;l 8 1 S;i 8 1 I;3 8 1 3;3 8 1 I;r 8 1 i
100
80
60
Scomber japonicus
o
20
__)■
Q_
z o. z v'z 0- z >-'z Q. z bz Q- z i'z Q. z >: ' z 0. z >: ' z Q- z >;
TWn5TU)nS=50)-)S-iV)->S->WnS->W-)S->W-iS
100
80
60
40
20
■ ■_
Engraulis mordax
Z 0. Z >-'z 0- Z >-'z D- z >-'z 0. Z i'z Q- z £ ' Z 0- Z £: Z 0. Z >:
t CO n S =) CO * S ' =j 0) n So CO n S =3 CO n S =5 CO n S =i CO =3 5
100
80
40
20
■ -m
Cetengraulis mysticetus
i & i fell a s s!i a ? si? & s fell a i fell a i fell a ? |
T CO n 5 n CO * S n CO n St » n S n (0 n St 0) n 5 ( => to -, S
100
80
40
20
^_ _L ^_ _L _^ -L
Trachurus symmetricus
Z 0- Z >".Z tL Z >,Z D- Z >-.Z 0- Z >ZtZ 0- Z ^,Z 0- Z £,Z Q- Z 5j
D S tf -t'D QJ < <It 111 rf <>D Ul < <b 11) < <'D Ul < <'3 111 < <
n B n S, => to * S|=i CO t S,=5 to n S,n to t S,=i to n Srn W n S
spm : est : ras : mac : can : GRA : LOB
Figure 4
Index of importance (IIMP) for nine prey species identified from samples of California
at seven rookeries in the Gulf of California, Mexico, during June and September 1995
sea lions scats collected
. and January and May
1996.
of California. The distribution pattern of Pacific sardine
closely agrees with its importance in the sea lions diet.
The Pacific sardine occurred in high concentrations around
Angel de la Guarda and Isla Tiburon during the summer
and along the coast of southern Sonora during the winter,
where spawning occurs (Cisneros-Mata et al.3). Sardines
58
Fishery Bulletin 102(1]
were consumed in the Canal de Ballenas region during
the summer (September), when they are very abundant.
Larger size Pacific sardines were consumed by sea lions
most frequently during the summer when adult sardines
occur more frequently in the Canal de Ballenas. As adult
sardine left Canal de Ballenas ( Cisneros-Mata et al., 1997 ),
the proportion of young individuals in the diet of sea lions
increased. The fish eaten by sea lions were apparently
smaller than those captured by the commercial fisher-
ies. The average estimated size of the sardines consumed
was 150.4 mm, whereas the average size of commercially
caught fish during the 1995-96 season was 162.4 mm (Cis-
neros-Mata et al.3). This 7% difference in size may have
been caused by an underestimation of otolith size because
of digestive erosion ( Jobling and Breiby, 1986). If this is so,
then the size of Pacific sardines consumed by sea lions is
similar to the size of those captured by the fishery.
Isla Lobos was the only rookery where Pacific sardine was
not consumed. This finding differs from those of Cisneros-
Mata et al.3 which show the Pacific sardines present as far
north as Isla Lobos. However, their study period was during
the 1991-92 El Nino episode, whereas our study occurred
during normal oceanographic conditios in 1995-96.
Less is known about the spatial
and temporal availability of other
important prey. As with commercial
captures (Arvizu-Martinez, 1987),
Pacific mackerel occurred together
with Pacific sardine. Similar varia-
tions in occurrence for both species
have been noticed from stomach
content analyses of the giant squid
(Dosidicus gigas) (Ehrhardt, 1991).
Lanternfishes were abundant north
of Isla Angel de la Guarda (Robison,
1972); however they were not im-
portant in the diet of the California
sea lion in this region. Their greater
importance in the diet at southern
rookeries was probably due to the
absence of more preferred prey such
as Pacific sardine, Pacific cutlass-
fish, or anchoveta. The consump-
tion of northern anchovy tended to
be less important towards Canal
de Ballenas, where Pacific sardine
reached its maximum importance. The low spatial overlap
of these two species has also been noted in other studies.
The anchoveta was present only at Isla Lobos. This is
an estuarine-lagoon species, typical of coastal lagoons of
northern Sinaloa and Sonora (Castro-Aguirre et al., 1995).
The presence of this prey in Isla Lobos is possibly due to
the sandy coast (Walker, 1960), which is similar to that of
the Sinaloa-Sonora coast.
The diet of California sea lions differed among rooker-
ies, probably due to differences in feeding sites and prey
availability. Antonelis et al. (1990) studied the foraging
characteristics of the northern fur seal (Callorhinus ur-
sinus) and the California sea lion at San Miguel Island
and found differences between foraging areas among
0.15
200-i
180-
160-
140-
| 120-
•£_ 100-
£ 80-
_J
60-
40-
20-
0
n=121
JUN95 SEP95 JAN95
Figure 5
Size of Pacific sardine iSardinops caeruleus) estimated
from otoliths found in California sea lions scats collected
in Isla San Esteban, El Rasito, Granito, Los Cantiles, and
Los Machos. One standard deviation is indicated from each
mean.
0.2
0.25
0.3
0.35
0.4
0.45
Figure 6
Dendrogram of cluster analysis of seven rookeries determined with Euclidean dis-
tance (computed from the IIMP of the 25 prey that had on at least one occasion a
value >10%) and the UPGMA (unweighted pair-grouping methods) strategy. The
vertical lines represent the points of references to delimit the groups.
species. The northern fur seal was found most frequently
foraging in oceanic water within 72.4 km from the island,
whereas Califorinia sea lions forgaged more often in the
shallower neritic zone, within 54.2 km from the island.
Different foraging distances in California sea lions from
San Miguel Island were found by Melin and DeLong
( 1999). During the nonbreeding season a higher percent-
age of foraging locations occurred at distances less than
100 km, whereas during the breeding season most of the
foraging locations occurred at distances greater than
100 km. These differences are probably due to the in-
creased California sea lion population in San Miguel;
this increase in population forces sea lions to exploit new
areas as a density-dependent response to population
Garcia-Rodriquez and Aurioles-Gamboa: Spatial and temporal variation in the diet of Zalophus californianus
59
SPM
■Jun95
»Sep96
■4 I I I I I I I I I I I I I I I I I I I I I I t I
0 2 4 6 8 10 G M 16 18 2022242628303234 36 384042'!
EST
0 2 4 6 8 10 12
2022 24 26283032 34 36 384042444648 50
RAS
0 2 4 6 8 10 12 14 16 18 202224262830323436384042444648 50
3 50 ■
MAC
3 00 .
* ■ " *
2 50 .
t
„ /
2 00 .
1 50 .
*/ i
-
-
-
Jan
t 00 .
0 50 .
1 t 1
1 1 1 1 1 1 1
* I I l l l l
I I l
■t-f
H-
■h-i
0 2 A 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50
Sample size
CAN
I'l I I I i I i i i I I I I I I I I I i I I I I l l
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50
GRA
I'l i i i i i i i i i i i i i i i i i i i
0246610121416 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50
3 50 -
LOB
3 00 .
2 50 .
_,
_. - -J—v
2 00 .
r v J
C^y
1 50 .
100 .
. A
/•
-
-
-
Jan96
0.50 ■
•_i/v
-
-
May9
/, i
-t-t-
Mill
i i i i i i i
0246810121416 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 40 50
Sample size
Figure 7
Trophic diversity curves for California sea lions determined from scat samples collected at seven rookeries in the Gulf
of California, Mexico. SPM = San Pedro Martir; EST = San Esteban; RAS = Isla Rasito; MAC = Los Machos; CAN =
Los Cantiles; GRA = Isla Granito; LOB = Isla Lobos.
60
Fishery Bulletin 102(1)
growth. Although, these differences could also be due to
variability in the distribution of prey (Melin and DeLong,
1999), as suggested by Antonelis and Fiscus (1980), forag-
ing areas might change with season and annual variations
in prey availability and abundance.
Foraging areas in the Gulf of California could lie closer
to rookeries than those recorded for San Miguel Island sea
lions because the diet was different among rookeries in
spite of the shorter distance between them (54.2 km). At
Los Islotes, Baja California Sur, adult females fed within
20 km of the colony (Duran-Lizarraga. 1998). Kooyman and
Trillmich (1986a, 1986b) reported similar data in sea lion
colonies of the Galapagos Islands. In the northern region of
the Gulf of California, feeding range could be shorter than
that at Los Islotes because of the higher concentration of
food at high nutrient concentrations (phosphate, nitrate,
nitrite, and silicate) in Canal de Ballenas that is associated
with strong tidal mixing (Alvarez-Borrego, 1983).
Four foraging zones were discerned from dietary differ-
ences in sea lions from the seven rookeries studied. Zone
I, which included San Pedro Martir. San Esteban. and El
Rasito, was characterized by the consumption of lantern-
fish; zone II, which included Los Machos was characterized
by the consumption of Pacific sardine and Pacific mackerel;
zone III, which included Isla Granito, by the consumption
of Pacific cutlassfish and the northern anchovy; and zone
IV, Los Cantiles and Isla Lobos, was characterized by the
consumption of the plainfin midshipman and the Pacific
cutlassfish. These four zones may indicate differences in
habits used by sea lions or may indicate different oceano-
graphic conditions exploited by sea lions. The eastern
coast of the Gulf of California displays high photosyn-
thetic pigment concentrations, associated with upwelling
induced by winds from the northwest in the winter. These
conditions may make Canal de Ballenas one of the most
important for the distribution of Pacific sardine during
the summer.
Trophic diversity varied spatially and temporally. San
Pedro Martir and Isla lobos sea lions seem to depend on a
more stable feeding areas compared to sea lions at rook-
eries on Isla Granito and Los Machos, where changes in
diversity of consumed species indicated that sea lions feed
on fewer species during certain times of the year. Similar
results in relation to the changes in diversity were also
noticed in the rookeries of the Channel Islands and Faral-
lon Islands, California (Bailey and Ainley, 1982; Antonelis
et al., 1984; Lowry et al., 1990; Lowry et al., 1991 ). Perhaps
the tendency to have the highest values of diversity and
little seasonal variation at San Pedro Martir is the result
of this rookery being located in a zone of transition between
two biogeographical areas. This geographical position con-
fers greater environmental heterogeneity and greater
ecological diversity (Walker, 1960).
California sea lions in the upper region of the Gulf of
California obtain the main portion of their diet from a
relatively small number of species. The decrease in abun-
dance of any of these food resources can seriously affect the
population, particularly at Isla Granito and Los Machos
because sea lions from these rookeries depend on a few
species.
Acknowledgments
We wish to thank Secretaria de Marina, Armada de Mexico,
for its great support during the field activities, and the
Consejo Nacional de Ciencia y Tecnologia (CONACYT)
for funding this study under grant number 26430-N. The
Secretaria de Medio Ambiente, Recursos Naturales y Pesca
(SEMARNAP) provided permits for field work (DOO.-700-
(2)01104 and DOO.-700(2).-1917). We would like to thank
Robert Lavenberg and Jeff Siegel for allowing us the use
of otoliths from the collection at the Natural Museum His-
tory of Los Angeles County and also Lawrence Barnes for
his logistical support during the stay of first author at Los
Angeles; we also thank Manuel Nava for allowing us the use
of otoliths from the collection in Tecnologico de Monterrey,
Campus Guaymas. We are also grateful to Unai Markaida
for his assistance in prey identification based on the
examination of cephalopods beaks. We thank Mark Lowry
for commenting on an earlier draft of the paper, Norman
Silverberg for reviewing the manuscript in English, and
two anonymous reviewers for their valuable suggestions
and criticism. The first author would like to thank Centro
Interdisciplinario de Ciencias Marinas-IPN for a scholar-
ship (PIFI, Programa Institucional para la Formacion de
Investigadores) assigned for postgraduate studies.
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Orta-Davila, F.
1988. Habitos alimentarios y censos globales del lobo marino
(Zalophus californianus) en el Islote El Racito, Bahia de
las Animas, Baja California. Mexico durante octubre
1986-1987. Tesis de Licenciatura, 59 p. Universidad
Autonoma de Baja California. Ensenada, B.C.
Pitcher, K. W.
1980. Stomach contents and feces as indicators of harbour
seal, Phoca vitulina, foods in the Gulf of Alaska. Fish.
Bull. 78:797-798.
62
Fishery Bulletin 102(1
Robison. B. H.
1972. Distribution of the midwater fishes of the Gulf of
California. Copeia (19721:449-61.
Roper. C. F. E., and R. E. Young.
1975. Vertical distribution of pelagic cephalopods. Smith-
sonian Contribution to Zoology 209(51 1:31.
Sanchez-Arias, M.
1992. Contribucion al conocimiento de los habitos alimen-
tarios del lobo marino de California Zalophus califomianus
en las Islas Angel de la Guarda y Granito, Golfo de Cali-
fornia, Mexico. Tesis de Licenciatura, 63 p. Universidad
Nacional Autonoma de Mexico. Mexico, D.F.
Tollit, D. J., M. J. Steward, P. M. Thompson. G. J. Pierce,
M. B. Santos, and S. Hughes.
1997. Species and size differences in the digestion of oto-
liths and beaks: implications for estimates of pinniped diet
composition. Can. J. Fish. Aquat. Sci. 54:105-119.
Walker, B. W.
1960. The distribution and affinities of the marine fish fauna
of the Gulf of California. System. Zool. 9(3):123-133.
Wolff, G A.
1984. Identification and estimation of size from the beaks of
18 species of cephalopods from the Pacific Ocean. NOAA
Tech. Rep. NMFS 17, 49 p.
63
Abstract— Recruitment of bay anchovy
{Anchoa mitchilli) in Chesapeake is
related to variability in hydrologi-
cal conditions and to abundance and
spatial distribution of spawning stock
biomass (SSB I. Midwater-trawl surveys
conducted for six years, over the entire
320-km length of the bay, provided
information on anchovy SSB, annual
spatial patterns of recruitment, and
their relationships to variability in
the estuarine environment. SSB of
anchovy varied sixfold in 1995-2000;
it alone explained little variability in
young-of-the-year (YOY) recruitment
level in October, which varied ninefold.
Recruitments were low in 1995 and
1996 (47 and 31xl09) but higher in
1997-2000 (100 to 265 xlO9). During
the recruitment process the YOY popu-
lation migrated upbay before a subse-
quent fall-winter downbay migration.
The extent of the downbay migration
by maturing recruits was greatest in
years of high freshwater input to the
bay. Mean dissolved oxygen (DO) was
more important than freshwater input
in controlling distribution of SSB and
shifts in SSB location between April-
May (prespawningl and June-August
(spawning) periods. Recruitments of
bay anchovy were higher when mean
DO was lowest in the downbay region
during the spawning season. It is
hypothesized that anchovy recruit-
ment level is inversely related to mean
DO concentration because low DO is
associated with high plankton produc-
tivity in Chesapeake Bay. Additionally,
low DO conditions may confine most
bay anchovy spawners to the downbay
region, where production of larvae and
juveniles is enhanced. A modified Ricker
stock-recruitment model indicated den-
sity-compensatory recruitment with
respect to SSB and demonstrated the
importance of spring-summer DO levels
and spatial distribution of SSB as con-
trollers of bay anchovy recruitment.
Recruitment and spawning-stock biomass
distribution of bay anchovy (Anchoa mitchilli)
in Chesapeake Bay*
Sukgeun Jung
Edward D. Houde
University of Maryland Center for Environmental Science
Chesapeake Biological Laboratory
1 Williams St., P.O. Box 38
Solomons, Maryland 20688
E-mail address (for S Jung): iung@cbl.umces.edu
Manuscript approved for publication
30 September 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:63-77 (20041.
Recruitment for marine fishes is vari-
able and is regulated or controlled by a
combination of density-dependent and
density-independent processes. It has
been hypothesized that density-inde-
pendent processes dominate from the
egg to larval stages whereas density-
dependent control by predation may be
more important in the juvenile stage
(Sissenwine, 1984; Houde, 1987). Den-
sity-dependent processes may be stock
dependent, regulated by adult abun-
dances, or dependent on abundances of
the early-life stages (Ricker, 1975). In
estuarine systems, where hydrological
conditions (e.g. dissolved oxygen, tem-
perature, and circulation) vary widely,
the roles of density-independent physi-
cal factors on fish recruitments may
be dominant, making it difficult, but
still important, to partition density-
dependent and density-independent
processes, particularly for short-lived
small pelagic fishes such as anchovies
and sardines.
Bay anchovy {Anchoa mitchilli) (En-
graulidae) is a coastal species distrib-
uted broadly in the western Atlantic
from Maine to Mexico. This small fish is
the most abundant and ubiquitous fish
in Chesapeake Bay, the largest estu-
ary on the east coast of North America
(Houde and Zastrow, 1991; Able and
Fahay, 1998). It is not fished, yet there
is evidence that recruitment is variable
(Newberger and Houde, 1995). It feeds
on zooplankton — primarily copepods and
other small Crustacea — and is a major
prey of piscivores, including several eco-
nomically important fishes (Baird and
Ulanowicz, 1989; Luo and Brandt, 1993;
Hartman and Brandt, 1995). Male and
female bay anchovy in Chesapeake Bay
mature at 40^15 mm fork length (44-50
mm total length) at about 10 months
of age, and peak spawning occurs in
July (Zastrow et al.. 1991). Most eggs
are produced by age-1 individuals (Luo
and Musick, 1991; Zastrow et al., 1991).
Bay anchovy may survive to age 3+ and
reach approximately 100 mm length and
5 g wet weight ( Newberger and Houde,
1995; Wang and Houde, 1995).
Newberger and Houde (1995) noted
large differences in annual survey
abundances of bay anchovy that appar-
ently resulted from variability in an-
nual recruitments. In Chesapeake Bay,
abundance, growth, and mortality rates
of bay anchovy eggs and larvae vary
temporally and spatially (Dorsey et
al, 1996; MacGregor and Houde, 1996;
Rilling and Houde, 1999a, 1999b). Indi-
vidual-based models were developed to
test the hypothesis that recruitment of
bay anchovy is determined by variable
growth and mortality during early-life
stages that are regulated by density-de-
pendent processes (Wang et al., 1997;
Cowan et al., 1999; Rose et al„ 1999).
In previous research, there was little
knowledge of levels of spawning stock
biomass or density-independent envi-
ronmental factors that may control re-
cruitment through their effects on spa-
tial and temporal variability in growth
and mortality of prerecruit anchovy.
* Contribution 3696 of the University of
Maryland Center for Environmental Sci-
ence, Chesapeake Biological Laboratory,
Solomons, MD 20688.
64
Fishery Bulletin 102(1)
39°N
38°N
^vt^w
N 37°N
gi
quehanna
Upper
—
Middle
Lower
Atlantic
Ocean
77°W
76°W
Figure 1
Chesapeake Bay and stations sampled by the midwater trawl in the 1995-2000 surveys.
Horizontal lines indicate boundaries of three designated regions.
We evaluated environmental factors, spatial distribution
of spawning stock biomass (SSB), and possible ontogenetic
migrations of prerecruits (Dovel, 1971; Loos and Perry.
1991; Wang and Houde, 1995; Kimura et al, 2000) with
respect to bay anchovy recruitment variability. Our objec-
tives were 1) to estimate annual and regional variability
in bay anchovy recruitment. 2) to evaluate effects of hy-
drological conditions (mainly, freshwater input, and dis-
solved oxygen concentration) on stage-specific distribution,
ontogenetic migration, and recruitment, and 3) to identify
mechanisms and describe patterns or trends in the bay
anchovy recruitment process. Data were obtained in a
six-year, multidisciplinary research program conducted
throughout Chesapeake Bay.
Materials and methods
Study area
Chesapeake Bay is a coastal plain estuary of partially mixed
fresh water and sea water. Its 320-km mainstem varies in
width from about 6 to 50 km (Fig. 1 ). The Bay is shallow;
less than 10' r of its area is >18 m deep and approximately
50' i is <6 m deep. More than 809& of the freshwater entering
the bay is from tributaries on its northern and western sides
(Chesapeake Bay Program1 ). Salinity grades from near-full
seawater at the mouth of the bay to freshwater near its
head. Water temperatures reach 28-30°C in mid summer,
and fall to 1^°C in late winter (Murdy et al, 1997 ). Despite
shallow depth, the bay usually has a strongly developed
pycnocline, and has seasonally strong vertical gradients in
temperature, salinity, and dissolved oxygen.
Surveys
Trawl surveys were conducted three times annually over
the entire bay (April-May, June-August, and October).
1995-2000 (Table l.Fig. 1). Midwater-trawl (MWT) fish col-
lections2 were made on transects in three regions: the lower
bay (37°05'N-37°55'N), middle bay (37°55'N-38°45'N I, and
upper bay (38°45'N-39°25'N). As defined, the lower bay
contains 51% of water volume, the middle bay 32^ .and the
upper bay 17^ (Fig. 1). The number of midwater trawl sta-
Chesapeake Bay Program. 2000. Chesapeake Bay: Introduc-
tion to an ecosystem. U.S. Environmental Protection Agency,
publ. EPA 903-R-00-001. 30 p. EPA. 410 Severn Ave, Suite 109,
Annapolis. MD 21403.
Trophic interactions in estuarine systems, midwater trawl sur-
vey. University of Maryland Center for Environmental Sci-
ence, Chesapeake Biological Laboratory, http://www.ch.esa
peake.org/ ties/mwt laccessed 15 October 20031.
Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli 65
Table 1
Cruise dates, mean
standard errors for
temperatures (°C)
individual cruises.
salinities (psul, and dissolved oxygen (mg/L). ir
years, seasons, and regions of Chesapeake Bay,
tegrated from surface to bottom, and pooled
1995-2000. CV = coefficient of variation for
annual means.
Temperature
SE Salinity
SE
Oxygen SE
Cruise date ( depart
28 Apr 95
ure)
13.88
0.11 15.01
0.42
8.53 0.1.3
23 Jul 95
28.13
0.12 15.48
0.44
6.50 0.14
28 Oct 95
17.26
0.12 17.39
0.45
7.59 0.14
28 Apr 96
13.87
0.10 10.84
0.36
10.21 0.11
17 Jul 96
24.66
0.11 11.80
0.41
7.43 0.13
22 Oct 96
16.10
0.10 11.26
0.36
8.55 0.11
20 Apr 97
10.93
0.13 11.41
0.50
10.01 0.16
11 Jul 97
25.28
0.13 13.59
0.51
7.10 0.16
29 Oct 97
14.64
0.13 18.19
0.51
8.01 0.16
11 Apr 98
12.26
0.12 8.90
0.44
9.95 0.14
04 Aug 98
26.15
0.12 12.89
0.46
7.01 0.15
19 Oct 98
18.60
0.13 16.64
0.49
8.64 0.15
19 Apr 99
11.97
0.13 13.51
0.49
10.04 0.16
26 Jun 99
23.52
0.15 16.02
0.56
5.75 0.18
23 Oct 99
16.30
0.14 17.38
0.53
8.87 0.17
29 Apr 00
12.95
0.17 12.51
0.64
8.98 0.20
25 Jul 00
24.26
0.14 14.06
0.53
5.17 0.17
17 Oct 00
17.89
0.15 16.73
0.56
7.63 0.18
Year
1995
19.76
0.07 15.96
0.25
7.54 0.08
1996
18.21
0.06 11.30
0.22
8.73 0.07
1997
16.95
0.08 14.40
0.29
8.37 0.09
1998
19.00
0.07 12.81
0.27
8.53 0.08
1999
17.26
0.08 15.64
0.30
8.22 0.10
2000
18.36
0.09 14.43
0.33
7.26 0.11
CV
5.8%
12.5%
1.2%
Season
April-May
12.64
0.05 12.03
0.20
9.62 0.06
June-August
25.33
0.05 13.97
0.20
6.49 0.06
October
16.80
0.05 16.27
0.20
8.22 0.06
Region of bay
Lower
18.40
0.04 21.19
0.16
8.15 0.05
Middle
18.33
0.05 14.06
0.19
8.33 0.06
Upper
18.04
0.06 7.02
0.23
7.85 0.07
tions per survey ranged from 24 to 52 (six-year total=597).
Additional baywide surveys (August 1997 and September
1998) and partial surveys (June 1997, July 1998, and July
1999) also provided data (total stations =146).
An 18-m2 mouth-opening midwater trawl (MWT), with
3-mm codend mesh was deployed from the stern of the
37-m research vessel Cape Henlopen. All trawling was
conducted at night. Standardized tows of 20-min dura-
tion were conducted and the trawl was deployed at graded
depth intervals from surface to bottom ( 2 minutes at each
depth interval ) in order to provide a sample of fish from
the entire water column. Fish catches (or subsamples) were
counted, measured (to the nearest 1.0 mm), and weighed
on deck immediately after a tow.
Abundance and biomass of bay anchovy recruits and
spawners
We separated bay anchovy catches into YOY and spawn-
ers based on total length (TL). The minimum length of bay
anchovy retained by the MWT was 21 mm TL, which we
also defined as the minimum TL for recruited YOY bay
66
Fishery Bulletin 102(1)
anchovy. Modal lengths of young-of-the-year (YOY) bay
anchovy cohorts were determined from length-frequency
distributions in MWT catches and a modal analysis (Bhat-
tacharya, 1967; King, 1995). Based on the modal analysis
of summer and fall survey data, the maximum TL of YOY
bay anchovy and, therefore, the minimum TL of spawners,
were estimated (Table 2).
Length-dependent gear selectivity for bay anchovy was
adjusted by comparing catches of the MWT and a 2-m2
Tucker trawl with catches from 707-iim meshes at the
same stations during a September 1998 baywide survey.
The length-specific MWT:Tucker-trawl catch ratios (N^^j/
iVj^catch per unit of effort MWT 4- catch per volume of
water Tucker trawl) for anchovies 21-70 mm TL indicated
that both gears fished with a consistent selectivity for bay
anchovy of 30-48 mm TL, and with a slight decrease in NTT
for 48-70 mm TL. However, the values ofNMWTINTT were
lower by factors of 1-7 for 21-30 mm TL fish, indicating
that small anchovies were collected less efficiently by the
MWT. We concluded that length classes of anchovies >30
mm TL were equally vulnerable to the MWT and those >48
mm TL were less vulnerable to the Tucker trawl. Accord-
ingly, we adjusted MWT catches of ^30 mm TL anchovy
by multiplying them by a weighting factor estimated from
the regression of values of iVMH,T/./V.r7. for 21-30 mm TL
bay anchovy.
( Weighting factor) = -0.59 TL + 19.08, (r2=0.96)
where TL = total length.
The weighting factor equals 1.0 for anchovy >30 mm TL
because MWT selectivity is constant for anchovy >30 mm
TL. To estimate water sampled in a 20-min MWT tow,
and
where D«
dn = nmwt/ vmwt = ( 1/s ' x Nt/Vtt
MWT — ^ x ^-^ MWT TT x TT ♦
bay
N,
MWT
N
77'
the concentration of 31-48 mm TL
anchovy at a station (i.e. number/m3);
the number of 31-48 mm TL bay anchovy
collected per 20-min MWT tow at a station;
VMWT = the effective water volume sampled
by a 20-min MWT tow (m:!);
the number of 3 1-48 mm TL bay anchovy col-
lected by the 2-m- Tucker trawl at the same
station;
vulnerability to the Tucker trawl (s=l if all
bay anchovies in water volume, V^, are col-
lected); and VTT is the volume filtered by the
Tucker trawl (m3) estimated from a flowme-
ter in its mouth.
The mean of AfWHT/./V7T for 30-48 mm TL bay anchovy
during the September 1998 survey indicated that V'WUT =
4961 m\ if 30-48 mm TL bay anchovy did not significantly
avoid the mouth of the 2-m2 Tucker trawl (i.e. s=l). Assum-
ing s=l (i.e. VMVVT=4961 m3), we estimated "relative" bay-
Table 2
Estimated
maximum
total lengths
of young-of-the-year
bay anchov
y (mm
) from Chesapeake Bay,
based on analy-
sis of length-frequency
distributions.
Year
Date
Length (mm)
1995
23 Jul
28 Oct
52
69
1996
17 Jul
22 Oct
57
68
1997
11 Jul
2 Aug
29 Oct
30
56
66
1998
4 Aug
7 Sep
19 Oct
50
62
69
1999
26 Jun
23 Oct
30
65
2000
25 Jul
17 Oct
52
67
wide abundance and biomass of YOY and spawners for the
18 surveys from 1995 to 2000.
To coarsely estimate a typical value of s. "absolute" bay-
wide spawner biomasses in June— August were estimated
for 1995-2000 according to an egg production method
(Parker, 1985; Rilling and Houde, 1999a). Bay anchovy
eggs had been collected in a 1-m2 Tucker trawl during the
same surveys and provided estimates of egg abundance.
The coverage of stations and sampling design for the
Tucker trawl was comparable to that of the MWT, but the
Tucker trawl was deployed during both day and night. We
presumed that all eggs collected between 00:00 and 20:00
h had been spawned near a midnight peak 1 00:00 h) (Za-
strow et al., 1991) and decreased in abundance at a mean
instantaneous mortality (reported for bay anchovy eggs
in Chesapeake Bay as M = 0.066/h; Dorsey et al., 1996).
Based on the estimated number of eggs spawned at 00:00
h for each station, the regional mean weight of individual
spawners (defined by the minimum TL in Table 2) in MWT
catches, and the reported fecundity-weight relationship for
females (Zastrow et al., 1991), we were able to coarsely
estimate "absolute" baywide spawner biomass. We as-
sumed that the spawning fraction of adult females per day-
was essentially 1.0 (i.e. all adult females participated in
spawning, Zastrow et al., 1991) and the fecundity-weight
relationship was constant over years.
Comparison of the baywide estimates of spawner bio-
mass in June-August based on the egg production method
("absolute" biomass) with estimates based on the MWT
catch-per-unit-of-effort ("relative" biomass) indicated that.
on average, for 1995 to 2000, s is equal to 0.20. Therefore,
the mean effective water volume fished by a 20-min MWT
tow was 4961x0.20 = 989 m3.
Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli
67
Because NmvT of bay anchovy was highly variable, even
at stations on the same sampling transect, and a mixed
model (SAS version 6.12, SAS Inst. Inc., Cary, NC) includ-
ing spatial covariance ( variogram ) did not significantly im-
prove precision in annual, seasonal, and regional means or
differences of NMWT, a stratified sampling design ( Steel and
Torrie, 1980), i.e. stratum = region, was adopted. Based on
the mean effective water volume (=sxVMWJ, ), we estimated
regional "absolute" abundance and biomass (number and
wet weight) and related standard errors of the linear com-
bination by regional subvolumes (Samuels, 1989) of bay
anchovy >21 mm TL for all MWT surveys from 1995 to
2000 by multiplying regional mean MWT catch by Vr/989,
where Vr represents the water volume (m3) in each bay
region (Cronin, 1971):
N!olal=(N^Vl+Nn
V,„ + N.
Vj/(sxVMWT)xVlotal
SEN=ScNjVr/n,+V*/nn
+v:?/n„
where Nlotal
v„ vm, vu
SEX
ScN =
baywide absolute abundance;
mean values of NmvT for the lower (1),
middle (m), and upper (u) bay;
bay subvolumes for the lower (1), middle
(m), and upper (u) bay (from Cronin, 1971),
V, = 26.7 x 109 m3, Vm= 16.8 x 109 m3, V„ =
8.7 x 109 m3, V„„„, = V, + Vm + V„ =52.1 x
109 m3;
standard error of Nlolal;
number of midwater trawl stations for the
lower (1), middle (m), and upper (u) bay;
pooled standard deviation of NMWT =
square root of mean squares within
groups in analysis of variance table =
t/< SS, + SSm + SS„ ) / ( n,lMl -3i, where SS,, SSm,
SStl = sum of squares of NMWT for the
lower (1), middle (m), and upper (u) bay,
and "total = nl + nm + nu-
Environmental factors
Depth profiles of temperature, salinity, and dissolved
oxygen ( DO ) concentration were determined from conduc-
tivity-temperature-depth ( CTD ) casts at sampling stations.
DO data were adjusted by calibrating against Winkler
titration data from water samples collected in Niskin bot-
tles deployed with the CTD cast. However, DO data from
the CTD could not be adjusted for the 1999 summer and all
calendar year 2000 cruises because Winkler titrations were
not conducted. To estimate regional means for the water
column, we averaged temperature, salinity, and DO values
by integrating the observed values with respect to depth,
after dividing the water column into "above pycnocline" and
"subpycnocline" layers.
Ontogenetic migration
We analyzed length-frequency distributions along the
south-north axis of the bay (i.e. by latitude) to delineate
possible ontogenetic migrations of YOY and adult bay
anchovy. To parameterize the distribution of YOY and
adult abundance and biomass, we estimated the biomass-
weighted mean latitudes of occurrence for each length class
(3-mm interval).
lb.i = 2_,BkjLk/2jBtl,
where LB , = biomass-weighted mean latitude of a length
class, /;
Lk = latitude of the station, k; and
B = biomass (g, wet weight) per 20-min tow.
We devised a metric to parameterize the location of bay
anchovy SSB. We assumed that the baseline boundary for
SSB distribution during the spring was at the mouth of
the bay (37°00'N). Then, the upbay difference between
biomass-weighted mean latitude of SSB (in decimal units)
in Jun-August and the baseline for SSB during the spring
lAL i was calculated:
SL
biomass-weighted mean latitude of
SSB in June - August
-37.00.
Recruitment model
As an exploratory step, a correlation analysis was under-
taken to examine the relationships between bay anchovy
SSB, migration patterns, and recruitment levels with
respect to regional and depth-layer-specific mean tempera-
ture, mean salinity, mean DO, their gradients, and monthly
mean freshwater flow from the Susquehanna River. Cross-
correlations revealed that SSB migration pattern {AD,
regional mean DO concentrations, and October YOY
recruitment level were closely correlated. Regional mean
DO concentration provided the best fit to YOY recruitment
level in October when baywide SSB also was included as
an explanatory variable in multiple regressions. However,
because there is uncertainty in the uncalibrated DO
measurements in 1999 and 2000. we did not use regional
mean DO in our recruitment model. Instead, we developed
a modified Ricker-type stock-recruitment model (Ricker,
1975) that included AL as an explanatory variable:
Rx = a S exp (-/3j S - /i, AL) + e (modified Ricker model )
where
R,
recruitment level = October YOY abun-
dance in each year ( 1995-2000);
y; a, l\ and p.-, = regression coefficients;
S = estimated baywide SSB (male-i- female) in
metric tons for April-May; and
£ = the error term.
In this model, if AL is held constant, Rs. is maximum at S =
l//3j. Although no abiotic factor was included explicitly in
the model, AL is strongly correlated with regional mean DO
and serves as a proxy for it. For the modified Ricker model,
collinearity, and jackknife influence diagnostic tools were
68
Fishery Bulletin 102(1)
Table 3
Seasonal mean freshwater flow entering Chesapeake
chesbay/RIMP/adaps.html.
Bay ft'
Dm the Susqu
ehanna River ( m3/s ). Data source
: http://va. water.
usgs.gov/
Period
1995
1996
1997
1998
1999
2000
Jan-Mar
1289
2495
1474
2563
1325
1379
Apr-Jun
728
1702
920
1625
791
1627
Jul-Sep
238
768
239
334
294
393
Oct-Dec
923
2230
746
194
642
504
Annual mean
795
1799
845
1179
763
976
applied to evaluate reliability of the regression model
(Belsley et al„ 1980; SAS, 1989).
Results
Environmental factors
Stream flows from the Susquehanna River (Table 3)
varied annually and seasonally. Freshwater stream
flows were higher in 1996 and 1998 than in other
years. Baywide mean values of water temperature,
salinity, and DO concentration, averaged from surface
to bottom, varied annually, seasonally, and regionally
(Table 1 ). Annually, mean temperature was highest in
1995 and lowest in 1997. Mean salinity was highest
in 1995 and lowest in 1996. Mean DO concentration
was highest in 1996 and lowest in 2000. Regionally,
salinity was more variable than temperature and
DO concentration. Seasonally, temperature and DO
concentration were more variable than salinity. Tem-
perature was highest in the June-August period, the
spawning season of bay anchovy. Seasonally, salinity
increased progressively from April-May to October.
Mean DO concentration was consistently lowest in
June-August.
Trends in abundance and recruitment
Estimates of bay anchovy abundance reported in our
study are for the entire mainstem of Chesapeake Bay.
The estimated recruitment levels (baywide abundance
of YOY bay anchovy >30 mm TL in October) varied
ninefold and were low in 1995 and 1996 (47.5 ±16.6
and 30.6 ±8.6xl09 individuals) but much higher in
1997-2000 (99.6 ±12.4 to 264.8 ±32.6xl09). Baywide
estimates of bay anchovy biomass for individuals >30
mm TL increased from April to October in each year
(Table 4). October baywide biomass varied sevenfold
from 27.1 ±5.5 x 103 to 192.9 ±20.4 x 103 tons and was
highest in 1998 and lowest in 1996.
Estimated spawning stock biomass (SSB) in
April-May was lowest in 1995 (3.3 ±1.1 x 103 tons),
and highest in 1997 (20.1 ±5.3 x 103 tons), indicating
sixfold variability. SSB in June-August was lowest
in 1996 (2.4 ±0.2 x 103 tons), and highest in 1997 (21.1
±2.3 x 103 tons). The SSBs in April-May and June-August
did not show any obvious relationship to YOY abundance
(recruitment) in October.
Ontogenetic migration
The length-specific mean locations (latitudes of occur-
rence ) of bay anchovy revealed an apparent ontogenetic
migration. Small juveniles of bay anchovy tended to move
upbay and were located primarily upbay until they were
approximately 45 mm TL, after which they began to move
downbay (Fig. 2). In April-May, age-1 bay anchovy <60 mm
TL, consisting of individuals recruited from the previous
year, varied annually in their mean latitude of occurrence,
whereas large (sage 1, a60 mm TL) bay anchovy had
relatively stable locations near the boundary between the
lower and middle bay regions, centered at latitude 37°40'N
(Fig. 2A). Compared to April-May, age-l+ bay anchovy in
June-August were more variable in their annual mean
locations, but both YOY and adult bay anchovy tended to
occur upbay of latitude 38°00'N, except in year 2000 (Fig.
2B). In 1997 and 1999, when annual mean temperatures
were lowest (Table 1), YOY bay anchovy were too small
to be sampled by the MWT in June-August and are not
represented in Figure 2B. In October, mean latitudes of
occurrence (Fig. 2C) indicated a consistent distribution
pattern and an apparent ontogenetic migration by YOY
anchovy. The most probable explanation for the observed
latitudinal distributions was that small YOY bay anchovy
tended to move upbay initially, but then downbay at about
45 mm TL. Distribution of age-l-t- individuals in October
was variable.
The SSB of bay anchovy (excludes YOY) from 1995 to
2000 was centered near 38°00'N in April-August except
in June-August of 1995 and 1996, when the SSB was
centered farther upbay (Fig. 3A). In 2000, the migration
pattern differed from other years. Spawning bay anchovy
in 2000 were located farther downbay in July than in April
(Fig. 3A). The April-May location of prespawning SSB was
mostly explained by the mean flow of the Susquehanna
River from June of the previous year to February of the
current year (r2=0.94, P=0.0012; Fig. 3B ). But, in June-Au-
gust, the mean location of spawning fish was more strongly
and significantly related to the subpycnocline-layer mean
Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli
69
Table 4
Baywide abundance and biomass
estimates for bay anchovy
>30 mm TL (young-of-the-year
+ adult). SE =
= standard
error.
Year
Period
Abundance I
xlO9)
Biomass
xlO3 metric tons)
Estimate
SE
Estimate
SE
1995
April-May
2.1
0.7
3.3
1.1
June-August
57.8
28.1
32.6
17.5
October
47.5
16.6
51.9
21.0
1996
April-May
4.9
1.1
8.9
2.0
June-August
5.3
1.6
3.7
1.3
October
30.6
8.6
27.1
5.5
1997
April-May
11.8
3.3
20.1
5.3
June-August
9.4
2.3
21.1
5.0
October
99.6
12.4
85.6
10.8
1998
April-May
3.5
0.7
6.1
1.3
June-August
14.4
4.5
17.0
7.9
October
264.8
32.6
192.9
20.4
1999
April-May
6.9
1.4
10.6
2.2
June-August
5.5
1.2
10.6
2.4
October
124.5
28.3
115.3
25.0
2000
April-May
6.2
4.1
13.0
6.6
June-August
144.6
51.2
56.0
17.0
October
169.1
43.7
152.9
40.0
DO during that same period in the middle bay (/•-=(). 75,
P=0.02;Fig. 3C).
Correlations
Correlation analyses suggested that regional mean DO
concentrations are the most important environmental
correlate associated with spatial distribution of SSB and
recruitment processes of bay anchovy. The mean locations
(latitudes of occurrence), abundances, and biomasses for
YOY and adult bay anchovy were analyzed with respect
to environmental variables (Table 5). Recruitment levels
(YOY abundance) in October were consistently inversely
correlated with DO concentrations in the lower and
middle bay in June-August (/-=-0.13 to -0.89). Biomass-
weighted mean latitude of SSB (age 1+) in April-May was
consistently and positively correlated with regional salini-
ties in April-May (r=0.30 to 0.88). On the other hand, in
June-August, surface-layer mean salinity in the lower Bay
and subpycnocline-layer mean DO in the lower and middle
bay were significantly and positively correlated with mean
latitude of SSB or AL (r=0.82 to 0.91). Baywide SSB in
April-May and June-August tended to be negatively cor-
related with water temperature in April-May (r=-0.45 to
-0.90).
Recruitment model
Although SSB alone did not correlate significantly with
recruitment level, mean DO in June-August was signifi-
cantly related to the mean latitude of SSB in June-August
(or AL) and bay anchovy recruitment level in October (Figs.
3C and 4). AL was selected as the explanatory variable,
rather than DO, because DO data were uncalibrated in
1999 and 2000. The correlation observed between AL and
DO ( Fig 3C ) suggested that AL can serve as a proxy for DO
in the stock-recruitment model. Including AL and SSB for
April-May in a modified Ricker model provided a good fit
to bay anchovy recruitment levels observed from 1995 to
2000 (Fig. 5). The model is
Rv = 365 S exp (-0.19 S 1.35 AL) (modified Ricker model).
In the model, if AL is held constant, predicted recruitment
level of bay anchovy is maximum when baywide SSB in
April-May is approximately 5.3 x 103 tons. Collinearity and
influence diagnostic statistics did not indicate collinearity
between the two independent variables (S and AL), or that
an observation in any year had a dominating influence on
parameter estimates.
Discussion
Complex environmental processes and biological interac-
tions control bay anchovy recruitment in Chesapeake Bay.
Dissolved oxygen (DO), freshwater flow, salinity, and tem-
perature acting on prerecruits and adults are important
factors affecting bay anchovy distribution and levels of
recruitment. Spawning stock size also is related to recruit-
70
Fishery Bulletin 102(1)
ment level. Our results have demonstrated that there is
a strong spatial component in the recruitment dynamics
of bay anchovy. Although fish recruitment processes his-
torically have been difficult to understand, our six-year,
spatially extensive research has provided new insights into
processes that control bay anchovy recruitment.
Ontogenetic migration pattern
It is apparent that ontogenetic migration plays a role in
the spatial and temporal patterns in abundance, biomass,
and production of bay anchovy. There are several lines of
evidence. Rilling and Houde (1999a), in a baywide analy-
sis, reported that mean density of eggs and larvae in June
and July 1993 was very high in the lower Chesapeake Bay
compared to more upbay sites. Dovel (1971) and Loos and
Perry (1991) reported possible upbay or upriver migra-
tion of bay anchovy larvae and juveniles in the mainstem
and tributaries of the Bay. Recent otolith microchemical
analyses have strongly supported the hypothesis that
an upbay ontogenetic migration by small YOY anchovy
(>25 mm, late larvae and small juveniles) occurs (Kimura
et al., 2000). In the middle Hudson River estuary (Schultz
April-May
39°00'
£ 38°00
37°00
39°00
38°00
37°00'
30 40 50 60 70 80 90 100
TL (mm)
1995 1996 1997 1998 1999 2000
Figure 2
Abundance-weighted mean latitude of occurrence of bay anchovy
(Am hoa mitchilli) in Chesapeake Bay, 1995-2000.
et al., 2000) and Chesapeake Bay (North and Houde, in
press), selective tidal-stream transport was suggested as
a mechanism for up-estuary movements of bay anchovy
larvae. Our conceptual model of the bay anchovy life cycle
includes migration patterns in the bay based on available
knowledge and evidence (Fig. 6).
It is uncertain what benefits YOY bay anchovy derives
from upbay migration in summer and whether the migra-
tion is passive or active before a subsequent reverse migra-
tion in the fall. To explain upbay movements of estuarine
fishes, Dovel ( 1971 ) proposed that there is a "critical zone"
of low salinity and high prey production in the upper bay,
which is important as a nursery for bay anchovy and
other fish species. In late spring and early summer, age-1
and age-l+ bay anchovy mature and move upbay while
spawning, although the year 2000, when mean freshwater
streamflow during the previous fall-winter was lowest, was
an exception. Recruited YOY bay anchovy apparently over-
winter primarily, but not entirely, downbay until spring.
There remains a possibility of significant immigration
to the bay by adult bay anchovy in some years from the
coastal ocean or tidal tributaries of the bay. Without such
immigration, baywide adult abundance would decrease
continuously during the April-October period through
natural mortality However, in two years of our six-year
study, 1995 and 1998, estimated adult abundance in-
creased substantially from April to July, and in 1999
adult abundance increased from June to October,
implying significant immigration to the bay in those
years (Jung, 2002).
Recruitment control and regulation
The modified Ricker recruitment model that included
SSB and AL as explanatory variables provided a good
fit to bay anchovy recruitments. Although the model
fitted well, there were only six years of data, and
the underlying mechanisms explaining relationships
between the distribution and level of SSB, hydro-
logical conditions, and density-dependent regulatory
processes in recruitment of bay anchovy are not yet
clear. Nevertheless, correlations and the recruitment
model clearly indicated a density-dependent effect of
SSB level and also implicated environmental factors
(at the mesoscale) that are related to mean DO concen-
tration, latitudinal distribution of SSB (AL), and the
recruitment level of bay anchovy (Fig. 4).
The modified Ricker model for bay anchovy < Fig. 5)
indicates a density-compensatory stock-recruitment
relationship (Ricker, 1975). although we do not know
at what life stages density-dependent processes are
most important. Without accounting for the control-
ling effect of AL and mean DO on a regional scale,
the density-dependence might have gone undetected
(Fig. 4 1. Recent individual-based models suggest that
density-dependent processes during early-life stages
could stabilize bay anchovy recruitments (Wang et
al., 1997; Cowan et al., 1999; Rose et al, 1999). At the
small scales of several meters modeled by Wang et al.
(1997) and Cowan et al. (1999), larval-stage feeding
Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli
71
Zl 39°00'
38°00'
CO
CO
CO
37°00'
April-May
June-August
1995
1996
1997 1998
1999 2000
2000
38°00'
1999^
1=38.30 - 0.00087 X
r-=0.94(/)=0.0012)
37045'
1995
--4?^- 1998
B
1996_
37°30'
i ,
300
<
39°00'
c
C
CO
CO
c
38°00'
400 500 600 700
Mean river flow from June to Feb (m3/sec)
1995
1996^
1999
1998
37°00'
2000
1997
Y= 35.78 + 0.53 A'
r2=0.75(p=0.02)
3.0 3.5 4.0 4.5 5.0
Dissolved oxygen (mg/L)
5.5
Figure 3
Mean location (latitude) of adult bay anchovy {Anchoa mitchilli) spawn-
ing stock biomass (SSB) in Chesapeake Bay. (A) Mean latitude and
standard deviation in April-May and in June-August. The upper verti-
cal bar represents mean + standard deviation for June-August, and the
lower vertical bar represents mean-standard deviation for April-May,
I B l Mean latitude in April-May and mean Susquehanna River flow from
June of the previous year to February of the current year. (C) Mean lati-
tude in June-August and mean dissolved oxygen in the subpycnocline
layer of the middle bay in June-August.
processes were important and high adult SSB could pro-
duce abundant first-feeding larvae with subsequent den-
sity-dependent food competition. In Tampa Bay, Florida,
Peebles et al. ( 1996) hypothesized that bay anchovy's size-
specific fecundity is directly related to prey availability
for adults. Modeled results of Rose et al. (1999) suggested
that density-dependent growth of bay anchovy larvae and
juveniles in Chesapeake Bay would lead to density-depen-
dent survival of these stages. Hunter and Kimbrell (1980)
and Alheit (1987) proposed that cannibalism by adults on
eggs and larvae provides a degree of density-dependent
regulation in anchovies of the genus Engraulis. Analyses
of feeding by adult bay anchovy did not indicate that pe-
lagic fish eggs were a significant part of bay anchovy diet
(Vazquez-Rojas, 1989; Klebasko, 1991), although no specific
study of cannibalism has been undertaken.
We propose three hypotheses that may explain the rela-
tionships among regional DO concentration, the latitudi-
nal shift in SSB distribution during the spawning season
(AL), and recruitment levels of bay anchovy in October. The
72
Fishery Bulletin 102(1)
hypotheses are the following: 1) averaged DO concentra-
tion is inversely related to levels of plankton productivity
in a region and high plankton productivity favors high re-
cruitments of planktivorous bay anchovy; 2 ) low dissolved
oxygen concentrations can restrict spatial distribution of
bay anchovy SSB to the lower bay insuring high egg and
Table 5
Cross-correlation coefficients for bay anchovy distribution and abundance with respect to region- and layer-specific means of tem-
perature, salinity, and dissolved oxygen from 1995 to 2000. Mean latitude is biomass-weighted mean latitude of occurrence of bay
anchovy. Abundance and biomass are baywide total estimates. AL = (mean latitude in June-August) -37.00. Abbreviations are
as follows: SAL = salinity, TEM = water temperature, OXY = dissolved oxygen; the fourth and fifth digits: 04 = April-May, 07 =
June-August; the sixth character: L = lower bay, M = middle bay, U = upper bay; The last character: S = layer above the pycnocline.
B = layer below the pycnocline. * = significant at a = 0.05.
Young-of-the-year
Adult
Mean latitude
Abundance
Mean latitude
Biomass
April-May
June-August
(orAL)
October
October
April-May
June-August
SAL04LS
0.29
-0.43
0.74
0.26
-0.17
-0.52
SAL04MS
0.45
-0.63
0.30
0.71
-0.41
-0.22
SAL04US
0.27
-0.60
0.42
0.53
-0.18
-0.02
SAL04LB
-0.24
0.01
0.88*
-0.16
-0.14
-0.31
SAL04MB
0.08
-0.17
0.59
0.33
-0.39
-0.05
SAL04UB
0.29
-0.61
0.45
0.46
-0.03
0.05
SAL07LS
0.83*
-0.75
0.91*
-0.46
SAL07MS
-0.12
0.06
0.14
0.31
SAL07US
0.06
-0.03
-0.04
-0.33
SAL07LB
0.70
-0.75
0.64
-0.11
SAL07MB
-0.41
0.60
-0.31
0.19
SAL07UB
0.15
-0.20
0.01
-0.42
TEM04LS
0.16
-0.25
-0.03
0.65
-0.90*
-0.48
TEM04MS
0.50
-0.46
0.14
0.65
-0.71
-0.85*
TEM04US
0.53
-0.32
-0.36
0.52
-0.56
-0.85*
TEM04LB
0.29
-0.49
0.19
0.71
-0.72
-0.45
TEM04MB
0.22
-0.42
0.39
0.47
-0.55
-0.62
TEM04UB
0.40
-0.26
-0.39
0.48
-0.60
-0.77
TEM07LS
-0.49
-0.04
0.11
0.45
TEM07MS
-0.16
-0.21
0.47
0.14
TEM07US
-0.29
-0.08
0.39
0.38
TEM07LB
-0.68
0.24
-0.11
0.38
TEM07MB
-0.24
-0.10
0.37
-0.04
TEM07UB
-0.45
0.16
0.2]
0.46
OXY04LS
0.63
-0.22
-0.80
0.39
-0.10
-0.30
OXY04MS
-0.27
0.56
0.23
-0.81
0.55
-0.04
OXY04US
-0.43
0.41
-0.30
-0.30
0.30
0.88*
OXY04LB
0.93**
-0.68
-0.59
0.63
0.04
-0.38
OXY04MB
0.47
-0.35
-0.31
-0.09
0.70
-0.12
OXY04UB
-0.57
0.65
-0.32
-0.46
0.21
0.78
OXY07LS
0.18
-0.30
0.29
0.32
OXY07MS
0.01
-0.13
0.29
0.56
OXY07US
0.23
-0.32
0.50
0.10
OXY07LB
0.67
-0.48
0.82*
-0.28
OXY07MB
0.72
(l,SH
0.87*
-0.04
OXY07TJB
0.01
0.16
0.21
0.37
Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchilli
73
larval production there; and 3) density-depensatory
predator satiation occurs when concentrations of bay
anchovy larvae and juveniles at the mesoscale ( 10-100
km ) are high in relation to satiation potential of preda-
tors, which favors larval production and high anchovy
recruitments.
First, averaged DO level in the bay or its regions
may be an indicator of ecosystem metabolism and sec-
ondary production. DO level in the subeuphotic layer
is an indicator of respiration and secondary produc-
tion by planktonic and benthic communities (Kemp
and Boynton, 1980; Kemp et al., 1992). Recruitment
levels of bay anchovy increased substantially in 1997
and in subsequent years. We speculate that enhanced
detrital production potentially increased zooplankton
prey abundances in the subsequent year and that asso-
ciated elevated levels of respiration by detrital micro-
organisms and zooplankton contributed to low mean
DO. Increased zooplankton prey abundances, in turn,
may have promoted production of larval and juvenile
bay anchovy in 1997 and 1998. Thus, increased prey
availability, associated with low mean DO concentra-
tion, could have enhanced recruitment (Fig. 4).
The second hypothesis proposes that spatial restric-
tion of SSB by low DO is a factor controlling bay anchovy
recruitment. Based on our results, hypoxic conditions in
the bay appear to define the distribution and potential for
upbay migration of bay anchovy SSB (Fig. 3C). In years
300
1998
7= -88 .V+ 5 10
C 200
o 1 00
cr
r-=0.79P=0.01S
2000
^~"-\1999
^^19,97
~"\J995
1W(,
0
3.0 3.5 4.0 4.5 5.0
Dissolved oxygen (mg/L)
Figure 4
Relationship between mean dissolved oxygen below the pycno-
cline in the middle Chesapeake Bay during the June-August
period and recruitment level of bay anchovy in October, r2 =
coefficient of determination.
when the baywide subpycnocline mean DO level was low,
spawning bay anchovy tended to be most concentrated in
the lower bay (Table 5, Fig. 3, A and C), possibly because
hypoxia in deeper waters of the mid-bay region discouraged
upbay migration. The region selected by adult anchovy as
the predominant spawning area and its variability played
R = 365 Sexpf-O.l0- S - 1.354Z.)
r2--
2.0 0
Figure 5
Stock-recruitment model (modified Ricker model). R = baywide number of recruits in
October (xlO9). AL = location of bay anchovy iA?iclioa mitchilli) spawning stock biomass
in June-August in relation to the baseline latitude at the mouth of the bay, 37°00'N. S =
baywide spawning stock biomass (SSB xlO3 metric tons for April-May 1. Balloon symbols
are observed data from 1995 to 2000.
74
Fishery Bulletin 102(1)
a strong role in controlling YOY recruitment levels. The
four highest recruitment years in our series had the lowest
mean subpycnocline DO levels and had distribution pat-
terns of SSB that differed little between the prespawning
April-May and spawning June-August periods (Fig. 4). Al-
though we do not fully understand how DO, and possibly
hypoxic conditions, affect migratory behavior and distribu-
tion patterns of bay anchovy, hypoxia in Chesapeake Bay
has been demonstrated in other research to affect spatial
and temporal patterns of fish abundance, including bay
anchovy (Breitburg, 1992; Keister et al., 2000).
Our third hypothesis proposes that predation is an im-
portant regulator of fish recruitment in early-life stages
(Sissenwine, 1984; Bailey and Houde, 1989). We hypoth-
esize that abundant and spatially concentrated larval
or juvenile anchovy, as observed in the lower bay, could
promote early-life survival by satiating predators, even if
some predators migrate to areas where larval and juvenile
anchovy are abundant. At mesoscale distances of 10-100
km, distribution of predators (e.g. YOY and age-1 weakfish
[Cynoscion regalis] ) may be important. If the maximum
number of prey that can be eaten by predators is reason-
ably constant, the effect of predation can be density-depen-
satory (Hilborn and Walters, 1992), i.e. predation mortality
rate decreases as prey density increases.
In support of the third hypothesis, a correspondence
analysis on fish species assemblages by year, season, re-
gion, and life stage (Jung and Houde, 2003) indicated that
distributions and abundances of YOY weakfish, a major
predator of bay anchovy in Chesapeake Bay (Hartman
and Brandt, 1995), and YOY bay anchovy were closely as-
sociated spatially, seasonally, and annually in our six-year
study. The major spawning area of bay anchovy is spatially
restricted. If predator migration to the area is limited, then
as the supply of larvae and juveniles increases, it may satu-
rate predator demand, the condition necessary for depensa-
tion to be important.
It may seem contradictory to propose that density-com-
pensation with respect to SSB (the negative sign of j\)
and density-depensation with respect to AL (the second or
third hypothesis ) can act simultaneously during larval and
juvenile stages. Under this circumstance, the number of
surviving postlarval anchovies is hypothesized to decrease
because of food limitation when larval abundance is high,
reducing subsequent predation-related mortality rate on
postlarvae and small juveniles. Low abundance of anchovy
early-life stages will lead to the opposite effect (Fig. 7). The
proposed opposing responses of the early-larval and late-
larval-juvenile stages are explained by differences in the
spatial scales of distribution and densities of life stages of
bay anchovy (Fig. 7). The spatial scale of processes that
affect distributions of late-stage larvae and juveniles is
large compared to that for early-stage larvae because of
the increased dispersal and swimming ability of juveniles.
Comparing early-larval and late-larval-juvenile stages of
bay anchovy, we propose that effects of prey concentration
(the first hypothesis) and SSB level (density-compensa-
tion) act primarily on the dynamics of early-larval stages,
whereas predation mortality and the inhibitory effects of
low DO (density-depensation; the second and third hy-
Nursery
Ground
(3) Fall
YOY recruits,
adults
Late-stage larvae,
juveniles, some adults
Eggs and larvae
Overwintering
Recruited
anchovy
Adult
Immigration from
tributaries'?
Major
Spawning Mature adults.
/ eggs, larvae
ground
(1) Spring
Adult
Immigration from
ocean?
Figure 6
Conceptual model representing bay anchovy (Anchoa
mitchilli) life cycle and ontogenetic migration within
Chesapeake Bay, and possible immigration of adults
from tributaries and coastal ocean.
potheses) are more important regulators and controllers,
respectively, during late-larval and juvenile stages.
The three hypotheses that relate DO, SSB distribution,
and recruitment of bay anchovy are not mutually exclusive.
If low mean DO level is an indicator of enhanced prey pro-
duction and availability to larvae and juveniles, increased
prey productivity in the lower bay could enhance bay
anchovy recruitment potential by supplying enough zoo-
plankton prey to spawning adults, larvae, and juveniles. At
the same time, low mean DO in the mid-Bay could confine
most spawning bay anchovy to the lower bay. thus increas-
ing spawning and larval production there, and possibly
enhancing survival of juveniles by predator satiation. Ul-
timately, other hypotheses may provide better explanations
of the relationships between regional mean DO. latitudinal
shifts in distribution of spawners, abundances of spawners.
and recruitment of bay anchovy. For example, abundant
gelatinous organisms, such as the scyphomedusa (Chn'sa-
ora quinquecirra) and the lobate ctenophore \Mnemiopsis
leidyi), can be important predators on early-stage anchovy
and competitors with juveniles and adults (Purcell et al.,
Jung and Houde: Recruitment and spawning-stock biomass distribution of Anchoa mitchil/i 75
Early-stage and larvae
Density-compensatory
Prey is smaller
Small scale (1 m-10 km)
Densiy of early-stage larvae
(1 m-10 m scale)
Late-stage larvae and juveniles
Density-depensatory
Predator is bigger
Mesoscale(IO-lOOkm)
Recruits
Ontogenetic migration
Densiy of late-stage larvae
(10-100 km scale)
SSB
Figure 7
Hypotheses and conceptual model of the bay anchovy {Anchoa mitchilli) recruitment process in
Chesapeake Bay. The density-compensatory process acts at a small spatial scale during the early-
larval stages, whereas the density-depensatory process acts at a broader spatial scale during late-stage
larval and juvenile stages. The ontogenetic migration is controlled by dissolved oxygen levels and other
hydrological factors.
1994), but their potential role with respect to bay anchovy
recruitment could not be defined in our study. For the
present, it is clear that most spawning occurs in the lower
and mid Chesapeake Bay, from which larval and juvenile
anchovies disperse upbay. We hypothesize that food avail-
ability is the major factor controlling production of bay
anchovy early-larval stages whereas predation becomes
more important during late-larval and juvenile stages.
Our results and hypotheses implicate density-related pro-
cesses, operating at different spatial scales, as regulators
of recruitment of bay anchovy in Chesapeake Bay.
Acknowledgments
We thank S. Leach, E. North, J. Hagy, C. Rilling, J. Cleve-
land, A. Madden, D. O'Brien, B. Pearson, D. Craige, T. Auth,
and the able crew of RV Cape Henlopen for assistance in
field surveys. T. Miller and E. Russek-Cohen provided com-
ments and assistance on statistical analyses. This research
was supported by a U.S. National Science Foundation, Land
Margin Ecosystem Research (LMER) program grant,
"Trophic interactions in estuarine systems (TIES)" (grant
DEB94-12113). Additional support was provided by NSF
Grant OCE-9521512 and by National Oceanic and Atmo-
spheric Administration grant NOAA, NA170P2656.
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78
Abstract— Increasing interest in the
use of stock enhancement as a man-
agement tool necessitates a better
understanding of the relative costs and
benefits of alternative release strate-
gies. We present a relatively simple
model coupling ecology and economic
costs to make inferences about optimal
release scenarios for summer flounder
(Paralichthys dentatus), a subject of
stock enhancement interest in North
Carolina. The model, parameterized
from mark-recapture experiments,
predicts optimal release scenarios from
both survival and economic standpoints
for varyious dates-of-release, sizes-at-
release, and numbers of fish released.
Although most stock enhancement
efforts involve the release of relatively
small fish, the model suggests that
optimal results (maximum survival
and minimum costs) will be obtained
when relatively large fish (75-80 mm
total length! are released early in the
nursery season (April). We investigated
the sensitivity of model predictions to
violations of the assumption of den-
sity-independent mortality by includ-
ing density-mortality relationships
based on weak and strong type-2 and
type-3 predator functional responses
(resulting in depensatory mortality
at elevated densities). Depending on
postrelease density, density-mortality
relationships included in the model con-
siderably affect predicted postrelease
survival and economic costs associated
with enhancement efforts, but do not
alter the release scenario (i.e. combina-
tion of release variables ) that produces
optimal results. Predicted (from model
output) declines in flounder over time
most closely match declines observed
in replicate field sites when mortality
in the model is density-independent
or governed by a weak type-3 func-
tional response. The model provides an
example of a relatively easy-to-develop
predictive tool with which to make
inferences about the ecological and
economic potential of stock enhance-
ment of summer flounder and provides
a template for model creation for addi-
tional species that are subjects of stock
enhancement interest, but for which
limited empirical data exist.
Manuscript approved for publication
17 July 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:78-93 (2004).
Coupling ecology and economy:
modeling optimal release scenarios for
summer flounder (Paralichthys dentatus)
stock enhancement
G. Todd Kellison
David B. Eggleston
Department ol Marine, Earth, and Atmospheric Sciences,
North Carolina State University
Raleigh, North Carolina 27695-8208
Present address (for G T. Kellison, contact author): National Park Service/ Biscayne National Park
9700 SW 328th St, Homestead, Florida 33033
E-mail address (for G T Kellison) todd_kellison 5 nps gov
Commercially important marine fish
and invertebrate populations are
declining worldwide in response to
overexploitation and habitat degrada-
tion (Rosenberg et al„ 1993; FAO 1998).
This reduction in harvestable fishery
resources has stimulated increasing
interest in the use of hatchery-reared
(HR) animals to enhance wild stocks
(Munro and Bell, 1997; Travis et al.,
1998; Cowx, 1999; Kent and Draw-
bridge, 1999). Unfortunately, many stock
enhancement programs proceed before
ecological concerns are adequately
addressed (Blankenship and Leber,
1996), and without the identification
of goals or the evaluation of the success
of enhancement efforts (Cowx, 1999).
If fishery managers can satisfactorily
determine that enhancement efforts
will have no ecologically significant
negative ramifications, then managers
should establish specific, quantifiable
goals and objectives of enhancement
efforts as part of a responsible approach
to stock enhancement (Blankenship
and Leber, 1996; Heppell and Crowder,
1998). Once such goals have been
established, managers should identify
stocking approaches that will lead to
the most cost-efficient realization of
enhancement goals — a process that
can be accomplished with the aid of
coupled ecological and economic models.
Although numerous (advanced) models
(conceptual and species-specific) exist
to predict the biological and ecological
impact of alternative enhancement
scenarios (e.g. Botsford and Hobbs,
1984; Salvanes et al„ 1992; Barbeau
and Caswell, 1999; Sutton et al., 2000),
there are few models ( of which we are
aware) that have attempted to link the
biological and ecological results of stock-
ing efforts (e.g. addition of biomass to a
stocked population) with the economic
costs associated with various release
scenarios (e.g. Botsford and Hobbs, 1984;
Hobbs et al., 1990; Hernandez-Llamas,
1997; Kent and Drawbridge, 1999). Such
a link is critical to the responsible use
of funding to rebuild or manage fisher-
ies, and for the comparison of predicted
costs of enhancement versus alternative
management techniques.
In North Carolina, there has been
recent interest in stock enhancement
with summer flounder (Paralichthys
dentatus) (Waters, 1996; Rickards,
1998; Waters and Mosher, 1999; Burke
et al., 2000; Copeland et al. ' ) because of
a combination of heavy commercial and
recreational exploitation, established
techniques for mass hatchery-rearing
(Burke et al., 1999), and considerable
knowledge of summer flounder life his-
tory (Powell and Schwartz, 1977; Burke
et al., 1991; Burke, 1995). Nevertheless,
there have been no large-scale release
experiments ( and subsequent collection
of data) by which to make empirical
inferences about stock enhancement
potential for this species. We present
a compartmental model, parameterized
from mark-recapture field experiments,
Copeland, B. J., J. M. Miller, and E. B.
Waters. 1998. The potential for flounder
and red drum stock enhancement in North
Carolina. Summary of workshop, 30-31
March. 1998, 22 p. ' (Available from North
Carolina State Univ, Raleigh. NC 27695.]
Kellison and Eggleston: Modeling release scenarios for Paralichthys dentatus
79
Table 1
Range of numbers of summer flounder (Paralichthys dentatus) released (and resulting postrelease densities), sizes-at-release, and
dates of release simulated in the model.
Number released
Postrelease density
Size-at-release
Dates of release
100-400,000
0.001-4.0
30-80 mm
1 April-15 July
that incorporates size of fish released, date-of-release, and
number offish released to calculate 1) predicted numbers of
survivors and 2 ) economic costs associated with varying re-
lease scenarios under density-independent mortality. We in-
vestigated the sensitivity of model predictions to violations
of the assumption of density-independent mortality because
there is abundant evidence that mortality rates, or processes
underlying mortality rates (e.g. growth), are affected by den-
sity-dependent relationships in the wild ( see, for recent ex-
amples. Bucket et al., 1999; Bystroem and Garcia-Berthou.
1999; Jenkins et al, 1999; Kimmerer et al., 2000). We did
so by repeating model simulations under varying density-
mortality relationships (depensatory in nature at elevated
densities ), using experimental evidence from our own field
studies and published observations for similar species to
parameterize density-mortality relationships. Additionally,
we used a scenario in which the density-mortality relation-
ship changed over time to make inferences about the effect of
more complex density-mortality relationships on postrelease
mortality of juvenile summer flounder. Finally, we generated
predicted temporal patterns of field densities under vary-
ing density-mortality relationships and compared them with
observed (in the field) patterns to determine whether model
output under the considered density-mortality relationships
matched actual patterns in the field. The model provides
an example of a relatively easy-to-develop predictive tool
with which to make inferences about the ecological and
economic potential of stock enhancement with summer
flounder and provides a template for model creation for
additional species that are subjects of stock enhancement
interest, but for which limited empirical data exist.
Materials and methods
Background
In North Carolina, wild summer flounder recruit to shal-
low-water estuarine nursery habitats from February to
May, after which small juvenile (20-35 mm total length
[TL] ) densities range from -0.1 to 1.0 fish/m2 (Burke et al.,
1991; Kellison and Taylor2). Juveniles subsequently make
an ontogenetic habitat shift to deeper waters ( Powell and
Schwartz, 1977), apparently after reaching a total length
2 Kellison, G. T., and J. C. Taylor. 2000. Unpubl. data. De-
partment of Marine, Earth, and Atmospheric Sciences, North
Carolina State University, Raleigh, NC 27695-8208.
of -80 mm (Kellison and Taylor2). By mid-July, densities
of juvenile summer flounder in the shallow water nursery
habitats are near zero (Kellison and Taylor2).
Model pathway
Our compartmental model simulated the daily mortality
and growth of different-size hatchery-reared (HR) fish
released in the field over a 105-day period ( 1 April to 15
July, based on observed field abundances) in a hypotheti-
cal release habitat of 10 hectares. The model predicted the
percentage of released fish surviving and economic cost-
per-survivor under 2730 release scenarios for a specified
number offish released (see below). To begin the model, a
value of number offish released (NFR) ranging from 100 to
400,000 (Table 1) was chosen (Fig. 1), resulting in postre-
lease densities (assuming even postrelease distribution) of
0.001-4.0 fish/m2. These values included a range of densi-
ties of juvenile summer flounder observed in wild nursery
habitats ( -0-1 fish/m2; mean -0.05 fish/m2; Kellison and
Taylor2), but also included unusually high densities (>1
fish/m2) in order to examine how such release strategies
would affect model output (we did not examine densities
>4 fish/m2 because of a lack of data on fish response to
resource limitation likely to occur as densities increased
past values for which we had empirical growth data). Each
group of NFR was initially assigned a "size-(TL) at-release"
of 30 mm (the smallest size-at-release simulated in the
model), after which a size-dependent economic cost associ-
ated with the release of the 30-mm-TL fish was calculated
(see below). The release group was then assigned a mini-
mum Julian "day of release" of 92 (corresponding to 1 April,
the earliest release date simulated in the model). A range
of Julian days of release was included in the model because
field-estimated growth rates were dependent on Julian day
(Kellison, 2000), and growth rates are potentially impor-
tant to the determination of mortality rates (Rice et al.
1993). With this model, we then calculated daily mortality
and growth (described below) in the hypothetical release
habitat over the number of days at large (DAL), where
DAL = 197 (the Julian day corresponding to 15 July) - 92
(Julian release day),
and output a number of survivors and a calculated cost-
per-survivor (CPS), where
CPS = cost associated with release -f
predicted number of survivors,
80
Fishery Bulletin 102(1 I
Input
number released
(NR)
' assign size-at-release (SAR)
* calculate cost of release
(COR)
<—
Size-at-release
N
Density-
independent
Julian day
' assign date of release
(DOR)
<
I
' determine
number of survivors (NOS)
DAL
at the beginning of the day (=
«\
initial # of fish or # surviving
from previous day)
/
/
1
da
ly mortality ^
da
ly growth
*M
* calculate
number of survivors and
total length (TL)
at the end of the day
1
I I
* output
- number of survivors
- cost per survivor (CPS)
\
/
Figure 1
Model flowchart. Dashed arrows represent model "backloops" to the indicated compartment where
simulations continue with the next value of the arrow-labeled variable. Side graphs indicate the three
relationships between density and mortality (number offish consumed) that were considered, and the
general relationship between growth and Julian day.
for the initial release scenario of fish size = 30 mm TL.
Julian day = 92, and an NFR input determined by the mod-
eler). The model then looped back to the "date-of-release"
step and simulated the release of the 30-mm-TL fish for
Julian release days 93-197, outputting a predicted number
of survivors and cost-per-survivor for each release date. The
model then repeated all previous steps under sequentially
larger size-at-release scenarios, looping back to the "size-
at-release" step and simulating the release of fish ranging
in size from 32-80 mm TL fish in steps of 2 mm TL. The
model output was a predicted number of survivors and
economic cost-per-survivor for each release day (92-197)
for each size-at-release (Fig. 1). Thus, for each input NFR,
there were 26 size-at-release possibilities x 105 Julian days
of release possibilities, which resulted in 2730 simulations,
each of which resulted in a predicted number of survivors
and cost-per-survivor for that particular release scenario.
For each input NFR, the results from the 2730 simulations
were plotted on two response surfaces, with an .v-axis of
size-at-release, a y-axis of date-of-release, and a 2-axis of
either 1) predicted number of survivors (NOS), or 2) cost-
per-survivor ( CPS ), to identify release scenarios resulting in
the maximum predicted number of survivors and minimum
cost-per-survivor, respectively. The scenarios resulting in
the maximum predicted number of survivors and minimum
cost-per-survivor were not necessarily identical.
Calculation of mortality, growth, survival, and economic
costs associated with release
During each day at large (DAL), released fish were sub-
jected to a density-independent daily mortality rate of
0.02153, derived from postrelease mark-recapture data
of HR summer flounder (Kellison et al., 2003b). In deriv-
ing this value, mean postrelease densities were used to
estimate a total number of survivors from experimental
releases. Daily survival was then calculated with the
equation
Kellison and Eggleston: Modeling release scenarios for Paraltchthys dentatus
81
NFR x SDDAL = NOS,
where NFR = number released;
SD = daily survival;
DAL - days at large (from release date
until Julian day 197); and
NOS = estimated number of survivors.
Daily mortality (MD) was then calculated from
the equation
Mr
1-Sr
At the end of each simulated day, all fish that
were alive increased in growth according to the
equation
GD = -0.0061 x Julian day + 1.2487,
which was derived from mark-recapture data
(Kellison, 2000), and in which GD is daily growth
in millimeters. Fish reaching 80 mm TL during the model
(i.e. by 15 July) were considered to make an ontogenetic hab-
itat shift to deeper waters. These fish were then subjected
to one half year of natural mortality to simulate mortality-
related losses from deeper-water habitats (M=0.28; Froese
and Pauley, 2001). Remaining fish, now having survived
-one year of natural mortality, were considered to be sur-
vivors (available to the commercial fishery), which is a con-
servative assumption because 1-yr-old summer flounder are
only partially recruited to the commercial fishery. All fish not
reaching a total length of 80 mm were assumed to perish.
To determine size-dependent economic costs offish pro-
duction, we used the following regression equation derived
for Japanese flounder (Paralichthys olivaceus) by Sproul
and Tominaga ( 1992 ) because equivalent economic data for
summer flounder were unavailable:
CPF = 14.24 + 1.234 x TL,
where CPF = the cost per fish in Japanese yen (¥); and
TL = the total length of the HR fish.
Costs were then converted into US$ by using an exchange
rate of 106. 7¥ per 1 US$ (universal currency converter).
We feel use of this cost-of-fish-production equation is appro-
priate because the Japanese flounder is closely related
and similar in life history traits to the summer flounder
(Tanakaet al., 1989; Burke etal., 1991 ), resulting in similar
optimal rearing practices for hatchery-reared Japanese and
summer flounder (Burke et al., 1999), and thus likely simi-
lar rearing costs. Additionally, the scale of Japanese floun-
der hatchery production is similar to, or greater than, other
government subsidized hatchery production programs (e.g.
red drum in Texas, cod in Norway [Svasand, 1998] ).
Density-mortality relationships
We tested the sensitivity of the model results (optimal
predicted number of survivors and cost-per-survivor esti-
mates under varying NFRs) to violations of the assumption
0.50 -i
~ 0.40 ■
* Type 2 - weak
k * Type 2 - strong
E 0.30 -
* ^—^-^ d Type 3 - weak
ra
k f ^^^^ ■ Type 3 - strong
o
t 0.20 ■
o
Q.
O
*# ^^^^
o- 0.10 -j
|^»W °°OOnnn„
0 12 3 4
Density (number of fish/m2)
Figure 2
Proportional mortality curves for juvenile summer flounder corre-
sponding to weak and strong type-2 and type-3 mortality responses.
of density-independent mortality by incorporating varying
types and strengths of density-dependent mortality (depen-
satory in nature at elevated densities; see below) into the
model. As a basis for these sensitivity analyses, we assumed
that predation was the driving mechanism underlying the
postrelease mortality of HR summer flounder under the
densities examined (Kellison et al., 2000; Kellison et al.,
2003b). Thus, we made daily mortality rates correspond
to either a type-2 or type-3 predator functional response
(Holling, 1959; see Lindholm et al., 2001 for example), in
which proportional mortality due to predation decreases
with increasing density (type-2 response) or increases ini-
tially with increasing density, reaches a zenith, and then
decreases with increasing density (type-3 response) (Fig.
2). Both type-2 and type-3 responses result in decreasing
(depensatory) mortality at elevated prey densities due to
predator satiation. We did not include scenarios in which
mortality increased at elevated densities (as would be
expected when densities reached those likely to result in
resource limitation ) because we did not include in the model
elevated release densities likely to result in resource limita-
tion. We parameterized the daily mortality curves so that
each response (type 2 or 3) incorporated the daily mortality
rate of 0.02153. These mortality curves contain mortality
values that are within ranges reported in the literature for
other species of juvenile marine fishes (Bax, 1983; Houde,
1987; Nash, 1998; Rose et al, 1999). To make further infer-
ences about the importance of density-dependent mortal-
ity to model results, we included a 1) weak and 2) strong
form of each functional response (types 2 and 3) (Fig. 2), as
well as scenarios in which the response shifted temporally
from 3) type 2 to 3, and 4) type 3 to 2 at the midpoint of
the nursery season (Julian day 145). We included both the
weak and strong forms of the type-2 and type-3 functional
responses to determine the extent to which variation in the
strength of the functional response would affect model pre-
dictions. The strength of the functional response could vary
because of annual variation in the presence or abundance
of prey or because predators could affect the density-mor-
tality relationship (see, for example, Hansen et al., 1998).
82
Fishery Bulletin 102(1)
For example, a strong positive (compensatory) density-
mortality relationship driven by predators might become
weaker in years when predator abundance was lower than
average. We included the temporally shifting functional
response scenarios to determine the extent to which tem-
poral variation in the form of the functional response would
affect model predictions. Temporal variation in the form of
the functional response might occur because of temporal
changes in the predator community, or because of changing
predator-prey size dynamics (e.g. Stoner, 1980; Black and
Hairston, 1988). For example, as the nursery season for
summer flounder progresses, proportionately greater num-
bers of juveniles grow to sizes at which they are capable
of preying on smaller juveniles (Kellison, personal obs. ). If
cannibalistic summer flounder exhibit a different predatory
functional response from that of the predator guild commu-
nity predominating earlier in the season, then the density-
mortality relationship may change seasonally.
We replicated all model simulations over each of the six
density-mortality relationships (weak and strong types 2
and 3, and shifting patterns [type 2 to 3 and type 3 to 2] )
to determine optimal release scenarios (maximum num-
ber of survivors, minimum cost-per-survivor) under each
relationship. We then compared results to those obtained
under density-independent mortality to make inferences
about the importance of density-mortality relationships to
model results.
Correspondence between predicted and
observed temporal abundance patterns
Different density-mortality relationships may result in
distinct temporal patterns of abundance (e.g. rapid versus
more gradual declines in abundance) depending on initial
densities. We generated predicted patterns of temporal
field abundance of juvenile summer flounder under den-
sity-independent mortality and four additional density-
mortality relationships (governed by weak and strong type
2 and 3 functional responses) and under varying initial
densities (0.1, 0.3, and 0.5 fish/m2) to examine whether the
different density-mortality relationships would result in
distinct temporal patterns of abundance. We used 1998-99
field data and logarithmic or polynomial regression models
to generate curves that best fitted (based on r2 values)
observed (from natural nursery sites) temporal declines in
abundance under varying initial densities. We compared
the best-fit curves to those predicted by the model under
density-independent and four additional density-mortal-
ity relationships. These comparisons allowed us to make
qualitative inferences about which density-mortality
relationship* s) resulted in the best match between pre-
dicted and observed temporal patterns of abundance.
Model assumptions
The assumptions of the model are the following:
1 Daily mortality is independent of size. Although there
is strong evidence that mortality of fishes in the wild is
size-dependent (Lorenzen, 2000 ), particularly in regard
to the importance of size to susceptibility to predation
(see, for example, Elis and Gibson, 1995; Furuta, 1999;
Manderson et al., 1999), we found no evidence (from
recaptures of released hatchery-reared fish ) of size-
selective daily mortality for juvenile summer flounder
ranging in size from -30-80 mm TL in shallow-water
nursery areas (Kellison et al., 2003a). Implications for
violations of this assumption are addressed in the "Dis-
cussion" section.
2 Daily growth is independent of fish density. We based
this assumption on field experiments that indicated
no growth limitation at densities roughly equal to the
maximum densities explored in the model (Kellison
et al., 2003b). Similar findings (i.e. no food-limitation
or density-dependent growth) have been reported for
similar-size plaice in shallow-water nursery habitats
(van der Veer and Witte, 1993).
3 Economic cost per fish (CPF) is independent of the
number of fish acquired for release (i.e. within the
range of numbers offish released in model simulations,
there is no decrease in cost per fish as the number of
fish acquired from the production hatchery for release
increases). This assumption is likely to be valid over
changes in numbers of fish released common to stock
enhancement programs (Sproul and Tominaga, 1992)
but may not be valid as numbers released change
over orders of magnitude because of economy of scale
(Adams and Pomeroy 1991; Garcia et al., 1999).
4 There is no emigration from the release habitat until
fish exhibit an ontogenetic shift in habitat at 80 mm TL.
Although pre-ontogenetic habitat shift emigration may
not truly be zero, we feel that it is also unlikely that pre-
ontogenetic habitat-shift emigration accounts for more
than a minimal amount of loss of released fish from
the habitat of release, as supported by several points.
First, rates of pre-ontogenetic shift emigration in wild
juveniles are apparently low (Kellison and Taylor2),
suggesting that large-scale spatial migrations may not
be part of the behavioral repertoire of early juvenile
summer flounder. Second, irregular temporally repli-
cated sampling outside of experimental release sites
resulted in zero captures of emigrating hatchery-reared
fish (Kellison et al., 2003b). Third, emigration rates of
closely related HR Japanese flounder {Paralichthys
olivaceus) are reported to be very low (Tominaga and
Watanabe, 1998). In combination, these points suggest
that our zero emigration assumption is appropriate.
5 Fish that do not grow to 80 mm TL during the model
period (i.e. by 15 July) do not survive. Although this
assumption cannot be examined with our field data,
data do show that juvenile summer flounder are
absent from shallow-water nursery habitats by mid
to late July (Kellison et al.3). Thus, all fish have either
perished or made ontogenetic habitat shifts to deeper
habitats by this time. Our field observations suggest
that the deeper habitats to which larger flounder
:t Kellison, G. T., J. C. Taylor, and J. S. Burke. 2000. Unpubl.
data. Department of Marine, Earth, and Atmospheric Sciences,
North Carolina State Univ., Raleigh, NC 27695-8208.
Kellison and Eggleston: Modeling release scenarios for Paralichthys dentatus
83
make ontogenetic habitat shifts are
inhabited by relatively high densities of
potential predators (e.g. blue crabs, age 1+
flounders, red drum [Sciaenops ocellatus],
searobin [Prionotus sp.], and lizardfish
[Synodus sp.] ), which may be considerably
less abundant in shallow-water habitats.
These relatively large and abundant
predators would presumably expose small
migrating fish to high rates of predation
(see, for example, Elis and Gibson, 1995;
Furuta, 1999; Manderson et al„ 1999). This
assumption is supported by research with
the congener Japanese flounder (Paralich-
thys olivaceus). Although a range of sizes
of hatchery-reared Japanese flounder may
survive within relatively shallow nursery
habitats, fishes less than 90 mm TL moving
into relatively deep waters are poorly rep-
resented in subsequent age classes, most
likely due to predation-induced mortality
(Yamashita et al., 1994; Furuta, 1999).
There is no relationship between length
of rearing period (time spent in the
hatchery environment) and probability of
postrelease mortality related to behavioral
deficits (Olla et al., 1998). Hatchery-specific
selection pressures may result in HR fish
that are behaviorally selected to survive in
the hatchery and not in the wild (see Olla
et al., 1998; Kellison et al., 2000; for discus-
sion). We assume that behavioral deficits
are not exacerbated with time spent in the
hatchery (i.e. behavioral deficits are equal
for all sizes-at-release).
Results
The most important factor affecting the
number of survivors (and therefore percent
survival) was size-at-release because the
greatest numbers and percentages of survi-
vors were always produced by releasing the
largest fish possible (80 mm TL in the model).
Number of survivors decreased with decreas-
ing size-at-release and with increasing Julian
day of release (Fig. 3A). The cost-per-survivor
( CPS ) was also most affected by size-at-release,
such that CPS decreased with increasing size-
at-release (Fig. 3B). CPS generally increased
with increasing Julian day of release (Fig. 3B), although
this effect was less important than the effect of size-at-
release. Because mortality was originally assumed to be
density-independent, the optimal cost-per-survivor did
not vary with the number offish released (Fig. 4), and the
relationship between number offish released and number
of survivors was linear (Fig. 4), such that the maximum
number of survivors were generated from the greatest
number offish released (NFR=400,000).
220
20 80
90 220
Figure 3
Response surfaces of iAi number offish survivors (summer flounder I
and (Bi cost-per-survivor (CPS) as a function of date of release and size
at release at number released (NR) = 5000 (postrelease density=0.05)
under density-independent mortality. CPS values greater than $10 were
set equal to $10 for ease of presentation.
Sensitivity of model predictions to violations of
density-independent mortality assumption
Model results varied considerably under the various den-
sity-mortality relationships (Fig. 5, A and B), indicating
the importance of knowledge of the relationship between
numbers of fish released (density) and mortality in the
wild to predicting optimal release scenarios. Variation in
model output was dependent on the type and strength of
Fishery Bulletin 102(1)
the density-mortality relationship. For example, at postre-
lease densities of 0.5 fish/m2 (NFR=50,000), survival of
released flounder under density-independent mortality
was ~28% higher than that predicted under strong type-3
mortality, but only -2% higher than that predicted under
weak type-2 mortality (Fig. 5A). At postrelease densities
of 0.001 fish/m2 (NFR=100), survival of released flounder
under density-independent mortality was ~41% higher
450000 -I
m 400000 •
§ 350000 •
£ 300000 •
« 250000 ;
° 200000 ■
E 150000 ■
| 100000 ■
z 50000 ■
— ■ — optimal number of survivors :
— o— optimal CPS ^^^"
r 1 60
: 1 50 O
■ 1.40 g
■ 1 30 -g
-1,20 5
[110 <§
- 1 00 g
■0.90 <
■0 80 -
■ 0.70 C
■ 0-60 W
0 50000 10000 15000 20000 25000 30000 35000
40000
Number released
Figure 4
Optimal number of fish survivors and cost-per-survivor as a function of
varying numbers of summer flounder released under density-indepen-
dent mortality.
0 12 3 4 5
Density (number of fish/m2)
Figure 5
l A i Optimal percent survival and iBi optimal cost-per-survival (US$) as a func-
tion of postrelease density undci density-independent and varying density-
dependent, mortality relationships for summer flounder.
than that predicted under strong type-2 mortality, but -2%
less than that predicted under strong type-3 mortality ( Fig.
5A). In contrast, when postrelease densities were relatively
high, there was less of an impact of density-mortality rela-
tionship on postrelease survival and costs associated with
stock enhancement. For example, at postrelease densities
of three fish/m2 (NFR=300,000), survival of released floun-
der differed by less than 4% between density-independent,
weak or strong type-2, and weak type-3 mor-
tality, although survival under strong type-3
mortality was ~99c less than that predicted
under density-independent mortality and
-11% less than that predicted under strong
type-2 mortality (Fig. 5A). Thus, the model
results were most sensitive to violations of the
assumption of density-independent mortality
at low densities offish released in the field.
Type-2 mortality As with density-indepen-
dent mortality, the most important factor
affecting number of survivors and cost per
survivor under type-2 mortality was size-at-
release (Fig. 6, A and B). In all simulations,
the greatest number of survivors was pro-
duced by releasing the largest fish possible.
Number of survivors decreased with increas-
ing Julian day of release (Fig. 6A). There was
a considerable interaction between size-
at-release and number of fish released,
such that low postrelease densities were
subjected to relatively high proportional
mortality. Thus, when fish were released
in low numbers and at small sizes, the
fish were subjected to relatively high
proportional mortality rates for long
periods of time (while they grew towards
the 80-mm-TL ontogenetic shift size) and
consequently produced few or no survi-
vors (Fig. 6A). Optimal release scenarios
under strong type-2 mortality produced
substantially lower (>40% in some
cases) percent survival (and therefore
substantially higher cost-per-survivor)
estimates at low to moderate numbers
released (NFR= 100-50,000; postrelease
density=0.001-0.5 fish/m2) than under
density-independent mortality (Fig. 5, A
and B). Differences in percent survival
estimates (and thus cost-per-survivor
estimates) between density-indepen-
dent survival and weak or strong type-2
mortality declined to less than 5ri when
the numbers released increased to
25,000 (postrelease density=0.25 fish/m2)
under weak type-2 mortality and 75.000
(postrelease density=0.75 fish/m2) under
strong type-2 mortality (Fig. 5A). Thus,
model predictions under density-inde-
pendent mortality differed most from
predictions under mortality governed by
- density-independent
-type 2 - weak
- type 2 - strong
-type 3 - weak
■type 3 - strong
density-independent
type 2 - weak
type 2 - strong
type 3 - weak
type 3 - strong
Kellison and Eggleston: Modeling release scenarios for Paralichthys dentatus
85
B
a type-2 predator functional response when
postrelease densities were relatively low.
Type-3 mortality As in all other simulations,
the most important factor affecting number
of survivors under type-3 mortality was size-
at-release, such that the greatest numbers of
survivors were always produced by releasing
the largest fish possible (Fig. 7A). Number of
survivors decreased with increasing Julian
day of release (Fig. 7A). Percent survival
was considerably lower (>25% in some cases)
under type-3 mortality than under density-
independent mortality at moderate to high
numbers released (NFR=10, 000-400, 000)
(Fig. 5 A).
In nearly all simulations, the lowest CPS
values were produced by releasing the larg-
est fish possible (Fig. 7B). The exceptions to
the "large size = optimal CPS" rule occurred
when postrelease densities were small (cor-
responding to numbers released of 100, 500,
and 1000) and the mortality curve was type 3
(weak or strong). In these instances, mortality
was sufficiently low at low release densities
( Fig. 7B ) so that the difference in overall sur-
vival between small- and large-released fish
was small enough to be overridden by the in-
creased cost of the larger fish, and the mini-
mum CPS was obtained when small (42-44
mm TL) fish were released (e.g. Fig. 7B).
At low numbers released (NFR=100-1000),
optimal cost-per-survivor was considerably
lower (>45% in some cases) under type-3
mortality than under density-independent
mortality (Fig. 5A). As NFR increased, CPS
under type-3 mortality became greater ( -40^
in some cases) than that achieved under den-
sity-independent mortality (Fig. 5B).
Temporal shift in functional response from
type 2 to type 3, and from type 3 to type 2
The optimal numbers of survivors under
varying numbers released were identical, and
optimal CPS values nearly identical, when
the form of the functional response changed
from a type 2 to a type 3, and from a type 3 to
a type 2, midway through the juvenile nurs-
ery season (Fig. 8, A and B). The differences
at low postrelease densities between optimal
CPS values under shifting type 2 to type 3 and type 3 to
type 2 scenarios (Fig. 8A) occurred because initial mortality
under the type-3 functional response was sufficiently low
that the difference in overall survival between small- and
large-released fish was small enough to be overridden by
the increased cost of the larger fish (Fig. 8A). The minimum
CPS was obtained when small (42-44 mm TL) fish were
released (in all other cases, optimal results were obtained
when size-at-release was maximized) (Fig. 8A). The major
difference between the two shifting scenarios is that the
re/ease
Figure 6
Response surfaces of (A) number offish (summer flounder I survivors and
(B) cost-per-survivor (CPS) as a function of date of release and size at
release at number released (NR) = 5000 (postrelease density=0.05l under
a strong type-2 functional response. CPS values greater than $10 were set
equal to $10 for ease of presentation.
release dates producing optimal results for a given number
of fish released varied depending on the direction of the
shifting functional response. For example, when the func-
tional response shifted from a type 2 to a type 3, a release
of 100,000 HR organisms achieved optimal results when
release occurred early in the season (Julian day <145)
(Fig. 9A). When the functional response shifted from a
type 3 to a type 2, a release of 100,000 HR summer floun-
der achieved optimal results only when releases occurred
later in the season (Julian day >145) (Fig. 9B). When the
86
Fishery Bulletin 102(1)
functional response shifted from a type 3 to a type 2, releas-
ing 100,000 HR organisms prior to Julian day 146 resulted
in markedly decreased survival (and therefore increased
CPS ) compared to results obtained from releases after day
146 (e.g. releasing on Julian day 92 resulted in a decrease
in number of survivors and an increase in CPS of 22.8%
and 29.7%, respectively) (Fig. 9B). Thus, date-of-release
had a significant effect on the results (and therefore in
determining optimal release strategies) when the relation-
ship between density and mortality changed temporally,
suggesting that the presence of a temporal shift in the func-
500
£ 400
300
200
E
z
100
220
OaV'
Size at re/ease
Figure 7
Response surfaces of (A) number offish (summer flounder) survivors and
(B) cost-per-survivor (CPS) as a function of date of release and size at
release at number released (NR) = 500 (postrelease density=0.005) under
a strong type-3 functional response. CPS values greater than $10 were set
equal to $10 for ease of presentation.
tional response of the predator guild would have consider-
able effects on the number of survivors and CPS for stock
enhancement efforts with juvenile summer flounder.
Correspondence between predicted and
observed temporal abundance patterns
Under the assumption of a type-2 functional response,
predicted declines in juvenile summer flounder density
over time were rapid when initial density was relatively
low (i.e. 0.1 fish/m2) (Fig. 10, A and B). These predictions
contrast with those observed in the field,
in which declines at relatively low initial
densities were gradual (compare Fig. 10A
and 10B to Fig. 10F). Under the assumption
of a type-3 functional response, predicted
declines were rapid when initial density was
relatively high (i.e. 0.5 fish/m2) I Fig. 10, C
and D). These results generally contrast with
those observed in the field, in which declines
at relatively high densities were much less
rapid than those predicted under a strong
type-3 functional response, and somewhat
less rapid than those predicted under a weak
type-3 functional response (Figs. 10F and 11).
Under density-independent mortality, there
was little difference in predicted declines in
juvenile summer flounder density over time
between the three initial density levels (0.1,
0.3, and 0.5 fish/m2); in each case there was
a gradual decrease in density over time (Fig.
10E). These results were similar to those
observed in the field, although declines at rel-
atively high densities in the field were some-
what more rapid than those predicted under
density-independent mortality ( compare Figs.
10E and 10F). Thus, a density-mortality rela-
tionship lying between that generated under
density-independence and that generated
under the weak type-3 functional response
in the model would most closely predict the
temporal declines observed in the field.
Discussion
Implications for stock enhancement of
summer flounder
Regardless of the relationship between den-
sity and mortality, size-at-release was the
most important variable in the model affect-
ing survival and costs associated with stock
enhancement of summer flounder. The model
predicts that under all release scenarios, 1)
survival will be maximized and 2) costs asso-
ciated with stock enhancement (i.e. cost per
survivor) will be minimized when HR fish are
released at the largest size possible. From a
survival standpoint, these results are not
Kellison and Eggleston: Modeling release scenarios for Paralichthys dentatus
87
surprising. Larger fish spend fewer days than smaller fish
in the wild nursery habitats before making an ontogenetic
habitat shift to deeper waters and thus are susceptible to
daily natural mortality for fewer numbers of days than are
smaller fish. Thus, total mortality of smaller fish is greater
than that of larger fish. Additionally, although we chose to
make mortality independent of size in the model, abundant
literature suggests that natural mortality (especially due
to predation ) may decrease with increasing size by mecha-
nisms such as enhanced resistance to starvation, decreased
vulnerability to predators, and better tolerance of environ-
mental extremes (Sogard, 1997; Hurst and Conover, 1998;
Lorenzen, 2000). Thus, the difference in predicted survival
between 1 ) relatively large and relatively small fish and 2 )
fish released early versus late in the season in our model
would be even greater if larger summer flounder suffered
lower natural mortality than smaller fish. Furthermore,
the daily mortality estimate used in the density-inde-
pendent simulations and to parameterize the different
types of density-mortality relationships may have been
an underestimate of daily mortality (Kellison, 2000). If a
greater estimate of daily mortality had been used, the dif-
ference in predicted survival between relatively large and
relatively small fish in our model would have been further
exacerbated because smaller fish spend longer amounts of
time in the model growing to the 80-mm-TL ontogenetic
shift size. These conclusions are supported by empirical
research demonstrating that relatively large released HR
fish suffer lower mortality than relatively small HR fish
released in the field (e.g. Yamashita et al., 1994; Leber,
1995; Willis et al., 1995; Tominaga and Watanabe, 1998;
Svasandetal.,2000).
Although the survival predictions of the model (total
mortality decreases with increasing size-at-release) are
not surprising, the economic (cost-per-survivor) predic-
tions were unexpected. The paradigm for stock enhance-
ment strategy is that the rearing of relatively large fish
for release is cost prohibitive, so that mass releases of
relatively small, inexpensive-to-rear fish are a better
strategy than the release of larger, expensive-to-rear fish
(Kellison, personal obs.). Thus, relatively small juveniles
are released in virtually all current stock enhancement
programs (e.g. Russell and Rimmer, 1997; Masuda and
Tsukamoto, 1998; McEachron et al., 1998; Svasand, 1998;
Serafy et al., 1999). Nevertheless, large-scale hatcheries
and grow-out facilities are using ever-increasing technol-
ogy to minimize the costs associated with the production
of relatively large fishes (Sproul and Tominaga, 1992).
Thus, for species for which 1) hatcheries are capable of
producing relatively large fish at relatively low costs (as
is likely for summer flounder), and 2) postrelease survival
rates increase with release size, release scenarios utilizing
the largest fish possible may maximize the potential (i.e.
produce maximum survival at minimum costs ) of stock en-
hancement efforts. In these cases, the "small fish maximize
stock enhancement potential" paradigm might be replaced
with a "large fish maximize potential" paradigm. As a ca-
veat, this "large fish" strategy may be limited by spatial
limitations of hatcheries in producing large numbers of
relatively large fish. Because reared fish generally must
1 40 i
*/»
^_
1.20-
o
2
1 00-
w
0 80-
(1>
Q.
0 60-
If)
O
0 40-
O
Type 2 to 3
Type 3 lo 2
0 20-1— -! , 1 r
Postrelease density
Figure 8
Optimal lA) economic cost-per-survivor and (B) per-
cent survival of released hatchery-reared summer
flounder under temporally shifting functional re-
sponses of type 2 to type 3 and type 3 to type 2.
be kept below critical densities in hatchery environments
because of water quality and fish interaction issues (e.g.
cannibalism), larger fish necessarily require more space
than smaller fish for rearing. If the demand for space to
rear large quantities of large fish can be realized, then the
model simulations indicate that stock enhancement strat-
egies in which size-at-release is maximized will produce
the maximum number of survivors.
Although not as important as size-at-release, Julian day
of release had a significant effect on survival and cost-per-
survivor in the model, such that enhancement efforts were
always more successful (more survivors, lower costs) when
fish were released at the earliest Julian day possible. These
results occurred because growth in the model decreased
with increasing Julian Day. Although the mechanisms un-
derlying this decrease in growth with increasing Julian day
are unknown, they may be related to decreased prey avail-
ability or metabolic efficiency as temperatures increase
with increasing Julian day (Malloy and Targett, 1994a,
1994b; Fujii and Noguchi, 1996; Howson, 2000). Thus, for
a given size-at-release, fish released earlier in the season
experienced greater growth rates than fish of the same
size-at-release released later in the season and therefore
reached the 80-mm-TL ontogenetic shift size faster (over a
period of fewer days) than fish released later in the season.
Thus, fish released earlier in the season were susceptible
to natural mortality for fewer days than fish released later
in the season and therefore suffered lower total mortality.
These results emphasize the importance of knowledge of
possible time-dependent growth in the field prior to stock
enhancement efforts.
Fishery Bulletin 102(1)
Is density important? Effects of varying density-mortality
relationships
Our results suggest that the relationship between density
and mortality has the potential to significantly affect opti-
mal release scenarios associated with stock enhancement
efforts. Because the original simulations were performed
under density-independent mortality, the number of
survivors originally increased linearly with the number
B
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8e+4
o
>
>
6e+4
tfl
n
m
4e+4
a
h
3
2e+4
z
0
80
released, resulting in a density-independent cost-per-
survivor. Thus, when mortality is independent of density
(over a given range of densities) for a target species for
stock enhancement, managers will maximize the number
of survivors produced by releasing the greatest number of
fish possible within that range for a given size class. When
mortality varied with density of released fish, the number
of survivors and cost-per-survivor depended on the den-
sity-mortality relationship. In some cases, optimal results
(maximum survival and minimum cost) differed
depending on whether the response variable was
number of survivors or cost-per-survivor. Under
the assumption of a strong type-3 functional
response and under relatively low postrelease
densities, survival was optimized (maximized)
by releasing the largest fish ( 80 mm TL) possible;
however, cost-per-survivor was optimized (mini-
mized) by releasing smaller fish (42-44 mm TL).
This result occurred because mortality at low
postrelease densities was sufficiently low that
the difference in total mortality attributed to the
longer "susceptibility" period of the smaller fish
was insufficient to override the economic advan-
tage of releasing smaller fish. Simulations under
shifting functional responses (type 2 to type 3
and type 3 to type 2) produced optimal results
similar to those obtained when nonshifting type-
2 or type-3 functional responses were employed
because densities were generally reduced to such
low numbers by the time the shift occurred that
the changing density-mortality relationship was
inconsequential. Importantly, when functional
responses shifted temporally, the predicted
number of survivors and economic cost per
survivor was at times very dependent on date of
release, suggesting that identifying or ruling out
shifting functional responses in the wild may be
critical to accurate prediction of response vari-
ables (survivors and economic costs) associated
with stock enhancement. Although we are not
aware of reports in the literature of shifting
functional responses in the wild, we are also
not aware of studies that have tested for such
a phenomenon, possibly because of the logisti-
cal difficulties inherent in identifying a shifting
functional response.
Correspondence between predicted and
observed temporal abundance patterns
Figure 9
(A) Response surface of optimal number of summer flounder survivors
as a function of date of release and size at release at number released
(NR) = 100,000 (postrelease density=1.0 fish/m2 1 under the assumption
of a temporally shifting functional responses from type 2 to type 3.
<B> Response surfaces of optimal number of survivors as a function of
date of release and size at release at number released (NR) = 100. 000
(postrelease density=1.0 fish/m2 > under the assumption of a temporally
shifting functional responses from type 3 to type 2.
Predictions of field abundance patterns of juve-
nile flounder density over time were noticeably
different under density-independent mortality
and density-dependent mortality governed by
type-2 and type-3 functional responses. For
example, our simulations predict that fish den-
sity should decrease rapidly under relatively
low initial densities if the functional response is
type 2, decrease rapidly at relatively high initial
densities if the functional response is type 3, and
Kellison and Eggleston: Modeling release scenarios for Parahchthys dentatus
89
OS-
04-
0.3
0.2
01
00
E
Strong type 2
Strong type 3
150
Dl
B
Weak type 2
05
0.4
0 3
02
110 130 150 170 190 210
D
Weak type 3
Julian day
Figure 10
Predicted temporal trends in summer flounder abundance under initial densities of 0.5, 0.3, and 0.1 fish/m2
under the assumption of a functional response that is a (A) strong type 2. IB) weak type 2, (C) strong type
3. i D i weak type 3. and under the assumption of (E) density-independent iDIl mortality. The curves in iFi
are best fitted (highest r2 value) to data collected in Duke Beach 1999 (curve a, r2=0.82). Haystacks Marsh
1999 (curve b, r2=0.73), Prytherch Marsh 1999 (curve c. ;-2=0.82), Towne Beach 1999 (curve d, r2=0.91).
Radio Beach 1999 (curve e, r2 = 0.27), Duke Beach 1998 (curve f, r2=0.31), and Prytherch 1998 (curve g,
r2=0.16) (see Fig. 11 for data).
gradually decrease regardless of initial density if mortal-
ity is density independent. From examinations of tempo-
ral abundance patterns from several nursery sites (see
Kellison et al., 2003b, for site descriptions), it is evident
that observed declines at relatively low initial densities
are similar to predicted declines under both density-inde-
pendent mortality and a weak type-3 functional response;
whereas observed declines at relatively high initial densi-
ties are somewhat less gradual than predicted under den-
sity-independent mortality, but somewhat more gradual
than predicted under the weak type-3 functional response.
These results suggest that model predictions made under
the assumption of a weak type-3 response may give rea-
sonably accurate but conservative predictions of juvenile
summer flounder mortality and economic costs associated
with stock enhancement for comparison with alternative
management methods. As a caveat, although we found no
evidence of size-dependent daily mortality over the range
of fish sizes examined in this study, it is very likely that
such a relationship exists to some extent (Sogard, 1997;
Lorenzen, 2000). Incorporating size-dependent mortality
into the model would decrease the slopes of the predicted
temporal abundance curves but should not change the
conclusion that the observed data lie somewhere between
values predicted under density-independent mortality
and those governed by a weak type-3 functional response,
respectively. Additionally, because the portions of the
curves used to delineate between temporal abundances
expected under density-independent versus varying den-
sity-mortality relationships are from early in the growth
season (later parts of the curve converge on very low den-
sities) and because nearly all fish in these portions of the
curves are at sizes well below that at which ontogenetic
emigration occurs, the exclusion of emigration from these
simulations should not affect the general conclusions
reached. These issues could be clarified with further field
trials to investigate the dependence of daily mortality
rates on fish size.
90
Fishery Bulletin 102(1)
E
E
Prytherch 1999
Radio 1999
003
♦
Prytherch 1998
* r* = 0.1575
0 02
♦
001
*
_. ♦ ♦♦
95 105 115 125 135 145 155 165
B
03
♦
Duke 1999
0 2
•
♦
r = 0 8162
01
♦
9*
♦
* ♦*4U**TMT *' •*♦
D
Haystacks 1999
Towne 1999
r" i 0 9063
^s^ •
♦ ""
"Y — ♦ ♦♦
» '«W. W. LT»
95 115 135 155 175 195
Duke 1998
0 1
♦
♦
*
r2 = 03113
0.05
•
*
**>
♦.
•
♦
♦ ~~7
•
♦ ♦ ♦
95 115 135 155 175 195
Julian day
Julian day
Figure 11
Temporal density patterns from (A) Duke Beach, 1999; (B) Haystacks Marsh, 1999; (C) Prytherch Marsh,
1999; (D) Towne Beach, 1999; (E) Radio Beach, 1999; (F) Duke Beach, 1998; and (G) Prytherch Marsh 1998.
Densities are corrected for gear bias (see Kellison, 2000).
Model utility and implications
Although model results varied considerably under the
various density-mortality relationships, the overall pre-
dictions that survival would be maximized and economic
costs minimized when relatively large fish were released
early in the season were unaffected by the density-
mortality relationship. These results suggest that manag-
ers may use this model to make inferences about optimal
release scenarios even if density-mortality relationships
are unknown. Additionally, these results have important
implications for the cost efficiency of stock enhancement
programs. Managers can use the model to determine
the release scenarios under which they can 1) maxi-
mize the number of survivors, given a financial limit
(e.g. given a budget of x dollars, what release scenario
or scenarios will produce the greatest number of survi-
vors?), and 2) minimize costs, given a goal of number-of-
survivors-produced (e.g. given a goal of producing
.v survivors, what release scenario or scenarios will be most
cost efficient?).
In conclusion, the compartmental model used in this
study provides an example of a relatively easy-to-develop
predictive tool with which to make inferences about the
ecological and economic potential of stock enhancement, in
relation to alternative management approaches, to rebuild
depleted fisheries.
Kellison and Eggleston: Modeling release scenarios for Paraltchthys dentatus
91
Acknowledgments
We thank Brian Burke (NCSU) for tutelage in the use of
Visual Basic. Mike Denson (South Carolina Department
of Natural Resources) and Pete Schuhmann (UNC-Wilm-
ington ) greatly contributed to the editing of an earlier ver-
sion of this manuscript. Mark Wuenschel, Michael Martin,
Brian Degan, Lisa Etherington. and Mikael Currimjoe pro-
vided valuable laboratory and field assistance necessary
for parameter estimation. This project was partially funded
by the University of North Carolina at Wilmington/North
Carolina State University Cooperative Ph.D. Program, and
a grant from the National Science Foundation (OCE 97-
34472) to D. Eggleston.
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94
Abstract— Sex-specific demography
and reproductive biology- of stripey bass
[Lutjanus carponotatus l I also known as
Spanish flag snapper. FAO ) were exam-
ined at the Palm and Lizard island
groups, Great Barrier Reef ( GBR). Total
mortality rates were similar between
the sexes. Males had larger L . at both
island groups and Lizard Island group
fish had larger overall L_,, Female:male
sex ratios were 1.3 and 1.1 at the Palm
and Lizard island groups, respectively.
The former is statistically different
from 1, but is unlikely significantly
different in a biological sense. Females
matured on average at 2 years of age
and 190 mm fork length at both loca-
tions. Female gonadal lipid body indices
peaked from August through October,
preceding peak gonadosomatic indices
in October, November, and December
that were twice as great as in any
other month. However, ovarian stag-
ing revealed 50^ or more ovaries were
ripe from September through February,
suggesting a more protracted spawning
season and highlighting the different
interpretations that can arise between
gonad weight and gonad staging meth-
ods. Gonadosomatic index increases
slightly with body size and larger fish
have a longer average spawning season,
which suggests that larger fish produce
greater relative reproductive output.
Lizard Island group females had
ovaries nearly twice as large as Palm
Island group females at a given body
size. However, it is unclear whether
this reflects spatial differences akin
to those observed in growth or effects
of sampling Lizard Island group fish
closer to their date of spawning. These
results support an existing 250 mm
minimum size limit for L. carponotatus
on the GBR, as well as the timing of a
proposed October through December
spawning closure for the fishery. The
results also caution against assessing
reef-fish stocks without reference to
sex-, size-, and location-specific biologi-
cal traits.
Sex-specific growth and mortality, spawning
season, and female maturation of the stripey bass
{Lutjanus carponotatus) on the Great Barrier Reef
Jacob P. Kritzer
School of Marine Biology & Aquaculture
and CRC Reef Research Centre-Effects of Line Fishing Project
James Cook University
Townsville. Queensland 4811, Australia
Present address: Department of Biological Sciences
University of Windsor
401 Sunset Avenue
Windsor, Ontario N9B 3P4, Canada
E-mail address kntzenSuwindsorca
Manuscript approved for publication
22 July 2003 by Scientific Editor.
Manuscript received 22 July 2003 at
NMFS Scientific Publications Office.
Fish Bull. 102:94-107 (2004).
Lutjanid snappers are among the
most prominent species comprising
the catch of hook-and-line fisheries
on tropical reefs worldwide (Dalzell,
1996). A notable exception is the line
fishery on Australia's Great Barrier
Reef (GBR). There, the finfish catch,
and therefore the majority of fisheries
research, is dominated by coral trouts
of the genus Plectropomus (Mapstone et
al.1). However, the GBR finfish harvest
is diverse and the catch of many sec-
ondary species has risen steadily since
the early 1990s (Mapstone et al.1).
Furthermore, over the past decade,
the GBR fishery has changed with the
advent of the lucrative Asian live reef-
fish market. At present, only a handful
of the many species harvested on the
GBR are exported to the live reef-fish
market. However, continued expansion
of the trade coupled with the depletion
of fish stocks in other source nations
(Bentley2) has the potential to intro-
duce demand for a wider range of spe-
cies. Even in the absence of changes in
the species composition of live reef-fish
exports, increased demand for second-
ary species due to changes in either
domestic preferences or availability of
primary species has the potential to
elevate harvest of currently nontarget
species (Kritzer, 2003).
Effective multispecies management
of the GBR fishery will ultimately re-
quire understanding the biology of more
than simply the primary target species.
For example, spawning closures of the
fishery have been proposed for nine-day
periods around the new moon in Octo-
ber, November, and December on the
rationale that this will protect spawn-
ing activity of a wide range of harvested
species (Queensland Fisheries Manage-
ment Authority3). Yet, spawning season
information for species beyond the com-
mon coral trout {P. leopardus ) ( Ferreira,
1995; Samoilys. 1997 ) is nearly nonexis-
tent. The GBR fishery is in a fortunate
position with respect to management
of many species for which exploitation
is still at relatively low levels because
baseline biological characteristics can
be estimated before stock structure is
drastically altered by fishing. These da-
ta can then be used in both formulating
management strategies and monitoring
effects of fishing.
1 Mapstone. B. D.. J. P. MacKinlay, and C. R.
Davies. 1996. A description of the com-
mercial reef line fishery log book data held
by the Queensland Fisheries Management
Authority. Report to the Queensland
Fisheries Management Authority. 480 p.
Primary Industries Building, GPO Box 4(i.
Brisbane. Queensland 4001. Australia.
2 Bentley. N. 1999. Fishing for solutions:
can the live trade in wild groupers and
wrasses from Southeast Asia be managed?
TRAFFIC Southeast Asia report. 143 p.
Unit 9-3A, 3rd Floor. Jalan SS23/11,
Taman SEA. 47400 Petaling Java, Selan-
gor, Malaysia.
3 Queensland Fisheries Management Auth-
ority. 1999. Queensland coral reef fin
fish fishery. Draft management plan and
regulatory impact statement, 80 p. Pri-
mary Industries Building. GPO Box 46,
Brisbane, Queensland 4001, Australia.
Kritzer: Sex-specific growth and mortality, spawning season, and female maturation of Lut/anus carponotatus
95
One of the most prominent secondary species in the
GBR fishery is the stripey bass (Lutjanus carponotatus)
(Spanish flag snapper. FAO). In relation to other large
predators on the GBR, L. carponotatus is highly abundant
on inshore reefs, common on mid-continental shelf reefs,
and absent from outer-shelf reefs (Newman and Williams,
1996; Newman et al., 1997; Mapstone et al.4). Although
this affinity for inshore reefs has the potential to make the
species more susceptible to recreational fishing, the limited
available data do not suggest that it is heavily exploited
by the recreational fleet (Higgs, 1993) in relation to the
commercial fleet (Mapstone et al.1). Lutjanus carponota-
tus has a broad-based diet, consuming a wide variety of
smaller reef fishes and invertebrates (Connell, 1998). Its
role as a predator coupled with its abundance, particularly
on inshore reefs, suggests that the species might have an
important ecological function on the GBR in addition to its
role as a fishery resource.
Davies (1995) and Newman et al. (2000) have collected
basic demographic data for L. carponotatus on the north-
ern and central GBR, respectively. They both reported a
pronounced asymptote in the growth trajectory and that
most growth occurred over the first three to five years and
little subsequent growth over a lifespan that can reach 15
to 20 years. Newman et al. (2000) also reported a heavily
male-biased sample and larger body sizes among males.
Unlike age and growth data, no information on reproduc-
tion of L. carponotatus has been available despite that fact
that existing (minimum size limits) and proposed (spawn-
ing closures) fisheries regulations are based largely on
reproductive traits (Queensland Fisheries Management
Authority3).
Specific aims of this study were 1) to estimate sex ra-
tios and sex-specific schedules of growth and mortality;
2) to estimate age- and size-specific schedules of female
maturation; 3) to identify the spawning season; and 4) to
determine whether reproductive output is proportional
to body size by examining the ovary weight-body weight
relationship and the average spawning duration of large
and small fish. All traits were estimated at the Palm Island
group on the central GBR. Additionally, sex-specific growth
and female maturity schedules were also examined at the
Lizard Island group on the northern GBR to develop spa-
tial comparisons.
Materials and methods
Field methods
Size, age, and reproductive data were obtained for 465
L. carponotatus collected by spear fishing on fringing reef
slopes during monthly fishery independent sampling at
4 Mapstone, B. D., A.M. Ayling, and J. H.Choat. 1998. Habitat,
cross shelf and regional patterns in the distributions and abun-
dances of some coral reef organisms on the northern Great Bar-
rier Reef. Great Barrier Reef Marine Park Authority research
publication 48, 71 p. GPO Box 1379, Townsville, Queensland
4810, Australia.
Pelorus, Orpheus, and Fantome Islands in the Palm Island
group on the central GBR ( Fig. 1 ) from April 1997 through
March 1998. No sampling took place in January 1998
because of severe flooding in the area. To develop spatial
comparisons, samples of 118 and 18 fish were obtained in
October 1997 and April 1999, respectively, by spear fishing
at the Lizard Island group approximately 400 km north of
the Palm Island group (Fig. 1). Fish were collected from
depths of 2 to 15 m by teams of two to four scuba divers.
Lutjanus carponotatus most commonly inhabits depths less
than 15 m (Newman and Williams, 1996); therefore sam-
pling efforts encountered the majority of the population.
Fish were targeted as encountered, without preference
based on size, in order to collect as representative a sample
as possible. Fish <150 mm fork length (FL) were rare in
the samples because they were infrequently observed on
reef slopes (Kritzer, 2002). Therefore, supplemental spear
fishing on reef flats targeting smaller fish was conducted
at the Palm Island group (n=24) in April and December
1999 and at the Lizard Island group (n=25) in May 1999
to obtain growth data for size classes against which the
primary sampling was biased.
Total weight (TW, g) and FL (mm) of each specimen
were recorded. Ovaries and testes of small lutjanids on
the GBR are characterized by a lipid body running along
the length of each lobe, akin to that found in tropical
acanthurids (Fishelson et al., 1985). Gonads and these
associated lipid bodies were removed and preserved in
FAAC (formaldehyde 4%, acetic acid 5%, calcium chloride
1.3%). Sagittal otoliths were removed, cleaned, and stored
for later analyses.
Gonad processing and ovarian staging
The lipid body was removed from each ovary or testis after
fixation and the weight of the gonad (GW) and lipid body
(LW) were measured to the nearest 0.01 g. A gonadoso-
matic index (GSI) and lipidsomatic index (LSI; after Lobel,
1989) were calculated for each sample as the percentage of
TW represented by GW and LW, respectively. Features of
whole fixed ovaries including color, speckling, and surface
texture were noted as potential criteria for macroscopic
staging after comparison with samples processed histologi-
cally. Sex of the April 1999 Lizard Island group samples
was determined macroscopically only, and was therefore
used in sex-specific growth analyses but not in analysis of
maturity. Fish <150 mm FL had undeveloped gonads and
sex of these specimens was not determined or assigned a
reproductive stage.
A subsample of 131 ovaries spanning the range of gonad
sizes and external appearances were prepared for histo-
logical examination. Samoilys and Roelofs (2000) found
that medial gonad sections were adequate for determina-
tion of reproductive status. Therefore, a medial section was
removed from one gonad lobe, dehydrated, and embedded
in paraffin. Embedded ovarian tissues were sectioned at
5 nm and stained with hematoxylin and eosin. Ovaries were
staged on the basis of the most advanced oocyte stage pres-
ent (West, 1990). Additional features used in histological
staging included the presence of brown bodies and atretic
96
Fishery Bulletin 102(1
120°
130°
N
4
Australia
Great
LG Barrier 15°
Reef
PG
Queensland
35°
Lizard Island group (LG)
J\
Lizard
Island <\
V-— V^" ,25km,
Palfrey Q . ' '
Island _ Seabird Islet
South Island
Palm Island group (PG)
Pelorus Island
Brisk Island
<V,Havannah Island
Figure 1
Location of the Palm Island group (PG) and Lizard Island (LG) group within the Great Barrier Reef
off the coast of Queensland, Australia.
oocytes and, in the case of inactive ovaries, the relative
thickness of the gonad wall and the compactness of the
ovarian lamellae (Samoilys and Roelofs, 2000). For those
samples processed histologically, macroscopic features
were compared within and between reproductive stages to
determine whether any macroscopic characteristics could
be used to accurately stage ovaries
Age determination
Ages offish were determined in order to estimate age-based
schedules of growth, mortality, and maturation. Otoliths
lacking broad, opaque macro-increments were processed
to enumerate finer presumed daily micro-increments.
These otoliths were ground by hand first from the anterior
end and then the posterior end through a progressively
finer series of P1200 sandpaper, 12-um lapping film, and
9-um lapping film until a thin section through the nucleus
remained. Micro-increments were enumerated on two inde-
pendent occasions. If the two counts for one specimen did
not deviate by more than 5% of their mean, the mean was
used as the age estimate. Otherwise, a third reading was
performed and the mean of this and the more similar of
the first two readings was used as the age estimate, again
provided that the counts differed by no more than 5' < of
their mean.
Macro-increments in the otoliths of L. carponotatus have
been validated as annuli by tetracycline labeling (Cappo et
al., 2000). A pilot analysis indicated that age estimates did
not differ between readings of whole left and right otoliths
(paired t-test: df=59; r=0.60; P=0.55); therefore one otolith
was randomly selected from each sample for age determi-
nation. All otoliths were initially read whole. A second pilot
analysis compared whole and sectioned age estimates for
a subsample of L. carponotatus otoliths. This comparison
suggested that whole readings began to drastically under-
estimate age beyond approximately sectioned age 12 (see
Kritzer, 2002 ). To capitalize on both the greater efficiency of
whole readings and the greater accuracy of sectioned read-
ings, whole readings were used for all fish except for those
for which any whole reading exceeded 10 or for which there
was not agreement in at least two out of three independent
whole readings. If at least two out of three independent
readings of either whole or sectioned otoliths (as appropri-
ate) agreed, then that value was used as the age estimate.
Ferreira and Russ (1994) have described the whole- and
sectioned-otolith preparation and reading methods used
in the present study.
Sex-specific demography
Early growth of L. carponotatus was estimated by linear
regression of FL on age for those samples processed to
read subannual micro-increments. Separate regressions
were performed for the Palm and Lizard island groups and
these were compared by analysis of covariance ( ANCOVA).
Because of the undeveloped nature of the gonads of the
smallest fish, early growth was estimated without refer-
Kritzer: Sex-specific growth and mortality, spawning season, and female maturation of Lutjanus carponotatus
97
ence to sex. Sex ratios at each island group were compared
with an expected ratio of 1:1 by x2 goodness-of-fit tests by
using all specimens (i.e. immature and mature) whose sex
could be determined.
Lifetime growth parameters were estimated for males
and females from each island group by fitting the von Ber-
talanffy growth function (VBGF),
2»=A.(1"
exp(
-Kit
■'„>)).
where Lt = FL at age t\
L^= the mean asymptotic FL;
A' = the Brody growth coefficient; and
t0 = the age at which fish have theoretical FL of 0.
Growth functions were fitted by nonlinear least-squares
regression of FL on age by using samples for which sex was
determined. Because VBGF parameter estimates can be
sensitive to the range of ages and sizes used (see Ferreira
and Russ. 1994, for an empirical example), a common t0
equivalent to the .v-intercept of the early growth estimates
was used in all models (see "Results" section). Although
the sex-specific sample sizes at the Lizard Island group
were smaller (n=65 for females; n=62 for males), VBGF
parameter estimates achieved high precision at sample
sizes between 50 and 100 (Kritzer et al., 2001); therefore
the Lizard Island group data were included in the analy-
sis. Growth parameters were compared by plotting 959c
confidence regions of the parameters K and Lx (Kimura,
1980) for each sex from each location and assessing the
degree of overlap.
Sex-specific total mortality rates, Z, were estimated by
using the age-based catch curve of Ricker (1975) as the
slope of a linear regression of natural log-transformed fre-
quency on age class. Everhart and Youngs ( 1981 ) proposed
that catch curve analysis should exclude age classes with
n<5 and Murphy ( 1997) proposed that age structures used
in catch curves should be truncated at the first age class
with n<5. Alternatively, Kritzer et al. (2001) proposed that
a sample should contain an average of at least ten fish per
age class irrespective of age class-specific sample sizes.
Therefore catch curves were fitted by two different methods
for each sex at the Palm Island group. The first catch curve
began at the modal age class and stopped before the first
age class with n < 5. The second catch curve likewise began
at the modal age class but included all age classes that
were thereafter represented in the data set. Sex-specific
sample sizes for the Lizard Island group were too small by
any of these criteria and this location was excluded. Mor-
tality estimates for Palm Island group fish were compared
between the fitting methods within each sex as well as
between sexes by ANCOVA.
Reproductive biology
Maturation schedules of female fish were estimated for
each island group by fitting a logistic model,
P, = l/(l + exp(a-W)),
where P- = the proportion of mature fish in age or 20-mm
size class i;
a adjusts the position of the curve along the
abscissa; and
r determines its steepness.
Age- and size-specific maturity functions were used to
estimate the mean age, r50, and size, L50, at which 50% of
females are mature at each island group.
Monthly mean LSI and GSI values of mature Palm
Island group fish were plotted separately for males and
females to determine seasonal patterns of energy storage
and the peak spawning period of L. carponotatus. The pro-
portion of specimens at each mature female reproductive
stage in each month was also plotted to examine ovarian
development patterns throughout the year and the degree
of spawning activity occurring outside of peak months.
To examine whether relative reproductive output in-
creases with body size, GW and GSI for stage-IV ovaries
collected during peak spawning months were regressed
against TW. Residual plots were used to assess deviation
from a linear relationship and to identify three outliers,
which were removed from the regression analysis. Regres-
sion slopes were compared between the two island groups
by ANCOVA. Also, mean GSI values and the proportion of
Palm Island group females with stage-IV ovaries during
spawning months were compared between females <230
mm FL and those >230 mm FL to examine whether the
duration of spawning varies between size classes (nota
bene: 230 mm FL is approximately the mean size of mature
Palm Island group females and splits each month's sample
approximately in half).
Results
Ovarian staging
Five female reproductive stages were identified through
histological analysis (Table 1) and were based largely
on the scheme of Samoilys and Roelofs (2000). Ovarian
stages I (immature) and II (resting mature) have similar
oocyte stages. These can be distinguished by the presence
of brown bodies or atretic oocytes, which are typically prod-
ucts of prior spawning (e.g. Ha and Kinzie, 1996; Adams
et al., 2000) and are usually absent from stage-I ovaries.
However, these structures will not necessarily persist in
ovaries that have spawned, and in fact were rare among
the samples; therefore identification of immature females
was based primarily on structural organization of the
ovary. Stage-I ovaries typically have a thin ovarian wall
and more compacted oocytes, whereas ovaries that have
previously spawned tend to have a thicker ovarian wall
and a more disorganized arrangement of oocytes (Table 1).
Also, there were distinct size differences between stage-I
ovaries and other stages. The mean GW of stage-I ovaries
was approximately one-third that of stage-II ovaries, and
mean GSI was approximately one-half of that at stage II
(Table 1), and the distribution of body sizes offish at stage
I had much lower minimum, maximum, and modal size
98
Fishery Bulletin 102(1)
Table 1
Description of histological and macroscopic features (after fixation in a formaldehyde, acetic acid, calcium chloride solution I of
ovarian developmental stages of Lutjanus carponotatus. Stage definitions and descriptions are largely a modification of the scheme
proposed by Samoilys and Roelofs (2000). Mean ovary weight (GW) and gonosomatic index (GSI) for the larger Palm Island group
sample are provided.
Stage
Histological features
Macroscopic features
Inactive I Immature
II Resting
Active III Ripening
IVa Ripe
IVb Running ripe
Relatively thin ovarian wall; lamellae well
packed; only darkly purple staining previ-
tellogenic oocyte stages (oogonia and peri-
nucleolar stages) present.
Relatively thick ovarian wall; spaces be-
tween lamellae common; only previtellogenic
oocyte stages and possibly brown bodies and
few atretic vitellogenic oocytes present.
Most advanced oocytes are at yolk globule or
migratory nucleus stage; atretic oocytes or
brown bodies possibly present.
Most advanced oocytes at yolk vesicle stage;
atretic oocytes or brown bodies possibly
present.
Similar to stage IVa but large, irregularly
shaped, clear to lightly coloured hydrated
oocytes are present.
Always even white color over entire surface;
smooth surface texture; lobes quite small (typi-
cally <2 cm long) and thin (mean GW=0.33 g;
meanGSI=0.24^).
Even white to cream or tan color over gonad sur-
face; surface may be smooth or somewhat convo-
luted; small white stage II ovaries are difficult to
distinguish from stage I without histology I mean
GW=1.01 g; mean GSI=0.43%).
Color sometimes white but more often cream to
tan; surface is commonly convoluted; difficult to
distinguish from stage II without histology (mean
GW=1.18 g; mean GSI=0.53% I.
Color tan to brown or mustard with opaque speck-
les that become larger and more dense as late
stage oocytes become more numerous; convoluted
surface sometimes with prominent vasculariza-
tion (mean GW=4.04 g; mean GSI=1.399S \.
External appearance identical to stage IVa and
can only be differentiated histologically (no sam-
ples found at Palm Island group).
classes compared with the distribution of body sizes offish
at stage II (Fig. 2).
Stage-Ill (ripening) ovaries contain oocytes at the yolk
vesicle vesicle stage, which some authors classify as vitel-
logenic (e.g. Samoilys and Roelofs, 2000) and others classify
as previtellogenic (e.g. West 1990). Like stage-II ovaries,
stage-Ill ovaries can, but do not necessarily, contain brown
bodies or atretic oocytes as evidence of probable prior
spawning. Although the fish might not have spawned pre-
viously, stage III is considered to be a mature stage in the
present study because the appearance of yolk vesicles is
associated with the initial development of the yolk globule
and represents advanced development of the oocyte beyond
perinucleolar stages (West, 1990). Therefore, the fish is pre-
paring for spawning and will soon be part of the mature
population if it is not already. Mean age and size of stage-II
(4.4. years and 219 mm FL), stage-Ill (5.0 years and 222
mm FL), and stage-IV (6.5 years and 261 mm FL) females
were much more similar to one another than they were
to stage-I females (1.9 years and 119 mm FL). Moreover,
size-frequency distributions of fish at stages II, III, and
IV showed considerable overlap and similarity with one
another and were all quite distinct from the size-frequency
distribution for stage-I females (Fig. 2). This suggests a
division between immature fish and those that are spawn-
ing or are nearly ready to do so. The pronounced difference
in GW and GSI between stage-I and stage-Ill ovaries and
similarity in these metrics between stage-II and stage-Ill
fish (Table 1) further support this division.
Most immature ovaries and all ripe ovaries could be
identified macroscopically. Because certain macroscopic fea-
tures were common to multiple ovarian stages, additional
histological features was required to separate the largest
immature from the smallest resting ovaries and all ripening
from resting ovaries among the samples remaining after
the initial comparison betw-een histological and macroscopic
features. Only one ovary with fully hydrated oocytes, col-
lected at the Lizard Island group, was found among the
samples prepared for histological analysis; therefore stages
IVa and IVb were treated as a single stage. Stage IV suf-
ficiently represents final development toward spawning on
the broad seasonal time scale adopted in this study but
encompasses a wide range of ovarian characteristics and
would need to be divided into more detailed stages for finer
temporal scale studies of lunar or diel spawning patterns.
No samples exhibited features of truly "spent" ovaries.
Sex-specific demography
Differences were not apparent in early growth of L. car-
ponotatus between the island groups (ANCOVA: df=l,
46; F=1.07; P=0.301); therefore the data were pooled to
Kntzer: Sex-specific growth and mortality, spawning season, and female maturation of Lut/anus carponotatus
99
80
70
60
50 H
40
30 H
20
10
0
rzL
estimate an early growth rate of
0.76 mm/d, assuming daily period-
icity of micro-increments (Fig. 3).
This rate of growth represents quite
rapid growth, given that fish are
adding 100 mm of length in around
4 months, increasing from approxi-
mately 20 to 120 mm FL (Fig. 3). The
x-intercept of the early growth curve
(=-17.98 d) was divided by 365 d/yr
to estimate a common t0 (=-0.049 yr)
for all VBGF models.
Although size at age for both sexes
at both island groups was character-
ized by substantial individual vari-
ability, different growth trajectories
were evident for males and females
(Fig. 4, A and B). Estimates (Table
2) and 95% joint confidence regions
(Fig. 4C) for the VBGF parameters
indicated that the primary differ-
ences in these trajectories at each
island group lay in LM (which indi-
cated that males grow larger than females). In
contrast, the common range of K values spanned
by the sexes within each island group indicated
similar curvature (Table 2, Fig. 4C). However, use
of a common t0 restricts the range of possible fitted
lvalues (Kritzer et al., 2001). In addition to the
differences between the sexes, the data revealed a
general pattern of larger body sizes at the Lizard
Island group (Table 2, Fig. 4).
Mortality estimates at the Palm Island group
were slightly higher when all age classes beyond 1
year were included compared with exclusion of age
classes with n < 5 (Fig. 5). These higher mortality
estimates contrast with Murphy's (1997) finding
that truncation of the age structure results in
higher least-squares estimates of Z. The differ-
ences between mortality rates estimated with
and without age classes with n < 5 were minor
for both males (ANCOVA: df=l, 20; F=0.009;
P=0.92) and females (ANCOVA: df=l, 23; F=1.35;
P=0.26). Therefore, for comparisons between the
sexes, the estimates that included all age classes
greater than 1 yr were used. In contrast to the sex-
specific growth differences, Z estimates of 0.26/yr
and 0.29/yr (Fig. 5) corresponding to annual survivorship
of 77% and 75% for females and males, respectively, at the
Palm Island group were similar between the sexes (ANCO-
VA: df=l, 27; F=0.505; P=0.483). Murphy's (1997) results
also suggested that least-squares mortality estimates are
likely to be around 30% less than the true mortality rate
when n = 200 and the true Z = 0.2/yr. Correcting these mor-
tality estimates based upon this potential bias results in Z
estimates up to 0.37/yr and 0.41/yr for females and males,
respectively, with corresponding annual survivorship of
69% and 66%-. However, the catch curve estimates (Fig.
5) corresponded well with estimates based upon Hoenig's
(1983) empirically derived relationship between Z and
n
In
I
I
□ Stage I
■ Stage II
□ Stage III
El Stage IV
I
■ ■
Bfl
51
1 I i ' ' i ii, mi i m
co,,3"ir>cor--ooa>o-<-<Mco-si-ir><or^coa>OT-
t-t-t-t-^t-t-CM<M<MCMCN(>J(N(MCM<MCOCO
Size class midpoint (mm FL)
Figure 2
Size-frequency distributions of female Palm Island group Lutjanus carponotatus at
each of the four stages of ovarian development. Stage descriptions are provided in
Table 1.
20 40 60 80 100 120 140 160
Number of increments (age in days)
Figure 3
Fork length at microincrement count for Lutjanus carponotatus lack-
ing the first annulus at the Palm (□; n =24 ) and Lizard (■; n=25) island
groups. Periodicity of increments is presumed to be daily. Data from
each island group are distinguished, but a pooled linear growth curve
is presented as separate growth curves did not differ (ANCOVA: df=l,
46;P=1.07;P=0.301).
maximum age, tmax (females: tmax=18 yr, Z=0.23/yr; males:
U,=16yr;Z=0.26/yr).
The observed female-to-male sex ratios of 1.3 and 1.1
were close to unity at the Palm and Lizard Island groups,
respectively ( Table 2 ). However, x2 tests suggest this ratio
is statistically different from 1 at the Palm Island group
( df= 1; ^2=7.74; P=0.005 ) but not at the Lizard Island group
(df=l;/2=0.031;P=0.86).
Age and size at maturity
Although there was some indication that Palm Island group
females mature at slightly younger ages and smaller sizes
100
Fishery Bulletin 102(1)
than Lizard Island group females, maturation schedules
were generally similar (Fig. 6). At both island groups, age
2 was the age at both earliest maturity and 50% maturity,
and 93-100% of females had matured by age 4 (Fig. 6A,
Table 3). Thus, maturation was rapid, beginning early in
life and ending within a 2-year period with nearly all mem-
bers of a cohort mature. Length-specific maturation sched-
ules also exhibited similarity between the island groups
with mature fish first appearing in the 160-179 mm FL
size class, estimated 50% maturation in the 180-199 mm
FL size class, and 93-100% maturity at the 220-239 mm
FL size class (Fig. 6B, Table 3).
310
300 -|
290
280
270 -|
260
250 -
240 -
230
0.4
0.5
0.6
0.7
0.8
0.9
K
Figure 4
Fork length at age and estimated von Bertalanffy growth
turves for male ■ solid lines) and female (□. broken lines)
Lutjuiius larpinuiliiliis at the Palm iA> and Lizard iBl island
groups and estimated 959! joint confidence regions of the
parameters A" and l. (C), Parameter estimates are presented
in Table 2.
Spawning season
Mature female LSI values were highest in August through
October with a maximum in September ( Fig. 7A). The peak
in GSI lagged that of LSI by two months with the high-
est values occurring from October through December and
with a maximum in November (Fig. 7A>. The absence of a
January sample unfortunately leaves some ambiguity as to
whether GSI, and therefore presumably spawning activity,
would still be high at this time or if it would have begun
to decline. Male GSI values also exhibited a November
maximum (Fig. 7B). Male LSI values, however, did not
show any clear trend of increase and decline throughout
the year and peaks in April, May, and August that did
not correlate with future GSI values as clearly as seen in
the female data (Fig. 7). Unlike LSI values for females,
monthly mean male LSI values were always greater than
the corresponding GSI values.
The seasonal pattern of L. carponotatus spawning
activity suggested by monthly trends in the proportions
of mature ovarian stages can be interpreted as differ-
ent from that suggested by GSI values. The lowest GSI
values in the October-December peak period were close
to twice as great as the next highest values in Septem-
ber and February < Fig. 7A). However, the percentage of
stage-IV ovaries in the September sample was greater
than 50%. which is well over half the percentage of the
October sample; whereas the February sample comprised
approximately the same percentage of stage-rV ovaries as
October (Fig. 8). Also, more than 50% of the March sample
was stage-rV ovaries (Fig. 8). whereas its GSI value was
close to that of the months with relatively few ripe ovaries
(Fig. 7A). Furthermore, September and March had the
highest proportions of ripening (stage-Ill I females and
thus far fewer resting mature (stage-II) females than the
April to August period of limited spawning activity I Fig.
8). Therefore, regardless of whether September, February,
and March are defined as nonspawning months or months
of limited spawning activity based upon GSI, analysis of
ovarian stage frequencies suggests these to be periods
of greater spawning activity than might be predicted
with GSI. Clearly, the presence of advanced oocytes is a
much better indication of imminent spawning than any
measure of gonad size; therefore the reproductive stage-
frequency data undoubtedly provide the more accurate
picture of L. carponotatus spawning patterns.
Of 59 ovaries staged from the October 1997 Lizard
Island group sample, eight were at stage I, two were at
stage II, and 49 (96% of mature females in the sample)
were at stage PV. This finding suggests that the island
groups share at least October as a common period of ac-
tive spawning.
Reproductive differences between locations and among
size classes
The variation in GW among females of like body sizes
during peak spawning months increased to some degree
with increasing TW, but there was a generally homoge-
neous spread of data around the predicted regression
Kntzer: Sex-specific growth and mortality, spawning season, and female maturation of Lut/anus carponotatus
101
male ages 2+:
y = -0.289x + 4.319
r2 = 0.896
male ages with n
0.844
female ages 2+:
y = - 0.261 x + 4.557
r2 = 0.872
4: female ages with n > 4:
0.272X + 4.282 y = - 0.203x + 4.289
0.879
6 8 10 12
Age class (years)
18
Figure 5
Age-based catch curves for female ■ higher elevation lines i and male (♦. lower
elevation lines) Lutjanus carponotatus at the Palm Island group fitted to all age
classes >1 (solid lines I and age classes >1 with n >4 (dashed lines I. Open symbols
represent age class 1, which was not used in the analysis.
Table 2
Sex-specific von Bertalanffy growth parameters
for Lu
tja
ms carpom
tatus at the Palm and Lizard Island groups
, Great Barrier
Reef, n is sample size; LF
is the mean fork length
( mm )
K
is the Brody growth
:oefficient
per yr)
L.
is the mean asymptotic fork
length (mm); a common t
-, of -0.049 yr was used
n all growth models.
Standarc
errors are
provided below parameter estimates.
n
LF
A"
L.
r2
Palm Island group
females
263
224.2
12.11)
0.77
(0.032)
246.3
(2.25)
0.515
males
202
224.7
(2.78)
0.69
(0.028)
264.3
(3.26)
0.629
sex ratio
1.3:1
Lizard Island group
females
65
239.9
(4.76)
0.56
(0.043)
263.5
(4.24)
0.618
males
62
256.4
(4.77)
0.51
(0.032)
284.8
(4.03)
0.714
sex ratio
1.1:1
lines across body sizes (Fig. 9A). This suggests that on
average GW at stage IV during peak spawning months is
a linear function of TW. Lizard Island group fish generally
had larger ovaries at a given size than did Palm Island
group fish (Fig. 9A), a difference supported by ANCOVA
(df=l, 125; F=34.7; P<0.001). In fact, regression slopes of
0.25 and 0.52 suggest relative ovary weights at the Lizard
Island group were approximately twice as large as those
at the Palm Island group. There were no differences in
the GW-TW relationship among October, November, and
December at the Palm Island group, and therefore the dif-
ferences in this relationship between the island groups was
consistent whether only the Palm Island group October
data were used or whether the October through December
data were used.
Although GW is a linear function of TW, the nonzero
regression constants (Fig. 9A) mean that GW is not a con-
stant proportion of TW. Consequently, GSI increases with
increasing TW ( Fig. 9B ). The relationship between TW and
GSI is not strong, with regression slopes close to zero and
low r2 values at both island groups (Fig. 9B). Despite this,
the relationship is statistically strong at both the Palm
( ANOVA: df=l,82; F=12.70; P=0.006) and Lizard (ANOVA:
df= 1,42; F=22.95; P<0.0001) Island groups. Also, there is
102
Fishery Bulletin 102(1)
some suggestion that, like the GW-TW relationship, the
GSI-TW relationship varies between the island groups,
although to a much lesser extent (ANCOVA: df= 1,125;
F=7.44;P=0.007).
o
o
A
40
34 22 19 12 16 18 12 4 5
2 1 1
4
1
1.0 -
8
33 6 29 5741
2
1
56 /o
E'"B
0.8 -
5/ .'
0.6 -
a ■*
0.4 -
15
/"-'
0.2 -
3/
00 -
There is some indication that larger fish spawn over
a longer period at the Palm Island group. During the
September-February spawning season, mean GSI values
were always higher for mature Palm Island group females
>230 mm FL compared with mature fe-
males <230 mm FL at the same location
(Fig. 10). This pattern is likely due in part
to the higher relative gonad weights of
larger fish (Fig. 9B) but also seems to be
driven by greater proportions of stage-IV
ovaries among larger mature females in
September, October, and February com-
pared with fish <230 mm FL (Fig. 10).
During these months, 13%, 13% and 25%
more large fish were at stage IV, respec-
tively, than were small fish.
0 1 2 3 4 5 6 7
B
9 10 11 12 13 14 15 16 17 M
Age class (years)
53 44 25 11 3 2
1.0
0.8
0.6
0.4
0.2
0.0
10 50 90 130 170 210 250 290 330
Size class midpoint (mm fork length)
Figure 6
Proportion of mature female Lutjanus carponotatus and estimated age-spe-
cific (A) and size-specific (B) logistic maturation schedules at the Palm ■
solid lines) and Lizard (□, broken lines) island groups. Sample sizes for the
Palm (top value) and Lizard (lower value) Island groups are presented above
the data for each age or size class. Parameters of the maturity functions are
provided in Table 3.
Discussion
Demography and reproduction of
L. carponotatus
Growth of L. carponotatus is rapid for the
first two years of life, slows over the next
two years, and nearly ceases by age 4. The
slowing and cessation of growth coincide
with the ages at 50% and 100% maturity,
respectively, and support the argument of
Day and Taylor (1997) that maturation
represents a pivotal physiological trans-
formation and consequently a fundamen-
tal shift in the growth trajectory. Further
supporting the idea that reproductive
development occurs at the expense of
somatic growth is the apparently longer
average spawning season among larger
fish that have ceased most somatic growth.
The limited growth over much of the lifes-
Table 3
Parameters of age- and
size-
specific logistic maturation schedules anc
estimated ages
and fork 1
engths
at
50',
maturity of female
Lu tja n 11 s ca rpon otatus
at the Palm and Lizar
d Island gi
oups, Great Barrier Reef.
a
adjusts th
e posit
on
of the logi
stic function
along the abscissa; r determ
ines the steepness
of the logistic function.
f i;n is the age
at 50%
maturity; Lr
0 is the
fork length at 509S
maturity. Standard errors are provided below parameter
estimates.
a
r
r2
*S0 OI" £50
Age-specific
Palm Island group
6.40
(1.42)
3.42
(0.12)
0.985
1.9 years
Lizard Island group
4.16
(0.48)
1.73
(0.19)
0.990
2.4 years
Size-specific
Palm Island group
14.72
(1.49)
0.081
(0.008)
0.994
182 mm
Lizard Island group
11.61
(3.84)
0.061
(0.020)
0.908
189 mm
Kritzer: Sex-specific growth and mortality, spawning season, and female maturation of Lut/anus carponotatus
103
pan of L. carponotatus can explain the
apparently constant mortality rate
over many age classes (evidenced by
high catch curve r2 values) given that
mortality is often largely a function of
body size (Roff, 1992).
The development and regression of
visceral fat stores preceding increases
in ovary weight is a pattern that has
been observed in other reef fishes, in-
cluding tropical surgeonfishes (Acan-
thuridae: Fishelson et al., 1985) and
groupers (Serranidae: Ferreira, 1995)
and temperate rockfishes (Scorpaeni-
dae: Guillemot et al., 1985). These pat-
terns suggest that the stored lipid is
fuelling the energetic costs of spawning.
The lack of a similar pattern for males
supports the idea that energetic costs
associated with production of sperm are
low in relation to eggs (Wootton, 1985)
thus enabling male L. carponotatus to
attain larger sizes, as also reported by
Newman et al. (2000). Alternatively,
males might spawn more frequently
throughout the year than females and
the lack of seasonal patterns in lipid
storage among males might reflect a
more regular energetic demand that
precludes energy storage. In any case,
these sex-specific growth patterns,
coupled with similar mortality rates
between the sexes and sex ratios that
are at unity or that are at most only
slightly female-biased (see below), sug-
gest that females are limiting reproduction of
this species. Therefore stock dynamics should be
modeled in terms of female biology (Hilborn and
Walters, 1992).
The apparently female-biased sex ratio at
the Palm Island group starkly contrasts with
the heavily male-biased sex ratio reported for
mid-shelf reefs of the central GBR by Newman
et al. (2000). However, neither a male- nor fe-
male-biased sex ratio would be expected from a
nonhermaphrodite that is not known to possess a
complex mating system such as defense of females
or territories. It is possible that the spawning sex
ratio (i.e. excluding juveniles) is closer to unity if
males mature earlier than females, but this ratio
is not possible to assess because male maturation
has not yet been examined for this species. The
difference between the sex ratio reported in this
study and that by Newman et al. (2000) might be
due to variation in mating systems across a cross-
shelf density gradient (Newman and Williams,
1996). Alternatively, the sampling by traps and
line fishing conducted by Newman et al. (2000) could be
more heavily biased toward males than the sampling by
spear fishing used in the present study because of larger
% 25
to
8 2.0
1.5
1.0
0.5
0.0
Figure 7
Monthly mean gonadosomatic index IGSI ±SE; ■) and lipidsomatic index (LSI
±SE; □) values for mature female (A) and all male (Bl Lutjanus carponotatus at
the Palm Island group.
B
-1.0 P
CO
-
- 0.8
■
- 0.6
v
-H"
- 0.4
- 0.2
April
June
Aug Oct
i i
Dec
Feb
Month (1997-98)
100%
80%
I" 60% -
CD
f 40°=
20%
0%
li
i
i
I
D Stage II
■ Stage III
D Stage IV
April June Aug Oct Dec Feb
Month (1997-98)
Figure 8
Monthly frequencies of ovarian stages of mature Lutjanus carpono-
tatus at the Palm Island group. Stage descriptions are provided in
Table 1.
size, wider gape, or more aggressive behavior toward bait
among males (Cappo and Brown, 1996). Furthermore, it
is likely that a female-biased sex ratio as observed at the
104
Fishery Bulletin 102(1)
30 -i
Lizard group:
25 -
y = 0.052x -6.33
Ol
£ 20 J
1 15 -
.-'•" " r2 = 0.711
5 10 -
o
5 -
° -■" . °^^<M^ Palm group:
'$'**T}e^*°^ ' y = 0.025x - 1.62
■J!i^^^, " r" = °-691
^&S*,>
0 200 400 600 800 1000
6.0 -
(J 5.0 -
B
Lizard group:
_»--' y = 0.0071X + 0.64
« 4.0-
■ ° aS°a!-'' f2 = 0353
c
g 3.0 -
to
o 2.0 -
c/i
o
13 1.0-
c
<§ 0.0-
□ D*
u m a £ . ' ° a °
' ° •*!..■■'' - ^—~—~'
■ n ^4 " ■ D □ ■
m ' • °~ " — m
• ■ ' <£J-zi~*~^° ' Palm group:
_*^*~""^° ■ ■ ' . y = 0.0029x + 1.02
."^1 "■ " r2 = 0.134
0 200 400 600 800 1000
Whole body weight (g)
Figure 9
Fixed ovary weight (A) and gonadosomatic index iBi at fresh whole body
weight for mature female Lutjanus carponotatus at ovarian stage IV (see
Table 1) collected during peak spawning months (Oct-Dec) at the Palm
■ solid lines) and Lizard (□, dashed lines) island groups.
Sep Oct Nov Dec Jan
Month (1997-98)
Feb
Mar
Figure 10
Mean gonadosomatic index (GSI ±SE) for mature female
Lutjanus carponotatus at the Palm Island group during the
September through March spawning season for small (<230 mm
fork length; ■> and large (<230 mm fork length; □) size classes.
The percentage of fish at stage IV (see Table 1) is indicated above
each data point.
Palm Island group is not a prevalent feature
of L. carponotatus populations. Rather, the
strong statistical suggestion of a sex ratio
quite different from unity might be due to
the fact that sex ratios often show temporal
variability (e.g. Stergiou et al., 1996) coupled
with the propensity to achieve statistically
significant differences when using large
sample sizes (Johnson, 1999).
Maturation schedules and sex-specific
growth differences were consistent between
the island groups, but overall growth pat-
terns differed, with Lizard Island group fish
reaching larger asymptotic body sizes. Given
the vast distance between the island groups,
these differences might be due to inherent
genetic differences between the populations.
Or, effects of temperature (the Palm Island
group sits at a higher latitude), turbidity,
freshwater run-off (the Palm Island group
sits closer to a river mouth and has more
developed mangrove systems), or other
environmental factors could be driving the
differences. Of course, these possibilities are
not mutually exclusive.
The larger ovaries observed among Liz-
ard Island females might be due to further
spatial differences or might be an effect of
timing of sampling. The temporal resolution
of sampling aimed to identify the extent of
the spawning season but was too coarse to
account for intramonth differences in ovar-
ian development. Large changes in ovary
size might occur within stage IV, and the
final progression to immediate prespawning
stages can be rapid (e.g. Davis and West,
1993). The Lizard Island group sample was collected
from 17 to 23 October 1998, whereas the corresponding
Palm Island group sample was collected from 11 to 12
October 1998. The October 1998 new moon was on the
20th, and P. leopardus, the only GBR species for which
lunar spawning patterns have been reported, spawns
primarily around the new moon (Samoilys, 1997). If
L. carponotatus spawning is also centered around the
new moon, the spatial differences in ovary weight at
body weight might be due to more advanced develop-
ment toward full hydration within the Lizard Island
group sample. In fact, the higher proportion of stage-FV
ovaries within the October Lizard Island group sample
(96%) compared with the October Palm Island group
sample (78'i ), coupled with the higher relative ovary
weights at the Lizard Island group in October, can be
taken as preliminary evidence that L. carponotatus
spawns at the new moon.
Comparison with other reef fishes
The growth differences between male and female L.
carponotatus contrast with a general trend of larger
body sizes among female lutjanids observed in Atlan-
Kritzer: Sex-specific growth and mortality, spawning season, and female maturation of Lut/anus carponotatus
105
tic, Caribbean, and Hawaiian species (Grimes, 1987).
However, the pattern observed in the present study seems
common in the Indo-Pacific where males frequently ( Davis
and West, 1992; McPherson and Squire, 1992; Newman et
al., 1996, 2000). but not universally (Hilomen, 1997), are
the larger sex. As noted above, these differences are consis-
tent with predictions based on energetic costs of producing
sperm and eggs.
Lutjanus carponotatus spawning patterns identified by
using both GSI and ovarian stage frequencies show pro-
nounced seasonal differences: there are at least five months
of very limited or no spawning activity from April through
August. This finding supports Grimes's ( 1987) observation
that continental lutjanid populations tend to have more
restricted spawning seasons than populations associated
with oceanic islands, which spawn more or less continu-
ously throughout the year. Although seasonal patterns ex-
ist, the prominence of ripe gonads over seven months from
September through March suggests an extended spawning
season and supports the general observation that tropical
reef fishes spawn over longer periods within the year than
do cooler water species (Lowe-McConnell, 1979). However,
a study with finer temporal resolution is needed to verify
that spawning actually occurs in months with a high pro-
portion of stage-IV ovaries.
Female L. carponotatus mature on average at approxi-
mately 75% of their mean asymptotic size, 54% of their
maximum observed size, and 119c of their maximum
longevity. The relative size at maturity contrasts with
Grimes's ( 1987) observations that shallow-water continen-
tal lutjanid populations like those of L. carponotatus on the
GBR typically mature at smaller relative sizes (=42% maxi-
mum size) compared to deep-water populations associated
with oceanic islands (=50% maximum size). Two sympatric
shallow -water species, L. russelli (Sheaves, 1995) and L.
fulviflamma (Hilomen, 1997), likewise contrast with the
general familial trend and mature at approximately 50%
and 75% of their maximum size, respectively. Hence, a
general pattern of relative size at maturity might exist
among shallow-water lutjanids in the GBR region that
is different from those regions covered by Grimes's ( 1987 )
review. Lutjanids on the GBR are generally lightly fished
(Mapstone et al.1); therefore the geographic difference in
sizes at maturity might be due to fishing pressure selecting
for smaller sizes at maturity in other regions.
The relative age at maturity of L. carponotatus cannot be
as readily placed in a broader familial context given that
ages at maturity were not widely estimated for lutjanids
at the time of Grimes's (1987) review. However, an array
of published studies suggests that many tropical and sub-
tropical demersal fishes share the absolute, but not relative,
ages of L. carponotatus at 50% and 100% maturity at 2 and
4 years, respectively. These include other small gonochores
on the GBR (Sheaves, 1995; Hart and Russ, 1996; Hilomen,
1997), as well as a range of gonochores in other regions
(Grimes and Huntsman, 1980; Davis and West, 199.3; Ross
et al., 1995 ) and hermaphrodites on the GBR and elsewhere
(Ferreira, 1993, 1995; Bullock and Murphy, 1994). The
ubiquity of this maturity schedule, despite a wide array of
maximum body sizes (160-1200 mm) and longevities (6-56
years) among these species, perhaps suggests a common
physiological threshold toward which many species gravi-
tate in order to maximize lifetime reproductive success.
More comprehensive analysis of life history trade-offs (e.g.
Roff, 1992) is needed to test this hypothesis.
Fisheries management
Harvest of L. carponotatus is currently restricted to fish
greater than 250 mm total length ( approximately 233 mm
FL) with the aim of allowing 50% offish to spawn at least
once, and this regulation is proposed to remain after revi-
sion by the GBR fishery management plan (Queensland
Fisheries Management Authority3). The estimated size
at 50% maturity of 190 mm FL suggests that the regula-
tion is meeting its objective. However, the objective itself
might not adequately protect the reproductive potential of
L. carponotatus and similar species if individuals require
multiple spawning years to ensure sufficient replenish-
ment of the stock. The extensive longevities of many reef
fishes have been hypothesized to be a mechanism for coping
with low and irregular recruitment rates through a process
dubbed the "storage effect" (Warner and Chesson, 1985).
The rationale behind the storage effect hypothesis is that
fish must reproduce during many breeding seasons in order
to endure poor recruitment years and realize high repro-
ductive success during the unpredictable and intermittent
good recruitment years. If this process is important for
population dynamics of L. carponotatus and other species,
management will need to protect an intact natural popula-
tion structure in some areas within the fishery. Protecting
older age classes cannot be achieved by using maximum
size limits for species like L. carponotatus that have a pro-
nounced asymptote in the growth trajectory because body
sizes are similar over a broad range of age classes and size
is therefore poorly correlated with age. Protecting natural
age structure could be accomplished through a system of
strategically designed marine protected areas that allow
some populations to experience natural survival free of
fishing mortality.
Proposed closures of the GBR line fishery during nine-
day periods around the new moon in October, November,
and December are aimed at protecting spawning activity
and particularly spawning aggregations of P. leopardus
and other harvested species (Queensland Fisheries Man-
agement Authority3). Lutjanus carponotatus shares a peak
spawning period during these months with P. leopardus
(Ferreira, 1995; Samoilys 1997) and several other sym-
patric exploited species (McPherson et al., 1992; Sheaves,
1995; Hilomen, 1997; Brown et al.5). In addition, the
larger ovaries of the Lizard Island group fish, which were
collected closer to the new moon, may indicate that, like
P. leopardus (Samoilys, 1997), L. carponotatus spawns at
5 Brown, I. W., P. J. Doherty, B. Ferreira, C. Keenan, G. McPher-
son, G. Russ, M. Samoilys, and W. Sumpton. 1994. Growth,
reproduction and recruitment of Great Barrier Reef food fish
stocks. Final report to the Fisheries Research and Development
Corporation, FRDC Project 90/18, Queensland Department of
Primary Industries, 154 p. Southern Fisheries Centre, GPO
Box 76. Deception Bay, Queensland 4508, Australia.
106
Fishery Bulletin 102(1
the new moon. Therefore, the timing of the proposed spawn-
ing closures seems appropriate. However, it is not known
whether L. carponotatus aggregate to spawn; therefore the
goal of protecting spawning aggregations might not be rel-
evant for this species. In fact, the prevalence and ecological
importance of spawning aggregations for any species on
the GBR is largely unknown; therefore the efficacy of the
proposed closures is difficult to predict.
Beyond the implications for management regulations,
these data have implications for modeling L. carponotatus
stock dynamics. In particular, the results suggest that
reproductive output by a unit of L. carponotatus biomass
cannot be predicted on the basis of that biomass alone.
Relative ovary weight increases slightly with increasing
body size and there is evidence that larger fish spawn more
frequently. The greatest difference in the proportion of ripe
ovaries between size classes occurred in February 1998 af-
ter severe flooding in January. It is possible that the lower
proportion of ripe ovaries among small fish in February was
due to stresses caused by changes in salinity or increased
run-off and is not a regular trait. However, increased resil-
ience to environmental stresses that allows more frequent
spawning would also increase the relative reproductive
success of large fish. Therefore, a population comprising
fewer larger fish is likely to show greater annual egg pro-
duction than a population with equivalent biomass that
comprises more numerous but smaller fish. Additionally,
the sex-specific patterns reported in this study further
suggest gross biomass might be an inadequate index of
replenishment potential and that female biomass needs
to be considered. Therefore, stock structure, in terms of
sex ratio and the frequency of size classes, and not simply
overall biomass needs to be considered when predicting
reproductive potential.
Acknowledgments
I thank the numerous assistants who participated in
fieldwork, as well as Sam Adams and Sue Reilly for assis-
tance with histological examinations. The manuscript was
greatly improved by comments from Howard Choat, Carl
Walters, Tony Fowler, Campbell Davies, Sam Adams, Bruce
Mapstone, an anonymous thesis examiner, and two anony-
mous reviewers. This work was conducted while the author
was supported by an international postgraduate research
scholarship from the Commonwealth of Australia and a
postgraduate stipend from the CRC Reef Research Centre.
Final preparation of the manuscript took place while the
author was supported by a postdoctoral fellowship funded
jointly by the University of Windsor and the Canadian
National Science and Engineering Research Council (col-
laborative research opportunity grant no. 227965-00) to
Peter Sale and others).
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108
Abstract— The increase in harbor seal
(Phoca vitulina richardsi) abundance,
concurrent with the decrease in sal-
monid [Oncorhynehus spp.) and other
fish stocks, raises concerns about the
potential negative impact of seals on
fish populations. Although harbor seals
are found in rivers and estuaries, their
presence is not necessarily indicative
of exclusive or predominant feeding in
these systems. We examined the diet
of harbor seals in the Umpqua River,
Oregon, during 1997 and 1998 to indi-
rectly assess whether or not they were
feeding in the river. Fish otoliths and
other skeletal structures were recov-
ered from 651 scats and used to identify
seal prey. The use of all diagnostic prey
structures, rather than just otoliths,
increased our estimates of the number
of taxa, the minimum number of indi-
viduals and percent frequency of occur-
rence C^FO) of prey consumed. The
*7fFO indicated that the most common
prey were pleuronectids, Pacific hake
(Merluccius produetus), Pacific stag-
horn sculpin [Leptocottus armatus),
osmerids. and shiner surfperch (Cyma-
togaster aggregata ). The majority ( 76%)
of prey were fish that inhabit marine
waters exclusively and fish found in
marine and estuarine areas (e.g. anad-
romous spp. ) which would indicate that
seals forage predominantly at sea and
use the estuary for resting and opportu-
nistic feeding. Salmonid remains were
encountered in 39 samples (6%); two
samples contained identifiable otoliths,
which were determined to be from Chi-
nook salmon (O. tshawytscha). Because
of the complex salmonid composition in
the Umpqua River, we used molecular
genetic techniques on salmonid bones
retrieved from scat to discern species
that were rare from those that were
abundant. Of the 37 scats with salmo-
nid bones but no otoliths, bones were
identified genetically as chinook or coho
(O. kisutch) salmon, or steelhead trout
(O. mykiss) in 90'? of the samples.
Examination of the foraging habits of
Pacific harbor seal (Phoca vitulina richardsi)
to describe their use of the Umpqua River, Oregon,
and their predation on salmonids
Anthony J. Orr
Adria S. Banks
Steve Mellman
Harriet R. Huber
Robert L. DeLong
National Marine Mammal Laboratory
Alaska Fisheries Science Center, NMFS, NOAA
7600 Sand Point Way NE
Seattle, Washington 98115
E-mail address (for A. J. Orr, contact author) tony.orr gnoaa.gov
Robin F. Brown
Oregon Department of Fish and Wildlife
2040 S E. Marine Science Drive
Newport, Oregon 97365
Manuscript approved for publication
9 October 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:108-117 (2004).
The Pacific harbor seal (Phoca vitulina
richardsi) is found along the west coast
of North America from the Aleutian
Islands, Alaska, to the San Roque
Islands. Baja California (King, 1983;
Reeves et al., 1992). Before the pas-
sage of the Marine Mammal Protection
Act (MMPA) of 1972, harbor seals in
Oregon were kept at relatively low
numbers (fewer than 500 animals in
1968) because of bounties offered by the
state and harassment from commercial
and sport fishermen (Pearson and Verts,
1970). Since passage of protective leg-
islation, harbor seals in Oregon have
increased an average of 6^ to 7% annu-
ally between 1978 and 1998, although,
in recent years, numbers appear to
be leveling at about 8000 individuals
(Brown and Kohlmann. 1998).
The rapid increase in harbor seal
numbers has revived fishery-manag-
ers' interest in seal diet because of the
potential for increased consumption of
commercial fish species. In addition,
there has been a heightened concern
about greater harbor seal abundance
in rivers and estuaries during migra-
tions of depressed salmonid popula-
tions because of the potential negative
impact on the recovery of these fishes
(NMFS, 1997). Because of the tenuous
status of many salmonid (Oncorhyn-
ehus spp. I species along the west coast,
the National Marine Fisheries Service
( NMFS ) recommended that the United
States Congress modify the MMPA to
allow lethal removal of seals from river
mouths where they may prey on de-
pressed salmonid populations (NMFS.
1997 ). Predation of salmonids by harbor
seals in Oregon has been documented
(Brown, 1980; Harvey. 1987; Brown
et al., 1995; Riemer and Brown, 1997;
Beach et al.1). The proportion of salmo-
nids in the diet of harbor seals varied
from 1% to 30'r depending on area,
season, and sampling method (NMFS,
1997).
Pinniped prey consumption can be
determined from direct observations
in some systems, if prey is consumed at
1 Beach, R.. A. Geiger. S. Jefferies. S. Treacy,
and B. Troutman. 1985. Marine mam-
mals and their interactions with fisheries
of the Columbia River and adjacent waters,
1980-1982. NWAFC (Northwest Alaska
Fisheries Science Center) processed rep.
NWAFC 85-04, 316 p. NWAFC, National
Marine Fisheries Service, Seattle, WA,
98115.
Orr et al.: Foraging habits of Phoca vitulma richardsi in the Umpqua River, Oregon
109
Pacific Ocean
A
N
the surface (Bigg et al., 1990); however,
consumption is typically determined by
examining scat (fecal) samples. In the
past, species-specific sagittal otoliths
found in scats were used exclusively
to determine the identification of prey
taxa. However, because otoliths can be
partially or completely digested, or are
not present in scats (because the head of
the prey was not consumed ), they are not
always an adequate representation of di-
et. Recently, investigators have begun to
use additional structures (e.g. cranial el-
ements, vertebrae) recovered from scats
to identify prey (e.g. Olesiuk et al., 1990;
Cottrell et al., 1996; Riemer and Brown,
1997; Browne et al., 2002; Lance et al.2).
These structures usually are more com-
mon than otoliths and frequently can be
identified to species; however, bones of
some species can be identified to family
only (e.g. salmonids). Consequently, the
National Marine Mammal Laboratory
(NMML) collaborated with the Conser-
vation Biology Molecular Genetics
Laboratory (CBMGL; Northwest Fish-
eries Science Center, Seattle, WA) to
develop molecular genetic identification
of salmonid species (Purcell et al., 2004).
Because of the complex salmonid species
composition in the Umpqua River, genetic identification
was vital to distinguish species that were rare from those
that were abundant.
The original impetus of this study was to assess the
impact of harbor seal predation on the recovery of the
Umpqua River sea-run cutthroat trout (O. clarkii) that
were listed as endangered under the Endangered Species
Act (ESA) during 1996 (Johnson et al., 1999). Umpqua
River cutthroat trout were removed from the ESA in 2000
because they were identified to be part of the larger Oregon
Coast evolutionary significant unit (U.S. Fish and Wildlife
Service, 2000). The present study was continued despite
the "delisting" of cutthroat trout because the Umpqua is
inhabited year-round by harbor seals that haul out sev-
eral kilometers upriver and is, thus, ideal for determining
whether the presence of a pinniped species within a sys-
tem is indicative of substantial feeding on fish species of
concern within that environment. In addition, the Umpqua
River contains several other salmonid species whose status
is precarious (NMFS, 1997). Therefore, the development of
genetic identification techniques was considered valuable
for this system, as well as for future foraging studies in
which species-specific identification may be desirable but
impossible by way of conventional identification methods.
Oregon
L mpquu River
hauiouts
2 Lance, M., A. Orr, S. Riemer, M. Weise, and J. Laake. 2001.
Pinniped food habits and prev identification techniques pro-
tocol. AFSC Proc. Rep. 2001-04, 36 p. AFSC, NMFS, NOAA.
7600 Sand Point Way NE, Seattle. WA 98115.
Figure 1
Map of the lower section of the Umpqua River, Oregon, where scat samples were
collected at two haulout sites during 1997 and 1998.
The objectives of this study were 1 ) to determine by an
examination of diet if harbor seals that haul out in the
Umpqua River feed primarily in the river or elsewhere,
and 2) to apply genetic techniques to identify salmonid
prey species.
Materials and methods
Study area
The Umpqua River, located in southern Oregon ( Fig. 1 ). is
a natal river for sea-run cutthroat trout, as well as chinook
(O. tshawytscha), coho (O. kisutch) salmon, and steelhead
trout (O. mykiss). The Umpqua estuary is also inhabited
year-round by approximately 600-1000 harbor seals and
has been designated as an area where pinnipeds and sal-
monids significantly co-occur (NMFS, 1997). Scat samples
for this study were collected from two hauiouts located
within 4.8 km of the river's mouth and within 1.6 km of
each other (Fig. 1).
Scat collection and analysis
Samples were collected during two seasons: "spring"
(March through June) and "fall" (August to December).
"Spring" corresponded to the migration of anadromous
cutthroat trout adults and some juveniles to the ocean and
"fall" coincided approximately with the freshwater return
of spawning anadromous adults. The migratory and spawn-
110
Fishery Bulletin 102(1)
Table 1
Collection dates of harbor seal scats and numbers of scats wi
th identifiable prey remains, without
identifiable remains
and without
remains from the Umpqua
River, Oregon,
during 1997 and
1998
Fall and spring
periods
correspond
to timing
of cutthi
oat trout
runs on the Umpqua River.
Collection dates With identifiable remains
Without
dentifiable remains
Without remains
Total
Fall, 1997
16-23 Sep
26
1
2
29
27 Sep-6 Oct
5
0
3
8
12-24 Oct
31
0
7
38
31 Oct-lONov
21
0
6
27
12-25 Nov
36
0
10
46
Total
119
1
28
148
Spring 1998
24-25 Mar
27
5
2
34
13-15 Apr
59
5
7
71
26-27 Apr
45
4
4
53
13-14 May
41
0
4
45
27-28 May
12
0
1
13
11-12 Jun
35
2
1
38
Total
219
16
19
254
Fall 1998
5-6 Aug
142
1
1
144
19-20 Aug
111
1
3
115
6-9 Sep
28
3
3
34
19-21 Sep
13
0
0
13
7-8 Oct
19
0
1
20
Total
313
5
8
326
ing periods of chinook and coho salmon, and steelhead trout
also occur during these times.
During fall 1997, all harbor seal scats present at the
haulouts were collected every other day during the day-
time low tide, weather permitting (Table 1). In 1998. bi-
weekly attempts were made to pick a minimum of 50 scats
during low tides at the haulout sites (Table 1). Scats were
collected, placed in individual plastic bags, and frozen for
later processing. At the laboratory samples were thawed
and rinsed in nested sieves (1.0 mm, 0.71 mm, and 0.5 mm
in 1997; 1.4 mm, 1.0 mm, and 0.5 mm in 1998). Fish struc-
tures were dried and stored in glass vials and cephalopod
remains were stored in vials with 70"* isopropyl or ethyl
alcohol.
Prey were identified to the lowest possible taxon by using
sagittal otoliths, skeletal, and cartilaginous remains from
fish and beaks and statoliths from cephalopods. Other in-
vertebrate remains were discarded from analysis because
of the uncertainty of identifying them as primary or sec-
ondary prey. Unknown prey were categorized as "unidenti-
fied" and "unidentifiable" (Browne et al., 2002). Items that
were categorized as "unidentifiable" were excluded from
analyses because they could not be distinguished from
prey already identified in the sample. Otoliths, beaks, and
diagnostic bones were identified by using an extensive ref-
erence collection at the NMML and voucher samples veri-
fied by Pacific Identifications (Victoria, British Columbia).
After identification, otoliths were separated by side (left,
right, or unknown ) and enumerated to determine minimum
number of specific prey. Unique diagnostic structures (e.g.
quadrates, angulars, basioccipitals, vomers) were used for
identification and enumeration offish. Non-unique skeletal
structures such as gillrakers and teeth were used to iden-
tify but not enumerate taxa (i.e. their presence indicated
only a single individual) unless the structures were from
different size classes. Vertebrae were treated like other
non-unique structures; however, for salmon, if the number
of vertebrae reflected more than one individual, then they
were used for enumeration. Cephalopod beaks were sepa-
rated by side (upper, lower, or unknown) and enumerated
to determine number of prey.
To discern where harbor seals were feeding, identified
prey were categorized as those exclusively found in rivers
or estuaries (e.g. gobiids, cyprinids), those found exclu-
sively in marine waters (e.g. gadids, mvxinids), and those
that could potentially be found in either environment (e.g.
anadromous species, osmerids, petromyzontids) by using
Eschmeyer et al. (1983). A seal was considered to feed in
the river-estuary system if all the prey taxa identified in
the scat were definitely or could potentially be found in the
system. For example, a sample containing remains of pea-
mouth chub iMylocheilus caurinus), threespine stickleback
( Gasterosteus aculeatus ), river lamprey iLampetra ayresii ),
and chinook salmon would be classified as a riverine-
Orr et al.: Foraging habits of Phoca vitulina richardsi in the Umpqua River, Oregon
111
estuarine species because these prey items could feasibly
be consumed in the river. It was assumed that the seal was
feeding in the marine environment if a sample contained
exclusively marine prey, such as Pacific hagfish (Eptatretus
stoutti). Pacific hake (Merluceius productus), and rockfish
(Sebastes spp. ). If a scat comprised prey taxa that poten-
tially could be found in a riverine-estuarine system or
marine waters (e.g. salmonids, osmerids), as well as those
found exclusively in marine waters, then it was assumed
that the feeding environment was marine or mixed.
Salmonid skeletal remains were sent to the CBMGL for
species identification. Remains to be analyzed genetically
were selected by number or size (or both) to represent dif-
ferent species or individuals present in each scat. For ex-
ample, if a scat had 95 approximately equal-size vertebrae
(a salmonid has approximately 65 vertebrae; Butler, 1990).
then at least two vertebrae (potentially representing at
least two individuals) were sent for genetic identification.
Also, if a sample had a very large gillraker and three small
vertebrae, then the gillraker and one vertebra were sent
for genetic identification. The size of diagnostic structures
was also used to categorize salmon remains as juvenile or
adult, when possible. The CBMGL identified salmonid spe-
cies by direct sequencing of mitochondrial DNA or analysis
of restriction fragment length polymorphism (Purcell et al.,
2004).
The abundance of prey taxa in harbor seal diet for each
period was described by using the minimum number of
individuals (MNI) and percent frequency of occurrence
(%FO). We compared the effect of including bone on the
number of prey consumed by estimating MNI using the
greater number of right or left otoliths and then again
using all diagnostic skeletal remains. Cephalopod MNI
was estimated from the greater number of upper or lower
beaks. The % FO of prey taxon i was defined as
I°"
%FO,
x 100,
where Oll; = absence (0) or presence (1) of taxon i in scat
k\ and
s = the total number of scats that contained
identifiable prey remains.
The presence of taxon ;' in scat k was determined by using
otoliths and then again using all structures. To account for
variability in diet, point estimates of %FO for a prey taxon
were determined during each sampling period and then
averaged for each season.
Results
Scats
Over 725 scats were collected during all periods. The
number of scats collected with identifiable remains was
119 (99%; n=148) in fall 1997, 219 (93%; ?z=254) in spring
1998, and 313 (98%; n=326) in fall 1998 (Table 1). Of the
651 samples with identifiable prey remains, 605 (93%) con-
tained fish bones, 347 (53%) had fish otoliths, 231 (36%)
contained remains from cartilaginous fish, and 41 (6% ) had
cephalopod beaks. A majority (65% fall 1997, 65% spring
1998, 63% fall 1998) of scats with identifiable remains had
one to three prey taxa present and less than 4% contained
more than ten taxa. Approximately 40 prey taxa, repre-
senting at least 25 families, were identified throughout the
study (Tables 2 and 3).
For nearly all prey taxa, MNI was greater when all skel-
etal remains were identified than when otoliths were used
exclusively (Table 2). For several species, such as Pacific
hake. Pacific herring (Clupea pallasii), and Pacific sardine
{Sardinops sagax), MNI at least tripled when all structures
were used for enumeration (Table 2). For most salmonids,
cartilaginous fishes, three-spine stickleback, Irish lords
(Hemilepidotus spp.), and Pacific mackerel {Scomber ja-
ponicus), no otoliths were recovered; therefore other skel-
etal elements had to be used for identification (Table 2).
For a few prey, such as cyprinids, gobiids, and butter sole
(Isopsetta isolepis), only otoliths were recovered (Table 2).
Foraging habits
The %FO for most prey taxa was greater when all struc-
tures were used than when j ust otoliths were used ( Table 3 ).
The %FO indicated that the prey most frequently con-
sumed were pleuronectids. Pacific hake. Pacific staghorn
sculpin {Leptocottus armatus), osmerids, and shiner surf-
perch (Cymatogaster aggregata). Prey frequently found
in scats included those that were exclusively marine (e.g.
Pacific hake, rex sole (Glyptocephalus zachirus), English
sole (Parophiys vetulus), and myxinids), and those that
occur in both marine and estuarine waters (e.g. Pacific
staghorn sculpin. and shiner surfperch (Table 3] ). Only 24%
of scats were composed entirely of prey taxa that could be
found in riverine-estuarine systems (Fig. 2). Consequently,
a majority of the scats contained prey species that were
exclusively marine (.v=25.3%) or were a mixture of marine
and potentially marine species (x=50.8%\ Fig. 2).
Salmonids
Salmonid remains were found in only 6% (39/651) of the
samples. Five chinook smolts were identified from otoliths
in two samples collected during fall 1997; in the remaining
37 samples, salmonid bones were unidentifiable to species
with conventional techniques. With the cooperation of
CBMGL, we examined 116 salmonid bones using molecular
genetic techniques. Species identification was successful
for 67% (78/116) of the bones and teeth from 90% (35/39)
of the scat samples that contained salmonid structures. In
the four samples that remained unidentified, three con-
tained only a single salmonid bone that failed to produce
any DNA. Most of the other bones where DNA could not be
extracted were small or fragmented and highly digested.
Seventeen of the samples contained chinook salmon bones
(including the two samples with chinook salmon otoliths);
11 contained coho salmon bones, four contained steelhead
trout bones, and three contained bones from two salmonid
112
Fishery Bulletin 102(1)
Table 2
Minimum number of individuals ( MNI ) offish prey derived from sagittal otoliths and all structures retrieved from
harbor seal scats
collected at the Umpqua River during 1997 and 1998. s represents the number of scats with identifiable
remains, na indicates taxon
did not have sagittal otoliths to be used for identification.
Fall 1997(s=119i
Spring
1998(s=219i
Fall 1998(s=313)
MNI
MNI
MNI
MNI
MNI
MNI
Family
Species
otoliths
all structures
otoliths
all structures
otoliths
all structures
Ammodytidae
Pacific sand lance
205
208
317
321
3
7
Bothidae
Pacific sanddab
12
13
9
9
1
2
Clupeidae
American shad
1
2
4
11
1
15
Pacific herring
6
22
3
10
121
345
Pacific sardine
0
0
50
235
39
185
Cottidae
Pacific staghorn sculpin
44
65
25
48
30
85
unidentified cottid
0
0
0
0
0
8
Cyprinidae
peamouth chub
1
1
4
4
4
4
Embiotocidae
shiner surfperch
104
109
209
274
23
104
Engraulididae
northern anchovy
1
3
0
0
1
2
Gadidae
Pacific hake
1
35
10
44
58
199
Pacific tomcod
9
21
19
52
8
26
Gasterosteidae
threespine stickleback
0
1
0
0
0
0
Gobiidae
unidentified gobiid
2
2
1
1
0
0
Hexagrammidae
lingcod
0
1
0
0
1
1
Myxinidae
Pacific hagfish
0
20
0
13
0
61
Ophidiidae
spotted cusk-eel
0
0
4
4
2
2
Osmeridae
unidentified osmerid
42
54
14
41
105
132
Petromyzontidae
Pacific lamprey
na
5
na
89
na
41
river lamprey
na
2
na
1
na
0
Pholididae
saddleback gunnel
3
7
1
3
0
1
Pleuronectidae
English sole
38
41
37
39
75
84
Dover sole
1
4
5
6
27
51
slender sole
1
1
18
24
28
42
butter sole
1
1
15
15
2
2
rex sole
19
44
44
53
96
125
petrale sole
0
0
0
0
1
1
starry flounder
10
17
8
12
6
31
Rajidae
unidentified rajid
na
1
na
7
na
4
Scombridae
Pacific mackerel
0
2
0
3
0
2
Scorpaenidae
Sebastes spp.
0
15
6
19
2
3
Trichodontidae
Pacific sandfish
0
0
0
1
2
3
Zoarcidae
unidentified zoarcid
0
0
0
0
2
2
Salmonidae
coho salmon
unknown
0
4
0
0
0
0
juvenile
0
1
0
4
0
2
adult
0
0
0
1
0
3
Steelhead or rainbow trou
t
unknown
0
0
0
2
0
2
juvenile
0
0
0
0
0
1
chinook salmon
unknown
5
6
0
0
0
3
juvenile
0
5
0
2
0
5
adult
0
1
0
0
0
0
unidentified salmonid
unknown
0
2
0
1
0
2
juvenile
0
1
0
0
0
1
Orr et al.: Foraging habits of Phoca vitulina richardsi in the Umpqua River, Oregon
113
Table 3
Mean percent frequency of occurrence (%FO) of common prey recovered from harbor seal scat samples collected at haulout sites in
the Umpqua River,
Oregon, during 1997 and 1998.
SD indicates standard deviation.
Family
Species
Fall 1997
Spring 1997
Fall 1998
Mean(±SD)
Mean(±SD)
Mean(±SDl
Ammodytidae
Pacific sand lance
12.5 ±8.3
12.6 ±8.3
9.1 ±8.9
Bothidae
Pacific sanddab
11.4 ±7.5
4.1 ±2.5
3.0 ±3.2
Clupeidae
American shad
4.3 ±0.6
13.0 ±2.3
5.3 ±3.1
Pacific herring
16.9 ±13.7
7.3 ±6.9
35.9 ±21.8
Pacific sardine
0
16.1 ±12.2
17.9 ±9.1
Cottidae
Pacific staghorn sculpin
23.9 ±8.5
21.0 ±19.0
11.8 ±4.5
unidentified cottid
16.5 ±20.4
3.2 ±0.7
0.8 ±0.1
Cyprinidae
peamouth chub
3.8
2.3 ±0.6
2.8
Embiotocidae
shiner surfperch
18.2 ±8.2
23.6 ±19.4
7.0 ±2.9
Engraulididae
northern anchovy
5.5 ±3.2
0
2.1 ±2.0
Gadidae
Pacific hake
27.9+9.7
17.0 ±5.7
41.6 ±25.5
Pacific tomcod
15.4 ±7.8
16.1 ±7.0
12.3 ±8.3
Gasterosteidae
threespine stickleback
2.8
0
0
Gobiidae
unidentified gobiid
7.7
1.7
0
Hexagrammidae
lingcod
3.8
0
0.7
Loliginidae
market squid
12.8 ±10.2
3.5 ±1.3
0
Myxinidae
Pacific hagfish
17.5 ±7.9
6.7 ±3.5
16.5 ±9.4
Octopodidae
Octopus rubescens
3.8 ±1.4
8.3 ±2.6
8.4 ±7.0
Ophidiidae
spotted cusk-eel
0
0
0.9
Osmeridae
unidentified osmerid
20.8 ±11.3
14.6 ±8.2
19.5 ±10.0
Petromyzontidae
Pacific lamprey
7.7 ±8.2
20.5 ±10.1
8.2 ±2.9
river lamprey
5.6
3.7
0
Pholididae
saddleback gunnel
14.7 ±16.9
2.6 ±0.3
5.3
Pleuronectidae
English sole
21.9 ±1.7
8.7 ±5.2
17.5 ±12.0
Dover sole
7.4 ±5.9
4.6 ±0.7
13.5 ±13.6
slender sole
0
11.0 ±7.2
14.9 ±14.9
butter sole
3.8
7.2 ±3.7
1.4
rex sole
27.4 ±12.1
14.2 ±9.6
19.9 ±20.5
petrale sole
0
0
0.7
starry flounder
15.8 ±7.4
3.7 ±1.0
5.8 ±1.2
Rajidae
unidentified rajid
2.8
5.0 ±1.6
2.8
Scombridae
Pacific mackerel
3.8 ±1.4
4.6 ±4.0
0.8 ±0.1
Scorpaenidae
Sebastes spp.
15.7 ±8.3
9.1 ±2.6
2.1
Trichodontidae
Pacific sandfish
0
1.7
2.1
unidentifed bothid/
unidentified flatfish
38.5 ±15.9
20.2 ±10.3
14.8 ±2.5
pleui-onectid
Zoarcidae
unidentified zoarcid
0
0
1.4
Salmonidae
coho salmon
unknown
5.8 ±3.6
0
0
juvenile
4.8
3.3 ±2.3
0.7
adult
0
2.4
6.2 ±6.2
steelhead/rainbow trout
unknown
0
2.7 ±1.4
0.7
juvenile
0
0
0.9
adult
0
0
0.9
chinook salmon
unknown
7.6 ±3.5
0
0.8 ±0.1
juvenile
4.0 ±1.1
3.4
3.6 ±3.0
adult
4.8
0
0
unidentified salmonid(s)
unknown
4.3 ±0.6
2.4
0.8 ±0.1
juvenile
4.8
0
7.7
114
Fishery Bulletin 102(1)
species (two with coho and chinook salmon and one with
coho salmon and steelhead trout, Table 2). No cutthroat
trout were identified with conventional or molecular
genetic techniques.
Using otoliths and other diagnostic skeletal struc-
tures, we enumerated at least 54 individual salmonids
in 39 scats (Table 2). All individuals identified as adults
I n =5 ) were coho salmon, except one chinook salmon from
spring 1997. Individual juveniles identified as steelhead
trout (n=l), coho salmon (re=7), chinook salmon («=12),
or unidentified salmonids (/2=2) were present during
all periods. Because of the difficulty of determining
age from size-variable structures such as gillrakers
and teeth, most individuals («=27) were designated as
"unknown age."
Discussion
Investigating diet is essential to assessing the role of
harbor seals in marine and freshwater ecosystems in
order to quantify their interactions with fisheries and
determine their impact on the recovery of endangered
species. All methods used to investigate diet of seals
and other pinnipeds have some limitations (Murie
and Lavigne, 1985, 1986; Harvey, 1989). With scats, it is
assumed that the relative frequency of prey identified
from undigested remains reflects the frequency of prey
eaten (Tollit et al., 1997). However, several investigators
have determined that this assumption may be seriously
biased in several ways (Hawes, 1983; da Silva and Neilson,
1985; Jobling, 1987; Dellinger and Trillmich, 1988; Harvey,
1989; Pierce and Boyle, 1991; Cottrell et al., 1996; Tollit
et al., 1997; Bowen, 2000; Orr and Harvey, 2001). No diet
study can estimate detrimental or lethal impacts to prey
resulting from harassment by pinnipeds. In addition, once
a prey is captured, a seal might consume only the soft
tissue (especially of larger prey), which would not leave
identifiable evidence in scats. Additionally, because skel-
etal remains from different prey species pass through the
alimentary canal and erode at different rates they may not
reflect the true number or proportions of prey consumed
(Hawes, 1983; Harvey, 1989; Pierce and Boyle, 1991;
Cottrell et al., 1996; Tollit et al., 1997). Therefore, preda-
tion estimates determined from scat samples should be
regarded as a measure of minimum impact. Although there
are complications inherent in the use of scats to describe
the diet of seals, scat analysis remains useful because
many scats can be collected quickly, with minimum effort
and without harm to the animals (Harvey, 1989).
Scats
Recently, skeletal remains other than otoliths and beaks
have begun to be used to identify and enumerate prey of
pinnipeds (e.g. Olesiuk et al., 1990; Cottrell et al., 1996;
Riemer and Brown, 1997; Browne et al., 2002). There are
constraints, however, for using all skeletal elements to
identify prey species, including the need for a reference col-
lect ion and the extensive training of personnel to identify
Fall I9M7
Q
nverine-estuanne
marine or mixed
Scat categorization
Figure 2
Mean percentage plus standard deviation (SD) of scats that
were classified as "riverine-estuarine" (i.e. samples composed of
prey taxa that are exclusively or potentially (e.g. anadromous
species, osmerids) found in rivers or estuaries), "marine" (i.e.
samples composed exclusively of prey that inhabit marine
waters l, and "marine or mixed" (i.e. samples composed of prey
taxa exclusively found in marine waters or those that might
inhabit marine waters at some stage in their life).
digested prey structures (Cottrell et al., 1996). Moreover,
there is usually a bias in the recovery and recognition of
prey structures from different taxa (Cottrell et al., 1996;
Laake et al., 2002). This bias may be a significant problem
in estimating relative abundance of prey or biomass con-
sumption by harbor seals and is the reason these indices
were not considered in this study.
Despite these complications, the use of all available
structures increased our estimates of prey diversity, MNI,
and % FO for most prey taxa. Examination of all diagnostic
structures also allowed us to consider a greater sample size
because 93% of scats with identifiable remains contained
bones, whereas only 53% of scats contained otoliths. Spe-
cies not represented by otoliths, such as salmonids (during
1998) and cartilaginous fishes, were detected because all
structures were used. In addition, the MNI of important
prey such as Pacific hake. Pacific herring, and Pacific sar-
dine would have been greatly underestimated had otoliths
been used exclusively because the MNI derived by using
all structures was at least threefold greater. Although there
are complexities associated with estimating MNI from all
structures, this method avoids the use of numerical correc-
tion factors determined from recovery rates of otoliths fed
to captive seals during laboratory experiments (Browne
et al., 2002). Results from captive experiments are highly
variable between repeated trials for the same individual
and among different individuals (Harvey, 1989; Bowen et
al., 2000; Orr and Harvey, 2001 1,
Foraging habits
Harbor seals in the lower Umpqua River consumed prey
from over 35 taxa; however, only a few prey taxa were
dominant in their diet, as reflected by %FO. Overall, the
five most abundant families of prey were Clupeidae, Cot-
Orr et al.: Foraging habits of Phoca vitulina nchardsi in the Umpqua River, Oregon
115
tidae, Embiotocidae, Gadidae, and Pleuronectidae. These
are similar to those reported in other studies of harbor
seal diet in Oregon (Riemer and Brown, 1997; Browne et
al., 2002; Riemer et al.3-4).
It was evident by the presence of prey like Pacific hake.
Pacific sardine, hagfish, and various flatfishes that seals
fed offshore in pelagic and demersal areas. Harbor seals
also consumed prey (e.g. Pacific staghorn sculpin) com-
monly found inshore or in estuarine waters. The NMFS
recommendations to remove pinnipeds from systems where
endangered prey also occur, rely on the assumption that
pinnipeds are primarily feeding (on ESA-listed species)
in that system. Our study indicated that this was not the
case. Although the seals at the Umpqua hauled out several
kilometers up river, they foraged primarily at sea.
Because of the life histories of many of the prey taxa, our
foraging habitat categories must be considered estimations
of where the prey might have been consumed. For example,
we estimated that 24% of scats contained prey attributable
to the riverine-estuarine environment. However, this may
actually be an overestimation because some of these spe-
cies potentially inhabit the marine environment at some
time in their life and may have been consumed there. Ad-
ditionally, scats categorized as marine or mixed may reflect
that the seal fed solely in the marine environment (because
all the taxa can potentially be found in marine waters) or
fed at sea and within the river. Nevertheless, these catego-
ries are useful for a broad apportioning of foraging habitat.
Even though we were able to determine that approximately
76% of the scats contained marine and potentially marine
prey taxa, we were unable to assess whether this reflected
a seal population with homogeneous or heterogeneous for-
aging patterns. In other words, because the scats could not
be attributed to a particular individual, we had no way of
discerning: 1) whether the entire seal population foraged
roughly three-fourths of the time at sea and one-fourth of
the time in the river, or 2) whether 76% of the seals fed at
sea whereas 24% foraged closer to shore and in the river.
This distinction may be important if only a subgroup of
seals is feeding in the river and preying on fish that are
seasonally abundant in the estuary, such as salmonids.
Studies that incorporate radio- or satellite-telemetry or
genetic identification of individual prey items in scats may
reveal these distinctions in the future.
Because the seals haul out almost 5 km upriver and
have been observed as far as 32 km upriver, it is clear that
3 Riemer, S. D., R. F. Brown, and M. I. Dhruv. 1999. Monitoring
pinniped predation on salmonids in the Alsea and Rogue River
estuaries: fall. 1997. //; Pinniped predation on salmonids: pre-
liminary reports on field investigations in Washington, Oregon,
and California, p. 104-152. Compiled by National Marine
Fisheries Service, Northwest Region. [Available from ODFW,
7118 NE Vandenberg Avenue, Corvallis, OR 97330.]
4 Riemer, S. D., R. F. Brown, and M. I. Dhruv. 1999. Monitoring
pinniped predation on salmonids in the Alsea and Rogue River
estuaries: fall, 1998. In Pinniped predation on salmonids: pre-
liminary reports on field investigations in Washington, Oregon,
and California, p. 153-188. Compiled by National Marine
Fisheries Service, Northwest Region. [Available from ODFW.
7118 NE Vandenberg Avenue, Corvallis, OR 97330.]
seals use the river environment. However, the prevalence
of marine fish remains in the scat samples indicates that
the seals that haul out at the Umpqua River do not feed
exclusively in the river. The predominance of marine prey
may reflect a foraging strategy in which the effort required
to find marine sources of food is offset by the energy gained
by exploiting large aggregations of marine schooling fish
(e.g. Pacific hake and Pacific sardine). In this scenario,
the seals in the Umpqua estuarine-riverine system may
depend on marine resources while taking advantage of
protected estuarine waters that provide a sheltered place
to rest and occasionally feed.
Salmonids
We used two methods to estimate the number of salmonids
eaten by harbor seals: prey remains and genetic analyses
of scat samples. Analysis of skeletal remains was of lim-
ited value because the majority of salmonid structures
recovered from scat samples were bones, which could be
identified only to family. This study represents a novel
application of genetic techniques to identify salmonid spe-
cies from bones found in scats. These techniques allowed us
to determine species for a majority of the salmonid samples
that would have otherwise remained unidentified because
they did not contain otoliths.
Salmonid bones or otoliths were found in 6% of the har-
bor seal scats collected during our study — a finding that is
comparable to the 5% found by Laake et al. (2002) at the
Columbia River. However, it is about one-half of what was
found by Riemer and Brown ( 13% ; 1997 1 at selected sites
in Oregon. Brown et al. (1995) found salmonids in 12% of
gastrointestinal tracts of harbors seals taken incidentally
by commercial salmon gillnet fishing operations, and Roffe
and Mate (1984) observed that salmonids made up 30% of
the prey for harbor seals surface feeding in the Rogue Riv-
er. Regardless of sampling method, in these studies, most of
the salmonids could be identified only to family because few
otoliths were recovered and genetic techniques to identify
bones to species had not yet been developed.
Salmonids are present in the Umpqua River year-round
although species and age composition change throughout
the year. In this study, most salmonid prey of known
age were juveniles; however, we could determine age of
only one-half of the individuals. Juveniles are found in the
Umpqua River system year-round and may be easier for
seals to catch than adults. Alternatively, perhaps seals did
not consume many adult skeletal elements because adult
salmonids are large fish, which may be ripped apart rather
than swallowed whole.
Our sampling seasons encompassed at least some por-
tion of the migrations of all salmonids, all of which (except
cutthroat trout ) were prey of harbor seals. The fact that
portions of all migrations were included in the sampling
design was noteworthy because there were a large num-
ber of seals in the river throughout the year and yet we
found no evidence through genetic or otolith identification
that seals consumed cutthroat trout in the Umpqua River.
The genetic identification tools developed and applied in
our collaboration with CBMGL were useful in discerning
116
Fishery Bulletin 102(1)
scarce from abundant salmonids. These techniques may
be useful in identifying other pinniped prey that lack spe-
cies-specific structures and would allow managers to better
assess the impact of pinniped predation on threatened or
endangered species.
Acknowledgments
This study was proposed and initiated in collaboration
with Joe Scordino. Scat collection and harbor seal counts
were conducted by Lawrence Lehman, Kirt Hughes, Mer-
rill Gosho, Sharon Melin, and Robert DeLong. The U.S.
Coast Guard Umpqua River Station provided boat storage
and a location for keeping a chest freezer during the 1997
field season. We would like to thank the Oregon Institute
of Marine Biology, Charleston, OR, where the samples col-
lected during 1997 were processed. We greatly appreciate
the collaboration with Conservation Biology Molecular
Genetics Laboratory, which resulted in the identification
of our salmon remains based on genetic methods. We would
also like to thank Susan Reimer who kindly helped us with
difficult identifications, as well as Lawrence Lehman and
Jason Griffith for their verification of bone and otolith
identifications. We thank Patience Browne, Patrick Gearin,
John Jansen, Mark Dhruv, and three anonymous review-
ers for providing helpful comments on earlier drafts of this
manuscript.
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118
Abstract— Larval development of the
sidestriped shrimp ^Pandalopsis dis-
par) is described from larvae reared
in the laboratory. The species has five
zoeal stages and one postlarval stage.
Complete larval morphological charac-
teristics of the species are described and
compared with those of related species
of the genus. The number of setae on
the margin of the telson in the first and
second stages is variable: 11+12, 12+12,
or 11+11. Of these, 11+12 pairs are most
common. The present study confirms
that what was termed the fifth stage
in the original study done by Berkeley
in 1930 was the sixth stage and that
the fifth stage in the Berkeley's study
is comparable to the sixth stage that
is described in the present study. The
sixth stage has a segmented inner fla-
gellum of the antennule and fully devel-
oped pleopods with setae. The ability to
distinguish larval stages of P. dispar
from larval stages of other plankton can
be important for studies of the effect of
climate change on marine communities
in the Northeast Pacific and for marine
resource management strategies.
Larval development of the sidestriped shrimp
(.Pandalopsis dispar Rathbun)
(Crustacea, Decapoda, Pandalidae)
reared in the laboratory
Wongyu Park
School of Fisheries and Ocean Sciences
University of Alaska Fairbanks
Juneau, Alaska, 99801-8677
E-mail address: wparkig'uaf edu
R. Ian Perry
Pacific Biological Station,
Fisheries and Oceans
Nanaimo, British Columbia, V9R 5K6, Canada
Sung Yun Hong
Department of Marine Biology
Pukyong National University
Pusan, 608-737, Korea
Manuscipt approved for publication
23 June 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:118-126 (2004).
Sixteen species of the genus Pandalop-
sis have been recognized in the South-
western Atlantic and North Pacific
Oceans (Komai, 1994; Jensen, 1998;
Hanamura et al., 2000). Most members
of the genus attain a large body size
and are valuable as commercial fishery
resources (Holthuis, 1980; Baba et al.,
1986). In the North Pacific, P. dispar,
P. ampla, P. aleutica, P. longirostris, P.
lucidirimicola, and P. spinosior have
been reported. Of these, Pandalopsis
dispar is an important component of the
commercial shrimp fisheries along with
several species of the genus Pandalus.
Commercial landings of shrimp during
1999 totaled approximately 19 million
tonstPSMFC, 1999).
Knowledge of the life histories of
these species, including the duration
and growth of their larvae, is important
for stock assessment and management.
However, remarkably little is known
about their early life histories because
most species of the genus live at con-
siderable depths. Of the 16 Pandalopsis
species, the larvae of only three species
have been described partly or com-
pletely from plankton samples or from
larvae reared in the laboratory. The
larvae of Pandalopsis japonica were
described completely from specimens
reared in the laboratory by Komai
and Mizushima (1993). Kurata (1964)
described the first stage of P. cocci nata
from plankton samples and from larvae
hatched in the laboratory. Thatje and
Bacardit (2000) assumed that larvae of
P. ampla occurring in Argentine waters
were similar to those of P. dispar and
Pandalopsis coccinata. Berkeley ( 1930)
described four larval stages of P. dispar
based on samples collected in British
Columbia coastal waters. The first stage
was obtained from ovigerous females,
whereas the larvae of the other stages
were separated from plankton samples.
In addition, the stage described as the
fifth stage was not clearly defined.
In this study, we describe the complete
series of larval stages of P. dispar using
specimens reared in the laboratory.
Materials and methods
Ovigerous females of Pandalopsis
dispar were collected on 25 March
Park et al.: Larval development of Pandalopsis dispor
119
1999 by using a small shrimp
trawl fished at depths of about
40 m near Gabriola Island in
the vicinity of the Pacific Bio-
logical Station, Nanaimo, Brit-
ish Columbia (latitude 49°13',
longitude 123°55'). Water tem-
perature at the collection site
was around 9°C, and salinity
was 29.0<?c The females were
each kept in a 20-L jar with
seawater. The larvae hatched
on 1 April 1999. Hundreds of
larvae hatched from one female.
Of these, one hundred newly
hatched larvae were transferred
into individual 250-mL jars. To
obtain samples for drawing and
descriptions, a total of 150 larvae
from the female were reared in a
20-L jar. Newly hatched Artemia
nauplii were used to feed the
larvae. We used filtered natu-
ral seawater from 40 m depth
without adjusting the water
temperature or salinity. Water
temperature during the rearing
experiments ranged from 8.7°C
to 12.2°C (mean 10.5°C). Salin-
ity during the rearing experi-
ments ranged from 26.0%c to
31.0%f (mean 28.9%o). The water
in each jar was changed daily.
All drawings were made with
a drawing tube attached to a mi-
croscope. Carapace length (CD
was measured with an ocular
micrometer from the posterior
edge of the orbital arch to the
middorsal posterior edge of the
carapace. The anatomical terms
used in this paper are from
Pike and Williamson ( 1969) and
Haynes (1985).
Measurement bars represent 1 mm.
Figure 1
Results
In the complete larval development of Pandalopsis dispar
there are five zoeal stages. In addition, there is one post-
larval stage. The duration of each larval stage and the
survival rate of P. dispar are shown in Table 1.
Larval description
First stage
Carapace (Fig. 1A) Carapace length (CL), 1.6 mm (SD:
0.06 mm, n=89); with concave lateral margin; rostrum long.
well developed and directed forward and upward; weak
Table 1
Duration
of each larval stage of Pandalopsis dispar at
8.7-12.2°C (mean 10.5°C) and 26.0-31.0%
(mean28.9%c).
Stage 6 is a postlarval
stage.
Mean duration
Range
Number of
Stage
(day)
(day)
]
arvae observed
1
10.7
9-15
89
2
8.9
8-11
81
3
9.5
8-14
67
4
10
9-12
59
5
10.8
10-13
51
6
10.5
9-12
48
120
Fishery Bulletin 102(1)
dorsal denticles and bare ventral tubercles on rostrum;
rostrum about 0.7 times as long as carapace.
Eyes (Fig. 1 A) Sessile.
Abdomen (Fig. 1A) 5 somites plus telson.
Antennule (Fig. 1, A and B) Peduncle unsegmented with
a strong seta at distromesial margin; outer flagellum with
2+2 short aesthetascs.
Antenna (Fig. 1, A and C) Longer than the whole body
length; flagellum segmented throughout its length; outer-
distal corner terminated with an acute spine and a minute
seta; inner-distal margin 5-segmented with 1, 1, 1, 1, 2
setae; inner margin fringed with 28-29 setae.
Measurement bars represent 1 mm.
Figure 2
Mandible (Fig. 1 D) Asymmetrical; without the same
arrangement of denticles, however, almost the same size;
incisor process not separated from molar process; armed
with several teeth on molar part.
Maxillule (Fig. 1 E) Coxal and basal endite with serially
developed strong spines and multiple setae; endopod with
2+3 terminal setae
Maxilla (Fig. 1 F) Palp with 2, 1, 1, 2 setae; coxal endite with
6 distal setae; basal endite with 8 distal setae; broad scaphog-
nathite with narrow posterior lobes having long naked setae.
First maxilliped (Fig. 1G) Endites separated by shallow
notch and with multiple setae; bilobed epipod; endopod 4-seg-
mented with 6, 3, 3, 4 setae; exopod
with 14 plumose natatory setae;
terminal segment with 3 terminal
spines and 1 subterminal spine.
Second maxilliped (Fig. 1 H) Coxa
with 7 setae; basis with 3 setae; no
epipod; endopod 5 segmented with
5, 5. 2. 4, 4 setae; exopod with 27
plumose natatory setae.
Third maxilliped (Fig. II) Coxa
with 1 seta; basis with 2 setae; endo-
pod 5-segmented with various
number of setae; exopod with 34-36
plumose natatory setae.
Pereiopods (Fig. 1, J— N) 1st pereio-
pod (Fig. 1J) not chelate; 3 long ter-
minal spines on dactylus; dactylus
short; propodus longer than carpus;
exopod without natatory setae;
endopod of 2nd pereiopod chelated
(Fig. IK); chela with numerous
small spines; ischium and carpus of
pereiopods 3-5 (Fig. 1, L-N) longer
than 1st and 2nd ones; propodus
armed with several minute spines.
Pleopods (Fig. lO) Bilobed buds,
not functional.
Telson (Fig. 1 P) Triangular form;
broadened at the end, posterolat-
eral margin with 11 + 12 (12+12.
11+11) marginal spines; each spine
with fine hairs.
Second stage
Carapace (Fig. 2A) CL,2.2mm(SD:
0.11, n=81>: rostrum not strongly
curved upwards; 5-6 prominent
dorsal denticles and 3-4 weak
ventral spines; rostrum shorter
than carapace; supraorbital spine
present.
Eyes (Fig. 2A) Stalked; separated
from carapace.
Antenna (Fig. 2A) General shape
unchanged; longer than that of 1st
Antennule (Fig. 2B) Peduncle 3-
Park et al.: Larval development of Pandalopsis dispar
121
segmented; inner flagellum with
2 distal setae; outer flagellum
with 2, 3, 4, 2 aesthetascs on
inner margin.
Mandible (Fig. 2C) General
shape unchanged; bigger than
that of 1st stage.
Maxillule (Fig. 2D) Coxal
and basal endite with serially
developed strong spines and
multiple setae; endopodite with
2+3 spines; a strong subtermi-
nal seta.
Maxilla (Fig. 2E) Palp with 2,
2, 2, 3 setae; broad scaphogna-
thite with narrow posterior lobe
having a long naked seta; coxal
endite with 6 distal setae; basal
endite with 7 distal setae.
First maxilliped (Fig. 2F) Epi-
pod bilobed; endopod with
3+1, 2+1, 2+1, 3 setae; exopod
unsegmented with 14 plumose
natatory setae.
Second maxilliped (Fig. 2G)
One long and several intermedi-
ate sized spines in basal endite;
endopod 5-segmented; exopod
with 24 plumose natatory setae.
Third maxilliped (Fig. 2H) En-
dopod 5-segmented, armed with
many spines; exopod of 36 plu-
mose natatory setae.
Pereiopods (Fig. 2, I— M) Not
chelate; 1st pereiopod of 4
spines in basal endite; 3 strong
and two weak spines in dactylus
of 1st pereiopod; general shape
unchanged from 2nd pereiopod
through 5th pereiopod.
Pleopods (Fig. 2N) Bilobed
buds, not functional; no seta and
hair on buds; no further devel-
opment from the 1st stage.
Telson (Fig. 20) Unchanged.
Third stage
Measurement bars represent 1 mm.
Figure 3
Carapace (Fig. 3A) CL, 2.7 mm (SD: 0.12, rc=67); longer
rostrum than that of 2nd stage; almost 0.9 times as long as
carapace; rostrum with 5-6 dorsal spines and 1-2 ventral
spines.
Antennule (Fig. 3B) Inner flagellum 2-segmented with
0, 2 setae; outer flagellum 2-segmented with 3+3+3, 3+3
aesthetascs.
Antenna (Fig. 3A) General shape unchanged; longer than
2nd stage.
Mandible (Fig. 3C) Molar and incisor processes present;
incisor process with 6-9 teeth; molar process with heavy
teeth on biting edge.
Maxillule (Fig. 3D) Palp with 2+3 setae; a small subtermi-
nal spine; basal and coxal endite with numerous spines.
Maxilla (Fig. 3E) Protopodite unsegmented; palp with 1, 2,
2, 1+2 setae and with 4 lobes; broad scaphognathite with
narrow posterior lobe bearing numerous setae.
First maxilliped (Fig. 3F) Epipod bilobed; endopod 4-seg-
mented with 4, 2, 2, 2 setae; exopod with 15-16 plumose
natatory setae;
Second maxilliped (Fig. 3G) Coxal endite with an epipod
and a strong spine; endopod 5-segmented with 3, 2, 2, 4, 6
setae exopod with setae.
Third maxilliped (Fig. 3H) Coxal endite with one long and
122
Fishery Bulletin 102(1)
one short spine; basal endite with 2 long and 2 interme-
diate sized spines; endopod 5-segmented with numerous
setae; exopod with 25-26 plumose natatory setae.
Pereiopods (Fig. 3, 1— M) General shape unchanged except
addition of setae.
Pleopods (Fig. 3N) Buds biramous; much longer than that
of 2nd stage.
Uropods (Fig. 30) Biramous; endopod with a fused spine
at distal quarter of outer margin and numerous setae on
inner distal margin; exopod with 4 spines on outer margin
and numerous setae on inner distal margin.
Telson (Fig. 30). With 12 pairs of posterolateral spines
plus a median spine.
,F,I-M,Q,
,B,G,H,N
Measurement bars represent 1 mm
Figure 4
Fourth stage
Carapace (Fig. 4A) CL. 3.1 mm (SD: 0.13. re=59); Rostrum
slightly longer than carapace and directed forward; ros-
trum with 15 dorsal spines and 6 ventral spines.
Antenna (Fig. 4A) General shape unchanged; longer than
that of 3rd stage.
Antennule (Fig. 4B) Much longer inner flagellum than
that of 3rd stage; inner flagellum about 0.9 times as long
as outer flagellum, 2-segmented with 0, 2 setae; outer fla-
gellum 6-segmented with 1, 2, 2, 3, 4 aesthetascs.
Mandible (Fig. 4C) Similar to third stage.
Maxillule (Fig 4D) General shape unchanged except addi-
tion of setae on endites.
Maxilla (Fig. 4E) Palp with 3, 2,
2, 3 setae; endites and scaphog-
nathite added numerous setae.
First maxilliped (Fig. 4F) Expod
with 15 plumose natatory setae.
Second maxilliped (Fig. 4G)
Basal endite with an epipod and
a long spine; exopod with 28-29
plumose natatory setae.
Third maxilliped (Fig. 4H) Ex-
popod with 36-37 plumose nata-
tory setae.
Pereiopods (Fig. 4, l-M) Num-
ber of spines increased.
Pleopods (Fig. 4N) Lobes much
longer than those of third stage.
Uropods (Fig. 40) Endopod
and exopod with numerous setae
on inner distal margin.
Telson (Fig. 40) With 12 pairs
of spines on posterolateral
margin; a pair of lateral spines
at distal third.
Fifth stage
Carapace (Fig. 5A) CL. 3.6
mm (SD: 0.15, re=51); Rostrum
directed forward and upward,
slightly longer than cara-
pace; rostrum with 17-18
dorsal spines and 7-8 ventral
spines.
Antennule (Fig. 5B) Inner
flagellum 3-segmented and
about 0.9 times as long as outer
flagellum: outer flagellum with
2+2+3+3+3+2+3+5 aesthetascs
and distal third 6-segmented.
Mandible (Fig. 5C) More ad-
vanced development than that
of 6th; not much change in biting
surface.
Maxillule (Fig. 5D) General
shape unchanged except addi-
tion of setae on endites.
Park et al.: Larval development of Pandalopsis dispar
123
Maxilla (Fig. 5E) General shape
unchanged.
First maxilliped (Fig. 5F) Exo-
pod with 16 plumose natatory
setae.
Second maxilliped (Fig. 5G)
Exopod with 31-33 plumose
natatory setae.
Third maxilliped (Fig. 5H) Exo-
pod with 46-48 plumose nata-
tory setae.
Pereiopods (Fig. 5, l-M) Is-
chium slightly expanded in first
pereipod.
Pleopods (Fig. 5N) Much more
developed than pleopods of 4th
stage; exopod with 13, 1 setae;
endopod with 6 setae and ves-
tiges of appendix interna.
Uropod (Fig. 50) Exopod with
numerous minute spines on
outer margin
Telson (Fig. 50) Both lateral
margins parallel; 19 termi-
nal spines; 2 pairs of lateral
spines.
Sixth stage
Carapace (Fig. 6A) CL, 4.0 mm
(SD: 0.21, n=48); adult-like.
Antennule (Fig. 6B) Inner
flagellum as long as outer fla-
gellum; inner flagellum with
multisegments; outer flagellum
with numerous segments.
Mandible (Fig. 6C) Incisor part
separated from molar process
and extended anteriorly.
Maxillule (Fig. 6D) 9 terminal
spines on basal endite.
Maxilla (Fig. 6E) Palp with 2, 2,
2, 1+2 spines; broad scaphogna-
thite with narrow posterior lobe
bearing 3 long setae.
First maxilliped (Fig. 6F) Exop-
odite with 4+2, 2, 2 3 long and
1 short spines.
Second maxilliped (Fig. 6G)
spines; vestigial dactylus.
Third maxilliped (Fig. 6H) Propodus armed with many
spines; dactylus with 2 spines.
Pereiopods (Fig. 6, l-M) 1st pereipods with subchelated
terminal segment; 1st pereiopod with slightly expanded
ischium.
Pleopods (Fig. 6N) Endopod and exopod with numer-
ous plumose natatory setae; endopod with epipod almost
adult-like.
Uropods (Fig. 60) Biramous; larger than those of fifth
stage; adult-like.
Measurement bars represent 1 mm.
Figure 5
Basal endite with 2 long
Telson (Fig. 60) Telson with 20 terminal spines and 4
pairs of lateral spines.
Discussion
The first stage larva of Pandalopsis dispar described by
Berkeley (1930) is identical to the larva described in the
present study. However, we found that she overlooked
some important characteristics. She described the first
stage larva as having 24 setae on the margin of the telson.
We found, however, that the number of setae is variable,
and that the larvae have 11+12, 12+12, or 11+11 marginal
124
Fishery Bulletin 102(1)
setae. Of these, 11+12 pairs are more common than the
others.
Berkeley ( 1930) described the fifth stage based on plank-
ton materials. In the present study, what was described by
Berkeley ( 1930) as the fifth stage larva turned out to be the
sixth stage because the larvae of this stage have fully devel-
oped pleopods. Although the larvae of the fifth stage have
somewhat natatory setose on their pleopods, they appear
not to be completely functional. Compared to the larvae of
P. japonica, P. dispar has one more stage than that of P.
japonica. The pleopod development of P. japonica from the
fourth stage to the fifth stage is very obvious, whereas that
off! dispar has another stage and the changes in its fea-
tures between the fourth and sixth stages are easily seen.
Measurement bars represent 1 mm.
Figure 6
The major characteristics of the six larval stages of P.
dispar are summarized in Table 2. This table can be used
for the identification of the larval stages of this species.
Komai ( 1994) reviewed the morphological characters of the
first larval stage of three Pandalopsis spp.: P. dispar. P. coc-
cinata, and P.japonica.The larvae of P. dispar at this stage
are quite different from those of the other two species. The
larvae of P dispar have a triangular telson, whereas those
of P coccinata and P. japonica have a semicircular telson.
The adults of the genus Pandalopsis differ from those of
other pandalid shrimps by having a laminated expansion
on the first pereiopod (Schmit, 1921; Butler, 1980). This
character is also present in larvae of P coccinata and P.
japonica, whereas it is not present in larvae of P. dispar.
From the third stage the is-
chium does indicate expansion,
however, it is not distinctive. It
is assumed that in P dispar. the
expansion should be distinctive
after the larval stages.
In P. coccinata and P. japonica
f ) 'vi_— the ischium of the first pereio-
pod has a laminated expansion;
however, in P. dispar it has no
lamination. The structure of the
ischium of the first pereiopod
can be a diagnostic feature of P.
dispar in addition to the shape
of the telson.
Interspecific variation in the
larval stages of pandalid shrimp
is large, ranging from three to
thirteen stages (Rothlisberg,
1980; Komai and Mizushima,
1993). Haynes (1980, 1985)
assumed that P. dispar might
have seven pelagic stages, or at
least more than four. The pres-
ent study has determined that
P. dispar has five zoeal stages
prior to the juvenile stage.
Pandalopsis dispar is one of
the four principal target species
of shrimp trawl fisheries in both
offshore and inshore areas of
the NE Pacific Ocean (PICES,
2001) but has undergone very
large fluctuations in abundance,
particularly in Alaska where it
was reduced to extremely low
levels during the late 1980s and
through the 1990s. These fluc-
tuations appear to have been
associated first with climate
fluctuations (Anderson, 2000),
and second with intense har-
vesting (Oresanz et al., 1998).
Anderson (2000) has suggested
that pandalid shrimp population
changes are one of the early in-
i i<
Park et al.: Larval development of Pandalopsis dispor
125
Table 2
Major characters of Pandalopsis
dispar larvae.
Characters
Larval stage'
1
2
3
4
5
6 (postlarva)
Antenna Inner
flagellum
One strong
spine
One peduncle
with a few
small spines
2 segments
2 segments
3 segments
Multisegmented
over 14
Outer
Not segmented
Slightly
developed
2 segments
6 segments
7 segments
12 segments
Telson
12+11, 12+12,
or 11+11
10 pairs of
terminal spines,
2 pairs of
uropods
One spine on
each midlateral
margin
2 spines on each
lateral margin
4 spines on each
lateral margin
Pleopod
development
Wide as much
as long
Longer than
wide
Almost
separated lobes
Longer lobes
than those of
stage 3
Lobes separated
completely with
natatory setae
Adult-like, with
many natatory
setae on both
lobes
' Eyes of the first stags
are sessile on carapace, whereas those of the second and later stages are stalked.
dicators of shifts in marine communities in this region.
Orensanz et al. (1998) have suggested it is important to
recognize that crustacean stocks can have multiscale
spatial structures; species have possibly both widely dis-
tributed populations (such as in the oceanic offshore) and
populations with discrete and localized distributions (as
may occur in the nearshore inlets).
The ability to distinguish the larval stages of Pandalopsis
dispar from routine plankton samples is therefore of use
in studying both these problems of population fluctuations
and population distributions. Early identification of trends
in strong versus weak year classes can provide rapid indica-
tions of possible changes in large-scale climate conditions.
Unambiguous identification of planktonic stages of P. dis-
par is also essential for studies of the spatial structure of its
populations, for studies of transport pathways and potential
mixing rates among populations, and ultimately for under-
standing the metapopulation structure of these populations.
This latter point is critical for the development of improved
management approaches, which may include identification
of reproductive refugia (Orensanz et al., 1998).
Acknowledgments
We wish to thank Jim Boutillier and Steve Head for their
support with this study. This study was supported by
the Korea Research Foundation Grant (KRF-2002-013-
H00005).
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Abstract— This study was undertaken
to resolve problems in age determina-
tion of sablefish (Anoplopoma fimbria).
Aging of this species has been ham-
pered by poor agreement (averaging
less than 45%) among age readers and
by differences in assigned ages of as
much as 15 years.
Otoliths from fish that had been
injected with oxytetracycline (OTC)
and that had been at liberty for known
durations were used to determine why
age determinations were so difficult
and to help determine the correct aging
procedure. All fish were sampled from
Oregon southwards, which represents
the southern part of their range. The
otoliths were examined with the aid of
image processing.
Some fish showed little or no growth
on the otolith after eight months at
liberty, whereas otoliths from other fish
grew substantially. Some fish lay down
two prominent hyaline zones within a
single year, one in the summer and one
in the winter. We classified the otoliths
by morphological type and found that
certain types are more likely to lay
down multiple hyaline zones and other
types are likely to lay down little or no
zones. This finding suggests that some
improvement could be achieved by
detailed knowledge of the growth char-
acteristics of the different types.
This study suggests that it may not
be possible to obtain reliable ages from
sablefish otoliths. At the very least,
more studies will be required to under-
stand the growth of sablefish otoliths.
Sources of age determination errors for sablefish
(Anoplopoma fimbria)*
Donald E. Pearson
Santa Cruz Laboratory
National Marine Fisheries Service
1 10 Shaffer Road
Santa Cruz, California 95060
E-mail address Don Pearsom&Noaa Gov
Franklin R. Shaw
Alaska Fisheries Science Center
National Marine Fisheries Service
7600 Sand Point Way NE
Seattle, Washington 98118
Manuscript approved for publication
14 July 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish Bull. 102:127-141 (2004).
Sablefish (Anoplopoma fimbria) are a
valuable groundfish resource off the
west coast of North America. The fish-
ery in California, Oregon, and Wash-
ington is tightly regulated according
to periodic stock assessments. Between
1990 and 1998 landings averaged more
than 8000 metric tons per year and an
average exvessel (retail) value of 12.5
million dollars per year (PFMC, 1999).
Sablefish are distributed in the
northeastern Pacific Ocean from
Baja California to the Bering Sea and
southeast to northern Japan (Miller
and Lea, 1972). Males and females are
sexually mature between 55 and 67 cm,
although there is considerable variation
(Fujiwara and Hankin 1988a; Hunter et
al, 1989). Off Washington, Oregon, and
California, sablefish spawn from Octo-
ber through April and spawning peaks
in January and February. Sablefish are
oviparous, releasing eggs that float
near the surface (Hunter et al., 1989).
After hatching, larvae and juveniles in-
habit surface waters offshore for several
years after which they migrate inshore
and settle to the bottom.
Sablefish are found on the continen-
tal slope and are commercially fished at
depths from 200 to 1400 meters (Leet et
al., 1992). Adult sablefish feed on fish,
cephalopods, and crustaceans (Laidig
et al., 1998). They reach a maximum
length of 102 cm (Miller and Lea, 1972)
and are believed to be a very long-lived
species (possibly 100 years or more).
Many physical features have been
used to age this species, including
scales, finrays, thin-sectioned otoliths,
and broken and burned otoliths, but all
methods have resulted in less than 45%
agreement among readers (Lai, 1985;
Fujiwara and Hankin 1988b; Kimura
and Lyons, 1991; Heifetz et al. 1999).
The broken and burned otolith method
(Chilton and Beamish. 1982) is the
principal method used in aging of the
species in both the United States and
Canada. Typically, age readers agree
on ages less than 50% of the time, and
for fish older than 7 years, agreement
drops to less than 15% (Kimura and
Lyons. 1991).
There have been repeated efforts at
validating sablefish ages and develop-
ing aging criteria. Beamish et al. ( 1983)
successfully used oxytetracycline (OTC )
marking to validate ages and repeated
his experiment in 1995 when additional
marked fish were recovered (MacFar-
lane and Beamish, 1995). Lai (1985)
validated the use of otoliths for aging
sablefish. Fujiwara and Hankin ( 1988b)
examined otolith growth characteristics
to help refine aging criteria. Heifetz et
al. (1999) validated the currently ac-
cepted aging practices and examined
sources of error in the aging of sablefish.
Kastelle et al. (1994) used radiometric
methods to generally validate the aging
criteria currently used. Even with all of
these studies that have validated age
* Contribution 119 from the Santa Cruz La-
boratory, National Marine Fisheries Ser-
vice, Santa Cruz, CA 95060.
128
Fishery Bulletin 102(1)
?8W 126"W 124°W 122 W 120W 118"W 116°W
Figure 1
Map of California and southern Oregon showing the locations ( black dots )
of sablefish sampling and tagging in September and October of 1991.
determinations, independent age readings seldom are in
agreement. This suggests that the methods used to validate
the ages were insufficient to allow development of precise
aging criteria. The lack of reliable age data has made stock
assessments difficult and controversial (Crone et al., 1997 ).
and in addition, accurate aging is needed to support eco-
logical and habitat studies.
In September and October of 1991, a tagging and oxytet-
racycline (OTC) injection study was included as part of a
fish trap survey of the abundance of sablefish in southern
Oregon and California. The purpose of this study was to
attempt, once more, to improve our ability to reliably age
sablefish, thereby improving our ability to manage the
species.
Methods
trarily selected fish at each station, and the rest of the fish
were tagged with blue spaghetti tags. Three of every four
tagged fish were injected intraperitoneally with 30 mg of
OTC per kilogram offish (Beamish et al., 1983) and the
fourth fish was used as a control. A complete description of
the survey can be found in Parks and Shaw ( 1994 ).
A scientist visited the major commercial fishing ports
in California and southern Oregon to make port samplers,
commercial dealers, and fishermen aware of the impor-
tance of the study and to explain handling procedures in
the study. A $50.00 reward was offered for the return of
whole tagged fish.
When a tagged fish was returned, the port sampler
measured it (fork length in mm), determined the sex, and
removed the otoliths. The otoliths were cleaned and stored
in painted glass vials (because the OTC mark was light
labile) with a 5095 ethanol solution.
Capture, tagging, injection, and recovery
In September 1991, the fisheries research vessel Alaska
was chartered by the National Marine Fisheries Service
to conduct a trap survey from Coos Bay, Oregon, to Cortez
Bank, California (Fig. 1). A total of nine sites were visited.
At each site seven strings of ten traps were deployed in
various depths between 250 and 1900 meters. The traps
were retrieved after 24 hours, the catch was removed, and
the traps reset for an additional 24 hours. All the sablefish
were counted, otoliths were removed from the first 20 arbi-
Processing of the otoliths
Two pairs of otoliths were initially selected to develop the
procedures to be used in the study. It was found that the
OTC mark was very faint and upon heating (as required
by conventional age determination methods), the mark
disappeared. Accordingly, we developed a method to
obtain images of the otoliths before and after heating, and
to superimpose the two images of the same otolith; the
first viewed under UV light and, the second, after heating,
under white light.
Pearson and Shaw: Age determination errors for Anoplopomo fimbria
129
OTC Mark
Alignment point
Alignment point
Pasted UV Image
Figure 2
Composite image of a sablefish otolith. The otolith was first viewed under UV light
and an image was captured. It was then baked and a second image was captured by
using white light. Then a small rectangle from the UV image was electronically cut
and pasted on the image of the baked otolith. The fiourescent mark produced by the
OTC appears as a dark line on the UV section. Points on the otolith used for correct
positioning of the pasted section are shown.
The otoliths were embedded in epoxy casting resin. After
the resin hardened, the blocks containing the otoliths were
sliced in half across the dorsoventral axis with a diamond
saw.
Images were captured in a two-stage process. The first
stage used ultraviolet light to reveal the OTC mark, and the
second stage used white light to reveal the growth marks
used for age determination. In the first stage, the room was
completely darkened and an image of the otolith, including
the OTC mark, was captured by using a video camera capa-
ble of capturing images under low light conditions. We used
an ultraviolet lamp which produced a strong beam of light
at 365 angstroms. The otolith was viewed on a compound
microscope using reflected light. The camera and image pro-
cessing system were connected to a PC computer equipped
with a frame grabber card. A version of NIH Image, a pub-
lic domain image processing software (Scion Corporation,
Frederick, MD), was used to process the images.
The embedded otolith was placed on the microscope and
a drop of mineral oil was placed on the surface of the oto-
lith. The limited amount of UV light available to the cam-
era required the use of frame averaging. Usually 30 frames
were sufficient to produce a sharp view of the otolith and
the fluorescing mark. In some cases, the mark was too faint
to allow an image to be captured. When there was sufficient
fluorescence, two composite images were captured, one at
4x and one at 40x.
In the second stage, the same embedded otolith was
placed in a small toaster oven at 270°C and heated for 20
to 25 minutes until it had turned dark brown. This baking
process enhanced the growth rings for visual analysis and
approximated what age readers see using the break and
burn method; however, the latter process results in darker
hyaline zones than those obtained with this method. After
cooling, the otolith was viewed under white light. A second
set of images was then captured. A section of each UV im-
age was then electronically cut and pasted onto the image
captured under visible light. With some experimentation it
was found that the pasted sections could be aligned exactly
over the visible light images, creating a final composite im-
age as shown in Figure 2.
Initial examination of the otoliths
Initially, all OTC-marked otoliths were examined with
knowledge of the year and season of release, but without
any other information about the fish. Composite UV and
white light images were obtained as previously described.
The age reader determined the following: whether or not
the OTC mark was visible; whether the OTC mark was in
a hyaline or opaque zone; the number of annual hyaline
zones visible beyond the OTC mark (and whether or not
the edge was included in the count); edge type (hyaline,
narrow opaque, wide opaque, or unidentifiable), and the
shape of the otolith. In some cases the OTC mark could
not be identified or the mark was too faint to be captured
as a composite image; these specimens were excluded from
subsequent analyses.
130
Fishery Bulletin 102(1)
: v.; - ■*■-■
count from here
Figure 3
Example of an image of a baked sablefish otolith which has been annotated with a
mark. The image is an example of one of the images provided to three researchers in
order to obtain cross-reading comparisons.
Following standard age determination procedures (Chil-
ton and Beamish. 1982), if a hyaline zone was not visible
on the edge between January and March, then the edge
was counted. If a mark was not visible on the edge between
April and May and there was a wide opaque zone, then the
edge was counted as a mark. If a mark was visible on the
edge and the month was after May, the edge was not count-
ed. This procedure is used to properly assign the fish to an
annual cohort. Because the reader was not given the month
of recapture, the ages were adjusted based on the count of
hyaline zones, the month of recapture, and whether the
edge had been counted. This adjustment provided a cor-
rected reader count of annual marks. The corrected count
was compared to the number of annual marks that would
have been present if marks were laid down annually.
Previous experience suggested that there are differ-
ent patterns of sablefish otolith growth. We attempted to
classify and characterize these different types of growth
patterns based on morphology of the otoliths as seen in
cross section. After the otoliths had been examined, we
developed a standard classification scheme of morphologi-
cal classes and types which could be used to classify the
most commonly observed morphological types. The otoliths
were re-examined and reclassified to see if difficulties and
discrepancies in aging were associated with morphological
type. It was hoped that this process could be used to refine
the aging criteria and improve precision.
Because sample size was small, we used a Fisher exact
test (Agresti, 1990) to test for independence of morphological
type versus tendency to over-estimate, correctly estimate, or
under-estimate the number of annual marks. The columns
in the test indicated whether the fish had been over-aged.
correctly aged, or under-aged. The rows in the test were the
four morphological types identified in this study.
Examination of the otoliths by the age readers
To determine how age readers would count the marks on
the otoliths, we selected a subsample of 25 otoliths to be
aged at four West Coast fisheries laboratories. The otolith
selection was based on having good quality images and
otoliths. The images of the baked otoliths (not the compos-
ite images ) were annotated with a mark ( Fig. 3 ). The mark
was placed in a location which could be readily located on
the actual otolith by the readers — on the zone just inside of
the OTC mark. Readers were given the following: a set of
printed images, an electronic file of the images for viewing
on a computer screen, the embedded otolith, the month of
capture, the size and sex of the fish from which the otolith
came, and a set of instructions for examining the otoliths.
Readers were not told where the mark on the image was
placed in relation to where the OTC mark was in order to
reduce bias from readers who may have known when the
fish were injected and recaptured. Readers were asked to
provide the following: the number of annual marks vis-
ible outside the mark on the image, whether the edge was
counted, how confident they were of their readings, and any
comments they might have.
Three readers participated in this analysis, two of whom
had extensive, long-term experience in aging sablefish.
The readings and age determination criteria (including
edge count criteria) were compared to each other and to
the time known to have passed between OTC marking and
recapture.
Pearson and Shaw: Age determination errors for Anop/opoma fimbria
131
Figure 4
Images of four otolith morphological types. (A) Otolith is a wide type, (B ) otolith is a wide,
wedge subtype. (C) otolith is a thick type, and (D) otolith is a thick, wedge subtype.
To determine if age determination difficulties were relat-
ed to sex, size, area of capture, depth of capture, or otolith
morphological type; Fisher exact tests were performed. In
each test, the variables were compared to whether the fish
had been correctly aged, over aged, or under aged.
Results
Recoveries
A total of 2575 fish were tagged at the nine sites, and 368
tagged fish were recaptured. Of the recaptured fish, 284
had been injected with OTC. Of the 284 injected fish, usable
otoliths were recovered from 191 fish; for the remaining
fish, otoliths either were not recovered or were too badly
damaged during removal to be used.
Otolith morphological types
After examination of all the otoliths, "wide" and "thick"
morphological types were identified, and each type had a
"wedge" subtype ( Fig. 4 ). Each otolith in the study was then
classified according to this scheme.
The wide type (Fig. 4A) is characterized by new growth
that steadily increases cross sectional width along
the dorsal and ventral surfaces. In the wedge subtype
(Fig. 4B), initial growth increases the width, but the most
132
Fishery Bulletin 102(1)
recent growth is concentrated on the medial or lateral
surface at the sulcus, decreasing towards the dorsal and
ventral surfaces, resulting in a wedgelike appearance.
The thick type (Fig. 4C) is characterized by new growth
that increases the thickness of the otolith without increas-
ing the cross sectional width, causing the annulii to appear
closely spaced on the lateral surfaces. In the wedge subtype
(Fig. 4D), the most recent growth is concentrated at the sul-
cus and narrows towards the dorsal and ventral surfaces,
forming a wedge shape.
It should be noted that these types and subtypes are not
always clearly defined. It should also be noted that clas-
sification to the subtype is based on the most recent one
or more hyaline zones. A wedge subtype is formed when a
single hyaline zone widens near the sulcus and comes to a
point at the outer edge.
Of the 191 otoliths examined, 63 (33.0%) were classified
as "wide" types, 76 (39.7% ) were classified as "wide, wedge
subtypes," 32 (16.8%) were classified as "thick" types, 5
(2.6%) were classified as "thick, wedge subtypes,' and 15
i 7.99? ), could not be classified by this scheme.
Position of the OTC mark
There was no detectable OTC mark in 22 of 191 otoliths.
The absence of marks appeared to be a random event,
occurring in otoliths from several different recovery years
and equally likely to be found among different sexes, otolith
types, different depths, and locations.
Of the 169 otoliths with detectable marks, the OTC mark
was found in a hyaline zone in 129 otoliths (76.3%), in an
opaque zone in 36 otoliths (21.3%), and could not be reli-
Pearson and Shaw: Age determination errors for Anoplopoma fimbria
133
Table 1
Frequency of otoliths with an OTC mark
appearing on the
edge
versus those with the marks inside the edge. All fish
were
injected between
September and October of 1991.
Mark
Mark
Year
Month
on edge
not on edge
1991
Oct
2
1
Nov
1
3
Dec
4
2
1992
Jan
2
4
Feb
1
6
Mar
7
4
Apr
3
1
May
7
26
Jun
2
Jul
1
7
Aug
1
4
Sep
1
2
Oct
5
Nov
3
Dec
ably determined in four otoliths (2Ac/c) because the marks
were between a hyaline and opaque zone. Of the .36 otoliths
with the mark in an opaque zone, the mark occurred just
after a hyaline zone in four otoliths. In 24 of the 36 otoliths
with the mark in an opaque zone, the mark was on the
edge where it can be difficult to determine whether it is
opaque or hyaline. In no case did the reader indicate that
the mark was in a hyaline zone at the edge and thus the
edge appeared to be opaque in most cases.
The OTC mark occurred on the otolith edge in 30 of the
otoliths recaptured prior to 1993 (up to 16 months after
injection). Examination of the monthly distribution of oto-
liths with marks on the edge ( Table 1 ) indicated that some
fish exhibited little or no otolith growth for substantial
lengths of time.
Otoliths from fish recaptured in 1992 with marks on the
edge (i.e. showing little growth) were examined and classi-
fied by morphological type (Table 2). This examination indi-
cated that the thick type is more likely to have little growth
Table 3
Number of visible hyaline zones occurring after an OTC
mark on otoliths from fish recaptured in 1992. This is
shown by three-month interval to show the progression of
development of the hyaline zones. All fish were injected in
September and October of 1991.
Interval
No. of hyaline zones
0 1 2
Jan-Mar
12 8 1
Apr-Jun
Jul-Sep
Oct-Dec
5 14 4
6 2
3 1
because 32"* of the otoliths with marks on the edge were the
thick type, yet they made up only Y1CA of the otoliths in the
study. Conversely, only 18% of the otoliths with the mark on
the edge were of the wide type; however, they made up 33^
of the otoliths in the study. This trend was not statistically
significant, however, because the P-value was 0.106.
Number of visible hyaline zones
The number of prominent hyaline zones after the OTC
mark for fish recaptured in 1992 at three-month intervals
is shown in Table 3. This distribution shows the otoliths
that had no detectable growth but also shows that a hya-
line zone forms in many fish during the winter. It also
shows that in some fish, a summer hyaline zone is formed;
however, the sample size for October-December was small
and this is a period when a summer hyaline zone would be
expected to be fully visible.
The number of visible and prominent hyaline zones after
the OTC mark for fish recaptured after 1992 (Table 4), com-
pared with the number of zones which should have been
counted, showed that if a reader had counted each of the
prominent hyaline zones as an annulus, the count would
have overestimated the age of the fish. An example of an
otolith with a larger number of prominent hyaline zones
than expected is shown in Figure 5. It should be noted that
a reader would not necessarily have counted each of the
Table 2
Number of otoliths in 1992 with OTC marks on the edge by otolith morphological type. Also shown is
morphological types in the present study. All fish were injected in September and October 1991.
the
overall percentage of the
Otolith type
Wide Wide, wedge
Thick
Thick, wedge
No.
Percent No. Percent No.
Percent
No. Percent
1992 otoliths 4
Otoliths in this study 63
18 10 45 7
33 76 40 32
32
17
1 5
5 3
134
Fishery Bulletin 102(1)
Figure 5
Image of a sablefish otolith having more prominent hyaline zones than should have
been present. The fish was caught after eight months at liberty. A single hyaline zone
should have formed; however, there is a zone on the edge and one midway between
the dark OTC mark.
Table 4
Counts of the number of prominent hyaline zones versus the number of annual hyaline zones that should have been present after
an OTC mark. These counts are for fish recaptured more than 15 months after initial capture. Agreement between counts and
number of expected annual hyaline zones is shown in bold.
Year
Expected number
1993
1994
1995
1996
1997
No. of prominent hyaline zones
10
3
1
3
1
5
1
2
1
1
1
2
1
1
2
Table 5
Percent and number (in parentheses I of sablefish otoliths
with more hyaline zones than were expected, with the
expected number of hyaline zones (correct count), and with
fewer hyaline zones than were expected for each otolith type.
Otolith type
More
zones
Expected
number
of zones
Fewer
zones
Thick 10.3% (3) 41.4%(12) 48.3% ( 14 1
Thick, wedge 0 (0) 40.09! (2) 60.09! (3)
Wide 39.39! (22) 48.29! (27) 12.5% (7)
Wide, wedge 35.29! (25) 45.19! (32) 19.79! (14)
prominent hyaline zones as an annulus (they might have
considered them to be checks). In many of these otoliths,
there were less prominent zones that were not counted and
which were interpreted as checks.
Thick type otoliths and thick, wedge subtype otoliths
tend to have fewer visible hyaline zones than expected
(Table 5). In contrast, wide type and the wide, wedge sub-
type otoliths are more likely to have more hyaline zones
than expected. The Fisher exact test yielded a significant
P-value of 0.001.
Blind comparisons of reader counts
A comparison of the counts of annual hyaline zones for each
reader to the expected number of annual hyaline zones
Pearson and Shaw: Age determination errors for Anoplopoma fimbria
135
Table 6
Comparison of number of annual hyaline zones
by reader 1 versus the expected number of annua
zones that should have been counted. Agreement
expected counts are shown in bold.
counted
hyaline
with the
Expected count
Reade
• 1 count
1 2 3
4
5
6 7
1
2 7 2
1
2
2 4
1
1
3
1
1
4
2
5
1
Table 8
Comparison of number of annual hyaline zones counted
by reader 3 versus the expected number of annual hyaline
zones which should have been counted. Agreement with
the expected counts are shown in bold.
Reader 3 count
Expected count 1 2
3 4 5 6 7
1 10 2
2 2 1
3 1 1
4 2
5 1
3 1 1
Table 7
Comparison of number of annual hyaline zones counted
by reader 2 versus the expected number of annual hyaline
zones that should have been counted. Agreement with the
expected counts are shown in bold.
Reader 2 count
Expected count 12 3 4 5
6 7
1 5 2 3 1
2 3 2 2
3 1 1
4
5 1
1
1
1 1
after the OTC mark are shown in Tables 6, 7, and 8. In
these tables, it is assumed that the readers should not have
counted the zone in which the OTC mark occurred because
that mark is presumed to have formed in the summer of
1991. Readers 1 and 2 tended to overestimate, whereas
reader 3 (the least experienced age reader) had generally
good agreement. Reader 1 agreed with the expected count
24% of the time, reader 2 agreed with the expected count
4% of the time, and reader 3 agreed with the expected count
44% of the time. The result for reader 3 is deceptive, how-
ever, because that reader did not follow accepted methods
of when to count the edge.
Reader 1 and reader 2 agreed on whether to count the
edge of the otolith in 24 of 25 otoliths (Table 9). Reader 3
agreed with reader 1 on whether to count the edge in 16 of
25 otoliths and 17 of 25 otoliths with reader 2. Had reader
3 followed accepted practice, agreement with the expected
count would have been much less.
Efforts to determine what factors (depth of capture, loca-
tion of capture, sex, size of the fish, and otolith morphologi-
cal type) resulted in a miscount of the true number of an-
nual marks were inconclusive. We first corrected the count
for the fact that all readers counted the mark in which
the OTC mark had occurred by subtracting one from their
counts, and we then eliminated the readings from reader
3 because of his lack of experience and anomalous age de-
termination criteria. Then we examined the relationship
of how many otoliths had been over-aged, correctly aged,
and under-aged to the above factors. Depth of capture was
divided into two groups: less than 600 m and 600 or more
m. Location was divided into two groups: north and south
of latitude 39 north. Sizes were divided into two groups:
<55 cm FL and ;>55 cm FL. And finally, we tested each of
the four otolith morphological types.
We used Fisher exact tests to determine the probability
that differences were due to chance alone. There were no
detectable differences from the null hypothesis for depth,
sex, or location of capture (Table 10); however, there was
some evidence that fish length and otolith morphological
type might be related to miscounting. Small fish showed a
slightly greater tendency to be over counted (more rings
than should have been present) than larger fish (P=0.150).
Otolith morphological type showed some departure from
randomness: thick types appeared to be more likely to be
undercounted (fewer rings than should have been pres-
ent) and wide types were more likely to be over counted
(P=0.066).
Discussion
Position of mark
There was no visible mark on 22 of the 191 otoliths ( 11.5%).
Beamish et al. ( 1983 ) reported that 14 of 129 OTC-injected
fish ( 10.9%) had no detectable mark. They attributed this to
improper handling of the fish after recapture. The similar-
ity in the number of otoliths failing to show the OTC mark
between their study and our study suggests that some
portion of the population may not absorb sufficient OTC to
produce a visible mark.
The finding that most of the OTC marks were in a
hyaline zone is important. This indicates that many of
the sablefish in our study laid down a prominent hyaline
zone in the summer. Age readers who conventionally as-
sume that an annual mark is laid down only in the winter
136
Fishery Bulletin 102(1)
Table 9
Blind reading results of 25 s
ablefish otoliths by 3 readers. All fish had been captured and injected with OTC in
September
and Octo-
ber of 1991. The counts thev providec
are the number of annual marks
outside of the OTC mark
"Expected
count"
indicate
s how
many winter hya
ine zones
should have been present.
The columns labeled "Edge'
refer to whether or not the edge
was
included
in the age reader'
s counts.
Fish ID no.
Recapture date
Expected count
Reader 1
Reader 2
Reader
3
Count
Edge
Count
Edge
Count
Edge
10375
4 May 92
1
2
Y
2
Y
N
10030
14 May
92
1
1
Y
2
Y
N
10267
17 May
92
1
2
Y
3
Y
N
10408
17 May
92
1
2
Y
2
Y
Y
10417
18 May 92
1
2
Y
3
Y
N
10630
25 May
92
1
4
Y
4
Y
N
12148
26 May 92
1
3
Y
4
Y
N
12176
26 May
92
1
2
Y
5
Y
N
12431
26 May
92
1
2
Y
2
Y
Y
10568
29 Jul
92
1
1
N
2
N
N
11121
lOct
92
1
2
N
6
N
N
11117
16 Oct
92
1
3
N
4
N
N
10400
12 Jan
93
2
3
Y
5
Y
3
Y
10370
14 Jan
93
2
4
Y
4
Y
3
Y
10870
15 Feb
93
2
2
Y
7
Y
5
Y
10246
15 Apr
93
2
3
N
3
Y
3
Y
11735
16 May
93
2
3
Y
3
Y
2
Y
11586
18 May
93
2
2
Y
4
Y
4
Y
11106
3 Aug
93
2
3
N
3
N
1
N
10617
2 Dec
93
2
5
N
5
N
1
N
10580
23 Mav
94
3
2
Y
4
Y
2
Y
10714
9 Dec
94
3
5
N
3
N
1
N
11516
3 Aug
95
4
4
N
7
N
1
N
11524
16 Dec
95
4
4
N
6
N
1
N
11761
25 Apr
96
5
3
Y
5
Y
3
N
Table 10
Comparison of the
lumber offish under counted.
correctly counted, and over counted by two
experienced age readers versus depth
of capture, location
( north
or south of 39 degrees
latitude),
sex, fork length
and otolith moi
•phological type. The P-value
from the
Fisher exact test is
shown
indicating the level of
significance.
LInder counted
Correctly counted
Over counted
P
Depth
<600 meters
7
14
15
0.987
>600 meters
3
6
5
Location
South
4
8
10
0.606
North
3
12
7
Sex
Male
3
2
5
0.381
Female
7
18
15
Length
<55 cm
4
1 1
15
0.150
255 cm
6
6
5
Otolith type
Thick
4
2
2
0.066
Thick, wedge
1
1
0
Wide
2
5
11
Wide, wedge
3
12
7
Pearson and Shaw: Age determination errors for Anop/opoma fimbria
137
Figure 6
Image of a baked sablefish otolith with an electronically pasted section taken from
an image captured under UV light. The dark OTC mark is clearly located within a
hyaline zone, and the hyaline zone persists through the entire otolith. The fish was
injected with OTC on 5 October 1991.
would probably mis-age these fish. Because the age read-
ers who examined the otoliths without knowledge of the
recapture information were not informed that the point
they were counting from was just inside the summer mark,
it was interesting to note that all three of them counted
the hyaline zone in which the OTC mark had occurred as
an annual hyaline zone in all cases. In other words, the
summer hyaline zone did not appear to be a check to the
readers. The readers indicated that the manner of prepa-
ration of the otoliths (embedded and baked) was not the
manner in which they were accustomed to view otoliths
and may have influenced their results. The fact that the
hyaline zones were not as dark with the baking method
as opposed to the burning method may have influenced
the readers age estimates; however, some otolith burns
can be quite light and experienced readers recognize the
various levels of burning, particularly when cross reading
otoliths from other age readers. Readers sometimes use
multiple sections and are free to manipulate the otolith
to improve viewing, which was not possible in the present
study. Beamish et al. (1983) indicated that when readers
knew how many marks to look for, they were able to iden-
tify false annual marks (checks). According to their study, a
check is not persistent throughout the otolith. In Figure 6,
the hyaline zone in which the OTC mark appeared clearly
persists throughout the otolith. If the hyaline zone which
contained the OTC mark began to be laid down in the win-
ter, then there would be very little time for the formation
of a wide opaque zone to form after injection in the fall.
Because the age readers counted the hyaline zone in which
the OTC mark occurred, they clearly assumed that it was
not a check. If the age readers had known that the hyaline
zone (in which the OTC mark occurred) had formed in the
summer, then they presumably would not have counted
it. It is therefore of interest to see the effect on agreement
between reader counts minus the hyaline zone where the
OTC mark occurred and the actual number of hyaline
zones that should have been present. When we adjusted the
reader counts by subtracting one year from their original
counts and compared their adjusted counts to the expected
number of annual marks (Table 11 ), agreement for readers
1 and 2 improved, whereas it decreased for reader 3 (the
least experienced reader).
Also of importance is the fact that on some otoliths, even
after eight months at liberty, no growth had occurred, as
evidenced by the fact that the OTC mark was on the edge.
For example, otoliths from two fish, recaptured after eight
months at liberty showed marked differences in otolith
growth ( Fig. 7 ). On otolith A there was no detectable growth
with the OTC mark on the edge, whereas on otolith B there
was substantial growth. The OTC marks on both otoliths
were very prominent. These otoliths came from similar fish;
that is, otolith A came from a 597-mm female fish caught
in 680 meters of water at 40°52' latitude, and otolith B
came from a 610-mm female fish caught in 480 meters of
water at 41°54' latitude. This provides strong evidence
that otolith growth, and presumably fish growth, varies
greatly among individual sablefish. Beamish et al. (1983)
reported that the OTC mark was on or near the edge in
28 otoliths (18.1%) of 154 fish which had been at liberty
for two to three years. In a similar time interval, we found
that 34 of 126 (27.0%) had the OTC marks on or near the
edge. Both the finding of a summer hyaline zone and the
differences in growth of the otolith among individual fish
138
Fishery Bulletin 102(1)
Figure 7
Images of otoliths from two sablefish showing differences in otolith growth rate. Both
fish were injected with OTC in early October of 1991 and were recaptured in May of
1992. (Al Otolith was from a 597-mm female caught in 680 meters of water at 40°52'
latitude. iBl Otolith was from a 610-mm female fish caught in 480 meters of water at
41°52' latitude. The OTC mark in A was on the edge, whereas the position of the OTC
mark in B is shown on the insert.
are important factors in developing reliable and consistent
age determination criteria.
The importance of using the same age determination
criteria among readers cannot be overestimated. In the
blind comparison, the readers were asked whether they
had included the edge in their count of annual zones. With
standard age determination methods, if no hyaline mate-
rial is visible on the edge up to about May, then the edge is
counted. This procedure is based on the assumption that a
zone is in the process of forming but is not yet clearly vis-
ible. On the other hand, if hyaline material is observed on
the edge after May, it is not counted because it is assumed
to be either a check or the beginning of the next winter's
hyaline zone. Reader 1 and reader 2 (the two most expe-
rienced age readers) agreed on whether to count the edge
96% of the time, indicating that they were using the same
criteria. Reader 3, however, agreed with reader 1 only 64%
of the time and with reader 2 only 68% of the time which
suggests that reader 3 was using different edge-interpreta-
tion criteria.
Pearson and Shaw: Age determination errors for Anoplopoma fimbria
139
Table 11
Percent agreement between number of hyaline zones counted by three age readers and the number which should have been pres-
ent. Also shown is the effect of removing the count of a hyaline zone which formed in the summer and which should not have been
counted as an annual mark.
Reader 1
Reader 2
Reader 3
Original
Corrected
Original
Corrected
Original
Corrected
24%
44%
36%
44%
20%
Effect of ages on stock assessments
Crone et al. (1997) noted that one of the problems with
stock assessments of sablefish is that the size at 50% sexual
maturity is between 55 and 67 cm ( age 5-7 ) and that there
is considerable variability in the these estimates. Further,
they noted that there has been difficulty in determining
age-specific selectivity because of problems with the ages
used in previous assessments. Crone et al. (1997) further
noted that there is a considerable discrepancy in ages
among the age determination laboratories on the west
coast. Finally, the model used to perform stock assessments
has estimated that in order to obtain a good fit with the
data, the actual level of aging error should be higher than
has been reported. The lack of reliable age data has been
used to criticize stock assessments.
Age and length at sexual maturity has been found to
vary substantially by depth (Fujiwara and Hankin, 1988a).
Fujiwara and Hankin found that both males and females
had a length of 550 mm for the length at 50% sexual matu-
rity in shallow water (<600 meters ). In depths greater than
600 m, the size at 50% sexual maturity was 450 mm for
males and 500 mm for females. To determine age, they used
sectioned otoliths and methods that may not have been
directly comparable to the methods used in other studies
or the methods used in the present study; nonetheless, they
found that both males and females matured at a younger
age in deeper water. Saunders et al. (1997) also reported
differences in length at maturity related to depth and loca-
tion of capture. Methot1 found that ontogenetic movement
into deeper water for spawning was more closely related to
age than size. If sexual maturity is more closely related to
age than length as suggested by Methot, then unreliable
ages may explain the variable maturity schedule for sable-
fish. In our study, fish were captured over a 900 nmi range
at depths from 200 to more than 1000 m. If depth is related
to growth of sablefish, then it is possible that the different
morphometric types of otoliths observed in our study may
also be a function of depth. If depth is responsible for the
morphological types, it also suggests that reliability of ages
may be a function of the depth at which the sablefish are
found. Further, if depth influences growth, a fish which
1 Methot. R. D. 1995. Geographic patterns in growth and
maturity of female sablefish off the U.S. west coast. Unpubl.
manuscript, 39 p. NOAA, NMFS, Northwest Fisheries Science
Center, Seattle, WA.
changes its depth over time, may exhibit different patterns
of growth throughout its life which would further compli-
cate the problem of determining reliable ages.
Potential sources of error in this study
This study used sablefish caught in the southern part of
the sablefish range. Many species show latitudinal varia-
tion in growth (June and Reintjes, 1959; White and Chit-
tenden, 1977; Leggett and Carscadden, 1978; Shepherd and
Grimes, 1983; Pearson and Hightower, 1991). It is possible
that the results of this study do not apply to the northern
portion of their range.
Another potential source of error in our study is the effect
of tagging on the growth of the sablefish. MacFarlane and
Beamish ( 1990 ) found that tagged sablefish grew slower
than untagged fish. If this is true, then the results of this
study are much more difficult to interpret. MacFarlane and
Beamish did not use OTC and as a result they based their
ages on conventional aging methods. If they had injected
the fish, it would have been interesting to note whether
the ages for the fish in their study would have been inter-
preted differently. If fish do grow differently after tagging,
many age, growth, and validation studies will need to be
re-evaluated.
Conclusion
Obtaining accurate ages, with reasonable precision, for
sablefish is very difficult. Previous aging studies of sable-
fish have obtained results similar to ours, even when the
readers knew how many annual marks should have been
present (Beamish et al. 1983; MacFarlane and Beamish,
1995). We found that some fish lay down two marks a year
and others may not lay down any. We also found that certain
morphological types of otoliths may be indicative of slow
growing fish and others may be indicative of rapidly grow-
ing fish (assuming otolith growth relates to fish growth).
The fact that agreement among readers or with the cor-
rect age consistently ranges between 30% and 45% sug-
gests that this imprecision may be inherent in sablefish
aging. A substantial fraction of the population may not be
able to be reliably aged: some otoliths do not appear to
grow and others grow very rapidly, laying down prominent
summer hyaline zones that even experienced age readers
cannot differentiate from winter hyaline zones.
140
Fishery Bulletin 102(1)
We believe the wide type and wide, wedge subtypes are
often over-aged, and the thick type and thick, wedge sub-
types are occasionally under-aged and further propose that
readers be made aware that a hyaline zone typically forms
in the winter, but that it is not uncommon for a second
mark to form in the summer.
Another, less desirable approach, would be for age read-
ers to record the morphological type of otolith as a routine
part of aging. Users of the data could then incorporate this
information into their studies by using a correction factor
for fish likely to be under-aged and for fish likely to be
over-aged. This factor could be in the form of an aging error
matrix as suggested by Heifetz et al. ( 1999 ). This approach
may not be practical until more data are available on the
true effect on ages for the morphological types described
in this study, including how many years would need to be
added or subtracted for each type. Finally, a more complete
description of the morphological types would be needed to
assist the age readers.
Acknowledgments
We would like to express our gratitude to Delsa Anderl
(Alaska Fisheries Science Center), Kristin Munk (Alaska
Department of Fish and Game), Shayne MacLellan (Pacific
Biological Station, Canadian Department of Fisheries and
Oceans), and Bruce Pederson (Oregon Department of Fish
and Wildlife) for participating in the otolith blind reading
component of this paper. We would also like to thank Dan
Kimura and Craig Kastelle of the Alaska Fisheries Science
Center for their assistance in developing the design of this
study. We would like to thank Michael Mohr (Southwest
Fisheries Science Center, Santa Cruz, CA) for his valuable
contribution to the statistical analyses used in this study
This study could not have been completed without the sup-
port of Gary Stauffer (Alaska Fisheries Science Center)
who provided funding for the recovery of the sablefish.
Additionally, this study would never have been completed
without the assistance of numerous commercial market
samplers, port biologists, commercial fishermen, and deal-
ers who were responsible for collecting and processing the
sablefish when they were caught. And finally, we would
like to thank William Lenarz (Southwest Fisheries Science
Center, retired) for his support of this study.
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142
Abstract— Life history aspects of larval
and, mainly, juvenile spotted seatrout
tCynoscion nebulosus) were studied
in Florida Bay. Everglades National
Park, Florida. Collections were made
in 1994-97, although the majority of
juveniles were collected in 1995. The
main objective was to obtain life history
data to eventually develop a spatially
explicit model and provide baseline
data to understand how Everglades res-
toration plans (i.e. increased freshwater
flows) could influence spotted seatrout
vital rates. Growth of larvae and juve-
niles (<80 mm SL) was best described
by the equation log, standard length
= -1.31 + 1.2162 (log,, age). Growth in
length of juveniles (12-80 mm SL) was
best described by the equation standard
length = -7.50 + 0.8417 (age). Growth
in wet weight of juveniles (15-69 mm
SL) was best described by the equation
logc wet-weight = -4.44 + 0.0748 (age).
There were no significant differences
in juvenile growth in length of spot-
ted seatrout in 1995 between three
geographical subdivisions of Florida
Bay: central, western, and waters adja-
cent to the Gulf of Mexico. We found a
significant difference in wet-weight for
one of six cohorts categorized by month
of hatchdate in 1995. and a significant
difference in length for another cohort.
Juveniles (i.e. survivors) used to cal-
culate weekly hatchdate distributions
during 1995 had estimated spawning
times that were cyclical and protracted,
and there was no correlation between
spawning and moon phase. Tem-
perature influenced otolith increment
widths during certain growth periods in
1995. There was no evidence of a rela-
tionship between otolith growth rate
and temperature for the first 21 incre-
ments. For increments 22-60, otolith
growth rates decreased with increas-
ing age and the extent of the decrease
depended strongly in a quadratic fash-
ion on the temperature to which the
fish was exposed. For temperatures at
the lower and higher range, increment
growth rates were highest. We suggest
that this quadratic relationship might
be influenced by an environmental
factor other than temperature. There
was insufficient information to obtain
reliable inferences on the relationship
of increment growth rate to salinity
Manuscript approved for publication
23 June 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications ( >ffice.
Fish. Bull. 102:142-155 (2004).
Growth, mortality, and hatchdate distributions
of larval and juvenile spotted seatrout
{Cynoscion nebulosus) in Florida Bay,
Everglades National Park
Allyn B. Powell
Robin T. Cheshire
Elisabeth H. Laban
National Ocean Service
National Oceanic and Atmospheric Administration
Center for Coastal Fisheries and Habitat Research
101 Pivers Island Road
Beaufort, North Carolina 28516
E-mail address (for A. B Powell): allyn powellgnoaa gov
James Colvocoresses
Patrick O'Donnell
Florida Fish and Wildlife Commission
Florida Marine Research Institute
2796 Overseas Highway, Suite 119
Marathon, Florida 33050
Marie Davidian
Room 209, Patterson Hall
2501 Founder's Drive
North Carolina State University
Raleigh, North Carolina 27695
The spotted seatrout (Cynoscion nebu-
losus) is an important recreational fish
in Florida Bay and spends its entire life
history within Florida Bay I Rutherford
et al.,1989). The biology of adult spotted
seatrout in Florida Bay is well known
(Rutherford et al., 1982, 1989), as are the
distribution and abundance of juveniles
in the bay, including a description of the
juvenile habitats and their diets (Het-
tler, 1989; Chester and Thayer, 1990;
Thayer et al., 1999; Florida Department
of Environmental Protection1). The
temporal and spatial distribution and
abundance of larval spotted seatrout in
Florida Bay and adjacent waters, and the
spatial and temporal spawning habits of
these larvae also have been determined
(Powell et al., 1989; Rutherford et al..
1989; Powell, 2003).
The early life history of spotted
seatrout in other south Florida estu-
aries also has been well documented.
Peebles and Tolley ( 1988) described the
distribution, growth, and mortality of
larval spotted seatrout in Naples and
Fakahatchee Bays, and McMichael and
Peters (1989) described the size distri-
bution, growth, spawning, and diet of
spotted seatrout in Tampa Bay.
Information on growth and mortality
of larval and juvenile spotted seatrout
in Florida Bay is lacking. Research on
these topics would enhance our under-
standing of the entire life history of this
valuable species, and in particular aid
in eventually developing a spatially ex-
plicit model for spotted seatrout that is
highly desired by the Program Manage-
ment Committee for the South Florida
Ecosystem Restoration Prediction and
Modeling Program. In addition, these
life history studies could help clarify ju-
venile growth and survival and provide
needed information for the restoration
Florida Department of Environmental
Protection. 1996. Fisheries-independent-
monitoring program. 1995 annual report,
58 p. Florida Department of Environmen-
tal Protection, Florida Marine Research
Institute, 100 8th Avenue SE, St. Peters-
burg, FL 33701.
Powell et al.: Growth, mortality, and hatchdate distributions for Cynoscion nebulosus
143
25°20'
25° 10'
2.V00'
— 24"50'
81 "00'
80"45'
so Mr
Figure 1
Location of sampling sites for spotted seatrout (Cynoscion nebulosus) in Florida Bay,
Everglades National Park, Florida, including Florida Bay Subdivisions.
of the Everglades, including a return of historic freshwater
flows into Florida Bay.
Two conceptual frameworks have been advanced to couple
the role of growth and mortality in influencing cohort dy-
namics. Anderson ( 1988), in a review of hypotheses relating
survival of prerecruits to recruitment, advocated a growth-
mortality hypothesis as a rational framework for early life
history studies that address recruitment variability. This
concept predicts that survival of a cohort is directly related
to growth rates during the early life stages. The growth-
mortality framework, which includes several important in-
tegrated components and is based on bioenergetic principles
of growth and ecological theory that predict growth rate, is
directly related to survival. If it can be demonstrated that
survival is a function of growth during the early life stage,
then a valuable tool becomes available for examining mecha-
nisms influencing recruitment of marine fishes.
Another framework suggests that the mortality rate does
not operate alone in determining stage-specific survival,
but it is the mortality:growth (M:G) ratio (mortality per
unit of growth) that determines stage-specific survival (see
citations in Houde, 1997 ). Houde ( 1997 ) advanced the idea
of using the M:G ratio as an estimator of production and
potential survivorship especially in early life stages when
both mortality and growth are high and variable. This con-
cept was partly based on the strong coupling of growth and
mortality demonstrated by Ware ( 1975 ) who argued that
when growth rate is poorer than average, larvae would be
exposed to sources of mortality over a longer period and
hence their mortality rate would increase. Growth and
mortality values for successive cohorts would tend to form
a cluster of points around a regression of mortality on
growth based on average values for a particular species.
Our intent is not to test the growth-mortality hypothesis
(sensu Hare and Cowen, 1997) as outlined by Anderson
(1988), nor fully to develop the M:G ratio concept (Houde,
1997), but rather to use these concepts as a framework
for our study. The major goal is to provide information on
growth and survival of larval and, mainly, juvenile spotted
seatrout that can ultimately be used to develop a spatially
explicit model that can be linked to Everglades restoration
activities. Therefore, the major objectives of this paper are
1 ) to determine overall growth rates of larval and juvenile
spotted seatrout in Florida Bay; 2) to determine and com-
pare juvenile growth rates geographically; 3) to estimate
natural mortality rates of juveniles; 4) to estimate hatch-
date distributions; 5 ) to compare cohort growth and mortal-
ity rates and G:M ratios for juveniles; and 6) to evaluate
the effects of salinity and temperature on otolith growth — a
surrogate for somatic growth.
Methods and materials
Field collections
Larval fish used for otolith microstructure analysis were
collected from September 1994 through July 1997, mainly
in the Gulf transition, western, and central subdivisions
(Table 1, Fig. 1). These subdivisions designated by the
144
Fishery Bulletin 102(1)
Table 1
Florida
Bay sampling stations where otoliths from spotted seatrout were collected
Included are numbers in > of larvae and juveniles
used in
the otolith microstructure ar
alysis. and subdivisions as defined by the South Florida Ecosystem Restoration Prediction and
Modeling Program, Program Management
Committee.
Station
Latitude
Longitude
Florida Bay
Juveniles
Larvae
numbei
(degrees and minutes)
(degr
ees and minutes)
subdivisions
Location
(n)
in)
1
25 06.81
81 05.27
Gulf transition
Cape Sable
4
2
25 06.37
81 01.42
Gulf transition
Middle Ground
1
10
3
25 06.40
80 58.58
Gulf transition
Conchie Channel
—
4
4
25 07.70
80 56.90
Gulf transition
Bradley Key
119
—
5
25 07.12
80 56.07
western
Murray Key
4
8
6
25 08.11
80 50.95
central
Snake Bight
3
—
7
25 09.45
80 53.42
central
Snake Bight
4
—
8
25 07.50
80 48.51
central
Rankin Lake
12
—
9
25 05.06
80 47.30
central
Roscoe Key
20
—
10
25 02.30
81 .1.12
Gulf transition
Sandy Key
49
—
11
25 02.90
80 55.00
western
Johnson Key Basin
125
—
12
25 06.00
80 52.50
western
Palm Key Basin
110
—
13
25 04.50
80 45.15
central
Whipray Basin
2
62
14
25 08.00
80 43.20
central
Crocodile Point
9
—
15
24 56.70
80 57.20
Gulf transition
Schooner Bank
2
—
16
24 54.70
80 56.31
Gulf Transition
Sprigger Bank
—
8
17
25 00.40
80 47.68
central
Sid Key Bank
6
—
18
24 57.03
80 47.52
central
Twin Key Basin
6
—
19
25 07.98
80 40.48
eastern
Madeira Point
1
—
20
25 11.85
80 37.15
northern
Little Madeira Bay
8
—
21
25 13.00
80 27.80
eastern
Shell Key
5
—
South Florida Ecosystem Restoration Prediction and
Modeling Program, Program Management Committee,
were based on modifications of the benthic mollusc com-
munity (Turney and Perkins, 1972). In 1994 and 1995, we
used 60-cm bongo nets fitted with 0.333-mm mesh fished
from the port side of a 5.4-m boat. Beginning in 1996, we
used a paired 60-cm bow-mounted push net with 0.333-
mm mesh nets similar to that described by Hettler and
Chester (1990).
Juvenile spotted seatrout were obtained from monitor-
ing programs established by the NOAA Center for Coastal
Fisheries and Habitat Research (NOAA) and Florida Ma-
rine Research Institute (FMRI). NOAA collections were
made from May 1995 through September 1997. Juveniles
were collected with an otter trawl towed between two 5-m
boats. The otter trawl measured 3.4 m (headrope) and was
fitted with a 3.2-mm mesh tailbag with 6-mm mesh. FMRI
collections were made in 1995 with a seine and a trawl. The
21.4-m center-bag drag seine was fitted with a 1.8 m x 1.8 m
x 1.8 m bag of 3.2-mm mesh. The 6.1-m (headrope) otter
trawl was fitted with a body of 38.1 -mm stretch mesh and a
3.2-mm mesh tailbag. The majority of juveniles (86ri ) from
NOAA and FMRI collections were collected in 1995.
Otolith microstructure analysis
Otolith processing Otolith removal and preparation gen-
erally followed the methods of Secor et al. (1991). All oto-
liths, except for the right sagitta, were mounted on a slide
with mounting media and archived. The right sagittal oto-
lith was embedded for transverse sectioning or polishing
(or both). The left sagitta was embedded for transverse sec-
tioning if the right was damaged. Sagittae were read with
a light microscope at lOOOx magnification under oil immer-
sion. The first increment was determined as that following
the core increment; which was defined as a well-defined
dark increment surrounding the core (Powell et al., 2000).
Two blind counts of increments were made by one reader
and if the counts differed by more than 5, then the otolith
was read again. If the counts were within the acceptable
range, the two counts were averaged. Based on a previous
validation study (Powell et al., 2000), 2.5 days were added
to the increment counts to obtain the daily age. A total
of 582 sagittal otoliths were aged. This total included 96
from larval collections from September 1994 through July
1997, 139 juveniles from NOAA collections from June 1995
through September 1997, and 347 from FMRI collections
from June 1995 through December 1995.
Increment widths were measured on 347 otoliths from
FMRI collections (1995) by using image analysis. The
measuring path consisted of two segments: a ventral path
from the core to the 21st increment and a ventral-medial
path along the sulcus, from the 21st increment to the edge
(Fig. 2). The 21st increment was selected as the transition
point in these measuring paths by test reading 30 otolith
sections representing the entire range of sample fish
Powell et al.: Growth, mortality, and hatchdate distributions for Cynoscion nebulosus
145
Distal Edae
Ventral
Counting Path 2
(21 days to capture)
Figure 2
Transverse polished section of a spotted seatrout ( Cynoscion nebulosus) ( 18 mm SL; age 48 days) otolith
showing the counting paths.
lengths. In all samples, the 21st increment could easily be
traced in both measuring paths and in all samples the first
21 increments could be measured within the same image.
Increment widths were averaged over a 7-day period. Age
estimates were also obtained and we eliminated any oto-
lith used to measure increment widths if the difference in
total increment count between the two methods ( counts ob-
tained directly from the microscope versus those attained
by image analysis) was greater than 7 days or 10%. On
this basis, 117 otoliths were removed from the increment
width analysis.
We believed counts obtained directly from the microscope
were more accurate than those obtained by summing the
number of increments measured on the computer moni-
tor with the image analysis system. Counting increments
directly through the microscope lens allows the reader to
optically section the otolith (by varying the focus), which
helps in detecting daily increments. "Frozen" multiple im-
ages are a result of using the image analysis; hence optical
sectioning is not possible.
Data analysis Data from all years and sources were used
for 1) overall growth (i.e. larval and juvenile); 2) juvenile
growth; and 3) estimates of juvenile mortality. Data from
NOAA larval and juvenile collections were used to estimate
a body-length-otolith-radius relationship. Data from 1995
FMRI and NOAA collections, which was the most com-
plete data set, were used for growth comparisons between
cohorts, and hatchdate distributions. Data from 1995 FMRI
collections were used for 1) growth comparisons between
geographical subdivisions; 2) estimating a wet-weight-age
relationship to compute the ratio of wet-weight specific-
growth to mortality (G:M ratios), which assesses the rela-
tive recruitment potential of individual cohorts (Houde,
1996; Rilling and Houde, 1999; Rooker et al., 1999); and 3)
determining the influence of temperature on otolith incre-
ment width. We used the FMRI data set exclusively for
the above analyzes because collections were spatially more
localized and wet weights were available.
Natural mortality (M) estimates were derived by regress-
ing log. unadjusted numbers on age classes (5-day bins);
the resulting slope provided an estimate of total mortality
(Ricker, 1975). However, on the basis of the age-frequency
distributions (Fig. 3), we considered juveniles a40 days old
fully recruited to our gear and juveniles >90 days old ap-
peared to avoid our gear. Hence, only juveniles between 40
and 90 days old were used to calculate mortality.
Hatchdate distributions were computed on a weekly ba-
sis and adjustments for mortality were made on individual
juveniles by the equation
N =N,/e-z<,
where N0 = estimated number at hatching;
Nt = number at time t (Nt=l because N0 was calcu-
lated for each individual fish);
Z = instantaneous daily mortality coefficient;
and
t = age in days.
Spotted seatrout cohorts were divided into weekly units,
but comparisons between cohort growth was done on a
monthly basis because of inadequate numbers for weekly
comparisons. A test of heterogeneity of slopes was imple-
146
Fishery Bulletin 102(1)
CJ
^f •* -a- Tt
n 't m to n
CO
■5f
o
CM
o o o o o
co -^- in co r*~
Age class (days)
o
CO
o
CD
Figure 3
Frequency distribution of spotted seatrout
{Cynoscion nebulosus) age classes used in deter-
mining minimum age at full recruitment to the
sampling gear, and mortality.
32
30
I 28
CO
ra 26
a>
Q.
E
CO
merited by using a generalized linear model
(SAS/STAT software, version 6.12, SAS Insti-
tute, Cary, NO to test if growth differed among
cohorts. A general linear test ( Neter et al., 1983 )
was used to compare growth between three geo-
graphical subdivisions (Gulf transition, western,
and central). This test is a function of the error
sum of squares of the reduced model minus the
error sum of squares of the full model. Adequate
numbers of juveniles were not available to com-
pare growth in eastern and northern subdivi-
sions (Table 1). Circular statistics (Batschelet,
1981) were used to determine if spawning, as
determined from hatchdate distributions, was
uniform over the lunar month. The phase of the
moon for 1995 was identified by the fraction il-
luminated (U. S. Naval Observatory Applications
Department, 1997). A 3-point moving average
was used to test if spawning was cyclical.
Cohorts (1995) were categorized according
to the following hatchdates: cohort A, 29 March-2 May
("April"); cohort B, 3 May-6 June ("May"); cohort C, 7
June-4 July ("June"); cohort D, 5 July-1 August ("July");
cohort E, 2 August-5 September ("August"); cohort F, 6
September— 3 October ("September").
Comparisons of the relative recruitment potential of
individual cohorts (G:M ratios) between all cohorts were
unresolved. Although cohort mortality estimates could
be generated, they were appropriate (by analyzing r2 and
P-values from regression analysis) for only three cohorts
(cohorts B, D, and F).
A random coefficient model was used to investigate the
relationship between growth rate of otoliths with age and
24
22
20 -
(I
O
II
4U -
35 -
30 -
<
, *
\
i
\
I
25 -
20 -
15 -
10 -
<
t
5 -
«
»
Station
Figure 4
Mean and ranges of temperature and salinity data by station used in
the otolith microstructure longitudinal analysis (relationship between
increment width and temperature and salinity). For station locations
relative to subdivisions, see Table 1 and Figure 1.
temperature from juveniles collected in 1995. Most fish
were exposed to salinities in a narrow range between 28
and 34 ppt; only 9 fish were exposed to salinities in the 5-13
ppt range (Fig. 4). Consequently, there was insufficient in-
formation to obtain reliable inferences on the relationship
of growth rate to salinity or the relationship to salinity
and temperature for growth information obtained by using
either otolith measuring path. This was a disappointment
because growth responses to salinity were considered an
important objective in relation to proposed Everglades
water management activities. Thus, investigation was
restricted to the relationship of growth with temperature.
A separate model was fitted for the first ( 1-21 increments)
Powell et al.: Growth, mortality, and hatchdate distributions for Cynoscion nebulosus
147
and second (22-60 increments) measuring paths because
otolith increment width changed at a constant (age-inde-
pendent) rate for each path. We did not include fish with
>60 increments because the relationship past this number
was determined for only 10% of the fish and included obvi-
ous outliers. Letting Y be the otolith width measurement
for fish ; at age a , where y indexes time, the model for each
path was
Y,j = «o, + «i
where a0l and «1; are the fish-specific intercept and slope
describing the relationship between increment width and
age for fish i, and e is a normally distributed error term;
thus, ah is the growth rate for fish i over the measuring
path. Temperature exhibited only negligible change for any
given fish over the measuring path; thus, temperature for
fish i was summarized as tr the average temperature over
the path for that fish. To determine an appropriate model
for the relationship between intercept and growth rate
and temperature, a preliminary analysis was performed in
which ordinary least squares estimates of «0; and ah were
obtained separately for each fish i and plotted against tem-
perature. For the first measuring path (1-21 increments),
the appropriate model was
«o, = A)0 + 0oi'i + bor «i, = Pw + Put, + P\4? + bii>
where b0l and bh are normally distributed random effects,
allowing growth rates for fish at the same temperature to
vary across fish. For the second measuring path (22-60
increments), the appropriate model was,
«o, = Poo + /V, + Po-i'r + V «ii = Pw + 0ii'i + Put? + bu-
By substitution, these considerations yielded models 1 and
2 for the first and second paths, respectively;
Y„ = {Poo + fVP + Cfto + 011*1 + 012*^ a„ + bo
blpii+eii
(•Pw + Pnl, + 012^ aa + bo, + bi,a„ + e,j
(1)
(2)
thus representing otolith increment width in each case
as having a straight line relationship with age, where the
slope (age-independent growth rate) depends on average
temperature according to a quadratic relationship. The
random effects allow observations on the same fish to
be correlated, whereas observations across fish are inde-
pendent. Models 1 and 2 were implemented in SAS Proc
Mixed (SAS/STAT software, version 6.12, SAS Institute,
Cary,NC).
Daily temperature records were obtained from the Unit-
ed States Department of Interiors National Park Service,
Florida Bay monitoring stations and averaged over a 7-day
period. In 1995, temperature records were available only
for Johnson Key Basin ( JKB), Whipray Basin (WB), Little
Blackwater Sound (LBS), and Little Madeira Bay (LMB),
but spotted seatrout were also collected at other sites
(Table 1). Daily temperatures were estimated for Sandy
Key (SK) and Roscoe Keys (RK) from values recorded dur-
ing sampling trips because both these stations are not in
close proximity to National Park Service monitoring sites.
Sandy Key values were regressed on JKB values (same
dates). Sandy Key temperatures were collected from Janu-
ary 1994 through August 1996. The regression model for
temperature was SK = 0.76 + 0.9536 JKB [r2=0.89; w=25],
Roscoe Key values were regressed on WB values (same
dates). Roscoe Key temperatures were collected from Janu-
ary 1994 through August 1996. The regression model for
temperature was RK = 5.60 + 0.7976 WB [r2=0.87; n=31).
Temperature values were available at Murray Key (MK) in
1997. To attain values for our 1995 analysis we regressed
MK on JKB (same dates). The temperature regression
model was MK = 0.77 + 0.9680 JKB [r2=0.99; re=342].
We reported measurements in standard length (SL). For
preflexion and flexion larvae, standard length was mea-
sured from the tip of the snout to the tip of the notochord.
For postflexion larvae and juveniles, standard length was
measured from the tip of the snout to the base of the hy-
pural plate.
Results
Overall growth of larvae and juveniles (<80 mm SL) was
best described by the equation log, standar-d length =
-1.31 + 1.2162 (loge age) [«=582; r2=0.97]. Growth in body
length of juveniles (12-80 mm SL) was best described by
the linear equation standard length = -7.50 + 0.8417 {age)
[n=486; /-2=0.84]; hence, juveniles between approximately
age 20-100 days grew on average 0.84 mni/d. There were
no significant differences in juvenile growth in body length
among three geographical subdivisions [F*327=0.756;
n=333] (Table 2), but there was a significant growth differ-
ence in length for one of six 1995 cohorts (Table 3, Fig. 5).
Growth in wet weight of juveniles ( 15-69 mm SL) was best
described by the equation log(, wet weight = -AAA + 0.0748
(age) [n=347, r2=0.84]. There was a significant growth dif-
ference in wet weight for one cohort (Table 4, Fig. 6).
Weekly 1995 hatchdate distributions, determined by us-
ing daily instantaneous mortality ( 0.0585. Fig. 7 ). indicated
juveniles in collections (i.e. survivors) were from spawning
that was cyclical and protracted (Fig. 8). The most intense
successful spawning occurred during 21-27 June (9.2% of
total). Using a 3-point moving average, we observed three
similar cycles (Fig. 8). From data on survivors, -25% of ju-
veniles were spawned by late May, 50% by early July, and
75% by late August and from data on cohorts, three cohorts
(cohorts C, D, and E; early June-late August) comprised
55% of the total estimated spawn of spotted seatrout. There
was no correlation between spawning and moon phase (pe-
riodic regression r2=0.019, P=0.754) (Fig. 8).
The relative recruitment potential (G:M ratio) of the 1995
year class estimated from the wet-weight specific growth
coefficient (0.0748) and the instantaneous daily mortal-
ity rate (0.0585, Fig. 7) was 1.28. The G:M ratio for three
cohorts (B, May; D, July; and F, September) was greater
than the ratio for the total 1995 year class because mortal-
148
Fishery Bulletin 102(11
Table 2
Summary of growth data used to compare
best described by the linear equation: stan
growth ir
dard leng
length of spotted
th = a + b ( age in
seatrout among
days).
three Florida
Bay subc
ivisions. Growth was
Subdivision
Intercept
Slope
n
r-
Size range (mm SD
Gulf transition
-11.07
0.8914
139
0.86
16-69
Central
-12.23
0.9298
49
0.80
15-63
Western
-10.56
0.8834
145
0.85
17-69
Table 3
Summary of statistics for a test for heterogeneity of slopes for cohort somatic growth rates
rized according to month of hatchdate (see text). The base parameter is cohort F and all
the base cohort. For growth equations, see Figure 5.
of spotted seatrout. Cohorts were catego-
parameter estimates are deviations from
Parameter
Estimate
Standard error
/-value
P-value
Intercept
-7.97270
3.02829
-2.63
0.0088
Cohort A
-0.86811
4.31970
-0.20
0.8408
Cohort B
-11.85849
3.91387
-3.03
0.0026
Cohort C
1.65094
3.86470
0.43
0.6695
Cohort D
-6.70820
4.74936
-1.41
0.1586
Cohort E
1.02077
3.50931
0.29
0.7713
Slope
0.82088
0.05613
14.62
<0.001
Cohort A
0.04054
0.08604
0.47
0.6378
Cohort B
0.24578
0.07106
3.46
0.0006
Cohort C
-0.00113
0.07091
-0.02
0.9873
Cohort D
0.15741
0.08730
1.80
0.0721
Cohort E
0.04544
0.06821
0.67
0.5058
Table 4
Summary of statistics
for a
test for heterogeneity of
slopes for cohort wet-weight
growth rate
of spotted
seatrout.
Cohorts were
categorized according
,o month of hatch date (see text ). The
base parameter is cohort F and
all parameter
estimates are deviations
from the base cohort. For growth equations, see
Figure 6.
Parameter
Estimate
Standard error
/-value
P-value
Intercept
-4.27384
0.23763
-17.99
<0.0001
Cohort A
0.10201
0.37014
0.28
0.7830
Cohort B
-0.46348
0.34092
-1.36
0.1749
Cohort C
-0.27866
0.32116
-0.87
0.3862
Cohort D
-0.19540
0.38352
-0.51
0.6108
Cohort E
-0.38260
0.29853
-1.28
0.2009
Slope
0.06974
0.00439
15.88
<0.0001
Cohort A
0.00195
0.00729
0.27
0.7889
Cohort B
0.00679
0.00622
1.09
0.2754
Cohort C
0.00502
0.00575
0.87
0.3835
Cohort 1)
0.00759
0.00702
1.08
0.2808
Cohort E
0.01188
0.00564
2. 11
0.0359
Powell et al.: Growth, mortality, and hatchdate distributions for Cynoscion nebulosus
149
Cohort A
Length = -8.84+0 8614 (Age)
60
40
20
0
20
60
Cohort B
Length = -19.83 + 1.0667 (Age)
F
B0
^ = 0.80
F
n = 57
<9
en
60
o
'O
a>
40
% o<g>
•n
nftri'™
20
--?-:
c
m
rn
40
80
100
Cohort C
i Length = -6.32 + 0.8198 (Age)
? = 0.90
B0 | n = 55
40
20
0
80
60
40
20
0
80
60
40
20
0
80
60
40
20
0
Cohort D
Length = -14 68 + 0.9783 (Age)
r2 = 0.80
n = 69
Cohort E
Length = -6.95 + 0.8663 (Age)
^ = 0.89
n =99
20
40
60
Cohort F
Length = -7.97 + 0.8209 (Age)
r = 0.86
n = 50
Age (days)
Figure 5
Comparison of growth in standard length among six spotted seatrout (Cynoscion
nebulosus) cohorts collected in 1995. See text for cohort hatchdates.
Table 5
Daily gr
owth (wet weight in grams)
rates and daily mort
ality rates for three cohorts in Florida Bay in 1995. Cohorts
were
cate-
gorized according to month of hatchdate (see text). The G:M ratio derived from the growth and mortality
rates is also
presented.
For growth equations and associated
r- values, see Figure
6.
Cohort
Hatchdate month
Growth rate
Mortality rate
r2
G:M ratio
Size range (mm SL)
B
May
0.0765
0.0445
0.54
1.72
28-
-62
D
July
0.0773
0.0565
0.82
1.37
37-
-68
F
September
0.0697
0.0354
0.67
1.97
37-
-66
ity rates appeared relatively low compared to the overall
mortality rate (0.0585) for juveniles (Table 5). However,
differences in mortality rates among these three cohorts
were not significant (F4.;i=1.414). There were no significant
differences in weight-specific coefficients among the three
cohorts (B, D, and F) (Table 4), but a significant difference
in length-specific coefficients among the three cohorts was
found (Table 3). Cohort B (May) had a significantly higher
growth rate than the other two cohorts.
There was a close relationship between otolith radius and
body length (Fig. 9). A linear equation with the sagittal ven-
tral radius, had a similar r2 as a curvilinear equation with
the sagittal dorsal radius. However, we were unable to mea-
sure increment widths along this plane and instead used a
combination of a ventral path and a ventral medial path.
As an initial demonstration that otolith increment width
increased with age along the 1-21 increment measuring
path and decreased along the 22-60 increment path, simpli-
150
Fishery Bulletin 102(1)
2 !
1
o
-1
-2
-3
Cohort A
Loge weight =
-4.17 + 0-0717 (age)
20
40
Cohort B
Loge weight
z2 = 0.88
n = 47
60
80
100
: -4.74 + 0.0765 (age)
20
40
60
80
100
Cohort C
Loge weight = -4.55 + 0.0748 (age)
^ = 0.94
n = 47
JM
o^°^
o
20
40
60
80
100
Cohort D
Log B weight = -4.47 + 0.0773 (age)
^ = 0.81
n = 61
20
40
60
80
100
3
2
1
0
-1
•2
-3
-4
20
Cohort E
Loge weight = ^1.66 + 0.0816 (age)
? = 0.85
n = 66
40 60 80 100
Cohort F
Log e weight = -4.27 + 0.0697 (age)
f2 = 0.86
n = 47
20
40
60
80
100
Age (days)
Figure 6
Comparison of growth in wet-weight (grams) among six spotted seatrout \Cynoscion
nebulosus) cohorts collected in 1995. See text for cohort hatchdates.
fieri versions of Equations 1 and 2 ( see above ) were fitted, in
which all coefficients of temperature were set equal to zero,
so that Equations 1 and 2 represent simple linear relation-
ships with age. For the first path, the estimate of slope was
0.153 fjm/d (P<0.0001); that for the second path was
-0.065 fim/d (P<0.0001>. Addition of quadratic terms to
each model was not supported (P=0.81 and 0.12, respec-
tively). For the first path, whether intercept or growth rate
were associated with temperature was determined by test-
ing whether the parameters j301, /3n, and j312 were equal to
zero. There was no evidence that any of these parameters
were different from zero (P=0.45, 0.35, and 0.42, respec-
tively); the latter two may indicate that the data do not
support the contention that growth rate depends on tem-
perature in this range (1-21 d). For the second path, tests
"I /'„ ,=0 and /i12=0 offered strong evidence that these pa-
rameters are different from zero (P<0.001 in each case). In
particular, these results suggested for the age range 22-60
d, otolith growth rates decrease. The extent of the decrease
is strongly associated with average temperature according
to a quadratic relationship such that growth rates were
more steeply decreasing with age for lower temperatures
and then became shallower at higher temperatures. In
summary, for temperatures at the lower and higher end of
the observed temperature range, otolith growth rates for
the age range 22-60 d were higher than they were in the
middle of the observed temperature range.
Discussion
Growth in body length of juvenile spotted seatrout in Flor-
ida Bay was faster than growth of juveniles from Tampa
Bay (Table 6, McMichael and Peters, 1989). Florida Bay is
generally considered an oligotrophic system (Fourqurean
and Robblee, 1999). Nevertheless, seagrass beds in west-
ern Florida Bay, where juvenile spotted seatrout are most
common (Chester and Thayer, 1990), are significantly
more dense than beds in northwestern Florida waters,
slightly north of Tampa Bay (Iverson and Bittaker, 1986).
Increased growth of juveniles in Florida Bay could be
attributed to the dense seagrass beds that provide habitat
for epifaunal crustaceans (Holmquist et al., 1989; Mathe-
son et al., 1999), which are important in the diet of juve-
Powell et al.: Growth, mortality, and hatchdate distributions for Cynosaon nebulosus
151
5.0 -
Log, abundance = 6.83 -0.0585 (age)
^ = 094
4.5 -
n n= 10
4.0 -
^^^\
8 3.5-
c
CO
T3
§ 3.0 -
.a
CO
Cu
g1 2.5 -
_j
^^\. 0
2.0 -
\
1.5 -
o
^f ^f -^ Tf r}-
■3- in cd h~ co
o o o o o
^f in cd r^. co
Age class (days)
Figure 7
Catch curve of juvenile spotted seatrout (Cynoscion nebulosus) used to
estimate daily instantaneous mortality (Z). Z = slope = -0.0585. Spotted
seatrout were fully recruited to the gear at age 40-44 days.
Comparison of spotted seatrout growth (size
Florida Bay, Florida (this study).
Table 6
in mm SL at age) betw
;en Tampa Bay.
Florida (McMichaels and Peters,
1989) and
Age (days)
Area 10 20
30 40
50
60 70
80
90
Tampa Bay 5.1 10.2
Florida Bay 4.4 10.3
15.3 20.3
16.9 23.3
25.4
31.4
30.5 35.6
39.2 47.2
40.7
55.6
45.8
64.1
nile spotted seatrout (Hettler, 1989; McMichael and Peters,
1989). Additionally, warmer water temperatures have been
observed in Florida Bay (Boyer et al., 1999) compared to
Tampa Bay (McMichael and Peters, 1989); these warmer
temperatures could enhance growth if adequate food is
available (Warren, 1971). However, our study and that of
McMichael and Peters ( 1989) were quite a few years apart;
hence differences that we observed could also be accounted
for by interannual variability. In addition, differences in
growth could also be attributed to differences in sampling
gear between the two studies.
Florida Bay is a heterogenous ecosystem and consists
of ecologically distinct regions (Phlips and Badylak, 1996;
Fourqurean and Robblee, 1999); however, we did not de-
tect any differences in growth of juvenile spotted seatrout
among our three subdivisions. In general, juvenile collec-
tions from the central subdivision were from stations that
were spatially dispersed; whereas, juvenile collections in
the western and Gulf transition subdivisions were from
relatively few stations (Table 1 ). Normally, the central sub-
division is characterized by the highest salinities in the bay
and the western and the Gulf transition are characterized
by high salinities (Orlando et al., 1997). However, in our
study, salinities in the three subdivisions were moderate
and similar (Fig 4). and growth rates estimated for the
three subdivisions could be useful as baseline rates, par-
ticularly in the central subdivision where salinities are
commonly hyperhaline (Orlando et al., 1997).
The spawning habits of spotted seatrout throughout
their entire range are generally similar. They have a
protracted spawning season, are multiple spawners, and
reach sexual maturity at an early age. Initiation of spawn-
ing might be temperature dependent, with water tempera-
tures between 20° and 23°C necessary to initiate repro-
ductive development (Brown-Peterson and Warren, 2001).
Hatchdate distributions calculated for spotted seatrout in
152
Fishery Bulletin 102(1)
Birthweek
Figure 8
( Al Spotted seatrout {Cynoscion nebulosus) («=417) weekly
hatchdate distributions adjusted for mortality, including
moon phases (#=new moon; 0=full moon), and 3-point
moving average (solid line) of hatchdate distributions. (B)
Cumulative frequency of spotted seatrout (n=417) hatch-
date distributions.
Florida Bay in this study along with early stage larval
collections (Powell, 2003) indicate that spotted seatrout
spawn between March and October (based on hatchdate
distributions) and that the majority of spawning occurs
between 27° and 35°C , with very little spawning between
20° and 26°C (based on early stage larval collections).
Spawning peaks, based on larval collections in 1994-96,
occurred in June, August, and September (Powell, 2003),
and early May, late June, and late August through early
September based on 1995 hatchdate distributions (this
study). However, Stewart (19611 reported that spotted
seatrout in Florida Bay spawned throughout the year and
that spawning peaked in spring and fall. Another larval
fish study in Florida Bay indicated that some spawning
occurs as early as February and continues into December
(Rutherford et al., 1989).
Loge Body length = -1 .64 + 0.7821 (dorsal radius)
? = 0.99
n = 232
80 -i
60
40
20 -
E
1 ' 1 ' 1 ' 1 ' ' 1
B> 0 200 400 600 800 1000 1200
Sagittal dorsal radius (microns)
£ 80
CO
(7)
au -i
Body length =
= 0.75 + 0.0503 (ventral radius)
? = 0.99
60 -
n = 232
rffO
40 -
CM§^>
QqAO
20 -
n-
kd
I ' I ' I ' I ' I
0 200 400 600 800 1000 1200
Sagittal ventral radius (microns)
Figure 9
The relationship between sagittal otolith radius
and standard length (top), and sagittal ventral
radius and standard length (bottom) for spotted
seatrout (.Cynoscion nebulosus).
Peak spawning activity of spotted seatrout is highly
variable (McMichael and Peters, 1989; Brown-Peterson and
Warren, 2001). McMichael and Peters (1989) observed two
spawning peaks; spring and summer. Older fish participate
in two peak spawning periods ( Tucker and Faulkner, 1987 ),
and a portion of the larger spring-spawned fish (age- 1+) en-
ter the spawning population during their second summer,
augmenting the number of summer spawning fish.
We found that spawning activity and moon phase were
uncorrelated, which is not in concordance with observations
of McMichael and Peters (1989). They found that distinct
peaks in spawning (based on hatchdate distributions of lar-
val spotted seatrout) occurred at monthly intervals, and this
periodicity might coincide with moon phase. However, this
monthly periodicity was not observed when their data for
juvenile spotted seatrout were examined. Moreover, statisti-
cal tests were not performed on the data in their study.
Powell et al.: Growth, mortality, and hatchdate distributions for Cynoscion nebulosus
153
Our inferences, from this study, in relation to spotted
seatrout peak spawning are based on hatchdate distribu-
tions and should be viewed with caution because hatch-
dates are based on survivors. Differential survival for early
life history stages can bias results. Hatchdate distributions
are valuable when compared to egg or recently hatched lar-
val densities and might suggest processes responsible for
differential cohort survivorship. Because spotted seatrout
undergo a protracted spawning period and because there is
high variation associated with icthyoplankton samples ( Cyr
et al., 1992), intensive and extensive sampling of recently
hatched larvae would be required over a long duration to
answer these process-oriented mortality questions.
The daily instantaneous mortality rate of juvenile spot-
ted seatrout was higher in Florida Bay than those reported
from northwestern Florida systems (Nelson and Leffler,
2001). Mortality rates of juvenile spotted seatrout from
Florida Bay were 5.7%/d; whereas, for the other systems,
rates approximated 3%/d. In general, mortality rates might
increase with increasing estuarine temperatures (Houde
and Zastrow, 1993). Although we were unable to estimate
instantaneous daily mortality rates for larval spotted seat-
rout, these data have been estimated for larvae (3.5-6.5
mm) in two southwestern Florida estuaries (Peebles and
Tolly, 1988). Highly variable rates were reported between
the two Florida estuaries (Naples Bay: 0.70 or 50%/d; and
Fakahatchee area: 0.37 or 31%/d). Houde ( 1996) reported a
generalized instantaneous daily mortality rate for marine
fish larvae of 0.239 (21%/d). Estimating mortality rates for
larval spotted seatrout in Florida Bay will be critical for
calculating G:M ratios in order to evaluate stage-specific
survival and to develop credible spatially explicit models.
Mortality rates of spotted seatrout cohorts could be cal-
culated for only three of six cohorts (B, May; D, July; and
F, September) because slopes were significantly different
from zero for only these cohorts. Furthermore, mortality
rates of two of the three cohorts (B and F) were associated
with low r2 values (Table 5); hence the G:M ratios along
with the mortality rates for these three cohorts should
be considered "rough" estimates. Attaining more accurate
mortality estimates for spotted seatrout would be valuable
in linking cohort variability with potential recruitment and
stage-specific survival. For example, larval cohorts of bay
anchovy [Anchoa mitchilli) from Chesapeake Bay, a tem-
perate estuary, exhibit growth rates that are temporally
variable and mortality rates that are spatially and tem-
porally variable (Rilling and Houde, 1999). Temperature,
zooplankton prey and gelatinous predators are believed to
influence growth and mortality rates of the bay anchovy.
For striped bass iMorone saxatilis ) in a subestuary of Ches-
apeake Bay, cohorts exhibited highly variable seasonal G:M
ratios that were strongly influenced by temperature
(Houde, 1997). In a subtropical estuary, cohort-specific
mortality rates for juvenile red drum varied temporally;
early and late season cohorts exhibited the highest mortal-
ity rates, which coincided with highest growth rates and
G:M ratios for midseason cohorts (Rooker et al., 1999). We
agree with Houde ( 1997) that future research should focus
on the variability and causes of variability in growth and
mortality, both of which interact to determine stage-spe-
cific survival. The developmental stage or age where G:M
variability is greatest, along with the relationship of this
variability to recruitment, need to be determined for spot-
ted seatrout in Florida Bay. No doubt a relationship exists
between G:M ratios and recruitment. Future research
should also determine if cohort G:M ratios and somatic
growth rates are seasonally or spatially variable. If they
are, then a limited spatial and temporal sampling program
could be designed to annually evaluate G:M ratios at highly
variable stages or ages as an index of year-class strength
of spotted seatrout in Florida Bay. Such an index could be
verified by examining year-class catch rates on an annual
basis or by virtual population analysis.
In our study there was little temporal difference in
growth of juvenile spotted seatrout cohorts. Larval growth
and mortality, which was not treated adequately in our
study, could be influenced by copepod prey — an important
dietary component of larval spotted seatrout (McMichael
and Peters, 1989). The copepod Acartia tonsa is dominant
in Florida Bay, but egg production rates for this species are
low in the bay compared to those in other systems (Kleppel
et al., 1998). We suspect the "bottleneck" to recruitment of
spotted seatrout could occur during the larval stage. Hence,
future research should examine mortality and growth of
larval and recently settled spotted seatrout; in particular
the patterns of larval production potential (G:M ratios).
Research in these areas should increase our understand-
ing of the degree of variability in stage-specific survival
and recruitment of spotted seatrout in Florida Bay (Houde,
1996).
For most species, especially those with protracted spawn-
ing habits, it is most informative to analyze cohort growth
and mortality. For example, striped bass and bay anchovy
cohorts in Chesapeake Bay exhibit highly variable growth
rates, mortality rates, and stage durations (Rutherford
and Houde, 1995; Rilling and Houde, 1999). This variabil-
ity could cause differential survival for cohorts and result
in frequency distributions of survivor hatchdates that do
not resemble recently hatched larvae or egg-production
frequency distributions (e.g. Crecco and Savoy, 1985; Rice
etal., 1987).
We are unable to interpret the significance of the abso-
lute value of the G:M ratio for juvenile spotted seatrout,
because interannual comparisons were not made, but we
presented the ratio for future comparisons. Generally, the
G:M ratio is <1.0 during the early larval stage, indicating
a decline in biomass. However, the G:M ratio of a cohort
will eventually exceed 1.0 as a result of a relative decline
in mortality as larvae grow (Houde and Zastrow, 1993).
Clearly, stage specific analysis of the spotted seatrout from
egg through juvenile stage would have been more informa-
tive in determining when the maximum G:M ratio occurs
(when cohort biomass increases at a maximum rate) and
in providing insight into stage-specific dynamics of spotted
seatrout (Houde, 1997). A constraint of our study was our
inability to estimate larval mortality rates; hence early life
history stage dynamics could not be examined.
Size-selective mortality in the juvenile life history stages
can have important consequences for recruitment. Sogard
( 1997 ) argued that "within-cohort size-selective mortality"
154
Fishery Bulletin 102(1)
is more evident in the juvenile stage than during the egg
and larval stages when random mortality independent of
fish size is more likely to occur (e.g. dispersal of eggs and
larvae away from suitable nursery areas). In addition, vari-
ation in size, which provides a "template" for size-selective
processes, increases during the juvenile stage as larval size
is constrained by egg size. Sogard ( 1997) cited a number of
recent studies that suggest the early juvenile period plays
a greater role in determining year-class strength than
previously thought.
We were unable to determine if salinity influenced incre-
ment width (a surrogate for somatic growth) at early life
stages. Understanding the relationship between salinity
and growth is critical because Everglades restoration will
most likely result in increased freshwater flows to Florida
Bay, and during low rainfall periods, salinities in the north
central portion of the bay can exceed 45 ppt (Orlando et
al., 1997; Boyer et al., 1999). But, salinities were moderate
and similar at most stations where juvenile trout were col-
lected in the bay during 1995 I Fig. 4). Very few fish were
collected at low salinities; in fact, juvenile spotted seatrout
are not commonly collected at low-salinity stations (Table
1; Florida Department of Environmental Protection1), and
hyperhaline conditions were not observed in 1995. There-
fore, we were only able to determine if temperature could
influence increment widths. The curvilinear relationship
between otolith growth rate and temperature, although
a statistically strong relationship, is difficult to explain
biologically. Temperature could mask other factors, e.g.
temporal variability in prey and predator availability, and
optimal temperatures for growth (Rooker et al., 1999). We
were able to demonstrate that one cohort grew faster than
five other cohorts, possibly indicating differential prey
availability in 1995. An individual-based bioenergetics
model for spotted seatrout now in preparation (Wuenschel
et al.2) should add to our understanding of the effects of
salinity and temperature on larval and juvenile spotted
seatrout
Acknowledgments
We are especially grateful to Al Crosby, Mike Greene, Mike
LaCroix, and other Beaufort staff that participated in the
field work. We thank James Waters of the NMFS Southeast
Fisheries Science Center for computer programing assis-
tance and Jon Hare of our laboratory for performing the
circular statistics. We are grateful to Dean Ahrenholz, Jon
Hare, Patti Marraro, Joseph Smith, and three anonymous
reviewers for their valuable reviews of the manuscript. We
also thank Steve Bobko at Old Dominion University for
the image analysis macro used to obtain otolith increment
widths.
2 Wuenschel, M. J., R. G. Werner, D. E. Hoss, and A. B. Powell.
2001. Bioenergetics of larval spotted seatrout (Cynoscion
nebulosus) in Florida Bav. Florida Bay Science Conference,
April 23-26, 2001, p. 215-216. Westen Beach Resort, Key
Largo, Florida. Abstract. Center for Coastal Fisheries and
Habitat Research, Beaufort Laboratory, 101 Pivers Island Road,
Beaufort, NC 28516.
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156
Abstract— Age and growth of the night
shark (Carcharhinus signatus) from
areas off northeastern Brazil were
determined from 317 unstained ver-
tebral sections of 182 males (113-215
cm total length [TLI>, 132 females
(111.5-234.9 cm! and three individuals
of unknown sex ( 169-242 cm ). Although
marginal increment (MI) analysis sug-
gests that band formation occurs in the
third and fourth trimesters in juve-
niles, it was inconclusive for adults.
Thus, it was assumed that one band
is formed annually. Births that occur
over a protracted period may be the
most important source of bias in MI
analysis. An estimated average percent
error of 2.4'S was found in readings for
individuals between two and seventeen
years. The von Bertalanffy growth
function (VBGF) showed no significant
differences between sexes, and the
model derived from back-calculated
mean length at age best represented
growth for the species (1^=270 cm, K=
0.11/yr, t0=-2.71 yr) when compared to
the observed mean lengths at age and
the Fabens' method. Length-frequency
analysis on 1055 specimens (93-260
cm) was used to verify age determina-
tion. Back-calculated size at birth was
66.8 cm and maturity was reached
at 180-190 cm (age 8) for males and
200-205 cm (age ten) for females. Age
composition, estimated from an age-
length key, indicated that juveniles
predominate in commercial catches,
representing 74.3% of the catch. A
growth rate of 25.4 cm/yr was esti-
mated from birth to the first band (i.e.
juveniles grow 38?< of their birth length
during the first year), and a growth rate
of 8.55 cm/yr was estimated for eight- to
ten-year-old adults.
Age determination and growth of the
night shark (Carcharhinus signatus)
off the northeastern Brazilian coast
Francisco M. Santana
Rosangela Lessa
Universidade Federal Rural de Pernambuco (UFRPE)
Departamento de Pesca, Laboratory de Dinamica de Populacoes Mannhas - DIMAR
Dois Irmaos, Recile-PE, Brazil, CEP 52171-900
E-mail address (for R. Lessa. contact author) rplessaigig.com br
Manuscipt approved for publication
26 June 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:156-167 (2004).
The night shark (Carcharhinus sig-
natus) is a deepwater coastal or semi-
oceanic carcharhinid that is found in
the western Atlantic Ocean along the
outer continental or insular tropical
and warm temperate shelves, at depths
exceeding 100 meters (Bigelow and
Schroeder, 1948). The species has been
recorded from Delaware to Florida, the
Caribbean sea (Cuba), and northern
South America (Guayana) (Compagno,
1984). It has also been recorded in
southern Brazil, Uruguay, and Argen-
tina (Krefft, 1968; Compagno, 1984;
Marin et al., 1998), and on the sea-
mounts off northeastern Brazil (02°16'
to 04°05'S and 033°43' to 037°30'W.
Menni et al., 1995) where it is called
"toninha."
Since 1991, tuna longline vessels have
targeted the night shark in northeast-
ern Brazil (Hazin et al., 1998) because
of its highly prized fins, the increasing
value of shark meat in the local market,
and their relatively large abundance
and accessability on seamounts (Menni
et al., 1995). This species is most im-
portant in the area, making up 909;
of catches over shallow banks (CPUE,
in number, is 2.94/100 hook), and only
15% of catches on the surrounding deep
area, yielding 0.04/100 hook (Amorim
etal., 1998).
Information on this species is re-
stricted to taxonomic descriptions
(Bigelow and Schroeder 1948; Cadenat
and Blache, 1981; Compagno, 1984,
1988), and some biological aspects
(Guitart Manday, 1975; Hazin et al.,
2000). Night sharks reach >270-280 cm
maximum total length (TL) (Compagno,
1984; Branstetter, 1990). Off northeast-
ern Brazil, females mature at 200-205
cm TL, males at 185-190 cm. Litter sizes
range from 10 to 15 pups and the gesta-
tion period may last one year ( Hazin et
al., 2000). The assumed size-at-birth off
the United States is 60-65 cm TL (Com-
pagno, 1984; Branstetter, 1990). Age and
growth have not been estimated.
The aim of this study is to present
the first growth curve for Carcharhinus
signatus from vertebral and length-fre-
quency analyses. This information will
permit the use of age-based stock as-
sessment methods for the management
of the species in the Exclusive Economic
Zone (EEZ) off Brazil.
Materials and methods
Sampling data and vertebrae were col-
lected from November 1995 to Novem-
ber 1999 from commercial landings
(Natal, Brazil) caught in deep (Aracati,
Dois Irmaos, Fundo, Sirius) and shallow
(Pequeno, Leste, and Sueste) seamounts
with depths between 38 to 370 m at the
summits (Fig. 1 ).
Commercial vessels were equipped
with -30 km Japanese-style multifila-
ment longline gear (Suzuki et al., 1977).
On average, each vessel used 970-980
hook per day; mainline sets began at
-02:00 h and ended at -06:00 h. The
retrieval of gear began at noon and fin-
ished by dusk. The Brazilian sardinella
(Sardinella brasiliensis), margined fly-
ingfish (Cypselurus cyanopterus), and
squid [Loligo sp. ) were used as bait
(Hazin etal, 1998).
A total of 1055 individuals, landed
whole, eviscerated, or as carcasses
(headless and finless). were sampled.
The interdorsal space (posterior dorsal
Santana and Lessa: Age and growth of Carcharhinus signatus off the northeastern Brazilian coast 157
0°
02°S -
04°S -
06°S
ATLANTIC OCEAN
Archipelago of
Fernando de
Noronha
40:W
38=W
36°W
34 =W
32W
Figure 1
Location of the sampling area for the night shark iC. signatus) collected off
northeastern Brazil.
fin base to origin of the second dorsal fin [IDS, cm] ), total
length (snout to a perpendicular line from the tip of the up-
per caudal fin [TL, cm] ) and fork length (snout to fork of tail
[FL, cm]) were measured. In carcasses, only IDS was mea-
sured, and IDS, FL, and TL were recorded for eviscerated or
whole individuals. A set of five or six vertebrae were removed
from below the first dorsal fin in 317 specimens. Total length
was measured as the "natural length" (without depressing
the tail) according to Garrick ( 1982).
To estimate TL for carcasses, relationships from sub-
samples of IDS versus TL and FL versus TL were estab-
lished for males and females separately. Linear regressions
derived for each sex were tested for homogeneity and ana-
lyzed for covariances (ANCOVA), resulting in TL=1.2049
FL + 1.7972 (r2=0.944.n=668,P=0.41) and TL = 3.3467 IDS
+ 30.879 (r2=0.824; rc=764, P=0.161). Whenever length is
mentioned hereafter, we always refer to TL.
Vertebrae were processed by removing excess tissue,
fixed in 49c formaldehyde for 24 hours, and preserved in
70% alcohol. Each vertebra was embedded in polyester resin
and the resulting block was cut to about a 1-mm thick sec-
tion containing the nucleus by using a Buehler® low speed
saw. Initially, alizarin-red-s stained sections (Gruber and
Stout, 1983) were compared to unstained sections from the
same individuals to define the best contrast for narrow and
broad zones. In the first procedure, sections were immersed
overnight in an aqueous solution of alizarin red s and 0.1%
NaOH at a ratio of 1:9 and then rinsed in running tap water.
In stained sections, narrow zones were visible as dark red
and broad zones as light red, whereas in unstained sections
translucent (narrow) and opaque (broad) zones were visible
under transmitted light. Unstained sections produced com-
parable results to alizarin stained sections and were used
for band observation in the study.
Bands counted in each section and distances from the focus
to the margin of each narrow zone were recorded. Vertebral
radius (VR) was measured by using a binocular dissecting
microscope equipped with an ocular micrometer. Measure-
ments were made at lOx magnification ( 1 micrometer unit=l
mm) with both reflected and transmitted light. The same
reader read sections from the same specimen twice at dif-
ferent times without knowledge of the individual size or
previous count. Whenever the counts differed between the
two readings, a third reading was used for back-calculation
of size-at-age.
The index of average percentage error (IAPE) (Beamish
and Fournier, 1981) to compare reproducibility of age de-
termination between readings was calculated.
IAPE = 1 / Ar]T ( 1 / R^ ( | Xtj - Xj \Xj)x 100,
where N = the number of fish aged;
R = the number of readings;
Xt - the mean age off1' fish at the i'h reading; and
Xj = the mean age calculated for the/,! fish.
Marginal increment ( MI ) analysis to determine the time
of band formation was used. The analysis was restricted to
1995-97, when samples were collected every month. The dis-
tance from the final band to the vertebral's edge (MI) was
expressed as a percentage of the distance between the last
two bands formed on vertebrae (Crabtree and Bullock, 1998).
The distance between the last and the penultimate band
was divided by the distance between the nucleus and the
158
Fishery Bulletin 102(1)
last band for each vertebra that was measured, and we then
calculated the mean of this number for the entire sample:
IK*.
,)-i?„)//2=0.13(SE = 0.0009).
The expected distance between the last (Rn ) and the pen-
ultimate (i?n_! ) bands was estimated as a function of the
distance between the vertebral nucleus and the last band
(MI). The percent marginal increment (PMI) was calcu-
lated as
PMI = [MI I (0. 13 x Rn )] x 100.
Analysis of variance to test for differences in PMI by
month was used. Post-hoc tests (Tukey honest significant
differences ( [HSD] ) were performed to indicate which
months were different.
Characterization of the vertebral edge was used to de-
termine the time period of band formation (Carlson et al.,
1999). Under reflected light, a narrow dark zone (MI 0), a
narrow light zone ( MI 0. 1 to 0.5 ), and a broad light zone ( MI
0.6 to 1 ) were observed. Absolute marginal increments ( MI )
were also analyzed by trimester for juveniles aged four and
five years, and for adults ( more than eight years ) to confirm
the time of translucent zone formation.
The relationship between VR and TL was calculated
by sex, tested for normality, and compared by ANCOVA
(Zar, 1996). The final regression in both sexes did not pass
through the origin, thus suggesting that the Fraser-Lee
method was the most appropriate for back-calculation
(Ricker, 1969).
[TL]„ = (RJVR)({TL\-a) + a,
where [TL]
R
= the back-calculated length at age n;
- vertebral radius at the time of the ring n\
VR = the vertebral radius at capture;
TL = the length at capture; and
a = the intercept on the length axis.
A von Bertalanffy growth function (VBGF) (von Berta-
lanffy, 1938) was fitted to back-calculated and observed
length-at-age data with the following equation.
L . 1-
kit („)i
where Lt = predicted length at age t;
Lr = mean asymptotic total length;
K = growth rate constant; and
t0 = the age when length is theoretically zero.
To obtain parameters of VBGF, data were analyzed by
using FISHPARM (Prager et al., 1987) for nonlinear least-
squares parameter estimation. The Kappenman's method
(1981), based on the sum of squares of the differences
between observed and predicted lengths from a growth
model, was used for comparing male and female growth
curves. In addition, likelihood-ratio tests were used to com-
pare parameter estimates of the von Bertalanffy equation
between sexes (Cerrato, 1990).
Von Bertalanffy parameters (Lx, K) were also estimated
by the method of Fabens ( 1965 ) usually employed for recap-
ture data and which takes into account the size at birth (L(l)
instead of t0. This method reconfigures VBGF and forces the
regression through a known size at birth:
L, =Ljl-be-
where b = (L.,
-L0)/Lx
We used Fabens routine for growth increment data
analysis of the FAO-ICLARM stock assessment tools (FI-
SAT) program (Gayanilo et al., 1996), assuming that the
time intervals (=At) for each size-at-age class were equal
and had a periodicity identical to that obtained from the
vertebral analysis.
The lengths of 1055 individuals were divided into 5-cm
intervals and analyzed by the Shepherd method ( 1987 ) with
the length-frequency data analysis program ( LFDA ). Initial
values of Lv were based on results from maximal lengths
in the sample and from literature (Compagno. 1984). K
values ranging from 0.05 to 1.8 were used as input into the
program, which was run repeatedly until the highest score
function was obtained. The Lx and /f values were then used
to calculate t0 (Sparre et al., 1989):
tQ = t + {l/K)(\nlL. -lt])/LJ.
Using an age-length key, based on 317 individuals for
which vertebrae were read, we evaluated the age composi-
tion of the sample (Bartoo and Parker, 1983). Maximal ages
in the sample were calculated by employing the inverted
VBGF (Sparre et al.. 1989). Further, the formula by Fa-
bens (1965) [5(ln2)/AT for longevity estimation was used.
All statistical inferences were made at a significance level
of 0.05.
Results
The total sample size consisted of 1055 individuals: (551
males [93-248 cm], 499 females [110-252 cm], and 5
individuals of undetermined sex [169-260 cm]) (Fig. 2). Of
these, vertebrae were removed from 317 specimens (182
males [113-215 cm], 132 females [111.5-234.9 cm], and
3 individuals of undetermined sex [169-242 cm]).
Differences in the relationship between VR and TL
between sexes were not found to be significant (P=0.81D.
The regression for the overall sample showed a linear
relationship: TL = 13.523V/? + 41.824 <rM).89: n=317>,
indicating that vertebrae are suitable structures for age
determination, and methods based on direct proportion are
appropriate for back-calculation.
The average percentage error, calculated between two
readings, ranged from 098 to 4.5^ in vertebrae with 2 to
17 bands and the average IAPE for the overall sample was
2.4'-. Coefficient of variation (CV) between readings for
total sample was 6.88' < .
Monthly PMI analysis, for the entire sample, indicated
that bands were formed from June to October, when high-
Santana and Lessa: Age and growth of Carcharhinus signatus off the northeastern Brazilian coast
159
70 i
60
50
>, 40
CJ
c
CD
=> 30 i
cr
CD
it 20-
10 ■
ii n i
if
1
1
1
n=1055
\\\] Jl 1 r, t I . .
Lengtl
easter
bars =
muimmmLfiifimiflminmmifimifimcn
OUCVJCvjCvjC\ic\JC\iC\i<NC\icNiC\ic\ic\JCcicNC\ic\J
cno*-c\jct3Ti/}(or^<oa>OT-cjpO'<fmc0
Total length (cm)
Figure 2
l-frequency distribution for the night shark (C. signatus) caught off north-
i Brazil between 1995-99 (black bars=females; white bars = males; grey
undetermined sex).
250
200
- 150
E 100-
M J J
Month
A S O N D
Figure 3
Percent marginal increments means (-) with the minimum and maximum values
for the night shark (C. signatus) caught from 1995 to 1997 off northeastern Brazil
(n=171). The number of individuals sampled per month is shown above the ver-
tical bars.
est mean values are reached (Fig. 3). These values are
followed by the lowest mean PMI in October, indicating
that the new translucent zone forms from that point on.
Monthly PMIs showed significant differences throughout
the year (P=0.0463) and post-hoc comparisons detected
differences in February, April, September, and October.
Furthermore, monthly categorization of vertebral edges
indicated that the highest frequency of broad light edges
(MI 0.6-1) appears from July through December and nar-
row dark edges (MI 0) from March through December,
with the exception for months of May and August (Fig. 4).
Trimonthly frequency distribution of absolute marginal in-
crements (Mis) was carried out for juveniles, revealing four
and five bands, and for adults, revealing more than eight
bands. For the former group, a higher number of broader
increments and fully formed bands in the third and fourth
trimesters were observed (Fig. 5). For adults, an unclear
pattern was observerd perhaps because a smaller sample
size was obtained.
Because there was no complete agreement on the time
of band formation among different MI analysis for juve-
niles and adults, age was assigned by assuming an annual
pattern of band deposition. The birth mark present in all
analyzed vertebrae was not taken into account for age as-
signation. Under this assumption, band counts indicate
relative age (years).
Mean observed lengths-at-age were higher than mean
back-calculated lengths for males and females and were
likely due to the strong variation in size for each age class
(Table 1). The tendency of back-calculated lengths of older
160
Fishery Bulletin 102(1)
Table T
Mean back-calculated (BC) and observed length-at-age
eastern Brazil (SD=standard deviation I.
( OL l data for male and female
night sharks (C. signatus) collected off north-
Age ( yr 1
Females
Males
BClcm)±SD
OL(cm) ±SD
BCicmi±SD
OLicml±SD
0
66.8 ±1.78
—
67.3 ±1.41
—
1
91.9 ±1.31
—
92.3 ±1.37
—
2
113.4 ±2.13
122.5 ±16.93
113.3 ±1.48
120.1 ±4.21
3
128.8 ±2.21
132.9+9.77
128.6 ±1.54
135 ±8.91
4
142.7 ±2.41
149.8 ±7.75
142.4 ±1.94
151.5 ±9.72
5
154.7 ±2.92
160.7 ±7.21
154.5 ±2.7
157.5 ±7.86
6
165.9 ±3.46
166.8 ±10.32
166.3 ±3.25
167.5 ±8.1
7
176.8 ±3.4
179.8 ±9.56
177.4 ±2.64
177.6 ±9.34
8
185.9 ±3.71
184.9 ±9.12
187.4 ±2.22
189.8 ±6.53
9
194.8 ±3.82
197.1 ±6.49
195.8 ±2.25
199.9 ±5.26
10
202 ±4.75
208.2 ±3.89
202.4 ±2.78
204.3 ±3.13
11
206.9 ±5.56
202
209.8
212.5 ±3.54
12
215.7 ±2.4
218
—
—
13
222.2
—
—
—
14
226.9
—
—
—
15
231.7
234.4 ±0.63
—
—
fish in the early years to be systematically lower than
younger ones at the same age (Lee's phenomenon) was
not evident (Tables 1 and 2).
Using back-calculated lengths-at-age (Table 3), we
plotted male and female growth curves separately and
then tested the data; no indication of significant differ-
ences in growth was observed between sexes with both
the Kapenman's (P>0.05) and likelihood ratio tests
(Table 4). Data were then treated together, incorporat-
ing individuals of undetermined sex. VBGFs derived
from observed length at age were not tested because
of missing values in different age classes. The method
of Fabens for combined sexes, fitted to back-calculated
data, provided L, and K, by using b = 0.781, L0= 62.5
cm (Compagno, 1984) and. At = 1 year (Table 2).
Parameters from back-calculation were close to
those derived from length-frequency analysis for 1055
specimens, whereas observed lengths and the Fabens
method, provided the most varying parameters with
lowest correlation and highest coefficients of variation
(Table 2).
The smallest specimen in the vertebral sample show-
ing two complete bands in sections was 111.5 cm, close
to the estimated mean back-calculated length at age
two of 113.7 cm (Table 3). Size at maturity, 185-190 cm for
males and 200-205 cm for females, corresponded to 8- and
10-year-old individuals, respectively (Fig. 6). The largest
and oldest specimen whose vertebrae were used, was 242
cm, which corresponded to 17-year-old individual.
A growth rate of 25.4 cm/yr was estimated from birth to
the first band — a rate that corresponded to 389 of the birth
0 •
■ 0
□ 0.1-0.5
5!
r
1
□ 0.6-1
33
45
8 ■
51
6 ■
15
2<
\
43
4 •
2 ■
1
7
9
1
6
5
'
%
-i
0 •
-|
i
IJI
1
J
■
1
-X
--I-1-
M A
J J
Month
Figure 4
Categorization of edges by month for the night shark iC.
signal its) off northeastern Brazil.
length (the length at birth being 66.8 cm). Also, a mean rate
of 8.55 cm/yr was calculated for 8- to 10-year-old individu-
als, when maturity is achieved (Table 3).
Considering mature individuals >185 cm. the age com-
position for the vertebral samples («=317) indicated that
17.3% of specimens were adults (Table 5). Instead, for the
total sample (ra=1055), where the age ranged between 2 to
al7 years, adults corresponded to 25.3% of the total sample
Santana and Lessa: Age and growth of Carcharhinus signatus off the northeastern Brazilian coast
161
0 1 0.2 0 3 0 4 0 5 0.6 0.7 08 0 9 1
12
10 -
8
6
4
2
0
ill
0 1 0 2 0 3 0 4 0 5 0.6 07 08 09 1
12
10
8
6
4 -
0
3,d Trimester
n=36
I.. I
0 1 0 2 0 3 0.4 0 5 0.6 0 7 0 8 0 9 1
12 -
10
4lh Trimester
Nihil. .
0 1 0 2 0 3 0 4 0.5 0.6 0 7 08 0 9 1
B
r' Trimester
n= 14
II I ■ -
2nd Trimester
12 -
n = 24
10 -
8
6
4
2
■
o -
01 0.2 0.3 0.4 0.5 0.6 0.7 08 09 1
12
10 -
3rd Trimester
n= 14
ll
01 0.2 03 0.4 05 0.6 0.7 0.8 09 1
12
10
8
6
4
2
0
4m Trimester
n=10
Jl
0 1 0.2 0 3 0 4 0.5 0 6 0.7 0 8 0.9 1
Ml
Figure 5
Marginal increments (MI) by trimester for ages 4 and 5 (n = 139) (A) and a8 (Bl (n=54) for the night shark (C.
signatus) from northeastern Brazil.
(Fig. 7). According to the inverted back-calculated VBGF
the oldest specimen in the sample was 31.7 years old (260
cm), whereas longevity was 31.5 years.
Discussion
Validating the time of band formation is considered critical
when using hard parts for age estimates (Brothers, 1983),
and validation is successful when growth zones are shown
to form annually in all age groups of the population (Beam-
ish and McFarlane 1983). Marginal increment analysis,
carried out on younger and faster growing individuals,
cannot always be used for validating older age groups, and
therefore all ages must be ascertained (Brothers, 1983).
In the present study, we obtained significant differences
in marginal increments for the total sample. However, the
significance level of the test (P=0.046) was close enough
to 0.05 to cause us to suspect that the distributions could
have been similar. The time of band formation varied when
different age groups were analyzed separately, despite
suggestions that bands are completed in the third and
162
Fishery Bulletin 102(1)
E o
150
100
B
\
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 0 1 2 3 4 5 6 7 8 9 10 1 1 12 13 14 15 16 17 1
250
200
150
100
50
0
i ! V '■
■ Back-calculated Observed Fabens
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Age (years)
Figure 6
Growth curves generated from (A) females. (B) males, and (Cl sexes combined for the night shark (C. signatus) off the northeastern
Brazil.
Table 2
Von Bertalanffy parameters derived from back-calculated lengths (BC), observed lengths (OL), lengths
the length-frequency data analysis (LFDA) package for the pooled database (SE is standard error; CV
from the Fabens method, and
is coefficient of variation i.
Methods
Sex
L_, (cm)
SE
CV
/f(/year)
SE
CV
f0(year)
SE
CV
r-
BC
Males
256.5
5.56
0.022
0.124
0.007
0.055
-2.538
0.119
0.047
0.999
Females
265.4
4.15
0.016
0.114
0.005
0.045
-2.695
0.127
0.047
0.999
Both
270
2.78
0.01
0.112
0.003
0.031
-2.705
0.099
0.037
0.999
OL
Males
306.1
37.71
0.117
0.076
0.02
0.267
-4.663
0.882
0.189
0.995
Females
297.1
26.71
0.09
0.077
0.018
0.235
-4.853
0.977
0.201
0.99
Both
289.9
7.6
0.026
0.085
0.006
0.077
-4.395
0.348
0.079
0.998
Fabens
Both
285.3
15.69
0.055
0.08
0.016
0.2
—
—
—
—
LFDA
Both
270.9
—
—
0.106
—
—
—
—
—
—
fourth trimesters (new bands begin to form in this period)
in juveniles. Results were inconclusive for adults. For C.
obscurus (Natanson et al., 1995), C. plumbeus (Sminkey
and Musick 1995), C. porosus (Batista and Silva, 1995:
Lessa and Santana, 1998), C. acronotus (Carlson et al.,
1999). and /. oxyrhynchus (Lessa et al., 2000), inconclusive
results for MI analysis were obtained. The inability to dem-
onstrate the periodicity of band deposition in adult sharks
Santana and Lessa: Age and growth of Carcharhinus signatus off the northeastern Brazilian coast
163
in the present study is similar to the
outcome for C. limbatus older than
four years (Wintrier and Cliff, 1996).
For the last mentioned species, the
problem was circumvented by
restricting MI analysis to juveniles
(Killam and Parsons, 1989).
Age was assigned by assuming
an annual pattern of deposition, as
commonly occurs for most carcha-
rhinids like C. brevipinna and C.
limbatus, Rhizoprionodon terraeno-
vae (Branstetter et al., 1987; Brans-
tetter and Stiles, 1987), Negaprion
brevirostris (Gruber and Stout,
1983), and C. longimanus (Seki et
al, 1998; Lessa et al., 1999c). Three
sources of bias generally occur with
MI analysis: 1) sample sizes are
small for any particular month or
for any age class (Cailliet, 1990); 2)
data are collected over a too long
a period causing variability on ac-
count of annual marks that are not
formed at the same time ( Brothers,
1983 ) and 3 ) births occur over a long
period (Brothers, 1983). All these
may have biased MI analysis in the
present study.
Research carried out in the study
area by Hazin et al. (2000) indi-
cated that copulation takes places
throughout the austral summer.
Embryos measuring 10 to 40 cm
were collected in February, whereas
31.8 to 37.2 cm embryos were found
in June. This remarkable variability
in embryo size during the gestation
period suggests that birth period
lasts several months. Furthermore,
with an estimated back-calculated
birth length of 66.8 cm, individuals
measuring -40 cm in February will
be born long before individuals that
measured 37.2 cm in June. Such a
protracted parturition period could
lead to differences in MI of the same
cohort. Thus, after an assumed -12
months gestation period, individu-
als are born with birth dates vary-
ing by several months. Moreover,
no significant differences in MI
analysis was found for C. porosus
and /. oxyrhynchus, which also have
a protracted birth seasons (Lessa et
al., 1999a, 1999b).
A comparison of growth model
parameters by using known size
information, such as size-at-birth
and maximum observed size, can be
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164
Fishery Bulletin 102(1)
Table 4
Likelihood ratio tests
comparing estimates of von
Bertalanffy parameters
for males (noted as
1 1 and females
(noted
as 2) for
C. signatus
in the linear constraints.
Hypothesis
Linear constraints
Residual SS
X2r
df
P
HQ
none
60536.4
Hwl
£=oi = Lx2
10511
0.049
1
0.996
Hto2
A, = K2
10524.3
0.047
1
0.996
Hto3
'01 = '02
10205.6
0.122
1
0.999
HvA
Same L^, A. and t0
24301.2
0.164
3
0.973
useful as a method of verification ( Cailliet et
al., 1983). Although no specimens younger
than 2-years-old were caught (perhaps due
to the gear selection bias), the presumed
size at birth was about 60-65 cm ( Compag-
no, 1984), which is similar to the estimated
size in the present study (66.8 cm). Also, the
estimated Lr value (270 cm), derived from
the back-calculated or observed VBGF is
close to the maximum size of 276 cm men-
tioned by Bigelow and Schroeder ( 1948), 280
cm off Cuba (Compagno, 1984), and 275 cm
byGarrick(1985).
Mean observed length-at-age is gener-
ally higher than back-calculated mean
length-at-age (Bonfil et al., 1993; Lessa and
Santana. 1998), leading to lower values of
La and higher values of K. However, in the
present study, although mean observed
length-at-age is higher than mean back-cal-
culated lengths, parameters derived from back-calculation
provided a lower Lx and a higher A' value. Inconsistency of
the observed length-at-age set is attributed to the missing
values in for ages 0, 1, 13, 14, and 16. This led to a VBGF
which provided an unrealistic birth size of 90 cm and which
present a flatter shape than the back-calculated curve.
Von Bertalanffy growth parameters generated from both
back-calculation and by the Fabens method were all consid-
ered suitable and were of the same magnitude. However,
taking into account 1 ) parameters close to those derived
for length-frequency analysis, and 2) the best statistical fit,
the back-calculated VBGF was chosen as best representing
growth in the species.
Comparisions of biological features such as maturity
size and maximum sizes have been used for inferences in
growth and to explain differences between sexes (Natanson
et al., 1995; Natanson and Kohler, 1996; Lessa et al., 2000).
Tin' studied species shows a disparity of -15 cm in matu-
rity sizes between sexes (Hazin, et al., 2000), corresponding
to ~2 years. In addition, the largest specimen, for which
six was determined, was a 252-cm female and the largest
male was 248 cm. These disparities, however, did not bring
about differences in growth between sexes, as indicated by
results of both tests used. Such a result can be explained by
the number of juveniles used for age determination (-83' I
300
250
n =1055
>. 200
0
c
S 150
O"
1
"- 100
■ |
50
0
.ll
Mil..
<1 3 5 7 9 11 13 15 >17
Age (years)
Figure 7
Age composition for the night shark (C. signatus) collected off northeastern
Brazil.
Thus, the number of adults was not high enough to bring
about any differences in the growth equation although
differences frequently occur after maturity, caused by dif-
ferent growth rates between sexes (Natanson et al., 1995;
Sminkey and Musick, 1995).
Assuming that the time elapsed between birth and the
band corresponding to age 1 is one year, the species grows
38% of its birth length during the first year. This growth
rate is close to that (50%) generally assumed (Branstetter
1990; Cortes, 2000). Furthermore, the estimated K value
falls within the range suggested by the first author, and
according to him, the night shark is a relatively fast grow-
ing species, presenting a life strategy similar to that of C.
falciformis, and apparently depending on rapid growth for
adequate neonate survival due to vulnerability to preda-
tion from large sharks.
In summary, considering the increasing fishing effort
on the night shark as a targeted species and that catches
are mainly composed by juveniles (representing 74.7' i of
specimens in landings), we believe that the A'-selected
characteristics of the species (including late maturity,
long gestation period, and low fertility 1 should be taken
into account in determining the management of this
resource. Demographic analyses will be required for the
examination of consequences of current levels of exploi-
Santana and Lessa: Age and growth of Carcharhtnus signatus off the northeastern Brazilian coast
165
c
Q.
C
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.Q
»
,(B
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be
3
O
bo
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bf no
■" cm
2 I
2 I
S 2?
oi >5
CO «o
CO !N
I I I I I I I I I I I I I I I I I I I I I I I I
I I I I I I I I I I I I I I I I I I I I I I I I I I I
I I I I I I I I I I I I I I I I I I I I I I I I 8 I
I I I I I I I I I I I I I I I I I I I I I I I I I I I
I I I I I I I I I I I I I I I I I I I I I I I I I I I
I I I I I I I I I I I I I I I I I I I IS I I I
I I ! I I I I I I II I I I I I I 12 I8S I M I I
I I I I I I I I I I I I I I
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COH!flCOCnmHCO!Mfflt*tOffiH05(NCO(Nt'0)NN
HH-fCOCO(N(N(N T-H i-H
HH^lNcoco^'<tlom^otD^^cocoo)a)OOHH(N(Ncoco't
166
Fishery Bulletin 102(1)
tation to ensure the sustainability of the night shark in
northeastern Brazil.
Acknowledgments
The present research was funded by Ministerio do Meio
Ambiente-MMA, Secretaria da Comissao Interministerial
para os Recursos do Mar-SECIRM in the scope of Programa
Nacional de Avaliacao do Potencial Sustentavel de Recur-
sos Vivos-REVIZEE. We are grateful to Norte Pesca S. A.
and to Conselho Nacional de Desenvolvimento Cientifico
e Tecnologico-CNPq for scholarships and research grants
iProcs: 301048/83, 38.0726/96-3 and 820652/87-3).
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168
Abstract— The prowfish (Zaprora sile-
nus) is an infrequent component of
bottom trawl catches collected on stock
assessment surveys. Based on pres-
ence or absence in over 40,000 trawl
catches taken throughout Alaskan
waters southward to southern Cali-
fornia, prowfish are most frequently
encountered in the Gulf of Alaska and
the Aleutian Islands at the edge of the
continental shelf Based on data from
two trawl surveys, relative abundance
indicated by catch per swept area
reaches a maximum between 100 m
and 200 m depth and is much higher
in the Aleutian Islands than in the
Gulf of Alaska. Females weigh 3.7%
more than males of the same length.
Weight-length functions are W (gl =
0.0164 L292 (males) and W = 0.0170
L292 (females). Length at age does not
differ between sexes and is described
by L = 89.3(1 - e
-0 181i;+0554l
), where
L is total length in cm and t is age in
years. Females reached 50r/f maturity
at a length of 57.0 cm and an age of 5.1
years. Prowfish diet is almost entirely
composed of gelatinous zooplankton,
primarily scyphozoa and salps.
Manuscript approved for publication
20 September 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Mull. 102:168-178 (2004).
Distribution and biology of prowfish
(Zaprora silenus) in the northeast Pacific
Keith R Smith
David A. Somerton
Mei-Sun Yang
Daniel G. Nichol
Alaska Fisheries Science Center
National Marine Fisheries Service
7600 Sand Point Way NE
Seattle, Washington 98115
E-mail address (for K. R. Smith, contact author) Keith.Smith@noaa.gov
Current taxonomy distinguishes the
prowfish (Zaprora silenus, Fig. 1) as
the only species and the only genus of
the family Zaproridae. Other families in
the encompassing suborder Zoarcoidei
include Bathymasteridae (ronquils),
Cryptacanthodidae (wrymouths), Pholi-
dae (gunnels), and Stichaeidae (prick-
lebacks). Systematics of most families
within Zoarcoidei, and of the suborder
itself within the order perciforms, is
uncertain (Nelson, 1994). Prowfish
(adult) physical features include an
elongate, laterally compressed body; a
high convex brow and interorbital area
ending with a short blunt snout; and
a distinctive protruding area below a
slightly upturned terminal mouth.
Fins consist of: a long, moderately high
dorsal fin; a moderately long anal fin;
a discrete truncate caudal fin with a
short, broad peduncle; and moderately
large, rounded pectoral fins (pelvic fins
are absent). Teeth are small, sharp, and
close-set in a single row attached only
to the jaws. Scales are ctenoid. Numer-
ous distinctive large round pores occur
on the sides and top of the head. Color
is olive-gray to brown dorsally, shading
lighter below, suffused on the sides
and back with many small dark spots
(Clemens and Wilby, 1961; Eschmeyer
et al, 1983; Hart, 1973; Kessler, 1985).
The maximum length reported is more
than 1 m (Tokranov, 1999).
Since its original description (Jordan,
1897), the prowfish has been observed
infrequently despite numerous and
extensive bottom trawl surveys com-
prising thousands of net deployments
off Alaska and the west coast of North
America. It is not clear whether this
lack of documentation indicates a spe-
cies of low abundance or a preference
by prowfish for a habitat, such as rough
rock substrate or steep bottom gradi-
ents, that is poorly sampled by bottom
trawl surveys. Nevertheless, the spe-
cies is common enough to be considered
representative of the ichthyofauna of
certain benthic biotopes within its
range (Allen and Smith, 1988; Tokranov,
1999). It has been encountered at loca-
tions along the outer continental shelf
and upper slope ranging in a long arc
from San Miguel Island, California,
north through the Gulf of Alaska, west
through the Bering Sea and Aleutian Is-
lands to the Asiatic shelf, thence south
to Hokkaido, at depths of 10-675 m
(Allen and Smith, 1988; Hart, 1973). In
addition to occurring in the catches on
biological surveys, prowfish have been
taken incidentally, and occasionally
processed, in commercial fishing op-
erations on the outer continental shelf
(Smith, pers. obs.; Berger1).
Prowfish are known to be pelagic
as pre-adults (Hart, 1973; Doyle et al,
2002). After larval transformation at
30 mm (Matarese et al., 1989), juve-
niles maintain close proximity to the
medusae of pelagic cnidarians (Schef-
fer, 1940). Brodeur (1998) observed
juveniles swimming near the bells of
scyphomedusae Cyanea capillata and
Chrysaora melanaster and retreating
1 Berger, J. 2002. Personal commun.
Alaska Fisheries Science Center, National
Marine Fisheries Service, 7600 Sand Point
Way NE, Bldg 4, Seattle, WA 98115-0070.
Smith et al.: Distribution and biology of Zaprora silenus
169
Figure 1
Aquarium prowfish specimen, National Marine Fisheries Service, Kodiak Laboratory,
Kodiak, AK. Photograph by Jan Haaga.
behind the tentacles or within the bells of these jellyfish
when approached by a remotely operated vehicle, appar-
ently as a means of protection from predators. Prowfish are
also believed to later become demersal and have a prefer-
ence for rocky areas (Tokranov. 1999).
The association with scyphomedusae and other large ge-
latinous zooplankton exhibited by juveniles may continue
throughout their lives, because such prey are reported to
constitute a considerable portion of the prowfish diet (Car-
olio and Rankin, 1998). In the stomachs of 16 juveniles
of 5-13.3 cm total length captured at midwater depths in
Prince William Sound in 1995, Sturdevant2 found prey
biomass was composed principally of hyperiid amphipods
but also found unquantifiable gelatinous matter which was
thought to be the remains of jellyfish tentacles.
Little is known regarding possible predators of prow-
fish, the relative frequency of prowfish among prey items,
or the sizes of prowfish consumed. Prowfish have been
found in the diets of diving seabirds and have comprised
25% of food biomass delivered to tufted puffin {Lunda cir-
rhata ) chicks (Sturdevant2). Yang ( 1993) found prowfish in
only 0.3% of 467 stomachs of Pacific halibut (Hippoglossus
stenolepis) taken by bottom trawl in the Gulf of Alaska in
1990, accounting for 0.03% (by weight) of total food pres-
2 Sturdevant, M. V. 1999. Forage fish diet overlap, 1994-1996.
Exxon Valdez oil spill restoration project final report (restoration
project 97163C), 184 p. Alaska Fish. Sci. Cent., Auke Bay Labo-
ratory, Natl. Mar. Fish. Serv., NOAA, Juneau, AK. [Available by
order no. PB2000- 100700 from Natl. Tech. Info. Serv, 5285 Port
Royal Rd., Springfield, Virginia 22161.]
ent. Orlov (1998) found prowfish in 0.13% of stomachs of
white-blotched skate (Bathyraja metadata) caught by bot-
tom trawl off the Northern Kuril Islands and Southeastern
Kamchatka in 1996. In comparisons of proximate composi-
tion among 17 taxa of forage-size fish from the northeast-
ern Pacific (Van Pelt et al, 1997; Payne et al, 1999), juvenile
prowfish averaged highest in moisture content (86-88% by
weight) and relatively low in lipids (10. 8±1.3%, dry weight
analysis).
In this study we examined information on this little-
known species, investigating spatial and depth distribu-
tions, size frequency, growth, reproduction, and diet in the
waters off Alaska.
Materials and methods
Data and sample collection
Data used in this investigation were collected during
bottom trawl surveys for groundfish and invertebrate
stocks conducted by the Resource Assessment and Con-
servation Engineering (RACE) Division of the Alaska Fish-
eries Science Center (APSC), National Marine Fisheries
Service. Areas surveyed were the continental shelf and
upper slope of the eastern Bering Sea, Aleutian Islands
region (Al), Gulf of Alaska (GOA), and west coast of North
America from Washington to California. Trawl catches
were sorted to species, weighed, and individuals were
counted, following procedures described in Wakabayashi
etal. (1985).
170
Fishery Bulletin 102(1)
To characterize prowfish distribution we obtained catch
data from 42,601 bottom trawl deployments (hauls) exe-
cuted from 1953 through 2000 using a variety of net de-
signs. We used these data to determine presence or absence
of prowfish at each haul location. Previous observations
have indicated that prowfish tend to be pelagic as larvae
and become demersal as adults (Matarese et al., 1989;
Hart, 1973). A full accounting of prowfish distribution by
life stage is beyond the scope of this investigation, which
focuses on adults. Therefore we confined our observations
to haul catches taken on bottom, as opposed to in mid-water
or at the surface.
On two of the bottom trawl surveys, one in the Gulf of
Alaska from 22 May to 30 July 1996, and the other in the
Aleutian Islands from 10 June to 11 August 1997, addi-
tional prowfish data were collected. Consistency between
these surveys in sampling procedures and equipment
(Martin, 1997, and Stark3) facilitated subsequent data
comparisons.
Density of prowfish at each sampling location was
estimated as the number caught divided by the km2 of
area swept by the trawl (catch per unit of effort, or CPUE).
Research vessels on both surveys employed the standard
RACE Division model poly-Nor'eastern high-opening bottom
trawl net with roller gear, and hauls were made during day-
light. Net configuration and bottom contact during trawling
were monitored by Scanmar instrumentation. Data were ob-
tained from 807 hauls in the Gulf of Alaska and 408 hauls in
the Aleutian Islands. The average area swept per haul was
0.025 km2 in the GOA and 0.024 km2 in the AI.
All prowfish were sorted to sex by examination of the
gonads and then length (total length; cm) was measured.
Sample sizes were 84 males and 90 females for the Gulf
of Alaska; 396 males and 431 females for the Aleutian
Islands. Whole-body weights (g) of 83 male and 88 female
prowfish from the Gulf of Alaska were measured and the
sagittal otoliths were removed and stored in 50% ethanol.
Whole ovaries from a representative subsample of 39 of
the females were removed, frozen, and later stored in 10%
buffered formalin solution.
Diet composition was examined from stomach contents of
76 individuals (18 from the Gulf of Alaska and 58 from the
Aleutian Islands). Stomachs containing food and with no
signs of regurgitation or net-feeding (e.g. the stomach was
in an inverted or flaccid state or there was the presence of
prey in the mouth or around the gills) were removed and
preserved in 10% buffered formalin.
Laboratory procedures
Standard otolith-prcparation techniques for age determi-
nation were modified to accommodate the relatively small
size of prowfish otoliths (usually <5 mm long). An anterior
portion of each otolith was removed by a transverse cut with
scalpel perpendicular to the sagittal axis and anterior to the
:! Stark, J. 1998. Report to industry: fishing log for the 1997
bottom trawl survey of the Aleutian Islands. AFSC Proc. Rep.
98-06, 96 p. Alaska Fish. Sci. Cent., Natl. Mar. Fish. Serv., NOAA.
7600 Sand Point Way NE, Bldg. 4, Seattle, WA 98115-0070.
nucleus. The remainder, which contained the nucleus, was
baked at 300-475°C for up to 17 min or heated over an alco-
hol flame to enhance visibility of annuli. The otoliths were
then individually mounted on slides by completely embed-
ding them in clear thermoplastic posterior end down. On
hardening, each mount was wet-sanded on increasingly fine
grades of sandpaper (400-2000 grit), parallel to the slide,
until the surface intersected the otolith nucleus (trans-
verse section). Preparing readable mounts was a delicate
procedure; besides cutting and polishing the small otoliths
precisely without fracturing them, precise heating tem-
perature and time were especially critical to expose annuli
without again causing fractures or burning the otolith.
Our method had advantages over the standard "break and
burn" method of simply coating the surface of a temporarily
mounted specimen with oil to enhance visibility of annuli,
in lieu of polishing. It allowed a more precise intersection of
the nucleus by the viewed surface and eliminated the need
to remove oil from specimens intended for further viewing
in order to prevent blurring of annuli. After preparation,
slides were placed in sufficient water to cover the surface
scratches and were examined under a dissecting microscope
with reflected light. Age in years was determined by count-
ing the annuli or hyaline bands according to the criteria
described in Chilton and Beamish (1982).
Prowfish ovaries were prepared for histological examina-
tion by removing a small portion from the middle of each
ovary, which was then embedded in paraffin, sectioned at
6 jim, and stained with hematoxylin and eosin. The histo-
logical slides were examined under a compound microscope
and donor females were classified as either sexually imma-
ture or mature based on the presence of yolk in the oocytes
(i.e. vitellogenesis).
Prowfish stomachs were processed by first neutralizing
the 10% formalin used for initial fixation and then by im-
mediately transferring the stomachs into 70% ethanol. The
food was removed, blotted with a paper towel, and exam-
ined with a dissecting microscope. Prey items were sorted
to the lowest practical taxonomic level and then weighed
to the nearest 0.1 gm. The percentage of total prey weight
which each taxon comprised, as well as the percentage of
stomachs containing each taxon, was calculated for each
haul sample and then estimated for each of the two regions
as the average of the per-haul percentages.
Analysis of data
The distribution of prowfish density over depth in the
Gulf of Alaska and the Aleutian Islands was determined
by calculating the mean CPUE for each 20-m depth inter-
val from 20 m to 480 m. Both surveys utilized a stratified
sampling design in which sampling density (hauls per
unit area) varied by geographical subarea (Martin, 1997;
Stark1). To compensate for this variation, the CPUE of each
haul was weighted by the inverse of the sampling density
in that geographic stratum. The mean bottom depth as
weighted by prowfish density was calculated for each of
the two regions as the weighted average of the midpoints
of the depth intervals, where the weighting factors were
the interval-mean CPUE values.
Smith et al.: Distribution and biology of Zaprora silenus
171
Frequency distributions of prowfish total length, sepa-
rated by sex and region, were calculated as the weighted
percent of measurements within 10-cm length intervals.
The weighting factors were calculated for each fish mea-
surement as the inverse of geographic-stratum sampling
(i.e. haul) density, multiplied by the inverse of the indi-
vidual haul area that was swept . Also, differences in mean
length between sexes or regions were examined by using
analysis of variance (ANOVA)4 to test the significance of
statistical differences based on the weighted lengths. Be-
cause potential grouping of prowfish by size could affect
within-haul variance, source haul (i.e. that in which each
measured fish was caught) was included in analyses as
a possible random variable affecting length. Variances in
length between regions and sexes were each tested for sig-
nificance against variance among hauls. The significance
of the haul variable was also checked by testing variance
among hauls against that among measurements.
The relationship of body weight (g; W) to total length
(cm; L) was assumed to be an exponential function:
W = e"U\
for which the parameters a and ft were estimated from
the data by first log-transforming both variables and then
calculating the intercept and slope of the least squares
linear regression:
\n(W) = a + p\n(L).
To determine whether the relationship differed by sex,
analysis of covariance ( ANCOVA; Statgraphics Plus, Manu-
gistics. Inc., Rockville, MD) was used to compare the fit of
a model with two regression lines, each with a sex-specific
intercept and slope, to the fit of a two-line model with sex-
specific intercepts and a common slope (null hypothesis).
If no significant difference was observed, then a second
test was performed by testing the latter model against the
null hypothesis of a common regression line with single
intercept and slope for both sexes combined. The relation-
ships in the best-fit model were then transformed back to
exponential form.
Prowfish growth was described by fitting the von Berta-
lanffy function to length (L) and age (year; t ) data by using
nonlinear least squares. The function is
L=L (1
-«'i/-(,ii)
where L^ = asymptotic maximum length;
k - a constant (per year) affecting model early
growth rate; and
U
hypothetical age at 0 length.
To determine whether parameters differed between prow-
fish sexes, we fitted the function separately to the data from
each sex as well as to the data for both sexes combined. A
4 Unless otherwise specified, ANOVA, log-likelihood, and nonlin-
ear regression analyses were accomplished by using Systat 10
software (Systat 10 Statistics I, SPSS Inc. .Chicago, ID.
likelihood ratio test was then used to determine whether
the separate-sex model fitted the data significantly better
than the combined-sex model (Kimura, 1980). Significance
of the likelihood ratio was based on the chi-squared sta-
tistic with degrees of freedom equal to the difference in
number of parameters between the two models.
The proportion of prowfish females that were mature
(Pmo() at a given length or age was described with logistic
functions of the formPma, = 1/(1 + e"+'iV), where X is either
length (L) or age in years (f), and a and /3 are function pa-
rameters. The models were fitted to the data by using maxi-
mum likelihood. After the relationships were estimated,
the length and age at which 50% of females were mature
were estimated by setting Pmat = 0.5 in each function and
solving forX The 959r confidence interval for each estimate
was calculated by using the delta method (Seber, 1973).
Results
Geographic distribution
Prowfish distribution in the waters off Alaska, as indicated
by their presence at 1528 out of a total of 35,159 histori-
cal bottom trawl locations, is shown in Figure 2. The total
count of individuals in catches was 11,401. Distribution
south of approximately 50°N latitude off Vancouver Island
is not shown because here 6 of 7442 bottom trawl hauls
caught a total of 8 prowfish. The southernmost occurrence
was at 34°13.4'N latitude near San Miguel Island, southern
California. Prowfish were taken at depths ranging from 24
m to 801 m but most frequently appeared in catches close
to the break between the continental shelf and upper con-
tinental slope near 200 m depth.
Prowfish CPUE was greater than zero at 64 of 807 haul
locations in the Gulf of Alaska in 1996 and at 48 of 408
locations in the Aleutian Islands in 1997. Over all areas at
the depths fished the range of per-haul CPUE was 0-547.5
prowfish/km2 (average=6.7 prowfish/km2 ) in the GOA and
0-5220.1 prowfish/km- (average=65.1 prowfish/km2) in
the AI. The average CPUE within 20-m bottom depth in-
tervals in each region indicated that fish tend to be most
concentrated at intermediate depths (Fig. 3). Depth at
trawl locations ranged from 20 to 479 m for the GOA and
from 22 to 474 m for the AI, and prowfish were collected
at 34-252 m (GOA) and 89-258 m (AI), respectively. The
CPUE-weighted average bottom depth was 163.8 m for the
GOA and 150.3 m for the AI.
The CPUE values within 20-m depth intervals (Fig. 3)
indicated that the regional difference in mean density was
largely due to differences at the same depth rather than
differences between regions in the amount of area available
at a given bottom depth.
Length distribution
Length-frequency histograms by region and sex for prowfish
from the Gulf of Alaska (84 males, 90 females) and Aleutian
Islands (396 males, 431 females) are shown in Figure 4.
Analysis of variance tests for a difference in mean length
172
Fishery Bulletin 102(1)
65 °N
HI \
55 °N
65 °N
- 60°N
- ^ \
170°E
65°W
Ii.ii \\
16(1 \\
155°W
150°W 145°W
40°W
135°W
130°W
65°N-
B
Alaska
60 °N-
"V^
^
^
t0r
:'' *UK5i8Si^
55°N-
y^tBs
N
A
Bathymetry (m) Noprowf
20Q ♦ Prowfish
sh caught
caught
Ml \ -
h
1
1
1 —
1 1 1
65°N
hi \
^ \
50 \
K.ll W
155°W
150 \\
145 \\
140 \\
135°W
130 \\
Figure 2
Lm; il inns i if Alaska Fisheries Science Center groundfish survey I mt turn trawls I prior to year
2001) in (Ai the eastern Bering Sea and the Aleutian Islands region and (B) the Gulf of
Alaska, indicating trawls in which prowfish occurred.
Smith et al.: Distribution and biology of Zaprora silenus
173
30 70 110 150 190 230 270 310
Bottom depth (m)
350 390 430 470
Figure 3
Average prowfish catch per unit of effort (CPUE; no/km2) within 20-m intervals over the
range of trawl depths of 20-479 m in the Gulf of Alaska (GOA) in 1996 (A) and 22-474 m
in the Aleutian Islands (AD in 1997 (B). The mean of interval midpoints, each weighted
by interval average CPUE, was 163.8 m for the GOA and 150.3 m for the AI.
between sexes were not significant for either the GOA
(P=0.83) or the AI (P=0.76). Although the weighted mean
for both sexes combined was 61.0 cm (range: 11-90 cm) in
the GOA and 51.9 cm (range: 25-87 cm) in the AI, the differ-
ence in length between regions was not significant (P=0.1 1 ).
Grouping of prowfish of similar size within hauls was highly
significant in both the GOA and the AI (P«0.01 ).
Weight-length relationship
In the between-sex ANCOVA comparison of the linearized
(i.e. log-transformed) weight-to-length relationships based
on prowfish caught in the Gulf of Alaska, the slopes were
not significantly different between sexes (P=0.38). How-
ever, the difference in intercepts was significant (P=0.044 ).
Thus the best fitting model varied by sex with two regres-
sion lines of equal slope but with sex-specific intercepts.
The equivalent functions in terms of the untransformed
variables (Fig. 5) were
and
Wmales = 0.0164 xL2922;
W/mwles = 0.017x7^22.
The model indicated that adult females are, on average,
3.7% heavier than males of the same length.
Age and growth
Readable otolith specimens were produced for 138 prowfish
(71 males, 67 females) of the 172 from which samples were
collected. Production of readable specimens did not appear
related to fish size or age. The likelihood ratio test for a
difference between males and females in the relationship
of length to age was not significant (P=0.53), indicating
that there was no difference in growth between sexes. The
best-fit von Bertalanffy function (Fig. 6) had the following
parameters (with 95% confidence intervals): La = 89.33
±6.5 cm; k = 0.18 ±0.05/year; and t() = -0.55 ±0.12 year.
Female maturity
The proportions of females that were mature were highly
significant logistic functions of length and age (P<0.005;
Fig. 7). The fitted functions of length and age were
and
Pmo,= l/(l+e37114-6-51L);
1/(1 +e9.66-1.90().
The theoretical length and age at which 50%' of females
were mature, with respective 95% confidence limits, were
57.0 ±0.4 cm and 5.1 ±0.7 years.
174
Fishery Bulletin 102(1)
40 50
Length (cm)
Figure 4
Frequency distribution of total lengths of (A) 84 male and 90 female prowfish from the
Gulf of Alaska (GOA; 1996) and (B) 396 males and 431 females from the Aleutian Islands
(AI; 1997). Gray bars show the percentage of male lengths and black bars the percentage
of female lengths within continuous 10-cm intervals (e.g. 25-35 cm).
9000 -I
8000 ■
f
O Males °rJy>
7000 ■
~ 6000 ■
£ 5000 ■
g>
|j 4000 ■
□ Females UfkJ/^B
wmales = o.oi 64 x u** 'jijr °
— w,emates = o.oi 79 * l* «* afljllo °
3000 ■
2000 J
r2 (combined model) = 0.95 _^ffl^
1000-
^«e**^
0 20 40 60 80 100
Length (cm)
Figure 5
Prowfish body weight (W) fitted by an exponential function of fish total length (/..land sex.
Data for males (/i=83) are shown by diamonds and the fitted model by a dashed line. Data
for females (n=88) are shown by squares and the fitted model by a solid line.
Food habits
Fish used for diet study averaged 63.8 cm in total length
(range: 49-87 cm) in the Gulf of Alaska and 56.9 cm (range:
30-79 cm) in the Aleutian Islands. The contents of 18
prowfish stomachs from the Gulf of Alaska and 58 from
the Aleutian Islands showed that jellyfish (999r and 31%
Smith et al.: Distribution and biology of Zaprora silenus
175
100
90
80
70
E 60
£ 50 \
S 40
30
20
10
0
L = 89 33(1-e-°,8'<'-<-°554»)
r = 0.752
10 15
Age (years)
20
25
Figure 6
Prowfish total length \L) fitted by a von Bertalanffy function of age (f). Data for males
(«=71) are shown by diamonds; data for females (rc=67) are shown by squares. The fitted
model is shown by a solid line.
Table 1
Mean percent weight (%W) and mean percent freque
icy of occurrence (%FO) of the prey items from 18 prowfish stomachs collected
in the Gulf of Alaska (GOA; 1996;
total prev
weight=
=299 g
and 58 stomachs from the Aleutian
Islands
area (Al; 1997; total prey
weight=1446.6 g). Sample prowfish had an average total length of 63.8 cm
(range
49
-87 cm) from the GOA and and 56.9 cm (range:
30-79 cm) from the AI.
Prey name
GOA(n =
18)
AI(n
=58)
%W
%FO
%W
%FO
Scyphozoa (jellyfish)
98.84
100
30.45
29.88
Ctenophora (comb jelly)
0.09
1.23
Polychaeta (worm)
0.03
5.8
Calanoida (copepod)
0.26
28.13
0.04
29.14
Thysanoessa raschii (euphausiid)
0.05
6.67
Mysidacea Mysida (mysid)
0.01
3.13
Hyperiidea (amphipod)
0.19
33.46
Gammaridea (amphipod)
0.12
30.49
Themisto sp. (amphipod)
0.32
28.57
0.14
36.91
Salpa sp. (pelagic salp)
34.06
46.79
Larvacea (pelagic tunicate 1
0.13
12.5
Sebastes sp. (rockfish) larvae, 5-8
mm long
0.43
42.86
Microsomus paeifieus (Dover sole)
eggs
0.01
3.13
Unidentified organic material
34.84
32.59
by weight of total food in the two regions, respectively)
and gelatinous pelagic tunicates (Salpa spp.; 34% in the
Aleutian Islands area only) were the most important food
(Table 1). Although calanoid copepods and Themisto sp.
(amphipod) were both often present in GOA specimens
(28.13% and 28.57% of stomachs, respectively), they were
not important food in terms of weight. The same was true
in the AI for calanoid copepods, Themisto sp., gammaridean
amphipods, and hyperiidean amphipods (29.14%, 36.91%,
30.49%, and 33.46% respectively). Mysids and larvaceans
from GOA specimens as well as ctenophors, polychaetes, and
euphasiids from AI specimens occurred in trace amounts.
Sebastes larvae (5-8 mm standard length), the only fish
species found, were found in 43% of Gulf of Alaska stomachs
but made up only 0.43% of prey weight. Some Dover sole
[Microstomas paeifieus) eggs had also been consumed.
176
Fishery Bulletin 102(1)
0.8 H
0.6
0.4-
0.2-
0
t*
000000
2
-e-
311 2 12
000 000
Pmat = 1/(1+e3"'»-"'M
00 i 0
30 35 40 45 50 55 60 65 70 75 80 85 90
Length (cm)
5 4
1 3
1 1
0.8 -
0.6 -
/ 3
Jo
0.4 -
P
1/(1 +e9«-,9°')
0.2 -
0-
1^2
6 0 i
10 15
Age (years)
20
25
Figure 7
Proportion of female prowfish mature (Pmat) as logistic functions of length (L) and age
it). Data points based on 39 maturity-at-length and 27 maturity-at-age observations are
shown by diamonds, and numbers of females of each cm-length and year-age class are
shown next to the corresponding symbol. The fitted logistic models are shown by solid
lines. The length and age at which Pmat = 0.5 with 95^ confidence limits are 57.0 ±0.4 cm
and 5.1 ±0.7 years.
Discussion
Geographic distribution
Historically occurring in the catch in AFSC bottom trawl
surveys in areas of the eastern Bering Sea, Aleutian
Islands, and Gulf of Alaska regions, prowfish were also
observed more rarely farther south along the West Coast
as far as the vicinity of San Miguel Island, California.
This is the apparent southern limit of their range in the
northeastern Pacific (Allen and Smith, 1988). They were
most often encountered in the vicinity of the edge of the
continental slope near 200 m depth (Fig. 2), although our
data increase the maximum known depth of occurrence
from 675 m (Allen and Smith, 1988) to 801 m. As indicated
by survey CPUE, prowfish density was greatest between
the depths of 100 m and 240 m (Fig. 3). Our distribution
data show similarities with those of Tokranov ( 1999), who
studied >300 bottom trawls executed in 1995-97 on the
shelf and slope off the southern Kamchatka Peninsula and
northern Kuril Islands, in which adult prowfish were taken
at 100-480 m. Tokranov often found fish concentrated in
areas of high-relief, rocky bottom — a common feature of
the shelf edge in the Gulf of Alaska and Aleutian Islands
regions. Such areas near the shelf break may be important
prowfish habitat. Underwater videos taken in the north-
east Gulf of Alaska by the Alaska Department of Fish and
Game (Brylinsky5) show numerous adult fish resting on or
just above this type of substrate.
Density was greater in the AI than in the GOA, over all
bottom depths combined and in most cases by individual
depth interval (Fig. 3). One reason may be that preferred
habitat comprises a larger proportion of the Aleutian Is-
5 Brylinsky, C. 2000. Pers. commun. Alaska Department of
Fish and Game, 304 Lake Street, Sitka, AK 99835.
Smith et al.: Distribution and biology of Zaprora stlenus
177
lands area. Because of the lack of a relatively broad shelf
in the region, a larger proportion of trawls are in or near
areas of steep seafloor gradient and therefore likely over
rough bottom (Fig. 2).
Length distribution
In both the Gulf of Alaska and the Aleutian Islands, few
prowfish <40 cm in length were captured (Fig. 4). This
paucity of small prowfish is not due to size selection by
the trawl net mesh because the codend is lined with small
mesh (1.3 cm stretched measure) webbing that retains
small individuals of other species. A different explanation,
based on the observations of Brodeur (1998) and Scheffer
(1940), is that pre-adult prowfish are pelagic, remaining
in proximity with large coelenterates and thus avoiding
bottom trawls. Thus, the minimum capture length may
indicate the length at which prowfish recruit to a demer-
sal habitat. Our data showed no statistically significant
length difference between sexes, in contrast with the data
of Tokranov (1999) who suggested a length dimorphism
where females are generally longer than males.
Weight-length relationship
The best-fitting model of weight versus length predicts
that for any length, female prowfish are, on average, 3.7%
heavier than males (Fig. 5). It seems unlikely that this
relationship exists over all developmental stages because
our samples were almost all adults and such a (relative)
difference might not remain constant during all ontoge-
netic sexual divergence. What is more certain is simply
the existence of some small degree of length-weight
dimorphism (females slightly heavier at a given length).
Also, this dimorphism is not likely to stem primarily from
a sexual difference in gonad weight because the maximum
proportion of total female body weight composed of ovarian
tissue was only 2.7%. Thus the difference is due to other
morphological or behavioral differences.
Growth
There was no significant difference between sexes in length
versus age. The predicted length of a prowfish of given age
based on our samples was higher than that indicated by
Tokranov (1999). In our study 5-year-old and 9-year-old
fish averaged 56.6 cm and 73.5 cm in length, respectively.
Tokranov (1999) considered that prowfish growth deter-
mined from otoliths of 102 specimens from the Northwest
Pacific indicated a comparatively fast-growing species
reaching an average length of 44.6 cm by 5 years of age
and 67 cm after 9 years. These data suggest prowfish are
indeed relatively fast growing and that growth rates for the
Gulf of Alaska are faster than those for off southeastern
Kamchatka and the northern Kuril Islands. Alternatively,
size-dependent mortality from such elements as incidental
capture by commercial fishing may affect the two popula-
tions differently.
Historically, two other prowfish have been aged from
otoliths: a male 84 cm long taken near Eureka, CA (Fitch
and Lavenberg, 1971), and a female 50.1 cm long ( standard
length) from off Monterey (Cailliet and Anderson, 1975).
The ages estimated were 12 and 3 years, respectively. Af-
ter converting the standard length record to an estimate
of total length for the second specimen of 58 cm by using
a ratio described by Baxter,6 both lengths are slightly
greater than our predictions for the same ages, albeit near
the limits of our data range. This finding contrasts with
the predictions of lesser length at a given age presented
by Tokranov (1999).
Maturity
Little previous data exist with which to compare our obser-
vations of female prowfish rate of maturation. Cailliet and
Anderson (1975) examined the ovaries of their 50.1-cm 3-
year-old female specimen for vitellogenesis and predicted
an age at first spawning of 4 years, slightly less than the
lower 95% confidence limit of 4.4 years for our expected
average age at 50% maturity.
Food habits
Our observation that gelatinous zooplankton was the
largest constituent in the contents of prowfish stomachs
(Table 1) is supported by Tokranov ( 1999), who found that
the two most common prey taxa among the contents of 102
stomachs of adult specimens from the northwestern Pacific
were Scyphozoa (59.6-62.0% of stomachs) and Ctenophora
(6.0-15.4% of stomachs). Anecdotal observations have also
been made of the feeding behavior of an aquarium specimen
over an approximate 2-year period (Carollo and Rankin,
1998). When first obtained, the fish ate only various jel-
lyfish species, rejecting other food, including a variety of
live invertebrates. In our food samples, we observed other
taxa, such as invertebrates and small fish, but these were a
minor part, possibly first captured by jellyfish and then sec-
ondarily ingested by prowfish. Carollo and Rankin (1998)
found that the aquarium specimen would ingest such items
when eating the bells of Chrysaora melanaster in which
such food had previously been placed, indicating the pos-
sibility of this occurring naturally. Possibly more reflective
of the unnatural circumstances, the specimen later began
accepting such items outside the bells of jellyfish.
Apparent adaptations of the prowfish to a diet of ge-
latinous zooplankton include the small, sharp, close-set
teeth in a single row attached only to the jaws, which are
capable of a 180-degree gape, and the large rough-scaled
lips (Clemens and Wilby, 1961; Hart, 1973; Carollo and
Rankin, 1998).
Acknowledgments
We are grateful for the expert advice given by Alaska Fish-
eries Science Center colleagues Delsa Anderl and Nancy
6 Baxter, R. 1990. Unpubl. manuscript. Annotated key to the
fishes of Alaska, 803 p. [Available from Sera Baxter, Box 182,
Seldovia, AK 99663.1
178
Fishery Bulletin 102(1)
Roberson regarding age-reading of prowfish otoliths,
and by AFSC colleagues Kathy Mier and Susan Piquelle
regarding statistical analyses of data.
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1988. Atlas and zoogeography of common fishes in the
Bering Sea and Northeastern Pacific. NOAA Tech. Rep.
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Brodeur, R. D.
1998. In situ observations of the association between juve-
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Cailliet, G. M., and M. E. Anderson.
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Tokranov, A. M.
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silenus (Zaproridae) in the Pacific waters of the Northern
Kuril Islands and Southeastern Kamchatka. J. Ichthyol.
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179
Abstract— Our analyses of observer
records reveal that abundance esti-
mates are strongly influenced by the
timing of longline operations in rela-
tion to dawn and dusk and soak time —
the amount of time that baited hooks
are available in the water. Catch data
will underestimate the total mortal-
ity of several species because hooked
animals are "lost at sea." They fall off,
are removed, or escape from the hook
before the longline is retrieved. For
example, longline segments with soak
times of 20 hours were retrieved with
fewer skipjack tuna and seabirds than
segments with soak times of 5 hours.
The mortality of some seabird species
is up to 45% higher than previously
estimated.
The effects of soak time and timing
vary considerably between species.
Soak time and exposure to dusk periods
have strong positive effects on the catch
rates of many species. In particular, the
catch rates of most shark and billfish
species increase with soak time. At the
end of longline retrieval, for example,
expected catch rates for broadbill
swordfish are four times those at the
beginning of retrieval.
Survival of the animal while it is
hooked on the longline appears to be an
important factor determining whether
it is eventually brought on board the
vessel. Catch rates of species that
survive being hooked (e.g. blue shark)
increase with soak time. In contrast,
skipjack tuna and seabirds are usu-
ally dead at the time of retrieval. Their
catch rates decline with time, perhaps
because scavengers can easily remove
hooked animals that are dead.
The results of our study have impor-
tant implications for fishery manage-
ment and assessments that rely on
longline catch data. A reduction in soak
time since longlining commenced in the
1950s has introduced a systematic bias
in estimates of mortality levels and
abundance. The abundance of species
like seabirds has been over-estimated
in recent years. Simple modifications
to procedures for data collection, such
as recording the number of hooks
retrieved without baits, would greatly
improve mortality estimates.
Manuscript approved for publication
22 September 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:179-195 (2004).
Fish lost at sea: the effect of soak time
on pelagic longline catches
Peter Ward
Ransom A. Myers
Department of Biology
Dalhousie University
Halifax, B3H 4JI Canada
E-mail address (for P Ward) wardiSmathstat.dal ca
Wade Blanchard
Department of Mathematics and Statistics
Dalhousie University
Halifax, B3H 44 Canada
Our knowledge of large pelagic fish in
the open ocean comes primarily from
tagging and tracking experiments and
from data collected from longline fish-
ing vessels since the 1950s. Abundance
indices for pelagic stocks are often
derived from analyses that model catch
as a function of factors such as year,
area, and season. However, the amount
of time that baited hooks are available
to fish is likely to be another important
factor influencing catch rates (Deriso
and Parma, 1987).
The activity of many pelagic animals
and their prey vary with the time of
day. Broadbill swordfish, for example,
feed near the sea surface at night. They
move to depths of 500 m or more during
the day (Carey, 1990). Other species may
be more active in surface waters during
the day (e.g. striped marlin) or at dawn
and dusk (e.g. oilfish). Longline fishing
crews take a keen interest in the tim-
ing of their fishing operations and soak
time (the total time that a baited hook
is available in the water). However, as-
sessments have not accounted for those
factors in estimating the abundance
or mortality levels of target species or
nontarget species.
In many assessments that use pelagic
longline catch rates, fishing effort is as-
sumed to be proportional to the number
of hooks deployed. The effects of soak
time and timing may have been omit-
ted because a clear demonstration of
their effects on pelagic longline catch
rates is not available. The few pub-
lished accounts on soak time in pelagic
longline fisheries have been based on
limited data and a few target species.
For example, in analyzing 95 longline
operations or "sets" by research vessels
Sivasubramaniam ( 1961) reported that
the catch rates of bigeye tuna increased
with soak time, whereas yellowfin tuna
catch rates were highest in longline seg-
ments with intermediate soak times.
In contrast to the limited progress in
empirical studies, theoretical approach-
es are well developed for modeling fac-
tors that may influence longline catch
rates. Soon after large-scale longlining
commenced. Murphy (1960) published
"catch equations" for adjusting catch
rates for soak time, bait loss, escape,
hooking rates, and gear saturation. He
suggested that escape rates could be es-
timated from counts of missing hooks
and hooks retrieved without baits.
Unfortunately, such data are rarely col-
lected from pelagic longline operations.
More recently, hook-timers attached
to longline branchlines have begun to
provide information on the time when
each animal is hooked and also whether
animals are subsequently lost, e.g.
Boggs (1992), Campbell et al.1-2 Such
data are particularly useful to under-
1 Campbell, R., W. Whitelaw, and G. Mc-
Pherson. 1997. Domestic longline fish-
ing methods and the catch of tunas and
non-target species off north-eastern
Queensland (1st survey: October-Decem-
ber 1995). Report to the Eastern Tuna
and Billfish Fishery MAC. 71 p. Aus-
tralian Fisheries Management Authority,
PO Box 7051, Canberra Business Centre,
ACT 26 10, Australia.
2 See next page.
180
Fishery Bulletin 102(1)
standing the processes affecting the probability of capture
and escape.
The purpose of our study is to determine whether varia-
tions in the duration and timing of operations bias abun-
dance and mortality estimates derived from longline catch
rates. We present a theoretical model that is then related to
empirical observations of the effects of soak time on catch
rates. The strength in our approach is in applying a random
effects model to large data sets for over 60 target and non-
target species in six distinct fisheries. We also investigate
the survival of each species while hooked because prelimi-
nary analyses suggested that the effects of soak time on
catch rates might be linked to mortality caused by hooking
(referred to as "hooking mortality").
Factors affecting catch rates
To aid interpretation of our statistical analysis of soak time
effects, we first developed a simple model to illustrate how
the probability of catching an animal may vary with soak
time.
The probability of an animal being on a hook when the
branchline is retrieved is a product of two probability
density functions: first the probability of being hooked
and then the probability of being lost from the hook.3 In-
fluencing the probability of being hooked are the species'
local abundance, vulnerability to the fishing gear, and the
availability of the gear. Catches will deplete the abundance
of animals within the gear's area of action, particularly for
species that have low rates of movement. Movement will
also result in variations in exposure of animals to the gear
over time — for instance, as they move vertically through
the water column in search of prey (Deriso and Parma,
1987).
Other processes that will reduce the probability of be-
ing hooked include bait loss and reduced sensitivity to the
bait (Ferno and Huse, 1983). Longline baits may fall off
hooks during deployment, deteriorate over time and fall
off or they may lose their attractant qualities. They may be
removed by target species, nontarget species, or other ma-
rine life, such as squids. Hooked animals may also escape
by severing the branchline or breaking the hook. Sections
of the longline may become saturated when animals are
hooked, reducing the number of available baits (Murphy.
1960; Somerton and Kikkawa, 1995). After an animal has
been hooked, it may escape, fall off the hook, be removed by
scavengers, or it may remain hooked until the branchline
is retrieved.
Some of the processes affecting the probability of an ani-
mal being on a hook when the the branchline is retrieved
2 Campbell, R., W. Whitelaw, and G. McPherson. 1997. Do-
mestic longline fishing methods and the catch of tunas and non-
target species off north-eastern Queensland (2nd survey: May-
August 1996). Report to the Eastern Tuna and Billfish Fishery
MAC, 48 p. Australian Fisheries Management Authority, PC)
Box 7051, Canberra Business Centre, ACT 2610, Australia.
In discussing continuous variables we use the terms "proba-
bility" and "probability density function" interchangeably.
are species-specific, whereas other processes may affect all
species. For example, bait loss during longline deployment
will reduce the catch rates of all species. In contrast, the
probability of a hooked animal escaping may be species-de-
pendent; some species are able to free themselves from the
hook whereas other species are rarely able to do this.
Our simple model of the probability of an animal being
on a hook is based on a convolution of the two time-related
processes described above: 1) the decay in the probability
of capture with the decline in the number of baits that are
available; and 2) gains due to the increased exposure of
baits to animals and losses due to animals escaping, falling
off, or being removed by scavengers.
The probability of an animal being on a hook when the
branchline is retrieved is the integral of the probability
density functions of capture and retention:
rtT) = J P(t)PrlT-t)dt,
(1)
where jriT) = the "catch rate" or probability of an animal
being on a hook when the branchline is
retrieved at time T (T is the total soak time
of the hook);
P(it) = the probability density function of an animal
being captured at time t; and
Pr(t) = the probability density function of a cap-
tured animal being retained on the hook for
a length of time f.
The probability density function of capture can be approxi-
mated with an exponential function:
Pit) = P0e-",
(2)
where P0 = the probability of capture when the hook is
deployed (r=0); and
o = a parameter determining the rate of change in
capture probability over time.
After the animal is hooked, the probability density function
of an animal being retained after capture can be approxi-
mated as
PIt) = e-pw,
(3)
where /I = the "loss rate," a parameter determining the
rate of change in the probability of an animal
being retained after it has been captured.
Substituting approximations 2 and 3 into Equation 1
gives
7l(T)= \P0e '"e <"' ' dt
(4)
/?-«'
Ward et al.: The effect of soak time on pelagic longlme catches
181
Seabirds
(-0.06)
p
c\i
(XX)
Skipjack
(-0.04)
()
()
(> <>
° () o ()
0
O
5 10 15 20 25
0 5 10 15 20 25
<)
<)
O O
o
C) °<»'
j (X)
o
o
o o°
Lancetfish
(-0.02)
in
Swordfis
h
(M
(+0.09)
o .
<>°o
<M
o
o
m
o
()
o
o
()
T—
(
)
()
in
o
o
o
o'
o
o
0 5 10 15 20 25 0 5 10 15 20 25
Soak time (h)
Figure 1
Mean catch rates plotted against soak time for skipjack tuna, long-nosed lancetfish. and
swordfish in the South Pacific yellowfin tuna fishery and for "other seabirds" in the South
Pacific bluefin tuna fishery. To reduce variability, the estimates were limited to longline
segments with more than 25 hooks and soak times of 5-20 hours. Vertical bars are 95%
confidence intervals for the mean hourly catch rate. In parentheses are the soak-time coef-
ficients from random effects models ( note that the soak-time coefficient is not the same as
the slope coefficient of a regression of the data presented in this graph).
Our model is similar to the parabolic catch model exam-
ined by Zhou and Shirley (1997). It is simpler than catch
equations developed by other authors because it does not
include specific terms for the loss of baits, for fish competi-
tion, and gear saturation.
Preliminary plots of observer data indicated a variety of
patterns in the relationship between catch rates and soak
time (e.g. Fig. 1). By varying the values of P0 (probability
of capture), a (capture rate), and p (loss rate), our simple
catch equation (Eq. 4) can mimic the observed patterns
(Fig. 2). However, estimates of P0, a , and /3 are not avail-
able. Instead, we used the empirical approach described
in the following section to model the effect of soak time
on catch rates. The relationship of soak time to catch rate
represents the product of the probability of capture and the
probability of being retained.
One approach to investigating the effects of soak time
on catch rates is to fit linear regressions to aggregated
data like those presented in Figure 1. Such an approach,
however, would violate assumptions of independence
(within each longline operation, catch rates in consecutive
segments will be related), normality (these are binomial
data), and homogeneity of variance (for binomial data, the
variance is dependent on the mean).
182
Fishery Bulletin 102(1)
hooks retrieved after 1 5 hours
have many swordfish
soak times
not observed
hooks retrieved before 6 hours
have few swordfish
10
15
Soak time (h)
No captures after deployment
Soak time coefficient <0
e.g. seabirds
Captures exceed losses
Soak time coefficient >0
e.g. swordfish
Losses eventually exceed captures
Soak time coefficient <0
e.g. skipjack
Captures balance losses
Soak time coefficient -0
eg lancetfish
20
Figure 2
Illustration of different patterns in the theoretical relationship between longline catch rates and soak time. The
probability of an animal being on a hook when a branchline is retrieved (the "catch rate") is estimated from
Equation 4 by using soak times iT) ranging from 0 to 20 hours and three different combinations of values forPn
(probability of capture), « (capture rate), and /3 (loss rate). For seabirds, the probabilities were estimated from
Equation 6. The probabilities are not on the same scale for all species.
Another approach might be to fit separate logistic regres-
sions to each operation and then to combine the parameter
estimates. This would overcome the problems of normality
and homogeneity of variance. However, the separate re-
gressions would not incorporate information that is com-
mon to all operations.
Instead, we used a logistic regression with random ef-
fects. The key advantage in using random-effects models
in this situation is that they carry information on the cor-
relation between longline segments that is derived from
the entire data set of operations.
Data and methods
Fisheries
We analyzed observer data from six different fisheries in
the Pacific Ocean to determine the effects of soak time
and timing on longline catch rates (Table 1, Fig. 3). These
fisheries involve two different types of longline fishing
operation: 1 ) distant-water longlining involves trips of
three months or longer and the catch is frozen on board
the vessel; and 2) fresh-chilled longlining, which involves
small vessels (15-25 m) undertaking trips of less than four
weeks duration, and the catch is kept in ice, ice slurries, or
in spray brine systems. The fresh-chilled longliners deploy
shorter longlines with fewer hooks (-1000 hooks) than
the distant-water longliners (-3000 hooks per operation)
(Ward, 1996; Ward and Elscot, 2000).
The six fisheries share many operational similarities,
such as the types of bait used and soak time. However,
they are quite different in terms of targeting, which is
determined by fishing practices, e.g. the depth profile of
the longline, timing of operations and the area and season
of activity. South Pacific bluefin tuna longliners operate in
cold waters ( 10-16°C) in winter to catch southern bluefin
tuna. In the South Pacific yellowfin tuna longliners tar-
get tropical species, such as yellowfin and bigeye tuna, in
warmer waters (19-22°C) (Ward, 1996). To target bigeye
tuna, longlines in the Central Pacific bigeye fishery are
deployed in the early morning with hook depths ranging
down to about 450 m. The depths of the deepest hook are
much shallower (-150 m) in the North Pacific swordfish
fishery where the longlines are deployed late in the after-
noon and retrieved early in the morning (Boggs, 1992).
Ward et al.: The effect of soak time on pelagic longline catches
183
Observer data
National authorities and regional organizations placed
independent observers on many longliners operating in the
six fisheries during the 1990s. The observer data consisted
of records of the species and the time when each animal
was brought on board. We restricted analyses to operations
where the last hook that had been deployed was retrieved
first ("counter- retrieved"), where there was no evidence of
stoppages due to line breaks or mechanical failure, and
where there was continuous monitoring by an observer.
Combined with records of the number of hooks deployed
and start and finish times of deployment and retrieval, the
observer data allowed calculation of soak time and catch
rates of longline segments. We aggregated catches and the
number of hooks into hourly segments. The soak time was
estimated for the midpoint of each hourly segment.
The Central Pacific bigeye tuna and North Pacific sword-
fish fisheries differed from the other four fisheries in the
species that were recorded and the method of recording
the time when each animal was brought on board. Observ-
ers reported catches according to a float identifier in the
Central and North Pacific fisheries. Therefore we estimated
soak times for each longline segment from the time when
each float was retrieved. For those fisheries, observers re-
ported the float identifier only for tuna, billfish, and shark
(Table 2). Data are available for protected species, such
as seals, turtles, and seabirds but were not sought for the
present study.
We assumed a constant rate of longline retrieval
throughout each operation. The number of hooks retrieved
during each hourly segment was the total number of hooks
divided by the duration of monitoring (decimal hours). For
each species we analyzed only the operations where at least
one individual of that species was caught.
Longline segments that involved a full hour of monitor-
ing had several hundred hooks. Segments at either end
of the longline involved less than an hour of monitoring
and had fewer hooks. Catch rates may become inflated in
segments with very small numbers of hooks. Therefore we
arbitrarily excluded segments where the observer moni-
tored less than 25 hooks.
For four of the fisheries, data were available on survival
rates, allowing the investigation of the relationship be-
tween soak time and hooking mortality. For the Western
Pacific and South Pacific fisheries, observers reported
whether the animal was alive or dead when it was brought
on board. We calculated survival rate (the number alive
divided by the total number reported dead or alive) for spe-
cies where data were available on the life status of more
than ten individuals.
Generalized linear mixed model
Logit model We applied a generalized linear mixed
model to the observer data. The model is based on a logis-
tic regression, with the catch (y) on each hook assumed
to have a binomial distribution with y ~ b(ra, n). n is the
expected value of the distribution for a specified soak time.
We refer to it as the probability of catching an animal or
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184
Fishery Bulletin 102(1)
North Pacific Swordfish
o
o
eg
Western Pacific Bigeye
o
CM
I
o
I
Western Pacific
Bigeye
Western Pacific Distant
South Pacific
Yellowfin
South Pacific Bluefin
— I —
140
T
T
160
220
180 200
Longitude (degrees)
Figure 3
Geographical distribution of the observer data analyzed for each fishery.
240
the expected number of animals per hook. For each longline
segment (j) within each operation (£), we link jr to a linear
predictor ( ?;( ) through the equation
rjj is then modeled as a function of soak time:
r?y = ft+ATy, (5)
where TtJ = the hook's soak time (decimal hours) in long-
line segment j;
P0 = the intercept; and
/3j = the slope coefficient, which we term the "soak
time coefficient."
Modeling the probability of a catch on each individual
hook would result in large numbers of zero observations
and thus test the limits of current computer performance.
Therefore we aggregated hooks and catches into hourly
segments for each longline operation.
We assumed that each longline segment had the same
configuration and that the probability of capture was the
same for each segment within a longline operation. The
assumption may be violated where segments pass through
different water masses or where they differ in depth profile
or baits. Saturation of segments with animals will also al-
ter the capture probability between segments. The effects
of water masses, depth profiles, baits, and gear saturation
were not analyzed in the present study.
Capture probability may also vary through the differen-
tial exposure of segments to the diurnal cycle of night and
day. The addition of dawn and dusk as fixed effects allowed
us to model diurnal influences on catch rates.
Fixed effects To explore factors that might affect the rela-
tionship between soak time and catch rate, we added four
fixed effects to the logit model: year, season, and, as men-
tioned above, whether the segment was available at dawn
or dusk. A full model without interaction terms would be
iu = A. + /Wj + AA> + PAi + PAj + P*Yu + °-
where 71, = the hook's soak time (decimal hours) in long-
line segment j;
At = an indicator of whether the hook was exposed
to a dawn period;
P = an indicator of whether the hook was exposed
to a dusk period;
S: , = the season (winter or summer);
Y- = the year;
Oi = the random effect for operation that we mod-
eled as an independent and normally distrib-
uted variable (see "Random effects" section);
and
)30-/34 are parameters (fixed effects) to be estimated.
We refer to fix as the "soak time coefficient."
Ward et al.: The effect of soak time on pelagic longline catches
185
Table 2
List of common and scientific
names of the species analyzed. Also shown is
the number of individuals of each species
analyzed in
each fishery. A dash indicates that the species was not analyzec
in the present study
it does not
necessarily mean that the spe-
cies was not taken in the fishery. In particular, observer data on
the time of capture were not aval
lable for
'other bony fish" in the
North Pacific swordfish and Centra] Pacific bigeye tuna fisheries
. NP = North Pacific;
CP = Central Pacific
WP = Western Pacific;
SP = South Pacific; LN = long-
nosed; and SN = short-nosed.
Fishery
CP
WP
SP
SP
NP
bigeye
bigeye
WP
yellowfin
Bluefin
Common name
Species
swordfish
tuna
tuna
distant
tuna
tuna
Tuna and tuna-like species
Albacore
Thunnus alalunga
9707
23,128
14,194
11,976
21,550
1399
Bigeye tuna
77? annus obesus
5409
45,476
9814
2581
1846
-
Butterfly mackerel
Gasterochisma melumpus
—
—
—
—
—
533
Skipjack tuna
Katsuwonus pelamis
546
13,882
1456
445
691
—
Slender tuna
Allothunnus fallai
—
—
—
—
—
28
Southern bluefin
Thunnus maccoyii
—
—
—
—
1030
10.537
Yellowfin tuna
Thunnus albacares
2811
21,654
16,029
4689
12,454
—
Wahoo
Acanthocybium solandri
383
5508
1345
—
308
—
Billfish
Black marlin
Makaira indica
25
41
353
226
160
—
Blue marlin
Makaira nigricans
981
2379
1467
529
179
—
Sailfish
Istiophorus platypterus
49
193
706
399
151
—
Shortbill spearfish
Tetrapturus angustirostris
543
5467
529
398
654
—
Striped marlin
Tetrapturus audax
1963
8332
681
182
724
—
Swordfish
Xiphias gladius
22,457
1680
1472
287
1173
92
Other bony fish
Barracouta
Thyrsites atun
—
—
—
—
53
—
Barracudas
Sphyraena spp.
—
—
707
153
—
—
Escolar
Lepidocybium flavubrunneum
1208
3983
1343
878
1726
84
Great barracuda
Sphyraena barracuda
32
743
303
442
92
—
Lancetfish (LN)
Alepisaurus ferox
2788
30,136
325
419
2868
610
Lancetfish(SN)
Alepisaurus brevirostris
—
—
155
84
257
59
Lancetfishes
Alepisaurus spp.
—
—
1431
98
—
—
Long-finned bream
Taractichthys longipinnis
—
—
—
—
—
292
Mahi mahi
Coryphaena hippurus
17,463
19,090
1436
211
447
—
Oilfish
Ruvettus pretiosus
555
1091
420
456
653
900
Opah
Lampris guttatus
68
4724
527
129
80
213
Pomfrets
Family Bramidae
—
—
623
60
—
40
Ray's bream
Brama brama
—
—
—
—
1074
10,547
Ribbonfishes
Family Trachipteridae
—
—
—
—
—
22
Rudderfish
Centrolophus niger
—
—
—
—
—
90
Sickle pomfret
Taractichthys steindachneri
—
—
122
21
—
—
Slender barracuda
Sphyraena jello
—
—
—
—
121
—
Snake mackerel
Gempylus serpens
1971
9881
256
44
—
—
Snake mackerels
Family Gempylidae
—
—
456
10
—
—
Southern Ray's bream
Brama spp.
—
—
—
—
—
28
Sunfish
Mola ramsayi
—
—
—
—
249
99
Sharks and rays
Bigeye thresher shark
Alopias superciliosus
149
1930
145
61
—
—
Blacktip shark
Carcharhinus limbatus
—
—
445
125
—
—
Blue shark
Prionace glauca
31,503
31,413
5601
1628
1689
12.797
Bronze whaler
Carcharhinus brachyurus
—
—
—
—
116
—
Crocodile shark
Pseudocarcharias kamoharai
153
73
continued
186
Fishery Bulletin 102(1)
Table 2 (continued)
Fishery
CP
WP
SP
SP
NP
bigeye
bigeye
WP
yellowfin
Bluefin
Common name
Species
swordfish
tuna
tuna
distant
tuna
tuna
Sharks and rays (continued)
Dog fishes
Family Squalidae
—
—
—
—
—
60
Dusky shark
Carcharhinus obscurus
—
112
—
—
20
—
Grey reef shark
Carcharhinus amblyrhynchos
—
—
282
64
—
—
Hammerhead shark
Sphyrna spp.
—
—
142
191
22
—
Long finned mako
Isurus paucus
—
83
108
15
—
—
Oceanic whitetip shark
Carcharhinus longimanus
568
2373
2376
384
142
—
Porbeagle
Lamna nasus
—
—
—
—
27
1011
Pelagic stingray
Dasyatis violacea
2374
2849
1212
248
534
109
Pelagic thresher shark
Alopias pelagicus
—
—
77
34
—
—
School shark
Galeorhinus galeus
—
—
—
—
—
143
Short finned mako
Isurus oxyrinchus
476
685
408
169
432
128
Silky shark
Carcharhinus falciformis
25
1433
5396
2406
8
—
Silvertip shark
Carcharhinus albimarginatus
—
—
168
74
—
—
Thintail thresher shark
Alopias vulpinus
—
74
—
—
—
31
Thresher shark
Alopias superciliosus
—
—
415
—
93
18
Tiger shark
Galeocerdo cuvier
—
—
56
18
38
—
Velvet dogfish
Zameus squamulosus
—
—
—
—
—
156
Whip stingray
Dasyatis akajei
—
—
78
15
—
—
Seabirds
Albatrosses
Family Diomedeidae
—
—
—
—
—
88
Petrels
Family Procellariidae
—
—
—
—
—
29
Other seabirds
Family Procellariidae
—
—
—
—
38
200
All operations
104,054
238,340
73,212
30,222
51,699
40,343
To maintain a focus on the effects of soak time, the models
were limited to simple combinations of fixed effects and
interaction terms. Dawn and dusk were added to various
models of each species in each fishery. To reduce complex-
ity, year and season were limited to models of seven spe-
cies (bigeye tuna, oilfish, swordfish, blue shark, albacore,
southern bluefin tuna, long-nosed lancetfish) in the two
South Pacific fisheries. The seven species represented
four taxonomic groups and the full range of responses
observed in preliminary analyses of the soak-time-catch-
rate relationship.
Random effects We added random effects to all models to
allow catch rates of segments within each longline opera-
tion to be related. The random effects model assumes that
there is an underlying distribution from which the true
values of the probability of catching the species, jt, are
drawn. The distribution is the among-operation varia-
tion or "random effects distribution." The operations are
assumed to be drawn from a random sample of all opera-
tions, so that the random effects (0() in the relationship
between catch rate and soak time for each operation (i) are
independent and normally distributed with 0~N(Q, a2).
The random effects and various combinations of the fixed
effects were added to the linear predictor presented in
Equation 5.
For each species in the South Pacific yellowfin tuna
data set we compared the performance of models under
an equal correlation structure with that of models under
an autoregressive correlation structure. Under an au-
toregressive structure, catch rates in the different hourly
segments within the operations are not equally correlated.
For example, the correlation between segments might be
expected to decline with increased time between seg-
ments. However, we used an equal correlation structure
for all models because the Akaike's information criterion
(AIC) and Sawa's Bayesian information criterion (BIO
indicated that there was no clear advantage in using the
autoregressive structure rather than an equal correlation
structure.
Implementation We implemented the models in SAS
(version 8.0) using GLIMMIX, a SAS macro that uses
iteratively reweighted likelihoods to fit generalized linear
Ward et al.: The effect of soak time on pelagic longline catches
187
Seabirds
Other fish
Tuna
Billfish
Sharks
i
-0.2
SP Bluefin
— « — Other seabirds (1 07)
-Albatross (0-99)
Petrel (1.17)
— Lancetfish(SN)(1)
"Opah(1 .03)
Pomfret(1 16)
-Lancetfish(LN)(1.02)
Southern Ray's bream (0.96)
"© — Long finned bream (111)
^Ray's bream (2.47)
— © Sunfish (0.97)
© Ribbonfish (0.93)
Seabirds
Other fish
e Rudderfish (0.89)
© Escolar (0.66)
-e-Oilfish (0.98)
-e-Albacore (0.94)
Slender tuna (0.9)
"-Butterfly mackerel (0.93)
eSouthern bluefin (1.4)
—©—Swordfish (0 9)
— Thintail thresher shark (0.88)
— Mako (0.93)
©Blue shark (1 87)
-©"Porbeagle (0.92)
-© Ray (0.89)
Tuna
Billfish -
Sharks
— I —
0.0
"I
0.2
SP Yellowfin
© — ; Other seabirds (1.26)
— © iBarracouta (0.99)
— © — 'Slender barracuda (0.98)
©-?— Opah (0.99)
-©iancetfish (LN) (1 14)
-s-Mahi mahi (1.09)
— «r-Lancetfish (SN) (0.96)
© Great barracuda (0.95)
:-e-Ray,s bream (1.71)
■ — e — Sunfish (0.99)
; — e— Oilfish (1.23)
-©"Escolar (1.33)
-©"Skipjack (1 .06)
©Yellowfin (2.33)
—f3— Southern bluefin (2.2)
©Albacore(2.12)
-r6— Wahoo (0.96)
-®-Bigeye(1 16)
— © — Sailfish (1 03)
— 9 — Blue marlin (0.88)
r-e-Shortbill spearfish (0.99)
:— e — Black marlin (0.92)
■ -©-Striped marlin (0.94)
-©"Swordfish (0.85)
©i Porbeagle (0.87)
j-e Silky shark (0.86)
Tiger shark (0.87)
"Mako (1.06)
-Ray (0 99)
> — Bronze whaler (0.95)
© — Oceanic whitetip (0.99)
©-Blue shark (0.99)
© Hammerhead (0.93)
© Dusky shark (0.85)
-0.2
Soak time coefficient
0.0 0.2
Figure continued on next page.
Figure 4
Coefficients for the effect of soak time on the catch rates of the most abundant species in each fishery. The coefficients are from
random effects models where soak time is the only factor. Horizontal bars are 95% confidence intervals for the estimated coefficient.
The dispersion parameter is shown in parentheses (it is 1.00 for species that are distributed as predicted by the model, but may be
higher for species that have a more clumped distribution along the longline).
mixed models (Wolfinger and O'Connell, 1993). To judge
the performance of the various model formulations, we
checked statistics, such as deviance and dispersion, and
examined scatter plots of chi-square residuals against the
linear predictor I rj) and QQ plots of chi-square residuals.
We used the AIC and BIC to compare the performance of
the various model formulations.
Variance in the binomial model depends on only one pa-
rameter, P. A dispersion parameter is therefore necessary
to allow the variance in the data to be modeled. In effect,
the dispersion parameter scales the estimate of binomial
variance for the amount of variance in the data. The disper-
sion parameter will be near one when the variance in the
data matches that of the binomial model. Values greater
than one ("over-dispersion") imply that the species may
have a clumped distribution along the longline.
Results
Soak time
For most species, soak time had a positive effect on catch
rates (Fig. 4). In addition to being statistically significant,
the effect of soak time made a large difference to catch
rates at opposite ends of the longline. In the South Pacific
yellowfin tuna fishery, for example, the expected catch rates
of swordfish can vary from 0.6 (CI ±0.1) per 1000 hooks
(5 hours) to 1.9 (CI ±0.3) per 1000 hooks (20 hours)
(Table 3). A soak time of 5 hours and 3500 hooks (if that
were possible) would result in a total catch of about
two swordfish. In contrast, almost seven swordfish are
expected from a longline operation of the same number of
hooks with 20 hours of soak time.
188
Fishery Bulletin 102(1)
WP Bigeye
WP Distant
Other fish
Tuna
Billfish -
Sharks
-0.2
Great barracuda (0.94)
-Mahi mahi(1.15)
-«— Lancetfish (LN) (0.99)
Lancetfish (SN) (0.97)
■e — Snake mackerel (1.06)
-Barracudas (0.96)
*- Opah (11)
■9-Escolar (0.97)
-9 Sickle pomfret (1 .2)
-e-Pomfret (0.99)
- &— Escolars (1.07)
— ° — OHfish (1.12)
-^Skipjack (1 12)
■«-Wahoo(1)
?Yellowfin (1.61)
:eAlbacore(1.45)
!eBigeye(1.18)
tShortbill spearfish (0.98)
-^Swordfish (1.04)
_e_Stnped marlin (1.23)
— e— Sailfish (1.51)
— e — Black marlin (1.32)
-o-Blue marlin (1.14)
Hammerhead (0.87)
Grey reef shark (1 .49)
1 Pelagic thresher shark (1.16)
■® Bigeye thresher shark ( 1 .06)
-° Tiger shark (1)
Other fish -
Pomfret (1.43)
-Mahi mahi (1.45)
Lancetfish (LN) (1.02)
e— Great barracuda (0.84)
— e Opah (1.24)
e Barracudas (0.97)
— e — — Sickle pomfret (2.13)
Escolar (1.15)
-Lancetfish (SN) (0 84)
Snake mackerel (3.56)
-Ollfish (1.17)
Tuna
Billfish
-e Sllvertip shark (1.17)
■Q-Silky shark (115)
-6— Thresher sharks (0.88)
-s— Short finned mako (0.91 )
"^Pelagic stingray (0.92)
"Long finned mako (0 96)
Sharks ■
-° — Blacktip shark (1.3)
9Blue shark (0.93)
-^Oceanic whitetip (0.91)
e Whip stingray (1 .37)
e Crocodile shark (1 .2)
0.0
I
0.2
Skipjack (0.91)
Wahoo (0.97)
e-Yellowfin (2.02)
&Albacore(1.51)
-e"Bigeye(1.32)
■Black marlin (0.89)
Striped marlin (1.19)
— Shortbill spearfish (1.17)
-°— Sailfish (1 .04)
-° — Swordfish (0.89)
— s— Blue marlin (0 98)
Tiger shark (1.2)
— Crocodile shark (0.95)
Hammerhead (0 88)
Whip stingray (1.01)
Sllvertip shark (1 .46)
■Blue shark (0.95)
Blacktip shark (0.91)
-e-Silky shark (1.5)
e Pelagic stingray (1)
e Oceanic whitetip (1 .06)
"Pelagic thresher shark (1.81)
-Bigeye thresher shark (1.17)
"Short finned mako (0.91)
-0.2
0.0
0.2
Soak time coefficient
Figure 4 (continued)
For some species (e.g. seabirds, skipjack tuna, and mahi
mahi), soak time had a negative effect on catch rates that
was often statistically significant (Fig. 4). For skipjack
tuna in the Western Pacific distant fishery, for example.
catch rates decreased from 1.3 (CI ±0.2) per 1000 hooks
for a soak time of 5 hours to 1.0 (CI ±0.1) per 1000 hooks
(20 hours). Soak time had a small or statistically insignifi-
cant effect on catch rates for several species, such as yel-
lowfin tuna and shortbill spearfish.
Fixed effects
Exposure to dusk had a positive effect on the catch rates
for most species (Fig. 5). Dusk often had a negative effect
on the catch rates of billfish, such as striped marlin and
sailfish. For most species, however, the effect of dawn was
weaker, and it influenced the catch rates of fewer species.
Like soak time, timing made a substantial difference to
catch rates (Table 4). For a soak time of 12 hours in the
South Pacific yellowfin fishery, for example, longlinc seg-
ments exposed to both dawn and dusk have a catch rate
of 2.0 (CI ±0.5) escolar per 1000 hooks. The catch rate is
0.8 (CI ±0.1) per 1000 hooks for segments that were not
exposed to dawn or dusk.
The effects of timing on catch rates were most pro-
nounced in the South Pacific bluefin tuna fishery. The
fishery also showed the greatest range in soak time coef-
ficients, and the coefficients tended to be larger than those
of other fisheries (Fig. 4).
Separately, the fixed effects often had statistically signifi-
cant relationships with catch rates of the seven species that
we investigated in detail. However, the interaction between
soak time and each fixed effect was less frequently signifi-
cant. Season was significant, for example, in none of the
six models that included a soak-time-season interaction
term. By comparison, season was significant in six of the
18 models that included season as a factor but not with a
soak-time-season interaction term. The effect of soak time
was not significant for southern bluefin tuna in any model
for the South Pacific bluefin tuna fishery. It was significant
Ward et al.: The effect of soak time on pelagic longline catches
189
Tuna
NP Swordfish
hBlgeye (0 94)
3 Pacific bluefin (0.95)
CP Bigeye
Billfish
Sharks
Tuna
*— Skipjack (0-84)
-s-Yellowfin (0 87)
^Albacore (1.03)
Slue marlin (0.91)
— Shortbill spearfish (0.93)
"Swordfish (0 96)
-°-Striped marlin (0.88)
e Sailfish (0 96)
Billfish
-Salmon shark (0.96)
"° — Oceanic whitetip (0.98)
"e Crocodile shark (0 89)
-e — Short finned mako (0 95)
eBlue shark (0.96)
e Bigeye thresher shark (0.83)
Sharks
-0.2
0.0
— I
0.2
-0.2
Soak time coefficient
Figure 4 (continued)
^Skipjack (0.85)
eAlbacore (0.81)
eYellowfin (0.93)
bigeye (0.88)
Black marlin (0.89)
eStnped marlin (0 86)
■^Shortbill spearfish (0 89)
"^Blue marlin (0.86)
— e Sailfish (1.05)
"^Swordfish (0.9)
— Sandbar shark (1.24)
e Bignose shark (1.19)
_e— Short finned mako (0.94)
eBlue shark (0 81)
-e-Silky shark (0.93)
-° — Pelagic thresher shark (0.88)
"^Oceanic whitetip (1.01)
"^Bigeye thresher shark (0.86)
e Long finned mako (0.86)
e Thintail thresher shark (0.9)
0.0
"Dusky shark (1.05)
-°— Crocodile shark (0.89)
I
0.2
in 36 of the 48 models for the other six species. We con-
cluded that the fixed effects modified the intercept of the
soak-time-catch-rate relationship, but they rarely altered
the slope of the relationship.
Akaike's information criterion (AIC) and Sawa's Bayes-
ian information criterion (BIC ) both indicated that models
with soak time as the only variable were the most or second
most parsimonious model. This was the case for all models,
except for several models of albacore and long-nosed lan-
cetfish. Therefore the following discussion concentrates on
the effects of soak time and timing on catch rates.
Discussion
In considering results of the random effects models, we
examined patterns in the effects of soak time and timing
among taxonomic groups, the mechanisms that may cause
the patterns, and their implications. First, however, we
investigated whether the effects were consistent for the
same species between fisheries.
Comparison of fisheries
The effect of soak time was consistent for several spe-
cies between the fisheries, despite significant differences
in fishing practices and area and season of activity. For
example, the soak time coefficients for species in the South
Pacific yellowfin tuna fishery were very similar to those of
the same species in the Central Pacific bigeye tuna fishery
(r=0.79) (Fig. 6).
Several species had a narrow range of soak time coef-
ficients over all the fisheries analyzed. Estimates of the
coefficient of yellowfin tuna, for example, ranged from 0.00
(CI ±0.01) in the South Pacific yellowfin fishery to 0.04
( CI ±0.0 1 ) in the North Pacific swordfish fishery. A coefficient
of 0.04 is equivalent to a difference of 1.3 yellowfin tuna per
1000 hooks between longline segments with soak times of
5 and 20 hours. The range in coefficients is also small for
other abundant and widely distributed species, such as al-
bacore (r=0. 00-0.05) and blue shark (r=0.01-0.05).
For many species, however, the correlation between soak-
time coefficients from different fisheries was poor (Fig. 6).
190
Fishery Bulletin 102(1)
Table 3
Examples of the effect of
soak time on expected catch
rates of species in the South Pacific yellowfin tuna
ishery.
The expected catch rates
i number per 1000 hooks I are
predicted from the soak-time coefficient for each
species
for longline segments exposed to a dusk period with
a soak
time of 5 or 20 hours. Figu
re 4 shows the 95% confidence
intervals for soak-time coe
fficients used to calculate the
expected catch rates. LN =
ong-nosed; SN = short-nosed.
Species
Soak time
h)
5
20
Tuna and tuna-like species
Albacore
15.5
13.4
Bigeye tuna
1.1
2.3
Skipjack tuna
1.3
1.0
Southern bluefin tuna
5.2
5.5
Yellowfin tuna
8.4
7.7
Billfish
Black marlin
0.4
1.6
Blue marlin
1.2
0.4
Sailfish
0.8
1.0
Shortbill spearfish
1.0
1.6
Striped marlin
0.8
1.0
Swordfish
0.6
1.9
Other bony fish
Barracouta
0.8
0.7
Escolar
0.8
3.1
Great barracuda
0.9
1.1
Lancetfish (LN)
2.7
2.4
Lancetfish (SN)
1.6
1.4
Mahi mahi
1.0
0.9
Oilfish
0.8
2.2
Opah
0.7
0.5
Ray's bream
1.8
2.0
Slender barracuda
1.7
1.6
Sunfish
0.6
1.3
Wahoo
1.0
1.1
Sharks and rays
Blue shark
1.1
2.0
Bronze whaler
0.7
0.8
Dusky shark
0.4
0.8
Hammerhead
0.2
1.8
Mako
0.6
0.8
Oceanic whitetip
0.5
0.9
Porbeagle
1.2
1.1
Pelagic stingray
0.9
1.2
Thresher shark
0.6
1.0
Tiger shark
0.5
0.5
Table 4
Examples of the effect of timing on expected catch rates
of species in the South Pacific yellowfin tuna fishery. The
expected catch rates (number per 1000 hooks I are pre-
dicted from the soak-time coefficient for each species for a
longline operation with a soak time of 12 hours. The differ-
ent catch rates are for longline segments exposed to nei-
ther the dawn or dusk period, for dawn only, and for dawn
and dusk periods. LN = long-nosed; SN = short-nosed.
Period
Neither
Dawn
Dawn
Species
period
only
+ dusk
Tuna and tuna-like species
Albacore
12.3
14.0
16.5
Bigeye tuna
0.9
1.2
2.1
Skipjack tuna
1.4
1.2
1.0
Southern bluefin tuna
3.8
2.9
4.1
Yellowfin tuna
7.7
7.6
8.0
Billfish
Black marlin
1.2
0.6
0.4
Blue marlin
0.4
1.0
1.4
Sailfish
0.8
0.7
0.7
Shortbill spearfish
1.3
0.9
0.9
Striped marlin
0.8
0.9
0.9
Swordfish
0.5
0.7
1.3
Other bony fish
Barracouta
1.1
1.2
0.7
Escolar
0.8
1.0
2.0
Great barracuda
1.0
0.8
0.8
Lancetfish (LN)
2.8
2.7
2.5
Lancetfish (SN)
1.2
1.1
1.3
Mahi mahi
1.2
1.3
1.1
Oilfish
0.8
1.1
1.8
Opah
0.5
0.5
0.6
Ray's bream
0.8
0.7
1.6
Slender barracuda
2.0
1.5
1.2
Sunfish
0.8
0.6
0.7
Wahoo
1.2
1.3
1.1
Sharks and rays
Blue shark
1.3
1.4
1.4
Bronze whaler
0.6
0.9
1.0
Dusky shark
0.1
0.1
0.6
Hammerhead
0.4
0.2
0.3
Mako
0.7
0.8
0.8
Oceanic whitetip
0.7
0.8
0.7
Porbeagle
1.0
0.6
0.6
Pelagic stingray
0.9
0.9
1.1
Thresher shark
0.6
0.6
0.7
Tiger shark
0.4
0.5
0.7
For a few species (e.g. tiger shark) the poor correlation may
have been a function of small sample sizes and the wide
confidence intervals of the estimates. For other species the
estimates were well determined, yet poorly correlated,
e.g. the coefficient for short-nosed lancetfish was 0.09
(CI ±0.05) in the Western Pacific distant fishery compared
to 0.01 (CI ±0.04) in the Western Pacific bigeye tuna fishery.
Therefore, we urge caution in applying our estimates to the
same species in longline fisheries in other areas.
Ward et a!.: The effect of soak time on pelagic longlme catches
191
SP Yellowfin WP Bigeye
o
dusk preference
dawn & dusk ^ -
dusk preference
dawn & du>k
•
Raj 's bream
•
• Swordfish
C3
• o
Oilfish .
Hammerhead 4 Blue martin
Oiltish
•
Tiger shark *
sk coefficient
0.0
•
• • Tiger shark
;• L '
• •
•
* • Swordfish
Q
• •
l
•
3
•
Black marlin
9 '
•
Spnped marlin
•
• •
Black marlin
Hammerhead •
c
nol dawn or dusk dawn preference _
not dawn or dusk dawn preference
~~
-1.0 -0.5 0.0 0.5 10 -1.0 -0.5 0.0 0.5 10
Dawn coefficient
Figure 5
Pair-wise comparison of coefficients for the effects of dawn and dusk on catch rates for two
fisheries. The shading of each symbol represents the sum of the standard errors of the dawn
and dusk estimates (heavy shading for the lowest standard errors; light shading for large
standard errors). Not all species names are shown.
Underlying mechanisms
The broad taxonomic groups taken by longlme each rep-
resent a wide range of life history strategies and feeding
behaviors. Nevertheless, the results show a tendency for
soak time to have a positive effect on catch rates of most
shark species (Fig. 4). It also had a positive effect on catch
rates of many billfish species, including striped marlin,
black marlin, and swordfish. There is no clear pattern in
the effect of soak time on catch rates of tuna or other bony
fish. It had a negative effect on the four seabird groups.
The results imply that the ability of a species to stay
alive and to escape or avoid scavengers while hooked is
important in determining the catch that is actually brought
on board. The effect of soak time is significantly correlated
with the ability of a species to survive while hooked on the
longline in the four fisheries with data on survival (Fig. 7).
Soak time has a strong, positive effect on catch rates of spe-
cies like blue shark, which are almost always alive when
branchlines are retrieved. Species like skipjack tuna and
seabirds are usually dead. Soak time had a negative effect
on their catch rates. The opposite trend would be expected
if escape is a significant process that affects catch rates; if
escape is important, soak time should have a negative af-
fect on the catch rates of the most active species. Therefore
removal by scavengers is likely to be more important than
escape in determining catch rates for many species.
Longline branchlines are usually 20-30 m in length, al-
lowing considerable room for a live, hooked animal to evade
predators or scavengers. Or, scavengers may be attracted
by immobile and dead animals. The scavenger avoidance
hypothesis is attractive, but it is difficult to test with ob-
server data. Data from hook-timer experiments may help
to estimate the total number of animals that are lost or
removed from the longline. Data presented by Boggs ( 1992 )
showed a large number of hook-timers that were triggered
but which did not hold an animal when the branchline was
retrieved, e.g. his data show that 2-4"7r of hook-timers on
10,236 branchlines that had "settled" were activated but
did not have an animal. It is unclear whether the trigger-
ing of hook-timers was due to equipment malfunction or
whether it represents high loss rates. Of particular signifi-
cance to the question of loss rates is the fact that current
hook-timer technology does not identify the species that
were lost and whether they were alive or dead.
We noticed that soak-time coefficients tended to be poorly
correlated between fisheries and that the effects of soak
time on catch rates were most pronounced in the South Pa-
cific bluefin tuna fishery. Our scavenging hypothesis might
explain those observations as evidence that the activities of
scavengers vary between fisheries. For example, blue shark
might be an important scavenger. They are most abundant
in temperate areas (Last and Stevens, 1994). Our analyses
showed a predominance of negative soak-time coefficients
192
Fishery Bulletin 102(1)
CD
a.
=0.10*
•>•'
y
-0 1 ( I 0 2
WP Distant coefficient
m
o.
/-0.65*
-o I o o ii I ii 2
SP Yellowfin coefficient
Q.
,-=oo,s
-ol I 0.2
CP Bigeye coefficient
r=0.15*
o
u
•ii
<u
• •
0
= -
•
fl
en
•
n
•
C/3
- .
-0 1
0
Ml
SP Yellowfin
coefficient
o
S
w
0_
CL
r=0. 12ns
«*•
-ii 1 0.0 0 I 0 2
CP Bigeye coefficient
r=0.79*
3=
o
S -
• •
-i' | 0.0 ii | (12
CP Bigeye coefficient
Figure 6
Pair-wise comparison of soak time coefficients for species that were common to fisheries. The coefficients are from ran-
dom effects models where soak time is the only factor. The shading of each symbol represents the size of the standard
error of the estimate. V is the correlation coefficient of a linear regression of coefficients ( * indicates that the regres-
sion slope is significantly different from one at the 95% level, whereas "ns" indicates that the null hypothesis, that the
regression slope equals one, cannot be rejected).
in the South Pacific bluefin tuna fishery — perhaps indicat-
ing that loss rates may be particularly high where blue
shark are abundant.
Nevertheless, there are other plausible explanations for
the differences in soak-time effects between fisheries. The
movement of branchlines caused by wave action will cause
animals to fall off hooks, especially when branchlines are
near the sea surface. Rough seas are frequently experi-
enced in the North Pacific swordfish and South Pacific
bluefin tuna fisheries where the soak-time effects were
most pronounced.
Another source of loss might be the breakage of longline
branchlines. The animal's teeth or rostrum might abrade
the branchline causing the branchline to fail and allow-
ing the animal to escape. In this regard it is noteworthy
that Central Pacific bigeye tuna longliners often use wire
for the end of branchlines or "leader" whereas North Pa-
cific wwordfish longliners use monofilament nylon leaders
(Ito4).
Mortality estimates
The results of our study show that longline catch rates that
are not adjusted for the effects of soak time will under-
estimate the level of mortality of several species because
they are lost after being hooked. The soak time effect was
negative for albatrosses and other seabirds. This finding
agrees with field observations (e.g. Brothers, 1991) that
most seabirds are taken during longline deployment in
the brief period after the bait is cast from the vessel until
the bait sinks beyond the depth that seabirds can dive to.
Those observations indicate that counts of seabirds when
they are brought on board do not cover the total number
hooked because many fall off or are removed by scavengers
or are lost during the operation.
1 It... K. 2002. Personal commun. National Marine Fisheries
Service (NOAA), 2570 Dole Street, Honolulu Hawaii 96822-
2396.
Ward et al.: The effect of soak time on pelagic longlme catches
193
WP Bigeye
CM .
d
d
Whip stingray
o
o
m
•
■a
• • •
•
• •
• m
r.~ •
••
Skipjack •
•
ci
r=0.42*
WP Distant
Grej reef shark
•
•
•
•
• •
•
•
•
•
•
•
•
•" • •
• •
•
•
Skipjack
r=0.46*
0 2" 4(1 <M 80 100
SP Bluefin
0 20 -40 no 80 100
SP Yellowfin
• Oiltish
Escolar
"... 1 % «
Other seabirds
=0.32ns
Escnlai
: •: •
Skipjack
f":
=0.54
20 40 60 80 100
0 20 40 60 80 100
Proportion alive (%)
Figure 7
Soak-time coefficients plotted against the proportion of each species reported to be alive
when brought on board. Not included are species where less than ten individuals for the
fishery had a record of life status. The coefficients are from random effects models where
soak time is the only factor. The shading of each symbol represents the size of the standard
error of the estimate. The proportion alive is assumed to be measured without error. V is
the correlation coefficient of a linear regression of coefficients (* indicates that the regres-
sion slope is significantly different from zero at the 95<7c level i.
Seabirds provide a unique case for estimating loss rates
because they are only caught when the longline is deployed
(Brothers. 1991). Within minutes of the branchline being
deployed, the capture rate ( a in Eq. 4 ) falls to zero whereas
the loss rate /3 might be constant or it might vary. There-
fore, the probability of a seabird being on a hook when the
branchline is retrieved is
n\T)
-0T
(6)
We estimated a soak-time coefficient of -0.0302 (CI
±0.0462) for albatrosses in the South Pacific bluefin tuna
fishery. Substituting 0.0302 for ft in Equation 6 and 10.4
hours for T ( the average soak time of hooks deployed by
the longliners), we estimated that 27% of albatrosses are
lost after being hooked but before the branchlines are
retrieved. The loss rate is about 12% for petrels 1/3=0.0123)
and 45% for other seabirds (0=0.0582). It is about 26% for
other seabirds in the South Pacific yellowfin tuna fishery
(j6=0.0307, T=10.0 hours).
For fishes and sharks, we do not know how the probabil-
ity of capture, or capture rate, or loss rate varies during
a longline operation. However, hook-timer experiments
194
Fishery Bulletin 102(1)
and observer programs may provide estimates of those pa-
rameters. Broad limits for the probability of capture may
also be obtained if observers were to report the number of
branchlines that are retrieved with missing baits or miss-
ing hooks.
For most species, capture rates must balance or outweigh
loss rates. In this case, captures result from the increased
exposure of animals to the longline as a result of movement
and, perhaps, the dispersal of chemical attractants during
the operation. However, we must stress that losses are also
likely to be occurring for the species that have positive co-
efficients. The analyses indicate the relative levels of loss
between longline segments of varying soak time. Other
than those for seabirds, we cannot estimate the levels of
catch that are lost.
Adding to the uncertainty over loss rates is the unknown
fate of lost animals. For seabirds it is known that most
drown soon after being hooked. The few seabirds that sur-
vive while hooked eventually drown during longline re-
trieval (Brothers, 1991). However, it is not known whether
other lost animals are dead or alive.
Results of our analyses may also be useful for monitoring
programs. Observers are increasingly being placed on long-
liners to collect data on bycatch and to independently verify
data reported in logbooks. A sampling approach is neces-
sary in some fisheries because observers are often unable
to monitor the entire longline retrieval. Indications that
catch rates of some species at the end of the retrieval are
double those at the beginning necessitate care in designing
observer monitoring protocols and in the interpretation of
the data. Observers could also collect information on the
number of hooks retrieved without baits. Such data would
greatly improve the estimates of a and fi required for the
theoretical model. For the empirical model, catch rate data
from research surveys where longline segments have very
short (<4 hour) soak times would improve estimates of
soak-time coefficients.
Historical changes
The interaction of year and soak time was rarely significant
for the random effects models of the seven species exam-
ined in detail. This might suggest that soak-time-catch-
rate relationships are stable over time. However, the range
of years that we analyzed was limited to 1992-97. Over
larger time scales there have been large variations in the
abundance of individual species and the mix of species
comprising the pelagic ecosystem. We cannot predict how
soak-time-catch-rate relationships would change with
those long-term variations.
Our original motivation for examining the effects of
soak time was the hypothesis that the number of hooks
per operation and soak time have increased since longlin-
ing commenced and that this may have resulted in an
overestimation of billfish catch rates in early years. Wardr'
presented information on temporal trends in soak time
5 Ward, P. 2002. Historical changes and variations in pela-
gic longline fishing operations, http://fish.dal.ca/-myers/pdf
papers.html. (Accessed 22 February 2003.1
and timing for several longline fleets. Although there is
uncertainty over the early operations, the available infor-
mation indicates significant historical changes in Japan's
distant-water longline operations. Average soak time
shows a decline from over 11.5 hours before 1980 to 10.0
hours in the 1990s. For species with a negative soak-time
coefficient, this apparently modest reduction in soak time
would inflate catch rate estimates for recent years. It would
result in reduced catch-rate estimates for species with posi-
tive coefficients. For example, the expected catch rate for
swordfish is 0.94 (CI ±0.06) per 1000 hooks for a soak time
of 11.5 hours compared to 0.82 (CI ±0.06) per 1000 hooks
for 10.0 hours.
More significant may be changes in the timing of op-
erations. During 1960-80 most baits used with Japan's
distant-water longliners were available to fish at dawn
whereas about 50% were also available at dusk. Longlines
were deployed and retrieved at later times in the 1990s so
that about 30% of baits were available at dawn and about
70% available at dusk. In the case of swordfish, the changes
in timing would moderate the effects of reduced soak time.
The expected catch rate for swordfish is 0.89 per 1000
hooks in the early operations compared to 0.83 per 1000
hooks in the later operations.
Conclusions
The results have important implications for fishery man-
agement and assessments that rely on longline catch
data. Modifications to data collection, such as recording
the number of hooks with missing baits during longline
retrieval, would greatly improve mortality estimates. The
mortality of species like seabirds is significantly higher
than previously estimated. Such underestimation may be
particularly critical for the assessment and protection of
threatened species of seabirds. Furthermore, the changes
in timing and reduction in soak time have resulted in a
systematic bias in estimates of mortality levels and abun-
dance indices for many species. For species like swordfish,
where soak time has a positive effect on catch rates, the
stocks might be in better shape than predicted by current
assessments ( if assessments were solely based on catch and
effort data). The opposite situation would occur for species
with negative soak-time coefficients: assessments that use
long time-series of longline catch data will over-estimate
the species' abundance so that population declines are
more severe than previously believed.
Acknowledgments
Grants from the Pew Charitable Trust, Pelagic Fisheries
Research Program, and the Killam Foundation provided
financial support for this work. Peter Williams (Secretariat
of the Pacific Community). U.S. National Marine Fisher-
ies Service staff (Kurt Kawamoto, Brent Miyamoto, Tom
Swenarton, and Russell Ito ) and Thim Skousen (Australian
Fisheries Management Authority) provided observer data
and operational information on the fisheries. We are espe-
Ward et al.: The effect of soak time on pelagic longline catches
195
cially grateful to the observers who collected the data used
in this study and thank the masters, crew members, and
owners of longliners for their cooperation with the observer
programs. Pierre Kleiber, Ian Jonsen, Julia Baum, Boris
Worm and an anonymous referee provided many useful
comments on the manuscript.
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196
Abstract— Annual mean fork length
(FL) of the Pacific stock of chub mack-
erel {Scomber japonicus ) was examined
for the period of 1970-97. Fork length at
age 0 (6 months old) was negatively cor-
related with year-class strength which
fluctuated between 0.2 and 14 billion in
number for age-0 fish. Total stock bio-
mass was correlated with FL at age but
was not a significant factor. Sea surface
temperature (SST) between 38-40°N
and 141-143°E during April-June
was also negatively correlated with FL
at age 0. A modified von Bertalanffy
growth model that incorporated the
effects of population density and SST on
growth was well fitted to the observed
FL at ages. The relative FL at age 0 for
any given year class was maintained
throughout the life span. The variabil-
ity in size at age in the Pacific stock of
chub mackerel is largely attributable to
growth during the first six months after
hatching.
Effects of density-dependence and
sea surface temperature on interannual variation
in length-at-age of chub mackerel
(Scomber japonicus) in the
Kuroshio-Oyashio area during 1970-1997
Chikako Watanabe
Akihiko Yatsu
National Research Institute of Fisheries Science
Fisheries Research Agency
2-12-4 Fukuura, Kanazawa
Yokohama 236-8648. Japan
E-mail address (for C Watanabe): falconer a affrc go ip
Manuscript approved for publication
22 September 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:196-206(2004).
Variability in growth of marine fishes
has been attributed to the effects of
density-dependence or environmental
factors such as water temperature, or
to the effects of both factors (e.g. Moyle
and Cech, 2002). Size-at-age data are
crucial because they are necessary
for stock assessment methods such
as virtual population analysis, yield
per recruit, and spawning-per-recruit
analyses (Pauly, 1987; Mace and Sissen-
wine, 1993; Haddon, 2001) and are pos-
sibly useful for detecting regime shifts
as well (Yatsu and Kidoroko, 2002).
Around Japan, the effects of population
density and sea water temperature on
fish growth have been shown for the
Pacific stock of chub mackerel (Scomber
japonicus) (Iizuka, 1974), Japanese
Spanish mackerel {Scomberomorus
niphonius) (Kishida, 1990), the Pacific
and Tsushima Current stocks of Japa-
nese sardine (Sardinops melanostietus)
(Hiyama et al, 1995; Wada et al., 1995),
and Japanese common squid ( Todarodes
pacificus) (Kidokoro, 2001).
The Pacific stock of chub mackerel is
one of the most important commercially
exploited fish populations in Japan and
has been managed by the total al-
lowable catch (TAC) system in Japan
since 1997. Chub mackerel seasonally
migrate along the Pacific coast of Japan
from Kyushu to Hokkaido. They spawn
in the coastal waters around Izu Islands
and off southwestern Japan between
February and June (Fig. 1, Watanabe,
1970; Usami, 1973; Murayama et al.,
1995; Watanabe et al., 1999). Adult fish
(after spawning) and their offspring
migrate eastward along the Pacific
coast with the Kuroshio Current. Ju-
venile mackerel of about 6 months old
usually recruit to the purse-seine and
set-net fisheries off the coast of north-
eastern Japan at the end of summer
(Fig. 1, Odate, 1961; Kawasaki, 1966;
Watanabe, 1970; Iizuka, 1974). The
total catch of the Pacific stock of chub
mackerel increased during the 1960s
and 1970s, peaked at 1.5 million metric
tons in 1978, and then declined to 2.3
thousand tons in 1990 (Fig. 2). The es-
timated total biomass increased in the
1970s from 2.8 million tons in 1970 to
5.9 million tons in 1977, and the consec-
utive occurrences of large year classes
exceeded 7 billion age-0 (6-month-old)
fish in the early and mid 1970s. In 1990,
the biomass was reduced to a minimum
of 0.2 million tons in 1990 (Table 1, Fig.
2; Yatsu et al.1). Relatively large year
classes occurred in 1992 (2.8 billion
fish) and 1996 (4.5 billion fish), and
the total biomass increased in the mid
1990s, but it remained at about 10%
of the level attained in the mid 1970s
(Yatsu et al.1).
On the basis of year-class strength
and variations in fork length (FL) at
ages 0-2 for the 11 year classes present
from 1963 to 1973, Iizuka (1974) sug-
gested an effect of density-dependent
growth on young chub mackerels. In
1 Yatsu, A., C. Watanabe, and H. Nishida.
2001. Stock assessment of the Pacific
stock of chub mackerel in fiscal 2000
year. /;; Stock assessment report, p.
64-87. |In Japanese. Available from Fish-
eries Research Agency, 2-12-4 Fukuura,
Kanazawa. Yokohama 236-8648. Japan.]
Watanabe and Yatsu: Interannual variation in length at age of Scomber japonicus
197
45°N
40CN
35°N
30°N -
Kuroshio-Oyashio transition zone
izu Islands
— i
130°E
140°E
150°E
160°E
Figure 1
Distribution of the Pacific stock of chub mackerel (Scomber japonicus)
and major oceanographic features around Japan. The hatched areas show
spawning grounds. The dotted areas show feeding grounds. Major purse-seine
fishing grounds are surrounded by dashed lines. The fishing grounds around
the eastern coast of Hokkaido failed in 1977 with the decline in biomass
(Hirai, 1991).
6,000 -,
- 20
uT
CO
o
o
i i Stock number at age 0
o
o
I 4,000 -
£1
Total biomass
—- Catch
k number a
/
03
CJ
"O
c
ro
nj
'
|-|
CD
CO
-io S
to
in
CD
E
.2 2,000 -
.o
rn
rn
o
5'
Q.
ro
o
H
^
.
•
•
\
•.
-5 a
v
jO\ y
♦J
rv^^D
nr^rt
rn
70 75 80 85 90 95
Year
Figure 2
Total biomass, total catch, and year-class strength for the Pacific stock of chub mackerel
{Scomber japonicus) (Yatsu, et al.1). Year-class strength was represented by the stock in
number at age 0, estimated by virtual population analysis (Yatsu, et al.1).
this study we describe the variation in FL at age of the
Pacific stock of chub mackerel in the Kuroshio-Oyashio
area, using data from 1970 to 1997 when the stock biomass
fluctuated between 0.2 and 5.9 million metric tons. We use
these data to evaluate the effects of population density and
sea surface temperature on FL at age.
198
Fishery Bulletin 102(1)
Materials and methods
Biological data
Biological data have been compiled since 1964 for purse-
seine, set-net, dip-net catches, and other catches by national
fisheries research institutes and local government fisher-
ies experimental stations in Japan. Fork length (FL) was
measured for one thousand to 100 thousand fish per year
and body weight (BW) and gonad weight were measured for
10-100Tf of these fish. The monthly FL compositions and
the relationships of FL to BW were established for each
year with this data set. Year-specific age-length keys from
1970 to 1994 were adopted from the reports of cooperative
research on Pacific mackerel by local government agencies
in Chiba, Kanagawa, Shizuoka, and Tokyo.2 Between 1995
and 1997, age-length keys were developed by national
fisheries research institutes and local government fisher-
ies experimental stations.
For calculating the mean FL for ages 0, 1, 2, 3, 4, 5. and 6
years and older, we used data from the purse-seine fishery
of northeastern Japan during September-December for
28 years, from 1970 to 1997. The catch of this fishery in
these four months constituted 26-80% ( the 28-year mean is
about 639c ) of the total annual catch of the Pacific stock of
chub mackerel. Catch in number at FL class i (cm) of each
month were calculated by
n.,=C.
(1)
I*
where na i = catch in number at FL class i (cm) (= 1, . . . ,
k, . . 50) of month a {= Sep., Oct., Nov., Dec.];
da t = frequency at FL class i of month a;
w a ( = a mean weight of each FL class derived from
the FL-BW relationship; and
Ca = a total catch of month a.
We then summed na , of 4 months to derive the annual
catch in number at FL class i:
where ntj = the annual catch in number at FL class i at
age J; and
r:j = the proportion of agej at FL class i ( rt 0 + r, 1 +
•••• + '-,*= 1»-
From nlt, we calculated the mean and variance of FL at
age./':
I" »
l.,=^\
(4)
and
I",X,-//
Va /•(/,) = -
2Xi
(5)
where L = mean FL at age./'; and
/,■ i = mean FL at FL class i at age j.
Sea surface temperature
Time-series data for sea surface temperature (SST tem-
peratures averaged over 10 days for 1° latitude x 1° longi-
tude blocks over the northwestern North Pacific between
0-53°N and 110-180°E since 1950) were provided by the
Oceanographical Division of the Japan Meteorological
Agency. The SST data for each block was averaged for
periods of three months (i.e. January-March, April^June,
July-September, and October-December). The relationship
between the SST of each block and FL at age 0 were exam-
ined from 1970 to 1997.
Autocorrelation
For correlation analysis, effective sample sizes («') were
calculated for all time series data to take autocorrelation
into account, n* was computed by the formula (Pyper and
Peterman, 1998):
"i = X "°"
(2)
a Sep
where /;, = the annual catch in number at FL class i.
Using the age-length key, we converted nt to catch at FL
class i at age j:
(3)
J_-i 1
5/jaC/XrO").
(6)
where rx>Xj) and r^Xj) are the autocorrelations of X and Y
at lagj, defined here with the additional weighting factor
proposed by Pyper and Peterman ( 1998):
^(Xt-XKXl+j-X)
r„U) =
"-./
£«■,-*)
(7)
2 Age-length keys. In Kanto Kinkai no Masaba ni tuite, Ap-
pendix 1, vol. 30, 30 p. [In Japanese. Available from Kanagawa
Prefectual Fisheries Research Institute. Jyogashima, Misaki.
Miura. Kanagawa 238-0237. .Iapan.1
Growth model
We used the modified von Bertalanffy growth model to
incorporate the effects of population density and sea sur-
Watanabe and Yatsu: Interannual variation in length at age of Scomber /aponicus
199
face temperature according to Millar
and Myers,3 who nvestigated three
formulations of the modified von Berta-
lanffv equations: 1) a reversible effect
on the growth constant k; 2) a revers-
ible effect on the asymptotic length Lr;
and 3) an irreversible effect on Lx or k.
We tested two of the models, 1 and 2,
to investigate the effect of population
density and SST. We did not test model
3 because we did not consider that the
environmental effects on growth were
permanent. Mean length at age i of
year-class y was estimated with the fol-
lowing formulas:
Model 1: reversible environmental
effect on k
L,v=L„(l-e"*°'-'°) (8)
4v = A-lv + ( L~ ~ A-i.v X 1 - e~* ■ ) ( 9 )
klv=k + PlT,fv+P2D:v. 110)
Model 2: reversible environmental
effect on L
L0,, = L^v(l-e-*'»)
Llv = L,_ly+(L^-L,_lvn-e-
Year
Figure 3
Interannual fluctuations in mean fork length (FLl at age 0, age 1, and age 2 for
chub mackerel iScomberjaponicus) in 1970-97. Horizontal lines show the 28 year
mean FL at age 0, 1, and 2, respectively. Vertical bars show standard deviations.
(Ill
(12)
(13)
We ran the models with all possible combinations of
explanatory variables (T, D, T, and D), and compared AIC
with that obtained with the base parameters (L,, r0, k).
Results
where tr,
XL, V
D.
= the age at length 0 (year);
= the asymptotic length; and
= the growth coefficient;
= L, at age i of year-classy;
= k at age ;' of year-class y;
= the sea surface temperature in year i+y; and
= a population density presented by the number
of stock at age i of year-class y.
These variables were z-score standardized. The model
parameters ax and /32 were estimated to represent the
effects of Tl+v and DI v on k or Lv.
The parameters were estimated by maximizing the like-
lihood function which is represented by
and
L(i,y) = L: v +£,,
f, -MO.cr),
UL,,k,t0,pvP2,o'f) =
{L(/y)-L,v}2
nnM'-p
2a;
(14)
(15)
(16)
3 Millar, R. B., and R. A. Myers. 1990. Modeling environmen-
tally induced change in growth for Atlantic Canada cod stock.
ICES CM 1990/G:24.
Fork length at age
Mean FL at age 0 varied substantially over the time series
examined. For example, it ranged from 16.9 (Sd ±3.0) cm
in 1975 to 25.9 (Sd ±1.0) cm in 1989. The mean FL for the
28 years period was 21.7 (±2.1) cm (coefficient of variation:
CV=9.8%, Table 1, Fig. 3). The FL-at-age-0 values were
smaller than the 28-year mean FL for the 1970s, varied
around the mean in the early and mid 1980s, reached a
maximum in 1989, and were at about 22-24 cm in the
1990s (Fig. 3).
Mean FL at age 1 was similarly variable; it ranged from
24.3 (±1.9) cm in 1976 to 31.6 (±1.4) cm in 1995. The 28-
year mean FL was 27.7 (±1.6) cm (CV=5.6%,Table 1). The
trend in interannual variability was similar to that in age
0, i.e. it was smaller in the 1970s and larger in the 1990s
(Fig. 3). In age-2 fish the 28-year minimum FL of 29.1 (±1.8)
cm was observed in 1986 and the maximum of 34.5 (±1.3)
cm was observed in 1990 (the 28-year mean FL=31.1 (±1.5)
cm, CV=4.7%, Table 1, Fig. 3).
In fish age 3 and older, mean FL varied year-to-year in a
manner similar to that found in the younger ages ( Table 1 ).
Annual mean FLs for 3-, 4-, and 5-year-olds were 33.7
(±1.3) cm (3.8%), 36.2 (CI ±1.4) cm (CV=4.0%), and 38.5
(CI ±1.5) cm (CV=3.8%), respectively (Table 1). The mean
FLs for ages 0-5 of each year were significantly different
among different years (one-way ANOVA, P<0.01 ).
200
Fishery Bulletin 102(1
Table 1
Total biomass, year class strength I stock number at age
1970 to 1997. Blanks show the lack of data.
0;Yats
u, et al.
), SST, and mean fork length (FL> of Scomber japonicus from
Year
Total
Biomass
(103t)
Stock number
at age 0
(106 individuals I
SST
(°C)'
Mean FL (SD) cm
0
1
2
3
4
5
1970
2833
10,199
11.5
19.2
12.6)
26.3
(1.8)
30.5
2.4)
34.2
(1.7)
37.7
(1.6)
40.5
1.4)
1971
3781
14.138
10.9
20.2
(2.3)
26.8
(1.9)
31.4
1.5)
34.3
(1.6)
37.7
(1.6)
40.4
1.3)
1972
4860
8342
13.2
19.3
il. 0)
27.2
(1.4)
31.1
1.6)
34.3
(1.5)
37.3
(1.7)
40.0
1.5)
1973
4650
7154
11.1
22.2
U.4)
27.9
(1.5)
29.4
1.6)
31.2
(1.8)
33.1
(2.0)
36.1
1.9)
1974
4048
7854
10.5
19.7
(1.4)
27.7
(2.5)
30.4
1.4)
31.9
(1.7)
33.9
(1.8)
37.6
1.7)
1975
3558
10,353
12.3
16.9
(3.0)
25.4
(1.8)
30.3
2.6)
32.7
(1.6)
33.8
(1.6)
35.5
1.7)
1976
3896
14,402
11.5
19.7
(2.0)
24.3
(1.9)
29.4
2.4)
33.7
(1.9)
35.3
(1.8)
38.1
1.8)
1977
5868
11.701
10.9
21.4
(1.3)
26.2
(1.8)
30.1
2.8)
33.5
(2.2)
35.7
(1.7)
37.4
1.4)
1978
5285
6249
10.0
21.5
(1.1)
28.5
(1.7)
29.8
1.6)
32.1
(2.3)
34.5
(2.D
36.1
1.9)
1979
3250
2931
12.3
19.5
(1.1)
27.1
(2.0)
30.2
2.0)
33.0
(1.7)
35.2
(1.6)
37.2
1.3)
1980
1898
2952
11.3
20.7
(1.1)
25.8
(2.6)
30.3
2.2)
32.4
(1.8)
33.9
(1.8)
35.6
1.6)
1981
1683
3374
9.4
22.7
(1.3)
27.2
(1.7)
30.5
1.5)
33.1
(2.1)
36.5
(1.8)
38.0
1.5)
1982
1567
2883
10.8
22.5
(1.8)
27.9
(1.6)
29.3
1.8)
33.6
(2.2)
36.6
(1.6)
38.3
1.4)
1983
1516
3175
11.5
19.6
(1.2)
26.7
(2.2)
30.8
1.6)
33.6
(1.5)
35.5
(2.0)
37.8
1.2)
1984
1759
3605
9.3
22.7
(1.3)
27.0
(2.4)
31.0
1.8)
34.8
(1.9)
36.6
(1.8)
38.2
2.0)
1985
1565
4998
11.4
20.1
(2.2)
27.3
(2.11
30.9
1.9)
33.3
(1.9)
37.4
(1.7)
39.0
1.8)
1986
1373
1833
9.7
21.5
(1.7)
26.4
(1.4)
29.1
1.8)
32.5
(2.4)
35.9
(2.1)
38.9
1.9)
1987
812
583
10.9
20.5
(2.1)
27.6
(1.7)
30.2
1.3)
32.8
(1.6)
36.4
(2.3)
39.2
0.8)
1988
555
236
11.4
24.9
(1.4)
28.1
(1.5)
30.5
1.4)
32.8
(1.7)
36.8
(1.6)
40.1
1.2)
1989
289
219
9.8
25.9
(1.0)
29.7
(2.3)
32.2
1.4)
34.6
(1.5)
35.7
(1.5)
39.2
1.5)
1990
185
356
11.7
24.4
(1.3)
30.3
(2.6)
34.5
1.3)
35.8
(1.5)
38.2
(1.1)
39.7
0.8)
1991
338
1017
12.2
24.1
(1.6)
28.9
(1.8)
33.5
1.9)
35.5
(1.2)
36.7
(1.9)
39.0
1.8)
1992
724
2839
9.7
24.0
(1.6)
29.0
(1.7)
32.1
1.4)
34.1
(1.5)
37.5
(1.6)
40.5
1.6)
1993
685
589
10.7
23.9
(0.9)
29.3
(1.3)
31.7
l.D
33.2
(0.5)
1994
343
547
11.3
23.7
(1.7)
28.8
(2.5)
32.8
1.0)
34.6
(0.8)
35.9
(0.7)
39.1
1.0)
1995
351
1183
11.3
22.0
(1.3)
31.6
(1.4)
32.9
1.8)
35.5
(1.8)
38.0
(1.3)
39.2
0.8)
1996
726
4452
9.9
22.5
(1.1)
28.7
(2.5)
34.1
1.2)
36.1
(1.1)
37.8
(0.9)
39.7
0.7)
1997
682
529
9.9
23.6
(1.4)
29.0
(1.5)
33.0
1.3)
35.4
(1.7)
37.6
(0.7)
38.6
0.5)
28-year
mean of FLs at ages
21.7
(2.1)
27.7
(1.6)
31.1
1.5)
33.7
(1.3)
36.2
(1.4)
38.5
1.5)
' SST during ApriUJ
une in the waters bounded by 38^tO°N ar
d 141-
143°E.
Mean growth increments I of each year class from age 0
(6 months old) to ages 1-5 (/0_,) showed significantly nega-
tive correlations (Table 2). Correlations between the two
variables tended to increase with age: -0.69 for /,, _,, -0.71
for I„_.,, -0.80 for /„_.,, and -0.77 for I0^.
The relative FL at age 0 for any given year class was
maintained throughout the life span. A correlation be-
tween the mean FL at age 0 and age 1 within each year
class (1970 to 1996 year class) was positive and statisti-
cally significant (P<0.05, Fig. 4). Similarly, the positive cor-
relations between the mean FL at age 0 and age 3 ( 1970
to 1994 year class, P<0.01, Fig. 4), and age 0 and age 4
(1970 to 1993 year class. P<0.05, Fig. 4) were significant
(P<0.05. Fig. 4).
Correlation between FL and population density
Population densities represented by stock in number at age
0 and total biomass were negatively correlated to FL at age.
Negative correlations between the logarithm of abundance
of age 0 (ln/V0) and FL at ages were relatively high in age 0
to 3 (-0.69 to -0.83, Table 3) and low in age 4 and 5 (-0.63
and -0.64, Table 3). Correlations were statistically signifi-
cant for ages 0, 2, and 3 (Table 3). Negative correlations
between the logarithm of total biomass and FL at ages
were relatively high at ages 0 to 2 (-0.73 to -0.75) and
moderate for age 3 to 5 (-0.50 to -0.52, Table 4). However,
the relationships were not statistically significant for all
ages (Table 4).
Watanabe and Yatsu: Interannual variation in length at age of Scomber /aponicus
201
32
E
3 29
26 --
23
15
H h
20 25
FL at age 0 (cm)
38
36
S. 34
IB
32 -■
30
B
15
H — H
H — i-
20 25
FL at age 0 (cm)
20 25
FL at age 0 (cm)
Figure 4
Scatter plots of FL at age 1 (A), age 3 (Bl and age 4 (C) on FL at age 0 for chub mackerel (Scomber japonicus). Correlations between
FL at age 1 with age 0 (r=0.83. n=28, actual sample size n'=8, df=6), age 3 with age 0 (r=0.62, ;i=26. n =11. df =9) and age 4 with
age 0 (r=0.67, u=24, n'=10) were all significant at P < 0.05.
Table 2
Correlation of FL at age 0 and growth increment after age
0. n = actual sample size, n* and degree of freedom (df)
show the effective ;? and df when the data were corrected
for autocorrelation (Pyper and Peterman, 1998). Signifi-
cance level: **, P<0.01.
Growth increment
Ages 0-1
Ages 0-2
Ages 0-3
Ages 0-4
Ages 0-5
df
0.69**
0.48
27
21
19
0.71**
0.51
26
25
23
0.80**
0.64
25
23
21
0.77**
0.59
23
24
22
0.78**
0.61
22
22
20
Table 3
Correlation between the natural logarithm of the abun-
dance of age 0 and mean FL for each age. n = actual sample
number, n* and degree of freedom (df) show the significant
n and df when autocorrelation was considered (Pyper and
Peterman, 1998). Significance levels: *, P < 0.05.
Age
r
r2
n
n df
0
-0.75*
0.57
28
8 6
1
-0.69
0.48
27
7 5
2
-0.83*
0.69
26
6 4
3
-0.71*
0.51
25
9 7
4
-0.63
0.40
23
8 6
5
-0.64
0.40
22
6 4
Correlation between FL and SST
Growth in the first six months of life was correlated with
SST. We detected significant negative correlation between
FL-at-age 0 and SST between April and June in the waters
bounded by 38-40°N and 141-143°E U--0.45, r2=0.20,
n=28, n =27, df=25, P<0.05, Fig. 5). The SST between July
and September of this area was also negatively correlated
with FL at age 0 although the correlation coefficient was
not significant at 5% level.
Growth analysis
Model 1 that incorporated SST ( T) and population density
(D) gave a minimum Akaike's information criterion (AIC)
of 457.68 (Table 5) and the model was expressed by
L- = 43.98 1 - exp( -2.585 )exp
-5X
:0. 271-0. 008T -0.2LD,
(17)
(18)
Table 4
Correlation between natural logarithm of total biomass
and mean FL for each age. n = actual sample size, n* and
dgree of freedom ( df ) show the effective n and df when the
data were corrected for autocorrelation (Pyper and Peter-
man, 1998). No correlations were significant (P>0.05).
Age
df
0.74
0.38
27
6
4
0.73
0.32
27
6
4
0.75
0.36
27
5
3
0.52
0.26
27
11
9
0.51
0.26
26
9
7
0.50
0.22
26
7
5
This model estimated the FL at ages 0-5 well (Fig. 6).
The AIC of model 1 incorporating T and D was smaller than
the AIC of model 2; therefore the environmental factors had
an affect on k rather than LT.
202
Fishery Bulletin 102(1)
45 N
40 N
35 N
30 N
140N
145 N 150
B
25 --
8> 20 +
CD
r =o.20
15 -I — l — l — l — i — I — i — i — i — i — I — i — i — i — i — I
8 10 12 14
Mean SST
Figure 5
(A) Map to show correlation between sea surface temperatures (SST) and mean fork length (FLl
at age 0 for chub mackerel (Scomber japonicus). The dotted area indicates the negative correla-
tion coefficient r above 0.4. The contour interval is 0.1 of the correlation coefficient and positive
contours are shown as dashes. (B) Relationship between mean SST for the area 38°-40°N and
141-143°E from April to June and mean FL at age 0. Correlation was significant at the 5^ level
(r=-0.45, n=28, n "=27, df=25).
To investigate the effect of T and D, we calculated the
total effect on k for year-class v according to Sinclair et al.
(2002):
lA^
I ft A,
for T, and
for D.
Discussion
Estimated population abundance of age-0 fish and total
biomass may explain density-dependent growth. FL at
age 0, 2, and 3 of the Pacific stock of chub mackerel were
negatively correlated with the number of age-0 recruits.
Correlations between biomass and FL at ages 0-5 were low
and not significant. Therefore, year-class strength is indi-
cated to have a greater negative influence on the growth
of the Pacific stock of chub mackerel than total biomass,
as reported for the Atlantic mackerel (Scomber scombrus)
(Agnalt, 1989; Overholtz, 1989; Neja, 1995) and Atlantic
herring (.CI upea harengus) (Toresen, 1990).
Density-dependent growth in fish populations seems to
be a common phenomenon for pelagic fishes found in the
temperate waters of Japan. The FL at age 0 of the 1963-69
year classes ranged from 16 to 20 cm, and were smaller than
those of the 1970s, possibly indicating density-dependent
growth ( Iizuka, 1974 ). According to Honma et al. ( 1987 ), the
stock abundance of the Pacific stock of chub mackerel from
1963 to 1969 was larger than it was in the 1970s. Wada et
al. (1995) and Hiyama et al. ( 1995) found negative relation-
ships between total biomass and body length in the Pa-
Table 5
Summary of statistics from the estimation of growth for
chub mackerel (Scomber japonicus). AIC
= Akaikf
's infor-
mation criterion.
No. of
Log
unknown
likeli-
Model Variables
parameters
hood
AIC
1 L„, k, tn, (jj . . .a5
9
-280.20
578.40
L,.k,t0,a1 ...a5, /3,
10
-270.10
560.20
Lr, k, t0, CTj . . .a5, p2
10
-222.38
464.77
L„, k, t0, a, . . .cts,/S]
ft 11
-217.84
457.68
2 La,k,t0,a1...as
9
-280.20
578.40
L,,k.t„.ax . . -cr5, jSj
10
-268.63
557.25
Lr, k, t0, at . . .ii-, />.,
10
-224.01
468.02
Lx, k, tQ, (Jj . . .Or,, fix
ft 11
-220.81
463.62
cific and Tsushima Current stock of the Japanese sardine
(Sarclinops melanostictus). Kishida (1990) demonstrated a
density-dependent relationship between the growth and
total stock density (CPUE) of Japanese Spanish mackerel
(Scomberomortis nipkonius).
Our results do not agree with the positive effect of sea wa-
ter temperature on somatic growth that has been shown for
several species, including Japanese common squid (Kidokoro,
2001). Atlantic herring ( Moores and Winters, 1981; Toresen,
1990). and Atlantic cod (Gadus morhua ) (Brander, 1995; Du-
til et al, 1999; Ratz et al. 1999; Otterson et al., 2002).
Watanabe and Yatsu: Interannual variation in length at age of Scomber /aponicus
203
15 I i mini 20 I i
70 75 80 85 90 95 70 75 80 85 90 95
35
30
Age 2
35
30 --
Age 3
25 I I I I I I I I I I I I I I I I I I II I I I I I I I I I 25 I I I I I I I I I I I I II I I I I I I I I I I I I I I I
70 75 80 85 90 95 70 75 80 85 90 95
40
35
Age 4
.. Age 5
40 --
35
30 I I I II I I II I I I I I I II II I I I I I I II I I 30 I I I I I I II I I I I I I III I I I I I I I I I I I I
70 75 80 85 90 95 70 75 80 85 90 95
Year
Figure 6
Time series of observed (open circles) and modeled (solid line) values of mean fork
length (FL) at ages 0-5 during 1970-97 for chub mackerel iScomber japonieus).
There was a positive correlation between FL at age 0 and
l°xl° block SST in the waters of 32-34°N and 144-149°E,
located south of the Kuroshio Extension flowing eastward
at the latitude of 35-37°N from April to June (Figs. 1 and
5A). But the correlation coefficient was not significant, and
this area was not considered to be inhabited by juvenile
mackerel (Watanabe, 1970). Thus, we considered that the
SST in the waters of 32-34°N and 144-149°E was not a
significant factor on the variation of FL at age 0.
The low SST in the waters bounded by 38-40°N and
141-143°E is indicative of a large inflow of Oyashio Cur-
rent waters (Hirai and Yasuda, 1988), which is a cold
water current and has high productivity (Odate, 1994),
into the Kuroshio-Oyashio transition zone, where is one
of the main feeding grounds of mackerels (Odate, 1961;
Watanabe, 1970; Watanabe and Nishida, 2002; Fig. 1).
Thus, we hypothesized that the large inflow of Oyashio
current waters into the Kuroshio-Oyashio transition zone
improved the feeding condition and accelerated the growth
of juvenile mackerel. Jobling ( 1988) suggested a parabolic
relationship between water temperature and fish growth.
The range of SST in this area, which was negatively cor-
related with FL at age 0 of mackerel, was 9-13°C (Table 1 ).
This temperature range is near the lowest nonstressful
temperatures for mackerel ( 10-12°C, Schaefer, 1986). Thus,
we do not consider that the negative relationship between
growth and SST was the result of suppressed growth by
the high ambient temperature.
In mackerel, maximum egg production appears to have
shifted to later in spring during the 1990s, as compared to
the late 1970s and 1980s, resulting in a shorter period of
growth and thus smaller fish (Fig. 8, Mori et al.4; Kikuchi
and Konishi5; Ishida and Kikuchi6; Zenitani et al.7; Kubota
et al.8). In the early 1970s, the main spawning period was
4 Mori, K., K. Kuroda, and Y. Konishi. 1988. Monthly egg
production of the Japanese sardine, anchovy, and mackerels off
the southern coast of Japan by egg censuses. Datum Collect.
Tokai Reg. Fish. Res. Lab. 12:1-321. [In Japanese. Available
from National Research Institute of Fisheries Science, 2-12-4
Fukuura, Kanazawa, Yokohama 236-8648, Japan.]
5 See next page.
6 See next page.
7 See next page.
8 See next page.
204
Fishery Bulletin 102(1)
0.015 T
-0.015
0.015
i i i i i i i i i i i ii n i i
70
75
80
85
90
95
-0.015 I I I I I I I I I I I I I I
70 75 80
Year
Figure 7
The total effect of I A) mean SST for the area of 38-40°N and 141-143"E from April to
June, and (Bl population density on k for each year class of chub mackerel i Scomber
japonicus).
also in April (Kuroda9). Delayed spawning in the 1990s
should have resulted in a reduction in the mean FL at ages
during September-December in the 1990s compared to the
1970s and 1980s; however the present study showed the op-
posite result (Table 1 ). We hypothesize that the effect of the
shift of spawning period on the FL at ages may have been
overwhelmed by the effect of population density (Fig.7).
■"' Kikuchi, H.,andY. Konishi. 1990. Monthly egg production of
the Japanese sardine, anchovy, and mackerels off the southern
coast of Japan by egg censuses: January, 1987 through December,
1988, 72 p. National Research Institute of Fisheries Science.
Tokyo. [In Japanese. Available from National Research Insti-
tute of Fisheries Science, 2-12-4 Fukuura, Kanazawa. Yokohama
236-8648, Japan.]
6 Ishida, M. and H Kikuchi. 1992. Monthly egg production of
the Japanese sardine, anchovy, and mackerels off the southern
coast of Japan by egg censuses: January, 1989 through December,
1990, 86 p. National Research Institute of Fisheries Science,
Tokyo. [In Japanese. Available from National Research Insti-
tute of Fisheries Science, 2-12-4 Fukuura, Kanazawa, Yokohama
236-8648, Japan.].
7 Zenitani, H., M. Ishida, Y Konishi, T Goto, Y. Watanabe, and R.
Kimura. 1995. Distributions of eggs and larvae of Japanese
sardine, Japanese anchovy, mackerels, round herring, jack mack-
erel and Japanese common squid in the waters around Japan.
1991 through 1993. Resources Management Research Report
Series A-2, 368 p. National Research Institute. Japan Fisheries
Agency, Tokyo. [In Japanese. Available from National Research
Institute of Fisheries Science, 2-12-4 Fukuura, Kanazawa, Yoko-
hama, 236-8648 Japan]
s Kubota, H.,Y Oozeki, M. Ishida, Y Konishi, T Goto, H. Zenitani,
and R. Kimura. 1999. Distributions of eggs and larvae of
Japanese sardine, Japanese anchovy, mackerels, round her-
ring, jack mackerel and Japanese common squid in the waters
around Japan, 1994 through 1996, 352 p. Resources Manage-
ment Research Report Series A-2., National Research Institute,
Japan Fisheries Agency, Tokyo. [In Japanese. Available from
National Research Institute of Fisheries Science, 2-12-4 Fuku-
ura, Kanazawa, Yokohama 236-8648, Japan.]
9 Kuroda, K. 2002. Personal commun. 1-1-3-406. Kasumi.
Narashino. Chiba 275-0022, Japan.
Jun 6
May 5 - -
Apr 4
Mar 3
H — l — I — I — I — I—
78 80 82 84
86 88
Year
—l — l — l — l — l — i — i
90 92 94 96
Figure 8
Interannual variation in the peak period (weighted
monthly means) of egg production for the Pacific stock
of chub mackerel (Scomber japonicus), which includes a
small portion from the eggs of spotted mackerel (Scomber
australasicus) (Mori et al.4: Kikuchi and Konishi''; Ishida
and Kikuchi1'; Zenitani et al.7; Kubota et al.8).
The estimated FL at age from our growth model, with
the use of AIC, fitted well to the observed FL at age
(Fig. 6). Mean growth increments / of each year class
from age 0 (6 months old) to ages 1-5 (/„_,) were signifi-
cant and negatively correlated with FL at age 0 (Table 2),
indicating that the growth rate of mackerel had changed
from year to year for a given year class. This negative
correlation indicated that the effects of population density
and SST was temporal, and influenced k rather than L r.
The negative correlation between FL at age 0 and growth
increments also suggested that the FL at age of mack-
erel approximated the asymptotic length. Thus, mackerel
growth was best fitted to the modified von Bertalanffy
growth model with the temporal environmental effect on
k (Table 5).
Watanabe and Yatsu: Interannual variation in length at age of Scomber /aponicus
205
The effect of population density on growth of mackerel
was higher than the effect of SST (Fig. 7, Table 6). Our
result agreed with the results for Japanese sardine ( Wada
et al., 1995 ) and Atlantic cod ( Sinclair et al., 2002 ). Particu-
larly, the effect of population density was significant in the
late 1980s, which resulted in a remarkable increase in FL
at age 0 (Figs. 3 and 7).
The relative size at age 0 was carried over to older ages
(Fig. 4), indicating that the cohorts that were small at age
0 could not compensate for this early small size. Iizuka
(1974) reported that the trend of growth established at
age 0 for chub mackerel was maintained until age 2 for
the 1963-73 year classes. Toresen (1990) demonstrated
from length data that a trend in rate of growth for a given
year class of Norwegian herring was determined at the im-
mature stage and was consistent after maturation. Total
length of Hokkaido-Sakhalin herrings iClupea pallasii) at
age 5 and older was positively correlated with the length
at age 4 (Watanabe et al., 2002). Because fish first mature
at age 4. this implied that the trend in total length of each
year class was determined by the age at maturity. From
these results we hypothesize that the variability in size at
age in the Pacific stock of chub mackerel is largely attribut-
able to growth before maturity, especially during the first
6 months after hatching.
Acknowledgments
We would like to thank K. Meguro of Chiba Prefecture
Governmental Office and K. Kobayashi of Shizuoka Pre-
fecture Governmental Office for providing insights into
chub mackerel's growth and into age determination. We
also thank T. Akamine, M. Suda, and N. Yamashita of the
National Research Institute of Fisheries Science for advice
on the statistical analysis. We also thank Y. Watanabe and
C. B. Clarke of the Ocean Research Institute, University of
Tokyo, for their constructive comments on this manuscript.
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207
Latitudinal and seasonal egg-size variation of the
anchoveta (Engraulis ringens) off the Chilean coast
Alejandra Llanos-Rivera
Leonardo R. Castro
Laboratorio de Oceanografia Pesquera y Ecologia Larval
Departamento de Oceanografia
Universidad de Concepcion
Casilla 160-C, Concepcion, Chile
E-mail address (for L. R Castro, contact author) lecastro@udeccl
occur among populations of E. ringens
along its distribution. In this study, we
1 ) report changes in egg size through-
out the anchoveta spawning season
as well as for the peak months of the
spawning season, 2) evaluate whether
egg size varies with respect to latitude,
and 3 ) evaluate whether differences in
larval length and yolksac volume occur
in hatching larvae from the two major
spawning stocks along Chile (central
and southern stocks).
The anchoveta Engraulis ringens is
widely distributed along the eastern
South Pacific (from 4° to 42°S; Serra et
al., 1979) and it has also supported one
of the largest fisheries of the world over
the last four decades. However, there
are few interpopulation comparisons
for either the adult or the younger
stages. Reproductive traits, such as
fecundity or spawning season length,
are known to vary with latitude for
some fish species (Blaxter and Hunter,
1982; Conover, 1990; Fleming and
Gross, 1990; Castro and Cowen, 1991).
and latitudinal trends for some early
life history traits, such as egg size and
larval growth rates, have been reported
for others clupeiforms and other fishes
(Blaxter and Hempel, 1963; Ciechom-
ski. 1973; Imai and Tanaka, 1987,
Conover 1990, Houde 1989). However,
there is no published information on
potential latitudinal trends during the
adult or the early life history of the
anchoveta, even though this type of
information may help in understand-
ing recruitment variability, especially
during recurring large scale events
( such as El Nino or La Nina) that affect
the entire species range.
Egg volume has been found to vary
widely among species and among popu-
lations of the same species. For fish that
broadcast planktonic or benthic eggs,
egg size often varies as the spawning
season progresses (Bagenal, 1971), and
the magnitude of this variation depends
on the species. For instance, the egg vol-
ume of the pelagic spawners Engraulis
anchoita and Solea solea decreases 23%
and 38%. respectively, throughout the
spawning season (Ciechomski, 1973;
Rijnsdorp and Vingerhoed, 1994). Ma-
ternal and environmental factors may
also affect egg volume (Bagenal, 1971;
Thresher, 1984; Rijnsdorp and Vinger-
hoed, 1994; Chambers and Waiwood.
1996; Chambers, 1997). Variations in
size of the spawning females and shifts
in energy allocation from reproduction
to growth as the spawning season pro-
gresses may influence the egg volume
(Wootton, 1990). Alternatively, seasonal
variations in photoperiod, seawater
temperature, and food supply during
the spawning season may affect the
reproductive output (Wootton, 1990).
Scarce information exists on the
variability of egg sizes for fishes in the
Humboldt Current. In this extensive
area, the heavily exploited anchoveta
Engraulis ringens is the dominant
small pelagic species. Throughout this
range, three major stocks are recog-
nized: the northern stock off northern
Peru ( the largest ); the central stock off
southern Peru and northern Chile (mid-
size), and the southern stock off central
Chile (the smallest of the three). For
the entire distribution of anchoveta,
the main spawning season is from July
through September, but may extend to
December or January (Cubillos et al.,
1999). The wide latitudinal range and
prolonged spawning period suggest the
possibility of egg-size variation, as ob-
served in other clupeifoms (Blaxter and
Hempel, 1963; Ciechomski, 1973; Imai
and Tanaka, 1987). Egg size correlates
with larval characteristics such as lar-
val length at hatching, the time to first
feeding, and time before irreversible
starvation (Shirota, 1970; Ware, 1975;
Hunter, 1981; Marteinsdottir and Able,
1992). To explore whether differences
in potential early-life-stage survival
would exist among populations and (or
seasons ), the objective of our research
was to determine whether variations
in some early-life-stage characteristics
Materials and methods
We collected anchovy eggs from four
locations along the coastal zone (<20
nmi offshore ) off northern and central
Chile during the austral winter and
spring spawning seasons 1995-97
(Fig. 1). Eggs were collected with a
Calvet net (150 urn mesh) in Iquique
and Antofagasta (northern Chile),
with a standard conical net (330 um)
in Valparaiso and with either a Tucker
trawl (250 ;<m mesh) or a standard
bongo net ( 500 um) in Talcahuano. The
shorter axis of the anchovy eggs varied
from 0.563 mm (SD=0.032) in Iquique
to 0.657 mm (SD=0.027 ) in Talcahuano.
Consequently, egg extrusion from the
nets was ruled out as a potential source
of variation in our collections. Egg size
(length and width) was measured with
an ocular micrometer on a dissecting
microscope at 25x magnification. Upon
collection, all eggs were preserved in
5% buffered formalin. Previous studies
on anchoveta eggs have reported no egg
size shrinkage or shape changes with
formalin preservation (Fisher, 1958).
Similarly, reports on this species and
other anchovies show that egg-size
variations throughout their develop-
ment do not occur iEngr-aulis ringens,
Fisher. 1958; Engraulis japonica, Imai
and Tanaka, 1987). We tested this
hypothesis using eggs that we col-
lected in northern Chile and found no
size differences among different egg
stages (ANOVA. n=535, P=0.1176).
Manuscript approved for publication
12 August 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:207-212 (2004).
208
Fishery Bulletin 102(1)
Egg volume was calculated considering the anchovy egg
as an ellipsoid ( V=4jt x a x b x c/3, where a, b and c are the
ellipse radii).
Statistical analyses included one-way ANOVA tests for
volume differences among eggs spawned in three subpe-
riods during the spawning season (initial, middle, and
final) in Valparaiso and Talcahuano (1996-97). We did
not have samples from the start of the spawning season
in 1996 for Valparaiso; thus, we used samples collected in
late June 1995 for this subperiod (Table 1). Variations in
the egg-size frequency distributions between contiguous
subperiods were also tested with nonparametric tests
(Kolmogorov-Smirnov test). Changes in egg volume with
latitude were tested by using egg sizes measured at four
localities (20°, 23°, 33°, and 36°S) during the peak spawn-
ing months (initial subperiod). The same statistical tests
were used as in the previous objective (ANOVA, Kolmogo-
rov-Smirnov test).
To evaluate the relationship between egg size and lar-
val length at hatching, live eggs from ichthyoplankton
samples from the field in August 2000 were transported to
the laboratory and reared at the normal mixed-layer tem-
perature off Antofagasta and Talcahuano (15°C and 12°C,
respectively) (Escribano et al., 1995; Castro et al., 2000).
A subsample of the incubated egg batch was preserved in
5% formalin and measured at the beginning of the experi-
ments. The rest of the eggs were placed in 1-L flasks and
incubated until hatching under 12h/12h photoperiod. This
procedure was repeated twice (4 days apart) in each zone.
From each rearing experiment, 30 just-hatched larvae
(max. 30 min from hatch) were anesthetized and measured
(notochord length) under a dissecting microscope with the
aid of an ocular micrometer. Additionally, yolksac sizes of
recently hatched larvae were measured and volume esti-
mated as one half of an ellipsoid by using the algorithms
given above.
Results
A total of 7196 anchovy eggs were measured. The egg size
tended to decrease as the spawning season progressed
(Fig. 2). From late June through January the mean
volume decreased by about 20% in Valparaiso and by
about 10"% in Talcahuano (ANOVA, P<0.05)( Table 1). The
size-frequency distribution between consecutive subperi-
ods (initial, middle, and final) also differed in both areas
(Kolmogorov-Smirnov test, P<0.05). The mean size of the
eggs in Valparaiso was smaller than in Talcahuano during
all subperiods (Table 1 ), and the largest difference between
areas was at the end of the spawning season ( 15% ).
During the spawning peak (spawning commencement ).
when the eggs were larger, the mean anchoveta egg size in-
creased with latitude (ANOVA, P<0.01; Fig. 3). At Iquique
(20"S), the mean egg volume was 21% smaller than at An-
tofagasta (23°S), 49% smaller than at Valparaiso (33°S),
and 5695 smaller than the eggs from Talcahuano (36°S),
the southernmost location (Table 2). The egg-size fre-
quency distribution differed between adjacent areas (Kol-
mogorov-Smirnov test. P<0.05). Interestingly, the smallest
Pacific Ocean
>
73
Longitude West
Figure 1
Areas where anchoveta eggs were collected to
determine egg-size variations along the Chil-
ean coast. Arrows show the locations depicted
in Table 2.
egg sizes measured in Iquique (<0.19 mm3) did not occur
in Talcahuano. Similarly, the largest sizes determined in
Talcahuano (>0.30 mm3) did not occur in Iquique. at the
lowest latitude.
Larval length at hatching determined in the rearing
experiments at normal field temperatures was greater for
the southernmost population (Talcahuano) (Table 3). The
mean larval size for the southern location (2.70 mm noto-
chord length) was 8.2% greater than the larvae hatched
from eggs collected at the northern experimental location
(Antofagasta, 2.50 mm). Furthermore, the yolksac volume
in the recently hatched larvae in Talcahuano (0.130 mm3)
Note Llanos-Rivera and Castro: Egg-size variation of Engraul/s ringens
209
80
60
40
20
0
„ 80
& 60
c
<D
= 40
(D
^ 20
0
80
60
40
20
0
Valparaiso (33°)
middle
0 15-0.19 020-0.24 0.25-0.29 0.30-0.34 0 35-0 39 0.40-0.44
80
60 -
40
20
0
80
60 -
40
20 -
Talcahuano (36 )
o
80
60
40
20
0
0.15-0.19 020-0.24 0.25-0.29 0.30-0 34 0.35-0 39 0.40-0.44
Size interval (mm3)
Figure 2
Seasonal variation in egg size of the anchoveta (£. ringens) off Valparaiso and Talcahuano. y-axis is frequency over
the total number of eggs measured at each locality. Initial, middle, and final are subperiods within the spawning
season (see Table 2).
Table 1
Mean volume of Engraulis ringens eggs at the beginning, middle, and end of the spawning season off Valparaiso
central Chile. SD = standard deviations, n = number of eggs measured.
and Talcahuano,
Valparaiso
Talcahuano
June 1995
October 1996
December 1996
August 1996
October 1996
January 1997
Volume (mm3) 0.298
SD 0.026
n 62
0.281
0.029
759
0.247
0.022
630
0.312
0.030
1833
0.308
0.034
718
0.286
0.029
1099
was much larger (33% larger) than the yolk volume of the
larvae hatched in Antofagasta (0.098 mm3).
Discussion
The results of this study identified several trends that
are related to egg-size variation. First, egg size tends to
decrease with the progression of the spawning season.
Second, egg size increases with latitude during the peak
spawning period. Third, larval size at hatching is smaller
in the northern latitude populations. Fourth, the yolk sac
of recently hatched larvae is much larger than expected
(based on the larval size at hatching) in the southern
population.
A number of hypotheses have been proposed to ex-
plain egg-size variations in fish that spawn at multiple
times as the reproductive season progresses. It has been
proposed that in clupeiforms, the decrease in egg size
may result from maternal reduction of energy reserves
over the spawning season, a switch in the stored energy
from reproduction to growth, seasonal changes in the age
structure of the spawning population, or changes during
ovogenesis that are correlated with temperature (Blaxter
and Hunter, 1982; Chambers, 1997, for a recent review). In
the anchoveta E. ringens, published data suggest that some
210
Fishery Bulletin 102(1)
80
60
40
20
0
80 -p
60 --
40
20
0
80
60
40
20
0
80
20--
20 S
n
.I ii
23 S
--
33°S
--
+
,1 1,
H 1 1
36 >S
-+-
0 10-0 14 0 15-0 19 0 20-0 24 0.25-0.29 0.30-0.34 0.35-0.39 0.40-0.44
Size interval (mm3)
Figure 3
Latitudinal variation in egg size of the anchoveta (£. ringens ) along northern
and central Chile during the peak months of the spawning season. Y-axis is
frequency over the total number of eggs measured at each locality.
of these factors co-occur. For instance, changes in growth
rates for yearly cohorts during the spawning season (low at
the beginning, fast at the end) have been documented for
the southernmost population (Cubillos et al., 2001). Alter-
natively, variations in the population age structure during
the spawning season have also been reported as the 1.5
year-old new recruits begin to spawn in early summer (late
December-January, Cubillos et al., 1999, 2001 ). Changes in
environmental factors affecting the spawning adults also
correlate with the egg-size variations. The photoperiod and
nearsurface temperatures increase as the spawning season
progresses from mid-winter to late spring.
Larger egg size at the beginning of the spawning season
in winter may be advantageous for these offspring because
the chances of survival increase with the larger sizes of the
hatching larvae. According to Cushing (1967), larger size
larvae should be favored over smaller larvae in seasons
with variable environmental conditions. In theTalcahuano
area, strong fluctuations in the hydrographic regime occur
during winter as strong north wind storms alternate with
short periods of south winds, and also because of the in-
creased river flow to the coastal zone (Castro et al., 2000).
Larval food, although variable, seems to be sufficient to
support most of the larval growth demands for larger
exogenous feeding larvae during winter (Hernandez and
Castro, 2000). For recently hatched larvae, however, the
picture might be slightly different because, in addition to
food supply variability, the strong turbulent environmental
conditions may jeopardize first feeding success. In these
highly variable areas, therefore, larger larval size at hatch-
ing and larger yolk reserves may be even more important
than in other less hydrographically variable areas and
seasons.
A remarkable increase in egg size at the peak spawn-
ing season occurred with respect to latitude. Egg from
the northernmost (20°S) latitude were at a maximum
559c larger than eggs from the southernmost (36°S) lati-
tude. Latitudinal variations in egg size have been previ-
ously reported for other anchovies (i.e. Engraulis anchoita;
Ciechomski, 1973). However, egg-size variations for fishes
Note Llanos-Rivera and Castro: Egg-size variation of Engraulis nngens
211
Table 2
Width, length, and volume of anchoveta eggs collected at different latitudes along the Chilean
coast during the peak months of the
spawning season. SD =
- standard deviations, n = number of
eggs measured.
Latitude and area
Width (mm)
Length (mm)
Volume (mm3]
mean SD
mean SD
mean SD
?!
20° Iquique
0.563 0.032
1.201 0.076
0.201 0.031
1670
23° Antofagasta
0.597 0.030
1.293 0.083
0.243 0.034
425
33° Valparaiso
0.643 0.023
1.373 0.064
0.298 0.026
62
36° Talcahuano
0.657 0.027
1.377 0.063
0.312 0.030
1833
Table 3
Morphological characteristics of
recently hatched Engraulis ringens
larvae from rearing experiments at normal field tempera-
tures in Antofagasta (15°C) and Talcahuano (12°C).
SD
= standard deviations. N = number of eggs
measured
Exp. = expe
riment.
Egg
volume
Larval length
Yolksac
size
( mm3
)
at hatching (mm)
at hatching
(mm3)
Exp. 1
Exp. 2
Exp. 1
Exp. 2
Exp. 1
Exp. 2
Antofagasta
15°C
Mean
0.264
0.260
2.49
2.50
0.099
0.096
SD
(0.023)
(0.023)
(0.170)
(0.1041
(0.012)
(0.0121
n
358
325
30
30
30
30
Talcahuano
12°C
Mean
0.302
0.292
2.71
2.69
0.126
0.134
SD
(0.023)
(0.026)
(0.111)
(0.103)
(0.016)
(0.017)
n
254
66
30
30
30
30
are not necessarily always associated with latitude (i.e.
north Atlantic herring stocks) because local environmen-
tal conditions that trigger spawning (i.e. specific tempera-
ture or others) may have a stronger effect in some species
(Chambers, 1997). Because of the extremely wide distri-
bution range of the anchoveta (4-42°S) and its residence
along an almost linear coast oriented exactly north-south,
we proposed that any potential differences in egg size due
to specific local conditions is probably over-driven by the
larger scale changes in environmental conditions associ-
ated with latitude.
The strong latitudinal gradient in egg size of the ancho-
veta may be an adaptive measure if different egg sizes are
favored at different latitudes or if there is a correlation
between egg size and adult life history traits that maximize
net reproductive output. Unfortunately, an analysis of the
anchoveta in which fecundity, age of first reproduction,
longevity, or other adult traits are compared in relation
to latitude has not yet been carried out. The timing and
length of the spawning season seem to be similar for the
northern (Iquique, 20°S) and southern (Talcahuano, 36°S)
stocks along Chile, despite the different temperatures at
which anchoveta spawn (Castro et al., 2001 ). The decrease
in egg size coincides with known temperature effects on
physiological rates (Houde, 1989) and on ecological factors
related to the need of anchoveta at early life stages to re-
main in nearshore environments (Bakun. 1996). At lower
latitudes, the sea temperature is higher and the seaward
surface Ekman transport is stronger and therefore eggs
and larvae in such conditions would likely develop rapidly.
Alternatively, anchovy egg and larvae at higher latitudes
are retained nearshore in winter (because the Ekman
transport is negative, Castro et al., 2000) but are exposed
to lower temperatures and to strong turbulence that may
not facilitate the first feeding of recently hatched larvae
and subsequent rapid larval development. Larger eggs,
larger larvae at hatching, and more energy reserves may
be the favored early life history strategy in southern popu-
lations. How the latitudinal variations in environmental
characteristics affect the rest of the life history traits of the
different populations of Engraulis ringens, one of the most
important fish species in the world in terms of catches,
remains to be assessed.
Acknowledgments
We acknowledge help from R. Escribano (U. Antofagasta),
G. Claramunt (U. Arturo Prat), and F. Balbontin (U. of
Valparaiso) who facilitated ichthyoplankton collections.
212
Fishery Bulletin 102(1)
H. Moyano (U. of Concepcion) allowed the use of his labora-
tory and optical material. This study was financed by the
project FONDECYT 1990470 to L. R. Castro. E. Tarifeno,
and R. Escribano. Alejandra Llanos-Rivera was also par-
tially supported by the Graduate School of the Universidad
de Concepcion.
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213
Molecular methods for the genetic identification
of salmonid prey from Pacific harbor seal
(Phoca vitulina richardsi) scat
Maureen Purcell
Greg Mackey
Eric LaHood
Conservation Biology Molecular Genetics Laboratory
Northwest Fisheries Science Center
National Marine Fisheries Service. NOAA
2725 Montlake Blvd. E.
Seattle, Washington 98112-2097
Harriet Huber
National Marine Mammal Laboratory
Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
7600 Sand Point Way NE
Seattle, Washington 98115
Linda Park
Conservation Biology Molecular Genetics Laboratory
Northwest Fisheries Science Center
National Marine Fisheries Service, NOAA
2725 Montlake Blvd. E.
Seattle, Washington 98112-2097
E-mail address (for L. Park, contact author): linda parkig'noaa gov
Twenty-six stocks of Pacific salmon
and trout [Oncorhynchus spp.), rep-
resenting evolutionary significant
units (ESU), are listed as threatened
or endangered under the Endangered
Species Act (ESA) and six more stocks
are currently being evaluated for
listing.1 The ecological and economic
consequences of these listings are
large; therefore considerable effort has
been made to understand and respond
to these declining populations. Until
recently. Pacific harbor seals (Phoca
vitulina richardsi) on the west coast
increased an average of 5% to 1% per
year as a result of the Marine Mammal
Protection Act of 1972 (Brown and
Kohlman2). Pacific salmon are season-
ally important prey for harbor seals
(Roffe and Mate, 1984; Olesiuk, 1993);
therefore quantifying and understand-
ing the interaction between these two
protected species is important for
biologically sound management strat-
egies. Because some Pacific salmonid
species in a given area may be threat-
ened or endangered, while others are
relatively abundant, it is important
to distinguish the species of salmonid
upon which the harbor seals are prey-
ing. This study takes the first step in
understanding these interactions by
using molecular genetic tools for spe-
cies-level identification of salmonid
skeletal remains recovered from Pacific
harbor seal scats.
Most studies of harbor seal food hab-
its rely on morphological identification
of indigestible parts (e.g. otoliths and
bones) from scat. Otoliths can be used
to identify fish species (Ochoa-Acuna
and Francis, 1995) but are not always
present in scats, which can result in an
underestimate of the number of species
and the number offish consumed (Har-
vey, 1989). Skeletal remains in scat are
much more common and generally
bones can be identified to the species
level (Cottrell et al., 1996). Morpho-
logical identification is possible to the
family level only with Pacific salmonid
bones; however, genetic markers have
the ability to discriminate between
species, and the feasibility of extracting
DNA from bones has been clearly dem-
onstrated (Hochmeister et al., 1991).
Mitochondrial DNA (mtDNA) has
been widely employed in systematic
studies (reviewed by Avise, 1994) mak-
ing it ideal for animal species identifi-
cation. In this study, we explored three
regions of the mitochondrial genome
that have been previously character-
ized in Pacific salmonids (Shedlock
et al., 1992; Domanico and Phillips,
1995: Parker and Kornfield, 1996).
DNA sequencing of these regions
provided an unambiguous way to de-
termine species identity. Because high
throughput sequencing can be prohibi-
tively expensive for laboratories with
limited facilities, restriction fragment
length polymorphism (RFLP) analysis
was also explored as an alternative for
species identification. A previous study
had established a species-specific poly-
merase chain reaction (PCR) test for
Pacific Northwest salmon and coastal
trout species (McKay et al., 1997). The
PCR test is based on the initial ampli-
fication of an approximately 1000-bp
fragment of the nuclear growth hor-
mone 2 gene. The degraded state of the
DNA isolated from bones recovered
from scat has generally limited suc-
cessful PCR to amplicons of 300 bp or
less (data not shown). Furthermore,
the amount of DNA isolated from bone
fragments can be quite small; mtDNA
is present in higher copy number per
cell than is nuclear DNA. Thus, we
considered mtDNA it to be a more
1 http://www.nwr.noaa.gov/lsalmon/salmesay
specprof.htm. [Accessed June 17, 2003.]
- Brown, R. F. and S. G. Kohlman. 1998.
Trends in abundance and current status
of the Pacific harbor seal tPhoca vitulina
richardsi) in Oregon: 1977-1998. ODFW
(Oregon Department of Fish and Wildlife i
Wildlife Diversity Program Technical
Report, 98-6-01. 16 p. [Available from
ODFW, 7118 NE Vandenberg Ave. Corval-
lis, OR 97333.]
Manuscript approved for publication
9 October 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:213-220 (2004).
214
Fishery Bulletin 102(1)
appropriate target for our assay. We chose to explore
smaller regions of the mitochondrial genome, including the
d-loop (Shedlock et al., 1992), a portion of the 16s ribosomal
gene (Parker and Kornfield, 1996), and a region spanning
the cytochrome oxidase III, t-RNA glycine, and ND3 genes
(hereafter, referred to as COIII/ND3) (Domanico and Phil-
lips, 1995 ). Significant interspecific variation but not intra-
specific variation was observed in the COIII/ND3 region
among salmonid species in previous studies, making it a
particularly good candidate region for the development of
diagnostic markers (Domanico and Phillips, 1995).
In the first phase of the study, we developed and vali-
dated the genetic tools for species identification by using
frozen or ethanol-preserved tissues collected from known
species and populations. In the second phase, we applied
these tools to the identification of bone remains from har-
bor seal scats collected at the Umpqua River (Oregon).
A number of Pacific salmonid species are present in the
Umpqua River but of particular concern were the sea-
run cutthroat (Oncorhynchus clarki) that were listed as
endangered under the ESA during 1996 (Johnson et al.,
1999). Here we report the method associated with these
two phases of the project. The salmonid bones that were
identified genetically were incorporated into a larger study
of the harbor seal diet and are reported in a companion
paper (Orr et al., 2004).
Materials and methods
Salmonid tissue samples of known species have been
collected over the past decade by geneticists from the
Conservation Biology Molecular Genetics Laboratory
(NOAA/NMFS/NWFSC) or generously donated by others
(see "Acknowledgments" section) and maintained either
frozen at -80°C or preserved in 95% ethanol. Reference
populations were chosen to represent the geographic
range of chinook salmon (O. tshawytscha), coho salmon
(O. kisutch), sockeye salmon (O. nerka). pink salmon (O.
gorbuscha), chum salmon (O. keta), steelhead (O. mykiss),
coastal cutthroat trout (O. clarki clarki), and Yellowstone
cutthroat trout ( O. clarki bouvieri ) ( collection information is
listed in Table 1 ). Tissues were extracted with either a stan-
dard phenol and chloroform extraction (Sambrook et al.,
1989) or by using the DNAeasy 96-well tissue kit (Qiagen,
Valencia, CA), following the manufacturer's instruction
for tissue preparations. PCR primers were either taken
directly from the published studies or designed from the
reported sequences (Table 2). All primers were cycled with
2.5 mM MgCl2, 0.8 mM dNTPs, 0.04 ,«M primers, 0.25 units
of Taq DNA polymerase (Promega, Madison, WI), 20-40 ng
of DNA, and cresol red loading buffer (final concentration
2' < sucrose and 0.005% cresol red) for 35-45 cycles of
94°C for 45 seconds, 55°C for 45 seconds, and 72°C for
1 minute.
A single individual of each salmonid species listed in
Table 1 was sequenced for both the 16s rRNA and COIII/
ND3 regions. For DNA sequencing, the PCR products were
purified with an Ultrafree MC column (Millipore, Beverly,
MA i and resuspended in 20 ,uL of sterile water. The puri-
fied product (1-10 uL depending on band intensity) was
manually sequenced by using the USB ThermoSeque-
nase cycle sequencing kit (Cleveland. OH), following the
manufacturer's instructions. MACDNASIS (Miraibio Inc.,
Alameda. CA) and SEQUENCHER (Gene Codes Corp., Ann
Arbor. MI) were used for sequence alignment and identifi-
cation of diagnostic restriction enzyme cut sites.
RFLP analysis of the unpurified COIII/ND3 PCR product
was performed in the presence of a cresol red loading buf-
fer. Restriction digests were incubated for 6 to 12 hours at
37°C for Dpn II, Sau 961, Fok I, Ase I, at 50° for Apo I, and
at 60°C for Bst NI with the supplied buffers (NEB, Beverly,
MA) and 1-5 units of enzyme. Restricted products were
electrophoresed in a 47c 3:1 high-resolution and medium-
resolution agarose gel (Continental Laboratory Products,
San Diego, CA). DNA bands on the agarose gels were
visualized with SYBR Gold, following the manufacturer's
instructions (Molecular Probes, Eugene, OR).
Personnel from the National Marine Mammal Laboratory
(NMML) collected and processed harbor seal scat samples
from the Umpqua River (Orr et al., 2004). NMML research-
ers identified bone remains to either family or species level
by using morphological characteristics of skeletal remains
(Orr et al., 2004). From 39 harbor seal scats, 116 bones were
identified morphologically to the genus Oncorhynchus and
subjected to DNA analysis for species identification. For a
positive DNA extraction control, we simulated digestion
by treating coastal cutthroat bones (collected from Cowlitz
Trout Hatchery, Winlock, WAi in a mixture of laboratory-
grade trypsin (a digestive enzyme), baking soda, and water
for 1 to 2 days. These trypsin-treated bones from a coastal
cutthroat trout were used as positive DNA extraction and
amplification control.
To prepare samples for DNA extraction, bones were
soaked in 107c sodium hypochlorite for 10 minutes to
destroy any contaminating DNA that may have adhered
to the outside of the bone and were rinsed twice in sterile
water. Bones ranged in weight from 0.1 to 105.6 mg and
included teeth, vertebrae, gillrakers, radials, and bone
fragments (hereafter, all bony parts and teeth will be re-
ferred to as "bone"). The bones were decalcified overnight
in 0.5M EDTA solution (Hochmeister et al., 1991); fragile
or small fragments were not decalcified. The EDTA was
removed and the decalcified samples were extracted with
the QIAamp tissue extraction kit (Qiagen. Valencia. CA)
according to the manufacturer's instructions with the
following modifications: 1) samples were proteinase K
digested overnight or until completely digested; 2) 10
mg/«L yeast t-RNA carrier was added to the extractant
before placement on the QIAQuick column; and 3) DNA
was eluted in a reduced volume (50-100 «L) of buffer AE.
Negative controls containing no tissue were simultane-
ously processed to verify that the extraction was free of
contaminating DNA. The trypsin-treated coastal cutthroat
bones were used as positive extraction and PCR controls.
Five to ten microliters of the extracted DNA were used
in each amplification reaction. Amplification success was
determined by electrophoresis through a 27c agarose gel
followed by staining with ethidium bromide or the more
sensitive SYBR Gold i Molecular Probes). Species identifi-
NOTE Purcell et al.: Genetic identification of salmonid prey from scat of Phoca vitulina nchardsi
215
Table 1
Species, locations, and sampl
; sizes (n 1 examined for RFLP analysis.
Species
Population
Location
71
Chinook
Walker Creek
Upper Frasier River. British Columbia
10
Grovers Creek Hatchery
Puget Sound, Washington
12
Lookingglass Hatchery
Snake River. Oregon
12
Carson Hatchery
Columbia River, Washington
12
Abernathy Hatchery.
Columbia River, Washington
11
Upper Sacramento Mainstem
Sacramento River. California
10
Coho
Edison Creek
Oregon Coast
13
Sandy River
Columbia River, Oregon
15
North Fork Moclips River
Washington Coast
15
Minter Creek Hatchery
Puget Sound, Washington
15
Yakoun River
Queen Charlotte Island, British Columbia
7
Sockeye
Nehalem Ponds
Oregon Coast
4
Redfish Lake
Snake River, Idaho
4
Alturas Lake
Snake River, Idaho
2
Ozette Lake
Washington Coast
14
Lake Wenatchee
North Cascades.Washington
10
Babine Lake
Central British Columbia
2
Kamchatka River
Kamchatka Peninsula, Russia
9
Chum
Hamma Hamma River
Hood Canal. Washington
11
Frosty Creek
Alaskan Peninsula
12
Utka River
Chucotka Peninsula, Russia
9
Miomote River
West Honshu. Japan
11
Pink
Nisqually River
South Puget Sound. Washington
6
Snohomish River Even Year
North Puget Sound, Washington
12
Skagit River
North Puget Sound, Washington
7
Hood Canal Hatchery
Hood Canal, Washington
9
Steelhead
Gaviota Creek
South California Coast
4
Coquille River
Oregon Coast
8
Upper Tucannon River
Snake River, Washington
12
Finney Creek
Puget Sound, Washington
12
Quinault Hatchery
Washington Coast
12
Tigil River
Kamchatka Peninsula. Russia
12
Cutthroat'
Alsea River
Oregon Coast
2
Alsea Hatchery
Oregon Coast
3
Duwamish River
Puget Sound Washington
12
Yellowstone River
Yellowstone River. Montana
5
' Cutthroat trout from the Yellowstone River are a different subspecies (O. clarki bouvieri) from the Washington and Oregon coastal cutthroat
trout
(O. clarki clarki).
cation was accomplished by sequencing of either the d-loop
or the COIII/ND3 region. RFLP analysis was performed
as described above with the following modifications: Bst
NI was excluded because it is redundant with Dpn II,
the enzyme amount was reduced to 0.4-1.0 units per
reaction, and incubation time did not exceed 2 hours. The
COIII/ND3 primers are specific to the family Salmonidae.
To test the possibility that the failure to obtain amplifica-
tion with the COIII/ND3 primers was due to morphologi-
cal misidentification of an Oncorhynchus species we used
the 16s primers that are conserved across a broad set of
taxa from Platyhelminthes through Chordata ( Parker and
Kornfield, 1996).
Results
The COIII/ND3 and 16s sequences were confirmed for all
seven salmonid naturally present in the Pacific Northwest
(Figs. 1 and 2) and deposited in Genbank (COIII/ND3:
AF294827-AF294833; 16S: AF296341-AF296347). Two
chinook salmon were sequenced representing two Dpn II
216
Fishery Bulletin 102(1)
Primer
sequences
size of amplified product in base
Table 2
Dairs, and references for mitochondria] loci used in this study.
Locus
Primer sequences (5' to 3')
Product size
Reference
d-loop
COIII/ND3
16sV
P2: tgt taa ace cct aaa cca g
P4: gec gaa tgt aaa gca tct ggt
F: tta caa teg ctg acg gcg
R: gaa aga gat agt ggc tag tac tg
F: tac ata aca cga gaa gac c
R: gtg att gcg ctg tta tec
230
368
260
Shedlocketal.. 1992
Domanico and Phillips
Parker and Kornfield,
1995
1997
Table 3
Restriction fragment
length polymorphisms of the cytochrome oxidase III a
id ND3 region digested w
ith six restriction
?nzymes.
The "A" haplotype does not cut with the
enzyme, "B" cuts
with the
enzyme,
and "C" cuts with the enzyme but at a different site
than "B."
Species
Dpn II
Sau 961
Fok I
Asel
Apo I
Bst NI
Chinook
A/B;
B
B
A
A
A
Coho
A
A
B
A
A
A
Sockeye
A
A
A
A
C
B
Chum
A
A
A
B
C
A
Pink
C
A
A
B
C
C
Steelhead
A
A
A
B
B
A
Cutthroat
A
A
A
A
A
A
1 Spring-running chinook from the Columbia and Snake Rivers were polymorphic foi
the Dpn II cut site. Spring
chinook from Carson
Hatchery
(derived from the upper Columbia River spri
ng-running ESU [evolutionary
significam
unit] I had the "A" haplotype at a frequency of 0.91 (
n=12) and
spring chinook from Lookingglass Hatchery (Snake River spring-summer-
■unning ESU) had the "A" haplotype at
a frequency of 0.83 (n = 12). All
other chinook samples
from Table 1 were invariant for the "B" h£
plotvpe.
haplotypes (A and B) and their sequences are presented
in Figure 1; the chinook salmon individuals were from the
Upper Columbia River summer and fall ESU (Methow
River, WA). A second intraspecific polymorphism in chi-
nook salmon was observed at position 341 between our
ND3 sequence and the published sequence (Domanico
and Phillips, 1995) (Fig.l). Sufficient nucleotide varia-
tion exists in the d-loop (Shedlock et al., 1992) and in the
COIII/ND3 region ( Fig. 1 ) to distinguish among the salmon
species by sequencing; both regions were used for bone
identification.
Six restriction enzymes were selected from the COIII/
ND3 sequence that appeared to distinguish among all the
species (Dpn II, Sau 961, Fok I, Ase I, Apo I, and Bst NI)
(Fig. 1). The Dpn II and Bst NI cut patterns are redundant
in that only one of these enzymes is required for species
identification when used in conjunction with the other four
enzymes (however, only Dpn II exhibits the intraspecific
chinook polymorphism, see below). Haplotype patterns for
all species are listed in Table 3. The haplotypes were scored
with a simple alphabetic system: "A" was uncut (368 base-
pair (bp) band) and "B" was cut (the size differed depending
on enzyme). A few of the enzymes had an alternative cut
site, and the resulting haplotype we labeled "C." The "B"
haplotype produced by Apo I occurs in steelhead and the
bands migrate at 300 and 68 bp, whereas the bands of the
"C" haplotype in sockeye, chum, and pink salmon migrate
at 250 and 118 bp. The enzyme Bst NI also has two cut pat-
terns: the sockeye salmon "B" haplotype bands migrate at
282 and 87 bp and the "C" haplotype bands in pink salmon
migrate at 271 and 98 bp. The Dpn II "B" haplotype in
chinook salmon creates two fragments, 290 and 80 bp; the
"C" haplotype in pink salmon creates three fragments, 292,
53, and 24 bp.
To confirm that the restriction enzyme polymorphisms
were diagnostic within each species, we surveyed all seven
Pacific salmon species representing multiple populations
spanning a large geographic range (Table II. No intra-
specific polymorphisms were detected among populations
with the exception of chinook salmon (Tables 1 and 3). A
single intraspecific polymorphism was found with the Dpn
II enzyme in chinook salmon lineages in the Columbia
and Snake River basins (Tables 1 and 3). Chinook salmon
from the Snake River spring-summer run (Lookingglass
NOTE Purcell et al.: Genetic identification of salmonid prey from scat of Phoca vitulina nchardsi
217
Chinook A
Chinook B
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
Chinook A
Chinook B
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
Chinook A
Chinook B
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
Chinook A
Chinook B
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
Chinook A
Chinook B
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
Chinook A
Chinook B
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
Chinook A
Chinook B
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
20 DpnII 40 60
* * * *
TTACAATCGCTGACGGCGTGTACGGCTCTACTTTCTTTGTCGCCACCGGATTCCATGGCC
. . . . A.
.T. .A.
.T. .A.
DpnII 80
100
Apol/ Sau96I
TACACGTGATTATTGGCTCAACCTTTCTAGCCGTTTGCCTTCTGCGACAGGTCCAATACC
A
. . . . A.
. . . . A.
.T. .A.
:. .G.
. . .G.
.T.G.
.A. .T.
. AA . T .
. AA.T.
. AA.T.
Fokl 140 160 180
**********
ACTTTACATCCGAACATCATTTTGGCTTTGAAGCTGCTGCTTGATATTGACACTTTGTAG
.T. . . .
.T. . . .
.T. .G.
200 220 start tRNA glycine
-->
ACGTTGTGTGACTCTTCCTATACGTCTCTATTTACTGATGAGGCTCATAATCTTTCTAGT
.A. .G.
. A. . . .
Asel
******
260
BSTNI
280
Start ND3
— >
ATTAACACGTATAAGTGACTTCCAATCACCCGGTCTTGGTTAAAATCCAAGGAAAGATAA
. .G
. TGA
. TTA
.TTA. . .CG.
.T
Apol DpnII 340 360
****** ****
TGAACTTAATTACAACAATCATCACTATTACCATCACATTRTCCGCAGTACTAGCCACTA
.CG.
.C.G.
.CG.
. . .A.
. . .G.
TTTCTTTC
Figure 1
Aligned sequences of the 3' region of the cytochrome oxidase III gene (COM I, the tRNA glycine gene,
and the 5' region of the ND3 gene for seven species of the genus Oncorhynchus. The cutthroat trout
sequence is represented by the coastal cutthroat subspecies (O. clarki clarki). Chinook "A" refers to
the "A" Dpn II haplotype; chinook "B" refers to the "B" Dpn II haplotype. Sequence identity relative
to the chinook salmon "A" sequence is denoted by dots; nucleotide substitutions are indicated. The
arrow at basepair (bp) 230 is the start of the tRNA glycine gene and the arrow at bp 300 is the start
of the ND3 gene. Stars above the sequence correspond to restriction enzyme cut sites used in this
study. At position 341 in chinook. the R represents an A or G.
218
Fishery Bulletin 102(1)
Chinook
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
Chinook
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
Chinook
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
Chinook
Coho
Sockeye
Chum
Pink
Steelhead
Cutthroat
20 40 60
GGAGCTTTAGACACCAGGCAGATCACGTCAAACAACCTTGAATTAACAAGTAAAAACGCAGT
G
80 100 120
GACCCCTAGCCCATATGTCTTTGGTTGGGGCGACCGCGGGGGAAAATTAAGCCCCCATGTGG
140 160 180
ATGGGGGCATGCCCCCACAGCCAAGAGCCACAGCTCTAAGCACCAGAATATCTGACCAAAAA
T T...A
200 220
TGATCCGGCAAACGCCGATCAACGGACCGAGTTACCCTAG. . .
Figure 2
Aligned sequences of a variable portion of the 16s gene for seven species of the genus Oncorhynchus.
Sequence identity in relation to the chinook salmon "A" sequence is denoted by dots; nucleotide
substitutions are indicated.
Hatchery) and hatchery stocks descended from the Upper
Columbia River spring run (Carson Hatchery) had the "A"
(uncut) haplotype at a frequency of 83% and 91%, respec-
tively, whereas those from the Lower Columbia River ESU
were invariant for the "B" (cut) haplotype. The "B" hap-
lotype was also invariant in the other lineages examined
(Sacramento River, CA; Puget Sound, WA; and the Fraser
River, BC). Despite this Dpn II polymorphism, the haplo-
type patterns were still chinook-specific.
Extractions from the trypsin-treated cutthroat trout
bones, used as positive controls, were amplified consis-
tently, but of the 116 salmonid bones from harbor seal
scats, only 78 (67%) were amplified. Failed samples were
repeated several times with all possible primer sets. Be-
cause each scat contained multiple bones, we were able
to amplify bones representing 35 of the 39 scats (90%).
The smallest bone we successfully amplified was a O.'2-mg
tooth and the largest was a 21.8-mg vertebra. There did
not appear to be a relationship between bone size and DNA
extraction success; no significant difference in mean bone
size was detected between 32 bones that either amplified
or failed (P=0.280; unpaired t-test; SYSTAT 8.0 [Chicago,
IL| ). The bone samples that failed to amplify repeatedly
were also tested by using the evolutionarily conserved
16s primers. Some samples were still refractory to PCR,
indicating that the overall DNA quality or quantity was
insufficient for this assay; however, those samples that did
amplify were identified by sequencing as salmon. In an un-
related study using river otter bones (data not presented),
one bone sample morphologically identified as salmonid
yielded a sequence with 100% identity to the published 16s
sequence available for Northern squawfish {Ptychocheilus
oregonensis) (Simons and Mayden, 1998).
After verifying the specificity of the RFLP analysis for
differentiating the Pacific salmon species, the assay was
applied to the bone samples. Restriction enzyme digestion
required some modification when applied to bone. On occa-
sion, the restriction enzyme protocol developed for the fresh
tissue resulted in degradation of the amplified bone PCR
product. Enzyme amount and digestion times were scaled
back for the analysis of the bone samples. The Fok I enzyme
proved the most difficult for the bone samples, which was
likely due to nonspecific restriction that occurs when the
enzyme is present at a high concentration in relation to its
target or if the reaction is allowed to digest for more than
two hours. In some cases, only very weak amplification was
achieved with the bone samples and it was difficult to get
digestion without degradation. Although sequencing was
the main technique used for bone identification. 23 bones
in this study were identified by using the RFLP technique.
Fourteen of these 23 bones were additionally confirmed by
sequencing and the two techniques gave matching results.
NOTE Purcell et al.: Genetic identification of salmonid prey from scat of Phoca vitulina nchardsi
219
Discussion
This study focused on the development of tools for the
genetic identification of Pacific salmon skeletal remains
recovered from harbor seal scats. These tools help to deter-
mine the diet of marine mammals and can also be used to
address direct management questions regarding interspe-
cific interactions in rivers such as the Umpqua River where
salmonid species of concern (cutthroat trout (occur with pro-
tected marine mammal species. The harbor seal diet in the
Umpqua River consisted of nonsalmonid fish and chinook.
coho, and steelhead; no cutthroat trout were observed in the
scat samples (Orr et al., 2004). The majority of salmonid
species identifications were possible only by using genetic
methods because very few otoliths were recovered in the
Umpqua River scats. A number of other sites exist were this
technology may also be applicable. In Hood Canal ( WA) the
summer chum salmon run is listed as threatened under the
ESA. A report of seal diets in Hood Canal determined that
2T7c of the fish consumed by harbor seals were salmonids
(Jeffries et al.3). The study used both bones and otoliths,
but only 25% of the samples contained otoliths that allowed
species-level identification. In the Alsea River (OR), coho
salmon are listed as threatened. A report by Riemer et al.4
indicated that 69r of fish consumed by pinnipeds in the
Alsea River are salmonids; none of the salmonid remains
were morphologically identifiable to species.
Extraction of DNA from bones can be done with a com-
mercially available kit with minor modifications. In our
study, only 67% of the bone DNA extracts could be ampli-
fied by PCR. PCR failure could be due to DNA degradation
during the digestive process or to environmental exposure
after defecation. However, multiple bones are often present
in scats and we were able to amplify DNA from at least one
bone representative from 35 out of the 39 scats examined.
Sequencing or RFLP analyses of the COIII/ND3 locus are
both viable methods of identifying the seven common On-
corhynchus species. This study used manual sequencing
with radioactivity and we did have better results using
this method compared to the RFLP method. A recently
published study also identified restriction enzymes in the
cytochrome B gene that distinguish among the salmonid
species (Russell et al., 2000). The study reported diagnostic
RFLP differences among these species but did not confirm
the lack of intraspecific variation in a wide geographic sur-
vey of each species. The goal of the cytochrome B RFLP as-
say designed by Russell et al. (2000) was to identify salmon
species found in processed food products but the primers
3 Jeffries, S. J., J. M. London, and M. M. Lance. 2000. Obser-
vations of harbor seal predation on Hood Canal summer chum
salmon run 1998-1999. Annual progress report to Pacific
States Marine Fisheries Commission, 39 p. [Available from
WDFW, Marine Mammals Investigations, 7801 Phillips Rd. SW,
Tacoma, WA 98498.]
4 Riemer, S. D., R. F. Brown, B. E. Wright and M. I. Dhruv.
1999. Monitoring pinniped predation on salmonids at Alsea
River and Rogue River, Oregon: 1997-1999. Oregon Depart-
ment of Fish and Wildlife, Marine Mammal Research Program,
Corvallis, OR, 36 p. [Available from ODFW, 7118 NE Vanden-
berg Ave., Corvallis, OR 97333.]
may also prove useful in species identification of bone re-
mains. The 16s primer set is also valuable for bones that
are morphologically unidentifiable. However for salmonid
species identification, the 16s region contains fewer diag-
nostic nucleotide substitutions in relation to the d-loop and
the COIII/ND3 region. Overall, the techniques established
here would be useful for further study of marine mammal
diets and may have the potential for forensic application.
Acknowledgments
The authors acknowledge Robert Delong for suggesting
this study. Jon Baker at the Northwest Fisheries Science
Center and Paul Spruell at the University of Montana
kindly provided cutthroat DNA. James Shaklee at the
Washington Department of Fish and Wildlife kindly
provided pink salmon samples. Sam Wasser and Virginia
Butler provided advice on the recovery of DNA from scat
and bone samples. Gail Bastrup assisted in technical
aspects of this study.
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221
Diel vertical migration of the
bigeye thresher shark (Alopias superci/iosus),
a species possessing orbital retia mirabilia
Kevin C. Weng
Barbara A. Block
Tuna Research and Conservation Center
Hopkins Marine Station of Stanford University
120 Oceanview Boulevard
Pacific Grove, California 93950
E-mail address (for K. C. Weng): kevin cm wengia'stanford edu
The bigeye thresher shark {Alopias
superciliosus, Lowe 1841) is one of
three sharks in the family Alopiidae,
which occupy pelagic, neritic, and
shallow coastal waters throughout the
tropics and subtropics (Gruber and
Compagno, 1981; Castro, 1983). All
thresher sharks possess an elongated
upper caudal lobe, and the bigeye
thresher shark is distinguished from
the other alopiid sharks by its large
upward-looking eyes and grooves
on the top of the head (Bigelow and
Schroeder, 1948). Our present under-
standing of the bigeye thresher shark
is primarily based upon data derived
from specimens captured in fisheries,
including knowledge of its morpho-
logical features (Fitch and Craig, 1964;
Stillwell and Casey, 1976; Thorpe,
1997), geographic range as far as it
overlaps with fisheries (Springer, 1943;
Fitch and Craig, 1964; Stillwell and
Casey, 1976; Gruber and Compagno,
1981; Thorpe, 1997), age, growth and
maturity (Chen et al., 1997; Liu et al.,
1998), and aspects of its reproductive
biology (Gilmore, 1983; Moreno and
Moron, 1992; Chen et al.. 1997).
Limited information on the move-
ment patterns of bigeye thresher
sharks has been obtained from mark-
recapture studies by using conven-
tional tags. The longest straight-line
movement of a conventionally tagged
bigeye thresher shark to date is 2767
km from waters off New York to the
eastern Gulf of Mexico (Kohler and
Turner, 2001). The bigeye thresher
shark has been captured on longlines
set near the surface at night (0 m to 65
m, Fitch and Craig, 1964; Stillwell and
Casey, 1976; Thorpe, 1997; Buencuerpo
et al., 1998) and at 400 m to 600 m
during the day (Nakamura1). There
is no published information available
regarding its habitat and behavior, al-
though Francis Carey tracked a bigeye
thresher with an acoustic tag for six
hours (Carey2).
Endothermy is a rare trait in fishes
and has been demonstrated only in
tunas (Thunnini), billfishes (Xiphiidae,
Istiophoridae), and lamnid sharks
(Lamnidael (Carey and Teal, 1969;
Carey, 1971, 1982a; Block, 1991). In all
endothermic fishes, the blood supply
to aerobic tissues such as slow-twitch
swimming muscle, visceral organs,
extraocular muscles, retina, and
brain occurs by counter-current heat
exchangers known as retia mirabilia.
The vascular supply reduces heat loss
to the environment and enables heat
conservation in metabolically active
tissues (Carey, 1971). Lamnid sharks
have retia mirabilia in the circulatory
anatomy supplying the slow-oxidative
swimming muscles, viscera, brain, and
eyes (Burne, 1924; Block and Carey,
1985; Tubbesing and Block, 2000). In
many lamnid species, tissue tempera-
tures significantly above ambient have
been recorded from freshly captured
specimens and through telemetry stud-
ies of swimming animals (Carey, 1971;
Carey et al., 1981, 1982, 1985; McCos-
ker, 1987; Goldman, 1997; Tubbesing
and Block, 2000).
The anatomy of alopiid sharks sug-
gests that endothermy may occur in
this family. The bigeye thresher and the
common thresher (Alopias vulpinus)
have centrally located slow-oxidative
muscle and primitive retia mirabilia
supplying blood to them (Carey, 1982b:
Bone and Chubb, 1983). Burne (1924)
noted a coiling of the pseudobranchial
artery supplying the orbit and cranial
regions in the common thresher. No
internal tissue temperature measure-
ments have been taken for free-swim-
ming thresher sharks to ascertain
whether heat is conserved in oxidative
tissues. A freshly caught bigeye thresh-
er shark was found to have a body-core
thermal excess of 4°C (Carey, 1971);
thus the species may have the ability
to conserve metabolic heat.
In this study we present electronic
tagging data on the movements, div-
ing behavior, and habitat preferences
of the bigeye thresher shark based on
two individuals studied with pop-up
satellite archival tags. In addition,
we provide a brief description of the
orbital rete mirabile of the species.
The presence of this highly developed
rete mirabile within the orbital sinus
suggests a physiological mechanism
to buffer the eyes and brain from the
large temperature changes associated
with diel vertical migration, potentially
conferring enhanced physiological per-
formance.
Materials and methods
The movements of two bigeye thresher
sharks were monitored with pop-up
satellite archival tags (PAT tag version
2.00, Wildlife Computers, Redmond,
WA; Gunn and Block, 2001; Marcinek
et al., 2001). The first shark was cap-
tured on a longline set in the Gulf of
Mexico at 26.5°N, 91.3°W on 12 April
1 Nakamura. I. 2002. Personal commun.
Institut National des Sciences et Technolo-
gies de la Mer. 28 rue 2 Mars 1934, 2025
Salammbo. Tunisia.
2 Carey. F. G. (deceased). 1990. Personal
commun. Woods Hole Oceanographic
Institution, Woods Hole, MA 02543.
Manuscript approved for publication
15 August 2003 by Scientific Editor.
Manuscript received 20 October 2003
at NMFS Scientific Publications Office.
Fish. Bull. 102:221-229 (2004).
222
Fishery Bulletin 102(1)
2000 in waters with a surface temperature of 21.9°C. The
longline set contained 184 hooks set at depths between
70 m and 90 m and was made at 06:00 h and retrieved at
09:00 h. Circle hooks (L2045 20/0 circle hook, Eagle Claw,
Denver, CO) were used to avoid hooking of the gut, and
the shark in this study was hooked in the corner of the
jaw. Hooks were baited with squid, and chemical light
sticks were attached to every other line. The mass of the
shark was visually estimated at 170 kg by an experienced
commercial longline fisherman, which corresponds to a
fork length of 229 cm, and a total length of 377 cm, based
on the weight-length relationship of Kohler et al. (1995).
According to this size estimation and the published size-at-
maturity data (Chen et al., 1997; Liu et al., 1998), the shark
was mature. The sex of the shark was not determined. The
second shark was captured by hook-and-line gear near
Hawaii at 19.5°N, 156.0°W on 13 May 2003 in waters with a
surface temperature of 25.5°C. A baited circle hook set at a
depth of 40 m was taken by the shark at 02:00 h. The mass
of the shark was estimated at 200 kg by an experienced
sportfishing captain, which corresponds to a fork length of
242 cm, and a total length of 400 cm (after Kohler et al.,
1995). Given this size, the shark was mature (Chen et al.,
1997; Liu et al., 1998), but its sex was not determined.
Each pop-up satellite archival tag was attached to a tita-
nium dart (59 mm x 13 mm) with a 17 cm segment of 136-
kg monofilament line ( 300-lb test extra-hard Hi-Catch, Mo-
moi Fishing Net Mfg. Co. Ltd., Ako City, Hyogo prefecture,
Japan). The dart was inserted into the dorsal musculature
of the shark at the base of the first dorsal fin, such that the
tag trailed behind the fin. Following attachment of each
tag, the fishing line was cut near the hook and both sharks
swam away vigorously. Tagging locations were recorded by
using the vessel's global positioning system. After the Gulf
of Mexico shark was tagged, a depth-temperature recorder
(ABT-1, Alec Electronics, Kobe, Japan) was used to deter-
mine the temperature-depth profile of the upper 200 m of
the ocean at the release site, at a resolution of 1 m.
The pop-up satellite archival tag deployed in the Gulf
of Mexico was programmed to collect pressure and tem-
perature data at two-minute intervals, which the on-board
software (PAT software version 1.06, Wildlife Computers,
Redmond, WA) summarized into six-hour bins. This version
of PAT software did not permit light-based geolocation. The
summary data for each time interval comprised percentage
distributions of time-at-depth and time-at-temperature,
and profiles of temperature-at-depth. Temperature-depth
profiles for this generation of software were recorded at
intervals by measuring a single temperature at depths of
0, 25, 50, 75, 100, 125, 150, 200, 250, 300, 350, and 400 me-
ters for the deepest dive. A mean temperature-depth profile
was obtained by calculating the mean temperature at each
specified depth for all profiles taken during the track. The
endpoint position of the shark's track was obtained from
the tag's radio transmissions to the Argos satellites. The
six-hour bins were later combined into 12-hour bins repre-
senting day (06:00 to 17:59 h local time) and night ( 18:00 to
05:59 h local time). At the time and place of tag deployment,
sunrise occurred at 05:45 h and sunset at 18:28 h; whereas
at the popup time and position, sunrise occurred at 05:02 h
and sunset at 18:55 h (U.S. Naval Observatory), such that
the day and night bin cutoffs were always within one hour
of true sunrise and sunset.
The pop-up satellite archival tag deployed off Hawaii col-
lected data at 30-second intervals and summarized them
into four-hour bins (PAT software version 2.08e, Wildlife
Computers, Redmond, WA). The data were later combined
into day and night bins as for the first tag, and the actual
sunrise and sunset times were within one hour of 06:00 h
and 18:00 h, respectively (U.S. Naval Observatory). The tag
measured the minimum and maximum temperature at the
surface, maximum depth, and six intermediate depths, for
the deepest dive in each time interval. Temperature-depth
profiles for each time interval were later constructed by us-
ing the maximum temperature at each depth for all profiles
taken during the track, and a curve was fitted by using a
LOWESS (locally weighted regression smoothing) function
(Cleveland, 1992). Version 2.08e PAT software collected
light data for geolocation; however the diel dive pattern of
the shark prevented the calculation of accurate positions.
The vascular circulation to the brain and eyes was exam-
ined in two bigeye thresher sharks: one common thresher
shark and one pelagic thresher shark iAlopias pelagicus).
A female bigeye thresher (1.5 m fork length) was captured
off Cape Hatteras, North Carolina, and a male (1.4 m fork
length) was captured in the Gulf of Mexico. The circula-
tory systems of the bigeye threshers were injected with
latex to aid in identifying the blood vessels. A male com-
mon thresher (1.3 m fork length) was captured off Cape
Hatteras, North Carolina, and was examined without
being frozen or preserved. An immature female pelagic
thresher shark (1.37 m fork length) was captured in the
Indian Ocean. The orbital retia mirabilia were prepared
from casts of the vascular circulation that were removed
from the orbit.
Results
One bigeye thresher shark was tracked in the Gulf of
Mexico for 60 days, and another in the Hawaiian Archi-
pelago for 27 days, by using pop-up satellite archival tags.
Both tags released from the sharks as programmed and
transmitted summary information to Argos satellites. The
tag deployed in the Gulf of Mexico popped up on 10 June
2000 at 27.95°N, 89.54°W (Fig. 1A). The shark moved a
straight-line distance of 320 km during the track, start-
ing from the central Gulf in depths exceeding 3000 m and
moving to waters 150 km south of the Mississippi Delta
where depths were approximately 1000 m. The second
shark was tagged off the Kona coast of Hawaii and the tag
released on 9 June 2003 at 24.2°N, 165.6°W. northeast of
French Frigate Shoals, a straight-line distance of 1125 km
from the deployment position (Fig. IB).
The depth and temperature distributions of the bigeye
thresher sharks showed a strong diel movement pattern
(Fig. 2). The Gulf of Mexico shark spent the majority of
the daytime (84f* (±2.39H. mean [±1 SE]) below the ther-
mocline between 300 m and 500 m and the majority of
nighttime (809? [±4.7%], mean (±1 SE] ) in the mixed layer
NOTE Weng and Block: Diel vertical migration in Alopias superaliosus
223
30° N
82°W
24°N
166
164
162
160
158
156°W
Figure 1
Deployment (A) and end-point (•) positions for the two pop-up satellite archival tags
attached to bigeye thresher sharks. Both tags surfaced on the programmed dates and
transmitted data to Argos satellites. Pressure sensors in the tags confirmed that the tags
remained attached to the sharks for the duration of the tracks. (A) In the Gulf of Mexico a
shark was tagged and released on 12 April 2000 and the tag surfaced on 10 June 2000. The
shark moved a straight-line distance of .320 km during the 60-day track. (B) In the Hawaiian
Archipelago a shark was tagged on 13 May 2003 off Kona, Hawaii, and the tag surfaced on
9 June 2003 northeast of French Frigate Shoals. The shark moved a straight-line distance
of 1125 km during the 27-day track.
and upper thermocline between 10 m and 100 m (Fig. 2A).
The shark spent most of the daytime in deeper waters of
6°C to 12°C (70% [±4.4%], mean [±1 SE]), and most of the
nighttime in shallower waters from 20°C to 26°C (70%
[±2.7%], mean [±1 SE]) (Fig. 2B). A temperature-depth
profile taken by the tag during the first day of the shark's
track closely matched a profile taken from the vessel with a
bathythermograph (Fig. 3A). The mean temperature-depth
profile for the 60-day track (Fig. 3B), when compared with
the shark's depth preferences (Fig. 2A), indicated that
224
Fishery Bulletin 102(1)
Percent time
00 75 50 25 0 25 50 75 100
0-5
5-10
10-50
50-100
~ 100-150
g 150-200
200-250
250-300
300-500
500-700
700-1000
,r
Percent time
50 25 0 25 50 75
45
25
Percent time
5 25
28-30
26-28
24-26
22-24
20-22
18-20
16-18
14-16
10-14
10-12
6-10
<6
_i i . i i_
45
j i
Percent time
50 25 0 25 50 75
Figure 2
Depth and temperature distributions of two bigeye thresher sharks showing diel vertical migration.
The tags recorded depth and temperature at two-minute (A, B> or 30-second (C, Di intervals; data
are summarized into a series of bins for the full duration of each track. (Al Depth distribution for the
Gulf of Mexico shark is shown as the percentage of day (□> and night ■ spent within depth bins
ranging from the surface to 1000 m. Error bars are 1 SE. (B) Temperature distribution for the Gulf
of Mexico shark is shown as the percentage of day (□) and night ■ spent within temperature bins
ranging from 6°C to 30°C. The shark occupied cool waters during the day and warm waters during
the night, a consequence of its deep daytime and shallow nighttime habitats. Error bars are 1 SE.
(Cl Depth distribution for the Hawaii shark showing diel vertical migration. The shark spent most
of the daytime at the base of the thermocline and must of the nighttime in the mixed layer and upper
thermocline. iD) Temperature distribution for the Hawaii shark showing cool daytime and warm
nighttime water temperatures.
NOTE Weng and Block: Diel vertical migration in Alopias superaliosus
225
10 15 20 25
Temperature (C)
10 15 20 25
5 10 15 20 25 30
50
100-1
-jT 150
n
Q_
q 200 -I
250
300 -I c
350
Figure 3
Temperature-depth profiles characterizing the thermal habitat of two bigeye thresher sharks. (Al Profiles of the
Gulf of Mexico taken with a bathythermograph ( ) sampling at 1-m intervals deployed from the fishing vessel
after the tagging event, and by the pop-up satellite archival tag (O) during the first day it was attached to the
bigeye thresher shark. The two profiles are similar, indicating that the pop-up satellite archival tag is capable
of characterizing thermal habitat. (B) Average temperature-depth profile for the 60-day track of the bigeye
thresher shark in the Gulf of Mexico, showing a mixed layer shallower than 50 m and a thermocline extending
beyond 400 m where waters were 10°C. The curve was fitted by using a LOWESS function and error bars are
1 SD, because 1 SE bars are invisible at this scale. (C) Average temperature-depth profile for the 27-day track of
the bigeye thresher shark in the Hawaiian Archipelago, showing a shallow mixed layer a thermocline extending
to approximately 600 m where waters were 6°C. Curve was fitted by using a LOWESS function and error bars are
1 SD, because 1 SE bars are invisible at this scale.
the shark spent most of the daytime below the maximum
gradient of the thermocline where temperatures were ap-
proximately 10°C. On 25 April and 25 May 2000 the shark
spent two hours of the day in waters between 4°C and 6°C.
The Hawaii shark showed a similar diel vertical migration,
with a lesser contrast between day and night (Fig. 2, C and
D). The shark's modal nighttime depth was between 10 m
and 50 m, whereas its modal daytime depth was between
400 m and 500 m (Fig. 2C). The temperature-depth profile
for the Hawaii shark ( Fig. 3C ) indicated that it spent night-
time above the thermocline and daytime below it.
The bigeye thresher shark possesses a large arterial
plexus between the posterior part of the eye and the wall
of the orbital sinus, which appears to be a rete mirabile
(Fig. 4). The orbital rete is bathed in venous blood from the
orbital sinus and its anterior surface is contoured to the
posterior surface of the eye. The sources of venous input
to the orbital sinus remain unknown but are most likely
within the surrounding extraocular muscles, which are
large and comprise numerous aerobic muscle fiber types,
and the retina. The rete shown in Figure 4 measures 72
mm by 49 mm by 19 mm. A reduced structure of similar
form is also found in the pelagic thresher shark, but is not
present in the common thresher. The orbital rete of the
bigeye and pelagic threshers is larger in absolute size and
occupies a greater cross sectional proportion of the orbital
sinus than the lamnid orbital rete noted by Burne (1924).
The arterial vessels form a finer and more orderly mesh-
work than those in the lamnid sharks (Block and Carey,
1985; Tubbesing and Block, 2000) and appear similar in
physical structure to the mammalian carotid rete used for
brain cooling (Baker, 1982).
Discussion
Observations of the biological features of the bigeye
thresher shark are rare and our knowledge of the species
is based primarily on incidental catches in fisheries. Using
pop-up satellite archival tags we were able to record behav-
ior for a total of 87 days, and for individual periods up to 60
days without recapturing or following the study animals.
We observed a pronounced diel alternation between warm
shallow waters and cool deep waters and a rete mirabile
that may confer physiological benefits during deep dives by
stabilizing brain and eye temperatures.
The depth data obtained for the bigeye thresher shark
shows a striking pattern of diel vertical migration. The big-
eye thresher shark's vertical movement pattern is distinct
from those of most other sharks for which observations
226
Fishery Bulletin 102(1)
Figure 4
Orbital rete of a bigeye thresher shark, showing the highly developed arterial network. The
rete was injected with latex so that the arterial structure (72 mm by 49 mm by 19 mm) could be
photographed. The structure of the rete and its position in the orbital sinus suggest that it may
be a heat exchanging vascular plexus. Retention of metabolic heat in the eyes and brain would
buffer these sensitive organs from the large ambient temperature swings that occur as a result
of the bigeye thresher shark's diel vertical migrations. A smaller but similar structure is found
in A. pelagicus but not in A. vulpinus.
exist. In satellite or acoustic tracks, diel vertical migra-
tion was not observed for white sharks (Carcharodon car-
charias; Carey et al., 1982; Goldman and Anderson, 1999;
Boustany et al., 2002), salmon sharks (Lamna ditropis;
Block et al.3), shortfin mako (Isurits oxyrhynchus; Carey,
1982b; Holts and Bedford, 1993), blue (Prionace glauca,
Carey, 1982b; Carey and Scharold, 1990), sixgill (Hexan-
chus griseus; Carey and Clark, 1995), tiger (Galeocerdo
cuvier; Tricas et al., 1981; Holland et al., 1999), Pacific
angel (Squatina californica; Standora and Nelson, 1977),
whale [Rhincodon typus; Gunn et al., 1999), or scalloped
hammerhead sharks (Sphyrna lewini; Klimley, 1993).
Diel vertical migration has been observed in the sword-
fish (Xiphias gladius; Carey and Robison, 1981; Carey4),
the megamouth shark (Megachasma pelagios; Nelson et
al., 1997), and the school shark iGaleorhinus ga/eus; West
Block, B.A., K.G.Goldman, and J. A. Musick. 1999. Unpubl.
data. Hopkins Marine Station of Stanford University. 120
Oceanview Boulevard, Pacific Grove, CA 93950.
Carey, R G. 1990. Further acoustic telemetry observations of
swordfish. In Planning the future of billfishes; proceedings of
the second international billfish symposium, 1-5 August 1988,
Kailua-Kona, Hawaii (R. H. Stroud, ed.), p. 103-122. National
Coalition for Marine Conservation, 3 North King St., Leesburg,
VA 20176.
and Stevens, 2001). Carey and Robison ( 1981) and Carey4
studied swordfish in both the Pacific and Atlantic Oceans,
acoustically tracking fish that moved from the surface at
night to over 600 m during day. A megamouth shark showed
a strong diel vertical migration when tracked acoustically
off southern California (Nelson et al., 1997) with shallow
nighttime and deep daytime distribution in a vertical range
of 20 m to 160 m. West and Stevens (2001) studied school
sharks in southern Australia using archival tags and noted
that they ascended in the water column at night.
The ambient temperature at the modal day- and night-
time depths of the two bigeye thresher sharks differed by
15° to 16°C, requiring them to be eurythermal. The sharks
spent most of the nighttime in shallow waters warmer
than 20°C and commonly spent 8 or more hours during
the daytime in deep waters cooler than 10°C. The coolest
waters occupied had temperatures between 4°C and 6°C.
The bigeye thresher sharks tracked in our study spent a
higher proportion of their time in waters below 10°C than
did white sharks (Carey et al., 1982; Boustany et al., 2002)
and mako sharks (Carey and Scharold, 1990; Klimley et
al.,2002).
The presence of a rete mirabile in the cranial region
may indicate a mechanism for heat conservation. Heat
conservation in the brain and eyes would enable the big-
NOTE Weng and Block: Diel vertical migration in Alopias superaliosus
227
eye thresher shark to prolong its foraging time beneath
the thermocline, as we observed for both of the sharks
tagged in our study. The retina and brain are extremely
temperature sensitive in most vertebrates and the large
changes in depth and temperature recorded would impose
significant effects on the biochemical processes occurring in
these tissues (Block and Carey, 1985; Block, 1994). Delayed
responses to retinal stimulation can be caused by cooling,
whereas increased noise and random firing of neurons can
be caused by warming — both responses having adverse
affects on sensory function (Konishi and Hickman, 1964;
Friedlander et al., 1976; Prosser and Nelson, 1981).
Anatomical and physiological adaptations to warm the
brain and eyes have evolved independently in divergent
pelagic fish lineages, including the lamnid sharks (Block
and Carey, 1985), billfishes of the Xiphiidae and Istiophori-
dae (Carey, 1982a; Block. 1983) and some scombrid fishes
(Linthicum and Carey, 1972). A cranial rete mirabile also
has been identified in mobulids (Schweitzer and Notarbar-
tolo di Sciara, 1986) and is thought to be a heat exchanger
(Alexander, 1995, 1996). Although it is premature to sug-
gest that the orbital rete of the bigeye thresher shark is a
heat exchanger without direct evidence of elevated tissue
temperatures in the brain and eyes, the structure is larger
than the rete mirabile of lamnid sharks, for which elevat-
ed brain and eye temperatures have been demonstrated
(Block and Carey, 1985). The anatomical arrangement of
an arterial plexus in an orbital sinus is correlated with
heat conservation strategies in other vertebrates (Baker,
1982). The phylogenetic relationships of the alopiid and
lamnid sharks (Compagno, 1990; Naylor et al., 1997) sug-
gest that endothermic traits evolved independently in the
two families.
This note presents new information on the depth and
ambient temperature preferences of the bigeye thresher
shark based on observations of two individuals, as well as
the anatomy of the orbital rete mirabile, which appears to
function as a vascular heat exchanger. Behavior of many
organisms varies with ontogeny, season and location;
therefore the present study should be considered as only
the beginning of an understanding of the bigeye thresher
shark's physical habitat preferences and adaptations to
temperature change. Further studies on individuals of
different sizes and in different regions will enhance our
understanding of the behavior, and morphological and
physiological adaptations, of the bigeye thresher shark to
variations in temperature.
Acknowledgments
This research was supported by grants from the National
Marine Fisheries Service, the National Fish and Wildlife
Federation and the Packard Foundation. The authors wish
to thank Captain David Price and crew of the FV Allison,
and Captain John Bagwell and crew of the FY Silky. Shana
Beemer provided scientific assistance on the cruise and
Captain McGrew Rice assisted in tagging and releasing the
Gulf of Mexico shark. This research was conducted under
Scientific Research Permit TUNA-SRP-2000-002, issued
by the Office of Sustainable Fisheries, National Marine
Fisheries Service, Silver Spring, MD 20910.
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229
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283-298.
Fishery Bulletin 102(1)
231
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Volume 102
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Fishery
Bulletin
Contents
The conclusions and opinions expressed
in Fishery Bulletin are solely those of the
authors and do not represent the official
position of the National Marine Fisher-
ies Service (NOAAi or any other agency
or institution.
The National Marine Fisheries Service
iNMFS) does not approve, recommend, or
endorse any proprietary product or pro-
prietary material mentioned in this pub-
lication. No reference shall be made to
NMFS, or to this publication furnished by
NMFS. in any advertising or sales pro-
motion which would indicate or imply
that NMFS approves, recommends, or
endorses any proprietary product or pro-
prietary material mentioned herein, or
which has as its purpose an intent to
cause directly or indirectly the advertised
product to be used or purchased because
of this NMFS publication.
Articles
233-244 Archer, Frederick, Tim Gerrodette, Susan Chivers,
and Alan Jackson
Annual estimates of the unobserved incidental kill of
pantropical spotted dolphin (Stenella attenuata attenuata)
calves in the tuna purse-seme fishery of the eastern
tropical Pacific
245-250 Chernova, Natalia V., and David L. Stein
A remarkable new species of Psednos (Teleostei: Liparidae)
from the western North Atlantic Ocean
251-263 Chiang, Wei-Chuan, Chi-Lu Sun, Su-Zan Yeh,
and Wei-Cheng Su
Age and growth of sailfish Ustiophorus platypterus)
in waters off eastern Taiwan
264-277 Clark, Randall D., John D. Christensen, and Mark E. Monaco,
Philip A. Caldwell, Geoffrey A. Matthews,
and Thomas J. Minello
A habitat-use model to determine essential fish habitat
for juvenile brown shrimp (Farfantepenaeus aztecus)
in Galveston Bay, Texas
278-288 Delgado, Gabriel A., Claudine T. Bartels, Robert A. Glazer,
Nancy J. Brown-Peterson, and Kevin J. McCarthy
Translocation as a strategy to rehabilitate the queen conch
(Strombus gigas) population in the Florida Keys
289-297 Lage, Christopher, Kristen Kuhn, and Irv Kornfield
Genetic differentiation among Atlantic cod (Gadus morhua)
from Browns Bank, Georges Bank,
and Nantucket Shoals
298-305 Lenihan, Hunter S., and Charles H. Peterson
Conserving oyster reef habitat by switching from dredging and
tonging to diver-harvesting
Fishery Bulletin 102(2)
306-327 Macewicz, Beverly J., John R. Hunter, Nancy C. H. Lo, and Erin L. LaCasella
Fecundity, egg deposition, and mortality of market squid (Loli/go opalescens)
328-348 Orr, James W., and James E. Blackburn
The dusky rockfishes (Teleostei: Socrpaeniformes) of the North Pacific Ocean
resurrection of Sebastes variabilis (Pallas, 1814) and a redescnption of Sebastes ci/iatus (Tilesius, 1813)
349-365 Powers, Joseph E.
Recruitment as an evolving random process of aggregation and mortality
366-375 Szedlmayer, Stephen T., and Jason D. Lee
Diet shifts of juvenile red snapper (Lut/anus campechanus) with changes in habitat and fish size
376-388 Webb, Stacey, and Ronald T. Kneib
Individual growth rates and movement of juvenile white shrimp (Litopenaeus setiferus) in a tidal marsh nursery
Notes
389-392 Forsythe, John, Nuutti Kangas, and Roger T. Hanlon
Does the California market squid (Loligo opalescens) spawn naturally during the day or at night?
A note on the successful use of ROVs to obtain basic fisheries biology data
393-399 Kotas, Jorge E., Silvio dos Santos, Venancio G. de Azevedo, Berenice M. G. Gallo,
and Paulo C. R. Barata
Incidental capture of loggerhead (Caretta caretta) and leatherback (Dermochelys conacea) sea turtles
by the pelagic longline fishery off southern Brazil
400-405 Yang, Mei-Sun
Diet changes of Pacific cod (Gadus macrocephalus) in Pavlof Bay associated with climate changes in the
Gulf of Alaska between 1980 and 1995
406 Subscription form
233
Abstract— We estimated the total
number of pantropical spotted dolphin
(Stenella attenuata) mothers killed
without their calves ("calf deficit") in
all tuna purse-seine sets from 1973-90
and 1996-2000 in the eastern tropical
Pacific. Estimates were based on a
tally of the mothers killed as reported
by color pattern and gender, several
color-pattern-based frequency tables,
and a weaning model. Over the time
series, there was a decrease in the calf
deficit from approximately 2800 for
the western-southern stock and 5000
in the northeastern stock to about 60
missing calves per year. The mean
deficit per set decreased from approxi-
mately 1.5 missing calves per set in
the mid-1970s to 0.01 per set in the
late-1990s. Over the time series exam-
ined, from 75% to 95% of the lactating
females killed were killed without a
calf. Under the assumption that these
orphaned calves did not survive with-
out their mothers, this calf deficit rep-
resents an approximately 14% increase
in the reported kill of calves, which is
relatively constant across the years
examined. Because the calf deficit as
we have defined it is based on the kill
of mothers, the total number of mis-
sing calves that we estimate is poten-
tially an underestimate of the actual
number killed. Further research on
the mechanism by which separation
of mother and calf occurs is required
to obtain better estimates of the unob-
served kill of dolphin calves in this
fishery.
Annual estimates of the unobserved
incidental kill of pantropical spotted dolphin
{Stenella attenuata attenuato) calves
in the tuna purse-seine fishery
of the eastern tropical Pacific
Frederick Archer
Tim Gerrodette
Susan Chivers
Alan Jackson
Southwest Fisheries Science Center
National Marine Fisheries Service
8604 La Jolla Shores Dr.
La Jolla, California 92037
E-mail address (for F Archer): enc.archeriainoaa.gov
Manuscript approved for publication
7 January 2004 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Sceintific Publications Office.
Fish. Bull. 102:233-244 (2004).
In the eastern tropical Pacific (ETP),
yellowfin tuna (Thunnus albacares)
are frequently found swimming under
schools of pantropical spotted ( Stenella
attenuata) and spinner (S. longirostris)
dolphins. For the past four decades,
the ETP yellowfin tuna fishery has
made use of this association by chasing
the more visible dolphins at the sur-
face and using purse-seines to encircle
the schools "carrying" the tuna (NRC,
1992). The large bycatch of dolphins in
this fishery has become widely known
as the "tuna-dolphin issue" (Gerro-
dette, 2002). During the 1960s, the
number of dolphins killed by the fishery
was estimated to be 200,000-500,000
per year (Wade, 1995), and two stocks
of spotted and spinner dolphins were
reduced to fractions of their previous
sizes (Smith, 1983; Wade et al.1). Along
history of technological innovations by
fishermen, laws and fishing regula-
tions, dolphin quotas, eco-labeling of
"dolphin-safe" tuna, and a comprehen-
sive international observer program
(Gosliner, 1999; Hall et al, 2000; Ger-
rodette, 2002) has reduced the dolphin
bycatch to less than 1% of its former
level. The reported bycatch in recent
years is less than 2000 dolphins per
year for all species combined (IATTC,
2002).
Although the reported kill has dra-
matically decreased, recent studies
suggest that there is little evidence
that the stocks are growing close to
expected rates (Wade et al.1). One hy-
pothesis for this lack of recovery has
been that there are unobserved kills of
dolphins during tuna purse-seine sets.
Archer et al. (2001) presented evidence
of an under-representation of suckling
spotted and spinner dolphin calves in
a sample of tuna purse-seine sets in
the eastern tropical Pacific. Given that
some of these missing calves are still
dependent on their mothers for nutri-
tion, it is likely that once separated
they would die and this under-repre-
sentation represents some degree of
unobserved kill.
In Archer et al. (2001), the sample
of sets examined was limited to those
sets in which all of the animals killed
had biological data collected by techni-
cians aboard the tuna vessel. Calves
still dependent on their mothers in the
kill were identified by five intervals of
body length, chosen to cover a range of
1 Wade, P. R.. S. B. Reilly. and T. Gerro-
dette. 2002. Assessment of the popula-
tion dynamics of the northeastern offshore
spotted and the eastern spinner dolphin
populations through 2002. National
Oceanographic and Atmospheric Admin-
istration Administrative Report LJ-02-
13. 58 p. Southwest Fisheries Science
Center. 8604 La Jolla Shores Dr., La Jolla,
CA 92037.
234
Fishery Bulletin 102(2)
calf sizes. Because of this approach, it was not possible to
derive a single estimate of the number of missing calves
or to extrapolate their estimate to sets not used in this
analysis.
In the current study, we present a different method of
estimating the number of missing calves in each set where
offshore spotted dolphins (S. attenuate! attenuata) were
killed. For brevity, we call the shortage of calves in the kill
in relation to the number of lactating females in the kill
the "calf deficit." We examined the western-southern and
northeastern offshore stocks separately according to the
geographic boundaries described by Dizon et al. (1994).
As they age, spotted dolphins change color through five
color phases (Perrin, 1970). We used the color-phase
frequency distribution of the kill in conjunction with age-
and color-based frequency distributions from a sample of
the kill to estimate the total number of missing calves in
each stock, along with confidence intervals derived from
bootstrap replications. This method also allowed us to
examine the calf deficit from sets in recent years from
which we did not have biological samples and to examine
the time series of available years for evidence of a trend
in the calf deficit.
Methods
Since 1973, observers have been randomly placed on tuna
purse-seine vessels. For each spotted dolphin killed during
an observed set, observers attempted to record the sex and
the color phase of the dolphin ( neonate, two-tone, speckled,
mottled, and fused, see Perrin, 1970). From the National
Marine Fisheries Service (NMFS) set log database, we
obtained the number of northeastern and western-south-
ern offshore spotted dolphins (by gender and color phase)
killed in every observed set from 1973 to 1990. The Inter-
American Tropical Tuna Commission (IATTC) provided
the same data from 1996 to 2000.
Proration
In each set, color phase or gender (or both) may not have
been recorded for some dolphins. Assuming that the distri-
bution of the demographic composition of this missing data
is equivalent to the overall demographic composition of the
kill, we allocated the number of dolphins cf unknown color
phase (nu) to unknown gender in each color phase (jigu)
according to the following formula,
ngu: = ngu, +
N.
I",
(1)
where c = one of the five color phases (neonate to fused I;
Nc = the total number of dolphins in each color
phase in the entire data set; and
ngu\. = the new number of dolphins in each color phase
where gender is unknown, including the indi-
viduals of prorated unknown color phase
The number of male (nm'c) or female (nf'c) dolphins in a
color phase was calculated as
nm,. = nm +
ngu, ■
Nm.
Nni + Nf\ j
nfc'=nft +
ngu
w
Nmc+Nfr
(2)
(3)
where Nmc and Nfc are the total number of males and
females, respectively, observed in that color phase in
the entire data. Table 1 gives the sample size of sets for
both stocks by year, as well as the fraction of the kill of
unknown gender and color phase that were prorated as
described above.
Number of suckling calves
As time permitted, NMFS observers would also collect
biological data from a subset of the kill. For this study,
we used ages estimated from teeth collected for a study of
spotted dolphin growth and reproduction (Myrick et al.,
1986 ). The specimens used were a random sample of all
male and female spotted dolphins collected between 1973
and 1978 for which total body length was recorded and
teeth were collected. However, additional specimens with
lengths less than 150 cm were selected in order to match
as closely as possible the length distribution of the aged
sample to the underlying length distribution of the spotted
dolphins in the kill. This was necessary because observ-
ers did not generally collect teeth from smaller, younger
animals. Later, another sample of female spotted dolphins
was selected from specimens collected in 1981. Specimens
were aged as described in Myrick et al. ( 1986 ).
The final data set used in our analyses included age
estimates for 1094 female spotted dolphin specimens and
798 male specimens. Of these, 649 females and 457 males
belonged to the northeastern stock and had color phase re-
corded. These 1 106 dolphins were used to generate the age
frequency distribution for each color phase (F , Table 2).
(4)
'""Is,,
where Sac = the number of samples of age a in color phase c.
The oldest age recorded was 36 years.
To derive an age distribution for the dolphins killed in
each tuna set, we estimated the number of dolphins in each
age class (na) as
»,,=x^„
i 5)
where n'
the sum of nm'c and «/' (the number of males
and females in each color phase after prora-
tion from Equations 2 and 3).
Archer et al.: Estimates of the incidental kill of Stenella attenuata attenuata calves in the tuna purse-seine fishery
235
Table 1
Sample
sizes of NMFS (1973-1990)
and IATTC (1996-2000) observed sets with spotted dolphin kill
made on two stocks of pan-
tropical
spotted dolphins iStenella a
ttenuata) by yea
r.
Northeastern stock
Western-southern stock
Fraction of
Fraction of
Fraction of
Fraction of
kill of
kill of
kill of
kill of
Number of
Observed
unknown
unknown
Number of
Observed
unknown
unknown
Year
sets with kill
kill
color phase
gender
sets with kill
kill
color phase
gender
1973
332
5242
0.09
0.31
75
1199
0.17
0.34
1974
515
5864
0.16
0.23
92
1715
0.10
0.31
1975
554
8073
0.31
0.19
75
1702
0.30
0.20
1976
239
2376
0.24
0.25
356
6293
0.27
0.23
1977
467
2146
0.23
0.26
528
3358
0.18
0.32
1978
224
1016
0.18
0.41
329
3998
0.37
0.34
1979
218
1045
0.38
0.27
168
1262
0.40
0.14
1980
165
1132
0.45
0.28
106
1206
0.73
0.13
1981
121
815
0.46
0.13
112
1346
0.48
0.12
1982
171
1696
0.51
0.22
159
1966
0.37
0.38
1983
12
177
0.80
0.08
35
148
0.32
0.35
1984
43
294
0.37
0.25
71
961
0.48
0.15
1985
186
2625
0.39
0.40
54
381
0.49
0.13
1986
150
1816
0.48
0.28
132
1818
0.60
0.22
1987
630
3327
0.25
0.31
175
1768
0.62
0.14
1988
207
1142
0.18
0.27
107
479
0.36
0.34
1989
293
1096
0.29
0.25
323
2793
0.48
0.14
1990
157
515
0.16
0.31
121
829
0.35
0.13
1996
273
724
0.27
0.44
161
374
0.18
0.54
1997
163
393
0.15
0.42
274
738
0.24
0.48
1998
161
260
0.21
0.51
125
236
0.19
0.46
1999
189
317
0.18
0.58
88
159
0.11
0.56
2000
146
291
0.23
0.47
115
250
0.20
0.61
In Equation 4, an age distribution was generated for each
color phase, and then the number of dolphins in each age
class was summed across all color phases.
To estimate the number of calves in each set, we used
this age distribution in conjunction with a weaning model
developed from a study of the stomach contents and ages
of calves (Archer and Robertson, in press). The model
predicts the probability that an animal of a given age (a)
will be suckling:
Pi milk)
(6)
1 + e1
The estimated number of calves (JV„„;f) in a set is then
N.
calf
IK
calf
Pmilk).
(7)
In our estimate of Ncal? we chose to use only the first
four age classes (0 to 3) because P(milk)4 was extremely
small (2xl0~4). These age classes allowed us to decrease
computational time without significantly affecting the
estimates.
Number of lactating females
Observers visually examined the mamillaries of the 649
females used in the age distribution above (Eq. 4) for the
presence of milk as part of the suite of biological data
collected. Using these data in conjunction with the color
phase of these females, we calculated the fraction of lactat-
ing females in each color phase (Flacv),
Flac
■S/ac
Sfem,
(8)
where Slacv and Sfemc
the number of females that were
lactating and the total number
of females in color phase c of the
samples examined.
Flacc was 0.00, 0.01, 0.04, 0.22, and 0.50 for neonate, two-
tone, speckled, mottled, and fused specimens, respectively.
The estimated number of lactating females (Nlac) in a set
was then
Nlai. = ^(nf; Flacv
(9)
236
Fishery Bulletin 102(2)
Calf deficit
As described in Archer et al. (2001), the calf deficit (D)
in each set was calculated by subtracting the number of
calves (iVca;J from the number of lactating females (N[ac).
If this value was zero or less, then D was set to zero to
indicate that there were enough calves to account for all
lactating females killed ( Fig. 1 1,
D-
0 if7V„„<iV„i;/-
(10)
We calculated three deficit-based fractions: 1) the mean
deficit per set (Ds); 2) the mean deficit per dolphin killed
(Dk); and 3), the mean deficit per lactating female killed
CD,):
D
D, =
D,=
1°
ObsSets
ObsKill
!*>
EstLacKill
(11)
(12)
(13)
where ZD = the total observed calf deficit in each year;
ObsSets = the number of observed sets used in the
analysis, including those sets without a
dolphin kill;
ObsKill = the number of dolphins killed in the observed
sets; and
EstLacKill = the total estimated number of lactating
females killed.
The above analysis was conducted each year. Estima-
tion error was evaluated with 20,000 bootstrap replicates
for each year. For each replicate, the sets within that year
were randomly resampled. The frequency tables Fni. and
Flact were also recalculated by resampling the list of bio-
logical specimens. The parameters for the weaning model,
P(milk)a, were estimated again by resampling the 29
calves and by fitting the logistic model to the new data set
as described in Archer and Robertson (in press). All resa-
mpling was done with replacement. Nralp Nlac, and D were
estimated as described above for each set, and Ds, Dh, and
Dj were calculated for the replicate. The 95°; confidence
intervals for Af n//, Nlac, D, Ds, Dk, and D/ were estimated
from the 2.5'; and 97.5% quantiles of the distributions of
the bootstrap replicate values.
The total calf deficit (Dtotal) was estimated as the deficit
per dolphin killed (Dk) multiplied by the total number of
dolphins killed [NkiUed) by stock each year,
Table 2
Age-
class frequency distribution for e
ich color phase CFac).
Age
Two-
(yr)
Neonate
tone
Speckled
Mottled
Fused
0
0.80
0.12
0
0
0
1
0.20
0.32
0
0
0
2
0
0.31
0.04
0
0
3
0
0.16
0.18
0.01
0
4
0
0.05
0.14
0.02
0
5
0
0.02
0.13
0.03
0
6
0
0
0.13
0.04
0.01
7
0
0
0.06
0.05
0
8
0
0
0.10
0.06
0
9
0
0
0.06
0.07
0.01
10
0
0
0.01
0.10
0.01
11
0
0
0.01
0.14
0.03
12
0
0
0.01
0.08
0.02
13
0
0
0.04
0.07
0.03
14
0
0
0.03
0.07
0.03
15
0
0
0
0.06
0.06
16
0
0.01
0.01
0.06
0.07
17
0
0
0.01
0.03
0.07
18
0
0
0
0.01
0.07
19
0
0
0
0.03
0.09
20
0
0
0
0.03
0.07
21
0
0
0
0.01
0.08
22
0
0
0
0
0.06
23
0
0
0.01
0
0.07
24
0
0
0
0.01
0.04
25
0
0
0
0.01
0.04
26
0
0
0
0
0.04
27
0
0
0
0.01
0.03
28
0
0
0
0.01
0.02
29
0
0
0
0
0.01
30
0
0
0
0.01
0.02
31
0
0
0
0
0.01
32
0
0
0
0
0
33
0
0
0
0
0.01
34
0
0
0
0
0
35
0
0
0
0
0
36
0
0
0
0
0.01
For the period 1973-84, annual values of Nhlllcil for each
stock were provided by the IATTC (Joseph2). For 1984-90
and 1996-2000. values were published by IATTC (2002).
In the bootstrap estimation of the 959? CI around Dlntal, for
the 1973-90 period, each replicate was randomly sampled
from a normal distribution by using the estimated total
kill standard error. For 1996-2000, the total kill was
reported to be exact; therefore the total kill was used
without variance in all replicates.
D
total
Dl; * Nkmd
(1 li
- Joseph. J. 1994. Letter of September 6 to Michael Tillman.
2 p. Southwest Fisheries Science Center. 8604 La Jolla Shores
Dr., LaJolla. CA 92037.
Archer et al.: Estimates of the incidental kill of Stene/la attenuata attenuate/ calves in the tuna purse-seine fishery
237
Fraction of females lactating,
by color (1973-78, 1981): Flac
Number of lactating
females killed: Nh„
Tally of females,
by color: nj '
Tally of dolphins killed, by color and
sex, from set log ( 1973-90. 1996-2000)
Tally of dolphins,
by color: n\
Fraction of dolphins in age class,
by color (1973-78, 1981): Fat
Number of dolphins
killed, by age: Na
Probability of suckling,
by age (1989-91): P(milk)a
Calf deficit: D
Number of suckling
calves killed: Ncay
Figure 1
Diagram of the analytical method used to estimate the spotted dolphin (Stenella attenuata attenuata)
calf deficit in each set as described in the text. Boxes identify original data that were bootstrapped to
produce confidence intervals. Values in parentheses are years for which data were available.
In a subset of the sets that we examined, every indi-
vidual killed had been examined and biological samples
had been collected from it; therefore, we knew the actual
number of lactating females killed. There were 1108 of
these "100% sampled" sets on the northeastern stock, and
697 on the western-southern stock from 1973 to 1990. We
evaluated the accuracy of our frequency-based method
by conducting a paired /-test between our estimate of the
number of lactating females and the number observed in
each of these sets.
Stomach-content data were not available for every
animal in these 100% -sampled sets; therefore, we did not
know the actual number of suckling calves. However, we
also used paired /-tests to compare our estimate of the
number of suckling calves in each set with the number of
animals smaller than 122 cm, which was the estimated
length at which the probability of milk in the stomach
was 0.5, given the weaning model of Archer and Robertson
(in press). Likewise, our estimate of the calf deficit was
compared with the deficit as estimated by using a cutoff
length of 122 cm. These tests were done to determine if the
method in the present study would produce significantly
different results from the method used in the previous
study Paired /-tests were conducted for each year sepa-
rately, as well as for all years combined. A power analysis
was also performed for these paired /-tests to determine
the minimum detectable difference at which we could re-
ject the null hypothesis of no difference between methods
given observed sample sizes and variability.
Results
The calf deficit as a fraction of the number of dolphins
killed (Dk) increased slightly during the mid-1970s but
remained relatively constant throughout the rest of the
time series at approximately 0.14 missing calves per dol-
phin killed for both stocks (Fig. 2). The total calf deficit
(Dtotal) as estimated from the annual kill decreased from
highs of approximately 5000 in the mid-1970s down to
2000-3000 by the early 1980s (Fig. 3). In the late 1980s,
this value increased to approximately 5000 in northeast-
ern spotted dolphins (Table 3A) and approximately 2800
in the western-southern stock (Table 3B), reflecting an
increase in the reported kills. In the last five years of the
time series (1996-2000), the estimated total deficit was
approximately 60 missing calves.
The mean deficit per set (Z),) for northeastern spotters
over all years was 1.03 missing calves per set, and the me-
dian was 0.30 (Fig. 4). For western-southern spotted dol-
phins, the mean was 1.28 missing calves per set, and the
median was 0.33. The estimated mean deficit per set was
approximately 1.5 in the mid-1970s and decreased over
time to 0.01-0.02 at the end of the time series (Fig. 4). For
both stocks, 75- 95% of lactating females killed were not
killed with their calf (Fig. 5).
In the sets that were 100% -sampled, for all years com-
bined, there was no significant difference between the
observed and the estimated number of lactating females
killed in either stock (Table 4). The results of paired /-tests
238
Fishery Bulletin 102(2)
0.3-
Northeastern
0.2-
•:.[••
" "»"..|
1"
0.1 -
\\- |t
" "" f ^T
ll'
o.o-
0.3-
Western-southern
0.2-
1 1
I "
}ll|ttftf ll
. i
0.1 -
o.o-
— 1 1 1 1—
1970
1980
1990
2000
Year
Figure 2
Calf deficit per spotted dolphin (Stenella attenuata
attenuata) killed (D/; ) by year. Vertical lines indicate
95% confidence intervals.
12000
8000 --
4000
0
= 12000 ■■
8000
4000 "-
+■
Northeastern
••At
Western-southern
»t Air *
-+-
-i-
1970
1980 1990
Year
2000
Figure 3
Total estimated calf deficit ^Dlotal) by year. Vertical
indicate 95% confidence intervals.
by year indicated that the observed number of lactating
females in each set was significantly greater (P<0.05)
than the estimated number in 1977 for the northeastern
and the western-southern stocks and in 1979 for the west-
ern-southern stock. The difference was significantly less
in 1984 for the western-southern stock. Using 0.1 as our
type-2 error level, we determined through power analysis
that the minimum detectable difference («=0.05) between
the mean observed and estimated number of lactating
females per set across all years was approximately 0.08
and 0.09 in the northeastern and western-southern stocks
respectively.
The observed number of calves per set, defined as the
number of dolphins less than 122 cm, was significantly
greater for both stocks, for all years combined, than the
values estimated in this paper ( Table 5 ). The overall mean
difference was 0.17 calves per set for the northeastern
stock and 0.12 for the western-southern stock. About
half of the years showed a significant difference for each
stock. In the comparison of the calf deficit by year, only a
few years showed significant differences in either stock
(Table 5). However, the estimated deficit tended to be
larger than the observed deficit. The paired t-test for all
years combined was significant for the northeastern stock,
although the mean difference was only -0.06 missing
calves per set. The minimum detectable difference from
the power analysis for the mean number of calves per set
and mean calf deficit per set across all years was 0.06 and
0.08 respectively for both stocks.
Discussion
In the present study, we present an estimate of the number
of missing dependent northeastern and western-southern
offshore spotted dolphin calves in the tuna purse-seine
kill from 1973 to 1990 and from 1996 to 2000. The total
number of missing calves decreased through the time
series, which, because we estimated the calf deficit as a
function of the size of the kill, was a direct result of the
large reduction in the annual dolphin kill by the fishery.
Between 1973 and 2000, the shortage of calves in the
kill remained at a relatively constant fraction of the kill,
about 14ri , for both stocks of pantropical spotted dolphins
(Fig. 2). On the assumption that suckling calves do not
survive separation from their mother ( Archer et al., 2001;
Archer et al.: Estimates of the incidental kill of Stenella attenuata attenuate calves in the tuna purse-seine fishery
239
3.0
2.5
2.0
1.5
1.0
2° 0.5
CD
if)
I 0.0
I 3.0
a
1 2.5
c
a
| 2.0 f
1.5
1.0
0.5"
0.0"
-+-
Northeastern
•(.tt
It
• *
Western-southern
1 1
■+-
-H
-t-
1970
1980 1990
Year
2000
Figure 4
Mean calf deficit per set (Ds) by year. Vertical
lines indicate 959? confidence intervals.
1.0"
1
0.9"
■
,,
.1
",, "
ii ii
ti ' ■
0.8"
'<
"
0.7-
Q
§ 0.6"
5
Northeastern
CD
;? 0.5-
CD
"5. 10-
c
J? 0.9 -
i ■
1 ' ,,
Deficit per
o
co
, ".
ti
,,
0.7 1
0.6"
Western-southern
0.5-
970 1980 1990 2000
Year
Figure 5
Calf deficit per lactating female killed (D,) by year.
Vertical lines indicate 95^ confidence intervals.
Edwards3!, the estimated calf deficit represents an approx-
imately 147c underestimate of the reported kill.
The calf deficit in the present study was estimated from
the number of dependent calves and lactating females
killed by using age-color frequency tables and data on the
stomach contents of weaning calves. Specimens used to
derive the age and color table were collected from 1973 to
1978 and 1981, and specimens used for the weaning model
were collected between 1989 and 1991. If the distributions
of these samples were not representative of all years that
we examined, then our results may be biased. However, the
results of a study to construct the annual age distribution of
the kill (Archer and Chivers4 ) indicated that there is no sig-
nificant difference in the age-color frequency table across
years. The sample size for the stomach data ( 29 calves) was
too small to examine differences between years.
Our finding of no significant difference between our esti-
mates of the number of lactating females and the observed
tally of lactating females in sets where the entire kill was
sampled validates this portion of our estimation proce-
dure. However, because the number of suckling calves
present in these 100% -sampled sets was not recorded, we
were unable to validate the method used to generate these
estimates in a similar manner.
The results of our paired Ntests indicated that the ob-
served number of animals smaller than 122 cm tended to
be greater than the number we estimated. This is most
likely a result of the difference between how calves were
counted in each method. Archer et al. ( 2001 ) considered all
animals under a series of cutoff values to be calves that
were dependent on suckling for survival. In the present
study, the weaning model that we used (Archer and Rob-
3 Edwards, E. F. 2002. Behavioral contributions to separa-
tion and subsequent mortality of dolphin calves chased by tuna
purse-seiners in the eastern tropical Pacific Ocean. National
Oceanographic and Atmospheric Administration Administra-
tive Report LJ-02-28, 34 p. Southwest Fisheries Science
Center, 8604 La Jolla Shores Dr., La Jolla, CA 92037.
4 Archer. F.. and S. J. Chivers. 2002. Age structure of the
northeastern spotted dolphin incidental kill by year for 1971 to
1990 and 1996 to 2000. National Oceanographic and Atmo-
spheric Administration Administrative Report LJ-02-12, 18 p.
Southwest Fisheries Science Center, 8604 La Jolla Shores Dr.,
La Jolla. CA 92037.
240
Fishery Bulletin 102(2)
Table 3
Estimated calf deficit per kill (Dt)
and total calf deficit
Total number of
spotted dolphins killed reported by the I ATTC ( 2002 ) and
Joseph (footnote 2 in the general text). Values in parentheses are 95% lower and upper confidence intervals.
Mean calf
Total number
Estimated calf
deficit
of NE spotted
Estimated
Stock and
deficit in
Observed
per kill
dolphins killed
total calf
year
observed sets
dolphin kill
(Dk)
(±SE)
deficit
A Northeastern (NE) stock
1973
599
5242
0.11
49928 ±8899
5709
(464,964)
(3947,6820)
(0.10,0.16)
(3972,9532)
1974
634
5864
0.11
37410 ±4222
4046
(583,10271
(4943,6916)
(0.10,0.16)
(3573,6708)
1975
1014
8073
0.13
49399 ±8809
6206
1618,12691
(6578,9965)
(0.08,0.14)
(3297.8254)
1976
300
2376
0.13
20443 ±4721
2583
(196,408)
(1786.3079)
(0.09,0.15)
(1284.3903)
1977
341
2146
0.16
5937 ±690
943
(249,416)
(1743.26221
(0.13,0.18)
(656,1167)
1978
148
1016
0.15
4226 ±827
616
(83,209)
(684,1431)
(0.11,0.16)
(336,8361
1979
138
1045
0.13
4828 ±817
640
(96.226)
(680,1629)
(0.11,0.17)
(428,963)
1980
178
1132
0.16
6468 ±962
1016
(107,239)
(724.1637)
(0.12,0.18)
(622,13001
1981
137
815
0.17
8096 ±1508
1366
(84,173)
(560,1122)
(0.12,0.18)
(753,1774)
1982
212
1696
0.12
9254 ±1529
1155
(155,347)
(1126,23951
(0.11,0.17)
(833,1840i
1983
27
177
0.15
2460 ±659
377
(7,59)
(35,410)
(0.11,0.23)
(169.678)
1984
38
294
0.13
7836 ±1493
1017
(26,57)
(191,417)
(0.10,0.17)
(608,1602)
1985
337
2625
0.13
25975 ±3210
3338
(235,508)
(1839.3529)
(0.11,0.16)
(2447,4748)
1986
290
1816
0.16
52035 ±8134
8297
H19.478)
(859.3440)
(0.10,0.17)
14496,9935)
1987
497
3327
0.15
35366 ±4272
5280
(397,667)
(2777,4002)
(0.13.0.18)
(3949.71061
1988
182
1142
0.16
26625 ±2744
4234
(122,215)
(880,1462)
(0.12.0.17)
(2825.4907)
1989
165
1096
0.15
28898 ±3108
4357
(120.217)
(871,1371)
(0.12.0.17)
(3186,54921
1990
65
515
0.13
22616 ±2575
2875
(53.90)
(421,632)
(0.11,0.17)
(2176,4085)
1996
88
724
0.12
818
99
(76.142)
(568,926)
(0.12.0.17)
(96.139)
1997
49
393
0.13
721
91
(42,69)
(331,461)
(0.11,0.17)
(81,121)
1998
33
260
0.13
298
38
(26,41)
(230,296)
(0.10.0.16)
(30,46)
1999
36
317
0.11
358
40
(30,48)
(282,357)
(0.10.0.15)
(35,53)
2000
43
291
0.15
295
44
(32.58)
(247.342)
(0.12,0.18)
(35.541
continued
Archer et al.: Estimates of the incidental kill of Stenella attenuata attenuate calves in the tuna purse-seine fishery
241
Table 3 (continued)
Stock and
year
Mean calf
Total number
Estimated calf
deficit
of NE spotted
Estimated
deficit in
Observed
per kill
dolphins killed
total calf
observed sets
dolphin kill
CD*)
(±SE)
deficit
141
1199
0.12
51,712 ±10.721
6076
(110,229)
(836,1638)
(0.10,0.17)
(3993-10,633)
254
1715
0.15
35,499 ±10.309
5254
(100,318)
(939,2733)
(0.07.0.15)
(1554,6890)
197
1702
0.12
48,837 ±10,055
5664
(123.322)
11104,2434)
(0.09,0.15)
(3285,9121)
795
6293
0.13
52,206 ±8883
6595
(524,1036)
(4925,7860)
(0.09,0.15)
(3833,9223)
491
3358
0.15
11.260 ±1186
1647
(345,563)
(2860,3906)
(0.11.0.16)
(1098,1959)
660
3998
0.17
11.610 ±2553
1917
(342,949)
(2508,5922)
(0.12.0.18)
(932.2614)
157
1262
0.12
6.254 ±1229
776
1104.216)
(939.1643)
(0.09,0.15)
(438.1138)
144
1206
0.12
11.200 ±2430
1339
(59.3441
(411.2542)
(0.10,0.17)
(831,2320)
191
1346
0.14
12.512 ±2629
1775
(90,340)
(577.2416)
(0.11.0.17)
(1010,2682)
306
1966
0.16
9869 ±1146
1536
(198,474)
(1337,2734)
(0.13,0.19)
(1156,2088)
23
148
0.16
4587 ±928
724
(15.33)
(99.206)
(0.12.0.20)
(418,1087)
114
961
0.12
10.018 ±2614
1183
(80.224)
(526,1513)
(0.12,0.18)
(712,2352)
52
381
0.14
8089 ±951
1105
(32,791
(225.5701
(0.11.0.17)
(781,1524i
275
1818
0.15
20,074 ±2187
3037
(143,373)
(1065.2784)
(0.10.0.17)
(1776,3617)
271
1768
0.15
19,298 ±2899
2959
(147,374)
(1068,2661)
(0.11,0.16)
(1754,3695)
75
479
0.16
13,916 ±1741
2166
(51,96)
(368,605)
(0.12,0.18)
(1453,2785)
392
2793
0.14
28,560 ±2675
4011
(242,589)
(1819,4277)
(0.11,0.16)
(2861.4977)
123
829
0.15
12,578 ±1015
1864
(78,160)
(582.1128)
(0.11,0.17)
(1283,2236)
53
374
0.14
545
77
(42,711
(308.448)
(0.12,0.18)
(64,97)
89
738
0.12
1044
126
(72,132)
(598.931)
(0.11.0.16)
(112,165)
31
236
341
44
0.13
(25,42)
(192.288)
(0.11,0.17)
(38,58)
22
159
0.14
253
35
(16.32)
(123,209)
(0.11,0.18)
(28,44)
28
250
0.11
435
48
(22.44)
(189,330)
(0.10.0.15)
(42.67)
B Western-
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1996
1997
1998
1999
2000
southern (WS) stock
242
Fishery Bulletin 102(2)
Table 4
Annual mean observed and mean estimated
are 95% lower and upper confidence intervals
ference from zero (P<0.05) in the paired t-test
number of lactating females per
assuming a normal distribution
s.
set in 100% sampled sets. Values in parentheses
of differences. Bold type indicates significant dif-
Year
Northeastern stock
Western-southern stock
No. of
sets
Observed
Estimated
Difference
(959S CI)
No. of
sets
Observed
Estimated
Difference
(95% CD
1973
116
0.55
0.61
-0.06 1-0.17.0.051
21
1.19
1.30
-0.11 (-0.63,0.421
1974
98
0.51
0.54
-0.03 1-0.13.0.07)
16
0.75
0.81
-0.061-0.36.0.24)
1975
99
0.57
0.48
0.09 (-0.05,0.22)
14
1.07
0.92
0.15 (-0.46.0.77)
1976
51
0.28
0.35
-0.08 1-0.18.0.02)
90
0.500
0.502
-0.002 (-0.119.0.115)
1977
167
0.55
0.46
0.09 (0.01.0.15)
163
0.49
0.37
0.12 (0.03,0.21)
1978
82
0.37
0.40
-0.03 1-0.14,0.08)
93
0.50
0.52
-0.02 (-0.19,0.13)
1979
75
0.47
0.46
0.01 (-0.13,0.14)
61
0.64
0.47
0.17 (0.01,0.33)
1980
54
0.39
0.38
0.01 (-0.11.0.13)
34
0.50
0.44
0.06 1-0.09,0.20)
1981
41
0.53
0.74
-0.21 (-0.81,0.38)
38
0.66
0.64
0.02 1-0.16.0.19)
1982
36
0.62
1.18
-0.56 (-1.40,0.27)
33
0.30
0.44
-0.14 1-0.37,0.10)
1983
33
1.33
2.14
-0.8K-7.89.6.28)
6
0.17
0.57
-0.40 (-1.57,0.77)
1984
4
0.25
0.49
-0.24 1-0.67,0.18)
29
0.48
1.08
-0.60 (-0.96,-0.23)
1985
70
0.34
0.50
-0.16 1-0.36,0.061
17
0.35
0.50
-0.15 1-0.49,0.20)
1986
45
0.71
0.47
0.24 1-0.04,0.51)
28
0.61
0.42
0.19 1-0.01.0.38)
1987
121
0.43
0.46
-0.03 (-0.18,0.11)
30
0.27
0.46
-0.19 1-0.44.0.06)
1988
6
0.44
0.57
-0.13 (-0.59,0.35)
—
—
—
—
1989
24
0.96
1.03
-0.07 1-0.59,0.44)
15
0.93
0.96
-0.03 (-0.68,0.64)
1990
16
0.56
0.47
0.09 1-0.25,0.44)
9
0.67
0.93
-0.26 1-0.94,0.42)
All
1108
0.50
0.53
-0.03 1-0.08,0.02)
697
0.545
0.546
-0.001 (-0.053,0.051)
ertson, in press) estimated the probability that a calf of a
given age class was still suckling. Given that body length
has a near linear relationship with age in these young
age classes (Perrin, 1976), this meant that for any chosen
length of independence, each individual smaller than that
cutoff value would only be counted fractionally, in effect
correcting for the probability that an animal of a given
age is not suckling. This procedure caused the method in
this paper to tally fewer "calves" in each set than in the
previous study. A secondary result of this effect was that
the mean deficit per set estimated in the present study
tended to be slightly higher than that presented by Archer
etal. in 2001.
We estimated the total number of missing calves as a
function of the number of dolphins killed in each stock
(Table 3). Prior to 1995, only a fraction of the purse-seine
trips carried scientific observers. To estimate the number
killed in each stock, kill rates from the observed trips were
applied to unobserved trips, stratified by area and stock
(IATTC, 2002; Joseph, 19942). Since 1995 it has been re-
ported that all dolphin sets have been observed, and that
the number of dolphins killed is therefore known without
error (IATTC, 2002).
The total calf deficit could also be estimated as a function
of the number of sets by multiplying the total number of
sets made on each stock by Ds (Fig. 4). In the only study to
estimate the number of sets made on each stock annually.
Archer et al.5 used a relatively simple proration scheme of
unobserved sets derived from ratios of the number of sets
made on each stock in observed sets. However, because
Archer et al.5 did not stratify unobserved sets by area, bas-
ing the total calf deficit on these estimates would produce
a different result from that presented in Table 3. Because
the estimates of the kill by stock included stratification
by area, estimates of the total calf deficit calculated by
multiplying the kill estimates by D,. are likely to be more
accurate. It is important to realize that the deficit that we
present is directly related to the kill observed in the sets
that we used. In other words, if proration schemes for un-
observed sets were the same for the number of sets made
and the number of dolphins killed, estimates of the total
calf deficit with either D^ or Dk would be equivalent.
Wade et al.1 explored the effects of 50% and 100' < ad-
ditional fisheries-related mortality on the assessment of
the northeastern spotted dolphin stock. The assumption of
additional mortality led to higher estimates of maximum
Archer. F.. T. Gerrodette. and A. Jackson. 2002. Prelim-
inary estimates of the annual number of sets, number of
dolphins chased, and number of dolphins captured by stock
in the tuna purse-seine fishery in the eastern tropical Pacific.
1971-2000. National Oceanographic and Atmospheric Admin-
istration Administrative Report LJ-02-10. 26 p. Southwest
Fisheries Science Center, 8604 La Jolla Shores Dr., La Jolla,
CA 92037.
Archer et al.: Estimates of the incidental kill of Stenella attenuata attenuata calves in the tuna purse-seine fishery
243
Table 5
Annua
1 mean number of dolphins killed sl22 cm (calves killed based
on length) and estimated number of
suckling calves (calves
based
3n weaning model 1 per set in 100rt sampled sets (first line for each year!. Mean deficit per set using
.22 cm as cutoff length
(calf deficit based on length
) and calf deficit
as estimated in this article (calf deficit based on weaning model) on second line for
each year. Values in parentheses are 959! lower and upper confidence intervals assuming a normal dist
•ibution of differences.
Differences in bold indicate
significant difference from zero (PsO.05)
in the paired Mest.
Northeastern stock
Western-southern
stock
Calves killed
Calves killed
Calves killed
Calves killed
based on
based on
based on
based on
length
weaning model
length
weaning model
No.
Calf deficit
Calf deficit
No.
Calf deficit
Calf deficit
of
based on
based on
Difference
of
based on
based on
Difference
Year
sets
length
weaning model
(95% CD
sets
length
weaning model
(95% CD
1973
116
0.54
0.21
0.33 (0.18,0.50)
21
0.33
0.06
0.27 (0.01,0.55)
0.35
0.48
-0.13 (-0.26,-0.03)
1.00
1.25
-0.25 1-0.79.0.29)
1974
98
0.39
0.05
0.34 (0.20,0.47)
16
0.56
0.09
0.47 1-0.53.1.47)
0.36
0.50
-0.14 (-0.26,-0.03)
0.56
0.74
-0.181-0.61,0.25)
1975
99
0.57
0.15
0.42 (0.20,0.64)
14
0.29
0.11
0.18(-0.03.0.39)
0.46
0.40
0.04 1-0.05.0.161
0.93
0.83
0.10(-0.45,0.66i
1976
51
0.18
0.11
0.07 1-0.01,0.15)
90
0.13
0.07
0.06 (0.001,0.13)
0.28
0.31
-0.031-0.14.0.06)
0.49
0.47
0.02 1-0.10.0.15)
1977
167
0.10
0.03
0.07 (0.02,0.12)
163
0.17
0.06
0.11 (0.06,0.16)
0.51
0.45
0.06 (-0.01,0.14)
0.46
0.35
0.11(0.03,0.20)
1978
82
0.17
0.03
0.14(0.05,0.23)
93
0.18
0.05
0.13 (0.04,0.23)
0.35
0.39
-0.04 (-0.14.0.07)
0.43
0.50
-0.07 1-0.22.0.09)
1979
75
0.09
0.04
0.05 (-0.02,0.13)
61
0.31
0.13
0.18(0.04,0.32)
0.44
0.43
0.01 (-0.11,0.13)
0.51
0.37
0.14 1-0.03,0.31)
1980
54
0.16
0.03
0.13 (0.02,0.25)
34
0.00
0.01
-0.01 (-0.02,-0.003)
0.373
0.371
0.002-0.115,0.119)
0.50
0.44
0.061-0.08.0.21)
1981
41
0.105
0.110
-0.005 1-0.194,0.185)
38
0.05
0.04
0.01 (-0.04.0.07)
0.53
0.65
-0.121-0.57,0.31)
0.63
0.62
0.01 (-0.17,0.20)
1982
36
0.44
0.21
0.23 (-0.10.0.55)
33
0.06
0.02
0.04 1-0.04,0.12)
0.44
1.00
-0.56(-1.27,0.14i
0.27
0.42
-0.15 (-0.37,0.08)
1983
33
0.00
0.14
0.14 1-0.64.0.36)
6
0.17
0.04
0.13 1-0.31.0.57)
1.33
2.00
-0.67 (-7.25.5.91)
0.17
0.56
-0.39 1-1.56,0.76)
1984
4
0.00
0.02
-0.02 1-0.08,0.04)
29
0.14
0.04
0.10 1-0.01,0.21)
0.25
0.49
-0.24 1-0.67,0.18)
0.35
1.04
-0.69 (-1.13,-0.26)
1985
70
0.13
0.04
0.09(0.02,0.15)
17
0.06
0.04
0.02 1-0.06.0.10)
0.29
0.47
-0.181-0.39,0.03)
0.35
0.49
-0.14 (-0.48,0.21)
1986
45
0.13
0.04
0.09 (0.01,0.17)
28
0.04
0.03
0.01 (-0.04,0.06)
0.64
0.44
0.20 1-0.04.0.44)
0.57
0.39
0.181-0.02,0.38)
1987
121
0.14
0.02
0.12 (0.05,0.20)
30
0.23
0.08
0.15(0.02,0.30)
0.38
0.45
-0.07 1-0.22,0.07)
0.27
0.43
-0.16 (-0.41,0.09)
1988
6
0.11
0.33
0.12
0.50
-0.01 (-0.23.0.22)
-0.17 1-0.62,0.28)
—
—
—
—
1989
24
0.22
0.13
0.09 (-0.11,0.29)
15
0.47
0.20
0.27 (0.05,0.49)
0.87
0.95
-0.08 (-0.60,0.43)
0.73
0.82
-0.09 1-0.66,0.48)
1990
16
0.31
0.21
0.10 (-0.18,0.38)
9
0.89
0.17
0.72 1-0.18,1.62)
0.56
0.41
0.15 (-0.20.0.51)
0.33
0.77
-0.44 (-1.15,0.27)
All
1108
0.25
0.08
0.17 (0.13,0.20)
697
0.18
0.06
0.12 (0.09,0.16)
0.42
0.48
-0.06 (-0.10,-0.01)
0.49
0.51
-0.02 (-0.08,0.03)
244
Fishery Bulletin 102(2)
growth rates and lower estimates of the current size of
the population in relation to carrying capacity. Wade et
al.1 did not model the calf deficit estimated in our present
study, but the effect of 14/r additional mortality would
probably be less than the 50f> additional mortality that
was modeled. The 50^ mortality was spread over all age
classes, and additional mortality due to missing calves
should be assigned to the first two year classes only. The
important question is whether the calf deficit in the kill
represents the main effect of mother-calf separation by
the fishing process. As outlined in Archer et al. (2001t,
the mechanism by which suckling calves are separated
from their mothers is unknown. If separation is simply a
function of the number of lactating females killed, then the
deficit presented here is an accurate representation of the
number of "missing" calves.
However, there is some evidence that separation can
occur without the mother being killed. In the early days
of the backdown procedure, purse-seine skippers reported
that "Babies swim around the outside of the net pushing to
get back in probably because their mothers are still inside"
i Gehresp (. It is unclear whether these calves were sepa-
rated prior to encirclement or were released early during
backdown, prior to their mothers. Regardless, given that
dolphins exhibit some of their fastest swimming during
a set immediately upon release from the net tChivers and
Scott' ), separated calves waiting immediately outside the
net may risk separation if their mothers join the rest of the
school rapidly swimming away from the net. If this, or any of
the other scenarios regarding the manner in which perma-
nent separation can occur without the mother being killed
i Archer et al.. 2001 1. then the calf deficit underestimates the
actual number of orphaned calves. Future research should
focus on the mechanism of calf separation because a better
understanding of this process is the only way we will be able
to estimate the magnitude of the unobserved calf mortality
and its subsequent effects on the population.
Acknowledgments
The authors wish to thank Michael Scott and Xick Vogel
of the IATTC for providing data as well as Jay Bar-
B Gehres. L. E. 1971. Letter of July 2 to Alan R. Longhurst.
2 p. Southwest Fisheries Science Center, 8604 La Jolla Shores
Dr.. La Jolla. CA 92037.
7 Olivers. S. J., and M. D. Scott. 2002. Tagging and tracking
of Stenella spp. during the 2001 Chase Encirclement S
Studies cruise. National Oceanographic and Atmospheric
Administration Administrative Report LJ-02-33. 21 p. South-
west Fisheries Science Center, 8604 La Jolla Shores Dr.. La
Jolla. CA 92037.
low and Bill Perrin for helpful reviews and analytical
suggestions.
Literature cited
Archer. F.. T. Gerrodette, A. Dizon. K. Abella and S. Southern.
2001. Unobserved kill of nursing dolphin calves in a tuna
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245
Abstract— Psednos rossi new species
(Teleostei: Liparidaei is described from
two specimens collected in the North
Atlantic Ocean off Cape Hatteras,
North Carolina, at depths of 500-
674 m. Psednos rossi belongs to the
P. christinae group, which includes
six other species and is characterized
by 46-47 vertebrae and the absence
of a coronal pore. Psednos rossi dif-
fers from those six species by having
characters unique within the genus:
straight spine, body not humpbacked
at the occiput, and a very large mouth
with a vertical oral cleft. Other distin-
guishing characters include a notched
pectoral fin with 15-16 rays, eye
17-19% SL, and color in life orange-
rose. With P. rossi, the genus Psednos
as currently known includes 26 de-
scribed and five undescribed species of
small meso- or bathypelagic liparids
from the Atlantic. Pacific, and Indian
Oceans.
A remarkable new species of Psednos
(Teleostei: Liparidae) from the
western North Atlantic Ocean
Natalia V. Chernova
Zoological Institute
Russian Academy of Sciences
Unlversitetskaya nab- 1
St. Petersburg 199034. Russia
David L. Stein
NOAA/NMFS Systematlcs Laboratory
Smithsonian Institution
P.O. Box 37012
National Museum of Natural History, MRC-0153
Washington, DC. 20013-7012
E-mail address (for D L. Stem, contact author): david.stenvanoaa gov
Manuscript approved for publication
7 January 2004 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:245-250 (2004).
The liparid genus Psednos Barnard
1927 is a group of meso- and bathype-
lagic snailfishes distinguished from the
genus Paraliparis by having the infra-
orbital canal of the cephalosensory
system interrupted behind the eye and
usually having a pronounced dorsal
curvature of the spine, producing a
"humpbacked" body. Psednos are small,
easily damaged, and often misidenti-
fied as juvenile Paraliparis. Until 1978,
the genus was known only from two
specimens of a single species (Psednos
micrurus Barnard 1927) collected off
Cape Point, South Africa. Two addi-
tional specimens were collected in the
southern Indian Ocean and reported
by Stein (1978). No further specimens
or species were described until Andria-
shev (1992) described another new
species. Since then, active searches for
material from collections around the
world have yielded many specimens
from the Atlantic. Pacific, and Indian
Oceans. To date, 25 species have been
described (Andriashev, 1992, 199.3;
Chernova. 2001; Stein et al.. 2001;
Chernova and Stein, 2002) and an
additional five are undescribed (one in
Stein et al., 2001, three in Chernova
and Stein, 2002, all in poor condition;
and another that is currently being
described by Stein). In this article, we
describe an especially noteworthy spe-
cies of the genus from two specimens
collected from the North Atlantic off
Cape Hatteras, North Carolina.
Materials and methods
All characters available for both speci-
mens were studied. Characters and
terms used were described by Andria-
shev (1992), Chernova (2001), Stein
et al. (2001), and Chernova and Stein
(2002 1. Counts were made from a radio-
graph of the holotype and from each
specimen where possible; vertebral
counts include the urostyle. The first
caudal vertebra is that with the haemal
spine supporting the first anal-fin ray.
The posterior tip of the lower jaw in
Psednos forms a distinct and promi-
nent ventrally directed angle, the ret-
roarticular process (Chernova, 2001).
Counts and proportions are given as a
percentage of standard length ( SL) and
head length (HL). Nonstandard mea-
surements are the following: distance
from mandible to anus (from ante-
rior tip of mandible to center of anus);
distance from anus to anal-fin origin
(from center of anus to anal-fin origin);
interorbital width (measured between
upper margins of eyes); postocular
head length (distance from posterior
margin of eye to tip of opercular flap).
246
Fishery Bulletin 102(2)
Figure 1
Psednos rossi n.sp., paratype, USNM 372727. Adult, 51.8 mm SL, 57.2 mm TL. Sta. CH-01-047,
off Cape Hatteras. Scale 5 mm. Infraorbital pore 6 not shown owing to damage.
We selected the smaller specimen to serve as the holo-
type owing to its better condition (skin, pores, shape of
head) and the availability of more characters. Unfortu-
nately, it is distorted and does not look natural; therefore
the undistorted larger (adult) specimen, the paratype, is
illustrated. It is also more useful to have a drawing of an
adult for comparison with other Psednos specimens.
In these small fishes, precise counts of number of tooth
rows are possible only in disarticulated cleared and
stained specimens; thus, we provide approximate counts.
Similarly, the drawing of the gill arch of the paratype was
made without dissection by viewing through an opening in
the branchiostegal membrane.
Although Andriashev (1986) and Andriashev and
Stein (1998) demonstrated the importance of the pectoral
girdle in distinguishing among species and in explain-
ing liparid relationships, we did not dissect, clear, and
stain a pectoral girdle from these specimens owing to the
high probability of damaging them and destroying other
characters (Chernova, 2001; Chernova and Stein, 2002).
The new species is so easily distinguished from congeners
that it is not necessary for a diagnosis of the species to
look at additional characters that the pectoral girdle can
provide. Future specimens should be used to study these
characters.
The holotype and paratype are permanently deposited
in the Division of Fishes, Smithsonian Institution, Na-
tional Museum of Natural History (USNM collection).
Results
Psednos rossi, n.sp.
Holotype
USNM 372726, juvenile, 37.2 mm SL. TL?, Sta. EL-00-033,
off Cape Hatteras (The Point), 35°30.036'N, 74°46.497'W,
500-674 m over about 900 m depth, 23 July 2000, Tucker
trawl. Good condition but distorted.
Paratype
USNM 372727, adult (sex not identified), 51.8 mm SL,
57.2 mm TL, Sta. CH-01-047, off Cape Hatteras (The Point),
35°28.93'N, 74°45.93'W, 628-658 m over 1090-704 m depth,
24 Aug. 2001, Tucker trawl. Throat slightly damaged, head
slightly compressed, skin on head partly missing.
Diagnosis
Vertebrae 47, dorsal-fin rays 42-44, coronal pore absent.
Mouth vertical, symphysis of upper jaw above level of
eye. Body not humpbacked, vertebral column not curved
behind cranium. Gill cavity enlarged. Anus on vertical
behind head. Pectoral fin notched, rays 8+2+5-6. Eye
17-19% HL.
Description
Counts and proportions are given in Table 1. Head large,
about one-third SL, its depth less than, and its width
equal to or a little greater than, its length (Fig. 1). Head
depth slightly greater than its width. Mouth very large,
distinctly superior. Jaws almost vertical, at angle of about
90° to horizontal. Symphysis of upper jaw above level of
eye. Ascending process of premaxilla horizontal, its distal
end almost above center of eye. Posterior tip of lower jaw-
exactly below symphysis of upper jaw. Posterior (lower)
end of mouth cleft well below level of lower margin of eye.
When mouth closed, ventral surface of lower jaw forms
entire frontal surface of head. Lower jaw included. Sym-
physeal process present at lower jaw symphysis, projecting
forward prominently; retroarticular processes of lower
jaw large, acute, directed anteroventrally (Fig. 2 A I. Teeth
large, sharp, spear-shaped, strongly curved inward (Fig.
2B), in (smaller) holotype in approximately 22 and 24 (32
and 35) rows on upper and lower jaw; 5 (8-9) teeth in first
full row near symphyses of both jaws. Snout short, 1.5 ( 1.0)
times eye diameter. Olfactory rosette (7 lobes) and nostril
above anterior third of eye. Eyes not large, close to upper
Chernova and Stein: A new species of Psednos from the western North Atlantic Ocean
247
Table 1
Counts and proportions for the holotype and paratype of Psednos rossi new species. Proportions are in % of standard length (SL)
followed by % head length (HL, in parentheses).
Vertebrae
Dorsal-fin rays
Anal-fin rays
Pectoral-fin rays
Caudal-fin rays
Gill rakers
Head length
Head width
Head depth
Body depth
Body depth at anal-fin origin
Predorsal-fin length
Preanal-fin length
Mandible to anus
Anus to anal fin origin
Upper pectoral-fin lobe length
Pectoral-fin notch ray length
Lower pectoral-fin lobe length
Eye diameter
Snout length
Interorbital width
Postocular head length
Upper jaw length
Lower jaw length
Gill opening length
Opercle length
USNM 372726
Holotype 37.2 mm SL
47
44
35
16 [L] 15 [R]
6
32.3
22.0(68.1)
23.7(73.4)
21.5(66.6)
13.4(41.5)
29.6(91.6)
47.8(148.0)
34.9(108.0)
23.7(73.4)
13.4(41.5)
8.1(25.1)
9.4(29.1)
5.4(16.7)
8.1(25.0)
13.4(42.0)
18.8(58.0)
16.1(49.8)
16.1(49.8)
5.4(16.7)
13.4(41.5)
USNM 372727
Paratype 51.8 mm SL
42
33
15 [L, R]
6
10
29.9
13.5(45.2)
17.4(58.2)
25.1(83.9)
17.0(56.8)
26.6(89.0)
48.3(161.5)
36.7(122.7)
21.2(70.9)
13.5(45.2)
5.8(19.4)
7.7(25.8)
11.2(37.4)
19.3(64.5)
12.5(41.8)
13.5(45.2)
5.4(18.1)
12.5(41.8)
contour of head. Interorbital space flat, 2.5 (1.9) times eye
diameter. Gill opening short, 1.0 (0.9) times eye diameter,
at 45° angle, entirely above pectoral-fin base and slightly
anterior to it (distance between ventral end of gill opening
and base of upper pectoral ray about equal to length of gill
opening). Opercular flap small, acute. Opercle very long,
directed ventrally and posteriorly, its tip below level of pos-
terior end of lower jaw. Interopercle of similar length, vis-
ible externally, its anterior tip projecting anteriorly from
ventral contour of head (Fig. 1). Long opercle, interopercle
and elongated branchiostegal rays support membranes
of enlarged branchial cavity that appears externally as
a black posterior part of head. Branchial cavity length
slightly more than half head length. Branchiostegal rays
(4+2) long and distinctly visible externally. Gill rakers
modified, closely but irregularly set, mostly alternating
(especially on gill arch one), often paired on the outer
and inner sides of each gill arch (central part of arches
two and three); plates flattened, triangular, similar in
shape to those in P. pallidus or Psednos sp.l of Chernova
and Stein (2002, Figs. 9 and 13). spinule-bearing surface
directed internally, flat and longitudinally oval. Spinules
closely set, usually in two longitudinal rows, each of five
to eight spinules, often with a few additional spinules in
between (Fig. 2C).
Sensory pores difficult to see because of thin transpar-
ent skin (damaged in paratype). Nasal pores 2, the poste-
rior on a vertical through center of eye. Paired nasal bones
(through which the nasal canals run) long, tubular, and
visible externally. Coronal pore absent. Lacrimal bones
(bearing anterior portion of infraorbital canal) large, vis-
ible externally, slightly prominent anteriorly. Infraorbital
canal (better preserved in holotype) interrupted behind
eye, infraorbital pores 6 (5+1), posteriormost above poste-
rior margin of eye (Fig. 2A). In paratype, skin behind eye
missing. Preoperculomandibular pores 6 (3 on lower jaw
+ 3 on preopercular area). Two temporal pores present: tx
a short distance behind posterior margin of eye, and tsb,
the suprabranchial pore, above and in front of gill opening
(Fig. 2A).
248
Fishery Bulletin 102(2)
Pectoral fin notched, of 16 (15) rays. Upper lobe of 8 (8)
rays, the 2 (2) notch rays more widely spaced and placed
exactly at middle of fin base. In holotype, left lower pec-
toral lobe with 6, on right 5, rays. In paratype, 5 rays on
each side. Bases of lower-lobe rays stronger and thicker
than those of upper-lobe rays. Level of uppermost pectoral
ray below horizontal through lower end of upper jaw. Base
of pectoral fin close to vertical, lowest ray almost directly
below uppermost. Upper-lobe rays not reaching anal fin
origin, lower-lobe rays not reaching vertical through ends
of upper lobe rays. In holotype, length of notch rays 1.7
times in upper pectoral-fin lobe length, lower pectoral-fin
lobe 1.4 times in it.
Body not humpbacked, dorsal contour of back almost
straight; spine horizontal, its anterior end not dorsally
"'Vt
B
Figure 2
Details of anatomy of Psednos rossi. (A) Cephalic pores
and prominent features of head. Portions of sensory canals
passing through bones are stippled. N = nostril and olfac-
tory rosette; io = infraorbital pores, n = nasal pores, t =
temporal pores; S = symphyseal knob; R = retroarticular
process. (B) Teeth of paratype: (leftl frontal view; (right)
lateral view. Tooth length about 0.25 mm. (C) First gill
arch of paratype, USNM 372727. right side; view from
inside of gill cavity. Raker height about 0.3 mm.
curved (Fig. 3). Neural spines of vertebrae 1-4 neither
longer nor broader than those posterior, unlike other spe-
cies (see Fig. 5 in Chernova, 2001). Maximum body depth
4.2 (4.0) times in standard length and 1.6(1.5) times depth
at anal-fin origin. In holotype, occiput slightly swollen
(Fig. 3); in paratype, dorsal outline of head and back in
front of dorsal fin origin almost perfectly flat (Fig. 1), pos-
sibly an age-related difference. Abdominal part of body
long, preanal length almost half of standard length. Inter-
neural of first dorsal-fin ray between neural spines 3 and
4. Dorsal and anal fins moderately deep, maximum depth
of erect dorsal fin in paratype 8.9 times in SL, 2.7 times in
head length (damaged in holotype). Dorsal and anal fins
overlapping about one-third of caudal-fin length. Anus on
vertical behind head, slightly behind base of uppermost
pectoral ray. Skin transparent. Gelatinous subcutaneous
tissue weakly developed. In holotype (smaller specimen)
body not as deep and jaws longer than in the paratype
(larger specimen). Differences in head width and interor-
bital width are great because head of paratype was slightly
compressed during fixation. Other proportions similar to
those of holotype.
Body color in alcohol pale; under magnification, slightly
dusky blotches of dots present caudally in paratype and
absent in holotype. Head musculature pale. Black perito-
neum visible through body wall. Mouth and gill cavities,
gill arches, tongue, and both jaws black; gill rakers pale.
Musculature of pectoral girdle appears pale on lateral
surface of belly. Color in life orange-rose.
Distribution
Western North Atlantic off Cape Hatteras, mesopelagic
at depths of 500-674 m.
Etymology
The patronym "rossi" after Steve W. Ross, who initially
notified us of the captures and furnished the specimens
to us for examination.
Comparative notes
Psednos rossi seems to belong to the P. christinae group
(see Chernova, 2001; Chernova and Stein, 2002), includ-
ing P. andriashevi, P. barnardi, P. christinae. P. dentatus,
P. groenlandicus, and P. harteli. Species of this group are
characterized by vertebrae 46-47, dorsal-fin rays 38-42,
anal-fin rays 33-35, and coronal pore absent (versus the
P. micrurus group having vertebrae 40-44. dorsal-fin rays
34-38, anal-fin rays 28-33, and coronal pore present)
(Chernova, 2001). Psednos rossi distinctly differs from the
other species of the christinae group in at least having
occiput not swollen (vs. greatly swollen), not humpbacked
because the vertebral column is straight (vs. humpbacked
owing to the greatly curved anterior part of the spine),
mouth vertical with jaws at 90° to horizontal, symphysis
of upper jaw above level of eye (vs. a more or less oblique
mouth at an angle of 30-45° and the upper jaw. symphysis
on a horizontal with the lower half of the eve); and anus
Chernova and Stem: A new species of Psednos from the western North Atlantic Ocean
249
Figure 3
Radiograph of Psednos rossi n.sp., holotype. USNM 372726. Juvenile, 37.2 mm SL. Sta. EL-00-033, off Cape Hatteras.
behind the head (vs. anus below the posterior third of the
head). The very oblique, almost vertical mouth occurs
often in species of the P. micrurus group, five of which
have the mouth at 75-85° to the horizontal (P. anoderkes,
P. cathetostomus, P. microps, P. mirabilis, P. sargassicus).
However, they all differ as described above.
Discussion
The physical features of Psednos rossi are unique in the
genus. The straight vertebral column and body are outside
the previous diagnosis of the genus, because all previously
known species are humpbacked owing to the curved spinal
column. Nevertheless, P. rossi clearly belongs in Psednos
rather than Paraliparis because it has the other generic
characters of Psednos (Chernova, 2001); particularly,
its sensory canal system and pores are of Psednos type,
having an interrupted infraorbital canal behind the eye.
We suggest that its remarkable body shape is an extreme
transformation of the usual Psednos body shape and is
associated with the change of the mouth from oblique and
of normal size to vertical and very large. In this process
the anterior movement of the bony elements of the jaws
greatly enlarges the branchial cavity.
The morphology of Psednos rossi invites speculation
about its ecology. The very large superior mouth with verti-
cal jaws, eyes located close to the dorsal contour of the head
and oriented to look forward and up, and straight body sug-
gest adaptation to feeding on detritus and animals (such as
copepods) above it in the water column. These adaptations,
similar to those of hatchetfishes (family Sternoptychidae),
are highly advantageous for a mesopelagic mode of life.
Sudden opening of the very large vertical lower jaw could
produce a strong orobranchial suction, simultaneously
bringing food into the mouth and thus saving energy for
this fish, which is probably a poor swimmer.
Work over the last several years has made it clear that
Psednos species exist at mesopelagic depths in the North
Atlantic, Indian, North Pacific, and South Pacific Oceans.
We confidently expect discovery of additional species from
meso- and bathypelagic waters.
Acknowledgments
We wish to thank S. W. Ross, K. J. Sulak, and J. V.
Gartner Jr. for collecting the specimens, bringing them
to our attention, and loaning them to us for description.
Collections were supported by the U.S. Geological Survey,
State of North Carolina, North Carolina Coastal Reserve
Program, and the Duke/UNCW Oceanographic Consor-
tium. The figures are drawn by the senior author, who
was supported by the Russian Science Foundation Grants
02-04-48669 and 00-15-07794.
Literature cited
Andriashev, A. P.
1986. Review of the snailfish genus Paraliparis (Scorpaeni-
formes: Liparididae) of the Southern Ocean, 204 p. The-
ses Zoologicae 7, Koeltz Scientific Books, Koenigstein
1992. Morphological evidence for the validity of the anti-
tropical genus Psednos Barnard ( Scorpaeniformes, Lipari-
didae) with a description of a new species from the eastern
North Atlantic. UO, Tokyo 41:1-18.
1993. The validity of the genus Psednos Barnard (Scor-
paeniformes, Liparidae) and its antitropical distribution
area. Vopr. Ikhtiol. 33(11:5-15 [in Russian] J. Ichthyol.
33 (5):81-98. [English translation.]
Andriashev, A. P., and D. L. Stein.
1998. Review of the snailfish genus Careproctus (Lipari-
dae, Scorpaeniformes) in Antarctic and adjacent waters.
Contr. Sci. Nat. Hist Mus. Los Angeles Cty. 470:1-63.
250
Fishery Bulletin 102(2)
Chernova. N. V.
2001. A review of the genus Psednos (Pisces, Liparidae)
with description often new species from the North Atlantic
and southwestern Indian Ocean. Bull. Mus. Comp. Zool.
155:477-507.
Chernova, N. V., and D. L. Stein.
2002. Ten new species of Psednos (Pisces, Scorpaeni-
formes: Liparidae) from the Pacific and North Atlantic
Oceans. Copeia 2002 (3):755-778.
Stein, D. L.
1978. The genus Psednos a junior synonym of Paraliparis,
with a redescription of Paraliparis mierurus (Barnardi
(Scorpaeniformes: Liparidae). Matsya 4:5-10.
Stein, D. L., N. V. Chernova, and A. P. Andriashev.
2001. Snailfishes (Pisces: Liparidae) of Australia, includ-
ing descriptions of 30 new species. Rec. Austr. Mus.
53:341-406.
251
Abstract— Age and growth of sailfish
(Jstiophorus platypterus) in waters off
eastern Taiwan were examined from
counts of growth rings on cross sections
of the fourth spine of the first dorsal fin.
Length and weight data and the dorsal
fin spines were collected monthly at the
fishing port of Shinkang (southeast
of Taiwanl from July 1998 to August
1999. In total. 1166 dorsal fins were
collected, of which 1135 (97r£> (699
males and 436 females) were aged suc-
cessfully. Trends in the monthly mean
marginal increment ratio indicated
that growth rings are formed once a
year. Two methods were used to back-
calculate the length of presumed ages,
and growth was described by using
the standard von Bertalanffy growth
function and the Richards function.
The most reasonable and conserva-
tive description of growth assumes
that length-at-age follows the Rich-
ards function and that the relationship
between spine radius and lower jaw fork
length ( LJFL I follows a power function.
Growth differed significantly between
the sexes; females grew faster and
reached larger sizes than did males.
The maximum sizes in our sample were
232 cm LJFL for female and 221 cm
LJFL for male.
Age and growth of sailfish Ustiophorus platypterus)
in waters off eastern Taiwan
Wei-Chuan Chiang
Chi-Lu Sun
Su-Zan Yeh
Institute of Oceanography
National Taiwan University
No 1, Sec. 4, Roosevelt Road
Taipei, Taiwan 106
E-mail address (for C L. Sun, contact author): chilufiintu edu.tw
Wei-Cheng Su
Taiwan Fisheries Research Institute
No. 199, Ho-lh Road
Keelung, Taiwan 202
Manuscript approved for publication
22 December 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102(2): 251-263 (2004).
The sailfish (Istiophorus platypterus)
is distributed widely in the tropical
and temperate waters of the world's
oceans. According to data from longline
catches, sailfish are usually distributed
between 30°S and 50°N in the Pacific
Ocean, and highest densities are found
in the warm Kuroshio Current and
its subsidiary currents. This species
has a tendency to be found close to the
coast and near islands (Nakamura,
1985). During the 1990s the annual
landings of sailfish off Taiwan ranged
between 600 and 2000 metric tons, of
which approximately 54% came from
waters off Taitung (eastern Taiwan).
Sailfish are seasonally abundant from
April to October (peak abundance from
May to July) and contribute substan-
tially to the economic importance of
the eastern coast of Taiwan where this
species is taken primarily by drift gill
nets, although they are also caught by
set nets, harpoons, and as incidental
bycatch in inshore longline fisheries.
Age and growth of sailfish caught
in recreational fisheries in the Atlan-
tic Ocean have been studied by using
various methods, including length-
frequency analysis (de Sylva, 1957).
analysis of release-recapture data (Far-
ber1), and inferences from observed
marks on hard parts, such as spines
(Jolley, 1974, 1977; Hedgepeth and
Jolley, 1983) and otoliths (Radtke and
Dean, 1981; Radtke, 1983; Prince et al.,
1986). In contrast, very few attempts
have been made to age sailfish in the
Pacific Ocean. Koto and Kodama ( 1962 )
estimated the growth of sailfish caught
with longlines from 1952 to 1955 in the
East China Sea using length-frequency
analysis, and Alvarado-Castillo and Fe-
lix-Uraga (1996, 1998) used the fourth
spine of the first dorsal fin to estimate
age and growth of sailfish caught from
1989 to 1991 in the recreational fishery
off Mexico. However, western Pacific
sailfish have not been aged with calci-
fied structures in any previous study.
The aging of fishes, and consequently
the determination of their growth and
mortality rates, is an integral compo-
nent of modern fisheries science (Paul.
1992). Mortality and growth rates pro-
vide quantitative information on fish
stocks and are needed for stock assess-
ment methods such as yield-per-recruit
and cohort analysis (Powers. 1983).
The objectives of this study were to
estimate age and growth of sailfish by
counting growth rings on cross sections
of the fourth spine of the first dorsal fin
and to determine which of the Richards
function and the standard von Berta-
lanffy growth function best represents
growth of sailfish in waters off eastern
1 Farber, M.I. 1981. Analysis of Atlantic
billfish tagging data: 1954-1980 Unpubl.
manuscr. ICCAT workshop on billfish,
June 1981. Southeast Fisheries Center
Miami Laboratory. National Marine Fish-
eries Service, NOAA, 75 Virginia Beach
Drive, Miami, FL 33149.
252
Fishery Bulletin 102(2)
120
125
130
135
140 E
Figure 1
Fishing grounds of the gillnet (cross lines) and longline (oblique lines) fish-
ing boats based at Shinkang fishing port.
Taiwan. This information could be used to determine the
age composition of the catch and to assess the status of
sailfish in these waters by using yield-per-recruit or se-
quential population analysis techniques.
Materials and methods
Materials
Data on total length (TL), eye fork length (EFL), lower
jaw fork length (LJFL) (in cm), round weight (RW) (in kg)
and the first dorsal fins of male and female sailfish were
collected monthly at the fishing port of Shinkang (Fig. 1)
from July 1998 to August 1999. In total, 304 TLs, 1166
LJFLs, 1166 RWs, and 1166 dorsal fins were collected.
The dorsal fins were kept in cold storage before being
boiled to remove surrounding tissue and to separate the
fourth spines. Three cross sections (thickness 0.75 mm)
were taken successively along the length of each spine
with a low-speed "ISOMET" saw (model no. 11-1280) and
diamond wafering blades, at a location equivalent to 1/2 of
the maximum width of the condyle base measured above
the line of maximum condyle width (Fig. 2A) (Ehrhardt
et al., 1996; Sun et al., 2001, 2002). The sections were
immersed in 95'/J ethanol for several minutes for cleaning,
placed on disposable paper to air dry, and then stored in a
labeled plastic case for later reading. Spine sections were
examined with a binocular dissecting microscope (model:
Leica-MZ6) under transmitted light at zoom magnifica-
tions of 10-20x depending on the sizes of the sections. The
most visible one of these three sections was read twice,
approximately one month apart. If the two ring counts
differed, the section was read again, and if the third ring
count differed from the previous two ring counts, the spine
was considered unreadable and discarded. The precision
of reading was evaluated by using average percent error
(APE) (Beamish and Fournier, 1981; Campana, 2001) and
coefficient of variation (CV) (Campana, 2001) statistics.
Images of the cross sections were captured by using the
Image-Pro Image analysis software package (Media Cy-
bernetics, Silver Spring MD, 1997) in combination with a
dissecting microscope equipped with a charged coupled de-
vice (CCD) camera (model: Toshiba IK-630) and a Pentium
II computer equipped with a 640x480 pixel frame grab
card and a high-resolution (800x600 pixel) monitor.
The distance from the center of the spine section to the
outer edge of each growth ring was measured in microns
with the Image-Pro software package after calibration
against an optical micrometer. The center of the spine
Chiang et al.: Age and growth of Istiophorus platypterus in waters off eastern Taiwan
253
SPINE
SHAFT
VASCULARIZED
CORE
SECTION
AREA
0.75 MM
CONDYLE
BASE
CROSS SECTION
Figure 2
Schematic diagram of the fourth dorsal spine of sailfish [I. platypterus) and the
location of the cross section (A), and a cross section showing the measurements
taken for age determination of sailfish (B). W= maximum width of condyle base, R
= radius of spine, r, = radius of ring i, d = diameter of spine, dl = diameter of ring i.
The vascularized core and growth rings (1, 2, 3, 4, 5) are also shown.
section was estimated according to the methods of Cayre
and Diouf (1983) (Fig. 2B). The distances (d,l were then
converted into radii (r,0 by using the equation (Megalofo-
nou, 2000; Sun et al., 2001):
r; = d: - W/2),
where ri
d
radius of the ring i;
distance from the outside edge of ring i to the
opposite edge of the cross section; and
d = diameter of the spine.
False growth rings were defined according to criteria
of Berkeley and Houde (1983), Tserpes and Tsimenides
( 1995 ), and Ehrhardt et al. ( 1996 ).
core of the spine. The number of early but missing growth
rings was therefore estimated by the replacement method
applied to Pacific blue marlin (Makaira nigricatis)by Hill et
al. (1989). This method involved first compiling ring radii
statistics from younger specimens that had at least the first
or second ring visible. Radii of the first four visible rings
from samples that had missing early rings were then com-
pared with the radii for these younger specimens. When
the radii of at least two successive rings of the first four
visible rings each fitted well within one standard deviation
from the mean radii of each of two or more rings from the
data compiled from the younger specimens, the number of
missing rings was computed as the difference between the
ring counts for the matched radii compiled from younger
specimens and those for the specimen of interest.
Accounting for missing early rings
The first several growth rings of the larger specimens may
be obscured because of the large size of the vascularized
Validation
The marginal increment ratio (MIR), which was used
to validate the rings as annuli, was estimated for each
254
Fishery Bulletin 102(2)
specimen by using the following equation (Hayashi, 1976.
Prince et al., 1988; Sun et al., 2002):
MIR = {R-rn)l{rn-rn_1),
where R = spine radius; and
rn and rnl = radius of rings n and re— 1.
The mean MIR and its standard error were computed
for each month by sex for all ages combined, and also for
the ages 1-5 and 6-11 for males and 1-5 and 6-12 for
females.
Growth estimation
Growth for males and females was estimated by back-cal-
culation of lengths at presumed ages. Two methods were
used. Method 1 was based on the assumption that the rela-
tionship between spine radius (R) and LJFL (L) is linear,
i.e., L=a1+61i? (Berkeley and Houde, 1983; Sun etal, 2002),
whereas method 2 was based on the assumption that this
relationship is a power function, i.e., L=a0Rh- (Ehrhardt,
1992; Sun et al., 2002). The parameters of the relationships
were estimated by maximum likelihood, assuming log-nor-
mally distributed errors. Akaike's information criterion
(AIC, Akaike, 1969) was used to select which of the linear
and power functions best represented the data:
AIC = -21nL + 2p,
where InL = logarithm of likelihood function evaluated
at the maximum likelihood estimates for the
model parameters, and
p = number of model parameters.
The equations used to back-calculate the lengths at
presumed ages were
where L, = the mean LJFL at age t;
Lx = the asymptotic length;
o
the hypothetical age at length zero;
M/? <L_a,)
h,
5-] L
R)
linear relationship
power relationship
where Ln = LJFL when ring n was formed;
L = LJFL at time of capture; and
rn = radius of ring n.
The standard von Bertalanffy growth function (stan-
dard VB) (von Bertalanffy. 1938) and the Richards func-
tion (Richards, 1959) were then fitted to the mean back-
calculated male and female lengths-at-age from methods
1 and 2, assuming additive error.
Standard VB:
L,=L (l-c'"" ■»),
Richards function:
L(=L.(l-e-K" '"•)''"' ,
k and A' = the growth coefficients; and
m = the fourth growth-equation parameter.
An analysis of residual sum of squares lARSS) was used to
test whether the growth curves for the two sexes were dif-
ferent (Chen et al., 1992; Tserpes and Tsimenides. 1995;
Sun et al., 2001 ), and the log-likelihood ratio test was used
to determine whether the Richards function provided a
statistically superior fit to the data than the length-at-age
standard VB growth function.
Results
Of the 1166 dorsal spines sampled, 1135 (97%) (699 males
and 436 females) were read successfully. The average per-
cent error (APE) was 6.31% (5.91% for males and 6.93% for
females) and the coefficient of variation (CV) was 8.93%
(8.36% for males and 9.81% for females). Of the 31 spines
that could not be read, 22 were considered unreadable
because the existence of multiple rings made the identifi-
cation of annuli difficult or resulted in aging discrepancies
between readings, and the remaining nine spines were
unreadable because of abnormal growth.
The length-frequency and weight -frequency distribu-
tions for the 1166 individuals are shown in Figure 3.
These individuals ranged from 78 to 221 cm LJFL
(mean=177.62, SD = 16.13, «=720l or 1 to 49 kg RW
(mean=22.13, SD = 5.68) for the males and from 80 to 232
cm LJFL (mean=179.96, SD=17.90, n = 446) or 2 to 58 kg
RW (mean=23.65, SD=7.34) for the females. The females
were significantly larger than the males (r-test, P<0.05).
Table 1 summarizes the relationships between EFL and
LJFL and TL, and that between LJFL and weight. The
latter relationship differed significantly between males
and females (analysis of covariance; P<0.05).
At least the first or second ring in 417 (60%) of male
spines and 300 1 69%) of female spines was visible. The
ring radii statistics by sex is summarized in Figure 4. All
other specimens were assigned inner rings and final age
estimates based upon these data. The mean ring radii by-
age group, for males and females, after correction for miss-
ing early rings, are listed in Table 2. The maximum age
of the sampled sailfish, after correction for missing early
rings, was 11 years for males and 12 years for females.
The maximum ages before correction were 8 years for
both sexes.
The monthly means of the marginal increment ratio
(MIR) for males of all ages during May-August were high
(-0.72) but declined markedly thereafter and reached a
minimum of 0.46 in November (Fig. 5). Similarly, the MIR
for females dropped from 0.71 in September to a minimum
of 0.47 in November (Fig. 6). The monthly means of MIR
did not differ significantly from each other over the period
December-March (ANOVA, P^O.86, P9=0.96). However,
the monthly means of MIR from April through August for
males and from April through September for females were
Chiang et al.: Age and growth of Istiophorus p/atypterus in waters off eastern Taiwan
255
100 -i
80
60
40
20 -
□ Male (n=720)
■ Female (n=446)
p pH , M ^
L*^
75 85 95 105 115 125 135 145 155 165 175 185 195 205 215 225 235
Lower jaw fork length (cm)
120
90
60
30
r? f P ^
2 16 20 24 28 32 36 40 44 48 52 56 60
Round weight (kg)
Figure 3
The size-frequency distributions by 5-cm intervals (upper figure) and by
2-kg intervals (lower figure) for male and female sailfish (/. platypterus)
collected from the waters off eastern Taiwan.
significantly higher than those from September through
November for males U-test, P<0.001) and from October
through November for females (f-test, P<0.001). Also, the
mean MIR in November was significantly lower than that
in December (f-tests, PCT<0.05, P9<0.05). The trends in the
monthly means of MIR when the data were split into ages
1-5 and 6+ were similar to those for all ages combined.
The results in Figures 5 and 6 indicate that one growth
ring is formed each year, most likely from September to
November for males and from October to November for
females.
Figure 7 shows the sex-specific relationships between
LJFL and spine radius based on method 1 (linear regres-
sion) and method 2 (power function). The relationships for
males and females are significantly different (method 1:
= 56.07, P<0.01; method 2: F,
- = 59.93, P<0.01).
According to AIC, the power function provides a better fit
to the data (4AIC = 38.57 and 30.96 for males and females,
respectively). Therefore, the most parsimonious repre-
sentation of the data is the power function with separate
parameters for males and females.
The mean back-calculated lengths-at-age obtained from
methods 1 and 2 are listed in Table 3. After the first year
of life, the growth rates of both sexes slow appreciably.
However, females still grow faster and consequently reach
larger sizes than males. The standard VB and the Rich-
ards function for males and females are shown in Figure 8
and the corresponding parameter estimates are listed in
Table 4. The growth curves for males differ significantly
from those for females (F=99.86 P<0.05 and P=107.38
P<0.05 for the standard VB curve [methods 1 and 2], and
P=144.01 P<0.05 and F=48.43 P<0.05 for the Richards
function [methods 1 and 2]). The Richards function pro-
vides a statistically superior fit to the data (log-likelihood
ratio test; P<0.001) when method 2 is used to back-calcu-
late length-at-age but not when method 1 is used.
256
Fishery Bulletin 102(2)
Table 1
Linear relationships (Y=a+bX) among total length (TL, cm), lower jaw fork length
and the log-linear length-weight (round weight, RW, kg) relationships for sailfish
parentheses are standard errors.
(LJFL, cml and eye fork length (EFL, cm),
in the waters off eastern Taiwan. Values in
Y
X
a
b
n
LJFL range (cm) RW range ikg) r-
Male
TL
LJFL
19.660
(6.334)
1.205
(0.037)
184
78-211 0.854
TL
EFL
24.782
(6.176)
1.364
(0.042)
184
78-211 0.854
EFL
LJFL
-5.196
(0.772)
0.893
10.004)
720
78-221 0.983
log10RW
log10LJFL
-5.381
(0.080)
2.985
(0.036)
720
78-221 1-46 0.906
Female
TL
LJFL
6.728
(9.351)
1.286
(0.055)
120
109-210 0.824
TL
EFL
6.754
(9.505)
1.489
(0.064)
120
109-210 0.820
EFL
LJFL
-2.209
(0.802)
0.876
(0.004
446
80-232 0.989
log]0RW
log10LJFL
-5.338
(0.103)
2.970
(0.0461
446
80-232 2-58 0.905
Discussion
Age estimate determined from dorsal-fin spines
Dorsal-fin spines appear to be useful for aging sailfish.
They are easily sampled without reducing the economic
value of the fish and can also be read easily (the growth
rings stand out clearly). In contrast, scales cannot be
used to age sailfish because scale deposition patterns
change as sailfish age (Nakumura, 1985), and otoliths are
extremely small and fragile and are often difficult to locate
(Radtke, 1983). Reading otoliths is more time consuming
and expensive than reading spines and spines can also
be easily stored for future re-examination (Compean-
Jimenez and Bard, 1983; Sun et al„ 2001, 2002).
The problems associated with the fin-spine aging meth-
od used in this study were the possible existence of false
rings and the presence of the vascularized core which can
obscure early growth rings in larger fish. These problems
were also noted by Berkeley and Houde (1983), Hedge-
pet h and Jolley (1983), Tserpes and Tsimenides (1995),
Megalofonou (2000), and Sun et al. (2001, 2002). However,
Tserpes and Tsimenides (1995) and Megalofonou (2000)
noted that experienced readers can overcome the problem
of multiple rings by determining whether the rings are
continuous around the circumference of the entire spine
section and by judging their distance from the preceding
and following rings. We observed false rings in spines for
all age classes larger than age two, which we read with-
out problem by using these guidelines. The missing early
growth rings in larger specimens were accounted for by
compiling ring radii statistics for younger specimens for
which at least the first or second ring was visible and by
comparing the radii of the first several visible rings of the
specimens that had missing early rings to the mean radii
and standard deviations of the compiled data. Similar ap-
proaches for solving the problem of missing rings have also
been used for Pacific blue marlin (Hill et al., 1989).
Marginal increment ratio (MIR) analysis is the most
commonly applied method for age validation (Campana,
2001). The MIR analysis conducted for sailfish suggested
that one growth ring is formed each year from September
to November for males and from October to November for
females. Spawning for sailfish in the waters east of Taiwan
lasts from April through September (Chiang and Sun-).
This is exactly the period when growth is low, as indicated
by the narrow and translucent rings. Similar findings
have been reported for skipjack tunatAntoine et al., 1983),
swordfish (Ehrhardt, 1992; Tserpes and Tsimenides,
1995), and bigeye tuna (Sun et al., 2001). Although the
timing of annulus formation coincides with spawning sea-
son for sailfish in the eastern Taiwan, annulus deposition
- Chiang, W. C, and C. L. Sun. 2000. Sexual maturity and sex
ratio of sailfish {Istiophorus platypterus) in the eastern Taiwan
waters. Abstracts of contributions presented at the 2000
annual meeting of the Fisheries Society of Taiwan, Keelung.
Taiwan, 16-17 December 2000, 15 p. The Fisheries Society of
Taiwan, 199 Hou-Ih Road, Keelung, 202 Taiwan.
Chiang et al.: Age and growth of Istiophorus platypterus in waters off eastern Taiwan
257
123456789
Ring number
Figure 4
Mean (±1 SD) ring radius for male and female sailfish (/. platypterus) collected
from the waters off eastern Taiwan that had at least the first or second ring
present. The numbers above the vertical bars are the sample sizes.
may also be related to sailfish migration and environmen-
tal factors, as suggested by Sun et al. (2002) for swordfish.
The MIR analysis provides only a partial age validation;
complete validation requires either mark-recapture data
or the study of known-age fish (Beamish and McFarlane.
1983; Prince et al., 1995; Tserpes and Tsimenides, 1995;
Sun et al., 2001, 2002).
Selection of a growth curve
Female sailfish are typically larger for similar ages in
males and grow faster than males, and the length-weight
relationship differs significantly between the sexes.
Similar results have been reported for east Pacific Ocean
sailfish (Hernandez-Herrera and Ramirez-Rodriguez,
1998 ). Indian Ocean sailfish (Williams, 1970 ) and Atlantic
Ocean sailfish (Beardsley et al., 1975; Jolley. 1974, 1977;
Hedgepeth and Jolley, 1983).
The Richards function appears to fit the data better
than the standard VB curve (Fig. 8) and provides a more
realistic description of growth for animals of age 0. The
standard VB curve is commonly used to describe asymp-
totic growth in fish but did not fit the back-calculated
lengths for fish younger than three (Table 4, Fig. 8).
Further discussion of growth curves will likely focus
on method 2 (i.e., a power function relationship between
spine radius and LJFL) because it provides a better fit to
the data than method 1. Ehrhardt (1992), Ehrhardt et al.
258
Fishery Bulletin 102(2)
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Chiang et al.: Age and growth of Ist/ophorus p/atypterus in waters off eastern Taiwan
259
09 -
Male All ages combined
0.8 -
0.7 -
06 -
f
43 117 158
3 18 Ti^A
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67 f
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JFMAMJJASOND
Month
Figure 5
Monthly means of marginal increment ratio for male sailfish (/. platy-
pterus) in the waters off eastern Taiwan for all ages combined and for
age classes 1-5 and 6-11, respectively. Vertical bars are ±1 SE; numbers
above the vertical bars are sample sizes.
Table 3
Mean back-calculated lower jaw fork lengths at age for sailfish in the waters off eastern Taiwan.
Back-calculated length (cm)
Method 1
Method 2
Age (yr)
Method 1
Method 2
Age lyr)
Male
Female
Male
Female
Male
Female
Male
Female
1
108.53
113.41
99.90
103.51
7
181.11
185.36
181.86
186.09
2
125.70
130.79
121.79
126.32
8
188.99
192.82
189.84
193.67
3
138.82
143.90
137.27
141.96
9
194.98
200.60
196.59
201.47
4
150.80
156.02
150.56
155.54
10
200.78
207.85
201.74
208.81
5
161.78
166.22
162.12
166.38
11
208.05
213.29
209.14
214.66
6
171.63
176.60
172.18
177.12
12
217.15
219.05
260
Fishery Bulletin 102(2)
0.9 I
Female
All ages combined
0.8 ■
0.7 -
0.6 •
0.5 •
2
J. 2
2
20
52
93
116
88 25
1\ m
\ 19
NL 10 /i
04 -
03 -
1
— i — i — i — i — i
0.9
08
0.7 -
0.6
05 -
0.4 -
0.3
09
08
07
06
05
0.4
03
02
40 Ages 1-5
- 1 r~
—l 1 1 1
Ages 6-12
— i 1 1 1 1-
JFMAMJJASOND
Month
Figure 6
Monthly means of marginal increment ratio for the female sailfish (/.
platypterus) in the waters off eastern Taiwan for all ages combined and
for age classes 1-5 and 6-12, respectively. Vertical bars are ±1 SE; num-
bers above the vertical bars are sample sizes.
(1996), and Sun et al. (2002) favored method 2 because
they believed it to be more biologically realistic. When
the back-calculated lengths-at-age are generated with
this method the Richards function provides a statistically
superior fit to the length-at-age data. Therefore, the pa-
rameter estimates for the Richards function with method 2
listed in Table 4 are recommended as the most appropriate
for calculating the age composition of sailfish in the waters
to the east of Taiwan. It is perhaps worth noting that the
tu values estimated for the Richards function with method
2 are much closer to zero than those estimated for the
Richards function with method 1.
Comparison with previous studies
Figure 9 compares the age-length relationships of this
paper with those for Atlantic (de Sylva, 1957; Hedgepeth
and Jolley, 1983; Farber1) and Pacific sailfish (Koto and
Kodama, 1962; Alvarado-Castillo and Felix-Uraga. 1998).
De Sylva ( 1957 ) and Koto and Kodama ( 1962 1 used length-
frequency analysis and concluded that sailfish are a very
fast growing and short-lived species. However, they likely
underestimated age and overestimated growth rate when
their results are compared with those of other more recent
studies.
The maximum ages found in this study (11 years for
males and 12 years for females) are close to the maximum
longevity of at least 13 years proposed by Prince et al.
(1986) based on tagging data. Farber1 analyzed Atlantic
billfish tagging data and suggested that the asymptotic
size was essentially reached by age 3 (Hedgepeth and Jol-
ley, 1983). whereas the present study found a more gradual
increase in length with age. in common with the results of
Hedgepeth and Jolley (1983).
Chiang et al.: Age and growth of Istiophorus platypterus in waters off eastern Taiwan
261
250 -I
Male
200 -
p
aij*||»|Pe§>o'
ylliliP^0 *
150 ■
0o >^P^
_^l°J -
100 ■
° n = 699
o -- LJFL =64.825 + 30.471 R
r2 = 0.704
-J 50 ■
ll
-J
— LJFL = 79.833 R06'2
r2 = 0.720
length
o
i i i i i i
1 25°-
Female
S
TO,
S 200 -
o
iJ0^^
150 -
<0^
100 -
o
0
n =436
o -- LJFL =70.31 2 + 30.093 R
r = 0.731
50 -
— LJFL =83.461 R0596
r2 = 0.750
0 12 3 4 5 6
Spine radius (R, mm)
Figure 7
Relationship between lower jaw fork length and spine radius for
male and female sailfish (/. platypterus) in the waters off eastern
Taiwan.
Table 4
Parameter estimates and standard errors (in
parenthesis) for the standai
•d von Berta
anffy growth function and the Richards
function for sailfish in the waters off eastern Taiwan.
Standard von Bertalan
ffy growth
function
Richards
function
Method 1
Method 2
Method 1
Method 2
Parameter Male
Female
Male
Female
Male
Female
Male
Female
L, 252.6
261.4
240.4
250.3
271.8
280.4
294.0
343.8
(3.652)
(3.397)
(3.794)
(4.278)
(22.713)
(19.882)
(29.607)
(47.921)
k 0.115
0.110
0.145
0.138
(0.005)
(0.004)
(0.008)
(0.008)
t0 -3.916
-4.207
-2.781
-2.990
-2.473
-2.608
-0.704
-0.468
(0.143)
(0.147)
(0.154)
(0.186)
(0.931)
(0.896)
(0.279)
(0.186)
A'
0.051
0.049
0.023
0.011
(0.034)
(0.030)
(0.013)
(0.007)
m
-0.551
-0.578
-1.288
-1.639
(0.472)
(0.436)
(0.308)
(0.243)
262
Fishery Bulletin 102(2)
250
H 200
150-
100-
50-
Male
Standard VB - method 1
Standard VB - method 2
Richards function - method 1
Richards function - method 2
zsu-
Female
o
200-
i L-4^**^^
150-
100-
4/
Standard VB- method 1
- - - - Standard VB - method 2
50-
■' **/ /
Richards function • method 1
f |
Richards function - method 2
n -
1
-5 -4 -3 -2 -1 0
1 2 3 4 5 6 7 8 9 10 11 12 -5-4-3-2-1
Age (year)
9 10 11 12
Figure 8
Observed and back-calculated length-at-age and standard von Bertalanffy and Richards function model-predicted growth curves
for male and female sailfish <■!. platypterus) in the waters off eastern Taiwan.
300 -i
250
200
150
100 -
50 -
-de Sylva (1957) -sexes combined'
- Koto and Kodama (1 962) - sexes combined'
- Farber (1981) - sexes combined*
- Hedgepeth and Jolley (1 983) - male"
- Hedgepeth and Jolley (1 983) - female'
- Alvarado-C and Felix-U. (1998) - sexes combined
- Present study - male
- Present study - female
6 7 8
Age (year)
10
12 13
Figure 9
A comparison of the growth curves for sailfish (/. platypterus) esti
by different authors. I ■ Data from Table 1 of Hedgepeth and Jolley
mated
1983.1
use in stock assessments of the sailfish popu-
lation in the western Pacific Ocean.
Acknowledgments
The authors express sincere gratitude to
Andre Punt, School of Aquatic and Fishery
Sciences. University of Washington, for his
valuable comments and comprehensive edit-
ing of the manuscript. This study was in
part supported financially by the "Fisheries
Agency, Council of Agriculture, Taiwan,"
through grant 91AS-2.5.1-FK7) to Chi-Lu
Sun.
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264
Abstract— A density prediction model
for juvenile brown shrimp (Farfan-
tepenaeus aztecus) was developed by
using three bottom types, five salinity
zones, and four seasons to quantify pat-
terns of habitat use in Galveston Bay,
Texas. Sixteen years of quantitative
density data were used. Bottom types
were vegetated marsh edge, submerged
aquatic vegetation, and shallow non-
vegetated bottom. Multiple regression
was used to develop density estimates,
and the resultant formula was then
coupled with a geographical informa-
tion system (GIS) to provide a spatial
mosaic (map) of predicted habitat use.
Results indicated that juvenile brown
shrimp (<100 mm) selected vegetated
habitats in salinities of 15-25 ppt and
that seagrasses were selected over
marsh edge where they co-occurred.
Our results provide a spatially resolved
estimate of high-density areas that will
help designate essential fish habitat
(EFH) in Galveston Bay. In addition,
using this modeling technique, we were
able to provide an estimate of the over-
all population of juvenile brown shrimp
(<100 mm) in shallow water habitats
within the bay of approximately 1.3
billion. Furthermore, the geographic
range of the model was assessed by
plotting observed (actual) versus
expected (model) brown shrimp densi-
ties in three other Texas bays. Similar
habitat-use patterns were observed
in all three bays — each having a coef-
ficient of determination >0.50. These
results indicate that this model may
have a broader geographic application
and is a plausible approach in refining
current EFH designations for all Gulf
of Mexico estuaries with similar geo-
morphological and hydrological char-
acteristics.
A habitat-use model to determine essential
fish habitat for juvenile brown shrimp
(Farfantepenaeus aztecus) in Galveston Bay, Texas
Randall D. Clark
John D. Christensen
Mark E. Monaco
Biogeography Program
Center for Coastal Monitoring and Assessment
National Center for Coastal Ocean Science
National Ocean Service. NOAA
Silver Spring, Maryland 20910
E-mail address (For R. D Clark) Randy Clarkfflnoaa gov
Philip A. Caldwell
Geoffrey A. Matthews
Thomas J. Minello
Fishery Ecology Branch
Galveston Southeast Fisheries Science Center Laboratory
National Marine Fisheries Service, NOAA
Galveston, Texas 77550
Manuscript approved for publication
22 December 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:264-277 (200 1 1
Shallow estuarine habitats, whose com-
plexity promotes survival and growth,
are used by many young fish and macro-
invertebrate species (Boesch and
Turner, 1984). A complete understand-
ing of how these habitats sustain spe-
cies productivity is unknown and has
become a focal point of federal fishery
management programs. The National
Marine Fisheries Service (NMFS)
has developed guidelines to identify
essential fish habitat (EFH) for all
federally managed species based on
four levels of available information
that encompass the ecological linkages
between habitats and fishery produc-
tion. Examination of habitat-use pat-
terns (habitat-related densities) are
needed to determine which habitats
are likely to be most essential. These
patterns are measurable and can be
reasonable indicators of habitat value.
Relative habitat values have been esti-
mated by comparing animal densities
under the assumption that high densi-
ties reflect greater habitat quality and
preferred habitat (Pearcy and Myers,
1974; USFWS, 1981; Zimmerman and
Minello, 1984; Sogard and Able, 1991;
Baltzetal., 1993).
Considerable bottom-type variation
exists in northern Gulf of Mexico estu-
aries, including intertidal marsh, sub-
merged aquatic vegetation, oyster reef,
mangroves, tidal mudflats, and sub-
tidal bay bottom. Within each of these
habitats, environmental and structural
gradients may affect the functional
role or importance of these habitats
for particular species. To understand
these relationships, fisheries indepen-
dent monitoring (FIM) data are needed
to determine species-habitat affini-
ties that provide evidence that not all
habitats are of equal importance for the
maintenance of a population (Monaco
et al., 1998; Minello 1999; Beck et al.,
2001). Habitat affinities may change
with spatial and temporal fluctuations
of environmental variables, such as sa-
linity and temperature (Copeland and
Bechtel, 1974; Baltz et al., 1998).
In this study we developed predictive
models that estimate brown shrimp
{Farfantepenaeus aztecus, formerly
Penaeus aztecus [see Perez-Farfante
and Kensley, 1997]) habitat-use pat-
terns and interactions as a function
of density-independent processes in
Galveston Bay, Texas. Previous com-
Clark et al.: A habitat-use model for juvenile Farfantepenaeus aztecus In Galveston Bay
265
29 5° N
29° N
North
A
■i-
%&*%
y
Trinity
Bay
C^l Galveston ^
Bay "^*^-
East
<_k ■:■ •
i.
j?
v. ■ '
.- '■
... r' v .
\.
) 7^
' i j&
m
vf-
*-\Christmas
Kilometers
i 1
Bay
0 10
95 W
Figure 1
Map of Galveston Bay, Texas.
94.5° W
parisons of brown shrimp densities among different bot-
tom types in Louisiana and Texas estuaries have been
conducted within limited temporal and spatial scales
(Peterson and Turner, 1994; Zimmerman et al., 1984; Zim-
merman et al., 1990b; Rozas and Minello, 1998; Minello,
1999).
Our work expands upon these studies by developing a
multivariate bottom-type use and environmental model
incorporated into a geographic information system (GISi
that provides a spatial assessment of habitat use. In ad-
dition, the model is designed to be transferable to other
northern Gulf of Mexico estuaries and thus would allow
fishery managers to identify the relative importance of
habitat types for population maintenance and recruitment
into the fishery.
Materials and methods
Geographic setting
The Galveston Bay complex (Fig. 1) encompasses approxi-
mately 2020 km2 and is one of the largest estuaries in
the northern Gulf of Mexico (NOAA, 1989). Comprising
several major embayments, including Trinity, Galveston,
East, and West bays, the complex contains many smaller
interconnecting subbays, rivers, streams, tidal creeks,
wetlands, reefs, and tidal flats around its periphery.
The bay bottom is mostly flat and shallow (mean depth
is approximately 2 m) and has slightly elevated oyster
reefs, elevated dredge material areas, river channels, and
deeper dredged navigation channels.
Data collection
Sixteen years (1982-97) of brown shrimp density data
were analyzed to quantify areas of potential EFH. A total
of 46,080 brown shrimp were captured during this time
period with a mean total length of 27.5 mm (Fig. 2). Data
from published studies by Czapla (1991), Minello et al.
( 1991), Minello and Zimmerman ( 1992), Minello and Webb
( 1997 ), Rozas and Minello ( 1998 ), Zimmerman et al. (1984,
1989, 1990a, 1990b), Zimmerman and Minello (1984),
and various unpublished sources from the Galveston
Laboratory of the National Marine Fisheries Service were
combined to comprise a comprehensive density database of
associated bottom-type and environmental data that would
support model development and GIS analyses. All samples
were collected by using a drop trap sampler, described in
Zimmerman et al. (1984), which employs large cylinders
( 1.0 or 2.6 m2 area) released from a boom affixed to a boat
to entrap organisms. This quantitative technique samples
fishes and macro-invertebrates in highly structured shal-
low-water habitats such as salt marshes, seagrass beds,
and oyster reefs where the efficiency of conventional trawl
and bag-seine gear is diminished.
266
Fishery Bulletin 102(2)
Habitat mapping
The underlying spatial framework for incorporating
model predictions into the GIS consisted of six maps:
four salinity periods, one bathymetric map, and one
map defining bottom-type distribution. All GIS maps
were developed in Universal Transverse Mercator
projection, UTM, datum-1983, zone-15, using ArcView
3.1 (Redlands, CA) software. Each map consisted of
10 x 10 m grid cells where each cell contained pertinent
salinity, depth, or bottom-type information.
Salinity maps were developed from depth-aver-
aged salinity models by using historical Galveston
Bay data collected during 1979-90 (Orlando et al.,
1993). Four salinity periods were identified to rep-
resent typical salinity conditions under average sea-
sonal freshwater inflow: low (March-June), increas-
ing (July), high (August-October), and decreasing
(November-February). Five isohalines were developed to
display spatial salinity distribution (Christensen et al.1):
0-0.5, 0.51-5, 5.1-15, 15.1-25, and >25 parts per thou-
sand (ppt) (Fig. 3).
Bottom types from the drop sample database were di-
vided into three categories:
Marsh edge (ME)
Submerged
aquatic
vegetation (SAV)
Shallow non-
vegetated
bottom (SNB)
intertidal marsh within 5 meters of
open water habitat. This category
consisted primarily of saltmarsh cord
grass (Spartina alterniflora), and
smaller proportions of salt meadow-
grass {Spartina patens), black needle-
rush {Juncus roemerianus), salt grass
(Distichlis spicata), bullrushes iScir-
pus spp.), and cattails (Typha spp.);
consisted primarily of shoalgrass
{Halodule wrightii), wigeongrass
iRuppia maritima), and a sporadic
distribution of wild celery (Vallisneria
americana);
generally restricted to waters less
than 1 meter deep, including creeks,
ponds, shoreline, and open bay habitat.
Density data for other bottom types were limited and were
not used in the analysis.
Wetland maps, used in the creation of the bottom type
map in the GIS, were obtained from the U.S. Fish and Wild-
life Service's national wetland inventory (NWI). The NWI
maps were obtained as vector files, created by digitizing
boundaries between wetland types from 1989 aerial photo-
graphs and classified by using the classification scheme of
Cowardin et al. ( 1979). Regularly flooded emergent vegeta-
tion and submerged aquatic vegetation distributions from
Christensen, J. D., T. A. Battista, M. E. Monaco, and C. J.
Klein. 1997. Habitat suitability modeling and GIS technol-
ogy to support habitat management: Pensacola Bay, Florida
Case Study, 58 p. NOAA/NOS Strategic Environmental
Assessments Division, Silver Spring, MD.
40 50 60 70
Total length (mm)
Figure 2
Total-length frequency distribution for juvenile brown shrimp
captured in drop traps within Galveston Bay (1982-971.
the NWI maps of Galveston Bay were chosen to represent
ME and SAV, respectively, from the drop sample database.
Nonvegetated open water areas with depths greater than
1 m were eliminated throughout the bay to reflect depth
range from the drop sample database. This elimination
was done by plotting approximately 400,000 depth sound-
ings obtained from the National Geophysical Data Center
(NGDC ), and a bathymetric grid map was developed in 1-m
contours with ArcView 3.1 (6 nearest neighbors, power=2).
The nonvegetated open water map from NWI was overlaid
with the bathymetric map and only those areas within the
1-m contour were extracted and added to the bottom-type
map (Fig. 4).
Two maps were used to plot (map) seasonal model
predictions, bottom type, and the respective salinity
period. The salinity maps did not completely correspond
temporally with seasons defined by cluster analysis of in
situ temperature recordings from the density database.
Salinity periods were chosen to correlate with temporal
seasons based on maximum monthly overlap to develop the
seasonal prediction maps: low salinity (spring); increas-
ing salinity (summer); high salinity (fall); and decreasing
salinity (winter).
The total area of Galveston Bay (2020 km2) was deter-
mined by combining the total areas for regularly flooded
emergent vegetation, irregularly flooded emergent vegeta-
tion, SAV, and open water classifications from NWI data.
The bottom-type map reflects the study area and totaled
565.6 km2 after excluding all areas >1 m in depth and with
irregularly flooded emergent vegetation: SNB = 476.2 km2.
ME = 84.9 km2, and SAV = 4.5 km2. Initially, NWI's SAV
classification totaled 5.7 km2, but the final SAV coverage
was reduced to 4.5 km2 based on SAV mapping by White
etal. (1993).
Regression modeling
ANOVA and Tukey-Kramer multiple means comparisons
were used to determine if mean density varied significantly
by bottom type, salinity zone, and season. Multiple regres-
sion with significant predictors was used to predict mean
log density. The model was then applied to the GIS maps
Clark et al.: A habitat-use model for juvenile Farfantepenaeus aztecus in Galveston Bay
267
Low salinity (April-June)
Increasing salinity (July)
&m
High salinity (August-October)
Decreasing salinity (November-March)
Salinity Zone (ppt)
□ 0-0.5 CZZI 0 51-5 CD 51"15 CZ] 15 1-25 H > 25
Figure 3
Galveston Bay seasonal salinity distribution maps.
to spatially display model predictions in each 10 x 10 m
cell. The resulting values for each cell (predicted mean log
density) were converted to numbers/m2 and reclassified
into 5 percentiles based on their resultant distribution:
0-20%, 21-40%, 41-60%, 61-80%, and 81-100%. All
statistical analyses were conducted with JMP statistical
software (SAS Institute, Cary, NO.
Due to difficulties in creating continuous salinity and
temperature contour maps in GIS, these variables were
classified as follows: salinity was classified by one of the
five isohaline zones described previously and analyzed as
such to determine its influence on brown shrimp distri-
bution; and water temperature was classified by season
determined by cluster analysis and analyzed to examine
possible temporal effects of brown shrimp distribution.
Spatial patterns were evaluated by comparing the pre-
dicted mean log density values with the observed mean
log density values from Galveston Bay drop samples. Addi-
tionally, the model's predictive performance was assessed
by comparing the predicted mean log density values with
observed mean log density values from samples collected
in Matagorda, Aransas, and San Antonio bays using the
same collection method. With this approach, the assump-
tion was made that brown shrimp modeled in Galveston
Bay respond similarly to the range of biotic and abiotic
factors in the other bay systems.
Drop sample data collected during July-September 1984
(/i=128), and April- June 1985 (re=144) from West Bay (ME,
SNB) and Christmas Bay (ME, SAV, and SNB) were used
to examine bottom-type preference or selectivity. Tukey-
Kramer multiple comparisons test was used to compare
log density patterns in areas where ME and SAV occurred
together and in areas where SAV was not present.
Results
Brown shrimp model
ANOVA and Tukey-Kramer pair-wise comparisons
showed significant differences in brown shrimp log density
between the three bottom types, five salinity zones, and
four seasons (Fig. 5). Multiple regression models were run
with these discreet variables (Mahon and Smith, 1989;
268
Fishery Bulletin 102(2)
"T .^
Nonvegetated bottom (SNB)
Marsh edge (ME)
Submerged aquatic vegetation (SAV)
Figure 4
Spatial distribution of Galveston Bay bottom types used in the multivariate
regression model.
Results of the least squares multiple
* = significant at P < 0.05.
regression model for
Table 1
predicting
seasonal brown
shrimp density in Galveston Bay, Texas.
Model fit
r2
Mean
Observations in)
Mean square error
0.73
0.47
47
0.20
Source
ANOVA
df
Sum of squares
Mean square
F ratio
Prob > F
Model
Error
Total
17
29
46
5.74
1.61
6.90
0.33
0.04
8.43
<0.0001*
Source
Effects
df
Sum of squares
F ratio
Prob > F
Season
Bottom type
Salinity zone
Bottom typex
Salinity zone
3
2
4
8
1.85
0.61
3.15
0.86
15.43
7.57
19.68
2.69
<0.0001*
0.0023*
<0.0001*
0.0242*
Krumgalz et al., 1992; Garrison, 1999) and we tested
for possible interactions between the variables. Only the
interaction between bottom type and salinity zone yielded
statistically significant results. ANOVA results for the
model including the bottom-type and salinity-zone interac-
tion term (Table 1) and variable coefficients (Table 2 (fitted
Clark et al.: A habitat-use model for juvenile Farfantepenaeus aztecus in Galveston Bay
269
Table 2
Variable coefficients (log +1) derived from brown shrimp multivariate regression model. ME
aquatic vegetation; SNB = shallow nonvegetated bottom.
marsh edge; SAV = submerged
y-intercept
Bottom type
Season
0.335
0.113 (ME)
0.043 (SAV)
-0.156 (SNB)
0.239 (spring)
0.165 (summer)
-0.045 (fall)
-0.359 (winter)
Salinity zone
Bottom type x salinity zone
-0.525
-0.147
0.079
0.286
0.307
(0-0.5)
(0.5-5)
(5-15)
(15-25)
(>25)
-0.104
-0.055
0.159
0.273
-0.396
0.123
-0.030
0.049
-0.018
-0.119
0.288
-0.168
-0.018
0.114
-0.096
(ME/0-0.5)
(SAV/0-0.5)
(SNB/0-0.5
(ME/0.5-5)
(SAV/0.5-5)
(SNB/0.5-5)
(ME/5-15)
(SAV/5-15)
(SNB/5-15)
(ME/15-25)
(SAV/15-25)
(SNB/15-25)
(ME/>25)
(SAV/>25)
(SNB/>25)
the data well (r2=0.73, n=47). Overall, density predictions
were highest in the spring, declined through summer and
fall, and reached the lowest values during winter (Fig. 6).
SNB density predictions were highest in the >25 ppt salin-
ity zone and declined as salinity declined in the estuary.
ME density predictions exhibited similar density predic-
tion trends; however, a smaller peak was observed in the
0.5-5 ppt salinity zone. This result may be an artifact of
two fall samples that exhibited high density within this
salinity zone. Density predictions within SAV were near
zero in the lower two salinity zones, peaked in the 15-25
ppt salinity zone, and slightly decreased in the >25 ppt
salinity zone.
Model prediction maps
For all seasons, highest density predictions corresponded
with ME and SAV bottom types within the region of the bay
with highest salinity — Christmas and West bays (Fig. 7).
Density predictions decreased within all bottom types as
salinity declined in the middle and upper regions of the
bay. Spring density predictions were the highest; maxi-
mum values were predicted within ME (6.14/m2) and SAV
(14.49/m2) located in Christmas and West bays (Fig. 7).
Density predictions steadily declined through the middle
bay and declined to 1/m2 or less within SAV and SNB in
the upper region of the bay (Trinity Bay) where salinities
were less than 5 ppt. Density predictions during summer,
fall, and winter were lower than those observed during the
spring but exhibited similar spatial trends — higher pre-
dictions within the high salinity vegetated bottom types,
and decreasing with decreasing salinity.
Model performance
Spatial patterns were assessed by plotting predicted mean
density values from the model and observed mean density
A 1"
K
08
*
0 6
0.4 ■
*
0.2 ■
/•2=0.16
P<0.0001
SAV ME SNB
Bottom type
B 08
*
>. 06
I 0.4-
*
3 0.2
r2=0.06 $
P<0.0001
0-0.5 0-5.5 5-15 15-25 >25
Salinity zone
c '■
0 8 -
0.6 -
*
*
04 -
*
02 ■
r2=0.13
P<0.0001
spring summer fall winter
Season
Figure 5
Analysis of variance and Tukey-Kramer pair-wise
comparisons of brown shrimp density between (A)
bottom type, (B) salinity zone and, (C) season. Mean
densities are represented by solid diamonds and lines
determine standard error. SAV = submerged aquatic
vegetation; ME = marsh edge; SNB = shallow non-
vegetated bottom.
270
Fishery Bulletin 102(2)
SNB
1.2
1
0.8
0.6
0.4
0.2
0
li ifll
spring summer fall winter
Salinity zone
|a 0-0.5 D 0.5-5 □ 5-15 G15-25B> 25 |
Figure 6
Seasonal density predictions for brown shrimp (F. aztecus) by bottom type and
salinity zone. ME = marsh edge; SAV = submerged aquatic vegetation; SNB =
shallow nonvegetated bottom.
values from drop sample data collected in Galveston Bay.
Regression analysis from this plot exhibited a strong posi-
tive relationship (r2=0.83, P<0.0001) between predicted
and observed density data (Fig. 8). This analysis was per-
formed to verify how the model represented the observed
density data.
Model performance and transferability were assessed
by regressing predicted mean density values from the
Galveston Bay model on observed mean density values
from drop sample data collected in Matagorda, San
Antonio, and Aransas bays (Fig. 9). Regression analy-
sis produced a positive relationship for the entire drop
sample data from these bays combined (r2=0.56) and in-
dividually: Matagorda — r2=0.54; San Antonio — r2=0.57;
and Aransas — r2 = 0.56. In Aransas and San Antonio
bays, brown shrimp densities were greatest during the
spring within the SAV bottom type and within salinities
>15 ppt. In Matagorda Bay, brown shrimp densities were
greatest in the spring within ME bottom types in waters
>15 ppt. No SAV samples were taken in this estuarine
system.
Use of bottom types
Results from spring (1985) and fall (1984) drop samples
within Christmas and West Bay (in lower Galveston Bay)
bottom types revealed significantly greater brown shrimp
densities in Christmas Bay SAV than adjacent ME and
SNB (P<0.0001). Brown shrimp densities in West Bay
ME were not significantly different from Christmas Bay
SAV but were significantly greater than densities within
adjacent SNB and Christmas Bay ME and SNB bottom
types (Fig. 10).
The model results were also used to roughly estimate
an overall population of approximately 1.3 billion juve-
nile brown shrimp in Galveston Bay during the spring
season, by multiplying predicted densities by bottom-type
area (Table 3). Total area of bottom types in Galveston
Bay were as follows: 4.5 km2 (SAV); 84.9 km2 of marsh
edge (ME); and 1627.2 km2 of nonvegetated bottom (29%
[476.2 km2] of the latter area was considered SNB). On
the basis of predicted densities in different salinity regimes,
we estimated that there would be 51.0 million shrimp
Clark et al.: A habitat-use model for juvenile Farfantepenaeus aztecus in Galveston Bay
271
spring
summer
winter
Predicted density (#/m2 )
m 0-0.12
0.13-1.51
1.52-2.72
2.73-5.46
■I 5.47-14.85
Figure 7
Seasonal spatial distribution maps of predicted densities for brown shrimp (F. aztecus).
in SAV and 858.7 million shrimp in SNB. We used marsh
edge densities to estimate 473.5 million shrimp in regu-
larly flooded vegetation or about 55,700 shrimp per hectare
of this habitat type.
Discussion
Various factors are considered important in defining
nursery areas for juvenile estuarine-dependent organ-
isms; however, the specific contributions of these factors
are poorly understood (Beck et al., 2001). Specific combi-
nations of physiochemical conditions and cyclic primary
production that are related to food availability, growth,
and sanctuary from predation often define optimal envi-
ronments (Miller and Dunn, 1980). Barry et al. (1999)
considered prey availability to be a necessary component
defining the nursery function of estuarine habitats.
Shrimp and blue crab production has been correlated with
the availability of wetland habitat in estuaries (Turner,
1977; Zimmerman et al., 2000). In the present study,
brown shrimp were most abundant in the lower bay where
vegetated habitats were most abundant. Zimmerman et al.
( 1990b) reported that benthic infauna are most abundant
in vegetated habitats within lower Galveston Bay and
are nutritionally important for penaeids (Zein-Eldin and
Renaud, 1986; McTigue and Zimmerman, 1991, 1998).
In addition, field and laboratory experiments have shown
that brown shrimp growth is positively correlated with
the abundance of marsh epiphytes and phytoplankton
(Gleason and Zimmerman, 1984).
Most estuarine nekton are adaptable to the highly
dynamic environmental conditions exhibited within es-
tuaries (Gifford, 1962; Tagatz, 1971; Zimmerman et al.,
1990b). These organisms are commonly found in a wide
range of salinities and temperatures and are most affected
by sudden changes in these environmental conditions
272
Fishery Bulletin 102(2)
Table 3
Estimated area (km2) of each bottom type
and salinity zone combination sampled dur
ing spring (March-
-May),
and estimated
brown shrimp population based
on spring
density predictions from the model. ME =
marsh edge; SAV
= submerged aquatic
vetetation; SNB =
shallow nonve
getated bottom.
Salinity zone
Bottom type
area
Density estimate
Population estimate
Shrimp/ha.
Bottom type
(ppt)
(km2)
(number/m2)
(millions)
(thousands)
ME
0-0.5
1.4
0.14
0.2
1428
0.5-5
1.6
5.50
8.8
55,000
5-15
22.4
4.44
99.4
44,375
15-25
59.5
6.14
365.3
61,394
>25
0
8.46
0
0
Total
84.9
473.5
55,771
SAV
0-0.5
1.0
0.09
0.09
9000
0.5-5
0.03
0.18
0.005
1667
5-15
0.02
4.56
0.09
45,000
15-25
3.5
14.52
50.8
145,142
>25
0
9.91
0
0
Total
4.5
51.0
114,680
SNB
0-0.5
29.6
0
0
0
0.5-5
54.2
1.01
54.7
10,092
5-15
183.6
1.61
295.6
16,100
15-25
203.3
2.41
489.9
24,097
>25
5.5
3.37
18.5
33,636
Total
476.2
858.7
18,032
Total
565.6
1383.2
24,455
(Christensen et al., 1997). In laboratory experiments,
Zein-Eldin and Aldrich (1965) concluded that higher sa-
linities are more favorable for brown shrimp. Salinities of
ME + SAV x SNB
0.2 0.4 0.6 0.(
Observed log density
Figure 8
Relationship between predicted and observed densities of
brown shrimp (F. aztecus) in Aransas, Matagorda and San
Antonio bays and predicted densities from the Galveston Bay
model. ME = marsh edge; SAV = submerged aquatic vegetation;
SNB = shallow nonvegetated bottom.
20 ppt or greater were considered optimum in data from
Louisiana (Barrett and Gillespie, 1973).
In the present study, brown shrimp were captured
throughout Galveston Bay, but highest densities
were observed in the lower bay where salinities were
greater than 15 ppt. This spatial trend was further
strengthened by greater abundance of vegetated
bottom types in the lower portions of the bay, where
nearly half of the total marsh edge and 90% of sea-
grass beds are located (Fig. 4). These bottom types
are regularly inundated and provide stable substrate
for brown shrimp prey (epiphytic algae and infauna),
whereas seasonal oligohaline marsh and SAV habitats
in the upper bay may not promote favorable condi-
tions for prey organisms (Zimmerman et al., 1990b).
Therefore, salinity effects and the greater availability
of vegetated habitats in the lower bay may work in a
complementary manner to provide nursery areas for
brown shrimp in Galveston Bay.
Previous attempts to examine spatial patterns
of abundance and to determine linkages between
organisms and habitat included the development of
habitat suitability index (HSI) models. Early methods
were derived by the U.S. Fish and Wildlife Service
(USFWS) for freshwater species, where the HSI was
defined as a numerical index that represented the
capacity of a given habitat to support a selected spe-
cies. The scale of HSI values (0-1.0) reflects a linear
relationship between suitability and carrying capacity
Clark et al.: A habitat-use model for juvenile Farfantepenaeus aztecus in Galveston Bay
273
1.2
1.0
0.8
0.6
0.4
02
0.0
-0.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
+ V
+ jr
■ >^ ■
+ ■ + S
■ y* *
- ■ ■ ■ ./
• X *
x . •/*& s +
x is «
_ ■>♦
All Bays
^ ♦ n = 63
r2 = 0.56
+
+ yT
X /^ '
x S ♦
X
Aransas Bay
n = 9
r2 = 0.56
x ■ _, X
x •\^ x
x^^^' X
- X
>
Matagorda Bay
n = 25
r2 = 0.54
I I I i i i
+
+ s
*s* *
x ^r
X v^
San Antonio Bay
^ + n = 29
r2 = 0.57
i i I i i i
0 0.2 0.4 0.6 0.8 1.0 1.2
0.2 0.4 0.6 0.8 1.0 1.2 1.4
Observed log density
ME + SAV x SNB
Figure 9
Relationships between observed densities of brown shrimp iF. aztecus) in
Aransas, Matagorda, and San Antonio Bays and predicted densities from
the Galveston Bay model. Relationships for all bays combined are shown
in the upper left graph. For each relationship, the r2 is shown for the least
squares regression, and the number of observations (n ) and the total number
of samples in parentheses. ME = marsh edge; SAV = submerged aquatic
vegetation; SNB = shallow nonvegetated bottom.
(USFWS, 1981). Recently, Christensen et al.1 and Brown
et al., 2000, developed suitability indices, based on lit-
erature reviews and expert opinion, and raster-based GIS
models that produce a spatial view of relative suitability.
The Florida Fish and Wildlife Conservation Commis-
sion-Marine Research Institute (FMRI) and the National
Ocean Service's Center for Coastal Monitoring and As-
sessment (NOS/CCMA) collaborated to develop a suite of
quantitative HSI modeling approaches, using fisheries-
independent monitoring catch-per-unit-of-effort (CPUE)
data (Rubec et al., 1998, 1999, 2001). These studies used
an unweighted geometric mean formula as part of the HSI
models to assess overall suitability. This approach assigns
equal weight to all factors by using scaled suitability indi-
ces as inputs to the model. The regression approach used
in this study more appropriately weights density according
to the factors in the model and allows a more robust tech-
nique to elucidate spatial patterns of habitat use by using
actual CPUE data. In addition, the method described
in our study can support more complex analyses, such
as interaction effects or trophic relationships (or both).
Our ANOVA (Table 1) revealed that season, bottom type,
salinity, and the interaction between salinity and bottom
type are significant factors that influence the distribution
of juvenile brown shrimp in Galveston Bay. The addition of
the interaction effect to the model increases the coefficient
of determination from 0.63 to 0.73. Without this term in
the model, predicted values for brown shrimp density are
overestimated compared to the observed density data.
Seagrass beds in salinities greater than 15 ppt supported
significantly greater densities of brown shrimp than did
marsh edge. However, in locations with salinities less
than 15 ppt, brown shrimp densities were not significantly
different between the two bottom types. These results in-
dicate significantly lower use among all the bottom types
analyzed in the fresher portion of the estuary. It is likely
that salinity and a combination of other environmental
factors directly or indirectly (or directly and indirectly)
affect abundance on bottom types and habitat quality in
this region. The results indicate that SAV supports greater
brown shrimp density than do ME and SNB; however, SAV
accounts for less than 1% of the total bottom type within
274
Fishery Bulletin 102(2)
April-June 1985
1.5 -
*
1.0 -
i
0.5 -
i
r2=0.46
*
*
P<0.0001
July-September 1984
1.5 -
i
i
1.0 -
$
0.5 -
i
r2=o.59
i
0 -
P<0.0001
i I
i
i
West Bay
ME
West Bay
SNB
Xmas Bay
ME
Xmas Bay
SAV
Xmas Bay
SNB
Figure 10
Brown shrimp (F. aztecus) observed log density and standard deviation for bottom
types in Christmas Bay and West Bay. ME = marsh edge: SAV = submerged aquatic
vegetation; SNB = shallow nonvegetated bottom.
Galveston Bay. Our data suggest that brown shrimp select
SAV over ME when these habitats co-occur (Christmas
Bay) and select ME when grassbeds are absent (West Bay)
( Fig. 10 ). Habitat submergence time may explain high SAV
use in Christmas Bay (Rozas and Minello, 1998). Subtidal
grassbeds may provide more continuous refuge and food
supply at both low and high tides than the marsh surface,
which can be accessed only during high tides. Additionally,
brown shrimp were significantly smaller in SAV (,v = 17
mm) than in ME (5=25 mm) (t-test, P<0.001>. which may
imply ontogenetic changes in habitat or trophic require-
ments (Conrow et al., 1990; Thomas et al., 1990; Rozas and
Minello, 1999). Differences in the use of bottom types may
correspond with the population's size distribution at the
time of sampling. Additional research is needed to reveal
ontogenetic habitat shifts and relationships among shal-
low estuarine bottom types (Mclvor and Rozas, 1996).
Assessment of the model performance was based on
FWS HSI theory where there is a positive relationship
between HSI value and the carrying capacity of the avail-
able habitat. In the present study, the relationship equates
high brown shrimp densities with optimal habitat condi-
tions that promote high carrying capacity. Therefore, low
densities would reflect a low suitability or a low capacity
to support the population. Comparisons of predicted den-
sity with that of observed values from Galveston Bay, and
other Texas bays (Figs. 7 and 8) agree with FWS theory
by exhibiting a strong relationship between density and
suitable habitat as determined from the model. Model per-
formance and transferability were examined by applying
Clark et al.: A habitat-use model for juvenile Farfantepenaeus aztecus in Galveston Bay
275
the Galveston Bay model (with interaction term) to brown
shrimp density data from Aransas, Matagorda, and San
Antonio bays. The results indicated similar habitat-use
patterns in Aransas and San Antonio bays; there were
higher densities in high-salinity seagrass beds and a de-
clining density as salinity decreased in these bay systems.
No SAV samples were taken in Matagorda Bay; however,
the model performed well in predicting greater brown
shrimp density in higher-salinity marsh-edge habitats.
Our analysis suggests that although the empirical model
is complex, it is general enough to be applicable across a
broader range of habitat types. The model results may,
however, have some geographic limitations. For instance,
the model may not perform well within the Laguna Madre
in south Texas, where freshwater inflow is diminished and
hypersaline conditions exist. This conclusion is consistent
with Rubec et al. (1999), who used similar methods to
demonstrate that HSI models are applicable across estuar-
ies in central Florida. Our results are promising in view
of previous efforts where predictions of nekton abundance
with empirical models have proven difficult.
Currently, estuarine EFH for most federally managed
species in the Gulf of Mexico exists as mapped estimates
of relative abundance from NOS's estuarine living marine
resources (ELMR) database (GMFMC, 1998; Nelson and
Monaco, 2000). The entire Galveston Bay complex was
considered EFH for brown shrimp based on ELMR relative
abundance data. Our model, generated by using brown
shrimp density data, provides a more spatially resolved
delineation of EFH (in waters <1 m depth) for brown
shrimp <100 mm.
The analyses described in the present study focused
on bottom types in waters less than 1 m which comprise
about 25% of the available habitat in Galveston Bay.
Trawl CPUE data from Texas Parks and Wildlife De-
partment (TPWD) were analyzed to compare abundance
and distribution patterns in waters >1 m. These trawls
(3.8-cm stretched mesh) do not capture small size classes
(<50 mm TL) of brown shrimp efficiently; thus the trawl
analysis provides information only on larger size classes
(mean=89 mm). However, few individuals in smaller size
classes of shrimp (<50 mm TL) are likely to inhabit deeper
bay waters; density estimates of small nekton, including
shrimp, decline rapidly with depth (Mock, 1966; Baltz et
al., 1993; Rozas, 1993; Rozas and Zimmerman, 2000). In
addition, these CPUE values are likely underestimates of
brown shrimp density; catch efficiency for shrimp in trawls
can be roughly estimated at 20f/f (Zimmerman et al., 1984;
Rozas and Minello, 1997). Despite these problems, shrimp
abundance estimates in water >1 m appear low; abun-
dance estimates from TPWD trawl data in deep open-bay
waters were almost two orders of magnitude lower than
densities in shallow water habitats.
Brown shrimp population estimates from the present
study (Table 3) were highest in the lower bay (224,568 per
ha.). Seagrass beds accounted for more than 607i of the es-
timate ( 145,142 per ha.) and marsh edge and nonvegetated
bottom types combined were estimated at approximately
79,000 per ha. As noted earlier, the NWI regularly flooded
emergent vegetation classification is not all marsh edge but
is a complex of SNB, marsh edge, and inner marsh with
different shrimp densities associated with each of these
microhabitat types. Minello and Rozas (in press) modeled
small-scale density patterns on the marsh surface in a
437-ha. salt marsh of lower Galveston Bay and applied
these data to a GIS analysis of marsh landscape patterns.
In this highly fragmented marsh complex that was 37%
SNB and 63% marsh vegetation, they estimated brown
shrimp populations at 37,000 per ha. We could not estimate
brown shrimp populations in irregularly flooded emergent
vegetation, although the areal coverage of this habitat type
was large. Compared with the regularly flooded wetlands,
overall densities of brown shrimp in these irregularly
flooded systems should be relatively low because of higher
marsh surface elevations (Rozas and Reed, 1993; Minello
et al., 1994; Minello and Webb, 1997) and restricted tidal
access (Rozas and Minello, 1999). We also were unable to
assess the contribution of oyster reef as habitat for brown
shrimp. Coen et al. ( 1999), however, reported brown shrimp
on oyster reefs, and Powell ( 1993 ) estimated that there was
108 km2 of this habitat in Galveston Bay.
Our modeling results provide evidence that estuarine
habitat types are discriminately used by brown shrimp.
The success of transferring our empirical model from
Galveston Bay to adjacent bay systems in Texas suggests
that the model has a broad application and can possibly
be used to simulate patterns of habitat use in systems
that lack sufficient density data. Continuing collections
of density data in Gulf estuaries are necessary to make
additional interestuary comparisons and to determine
whether these habitat-use patterns differ throughout the
distributional range of brown shrimp. The use of other
habitat types also needs to be examined. For example,
other available habitat types from Galveston Bay, such as
oyster reef and inner marsh, and from other Gulf estuar-
ies, such as mangrove, calcium carbonate rock formations,
and sponge communities, may be important habitats for
this federally managed species.
Acknowledgments
Funding and support for this work was provided by the
Southeast Region of NOAA's National Marine Fisheries
Service, The Southeast Fisheries Science Center, and the
Biogeography Program of the National Ocean Service. We
would like to thank Pete Sheridan, Lawrence Rozas, Ken
Heck, and Roger Zimmerman for providing access to pub-
lished and unpublished data sets. John Boyd helped with
construction of the nekton density database.
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1998. Food, density, and microhabitat: factors affecting
growth and recruitment potential of juvenile saltmarsh
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Abstract— Queen conch (Strombus
gigas) stocks in the Florida Keys once
supported commercial and recreational
fisheries, but overharvesting has
decimated this once abundant snail.
Despite a ban on harvesting this spe-
cies since 1985, the local conch popu-
lation has not recovered. In addition,
previous work has reported that conch
located in nearshore Keys waters are
incapable of spawning because of poor
gonadal condition, although reproduc-
tion does occur offshore. Queen conch
in other areas undergo ontogenetic
migrations from shallow, nearshore
sites to offshore habitats, but conch in
the Florida Keys are prevented from
doing so by Hawk Channel. The pres-
ent study was initiated to determine
the potential of translocating non-
spawning nearshore conch to offshore
sites in order to augment the spawning
stock. We translocated adult conch
from two nearshore sites to two off-
shore sites. Histological examinations
at the initiation of this study confirmed
that nearshore conch were incapable of
reproduction, whereas offshore conch
had normal gonads and thus were able
to reproduce. The gonads of nearshore
females were in worse condition than
those of nearshore males. However, the
gonadal condition of the translocated
nearshore conch improved, and these
animals began spawning after three
months offshore. This finding suggests
that some component of the nearshore
environment (e.g.. pollutants, tem-
perature extremes, poor food or habitat
quality) disrupts reproduction in conch,
but that removal of nearshore ani-
mals to suitable offshore habitat can
restore reproductive viability. These
results indicate that translocations
are preferable to releasing hatchery-
reared juveniles because they are more
cost-effective, result in a more rapid
increase in reproductive output, and
maintain the genetic integrity of the
wild stock. Therefore, translocating
nearshore conch to offshore spawn-
ing aggregations may be the key to
expediting the recovery of queen conch
stocks in the Florida Keys.
Translocation as a strategy to rehabilitate
the queen conch (Strombus gigas) population
in the Florida Keys
Gabriel A. Delgado
Claudine T. Bartels
Robert A. Glazer
Florida Fish and Wildlife Conservation Commission
Florida Marine Research Institute
2796 Overseas Highway, Suite 119
Marathon, Florida 33050
E-mail address (for G. A Delgado) gabneLdelgado;g>fwc. state fl us
Nancy J. Brown-Peterson
Department of Coastal Sciences
College of Science and Technology
The University of Southern Mississippi
P.O. Box 7000
Ocean Springs, Mississippi 39566
Kevin J. McCarthy
National Marine Fisheries Service, NOAA
75 Virginia Beach Drive
Miami, Florida 33149
Manuscript approved for publication
24 November 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:278-288(20041.
The queen conch (Strombus gigas) is
a large marine gastropod harvested
intensively throughout the Caribbean
for its meat and shell. In the Florida
Keys, conch once supported commercial
and recreational fisheries, but overhar-
vesting severely depleted the popula-
tion. The harvesting of conch has been
banned in Florida since 1985, but the
population has not recovered to levels
that can support exploitation (Glazer
and Berg. 1994; Berg and Glazer, 1995;
Glazer and Delgado, 2003). Intensive
fishing may invoke depensatory mecha-
nisms as densities are reduced, limit-
ing the ability of conch to locate mates
and increasing the chance of recruit-
ment failure (Appeldoorn, 1995). This
seems to be the case in Florida because
the lack of recovery has been attrib-
uted to diminished recruitment due in
part to small spawning aggregations
(Stoner et al., 1997; Stoner and Ray-
Culp, 2000).
Queen conch occur in the various
oceanside habitats of the Florida Keys
archipelago with the exception of Hawk
Channel (Glazer and Berg, 1994). This
naturally occurring deep-water channel
runs parallel to the Florida Keys, be-
tween the island chain and the offshore
reef tract. The substrate on the bottom
of Hawk Channel is predominantly soft
sediment, which is poor conch habitat;
consequently, Hawk Channel serves
as a barrier to migration and isolates
nearshore from offshore conch aggre-
gations (Glazer and Berg, 1994). We
have been monitoring queen conch
stocks throughout the Florida Keys
since 1987, and despite extensive sur-
veys, we have never observed reproduc-
tive activity among conch in nearshore
aggregations (Glazer and Berg, 1994).
Conversely, reproductive behavior has
been commonly observed among conch
in offshore aggregations (Glazer and
Berg, 1994). Moreover, a preliminary
histological examination of conch from
these two regions indicated that the
gonads of offshore conch were capable
of undergoing gametogenesis, whereas
the gonads of nearshore conch were
nonfunctional (Glazer and Quintero,
Delgado et al.: Translocation of Strombus gigas as a strategy to rehabilitate the Florida Keys conch population
279
DK
Key West 4jSt-^*'
PS
Atlantic Ocean
I I Hawk Channel
Reef Tract
25 00' N
24 30' N
8130'W
81 00' W
80 30' W
Figure 1
Queen conch lStroi7ibus gigas) translocation sites in the Florida Keys (adapted from
McCarthy et al. 2002). The nearshore region is the stretch of water on the landward
side of Hawk Channel; the offshore region is the stretch of water on the other side
of the channel, contiguous with the Atlantic Ocean. Nearshore conch were translo-
cated from Tinglers Island (TI) to Alligator Reef (AR) and from Duck Key (DK) to
Pelican Shoal (PS).
1998; McCarthy et al., 2002). In a metapopulation context,
the nearshore region in the Florida Keys can be considered
a "blackhole sink" for larval recruitment because conch
that settle there do not spawn and thus do not contribute
to the reproductive output of the stock (se?isu Morgan and
Botsford, 2001).
In 1990, the Florida Fish and Wildlife Conservation
Commission's (FWC) Florida Marine Research Institute
constructed an experimental hatchery to test the feasi-
bility of rehabilitating queen conch stocks in the Florida
Keys by releasing hatchery-reared juveniles. A series of
experiments to determine the best size of juveniles, time
of release, and area to release hatchery-reared juvenile
conch were conducted, and a cost-benefit analysis was
performed. Unfortunately, the high mortality of conch
after release, coupled with high production costs, caused
us to examine alternate strategies (Glazer and Delgado,
2003).
Translocation is defined as the intentional introduction
or reintroduction of animals in an attempt to establish,
reestablish, or augment a population in order to aid in the
recovery of a native species whose numbers have been re-
duced by overharvesting or habitat loss (or both) (Griffith
et al., 1989). This method of population recovery has been
used to facilitate the recovery of numerous species of birds
and mammals (Griffith et al., 1989) and several aquatic
species, including cutthroat trout (Harig et al., 2000) and
corals (Edwards and Clark, 1999; Rinkevich, 1995; van
Treeck and Schuhmacher, 1997). Nest translocations
have also proven effective in efforts to recover sea turtles
(Garcia et al., 1996).
The present study was initiated to determine the po-
tential of translocating nonspawning nearshore conch to
offshore sites as a method to augment spawning aggrega-
tions and as an aid in the recovery of the queen conch
population in the Florida Keys. However, this strategy will
be beneficial only if the translocated conch regain their
reproductive capacity. To test this approach, we translo-
cated adult conch from the nearshore region into existing
offshore breeding aggregations and examined changes
in reproductive behavior (i.e., mating and spawning) and
gonadal development.
Materials and methods
Translocations and reproductive behavior
During March 1999, we translocated adult conch from
nearshore aggregations to aggregations offshore. Near-
shore aggregations were located at Tinglers Island
(24°41'N, 8r05'W; water depth <l-2 m) and Duck Key
(24°45'N, 80°55'W; water depth <l-2 m) (Fig. 1). The
habitat at the two nearshore sites was characterized as a
matrix of hard-bottom and Thalassia testudinum patches.
Offshore aggregations were located at Alligator Reef
(24°51'N, 80°37'W; water depth 9-11 m) and Pelican Shoal
(24°30'N, 81°37'W; water depth 5-7 m) (Fig. 1). The habitat
at the offshore sites consisted of back-reef rubble, sandy
plains, and patches of Thalassia testudinum.
We tagged 44 adult conch at Tinglers Island; 23 were
translocated to Alligator Reef, and 21 were rereleased at
280
Fishery Bulletin 102(2)
Table 1
The number of gonadal tissue samples taken from resident nears
conch, by sex and season.
hore, resident offshore, and translocated nearshore queen
Spring
Summer
Fall
Females Males
Females Males
Females Males
Resident nearshore 13 12
Resident offshore 22 20
Translocated nearshore
14 12
19 20
12 12
10 6
25 15
13 4
Table 2
Index and definitions
used to quantify gonadal maturity in queen conch. This index is patterned after the maturity scale devel-
oped by Egan (1985).
The dashed line
separates the scores 1-5 from 6-8 that were combined for statistical analyses.
Gonadal condition
Score
Definition
Early development
1
primary and cortical alveolar oocytes in females; spermatogonia and spermato-
cytes in males
Mid development
2
vitellogenesis beginning in females; spermatozoa present in males
Late development
3
fully developed oocytes in females, none in oviduct; all stages of spermatogenesis,
no spermatozoa in vas deferens
Ripe
4
oocytes in oviduct for females; spermatozoa in vas deferens for males
Spent
5
reabsorption of vitellogenic oocytes in females; empty lobules, residual spermato-
zoa in males
Atresia
6
reabsorption of oocytes and no vitellogenesis in females; reabsorption of spermato-
zoa in males
Regressed
7
only primary oocytes in females; only primary spermatogonia in males
No tissue
8
no gonadal tissue development and no germ cells present; this is an abnormal
condition in adult females and males
Tinglers Island. We also tagged 132 adult conch at Duck
Key; 73 were translocated to Pelican Shoal, and 59 were
re-released at Duck Key. In addition. 100 resident offshore
conch were tagged in situ at both Alligator Reef and Peli-
can Shoal. Conch were tagged with individually numbered
tags that were secured to the shell spires by Monel wire;
in addition, colored flagging tape was similarly attached
to facilitate recapture.
Reproductive behavior of tagged queen conch was moni-
tored at each of the four sites on a weekly basis, weather
permitting, from March 1999 through November 1999. Off-
shore sites were surveyed by using SCUBA; nearshore sites
were surveyed by snorkeling. Mating activity was quanti-
fied by counting the number of tagged individuals (both
males and females) copulating; spawning activity was
quantified by counting the number of tagged females laying
egg masses. Data from the two nearshore sites were pooled
and data from the two offshore sites were pooled. Data were
also pooled by season: spring consisted of March, April, and
May; summer consisted of June, July, and August; and fall
consisted of September, October, and November.
Histological examinations
Gonadal tissue samples from adult conch were collected
for histological examination at the initiation of the
study (spring; the start of the breeding season), during
July-August (summer; breeding season), and during
October (fall; the end of the breeding season) in order to
assess gonadal development in relation to time after trans-
location. We collected approximately 40 resident offshore
conch during each season (Table 1). However, because
of the small size of the nearshore aggregations and the
small number of nearshore conch translocated offshore,
we collected about 20 individuals from these two groups
each season (Table 1). We did not determine the sex of the
animals before sample collection; therefore the breakdown
by sex is not exactly even (Table 1).
A one-cm:i piece of tissue from the middle of the gonad of
each animal was placed in a labeled plastic cassette and
preserved in 10f;i neutral buffered formalin. After 7 to 14
days in fixative, the tissue samples were rinsed overnight
in freshwater. The samples were then dehydrated in a se-
Delgado et al.: Translocation of Strombus gigas as a strategy to rehabilitate the Florida Keys conch population 281
ries of graded ethanols (one change of 60% ethanol and two
changes of 70% ethanol for two hours each) and loaded into
an automatic tissue processor (Shandon Hypercenter XP,
Shandon Scientific Ltd., Pittsburgh, PA) for dehydration,
clearing, and paraffin infiltration. Tissues were embedded
in Paraplast Plus (Fisher Scientific, Pittsburgh, PA) and
sectioned at 4 jim with a rotary microtome. Two serial
sections from each tissue sample were mounted on glass
slides, allowed to dry overnight, and stained with hema-
toxylin 1 and eosin Y (Richard Allen Inc., Richland, MI).
All laboratory procedures followed approved standard op-
erating procedures developed under the Good Laboratory
Practices guidelines (EPA and FDA guidelines).
A detailed histological inspection of each sample was
made to assess the stage of gonadal maturity and the
percentage of gametogenic tissue. Each animal was given
a score from 1 to 8 to quantify gonadal maturity (Table 2).
This index was derived from a maturity scale developed
by Egan (1985). Because of the small number of animals
collected, gonadal maturity scores from 1 to 5 were com-
bined to group animals that would be capable of spawning
or had recently spawned (Table 2). Scores from 6 to 8 were
combined to group animals that would not spawn again in
a season or were not capable of spawning (Table 2). In ad-
dition, the percentage of gametogenic tissue present (i.e.,
the percentage of ovarian or testicular tissue occupying
the available space of the section) was visually estimated
by using the following index: <25%, 25-50%, 51-75%, and
>75%. For statistical analyses, this index was reduced to
two categories: <50% and >50%.
Statistical analyses
We evaluated differences in reproductive behavior (mating
and spawning) between resident nearshore and translo-
cated nearshore conch for each season by using Fisher's
exact test because it is not sensitive to small sample sizes
(Zar, 1996). We also examined differences in gonadal
condition (i.e., gonadal maturity and the percentage of
gametogenic tissue) between resident nearshore and
resident offshore conch for each season by using Fisher's
exact test. Males and females were analyzed separately.
In order to assess the effectiveness of the translocations to
the offshore region, we used Fisher's exact test to compare
the gonadal condition of translocated nearshore conch
with the gonadal condition of resident nearshore conch
in summer and in fall. Again, the sexes were analyzed
separately. All tests were run on SPSS 9.0 (SPSS Inc.,
Chicago, ID for Windows. Results were considered sig-
nificant if P<0.05.
Results
Reproductive behavior: mating
Approximately 84% of the tagged resident nearshore conch.
69% of the tagged translocated nearshore conch, and 88%
of the tagged resident offshore conch were observed at
least once during monitoring. Resident nearshore conch
Table 3
Percentage of mating (the number of males and females
mating divided by the total number of conch observed
during that season) and spawning (the number of females
spawning divided by the total number of females observed
during that season I in nearshore conch and offshore conch
by season I adapted from McCarthy et al.. 2002 ). Numbers
in parentheses represent the number of observations;
P represents the probabilities from Fisher's exact test
of differences in reproductive behavior between resi-
dent nearshore and translocated nearshore conch. The
asterisk (*) indicates that the test was statistically sig-
nificant. N/A indicates that statistical analyses were not
conducted because no mating or spawning was observed
among either resident nearshore or translocated near-
shore animals.
Offshore
conch
Nearshore conch
Resident Resident Translocated P
Mating
Spring
Summer
Fall
Spawning
Spring
Summer
Fall
5.3(95) 0.0 1 37 i
2.4(4671 0.0(1061
0.9(2321 0.0(20)
46.2(39) 0.0(6)
16.8(191) 0.0(34)
5.2(97) 0.0(9)
0.0(19) N/A
0.0(81) N/A
0.0(51) N/A
0.0(10) N/A
12.2(41) 0.041*
18.5(27) 0.214
and translocated nearshore conch were not observed
mating during any of the field surveys; conversely, resi-
dent offshore conch were observed mating throughout the
study (Table 3). The mating frequency of resident offshore
conch was highest during the spring ( 5.3% ) and decreased
during subsequent seasons to 0.9% in the fall (Table 3).
All observed mating occurred between resident offshore
animals.
Reproductive behavior: spawning
Neither resident nearshore females nor translocated near-
shore females were observed spawning during the spring
(Table 3). However, by summer, translocated nearshore
females had attained the capacity to spawn and had a
significantly higher spawning frequency than resident
nearshore females (12.2% vs. 0.0% , respectively) (Table 3).
During the fall, spawning frequency of translocated
nearshore females peaked at 18.5%, whereas resident
nearshore females had still not exhibited any spawn-
ing behavior (Table 3). However, this difference was not
statistically significant because of the small number of
resident nearshore conch observed (Table 3). Looking at
individual performance instead of spawning frequency,
seven (or about 14%) of the approximately 50 nearshore
females translocated offshore were observed spawning at
least once during the study period.
282
Fishery Bulletin 102(2)
" " TV.- w .
'■ "0
o
k O-'
VJ,
■■
B
i • - &* < • >: ^
it ' ■
/ . •■ S§i s , ; . u
E
i:;
4 ..<-_.■> v*
Figure 2
Photomicrographs of the gonadal condition of resident nearshore, resident offshore, and translocated nearshore
queen conch (Strombus gigas). (A) Resident nearshore female during spring, no tissue and <25% gametogenic
tissue. (B) Resident offshore female during spring, ripe and >75% gametogenic tissue. (C) Translocated nearshore
female during summer, late development and 25-50% gametogenic tissue. (D) Resident nearshore male during
spring, early development and <25% gametogenic tissue. (E) Resident offshore male during spring, ripe and >75%
gametogenic tissue. (F) Translocated nearshore male during summer, ripe and 25-5095 gametogenic tissue.
Resident offshore females were observed spawning
throughout the study (Table 3 1. Their spawning frequency
peaked during the spring at 46.2% and decreased during
subsequent seasons to 5.2% in the fall (Table 3).
Histology: females
Histological examinations revealed that the gonadal con-
dition of resident nearshore and resident offshore female
Delgado et al.: Translocation of Strombus gigas as a strategy to rehabilitate the Florida Keys conch population 283
Females
100
80 •
60
40
20
100
80
60
40
20 •
100
80
60
40
20
0
Spring
n
i
Summer
i i n
. n .1 i
Fall
n n Jllii
A«
6^ J
Males
Spring
ill
■ 1
Summer
Ml 1
Li
Fall
n
1
<8
6B s" i
c5- 9 d? ■&
resident nearshore
resident offshore
Figure 3
Gonadal maturity of resident nearshore and resident offshore queen conch (Strom-
bus gigas) by sex and season. The dotted line separates the categories that were
combined for statistical analyses.
conch were markedly different at the beginning of the
study (Fig. 2. A and B). There were significant differences
in gonadal maturity between resident offshore and resi-
dent nearshore female conch during the spring, summer,
and fall (Table 4). During the spring, the gonads of most
resident offshore females were categorized as being in
late development; by summer most were ripe and by fall
most were either spent, in atresia, or regressed (Fig. 3). In
contrast, the gonads of most resident nearshore females
contained no germ cells during the spring (Fig. 3). By
summer, the gonads of some resident nearshore females
were found to be in the early stages of development, but
most females were still incapable of spawning, and by fall,
all the resident nearshore females sampled were incapable
of spawning (Fig. 3). There were also significant differ-
ences in the percentage of gametogenic tissue between
resident offshore and resident nearshore females during
the spring, summer, and fall (Table 4). The gonads of most
resident offshore females contained >75% gametogenic
tissue throughout the study period, whereas those of most
resident nearshore females had <25% (Fig. 4).
The gonadal condition of translocated nearshore females
(Fig. 2C) improved when compared with the gonadal
condition of resident nearshore females (Fig. 2A). There
were significant differences in gonadal maturity between
Table 4
Probabilities from Fisher's exact test
of differences in
gonadal maturity and
the percentage
of gametogenic
tissue between resident nearshore and
resident offshore
conch by sex and season. n r
?presents
the total number
of observations. Asterisks ( I
indicate that the test was
statistically significant.
Females
Males
n
P
H
P
Gonadal maturity
Spring
35
<0.001*
32
0.004*
Summer
33
<0.001*
32
0.002*
Fall
35
0.006*
21
<0.001*
% gametogenic tissue
Spring
35
<0.001*
32
<0.001*
Summer
33
<0.001*
32
<0.001*
Fall
35
0.002*
21
<0.001*
translocated nearshore and resident nearshore females
during both the summer and fall (Table 5). There was
284
Fishery Bulletin 102(2)
Females
Males
a
60
40 ■
20 ■
0
80
i- 60
CD
~ 40
| 20
D- 0
80
60
40
20
0
Spnng I
J_i Q_m
In rfi J1
&' ,5? & &
Spnng
mmer
It
rail
IL
n
resident nearshore
resident offshore
Figure 4
The percentage of gametogenic tissue of resident nearshore and resident offshore
queen conch iStrombus gigas) by sex and season. The dotted line separates the cat-
egories that were combined for statistical analyses.
Nearshore females
Nearshore males
100
80
60
40
20
100
80 •
60 ■
40
20
0
An
L
n n
L
Summer
J
nl I
Fall
[
] n
■
?*/
& 8
<? s*
6*
resident
translocated
Figure 5
Gonadal maturity of resident nearshore and translocated nearshore queen conch
iSlrombus gigas) by sex and season. The dotted line separates the categories that
were combined for statistical analyses.
a higher percentage of translo-
cated nearshore females in some
stage of gonadal development than
resident nearshore females during
the summer; in fact, about 30% of
the translocated females were ripe
(Fig. 5). By fall, the differences
were even more extreme; over 60%
of the translocated nearshore fe-
males were ripe, whereas all of the
resident nearshore females were
incapable of reproducing (Fig. 5).
Although there was a significant
difference in gonadal maturity be-
tween translocated nearshore and
resident nearshore females during
the summer, there was no signifi-
cant difference in the percentage
of gametogenic tissue (Table 5 and
Fig. 6). However, by fall, there
were significant differences in the
percentage of gametogenic tissue
between translocated nearshore
and resident nearshore females
(Table 5 1. Most translocated near-
shore females had developed >75' i
of the gonad, whereas most resi-
dent nearshore females still had
<259c gametogenic tissue (Fig. 6).
Histology: males
There were marked differences in
gonadal condition of resident near-
shore and resident offshore male
conch (Fig. 2, D and E). There were
significant differences in gonadal
maturity between resident offshore
and resident nearshore male conch
during the spring, summer, and fall
(Table 4). During the spring and
summer, the gonads of most resi-
dent offshore males were catego-
rized as ripe; by fall most were spent
(Fig. 3). In contrast, at least half of
the resident nearshore males were
not capable of spawning during
the spring and summer, although
some were in the early stages of tes-
ticular development and some were
even ripe (Fig. 3). However, all the
sampled resident nearshore males
were incapable of spawning by fall
and none were identified as spent
(Fig. 3). Histological examinations
also revealed significant differ-
ences in the percentage of game-
togenic tissue between resident
offshore and resident nearshore
males during the spring, summer.
Delgado et al.: Translocation of Strombus gigas as a strategy to rehabilitate the Florida Keys conch population
285
Nearshore females
Nearshore males
Figure 6
The percentage of gametogenic tissue of resident nearshore and translocated near-
shore queen conch {Strombus gigas) by sex and season. The dotted line separates the
categories that were combined for statistical analyses.
and fall (Table 4). Most resident offshore males had >75%
gametogenic tissue throughout the study period, whereas
most resident nearshore males had <25% (Fig. 4).
The gonadal condition of translocated nearshore males
(Fig. 2F) improved in relation to the gonadal condition of
resident nearshore males (Fig. 2D). There were significant
differences in gonadal maturity between translocated
nearshore and resident nearshore males during both the
summer and fall (Table 5). Almost 80% of the translocated
nearshore males were ripe during the summer, whereas
about half of the resident nearshore males were incapable
of reproducing (Fig. 5). By fall, most translocated near-
shore males were still capable of reproduction, whereas
none of the resident nearshore males were (Fig. 5). There
were also significant differences in the percentage of
gametogenic tissue between resident nearshore and
translocated nearshore males during the summer and
fall (Table 5). During the summer, the gonads of most
of the resident nearshore males contained <25% game-
togenic tissue, whereas translocated nearshore males
were divided equally among the four gametogenic tissue
categories (Fig. 6). During the fall, the gonads of most of
the resident nearshore males still had <25% gametogenic
tissue; however, most translocated nearshore males had
developed >50'/r of the gonad (Fig. 6).
Discussion
In the nearshore region of the Florida Keys, adult queen
conch had severe deficiencies in reproductive behavior and
gonadal development. Histological examinations of resi-
Table 5
Probabilities from Fisher's exact test of differences in
gonadal maturity and the percentage of gametogenic
tissue between resident nearshore and translocated near-
shore conch by sex and season, n represents the total
number of observations. Asterisks (*) indicate that the
test was statistically significant.
Females
Males
Gonadal maturity
Summer
Fall
7o gametogenic tissue
Summer
Fall
26 0.019*
23 <0.001*
26 0.130
23 0.038*
24
10
0.045*
0.033*
24 0.014*
10 0.033*
dent nearshore conch revealed that most were incapable
of reproducing, whereas resident offshore conch exhibited
a normal reproductive cycle (as described by Egan, 1985,
and Stoner et al., 1992). Furthermore, our results suggest
that female conch may be more sensitive to the nega-
tive effects of nearshore conditions than male conch. For
example, during the spring and summer, some resident
nearshore males were ripe (although their reproductive
output would have been severely reduced because of a low
percentage of gametogenic tissue), whereas the gonads of
286
Fishery Bulletin 102(2)
most resident nearshore females contained no germ cells.
The latter condition may have been due to the fact that
egg production is more costly bioenergetically than sperm
production (Ricklefs, 1990).
Mating and spawning do not occur among resident near-
shore conch presumably because of their retarded gonadal
development; however, the translocation of nearshore
conch to the offshore region mitigated the deleterious ef-
fects that the nearshore environment had on their gonadal
development. The reproductive tissues of translocated
nearshore conch began to develop during the summer
after the conch had spent about three months offshore.
Most translocated female conch were in the early stages
of gonadal development, whereas most translocated male
conch were ripe. We believe this difference in gonadal de-
velopment is due to the fact that the starting gonadal con-
dition of nearshore females was worse than the starting
condition of male conch. By fall, after six months offshore,
most translocated females had become ripe. In addition,
the percentage of gametogenic tissue in the gonads of both
sexes increased through the summer and fall.
In conjunction with the improvement in gonadal condi-
tion, nearshore females translocated to the offshore region
were observed spawning during the summer and fall;
however, no mating was observed among nearshore conch
translocated offshore. Resident offshore conch also had low
mating frequencies (<6"7r ). Similarly low mating frequen-
cies have been reported in the Virgin Islands (Randall,
1964) and the Bahamas (Stoner et al., 1992). We suspect
that the lack of observations of nearshore conch mating in
the offshore region may have been an artifact of the low
probability of encountering that activity due to the small
number of nearshore conch translocated offshore. Never-
theless, we believe mating must have occurred because
translocated nearshore conch were observed spawning.
However, it is unknown if queen conch are capable of lay-
ing unfertilized egg masses.
The beginning of reproductive activity in queen conch
is linked to the start of spring, when water temperatures
begin rising (Randall, 1964; Stoner et al, 1992; Weil and
Laughlin, 1984). This same seasonal pattern was observed
in our study with resident offshore conch. They exhibited
the highest mating and spawning frequencies during the
spring and reproductive behavior decreased during the
ensuing seasons. However, compared with the spawn-
ing pattern of resident offshore conch, peak spawning in
translocated nearshore conch was delayed; peak spawning
occurred during the fall. Nevertheless, there was evidence
to suggest that the timing of reproductive behavior of
both resident offshore and translocated nearshore conch
might eventually become similar. Our results indicated
that it takes at least three months after translocation for
the negative effects of the nearshore environment to be
mitigated and for gonadal maturation to occur. The out-
of-phase spawning may have been prevented if the trans-
locations had occurred earlier in the year (e.g., January,
instead of March).
Identifying the causative factor or factors that inhibit
the reproductive viability of nearshore queen conch re-
quires further study. However, the juxtaposition of the
nearshore conch aggregations with human population cen-
ters suggests that anthropogenic changes to the nearshore
region may be partially responsible. Decreased reproduc-
tive output caused by anthropogenic contaminants has
been observed in several marine invertebrates, including
dogwinkles iNucella lapillus) (Bryan et al., 1987; Gibbs
and Bryan, 1986), scallops (Gould etal., 1988), sea urchins
(Krause, 1994; Thompson et al., 1989), and shrimps and
crabs (Wilson-Ormond et al., 1994). For example, chronic
exposure to tributyltin has been shown to sterilize females
of several species of mollusks (Matthiessen and Gibbs,
19981, and sublethal levels of copper greatly inhibited
gamete production and maturation in scallops (Gould et
al., 1988). There have also been numerous reports impli-
cating eutrophication in nearshore habitat degradation
in the Florida Keys (Lapointe et al., 1990; Lapointe and
Clark, 1992; Szmant and Forrester, 1996); however, very
little is known about the effects of increased nutrient levels
at the organismal level.
The retarded gonadal condition in nearshore queen
conch may also be due to environmental factors such as
suboptimal habitat, poor food quality, or temperature
extremes associated with shallow water. Research on
bivalves has shown that habitat, diet, and food quality
directly affect gamete production (Le Pennec et al.. 1998:
Madrones-Ladja et al., 2002). As they increase in age and
size, queen conch undergo ontogenetic migrations from
shallow, nearshore sites to deeper-water habitats (Ran-
dall, 1964; Sandt and Stoner, 1993; Stoner, 1989; Weil and
Laughlin, 1984). It has been hypothesized that as conch
grow larger and require more food, they migrate to take
advantage of the augmented food supply in more produc-
tive offshore habitats (Sandt and Stoner. 1993; Stoner.
1989). However, nearshore queen conch in the Florida
Keys are prevented from migrating offshore by Hawk
Channel (Glazer and Berg, 1994). Therefore, translocat-
ing nearshore conch offshore would, in effect, link these
isolated environments.
The implications of this study are of particular impor-
tance to the FWC-Florida Marine Research Institute's
ongoing queen conch stock restoration program. Trans-
locating naturally recruiting nearshore conch to offshore
areas would be more cost effective than hatchery produc-
tion of juvenile conch, especially because production costs
are eliminated and survival of translocated conch is likely
to be much greater than that of hatchery outplants (see
Stoner, 1997. for a review of juvenile mortality in stock
enhancement efforts). Translocations would also have a
more immediate effect on reproductive output than would
the release of hatchery-reared conch. A translocation pro-
gram would focus on moving large juveniles and adults
offshore, whereas a hatchery program must release small
juveniles (to minimize production costs) that would then
have to survive to maturity. Consequently, translocations
would quickly alleviate the depensatory mechanisms de-
scribed by Appeldoorn (1995) that can affect the recovery
of queen conch stocks. Finally, translocations provide the
added benefit of maintaining the genetic diversity of the
population. Hatchery-reared conch are typically derived
from a few egg masses and there is a concurrent loss in
Delgado et al.: Translocation of Strombus gigas as a strategy to rehabilitate the Florida Keys conch population
287
rare alleles (Allendorf and Ryman, 1987). However, the
use of wild conch to enhance the spawning aggregations
eliminates this problem.
Queen conch appear to be a prime candidate for reha-
bilitation by translocation because they meet the criteria
associated with successful translocations reported by
Griffith et al. (1989). These factors include release within
the historical range of the species or into areas of in-
creased habitat quality (or both). Additionally, herbivorous
animals stand a greater chance of translocation success
than do carnivores or omnivores. Lastly, wild animals
translocate more successfully than captive-bred animals.
According to these parameters, queen conch are ideally
suited for translocations.
However, before a full-scale translocation program can
be implemented, there are some theoretical considerations
that must be addressed. For example, Stoner and Ray-
Culp (2000) reported that conch reproductive behavior
reached an asymptotic level near 200 conch/ha.; therefore,
it would seem advantageous to enhance reproductive ag-
gregations to that density. However, without high habitat
quality, translocations have low success rates regardless
of how many animals are released (Griffith et al., 1989).
First, we must ascertain if offshore habitats can support
the added number of conch or if the translocated or na-
tive animals (or both) will simply disperse after release
because of density-dependent factors (e.g., intraspecific
competition for limited resources). Conch grazing has been
shown to significantly reduce the biomass of seagrass mac-
rodetritus and epiphytes (Stoner, 1989). In addition, the
effects of removing nearshore conch from the nearshore
environment need to be investigated.
Additionally, if increased recruitment is the ultimate
goal of the translocation program, larvae must survive
and be retained within the Florida Keys. At this point, it
is unknown whether larvae produced from translocated
nearshore conch are viable or as viable as the larvae pro-
duced by native offshore conch. Furthermore, the relative
contribution of local and upstream sources to recruitment
is unknown. Stoner et al. (1996, 1997) suggested that most
of the queen conch larvae entering the Florida Keys come
from upstream sources. If this is indeed the case, then local
translocations will not be as effective as an international or
regional management strategy. However, mechanisms for
larval retention in the Florida Keys have been described
by Lee and Williams (1999), who suggested that the pe-
riodic formation of gyres in the lower Keys may facilitate
the retention and recruitment of locally produced larvae.
If larvae are retained within the Florida Keys system, any
increase in local larval production will increase larval sup-
ply and may increase recruitment. Therefore, translocation
sites should be located in the lower Keys in order to ensure
maximum larval retention and recruitment.
The present study has shown that translocation may be
a viable method for rehabilitating queen conch populations
in the Florida Keys. We have demonstrated that nearshore
conch that were translocated offshore regained some of
their reproductive capacity and abilities. Therefore, mov-
ing conch from nearshore larval sinks to offshore larval
sources may be the key to expediting the recovery of queen
conch stocks. Further research (e.g., larval retention
studies, studies on the effect of water quality on larval
survival, carrying capacity studies) and monitoring will
determine the efficacy of this restoration strategy.
Acknowledgments
John Hunt, William Sharp, James Colvocoresses, Allan
Stoner, and one anonymous reviewer provided insightful
comments on the manuscript. Judy Leiby and Jim Quinn
provided editorial comments. We thank Mary Enstrom
and Sherry Dawson of The Nature Conservancy (TNC) as
well as the numerous TNC volunteers who participated in
the field surveys. Meaghan Darcy and other staff members
at the Florida Marine Research Institute assisted in the
field and in sample processing. This project was funded by
Partnerships for Wildlife Grant no. P-3 from the U.S. Fish
and Wildlife Service and by the Florida Fish and Wildlife
Conservation Commission.
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289
Abstract— This study examines gene-
tic variation at five microsatellite loci
and at the vesicle membrane protein
locus, pantophysin, of Atlantic cod
{Gadus morhua) from Browns Bank,
Georges Bank, and Nantucket Shoals.
The Nantucket Shoals sample rep-
resents the first time cod south of
Georges Bank have been genetically
evaluated. Heterogeneity of allelic dis-
tribution was not observed (P>0.05)
between two temporally separated
Georges Bank samples indicating
potential genetic stability of Georges
Bank cod. When Bonferroni correc-
tions («=0.05, P<0.017) were applied
to pairwise measures of population
differentiation and estimates of FST,
significance was observed between
Nantucket Shoals and Georges Bank
cod and also between Nantucket Shoals
and Browns Bank cod. However, nei-
ther significant differentiation nor sig-
nificant estimates ofFST were observed
between Georges Bank and the Browns
Bank cod. Our research suggests that
the cod spawning on Nantucket Shoals
are genetically differentiated from
cod spawning on Browns Bank and
Georges Bank. Managers may wish to
consider Nantucket Shoals cod a sepa-
rate stock for assessment and manage-
ment purposes in the future.
Genetic differentiation among Atlantic cod
(.Gadus morhua) from Browns Bank,
Georges Bank, and Nantucket Shoals
Christopher Lage
Department of Biological Sciences
Murray Hall
University of Maine
Orono, Maine 04469
Kristen Kuhn
Irv Kornfield
School of Marine Sciences
Murray Hall
University of Maine
Orono, Maine 04469
E-mail address (for I Kornfield, contact author): irvk@maine.edu
Manuscript approved for publication
5 November 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:289-297 (2004).
The Atlantic cod (Gadus morhua) is a
migratory gadid found on both sides of
the North Atlantic. In the Northwest
Atlantic, cod are distributed nearly
continuously along the continental
shelf from Greenland to North Caro-
lina, spawning in relatively discrete,
temporally stable areas, and differ-
ent regions are regarded as different
management units defined primarily
by latitude and bathymetry ( Ruzzante
et al, 1998). Atlantic cod historically
supported economically important
fisheries in the Northwest Atlantic
(Halliday and Pinhorn, 1996). In U.S.
waters, cod are assessed and managed
as two stocks: 1) Gulf of Maine and 2)
Georges Bank and southward (includ-
ing Nantucket Shoals). Growth rates
differ between the two stocks; growth
is slower in the Gulf of Maine compared
to growth in Georges Bank (Pentilla et
al., 1989 ); each stock is exploited by the
same gear type and may show similar
biological responses towards such gear
selection. Although both stocks sup-
port important commercial and recre-
ational fisheries, each is overexploited
and remains at a low biomass level
(Mayo and O'Brien, 1998; O'Brien and
Munroe, 2001; Mayo et al„ 2002). Over-
exploitation may result in significant
life-history changes such as a decline
in time to reproductive maturity which
has been observed in Georges Bank cod
(O'Brien, 1998); such changes maybe a
compensatory response to overfishing
but may also be influenced by shifts in
underlying genetic control (Policansky.
1993).
Commercial fisheries are conduct-
ed year round, using primarily otter
trawls and gill nets. The Canadian
fishery on Georges Bank is managed
under an individual quota system.
United States cod fisheries are man-
aged under the New England Fishery
Management Council's Northeast Mul-
tispecies Fishery Management Plan
(FMP)1 as implemented by the U.S.
Federal Register, 50 CFR Part 648
(U.S. Federal Register, 2003). Under
this FMP, cod are included in a com-
plex of 15 groundfish species managed
by time and area closures, trip limits,
gear restrictions, minimum size limits,
days-at-sea restrictions, and a permit
moratorium. The FMP's goal is to re-
duce fishing mortality to levels that
will allow stocks within the complex
to initially rebuild above minimum
biomass thresholds, and, ultimately, to
remain at or near target levels.
When ecological and evolutionary
processes are responsible for stock
structuring, it is necessary to incorpo-
1 New England Fishery Management Coun-
cil. 2003. Northeast Multispecies
Fishery Management Plan. NEFMC.
50 Water St., Mill 2, Newburyport. MA,
01950
290
Fishery Bulletin 102(2)
rate them into strategies designed to manage exploited
species (Avise, 1998). High dispersive capabilities of many
marine fish often correlate with low levels of population di-
vergence over vast areas (Ward et al., 1994; Graves, 1998)
and may be particularly true for species characterized by
high fecundity, large population size, and potentially long-
distance egg and larval dispersal. Although marine fish
predominantly have high dispersal rates and low levels of
population structuring, migratory species with continuous
distributions may develop and maintain stock structure
if they show fidelity to natal spawning sites or limited
egg and larval dispersal. Fidelity to natal grounds has
been shown in Greenland-Iceland cod (Frank, 1992) and
Georges Bank haddock (Polacheck et al., 1992). Genetic
divergence between areas originates when populations are
formed or through the restriction of gene flow. Cod in some
regions are known to migrate long distances, whereas in
other regions they are nearly stationary (Lear and Green,
1984). Tagging studies in the Gulf of Maine show little
exchange between the region east of Browns Bank and
Georges Bank, and the inner Gulf of Maine (Hunt et al.,
1999); however exchange has been reported among Bay of
Fundy, southern Nova Scotia, Browns Bank, and Georges
Bank populations (Klein-MacPhee, 2002). Such exchange
among cod from different management areas may be im-
portant for stock assessments and management practices.
Determining underlying genetic structure of spawning
stocks is paramount to the conservation and management
of overexploited species.
In the last 30 years the use of molecular-based stud-
ies in fisheries science has become common (Shaklee
and Bentzen, 1998). In cod, a number of studies have
used allozymes (Moller, 1968; Jamieson, 1975; Cross and
Payne, 1978; Dahle and Jorstad, 1993), but their use and
sensitivity are limited because of weak statistical power
resulting from low levels of polymorphism and because
of processes of balancing selection (Mork et al., 1985;
Pogson et al, 1995). Mitochondrial DNA (mtDNA) char-
acterization among Northwest Atlantic cod indicates that
there is limited, albeit significant, population structuring
throughout most the species' range (Smith et al., 1989;
Carr and Marshall, 1991; Pepin and Carr, 1993; Carr et
al., 1995; Arnason and Palsson, 1996). Genetic divergence
at the vesicle membrane protein locus, pantophysin (Panl),
originally called GM798 and identified as synaptophysin
{SypT) (Fevolden and Pogson, 1997), has been reported
among populations of cod from the Northwest Atlantic
(Pogson, 2001; Pogson et al., 2001), Norway and the Arctic
(Fevolden and Pogson, 1997), and Iceland (Jonsdottir et
al., 1999, 2002). High levels of variation have been re-
ported at nuclear RFLP loci (Pogson et al., 1995; Pogson
et al., 2001), and especially at microsatellite loci (Bentzen
et al., 1996; Ruzzante et al., 1996a, 1996b, 1997, 1998;
Beacham et al., 1999; Miller et al., 2000; Ruzzante et al.,
2000, 2001). By using microsatellites, significant genetic
structuring has been detected among cod populations on
major continental shelves and on neighboring banks that
are separated by deep channels and have gyre-like circula-
tion patterns hypothesized to act as retention mechanisms
for eggs and larvae (Ruzzante et al., 1998). Although both
Browns and Georges Bank maintain persistent gyre-like
circulation patterns that may act to retain eggs and lar-
vae, they are separated by the Fundian Channel (>260 m )
which may pose a barrier to juvenile and adult migration
(Klein-MacPhee, 2002). Evaluation of Northwest Atlantic
haddock by using microsatellites showed similarly signifi-
cant stock structuring from Newfoundland to Nantucket
Shoals (Lage et al., 2001). Current assessment and man-
agement of cod in U.S. waters combine Georges Bank with
the regions to its south including Nantucket Shoals. This
study investigates genetic stock structure among cod from
this region and provides additional insight for scientists
and managers.
Materials and methods
Sampling
Samples of adult cod were collected through the U.S.
National Marine Fisheries Service and the Canadian
Department of Fisheries and Oceans groundfish surveys
between 1994 and 2000. Adult cod were obtained from each
of the following spawning grounds (Fig. 1): Browns Bank
(July 1994, n = 30), Georges Bank (March 1994, n = 48;
March 1999. >*=96; In = 144), and Nantucket Shoals
(March 2000. n = 97). Blood or tissue (or both) was obtained
from individual fish and preserved in 95% ethanol for
subsequent DNA extraction.
DNA extraction, amplification, and visualization
DNA was extracted by using either a Qiamp DNA Mini
Kit ( Qiagen Inc., Valencia, CA) or by following a published
protocol designed for nucleated blood cells ( Ruzzante et al.,
1998). Five microsatellite loci — Grnol, Gmol32 (Brooker
et al., 1994), Gmo8, Gmol9, Gmo34 (Miller et al, 2000).
and the pantophysin locus. Panl (Fevolden and Pogson,
1997; Pogson, 2001) — were used to evaluate genetic diver-
sity. Polymerase chain reactions (PCR) of all loci were per-
formed in an Eppendorf Mastercycler Gradient thermal
cycler. Final concentrations of reagents in a 25 uL PCR
cocktail were as follows: -10 ng of genomic DNA. lxPCR
buffer pH 9.5 110 mM KC1, 20 mM Tris-HCl pH 8.3, 10 mM
(NH4)2SOJ, 1.5 mM MgCl2, 200 /iM each dNTP, 0.15 nM
forward primer. 0.15 ,«M reverse primer (unlabeled for the
Panl locus and 5-labeled with a TET, FAM, or HEX ABI
dye for all microsatellite loci), and 0.75 units of Taq DNA
polymerase. PCR conditions were as follows: initial 5 min
at 95°C. 30 cycles of denaturing at 95°C for 1 min, anneal-
ing at 50°C (Gmo8, Gmol9, and Gmo34>. 55°C (Pan I), and
57°C (Gmol and Gmol32) for 1 min 30 s, and extending
at 72°C for 1 min 30 s with a final extension of 72°C for 10
min. Gmol9 and G/?2o34, as well as Gmol and Gmol32,
were multiplexed in two 25 «L PCR reactions. Flourescent
microsatellite PCR products were visualized on an ABI377
automated DNA sequencer (Perkin-Elmer Corporation.
Foster City, CA) and were analyzed by using GeneScan
(vers. 2.1) and Genotyper (vers. 2.1) software programs
(Perkin-Elmer Corporation, Foster City, CA). Panl PCR
Lage et al.: Genetic structuring of Gadus morhua
291
44
« 42° -
40 -
West longitude
Figure 1
Map of Northwest Atlantic sampling regions for Atlantic cod [Gadus morhua).
Dashed lines indicate the 100-m isobath.
products were digested with the restriction endonuclease
Dral for at least 2 hours at 37°C and visualized on 2%
agarose gels to determine presence of PanlA or PanlB (or
both) allelic variants.
Genetic analyses
Samples were tested for conformation to Hardy- Weinberg
equilibrium (HWE) expectations by the Markov chain
method (Guo and Thomson, 1992) by resampling 2000
iterations per batch for 200 batches with GENEPOP
vers. 3. Id (CEFE/CNRS, Montpelier, France; available
at http://www.cefe.cnrs-mop.fr/) (Raymond and Rous-
set, 1995); the null hypothesis tested was random union
of gametes within a population. All loci were tested for
genotypic disequilibrium across the entire data set, as well
as for individual populations by using Markov chain resa-
mpling with 2000 iterations per batch for 200 batches in
GENEPOP vers. 3. Id; the null hypothesis tested was that
the genotypes at one locus are independent from genotypes
at the other locus.
Tests of allelic and genotypic differentiation among
and between population samples were conducted by using
FSTAT 2.9.1 (UNIL, Lausanne, Switzerland; available at
http://www.unil.ch/izea/softwares/fstat.html) (Goudet,
1995); the null hypothesis tested was homogeneous distri-
butions across samples. Because alleles can be considered
as independent when samples conform to HWE, it is valid
to permute alleles among samples to test for population
differentiation. On the other hand, when HWE is rejected
within samples, alleles within an individual cannot be
considered independent, and thus permuting genotypes
among samples is the only valid permutation scheme. In
both cases, contingency tables were generated and classi-
fied by using the log-likelihood statistic G (Goudet et al,
1996). Estimates of among- and between-sample FST's
were generated according to Weir and Cocherham (1984)
with FSTAT vers. 2.9.1 and GENETIX vers. 4.04 (available
292
Fishery Bulletin 102(2)
Table 1
Genetic variation in sampled populations of Atlantic cod (Gadus morhua) and P-value (in parentheses I for among sample popula-
tion differentiation, n = observed number of alleles; H0 = observed heterozygosity; FST = the among-sample P-valueJ; bp = base
pairs; * = significant deviation from HWE («=0.05. P<0.0083); t = P <0.05; ? P= sO.OOl
Locus
In
Allelic range
Browns Bank
Georges
Bank
Nantucket Shoals
Fst
Differentiation
H0
n
Ho
n
Ho
n
Panl
2
PcmlA/PanlB
0.0385
2
0.0397
2
0.0222
2
-0.0052(0.767)
0.7820
Gmol
5
96-110 bp
0.1000
4
0.1319
5
0.1505
5
0.0019(0.307)
0.3210
Gmo8
23
118-201 bp
0.8929
17
0.8370
19
0.8444*
20
0.0001(0.437)
0.5200
Gmol9
26
120-237 bp
0.8846
17
0.8148*
25
0.7975*
23
-0.0021(0.857)
0.8320
Gmo34
11
82-120 bp
0.7778
5
0.5683
11
0.6630
7
-0.0033(0.797)
0.8400
Gmol32
21
105-155 bp
0.8333
13
0.8214
17
0.7727
16
0.0255(0.000)?
0.0010?
All loci
88
—
—
—
—
—
—
—
0.0047(0.001)?
0.0240t
at http://www.univ-montp2.fr/~genetix/genetix/genetix.
htm) (Belkhir et al.2). Significance of FST estimates was
determined with 2000 randomizations. Tests of population
differentiation and estimations of FST were calculated at
each locus individually and at all loci combined. To correct
for simultaneous comparisons, standard Bonferroni cor-
rections were applied by using a global significance level
of 0.05 (Rice, 1989).
Results
Genetic variation
Observed numbers of alleles, allelic ranges, heterozygosi-
ties, and deviations from HWE are presented in Table 1.
All tests of genotypic linkage disequilibrium were non-
significant at the global and population levels. When
Bonferroni corrections for multiple tests were applied to
tests of HWE (a=0.05, P<0.0083), the pooled Georges
Bank sample deviated significantly at Gwol9, and the
Nantucket Shoals sample deviated at Gmo8 and at Gmol9.
Interestingly, these two loci have the greatest variation
based on number of alleles and heterozygosity. In each
case, the cause of deviation was due to an excess of homo-
zygotes. Population samples that generally conform to
expectations of random mating but show a lack of concor-
dance to HWE at one or more loci may be due to a number
of processes including null alleles, genetic drift, admix-
ture, selection, and insufficient sampling (e.g., Ruzzante,
1998). Possible explanations of homozygote excess include
sample admixture ( Wahlund effect) or drift; however these
explanations are unlikely because one would expect to see
similar results at all loci. More likely explanations are the
- Belkhir K., P. Borsa, L. Chikhi, N. Raufaste, and F. Bon-
homme. 2002. GENETIX 4.04, logiciel sous Windows TM
pour la genetique des populations. Laboratoire Genome,
Populations, Interactions, CNRS UMR 5000, Universite de
Montpellier II, Montpellier i France).
presence of null alleles or selection. Deviations of HWE
at Gmo8 and Gmol9 were not observed in all population
samples, indicating that null alleles were not present at a
global-level but may be present at the population-level for
these two loci. Subsequently, any significant population
structuring observed at these loci should be viewed with
caution (see below).
Population structure
Tests of population structure are shown in Table 2. Al-
though Gmo8 and Gmol9 showed significant deviations
from HWE, they did not support any significant population
structuring even when tests of population differentiation
were performed without assuming conformation to HWE
(i.e., permuting among genotypes rather than alleles).
Heterogeneity of allelic distribution was not observed
(P>0.05) between the 1994 and 1999 Georges Bank
samples at each locus individually and at all loci combined,
thus indicating potential genetic stability of Georges Bank
cod. These samples were subsequently pooled to form
a single Georges Bank population sample to facilitate
statistical analyses by allowing for better estimations of
allele frequencies and by reducing the number of pairwise
tests. Tests of population differentiation among samples
showed significant divergence at Gmol32 (P<0.01) and
at all loci combined (P<0.05). When Bonferroni correc-
tions were applied to pairwise measures of divergence
(«=0.05, P<0.017), significance was observed between
Nantucket Shoals and Georges Bank at Gwol32 and at
all loci combined, and also between Nantucket Shoals and
Browns Bank at Gwol32. No significant differentiation
was observed between individual or pooled Georges Bank
samples and the Browns Bank sample.
Significant among-population FST values were esti-
mated at Gmol32 (0.0255, P<0.001) and at all loci com-
bined (0.0047, P<0.01). When Bonferroni corrections were
applied, significant pairwise-population FST values were
estimated between Nantucket Shoals and Browns Bank
at Gwol32 (0.0624, P<0.001) and at all loci combined
Lage et al.: Genetic structuring of Gadus morhua
293
Table 2
Genetic structuring in
sampled populations of Atlantic cod ^Gadus morhua): Above diagonal
are
P
values for
pairwise differen-
tiation. Below diagona
are pairwise
FST values; upper va
ues are for all loci combined; lower values are for Cm
3132. *=P<0.0167
1 1< = 0.05 for three comparisons); ** =
P
sO.001.
Browns Bank
Georges Bank
Nantucket Shoals
Browns Bank
—
0.5440
0.1120
0.2970
0.0020*
Georges Bank
0.0012
0.0124
0.0030*
0.0010**
Nantucket Shoals
0.0114*
0.0624**
0.0045*
0.0226**
—
(0.0114, P<0.017), and between Nantucket Shoals and
Georges Bank at Gmol32 (0.0226, P<0.001) and at all
loci combined (0.0045, P<0.0i7). Estimates of FST values
between Browns Bank and Georges Bank samples were
all nonsignificant. No significant genetic structuring was
observed in any comparison when Gmol32 was excluded
from the analysis.
Discussion
Georges Bank, a large, shallow offshore bank located along
the southern edge of the Gulf of Maine off the U.S. and
Canadian coasts (Fig. II, supports a large fish biomass.
High primary productivity and tightly bound system
energetics on the bank result in relatively stable levels of
overall biomass and total fish production, although major
shifts in species composition routinely occur (Fogarty and
Murawski, 1998). The largest spawning aggregation of
cod on Georges Bank is found on the Northeast Peak, a
gravel region that is an important habitat for the early
demersal phase of cod, and may represent a limiting
resource for this stock (Lough and Bolz 1989; Langton et
al.. 1996). The bank maintains its own circulation pattern
in a slow clockwise gyre which may act as a transportation
and retention mechanism for planktonic eggs and larvae
(Smith and Morse, 1984; Lough and Bolz, 1989). There
may be exchange of biota among regions by episodic fluxes
of shelf water carrying eggs and larvae away from the Sco-
tian Shelf and Browns Bank onto Georges Bank (Cohen
et al., 1991; Townsend and Pettigrew, 1996; Bisagni and
Smith, 1998). Once on Georges Bank, planktonic eggs
and larvae may, depending on depth, be entrained and
transported to gravel settlement sites along the western
edge of Georges Bank (Smith and Morse 1984; Lough and
Bolz, 1989; Werner et al., 1993). However, wind-driven
advection may cause egg and larval loss from the North-
east Peak and southern flank of Georges Bank (Lough
et al., 1989). Cod spawned in the Gulf of Maine usually
drift southeasterly towards Georges Bank because of the
counterclockwise Gulf of Maine gyre, but the extent of egg
and larval exchange between these regions is unknown
(Serchuketal., 1994).
Cod have been found from the surface to depths greater
than 450 meters; however few cod proximate to the Gulf
of Maine occur deeper than 180 meters (Klein-MacPhee,
2002). Browns Bank and Georges Bank are bathymetri-
cally separated by the relatively deep (>260 meters) Fun-
dian Channel which may act as a barrier to adult migra-
tion, whereas Georges Bank and Nantucket Shoals are
separated by the relatively shallow (<100 meters) Great
South Channel. Although the latter channel is probably
not a significant barrier to adult migration, it is an area of
strong recirculation towards Georges Bank and could limit
egg and larval dispersal. Tagging studies show little ex-
change of adults between the inner Gulf of Maine and the
region east of Browns Bank and Georges Bank (Hunt et
al., 1999), but limited exchange has been reported among
the Bay of Fundy, southern Nova Scotia, Browns Bank,
and Georges Bank (Klein-MacPhee, 2002).
The likelihood of determining correct population struc-
ture increases when population differentiation is sta-
ble over time (Waples, 1998). Results from this study are
concordant with observations of temporal stability of mic-
rosatellite variation observed in Atlantic cod ( Ruzzante et
al., 1996a, 1997, 2001). Tests of population differentiation
and subdivision cannot reject the maintenance of genetic
homogeneity among Georges Bank cod from 1994 to 1999
and thus may indicate some degree of temporal genetic
stability among adult Georges Bank cod.
Our results indicate that cod from Nantucket Shoals
are genetically distinct from those from Browns Bank
and Georges Bank, and cod from the two Banks are more
genetically similar. The observed lack of heterogeneity be-
tween Browns Bank and Georges Bank is consistent with
gene flow — perhaps due to episodic larval transport and
some level of limited adult exchange. Nantucket Shoals
cod may be genetically distinct because of egg and larval
isolation by entrainment in the Georges Bank gyre or be-
cause of limited movement of adults between regions (or
a combination of both). Eggs and larvae spawned on Nan-
tucket Shoals most likely do not enter the Georges Bank
gyre system; these early life history forms may be retained
on the shoals or transported to the southwest by prevailing
circulation (Fogarty and Murawski, 1998). Some North
Atlantic cod stocks have shown substantial differences in
294
Fishery Bulletin 102(2)
growth rate, reproductive capacity, and maturity sched-
ules related to temperature (Brander, 1994). Cod within
our study zone generally avoid water temperatures greater
than 10°C, but Nantucket Shoals cod are abundant in
temperatures as warm as 15°C (Klein-MacPhee, 2002).
This differential thermal tolerance may support genetic
structuring of Nantucket Shoals cod by selecting against
individuals from other areas.
Closely related gadid species such as cod and haddock
may exhibit similar patterns of population genetic struc-
turing associated with similar life histories, selective
pressures, and ecological constraints. Our results are
concordant with a previous study suggesting that had-
dock from Browns Bank and Georges Bank are genetically
similar and that haddock from Nantucket Shoals are dis-
tinct (Lage et al., 2001). However, Ruzzante et al. (1998)
observed significant genetic differentiation between cod
from Browns Bank and Georges Bank. Our results do not
agree with this previously observed heterogeneity between
Browns Bank and Georges Bank and may be due to the
examination of different loci, different sampling compari-
sons, or small sample sizes used in both studies (or to a
combination of these variables) (Ruzzante, 1998; Smouse
and Chevillon, 1998).
Among loci, the greatest genetic differentiation was
observed at locus Gmol32. Indeed, observed statistical
significance of population differentiation and FST depends
entirely on Gmol32. Length variation at Gmol32 is a func-
tion of mutations in the repetitive array and of an indel in
a flanking region (Ruzzante et al., 1998) causing bimodal
allele distributions in some populations. When compared to
other microsatellite loci, Gwol32 has shown the greatest
differentiation among other Northwest Atlantic cod popu-
lations (Bentzen et al., 1996; Ruzzante et al, 1998, 2001)
and among Northwest Atlantic haddock populations (Lage
et al., 2001) by an order of magnitude. Other loci examined
have not shown similarly strong measures of population
structuring. Observed genetic structuring may be due to
forces currently determining regional larval and adult
distributions, including bathymetry and oceanographic
patterns. However, because similar genetic structuring
is not observed at all loci, another potential explanation
is that structuring at Gmol32 is due to forces that acted
during the formation of populations rather than to forces
presently maintaining strong reproductive isolation. Once
genetic structure was generated during the formation of
these populations subsequent to the last ice age. biological
and oceanographic forces may have maintained such struc-
ture; other loci may show an absence of structure simply be-
cause it may not have been present when populations were
formed. Pogson et al. (2001) reported that the recent age
of populations, rather than extensive gene flow, may be re-
sponsible for weak population structure in Atlantic cod, and
that interpreting limited genetic differences among popula-
tions as reflecting high levels of ongoing gene flow should
be made with caution. This suggests that the observed lack
of heterogeneity between Browns Bank and Georges Bank
may not be due to high levels of ongoing gene flow, but to
similarities between recently generated populations main-
tained by small but adequate levels of gene flow.
Alternatively, significant structuring associated with
Gmol32 in both cod and haddock may suggest that selec-
tion is acting at this or at a linked locus. Although micro-
satellites themselves may be generally considered neutral,
there is, in theory, potential for physical linkage or drift-
generated linkage disequilibrium between microsatellite
and functional loci. There is however, recent evidence of
selection acting directly on microsatellite loci in tilapia in
high-salinity environments. Streelman and Kocher ( 2002 )
found a strong functional genotype-environment interac-
tion and suggested that microsatellite repeats of varying
length might induce promoter conformations that differ in
their capacity to bind transcriptional regulators. A poten-
tial selective mechanism to support the observed genetic
structuring of Nantucket Shoals cod (and haddock) may
be differential thermal tolerance, although this hypothesis
remains untested.
There is strong evidence for an unusual mix of balanc-
ing and directional selection at the pantophysin (Pa«I ) lo-
cus in cod but no evidence of stable geographically varying
selection among North Atlantic populations ( Pogson, 2001;
Pogson et al., 2001). In the present study, the Paul locus
showed little variation and no significant genetic structur-
ing (Table 1). The observed lack of geographic structuring
at Panl provides no evidence for local adaptation. How-
ever, our observations may be due to strong balancing
selection among the geographically proximate populations
examined or, if Panl is not under selection, insufficient
variation to resolve genetic structure. Alternatively, this
observed lack of genetic divergence at Panl could be due
to similarities among recently generated populations of
North Atlantic cod.
Our research suggests that the cod spawning on Nan-
tucket Shoals are genetically differentiated from cod
spawning on Browns Bank and Georges Bank. Managers
may wish to consider Nantucket Shoals cod as a separate
stock for assessment and management purposes in light of
current practices that combine Georges Bank with regions
to the south as one management unit. Cod from within the
Gulf of Maine can potentially migrate along the coast to
Nantucket Shoals where there is little geographic barrier
to adult movement. If this is true, the Nantucket Shoals
sample that we analyzed may actually be representative of
a mixed Gulf of Maine and Nantucket Shoals population.
Additional analyses are needed to evaluate the hypothesis
that Nantucket Shoals cod are genetically distinct from
cod spawning within the Gulf of Maine. Further studies
should address the issues of temporal stability and robust
sampling and should incorporate cod samples from within
the Gulf of Maine.
Acknowledgments
We thank three anonymous reviewers for their insightful
comments. We thank the captains, crews, and scientists
from the Canadian Department of Fisheries and Oceans
and the United States. National Marine Fisheries Service.
In particular, we would like to thank Chris Taggart. Nina
Shepard, and Holly McBride for assistance in obtaining
Lage et al.: Genetic structuring of Gadus morhua
295
samples. IK thanks Maryhaven for support. This work
was funded by OCE9806712 from the U.S. National Sci-
ence Foundation.
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Abstract -A major cause of the steep
declines of American oyster ( Crassos-
trea virginica) fisheries is the loss
of oyster habitat through the use of
dredges that have mined the reef
substrata during a century of intense
harvest. Experiments comparing the
efficiency and habitat impacts of three
alternative gears for harvesting oys-
ters revealed differences among gear
types that might be used to help im-
prove the sustainability of commercial
oyster fisheries. Hand harvesting by
divers produced 25-32^ more oysters
per unit of time of fishing than tradi-
tional dredging and tonging. although
the dive operation required two fish-
ermen, rather than one. Per capita
returns for dive operations may none-
theless be competitive with returns for
other gears even in the short term if
one person culling on deck can serve
two or three divers. Dredging reduced
the height of reef habitat by 34rr . sig-
nificantly more than the 23fr reduction
caused by tonging, both of which were
greater than the 6Q< reduction induced
by diver hand-harvesting. Thus, con-
servation of the essential habitat and
sustainability of the subtidal oyster
fishery can be enhanced by switch-
ing to diver hand-harvesting. Man-
agement schemes must intervene to
drive the change in harvest methods
because fishermen will face relatively
high costs in making the switch and
will not necessarily realize the long-
term ecological benefits.
Conserving oyster reef habitat by switching
from dredging and tonging to diver-harvesting
Hunter S. Lenihan
Bren School ol Environmental Science and Management
University of California, Santa Barbara
Santa Barbara, California 93106-5131
E-mail address: tenihamfflbren ucsb edu
Charles H. Peterson
Institute of Marine Sciences
University of North Carolina at Chapel Hill
Morehead City, North Carolina 28557
Manuscript approved for publication
25 November 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications office.
Fish. Bull. 102:298-305(2004).
Commercial fishing for demersal fish-
es and benthic invertebrates, such as
mollusks and crabs, is commonly under-
taken with bottom-disturbing gear that
can inflict damage to seafloor habitats
(Dayton et al., 1995; Engel and Kvitek,
1995; Jennings and Kaiser, 1998; Wat-
ling and Norse, 1998). Habitat damage
from dredges and analogous gear,
designed to excavate invertebrates
that are partially or completely buried
beneath the surface of the seafloor, is
generally much more severe than the
damage caused by bottom trawls ( Collie
et al., 2000). Furthermore, impacts on
and recovery from bottom-disturbing
fishing gear vary with habitat type;
generally smaller effects and more
rapid rates of recovery are found for
infauna in sedimentary habitats and
the most severe and long-lasting
damage in biogenic habitats that
emerge from the seafloor (Peterson et
al., 1987; Collie et al., 2000). Such bio-
genic habitats include seagrass beds,
fields of sponges and bryozoans. and
invertebrate reefs. Biogenic reefs that
provide important ecosystem services
such as habitat for other organisms
include not only tropical coral reefs
but also temperate reefs constructed
by oysters (Bahr and Lanier, 1981;
Lenihan et al., 2001), polychaetes like
Petaloproctus (Wilson, 1979; Reise,
1982), and vermetid gastropods (Saf-
riel, 1975). The recovery of such emer-
gent invertebrate reefs is a slow process
because of the relative longevity of the
organisms that provide structure for
the reef after they die and because of
the nature of reefs as accumulations of
multiple generations of reef builders.
One widespread temperate reef
builder, the American oyster iCrassos-
trea virginica, also known as the "east-
ern oyster," Am. Fish. Soc), has been
especially affected by bottom-disturb-
ing fishing gear as the target of fisher-
ies. More than one hundred years of
dredging and tonging oysters in the
Chesapeake Bay and Pamlico Sound
have caused severe degradation of the
oyster reef matrix (deAlteris, 1988;
Hargis and Haven, 1988), such that
reef area and elevation have been dra-
matically reduced (Rothschild et al.,
1994; Lenihan and Peterson, 1998).
Reduction in reef height has a serious
consequence for the oyster population
because one function of naturally tall
subtidal oyster reefs is to elevate the
oysters up into the mixed surface layer
of the estuary; this layer of mixed sur-
face water allows them to avoid mass
mortality from persistent exposure to
seasonally anoxic and hypoxic bottom
water (Lenihan and Peterson. 1998).
Reef height and structure also control
reef hydrodynamics (e.g., flow speed,
turbulent mixing, and particle delivery
and deposition), which influence oyster
population dynamics and production
(Lenihan, 1999). Consequently, har-
vest-related reef destruction and degra-
dation are considered major factors that
have led to declines of American oys-
Lenihan et al.: Conserving oyster reef habitat
299
ters in many estuaries located along the coasts of the At-
lantic Ocean and Gulf of Mexico (Lukenbach et al., 1999).
Loss of oysters and the biogenic habitat that they provide
appears from archaeological and paleontological evidence
to be a worldwide phenomenon in temperate estuaries
(Jackson et al., 2001). Oyster loss hurts not only the oys-
ter fishery but, more importantly, imperils the ecosystem
services provided by the oysters. These include, especially,
the provision of emergent habitat and reef-dependent prey
resources for many fish and crustacean populations of com-
mercial and recreational importance (Peterson et al.. 2000;
Lenihan et al, 2001; Peterson et al, 2003), the filtration
of estuarine waters (Newell, 1988), and the promotion of
estuarine biodiversity by provision of hard-bottom habitat
in fields of mobile sediments (Wells, 1961).
Because of the importance of restoring and sustaining
oysters and their reefs to serve both the oyster fishery and
the ecosystem, we designed a field test of the habitat im-
pacts of three oyster harvesting methods: dredging, tong-
ing, and hand extraction by divers (diver-harvesting). Our
study is a gear comparison, in which we assess not only
the traditional response variable of quantitative harvest
per unit of effort with each gear but also the degree of reef
habitat damage induced by the extraction of the oysters
(analogous to Peterson et al., 1983). We additionally ex-
amine the quality of the oysters harvested as a function
of gear type. The results indicate that diver-harvesting is
a more environmentally sound way of harvesting oysters
than traditional methods with dredges and tongs and may
be more compatible with conserving oyster reef habitat.
Methods
Study site
Gear comparisons were conducted on subtidal oyster reefs
in the Neuse River estuary. North Carolina (35°00'20"N,
76°33'50"W). Environmental conditions of this estuary
are well described elsewhere (Paerl et al., 1998; Lenihan,
1999). Briefly, the estuary is mesohaline, an optimal
habitat for the American oyster, and was once an impor-
tant oyster fishery ground (Lenihan and Peterson, 1998).
The estuary contains remnants of many large, natural
subtidal oyster reefs that have been intensely mined by
oyster harvesting gear for over a century. Dredging is the
most common fishing practice. Mining of the reef matrix
has combined with sediment loading and eutrophication-
associated hypoxia (Paerl et al., 1998) to degrade the
oyster reef habitats and greatly reduce oyster populations
(Lenihan and Peterson, 1998). In harvested areas, reefs
that were 2-3 m tall in quantitative surveys in the late
1800s (n = 8 reefs) were all <1 m tall in our survey con-
ducted in 1994 — a modification of habitat caused entirely
by the removal of oysters and shells during harvesting
with dredges and tongs (Lenihan and Peterson, 1998).
To help maintain oyster harvests, the North Carolina
Division of Marine Fisheries (NCDMF) restores oyster
reefs throughout many locations in the estuary by creat-
ing piles of oyster shell, or marl, on the seafloor. These
restored oyster reefs are also targeted by oyster fishermen
using dredges and, less often, using manual oyster tongs
(Marshall1).
Experimental oyster reefs
Gear comparisons were conducted in March 1996 on 16
subtidal oyster reefs that had previously been created in
July 1993 as part of a reef restoration experiment (Leni-
han and Peterson, 1998; Lenihan, 1999) in collaboration
with NCDMF. The experimentally restored reefs (referred
to as "experimental reefs" in this gear-comparison study)
were piles of oyster shells 1 m tall, 6-7 m in diameter
(28.3-38.5 m2 in area), and generally hemispherical in
shape. Natural subtidal reefs located elsewhere in the
estuary are typically larger, rectangular biogenic struc-
tures, ranging from 8-13 m wide and 20-30 m long.
Experimental reefs were constructed in 3-4 m of water on
a firm and sandy bottom, and were separated by at least
50 m. From the time of their construction until use in our
experiments, the restored oyster reefs remained research
sanctuaries, protected from commercial and recreational
shellfishing.
As oysters settle and undergo metamorphosis on the
shells of other (live and dead) oysters, to which they are
attracted by chemical cues (Tamburri et al., 1992), they
help cement together and add to the shell matrix of the
reef over years. Prior to our harvest treatments, the ex-
perimentally restored reefs were colonized by at least three
generations of oysters, many of which grew to adult size
(range of oyster sizes on experimental reefs at the start
of our experiment: 2-11 cm in shell height). Consequently,
the shell matrices of the reefs had become somewhat cohe-
sive, although probably less so than natural oyster reefs. In
February 1996, before initiation of experimental harvests,
there was no significant difference in the mean density
of adult (>1 cm in shell height) oysters (mean ±SD 179.1
±18.4/m2) among the four sets of four experimental reefs
randomly selected to receive the four harvesting treatments
(one-way ANOVA; F3 12=0.29; mean square error=285.06;
P=0.83). Experimental reefs in the Neuse River usually
had slightly higher oyster densities nearer their base and
larger oysters near the crest (see Lenihan, 1999).
Experimental harvests
We compared three types of oyster-harvesting techniques:
dredging, hand-tonging, and diver-harvesting. In March
1996, each of 16 reefs was either dredged, tonged, diver-
harvested, or left unharvested as a control (four replicates
of each treatment). Experimental dredging and hand-tong-
ing were conducted in the manner applied by commercial
oyster fishermen. The dredge, 25 kg in weight and 1 m in
width, was pulled behind a powerboat operated by NCDMF
personnel with commercial oyster-dredging experience.
Hand-tonging was also conducted by a professional oyster
Marshall, M. 1999. Personal commun. North Carolina
Division of Marine Fisheries, 3431 Arendell St., Morehead
City, NC 28557.
300
Fishery Bulletin 102(2)
fisherman, R. A. Cummings. Oysters and shell material col-
lected by dredges and tongs were separated aboard the boat
on a culling board, using the common culling techniques
(i.e., breaking apart oysters and shell with hammers, mal-
lets, and chisels). As mandated by law, oyster shell and
undersized oysters (<7 cm in height) were thrown overboard
above the reef from which they had been collected.
Hand collections of oysters were conducted by scuba
divers (J. H. Grabowski and H. S. Lenihan). Unlike profes-
sional oyster divers in Chesapeake Bay and other areas,
who rake large quantities of shell and attached oysters
into baskets that are pulled aboard ship to be culled, the
divers in this trial adopted a different method designed to
preserve reef habitat. Instead of collecting shell and oys-
ters indiscriminately, the divers chose only those oysters
that appeared alive and of market-size. Selected oysters
were hand picked from the reef and placed in heavy plastic
mesh baskets that, when full, were subsequently pulled
aboard the boat with haul lines.
To standardize fishing effort, each of the 12 harvested
reefs was harvested for 2 hours, regardless of the num-
ber of oysters collected. A 2-h harvest period for each
28.3-38.5 m2 reef was considered to be a thorough but
not excessive level of harvesting by the professional
fishermen. The numbers of oysters collected in the final
three or four dredge hauls and oyster tongs were typically
lower (by -10-20%) than the preceding dredge hauls and
tongs. This reduction in the catch per unit of effort was
great enough that a fisherman foraging optimally would
normally cease harvesting at that time and move on to
another reef. Similarly, after 2 hours of diver-harvesting,
most of the clearly visible market-size oysters had been
harvested.
Quantifying reef structure
Measurements of oyster reef height and diameter were
conducted on all 16 experimental reefs both before and
after application of the three fishing methods. In Febru-
ary 1996, the preharvest height and radius of each oyster
reef were measured by scuba divers using a custom-made
"square angle," consisting of two pieces (2 m and 5 m
long) of 3-cm wide steel angle-iron, each with an attached
1-m long carpenter's level. Both pieces of angle iron were
marked at 1-cm intervals. The 5-m long (cross) piece was
attached to the 2-m long (upright) piece by a roller-joint.
The roller-joint allowed the cross piece to move up and
down the upright piece, thus providing a measure of reef
height, and to move horizontally in relation to the upright
piece, thus providing a measurement of reef radius. The
2-m long piece also had a 0.75-m long piece of angle iron
attached perpendicularly near its bottom so that it would
not sink into the seafloor when placed upright.
One diver held the 2-m long angle iron perpendicular
to the seafloor at the edge of a reef, while the other diver
placed the 5-m long angle iron parallel to the seafloor, so
that one end rested on the highest point of a reef and the
other end met the upright angle iron at the reefs edge.
The height and radius of the reef were then measured
by recording the height at which the cross piece met the
upright piece, and the distance at which the upright piece
met the cross-piece. For each reef, a mean diameter was
calculated by measuring three separate radii (oriented
at three compass bearings, all 120° apart), multiplying
the radii by two to estimate diameters, and then averag-
ing the three diameters. This averaging procedure was
undertaken because the reefs were not perfectly circular.
Measurements of reef height and radius were repeated in
March, two-five days after experimental harvests were
completed.
Sampling oyster populations
We sampled live and dead oysters on each treatment and
control reef before (late February 1996) and immediately
after (late March) experimental harvests to estimate
the proportion of oysters incidentally killed but not har-
vested by each harvesting treatment. Specifically, oyster
data was collected within 30 hours of the application of
the harvest treatment on each replicate reef. Densities of
live and dead oysters were quantified by divers who hap-
hazardly placed eight 0.5-m'2 weighted PVC quadrats on
the reef surface at haphazard locations and recorded the
number of live and dead oysters greater >1 cm in height.
The density of dead oysters was measured by count-
ing the number of oyster shells that were articulated
and appeared relatively fresh (i.e., not black in color or
decayed), or oysters with somatic tissue exposed because
of cracked, broken, or punctured shells. Oysters with
exposed somatic tissue almost certainly die because of
predation by fishes and crabs in the Neuse River estuary
(Lenihan, 1999; and see Lenihan and Micheli, 2000).
Mean proportions of dead oysters were computed (dead
oysters/dead+alive oysters), as well as mean densities of
live and dead oysters on each reef.
Catch per unit of effort
The relative efficiency of each harvesting method was
determined by comparing the numbers of bushels (1
bushel=36.4 L) of market-size oysters taken per hour of
fishing. We quantified numbers of bushels for each har-
vesting method aboard the boat by placing oysters of legal
size in premeasured mesh baskets. After being counted,
and upon termination of the harvest trial, many of the
oysters were returned to other nearby reefs not involved
in the experiment.
Statistics
One-way analysis of variance (ANOVA) was used to com-
pare the following across harvest treatments and controls:
1) changes in mean reef height and diameter; 2) catch per
unit of effort; 3) the proportion of oysters found dead on
reefs before harvest; 4) the proportion of oysters found
dead on reefs after harvest; and 5) the absolute difference
in the proportion of oysters found dead before versus after
harvesting ([after minus before]). Data from all treat-
ment (dredging, tonging, and diver-harvesting; n = 4 for
each treatment) and the control Ui = 4) reefs were used in
Lenihan et al.: Conserving oyster reef habitat
301
Table 1
Results of one-way ANOVAs comparing differences in reef height (cm), reef diameter (cm), and catch per unit of effort (number
of oysters collected per hour) among experimental reefs harvested by different methods (dredging, tonging, diver-harvesting,
and controls), df = degrees of freedom; ms = mean square; F = F-value; P = P-value; ss = sum of squares. Partial r2= treatment
ss/total ss.
Reef height
Reef diameter
partial
Source
df ms
partial
7'2
Catch per unit of effort
partial
Harvesting treatment
3 0.09 36.90 0.0001 0.90
0.07 15.79
Residual
12 0.003
0.005
Total
15 Total ss: 0.31
0.0002 0.80
0.27
3.21
0.08
17.84 0.0001 0.11
9.64
the ANOVA. Before ANOVA, homogeneity of variances
was tested by using Cochran's method (a=0.05). All data
passed this test. After ANOVA, post hoc differences among
means were compared by using Student-Newman-Keuls
(SNK) tests (a=0.05).
Results
Reef height and diameter
Dredge harvesting on experimental reefs removed the
largest amount of shell material from the reefs, based on
the reduction of reef height (Fig. 1A) and on the qualitative
assessment of increases in numbers of oyster shells found
on the seafloor around the reefs. Hand-tonging removed
an intermediate amount of reef materials, and diver-har-
vesting removed far less shell matrix than either dredging
or tonging. All harvesting methods reduced the height of
restored oyster reefs (Fig. 1A), but dredging (34% of reef
height) and tonging (23%) had greater impacts than did
diver-harvesting (6%). ANOVA demonstrated significant
differences among harvest treatments in mean change in
reef height (Table 1); all harvest treatments induced a loss
in reef height as compared with unharvested control reefs
(SNK; P<0.05). Dredging reduced reef height more than
any other treatment (SNK, P<0.05), and tonging reduced
reef height more than diver-harvesting (SNK, P<0.05).
The reduction in reef height caused by diver-harvesting
was small (mean ±SD: 6 ±3 cm). However, diver-har-
vesting nearly eliminated the veneer of live market-size
oysters on reefs, which provides substantial structure on
reef surfaces.
Oyster harvesting either slightly increased or slightly
decreased reef diameter, depending upon method ( Fig.
IB). Reef material was apparently removed from edges
of reefs by tonging. thereby reducing reef diameter. Shell
was spread around the reefs by dredging, thereby increas-
ing reef diameter after application of that harvesting
method. The effects of oyster harvesting on reef diameter
proved significant (Table 1). Tonging significantly re-
duced reef size compared with controls and the other two
harvesting treatments (SNK; P<0.05), whereas dredging
DC
I A
A
T
B
1
C
T
D
] B
A
1
B
i T i
C
1 1
1
D
control diver-harvested tonged dredged
Figure 1
Modification of reef size and structure caused by various
harvesting techniques. (A) Mean (+SE) reduction in the
height of experimentally restored oyster reefs caused
by three types of oyster harvesting: hand-harvesting by
divers, hand tonging. and dredging. Dredges are pulled
behind power boats. Reefs were located in the Neuse River
estuary, North Carolina. Letters represent results of SNK
post hoc tests: dredged>tonged>diver-harvested>control
at P<0.05. (B) Mean ( + SE) change in the diameter of
experimental oyster reefs caused by different oyster-
harvesting techniques. Letters represent results of SNK
post hoc rests: dredged>diver-harvested>control>tonged
atP<0.05.
302
Fishery Bulletin 102(2)
Table 2
Results of one-way ANOVAs comparing differences in the proportion of oysters found dead ("mortality" i on reefs before and after
harvesting by different methods (dredging, tonging, diver-harvesting, and controls), and the absolute difference (\after-before])
in the proportion of dead oyster found before versus after harvesting, df = degrees of freedom; ms = mean square; F = F-value;
P = P-value; ss = sum of squares. Partial r2 = treatment ss/total ss.
Before mortality
After mortality
partial
Source
df ms
partial
r2
Difference in mortality
partial
Harvesting treatment
3 0.001
0.49 0.69 0.11
0.02
Residual
12 0.001
0.002
Total
15
Total ss: 0.01
7.90 0.004
0.58
II us
0.01
0.08
7.56 0.004 0.57
0.04
increased reef diameter compared to the other treat-
ments (SNK; P<0.05). The increase in diameter of
diver-harvested reefs was also greater than that for
controls (SNK; P<0.05). The substantial increase in
shell material (with oysters of all sizes) spread out on
the seafloor on dredged reefs indicates that the collec-
tion efficiency of dredges is less than 100%.
Catch per unit of effort
Catch per unit of effort of oysters included the time
required to collect oysters from the reef and the time
needed to separate (i.e., cull) them from undersized
oysters and shell material. Two of the harvesting
methods, hand-tonging and oyster dredging, are one-
man operations in which one fisherman can operate
the harvesting gear, cull oysters, and drive the boat.
Therefore, measurements of catch per unit of effort for
dredging and tonging represent the numbers of bush-
els of oysters one fisherman can collect per hour. In
contrast, scuba diving is rarely attempted alone and it
is usually necessary for someone else to tend the diver
(e.g., helping him or her in and out of the water) and
to haul oysters up to the boat when given a signal by
the diver on the reef. Divers should preferably work as a
team using the "buddy" system for safety reasons. Data for
diver-collections are given in bushels per hour collected by
one diver but hauled up to the boat and culled by a second
person.
There was a significant difference in the numbers of
bushels collected per hour by the different harvesting
techniques (Table 1). Diver-harvesting had a higher catch
efficiency than all other treatments ( SNK; P<0.05; Fig. 2).
Diver-harvesting was about 25% more time efficient than
dredge harvesting and 32% more efficient than tonging.
There was no statistically significant difference in effi-
ciency between dredging and tonging (SNK; P>0.05).
Incidental oyster mortality
The proportion of oysters found dead on experimental
reefs in February 1996 (-20%), prior to experimental
3.0 -I
1 bushel = 36.4 L
- 2.5 -
o
1 2.0-
A
T
B
harvested
B
T
I
I '■»■
sz
CO
™ 0.5-
C
control diver-harvested tonged dredged
Figure 2
Mean (+SE) number of bushels collected per hour on experi-
mental reefs by different oyster-harvesting techniques.
Letters represent results of SNK post hoc tests: diver-
harvested>dredged and tonged>control at P<0.05.
harvesting, was similar to that found on other nearby ex-
perimental and natural reefs in the Neuse River estuary
in preceding years (e.g., Lenihan and Peterson. 1998:
Lenihan 1999). In February, the proportions of dead oys-
ters did not differ among the four sets of reefs destined
to be experimentally harvested (Table 2. Fig. 3A). In
contrast, there was a large and statistically significant
difference in the proportions of dead oysters on the reefs
after harvesting (Table 2, Fig. 3A). The proportions of
dead oysters on reefs that had been tonged and dredged
were significantly greater than on diver-harvested and
control reefs (SNK; P<0.05).
Before-after-control-impact (BACI) comparison of the
change in proportions of dead oysters from before to after
harvesting ( [after— before] ), a direct estimate of incidental
mortality caused by harvesting gear, showed a similar
pattern to mortality inferred from in situ proportions of
dead oysters in March after harvesting (Table 2, Fig. 3B).
Lenihan et al.: Conserving oyster reef habitat
303
A significant treatment effect in the after period
(Table 2) indicated that the change over time in
proportion of dead oysters varied among harvest
treatments. Tonging and dredging increased the
fraction of dead among in situ oysters on reefs
(SNK; P<0.05; Fig. 3B), but diver-harvesting
did not. Immediately after harvesting, divers
found that many oysters on tonged and dredged
reefs had been broken open, severely cracked, or
punctured.
Discussion
Our comparisons of gear revealed relatively
unambiguous differences in their harvesting
efficiency for oyster dredges, tongs, and hands
of divers. Dredging and tonging had similar and
statistically indistinguishable catch efficiencies,
which seems reasonable given that both tech-
niques are commonly employed in the same loca-
tions and times in the oyster fishery. Presumably,
fishermen choose between these two gears on the
basis of personal preference, history, and skill, as
well as on the basis of water depth, bottom type,
and other factors that did not vary in our study.
Diver-harvesting of oysters resulted in higher
rates of harvest per hour, but this enhancement
in catch efficiency required the presence of two
people, one diver beneath the surface and another
person on deck involved in hauling baskets of
oysters onto the deck and culling out market-
able oysters. Because the increase in efficiency
was only 25-32%, this enhancement falls short of
the 100% required to compensate each fisherman
to the same degree that dredging and tonging pro-
vide. Nevertheless, the immediate economics of
diver-harvesting could prove competitive or even
superior if the single deckhand could serve two or
more divers, which seems likely from our experi-
ence with the workload on deck, and if the oysters
taken are priced more favorably because of larger
size or less damage, which seems possible. A
complete short-term economic comparison would
need to include higher costs for fuel in dredging
and costs of filling air tanks for diving, as well as
depreciation of gear.
This discussion of the basic efficiencies and eco-
nomics of the methods of commercial oyster fish-
ing is based upon short-term considerations only.
That short-term time perspective is the cause of
failures to achieve sustainability in fisheries quite
generally (Ludwig et al., 1993; Botsford et al., 1997). We
show that adoption of hand-harvesting by divers would
result in substantially less fishery-induced reduction in
reef height by a factor of four to six, implying greater
preservation of the habitat and thus a more sustainable
fishing practice. Our data on the changes in area covered
by reefs as a function of harvest treatment revealed only
small differences among treatments. The height of a reef
40
30
20-
10
control diver- longed dredged
harveted
Before
control diver- tonged dredged
harveted
After
14 -
B
12 -
10 -
8 -
6 -
A -
B
T
I
T
2 -
control diver-harvested tonged
dredged
Figure 3
Mortality of oysters caused by various harvesting techniques. (A)
Mean ( + SE) % dead within oyster populations on experimental
reefs before and after being harvested by three different harvest-
ing techniques: dredging, tonging, and diver-harvesting. Control
reefs were not harvested. Letters represent results of SNK post hoc
tests: dredged, after>tonged, after>all other treatments at P<0.05.
There was no difference among treatments before harvesting. (B)
Mean ( + SE) absolute difference in the % dead oysters on experi-
mental reefs before and after harvesting. Difference calculated by:
\9o after-% before]. Letters represent results of SNK post hoe tests:
dredged and tonged>diver-harvested and control at P<0.05.
is a critical variable in sustaining the reef as an engine of
oyster production because short reefs can be easily covered
by sediment (Lenihan, 1999), can be abraded by sediment
transport (Lenihan, 1999), and can fail to extend above
hypoxic bottom waters (Lenihan and Peterson, 1998).
Tall reefs (i.e., reefs not degraded by harvesting) produce
faster flow speeds and more turbulence for oyster popula-
tions, which in turn increase oyster growth rate, increase
304
Fishery Bulletin 102(2)
physicalogical condition, reduce disease incidence and
intensity, and decrease mortality (Lenihan, 1999). Con-
sequently, assessment of economics of the oyster fishery
over longer time frames would likely demonstrate higher
returns from practicing diver-harvesting, assuming that
this technique conserved reef structure. Diver-harvesting
also killed fewer of the oysters that remained on the bot-
tom, thereby sustaining future harvests better through
reduced wastage and by retention of more live oysters that
would produce more reef material.
Although the relative advantage of diver-harvesting for
conserving reef structure is evident, the absolute conser-
vation of reef habitat under the various oyster harvesting
methods is not clear from our study. Our data on impacts
of diver-harvesting revealed slight declines in reef height,
but whether these same declines would apply to an older
reef, as opposed to a recently restored reef, is open to ques-
tion. The level of cementation that binds the shells of the
reef is not as great on recently restored reefs, making them
more susceptible to degradation with physical disturbance.
Our study measured only the immediate drop in reef eleva-
tion after fishing at a level that removed a large fraction
of legally marketable oysters. In a well-managed fishery,
this drop in reef elevation would represent virtually an en-
tire season's decline, after which substantial reef growth
would occur through recruitment and growth of smaller
oysters before a new harvesting season. Thus, a healthy
oyster reef may well be able to compensate for the modest
reduction in elevation caused by diver-harvesting. If so,
oyster reef sanctuaries now being created throughout the
Chesapeake Bay (Luckenbach et al., 1999) could conceiv-
ably be opened to diver-harvesting (without implements)
and still preserve the reef services to the ecosystem. This
possibility deserves to be evaluated in order to minimize
conflicts between the goals of restoring oyster reef habitat
for conservation purposes and restoring oyster reefs for
the restoration of lost fisheries.
Application of the results of our gear comparisons to
management of oyster fisheries will likely encounter
some impediments. Although various artisanal fisheries
worldwide have employed free diving as a fishing tech-
nique and some modern fisheries, including the American
oyster fishery, involve the use of scuba, diving is not a skill
possessed by most oyster fishermen and probably is not a
method under consideration for oyster fishing in general.
In addition, the peak of oyster harvesting season on the
Atlantic and Gulf coasts is usually during winter months
(e.g., November-March) when water temperatures in
estuaries are quite low (0-10°C). Such conditions require
cold-water diving equipment (e.g., dry-suits), which will
further increase the cost of this new harvesting tech-
nique. Thus acceptance of diver-harvesting by the indus-
try would require training in diving skills and safety,
education and demonstration of the advantages of this
gear, and perhaps even investment of public funds to de-
fray costs of the transition from traditional dredges and
tongs to scuba or hookah. Because the gains of switching
to diver-harvesting accrue to the industry over the long
term, while individual fishermen who switch may suffer
economically in the short-term, gear choice represents a
modified example of the tragedy of the commons (Ludwig
et al., 1993). Only when armed with some form of owner-
ship rights and an attendant long-term perspective would
an individual oyster fisherman choose to switch to diver-
harvesting. The precipitous declines of over 99r< in oyster
landings in mid-Atlantic estuaries (Rothschild et al., 1994;
Lenihan and Peterson, 1998) mean that oyster fishermen
can hardly be expected to bear the costs of switching fish-
ing methods. Therefore, government intervention would
be required to convert subtidal oyster dredge and tong
fisheries into diver-harvesting operations for two reasons;
the need for compensation of start-up costs and the need to
overcome the tragedy of the commons. Given the dire state
of oyster fisheries today ( Rothschild et al., 1994 ), the habi-
tat destruction in these declines (deAlteris, 1988; Hargis
and Haven, 1998; Rothschild et al., 1994; Lenihan and
Peterson, 1998). the broad ecosystem services provided
by healthy oyster reefs (Jackson et al., 2001; Lenihan et
al. 2001), and the very real potential for restoring oysters
and their reefs (Luckenbach et al., 1999: Lenihan, 1999).
a mandate to switch fishing methods for subtidal oyster
fisheries could pay large dividends.
Acknowledgments
We thank Mike Marshall, Jeff French, and those many
NCDMF people working on deck for initially creating
experimental reefs to our specifications and for later
applying the experimental dredge harvesting treatment.
We thank Robert A. Cummings for applying the hand-
tonging treatment, and Jonathan H. Grabowski for help-
ing with diver-harvesting of reefs. This work was funded
by the North Carolina General Assembly through the
Cooperative Institute of Fisheries Oceanography (to C. H.
Peterson), and NOAA-Chesapeake Bay Program Oyster
Disease Program (to H. S. Lenihan, C. H. Peterson, and
F. Micheli)
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306
Abstract— Loligo opalescens live less
than a year and die after a short
spawning period before all oocytes are
expended. Potential fecundity iEP),
the standing stock of all oocytes just
before the onset of spawning, increased
with dorsal mantle length (L), where
EP = 29. 8L. For the average female
squid (L of 129 mm), EP was 3844
oocytes. During the spawning period,
no oogonia were produced: therefore
the standing stock of oocytes declined
as they were ovulated. This decline in
oocytes was correlated with a decline
in mantle condition and an increase
in the size of the smallest oocyte in
the ovary. Close agreement between
the decline in estimated body weight
and standing stock of oocytes during
the spawning period indicated that
maturation and spawning of eggs could
largely, if not entirely, be supported
by the conversion of energy reserves
in tissue. Loligo opalescens, newly
recruited to the spawning population,
ovulated about 36^ of their potential
fecundity during their first spawning
day and fewer ova were released in
subsequent days. Loligo opalescens do
not spawn all of their oocytes; a small
percentage of the spawning population
may live long enough to spawn 78% of
their potential fecundity.
Loligo opalescens are taken in a
spawning grounds fishery off Califor-
nia, where nearly all of the catch are
mature spawning adults. Thirty-three
percent of the potential fecundity of
L. opalescens was deposited before they
were taken by the fishery (December
1998-99). This observation led to the
development of a management strategy
based on monitoring the escapement
of eggs from the fishery. The strategy
requires estimation of the fecundity
realized by the average squid in the
population which is a function of egg
deposition and mortality rates. A model
indicated that the daily total mortality
rate on the spawning ground may be
about 0.45 and that the average adult
may live only 1.67 days after spawning
begins. The rate at which eggs escape
the fishery was modeled and the sen-
sitivity of changing daily rates of fish-
ing mortality, natural mortality, and
egg deposition was examined. A rapid
method for monitoring the fecundity of
the L. opalescens catch was developed.
Manuscript approved for publication
19 December 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:306-327 (2004).
Fecundity, egg deposition, and mortality of
market squid (Loligo opalescens)
Beverly J. Macewicz
1. Roe Hunter
Nancy C. H. Lo
Erin L. LaCasella
Southwest Fisheries Science Center
National Marine Fisheries Service, NOAA
8604 La Jolla Shores Drive
La Jolla, California 92037-1508
E-mail address (for B J. Macewicz): Bev Macewiczi5noaa.gov
Many loliginid squid populations
depend entirely upon the reproduc-
tive output of the preceding genera-
tion because individuals live less than
a year (Yang et al., 1986; Hatfield,
1991, 2000; Natsukari and Komine,
1992; Arkhipin, 1993; Arkhipin and
Nekludova, 1993; Jackson, 1993, 1994;
Jackson et al., 1993; Boyle et al., 1995;
Jackson and Yeatman, 1996; Jackson
et al., 1997; Moltschaniwskyj and Sem-
mens, 2000; Semmens and Moltschani-
wskyj, 2000). In California waters,
Loligo opalescens (market squid, also
known as the opalescent inshore squid
[FAO]) live only 6-12 months (Butler
et al., 1999) and die after spawning
(McGowan, 1954; Fields, 1965). Thus,
fecundity of L. opalescens is a criti-
cal life history trait and, in addition,
must be known in order to estimate the
biomass with either egg deposition or
larval production methods (Hunter and
Lo, 1997). Loligo opalescens is one of the
most valuable fishery resources in Cali-
fornia waters and is monitored under
the Coastal Pelagics Species Fishery
Management Plan of the Pacific Fishery
Management Council as market squid.
Laptikhovsky (2000) pointed out
that squid fecundity estimates would
be biased if the females spawned ova
prior to capture, if oocytes remained
in the ovary after death, or if some of
the standing stock of oocytes were lost
because of atresia. Previous field work
on squid fecundity has been limited to
the traditional method of simply count-
ing oocytes or ova (or both) of animals
taken on the spawning grounds, and
none of the biases identified by Lap-
tikhovsky (2000) have been evaluated
(Boyle and Ngoile, 1993; Coelho et al.,
1994; Guerra and Rocha, 1994; Boyle et
al„ 1995; Collins et al., 1995; Moltscha-
niskyj, 1995; Lopes et al., 1997; Lap-
tikhovsky, 2000). On the other hand,
laboratory studies (Ikeda et al., 1993;
Bower and Sakurai, 1996; Sauer et al.,
1999; and Maxwell and Hanlon, 2000)
have indicated that oocytes remain in
the ovaries after spawning and death.
Additionally, atresia was found to oc-
cur in all stages of oocytes of Loligo
vulgaris reynaudii (Melo and Sauer,
1998). Modern approaches to estimat-
ing lifetime fecundity in fishes take
the potential biases of past spawning
history, residual fecundity, and atresia
into account (Hay et al., 1987; Hunter
et al., 1992; Macewicz and Hunter.
1994; Kjesbu et al., 1998). The initial
objectives of the present study were to
estimate the fecundity of L. opalescens
by using a modern approach that con-
siders such biases, and to provide a
histological description of those aspects
of ovarian structure upon which mod-
ern fecundity analyses are based. As
our work progressed, we realized that
it might be practical to manage the
market squid fishery by monitoring egg
escapement based on fecundity mea-
surements. Thus, we added two new
objectives: to conduct a preliminary
evaluation of the use of egg escapement
as a tool for management of the market
squid fishery; and to develop a method
Macewicz et al.: Fecundity, egg deposition, and mortality of Loligo opalscens
307
0 7^
Santa Cruz 1.
Female Market Squid,
-v Loligo opalescens,
V^^ Collection sites
34°N
Santa Rosa 1
a\
Research Cruises
° Jan. 1998 R/V Jordan
* Dec. 1998 R/V Mako
Santa ^-♦O
Catalina I.
33°
■^
121°W
1 20°
119c
1 1 8:
Figure 1
Collection locations for female Loligo opalescens during two joint research cruises during
1998 by California Department of Fish & Game (CDF&G) and National Marine Fisheries
Service (NMFS) and for three immature females (triangles) collected during February
2000 (CDF&G).
to monitor the fecundity of the catch that avoids the costly
process of counting all oocytes and ova.
In this study we consider four aspects of the fecundity
of L. opalescens: potential fecundity, minimum residual
fecundity, maximum fecundity, and the fecundity depos-
ited by the average female in the population. Potential
fecundity, or potential lifetime fecundity, is the standing
stock of all oocytes in the ovary just before the onset of the
first ovulation. Because L. opalescens are semelparous, the
standing stock of all oocytes in the ovary just before first
ovulation equals their potential lifetime fecundity. Clearly,
once ovulation and spawning (deposition of ova in egg cap-
sules on the sea floor) begin, the standing stock of oocytes
can no longer be considered a measure of the potential
fecundity of the female. Minimum residual fecundity is
the minimum number of oocytes that might be expected
to remain in the ovary at death. Because ovaries of dying
L. opalescens contain oocytes (Knipe and Beeman, 1978),
only a portion of the potential fecundity will be spawned
in their lifetime. We use ancillary information on L. opal-
escens (an index of mantle condition and extent of ovarian
development) to project what the minimum residual may
be. Maximum fecundity (potential fecundity less the mini-
mum residual fecundity) is the maximum number of eggs
a female might be expected to deposit in a lifetime. We also
estimate the fraction of the potential fecundity deposited
by the average female, a key vital rate we approximate
by modeling the daily rates of total mortality and egg
deposition. Lastly, the term "standing stock of oocytes" is
used throughout this article to indicate the total number
of oocytes at all stages in an ovary. Whether the standing
stock of a particular female is to be considered a potential
fecundity, a residual fecundity, or something in between,
depends upon ancillary information (i.e., presence of post-
ovulatory follicles in the ovary, ova in the oviduct, mantle
condition, or the level of ovarian maturity).
Materials and methods
We collected Loligo opalescens during two southern Cali-
fornia research cruises in 1998 (7-15 January and 3-10
December) (Fig. 1). Most specimens were taken at night
by using trawls, jigging, or by removing them from com-
mercial purse-seine catches at sea; some specimens were
collected during the day by using bottom trawls. We mea-
sured dorsal mantle length (mm), weighed the whole body
(g), and classified the ovary and preserved it with viscera
and oviduct attached in 10% neutral buffered formalin.
To determine reproductive state we decided not to use the
familiar ovary classification systems but rather tabulated
gross anatomical characters and, later on, selected the
most useful characteristics. See Table 1 for characters
selected for scoring.
Preserved ovaries and oviducts were reclassified in the
laboratory and weighed (to nearest 0.001 g). A piece of the
preserved ovary from each of the 135 female L. opalescens
from January and the 117 females from December was
sectioned and stained (hematoxylin and eosin). Analyses
of the histological sections included identification of the
oocytes in the various development stages (I-VI) as de-
scribed by Knipe and Beeman (1978), and identification of
atresia and postovulatory follicles (Fig. 2 ). We use the term
"ova" to indicate an ovulated mature oocyte (stage VI).
308
Fishery Bulletin 102(2)
Figure 2
Slide of the ovary (stained with hematoxylin and eosin) of a mature spawning
female L. opaleseens. Bar = 1.0 mm.
Table 1
Classification system for the gross anatomical characteristics of the reproductive system of female market squid (Loligo
opaleseens).
Female organs
Character
Grade
Nidamental gland
Accessory nidamental gland
Oviduct
Ovary
Ovary
length
color
number of large clear eggs
number of large clear oocytes
number of opaque or white oocytes
millimeters
0=clear, l=whitish, 2 = pink. 3=peach.
4 =reddish-orange
l=none. 2 = 1-20. 3=21-200, 4=>200
l=none, 2 = 1-20, 3=21-200. 4=>200
l=none, 2 = 1-20, 3=21-200, 4=>200
Postovulatory follicles were classified as either new, degen-
erating, or very degenerative. We assigned the females to
one of the following reproductive categories on the basis of
the histology of their ovaries (numerical stages in Knipe
and Beeman, 1978):
Immature Ovary contains only unyolked oocytes;
oocyte development ranged from stages I
(oogonia) to IV (follicular invagination oocyte)
and requires microscopic examination.
Mature No postovulatory follicles are present. Ova-
preovulatory ries contain oocytes with yolk (stage V,
yolking begins about 1.1 mm in size); ovary
usually contains unyolked oocytes.
Mature Ovary contains postovulatory follicles
spawning ( POFs) of any degree of degeneration (none
to extensive); more than one degenerative
POF class may be present. Oocyte develop-
ment stages III— VI are often present but
stages Ic-II are rare. (29t of the ovaries
have late stage Ic oocytes and none have
any of the earliest stages, la or lb.)
In some histological sections of ovaries we saw 1-10 yolking
oocytes (development stage V) with a broken follicle layer,
and the yolk seemed to be oozing out between the other
oocytes. Because this may have been an artifact of hand-
ling, we did not use such females to estimate fecundity.
Macewicz et at: Fecundity, egg deposition, and mortality of Lo/igo opalscens
309
We used the gravimetric method (Hunter et al., 1985,
1992) to estimate the standing stock of oocytes in 98
L. opalescens ovaries. The gravimetric method overes-
timated the total number of oocytes of Loligo pealeii,
but the difference between a count of all oocytes and a
weight-based estimate was slight (Maxwell and Hanlon,
2000). We did not compare our estimates with a count of
all oocytes in the ovary because we used a portion of the
ovary for our histological examinations, and each value
is the mean of the counts from two tissue samples (aver-
age coefficient of variation between samples was 0.12).
All oocytes in each tissue sample were macroscopically
classified (Fig. 3) as either unyolked, yolked, mature, or
atretic; they were then counted by class and all stages
were summed. "Atretic" was defined as oocytes in the
alpha stage of atresia (Hunter and Macewicz, 1985b),
recognizing, however, that poor preservation can create
oocytes of similar macroscopic appearance. The number of
ova in the oviduct was also counted directly (usually when
n was less than 300) or the mean number was estimated
from two tissue samples by using the gravimetric method.
To illustrate the form of the oocyte-size distribution in
the ovary, we measured (to 0.01 mm) the major axis of
all the oocytes in one tissue sample from each ovary of
six females by using a digitizer linked by a video camera
to a dissection microscope. In all other ovaries used for
fecundity estimation, we measured only the smallest and
largest oocyte in the sample. The length of the major
axis of the smallest oocyte (D) was used as an index of
the extent of ovarian maturity. D is a crude index of time
elapsed during the spawning period — as long as oocyte
maturation continues throughout the spawning period
and no new oocytes are produced — both of which appear
to be true for L. opalescens.
To monitor body condition we cut a tissue sample disc
from the mantle using a number 11 cork borer (area of
251.65 mm2) and removed the outer dermis and the in-
ner membrane. The mantle sample discs were frozen and
subsequently dried at 56°C to a constant weight. An index
of mantle condition (C) was calculated as the weight of the
dry mantle in milligrams divided by disc surface area and
is expressed as mg/mm-.
We evaluated the extent that body reserves might be
used to support egg production by comparing dry weight
of the eggs and capsules to prespawning female body dry
weight. For these calculations we made the following mea-
surements: 1) the mean dry weight of one squid egg was
0.00177 g, including a fraction of the egg capsule because
the value is based on the dry weight of 34 egg capsules
(1-2 days old) containing 2 to 403 eggs each (total of 7341
eggs, capsules collected from La Jolla Canyon 6 July and
11 September 2000); 2) the relationship of dorsal mantle
length (L) and whole-body wet weight (Ww) for immature
and mature preovulatory females of Wu. = 0.000051L2 8086,
where Ww is in grams and L is in mm (Fig. 4); and 3) the
mean wet weight to dry weight conversion factor of 0.24
(2SE = 0.001), based on the wet and dry weights of mantle
tissue sampled from 214 mature females. The latter con-
version factor was constant regardless of mantle condition
index; apparently, in L. opalescens, starvation does not
unyolked
j?m
M
.early
yolking
~ *> KBHI
*
S
-^ smallest
^ oocyteM
(unyolked)
new-mieM
postovulator^M
Figure 3
Whole L. opalescens oocytes as viewed under a dis-
section microscope used for counting and classifying
oocytes. Bar = 1.0 mm.
result in the replacement of muscle tissue with water as it
does in fishes (Woodhead, 1960).
In addition to the specimens taken during the research
surveys, we also estimated the fecundity of 60 L. opal-
escens from the commercial catch sampled by California
Department of Fish & Game (CDF&G) during 1998 and
1999. Landed specimens were not analyzed histologically
because their ovarian tissues had begun to deteriorate
before preservation. The 60 females were selected by dor-
sal mantle length and mantle condition index to provide a
wide and uniform distribution of length and mantle condi-
tion. The number of oocytes in the ovaries was estimated
(as described above) and the number of ova in the oviducts
were predicted from oviduct weight (Fig. 5). CDF&G also
provided data on the dry mantle disc weights of 1275 ma-
ture females taken from the catch from December 1998
through December 1999 as random samples taken during
the Southern Californian Bight market squid fishery.
About 100,000 tons of market squid were landed during
this sampling period .
Modeling egg deposition
To identify egg deposition and mortality rates most consis-
tent with our current understanding of spawning biology,
we developed a model to estimate the proportion of the
potential fecundity deposited by a cohort in its lifetime.
The mean proportion of the potential fecundity deposited
is the proportion of eggs deposited weighted by the propor-
310
Fishery Bulletin 102(2)
tion of the cohort that died. Both the proportion of eggs
deposited and squid that died were expressed as negative
exponential functions. The cumulative eggs deposited up
to elapsed time t (days I for a mature female L. opalescens
is the difference of two terms: ESPl = EP- EYDt where ESP/
is the total eggs deposited by one female up to time t, EP is
the potential fecundity, and EYDl is the standing stock of
oocytes in the ovary plus the standing stock of ova in the
oviduct remaining in the body at time t. If we assume that
EYDl declines at an exponential rate from EP: EYDl = EP
e~ut, where v is the daily rate of eggs deposited, then ESPt
= Ej, ( l-e_1 0. We constructed the cumulative egg deposition
curve as Qspt~ ESPl IEP= l-e~vt. Assuming the mortality
(survival) curve for the squid is e~zt , where z is adult daily
total mortality rate iz=m+f, where m is natural and f is
fishing mortality), we computed the mean fraction of the
potential fecundity deposited (QSPt):
S
80
70
60
50
40 -
30
20
10
W= 0.000051 Z_28086
,2=0.964
n = 42
50 60 70
n 1 1 1 1 1 1
100 110 120 130 140 150 160
80 90
Dorsal mantle length (mm
Figure 4
Female squid whole body weight ( W) as a function of dorsal mantle
length (L) for the 158 females with fecundity analyses. The line
expresses the length-weight relation of females before weight
losses associated with spawning and was fitted to the combined
data for immature females (solid triangles), mature preovulatory
females (solid circles), and mature females judged by their mantle
condition to be new recruits to the spawning ground (solid circles).
Open circles indicate females that have spawned.
2000
o
y = 245x " -x"
-o 1500
>
o
pseudo r2= 0.98 ^S^ •
c
| 1000
Number of
o
o o
• St**
I I I I I I I I I I i i i i
0
12 3 4 5 6 7
Oviduct weight (g)
Figure 5
Number oi
ova in each oviduct shewn as a function of the oviduct
weight; n
equals 91 mature females, pseudo r- = 1 - residual
ss/ total ss.
| ze-zta-e-vt)dt
Qsp
dt
(!)
= 1-
zil-e'
)
(z + y)(\-e
) z + v
for large /n
where tmax is the total elapsed time (days).
The mean fraction of the potential fecundity that
remains in the average female (standing stock of
oocytes and ova) over her lifetime is 1 - Qsp, and
mean QSP is always less than one because of mor-
tality. The mean duration of the spawning period in
days is computed as the elapsed time correspond-
ing to the mean fraction of eggs deposited (QSP: Eq.
1 and by setting QSP=l-e-'''):
^sf=ln(l- QP )/(-«).
(2)
We evaluated various rates of adult daily total
mortality (z) and egg deposition (r) using these
models to determine the combination of rates that
would provide estimates of fecundity nearest to our
observed field data.
Modeling the effect of fishing effort on
egg escapement
In theory we could manage the market squid fish-
ery by monitoring egg escapement, that is, the frac-
tion of the fecundity realized by the average female.
Under such a management scheme, egg escapement
would be maintained at a specified level by chang-
ing fishing effort whenever escapement of eggs
fell below it. In this section we develop a model to
explore the relative effects of fishing effort on egg
escapement. We use this model to discuss some of
the biological issues related to using egg escape-
ment as a management tool.
In the modeling process, we follow one cohort of
spawners. The elapsed time 0 is defined as the time
when squid start spawning. The total escapement
of eggs for a given elapsed time (tk in days) is the
sum of three sources of egg escapement: Ec, the
total number of eggs deposited by mature females
in the catch; EM, the total number of eggs deposited
by mature females dying of natural causes; and
EA, the total number of eggs deposited by females
Macewicz et al.: Fecundity, egg deposition, and mortality of Lo/igo opalscens
311
alive and not taken by the fishery up to time tk, and tk
< tmax. The egg escapement rate, ReJk, up to time tk is the
sum of the three sources of egg escapement divided by the
total number of eggs that would have been spawned if no
fishery existed (E):
Ec + ESI + EA
(3)
Egg escapement rate at the maximum elapsed time Umax) is
Re,tn
EC + EM
(4)
where tk = tn
Because there are no survivors at time tmax, no eggs can
be deposited and EA is zero.
Each term in Equation 3 can be expressed as functions
of the mean cumulative number of eggs deposited up to
time tk, ESP t. =EP- EYD tk = EP ( 1— e-"'* ), and total mortal-
ity (z) of the cohort; z includes both natural morality (m)
and fishing mortality if). For practicality, we considered
cases when tk = tmax, where EA is zero. For formulas of any
tk, see appendix. The total number of eggs deposited by the
females in the catch iEc) is
'max
Ec= j E^tN0e-
m+l V
fdt
-EPN0 J (l-e-l")e-""+'"fdt
o
E~N0f
{m + f )( m+f + v)
(5)
(6)
where EP - the mean number of oocytes in the ovary per
mature female prior to spawning; and
Nn = the number of mature females at time 0.
EPN0m
( m + f X m + f + v )
(9)
The total eggs that would be deposited for the cohort
without fishing mortality is
'max 'max
E= \ E~^p~tN0me~mtdt = E~pN0 J Tl-e"1'' )me-""dt (10)
o o
E = EPN0 ■
(11)
m + v
where tmax (days) = the maximum elapsed time; and
time 0 = the time at the onset of egg deposition.
Egg escapement based on Equation 4 is
f
■ + m-
R..
( m + /')(/?? + f + v) ( w + f)(m + f + v)
(12)
m + f + v
Thus, egg escapement reduces down to a simple ratio,
involving three daily instantaneous rates: natural
mortality (m), egg deposition (v), and fishing mortality (/").
R„, =1 when there is no fishing and thus i?„„<l with
(Vmax ° '-■'I:
fishing mortality. The lower bound of the egg escapement
rate for the cohort is equal to the ratio of the eggs escap-
ing the fishery (Er) to the total eggs deposited if no fishery
existed (£):
R=ECIE.
(13)
From the fishery data, we can estimate the total number
of eggs deposited by the females in the catch (Ec) as
Ec =nc[ep-eyd)>
(7)
where EP and EYD = sample estimates from the catch;
and
Nc = the total number of spawners in the
catch.
The total number of eggs deposited by L. opalescens prior
to death due to natural mortality iEM) is
EM=jESPlN0e-'"-'"mdt =
(8)
EpN0J(l-
•")e-"'
mdt
Results
Oocyte maturation and production
Immature ovaries contain many small unyolked oocytes
with a pronounced peak at about 0.15 mm in size distribu-
tion ( Fig. 6A). As development continues and vitellogenesis
begins, the peak diminishes and shifts to a larger size
class of unyolked oocytes (Fig. 6B). Just before the onset
of spawning, the size distribution of oocytes becomes
relatively fiat without pronounced modes (Fig. 6C) and
remains so through the rest of the spawning period ( Fig. 6,
D-F). The standing stock of oocytes declines throughout
the spawning period. The minimum size of oocytes in
the ovary gradually increases after the onset of yolking,
indicating that new oocytes are not produced. We saw no
primary oogonia in our histological sections of mature ova-
ries, another indication that new oocytes are not produced
in mature ovaries. Knipe and Beeman (1978) reached the
312
Fishery Bulletin 102(2)
A No yolk in oocytes
86 mm 15 g
5646 Total oocytes
0 ova
0.719 = C
2.0 2.5 3.0
300
100
B Begun yolking
112 mm 39 g
44 10 Total oocytes
0 ova
0.711 = C
JUiiLl
i i - 1 1 1 1 1 1 1 1 1 > <
2.5 3.0
C Before 1st spawn - no POF
122 mm 39 g
3724 Total oocytes
0 ova
0.694 = C
0.5 1.0 1.5 2.0
600
500
400
300
200
100
0
600
500
400
300
200
100
0
D 2 stages of POFs
137 mm 50 g
2988 Total oocytes
88 ova
0.667 = C
..Illllllllllllll.ll.lh.lJ.. I..II. IllMl....
1.0 1.5 2.0 2.5 3.0
E 3 stages of POFs
133 mm 45 g
1 642 Total oocytes
1 446 ova
0.574 = C
■■lllllllllllH I ■■■■•■ "iHl--! ■
100
0
2.5 3.0 0 0.5
Oocye major axis diamter (mm
F Diver caught - Dying
1 36 mm 33 g
1 487 Total oocytes
0 ova
0.544 = C
lillllllllilililn.iiiinl.lii.,liiiii..i
1.0 1.5 2.0 2.5
3.0
Figure 6
Oocyte-size distribution for six female Loligo opalescens. Dorsal mantle length (mm),
body weight (g), the total number of oocytes in the ovary, and the number of ova are
indicated for each specimen. (A) Female that is immature. (B and C) Females that
are considered to be mature and preovulatory because neither has postovulatory fol-
licles (POFs) in their ovaries nor ova in their oviducts. Although the oocytes have just
begun yolking in the ovary of female B, female C has well-yolked oocytes and is close
to its first ovulation. (D-F) Females are mature spawning females and their ovaries
contained postovulatory follicles. Female F was caught by a scuba diver and appeared
to be dying.
same conclusion from their histological analysis of L. opal-
escens ovaries. Thus, potential fecundity in L. opalescens
probably becomes fixed near the onset of spawning. Not
all oocytes are deposited, however, because all spawning
females had some oocytes and many oocytes were counted
in the ovary of a dying female (Fig. 6F).
In L. opalescens the migration of the oocyte nucleus
begins early in the maturation process shortly before the
onset of vitellogenesis, whereas in fishes, migration is
near the end of vitellogenesis. The follicle of a migratory-
nucleus-stage oocyte (late stage IV) of L. opalescens has a
very large granulosa cell layer (in relation to the size of the
oocyte) and is highly folded and perhaps fully developed.
Subsequent maturation of the oocyte seems to consist
primarily of the massive addition of yolk and fluid and the
consequent stretching and unfolding of the follicle, ending
with the formation of a chorion. Apparently, the formation
of the chorion compacts the yolk because many mature
oocytes (endpoint of stage V) have a smaller major axis
than advanced yolked oocytes prior to chorion formation.
Thus, maximum oocyte size is not a good proxy for oocyte
maturation in L. opalescens and is not an indicator of the
time remaining before spawning of the next batch. More
importantly, the ovary of L. opalescens seems well adapted
for rapid oocyte vitellogenesis, maturation, and spawning
because nuclear migration and follicle cell proliferation is
completed at an early stage.
Ovulation appears to occur in small batches. The distri-
bution of oocyte sizes in spawning L. opalescens was flat
(e.g., Fig. 6, D-F) and lacked the separate and distinct mode
of hydrated oocytes that is typical in fishes. Batch sizes of
mature oocytes ranged from 5 to 246 and averaged 50 (n =72
Macewicz et al.: Fecundity, egg deposition, and mortality of Loligo opalscens
313
females). The maximum number of mature oocytes (246)
was never close to the maximum number of ova ( 1726 ) in the
oviduct. In addition, spawning females with 900 or more ova
in their oviduct had in every case three or more distinctly
different stages of postovulatory follicles in their ovaries
(Table 2). Thus the oviduct is probably filled by a series of
ovulation bouts separated by enough time to produce dis-
tinct age classes of degenerating follicles in the ovary.
Potential fecundity (EP)
Potential fecundity (EP) is the standing stock of oocytes
of all stages in the ovary of a mature female just prior
to the first ovulation. Finding females at this point in
their reproductive cycle was difficult because nearly all
specimens had already ovulated. The ovaries of 94% of
the 247 mature females, from our research cruises, con-
tained postovulatory follicles, indicating that they had
recently ovulated and would not be suitable for estimating
EP. As can be seen in Figure 7A, spawning females had
fewer oocytes in their ovaries than did mature preovula-
tory females. The relation between fecundity and squid
size is best expressed in terms of dorsal mantle length
(L) because L. opalescens lose weight during spawning
(Figs. 4, 7C). The data from thirteen mature preovulatory
females were used to establish the relationship between
potential fecundity and L:
EP = 85.62L - 6715, [r* = 34.3%]
where L = dorsal mantle length in mm.
(14)
Because the constant was not significant (P=0.146) and
the coefficient was (P= 0.036), we forced the regression
through zero which resulted in the equation
EP = 29.8L.
(15)
Thus, the average female (129 mm) according to Equation
15 had a potential fecundity of 3844 oocytes (SE = 317).
Clearly it would be preferable if the sample size for the
estimate of potential fecundity were larger because thirteen
females may not accurately represent theL. opalescens stock.
Although the landed catch provides an unlimited supply of
specimens, histological detection of postovulatory follicles
is not possible because of deterioration of the ovaries. An
alternative approach is to use mantle condition of mature
females from the catch as a proxy for the preovulatory state.
As can be seen in Figure 7C, the mantle condition index (C)
of mature females declines as oocyte maturation continues
and females deposit eggs. The mature preovulatory females
(n=ll, two discs were lost) had a mean C of 0.73 mg/mm2
(SE = 0.02). We believe that the twenty-two mature females
from the landed catch with C&0.7 mg/mm2 had not begun
to deposit eggs (Table 3). Because many of them had ovu-
lated, we combined our estimates of the standing stock of
oocytes (EY) with those of ova (ED) to calculate total fecun-
dity (EY + ED = EYD), and then regressed total fecundity
on length. Although the regression was not significant, the
average total fecundity of 3890 oocytes (Table 3) was within
Table 2
Percentage of s
the number of
of ages (stages
(POFs)intheii
pawning female market squid classed by
eggs in their oviducts and by the number
of degeneration) of postovulatory follicles
ovaries.
Number of
Number
Percentage of females
eggs in
the oviduct
of
females
1 or 2 ages
of POFs
s3 ages
of POFs
0
1
100
0
1-300
36
22
78
301-600
20
35
65
601-900
10
20
80
901-1200
7
0
100
1201-1500
2
0
100
1501-1800
2
0
100
5% of the potential fecundity of 4083 oocytes computed by
substituting the mean length of the twenty-two females
(137 mm) in Equation 15. The close agreement between
these two values increases our confidence that the potential
fecundity equation is accurate despite the low /;. On the
other hand, this rough comparison is not a substitute
for increasing the sample size of specimens analyzed
histologically, because females from the catch may have
spawned some of their ova before they were captured.
Maximum fecundity (EP — ER)
Few if any L. opalescens live to realize their full potential
fecundity (EP). The literature on L. opalescens indicates
that females that were described as "spawned out," dying,
or dead had oocytes in all stages of development except the
earliest previtellogenic stage (Knipe and Beeman 1978).
In addition, all the spawning females that we collected
had some oocytes in their ovaries. Thus, the maximum
fecundity that L. opalescens might be expected to realize
is the potential fecundity less an estimate of the number
of oocytes that might be left in the ovary at death (residual
fecundity [ER]). To estimate residual fecundity we exam-
ined the relationship of the standing stock of oocytes in the
spawning period with mantle condition index (C), size of
the smallest oocyte (D), and dorsal mantle length (L).
The standing stock of oocytes in ovaries of mature fe-
males declines rapidly with decreasing mantle condition,
between a C of 0.8 and 0.6 mg/mm2, and more gradually
over lower mantle conditions (Fig. 7C). A curvilinear rela-
tionship also exists between oocyte standing stock and the
size of the smallest oocyte (Fig. 7B). Thus the number of
past spawnings (decline in oocyte standing stock) appears
to be inversely correlated with C and directly correlated
with the extent of ovarian maturation as measured by D.
To quantify how the standing stock of oocytes changes
during the spawning period we fitted a nonlinear model to
the fecundity data of 75 mature spawning females (Fig. 7)
from our research cruises:
314
Fishery Bulletin 102(2)
12000 r
10000
8000 -
6000
4000 -
2000
0
Hrr-
0 60
\f^H^.
-H-++
80
T"
t
~T
100 120
Dorsal mantle length (mm)
— I —
140
160
2000
_ B
_ o
0000
_ o
_ o
8000
-
6000
4000
2000
0
I I I I I
+
-H-
I I
+
I I I
0.0
6000
5000
4000
3000 -
2000
1000
0.8
0.2 0.4 0.6
Major axis diameter (mm) ot smallest oocyte
1.0
0.3
0.4
0.5
— r~
0.6
-I 1-
0.7
"i r
0.8
— I r
0.9
1.0
Mantle condition index (mg/mm2)
O Immature * Mature preovulatory + Mature spawning a Diver caught
Figure 7
The number of oocytes in ovaries of 98 Loligo opalescens as a function of
dorsal mantle length (A) and the diameter of the major axis of the smallest
oocyte (Bl. In (C), the number of oocytes is plotted as a function of mantle
condition index (the dry weight per surface area of a mantle tissue disci for
87 mature females (4 discs were lost and the 7 immature were not included I.
Line in A expresses potential fecundity as a function of length (£^=29.8/,)
for the 13 mature preovulatory females (solid circles); open circles represent
immature females; plus signs represent spawning females; and the triangle
represents a dying mature female.
ER = 30283e'_1 24W ■ B 19('- 0.024i + 0.059LC)
where C = mantle condition index;
D = size of the smallest oocyte; and
L = dorsal mantle length.
(16) Substituting into the model (Fig. 8) the maximum ob-
served D (0.771 mm) and the minimum observed C (0.323
mg/mm2) from our research survey data set, we estimated
that a female L. opalescens with L of 129 mm may have
a minimum residual fecundity of 834 oocytes (CV=0.12).
Macewicz et al.: Fecundity, egg deposition, and mortality of Loligo opa/scens
315
Table 3
Mean fecundity, gonad weight, and dorsal mantle length fo
ports December 1998 to December 1999.
■ 60 mature
female market squid (Loligo
opalescens) sampled at the
Mantle condition
(mg/mm2)
ndex
(
Fecundity
mean numberl
Mean
gonad weight
Cg)
Dorsal
mantle length
( mm )
Number
of
females
Oocytes
in ovary
(EY) '
Ova in
oviduct
(ED)
Total
(EYD)
Class
Mean
Mean
Range
0.347-
-0.499
0.432
1134
231
1365
2.215
132
106-
-146
22
0.500
-0.699
0.613
2072
522
2594
4.959
125
102-
-154
16
0.700-
-0.951
0.824
2589
1301
3890
8.988
137
106-
-160
22
0.347-
-0.951
0.624
1917
701
2618
5.397
132
102-
-160
60
A 129-mmL. opalescens with a potential fecundity of 3844
oocytes would have a maximum fecundity of 3010 eggs
(3844-834 eggs) or about 78% of the potential fecundity.
Very few females would be expected to deposit 78% of
their potential because this maximum is based on extreme
values for both mantle condition index and ovarian matu-
ration. In a much larger set of mantle samples from the
catch (Table 4), only 1.5% of the females had values of
C less than 0.35 mg/mm-. Clearly very few squid live to
deposit 78% of their potential fecundity.
Another approach is to count the number of oocytes
remaining in the ovaries of females presumed, from their
behavior and appearance, to be dying. Although L. opal-
escens has been observed to be dying or dead on the bot-
tom on video from a remotely operated vehicle (Cossio1),
capturing such females was not attempted at the time. A
female L. opalescens (136 mm) believed to be dying was
opportunistically collected by a diver 6 July 2000 on the
La Jolla Canyon spawning grounds (McGowan, 1954).
There were no ova and the ovary contained 1487 oocytes —
substantially more oocytes than our estimate of the mini-
mum residual fecundity. In fact, the female had deposited
only about 63% of her potential fecundity.
Role of body reserves
We used weight relationships to evaluate the extent to
which body reserves might be used to support the repro-
duction of spawning female L. opalescens. In these crude
energetic calculations we did not include metabolism,
conversion efficiencies, or caloric values of tissues. We
used the average dry weight of squid eggs, length to body
weight conversion, potential fecundity equation, and
the conversion factor from wet to dry mantle weight. We
assumed preovulatory mantle condition index (C) for an
average mature female of 130 mm was 0.798 mg/mm2,
the mean for values (/!=41) of C > 0.700 mg/mm2 in the
Table 4
Distribution of mantle condition index for 1275 mature
female L. opalescens sampled from the landed catch from
December 1998 to December 1999.
Mantle condition
index ( mg/mm2 1
Mature females
Number
Percentage
0.263-0.299
4
0.3
0.300-0.349
15
1.2
0.350-0.399
29
2.3
0.400-0.449
54
4.2
0.450-0.499
91
7.1
0.500-0.549
128
10.0
0.550-0.599
207
16.2
0.600-0.649
210
16.5
0.650-0.699
216
16.9
0.700-0.749
137
10.7
0.750-0.799
94
7.4
0.800-0.849
53
4.2
0.850-0.899
18
1.4
0.900-0.949
10
0.8
0.950-0.999
6
0.5
1.000-1.043
3
0.2
1 Cossio, A. 2000. Personal commun. Southwest Fisheries
Science Center, National Marine Fisheries Service. 8604 La
Jolla Shores Dr., La Jolla, CA 92037
our fecundity data set. We calculated that the potential
fecundity of a 130-mm L. opalescens (i.e., 3874 encapsu-
lated eggs) has a dry weight of 6.86 g which is equivalent
to 64.8% of the whole-body dry weight (10.58 g) of that
female just before spawning. If mantle condition is reduced
in proportion to the dry weight of all the eggs, our hypo-
thetical female would have a C of about 0.281mg/mm2
(0.798x[(10.58-6.86)/10.58]). This end point (C=0.281,
egg=0) and the beginning point for the mature preovula-
tory female (C=0.798, eggs=3874) create a hypothetical
316
Fishery Bulletin 102(2)
2000
1500
1000
500
L= 129mm Er
- C= 0.323 mg/mm2
30283e<'1 24D-6.19C-0.024L+0.059f.C)
Maximum Observed D
(0.771) b
i
I
.Yolking
Begin
Ovulation
t — i — i — i — i — i — rn — I — I — I — I — I I I I I I I I
0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
Maior axis of smallest oocyte (D) (mm)
2000 -
1500
1000 -
500 -
L = 129mm
D= 0.771mm
Minimum Observed C
(0.323)
0.2
0.3
0.4
T
— I —
0.8
0.5 0.6 0.7 0.8
Mantle condition index (C) (mg/mm:
"l 1
1.0
Figure 8
Changes in the standing stock of oocytes predicted by Equation
16 (equation also given at top of panel) when major axis of small-
est oocyte (D) is varied and mantle condition index (Cl held con-
stant (upper panel), and when C is varied and D held constant
llower panel). The major axis size of oocyte when yoking begins
and when ovulation begins is also indicated, as are the maximum
observed D and minimum observed C. Substitution of the latter
two values into the equation yields the standing stock of oocytes of
females close to the end of their reproductive activity and is consid-
ered to be a minimum estimate of residual fecundity.
line that expresses oocyte standing stock for the average
mature female of 130 mm as a function of mantle condi-
tion. In addition to the hypothetical line, we plotted the
total standing stock of oocyte and ova (EYD) and mantle
condition index for all 147 mature females used for direct
fecundity determinations (Fig. 9). Our hypothetical line,
based on direct proportionality between egg dry weight
and body dry weight, follows the general trend in the
data, indicating that energy reserves in mantle tissue
may largely support the production and spawning of
eggs. Of course, actual energy costs would be higher
because metabolism, other somatic tissue, and conversion
efficiency of mantle tissue to eggs are not considered. The
lowest observed C in the fecundity data set was 0.323 and
the lowest C observed in the 1275 mature females from
the landed catch was 0.263. Using the above preovulatory
C (0.798 mg/mm2), we determined that these values of C
are equivalent to 60% and 67% losses in body dry weight
for these individuals. Fields (1965) suggested body wet
weight declined by as much as 50% , which is consistent
with our results.
These rough calculations support the long held belief
that oocyte maturation is supported primarily by body
reserves. Some feeding occurs during spawning; L. opal-
escens has been observed feeding under lights at night
on the spawning grounds (Butler2). Maxwell and Hanlon
(2000) observed L. pealeii feeding between egg-laying
bouts when they were held in the laboratory. Feeding be-
tween spawning bouts by the more robust spawners that
may migrate on and off the grounds each day seems quite
2 Butler, J. 2000. Personal commun. Southwest Fisheries
Science Center. National Marine Fisheries Service, 8604 La
Jolla Shores Dr., La Jolla, CA 92037.
Macewicz et al.: Fecundity, egg deposition, and mortality of Lohgo opalscens
317
7000
>
o
■n
6000
t
CO
W
5000
>N
4000
o
o
3000
<1)
F
2000
-j
r
"Hi
1000
o
-
0
-70
A
A
A
° *A
4 ~° o
a ^ o ^ °^ <A
^kK^A °:
A A AO<^§^^ O
o2*A^r^^AO
A±£* \ O *
^^ 30 0 % loss
l l i i i i of body wt.
I I I I I I I i
0.2
0.4 0.6 OS
Mantle condition index (mg/mm2)
1.0
Figure 9
Standing stock of oocytes and ova as a function of mantle condition
index for 60 mature females taken in the fishery (triangles) and 87
mature females taken in research surveys (circles I. The line (not
drawn to the data points plotted) represents a possible relation if
losses in body weight were equivalent to the weight of the spawn
released, computed for an average female (130 mm) where the
starting point is her potential fecundity of 3874 oocytes and ends
with 0 eggs and a mantle condition index of 0.281 mg/mm2.
possible, but it seems unlikely for the nearly exhausted
L. opalescens that are near the end of their life.
Longevity and egg deposition rates
Inferences regarding the longevity of adult spawning L.
opalescens are the best proxy we have for the mortality
rates of spawning adults. Previous observers (McGowen,
1954; Fields, 1965) suggested that females deposited all
their eggs in one night and death soon followed. On the
other hand, it is unreasonable to expect that a reduction
of 609 in body weight and the maturation and deposition
of up to 78% of the potential fecundity could take place
in 24 hours. Our data on fecundity and mantle condition
show an initial rapid decline in the number of oocytes
followed by a more gradual decline (Fig. 7C), indicating
an initial period of intense egg laying may be followed
by a longer one where fewer eggs are deposited. It is also
important to recognize that ovaries of spawning animals
contain a wide range of oocyte sizes (Fig. 6), includ-
ing many small unyolked oocytes (0.3-1 mm) that may
mature and be deposited during the spawning period.
It is unlikely that all these processes (body resorption,
dynamic changes in rates of egg deposition, and matura-
tion of small unyolked oocytes) could occur in one 24-
hour period. Spawning periods longer than two weeks
also seem unlikely because mature L. opalescens females
may require extensive feeding periods and prolonged ab-
sences from the spawning grounds; these behaviors are
inconsistent with our energetic analysis in the preceding
section. Our analysis indicated that the observed reduc-
tion in eggs can be fairly well explained by the observed
reduction in squid dry weight.
Egg deposition rates provide another way to infer the
longevity of spawning squid. The best evidence for the
rate of egg deposition is provided by females judged, on the
basis of their high mantle condition ( C^O.700 mg/mm2), to
be new recruits to the spawning grounds. Considering only
those new recruits that have ovulated (postovulatory fol-
licles present or ova in the oviduct ), the difference between
their average oocyte standing stock (£y=2571) and their
average potential fecundity (£P=4020) was equivalent to
a reduction of 1449 oocytes or 36% of their potential fecun-
dity (Table 5). If the difference is spawned in 24 hours or
less, then 36% can be considered as an average for the first
day of egg deposition. Instead of using the reduction of oo-
cyte standing stock, one could consider the standing stock
of ova (ED ) to be equivalent to the first day ( 24-hour period )
of spawning in these new recruits. Their average ED was
1073 or 27% of their potential fecundity. Thus depending
on the criteria, the first day of spawning might be 27% to
36% of the potential fecundity. We prefer 36% because it is
unaffected by any losses due to egg deposition.
The standing stock of ova (ED) of spawning females
with lower mantle condition (C<0.7 mg/mm2) averaged
9% of their potential fecundity. If the average ED from
these females is a crude measure of daily egg deposition
rates after the first day, then we calculate it would take
seven additional days [U00%-36%)/9%] to use up the
remaining potential fecundity or a total spawning period
of eight days. Eight days is an extreme value because
an adult L. opalescens has never been taken with zero
oocytes. The minimum residual fecundity was 22% of the
potential which is roughly equivalent to about two days
of egg deposition. Thus, six days may be a better guess
of the maximum longevity of spawning L. opalescens.
318
Fishery Bulletin 102(2)
Probably very few females would be expected to survive
six days because only a small percentage of the spawning
population (Table 4) met the mantle criteria for minimum
residual fecundity.
In summary, our best guess of the maximum longevity
of squid on the spawning grounds is about six days. Our
best description of daily egg deposition is a rate that ends
the first day with 36% of the potential fecundity deposited
and averages about 9% of the potential per day over the
remaining five days and where only a small percentage
of the females live to deposit 78% or more of their poten-
tial fecundity.
Egg escapement
We examine the spawning dynamics of Loligo opalescens
from the standpoint of possibly using fecundity of the
catch to monitor and ultimately regulate escapement of
eggs from the fishery. The key variable in this approach
is the fraction of the potential fecundity that is actually
deposited as eggs on the bottom because this value can be
directly estimated from the fecundity of the catch. Two
other important parameters are the daily rate of total
mortality (2) on the spawning grounds and the daily rate
of egg deposition (y). Neither of these parameters can be
directly estimated but they are approximated by values
that are most consistent with our observations by using
a model (Eq. 1). Our observations consist of the fecundity
of the catch and the inferences regarding longevity and
egg deposition, presented in the previous section. We use
our approximations for egg deposition and total mortality
in a second model (Eq. 12) to gain an idea of how natural
mortality and fishing mortality may affect egg escape-
ment. Lastly, we present a rapid method for monitoring
the fecundity of the catch which does not require direct
counting of oocytes or ova.
Fraction of the potential fecundity spawned (Q5P) In a
spawning population of L. opalescens, the mean standing
stock of oocytes and ova (EYD), when expressed as a frac-
tion of potential fecundity, is equivalent to the fraction
of the potential fecundity of the population that remains
in the spawners (EYDIEP). When subtracted from one (1-
[EyD/EP] ), the difference becomes the fraction of the poten-
tial fecundity of the population that is actually spawned
(Qsp). For this interpretation to be correct, samples must
be randomly drawn from the population and represent all
spawners according to their abundance on the spawning
grounds — from the newly recruited to those that have
been spawning for extended periods.
Neither the females taken from our research cruises nor
those used to estimate fecundity from the landed catch
were random samples of the spawning population. First,
not all of the specimens taken during the two research
cruises were from the spawning grounds. Second, the 60
females from the commercial catch were not randomly
chosen but were selected to represent a full range of L
and C. However, by weighting our fecundity estimates by
a random sample of mantle condition from the fishery, it
was possible to approximate a random fecundity sample of
spawners. The population we used for weighting was based
on the mantle condition index (C) of 1275 randomly taken
specimens from the commercial catch sampled December
1998 through December 1999 (Table 4). The weighted
and unweighted mean standing stocks of oocytes and ova
(EYD) were similar (Table 5), indicating that our previous
selection of specimens by C did not introduce a large bias.
For the unweighted data, EYD was 2541 and was 2599
Macewicz et al.: Fecundity, egg deposition, and mortality of Lo/igo opa/scens
319
Table 6
Estimates of number of days of egg deposition, the mean number of eggs deposited, mean standing stocks of oocytes and ova
remaining in female L. opalescens, mean number of eggs deposited at the end of the first night (all means are expressed as a
fraction of the potential fecundity), for various combinations of possible egg deposition (u) and total adult mortality (z) rates.
Model provided estimate nearest observed data when z = 0.45, v = 0.25, and tmax = 8 days.
Daily
total
mortality
Cz)
Daily
egg
deposition
rate
(v)
Fraction of
potential
fecundity
deposited
Qsp
(Equation li
Fraction of
potential
fecundity
remaining
in females
a-Qsp)
Mean number
Fraction of
of nights
eggs deposited
of egg
at the end
Days
deposition
of the
to reach
tQsp
first night
78% eggs
(Equation 2)
Q-e-")
deposited
2.45
0.221
6.057
2.13
0.362
3.365
1.88
0.478
2.329
1.67
0.221
6.057
1.48
0.362
3.365
1.33
0.478
2.329
1.08
0.221
6.057
0.99
0.362
3.365
0.91
0.478
2.329
0.36
6.0
0.2
0.2
0.2
0.45
0.45
0.45
0.8
0.8
0.8
Observed
0.25
0.45
0.65
0.25
0.45
0.65
0.25
0.45
0.65
0.458
0.617
0.706
0.341
0.486
0.580
0.237
0.359
0.447
0.326 (SE 0.075)
0.542
0.383
0.294
0.659
0.514
0.420
0.763
0.641
0.553
0.674
when the data were weighted by the distribution of mantle
conditions in the catch. The mean fraction of the poten-
tial fecundity deposited (QSP) by L. opalescens was 0.326
(1-2599/3859). That much of the fecundity had escaped
(eggs were deposited) before the market squid were taken
by the fishery does not seem unreasonable because 22-
36% of EP may be deposited during the first day of spawn-
ing. The mean QSP is an important index because it mea-
sures egg escapement as a fraction of potential fecundity
over its lifetime (Eq. 1). It is used in subsequent sections
to identify a daily total mortality rate and egg escapement
rate for the average female in the population that best
characterizes the sampled L. opalescens population.
Preferred mortality and egg deposition rates We used
Equation 1 to evaluate which combination of a range of
plausible values for the rates of daily total mortality (z of
0.2, 0.45, and 0.8) and daily egg deposition (v of 0.25, 0.45,
and 0.65) provides an estimate closest to observed Qsp
(ESPIEP) (Table 6). The combination of an adult daily total
mortality (z) rate of 0.45, a daily egg deposition (v) rate of
0.25, and using a £max of 8 days gave an estimate that was
most consistent with the observed value for QSP of 0.326
(Table 6, Fig. 10). This combination of rates also gave an
egg depletion of 78% of the potential fecundity in 6 days
which was consistent with our best guess for maximum
longevity and maximum fecundity. On the other hand, the
model (using 1-e-"' and t=l) predicts that about 22% of the
potential is deposited by the end of the first 24 hours (day 1)
which is less than our preferred estimate (36%) based on
the reduction in standing stock of oocytes but is closer to the
one based on the standing stock of ova ( 27%). A possible bio-
logical explanation for the difference might be that some of
the ova produced during the first day of deposition might
remain in the oviduct and then be deposited on the second
day. Regardless of the uncertainties regarding the fit for
the initial day of egg deposition, a daily total mortality rate
of 0.45 and daily egg deposition rate of 0.25 are most con-
sistent with the field data known at the present time. This
means that the average spawning period is very short; the
average female lives only 1.67 days after spawning begins
(ln(0.659)/-0.25; Eq. 2). It is interesting that 1.67 days for
the average animal is not a radical departure from Fields's
(1965) original conclusion of a single night of spawning.
Egg escapement from the fishery In L. opalescens, where
the fishery targets spawning adults that die after spawn-
ing, it is important to know the effect of fishing mortality
on the egg escapement rate with respect to the lifetime
fecundity deposited, RL, t (Eq. 12). However, not all terms
in Equation 12 are observable and it may be practical
to manage the fishery by monitoring the fraction of the
potential fecundity that is deposited on the bottom (QSP=
1-[EYD/EP]). Nevertheless, we examined the potential
effects of fishing mortality if) on the egg escapement rate,
Bf(mii, when natural mortality (m) is 0.1, 0.25, or 0.4, and
egg deposition (v) is 0.25, 0.45, or 0.65 (Fig. 11). Because
our preferred rates from the previous section are v = 0.25
and 2 = 0.45, then m is <0.45 with fishing because z = m
+ f. If we use v = 0.25 and set daily natural mortality rate
high (»i=0.4), then /"is 0.05 andi?f Jum is 93%. Doubling the
fishing mortality (to 0.1) produces an absolute difference of
6% in egg escapement (Fig. 11C). Thus at a high m of 0.4,
escapement is relatively insensitive to changes in daily
320
Fishery Bulletin 102(2)
fishing mortality. At lower natural mortalities, a
change in fishing mortality has a greater effect on
escapement. At m =0.1 and /'= 0.35 i?e,,malI is 50%.
Doubling the fishing morality to 0.7 Retnm would
be 33%, producing a loss of 17% in escapement
(Fig. 11A). Increasing the rate of daily egg deposi-
tion (v) from our preferred value of 0.25 to 0.65 also
diminishes the effect of fishing mortality on escape-
ment but the effect of fishing on egg escapement is
most marked at the low natural mortality of m =
0.1 and is relatively minor when natural mortality
reaches /?; = 0.4. Thus, uncertainties regarding the
true initial values of egg deposition seem relatively
unimportant at these high mortality rates. It is
important to remember that in this discussion that
we are discussing daily mortality rates that last
only a few days or weeks of the life of a semelparous
animal; hence the rates are very high and resemble
the typical daily mortality rates of small pelagic fish
eggs (Alheit, 1993) that also exist for short periods.
Cost effective methods for monitoring fecundity If
egg escapement were adopted as a monitoring and
management tool for the market squid fishery, a
cost-effective method for monitoring fecundity of
L. opalescens would be needed. A direct estima-
tion of the standing stock of oocytes in an ovary by using
a microscope and video system (as preformed in this
study) is too time consuming for routine monitoring of the
fishery because it takes about 4 hours per specimen.
Our first approach for an indirect estimator was to
use the measurements routinely taken by CDF&G staff
who sample the catch. These measurements were dorsal
mantle length, mantle condition index, and an oviduct
classification system for approximating the numbers of
ova. To estimate the oocyte standing stock (EY) of the
catch females, using only length and mantle condition, we
fitted a nonlinear model to the data for all squid classed
1.0
0.9
0.8
z=0.45
~ v=0.25
0.78 of potential
fecundity deposited^^ —
0.7
^ up to 6.06 days
0.6
1 - e-"^-^"^
0.5
0.4
0.3
'm 67 n ^41 mean duration of spawning,
( -o . u.j ) mean fracti0n eggS deposited
0.2
0.1
-/^^
0
I I I
1 1 1 1 1 1 1 1 1 1 1 1 1
Elapsed time (/, days)
Figure 10
The cumulative egg release curve (solid line) and the density func-
tion of longevity on the spawning grounds of adult females I dashed
line) of Loligo opalescens for a total mortality rate (z) of 0.45 and
a egg release rate (v) of 0.25. The plotted solid circle represents
mean egg deposition estimated by the model as a proportion of the
potential fecundity and model estimate of the mean duration of
the spawning period.
as mature (spawning individuals and pre-ovulatory) in our
1998 research survey data set. This yielded the equation
£v= 220.453ell-99C + 0-0079il, (17)
where L = dorsal mantle length; and
C = mantle condition index.
Equation 17 for EY explains only 33% of the variability
within the survey data set (n=90) and therefore is rather
imprecise. Using this model we estimated EY to average
about 2221 oocytes in the ovaries of the mature females
l.U
m=0.10
0.9
r\\s
0.8
0.7
\ v=0.65
W v=0.45
v "••-.. N. v=0.25
0.6
0.5
0.4
V^\
\^ ""••••■""""~~
0.3
0.2
1
I I I I I I I I I
0.0
0.2
0.4
0.6
1.0
Fishing mortality (I)
Figure 11
The egg escapement rate, R, , ( Eq. 12) of L. opalescens as a function of various daily natural adult mortality rates (in ), daily egg
deposition rates (rO, and daily fishing mortality rates if). In each panel, the solid circle indicates the /'value for preferred values:
2 = 0.45 and v = 0.25.
Macewicz et al.: Fecundity, egg deposition, and mortality of Loltgo opalscens
321
(n.=1275) sampled from catch during the period
1998-99 (Fig. 12); this estimate is equivalent
to approximately 58% of the potential fecundity
calculated from mean length (129 mm).
Our second approach was to estimate total
fecundity (EYD, standing stock of oocytes and
ova) indirectly using the combined formalin wet
weight of the ovary and the oviduct, in addition to
mantle condition. Combining ovary and oviduct in
one weight is more efficient than weighing them
separately because much less time is required for
dissection. Dorsal mantle length was also con-
sidered as a variable but it was not significant.
The final equation for the total standing stock of
oocytes and ova in a mature female squid is
EYD = 378.28e12 33C + ° 2447G - °-24CG>
(18)
where C = mantle condition index; and
G = gonad (ovary and oviduct) weight.
5000 r
4000 -
o 3000 -
2000
1000
EY = 220.453e<1 99C + 000791.)
for L= 129 mm
Mature Females
Collected Dec. 1998-Dec.1999
n= 1275
Mean C (0.625) ±2SE
1 — 1 — 1 — r
0.2
0.3
0.4
1 — 1 — r~
0.5 0.6
~~ 1 — 1 — r
0.7 0.E
~\ T~
0.9
1 1
1.0
Mantle condition index (C) mg/mm2
The predicted fecundity related well to the observed
with a pseudo r2 of 0.60 (df=143). We also used
generalized additive models to estimate fecundity
(GAM, pseudo r2=0.64), as well as regression on
the first principal component which explained 867r of the
total variation (pseudo r2=0.55). Although the GAM gave
a slightly higher pseudo r2 than the parametric nonlinear
regression, we chose the later for easier interpretation and
implementation. A pattern existed in the residuals from our
model (Fig. 13); the model overestimated some fecundities
at high mantle condition and underestimated fecundity
at low mantle condition. This pattern in the residuals is
probably related to the differences in density and size of
oocytes in the ovary. Regardless of the minor problem with
the residuals, this proxy (Eq. 18) for the standing stock of
oocyte and ova is preferred because it gives a much more
precise estimate at the minor additional cost of preserv-
ing and subsequently determining the combined weight
of ovary and oviduct. Although formalin weight of ovary
and oviduct are not presently monitored in the fishery, it
is a variable that could be added to fishery protocols at a
minor increase in cost. Another benefit of this more pre-
cise approach using EYD is that oviduct is included in the
estimate. If an estimate of the removal of fecundity by the
fishery is needed, ova must be included. Because ova are not
included in Equation 17, to add them requires using the ovi-
duct classification system (Table 1) to estimate the average
number of ova — a system that is imprecise but cheap. One
could, of course, use Equation 17 for EY and either count the
ova in the oviduct or weigh the oviduct, but that would take
more work than applying Equation 18 for EYD.
Discussion
Potential fecundity
Our estimate of Loligo opalescens potential fecundity is
based on a regression of the standing stock of oocytes on
Figure 12
Standing stock of oocytes in the ovary (£>•) as a function of mantle
condition index (C) for a 129-mm mature female L. opalescens as
predicted by Equation 17 (equation also given on top of panel; L is
dorsal mantle length). Dashed lines are ±2SE. The mean EY for the
females taken in the fishery was 2221 oocytes.
dorsal mantle length for mature preovulatory females
having yolked oocytes in their ovaries. The accuracy of
this approach depends upon the assumption that these
females are at the point in life when the standing stock
of oocytes in their ovaries is equivalent to their potential
lifetime fecundity. This key assumption would not hold if
some of the mature squid classed histologically as pre-
ovulatory had in fact spawned. We do not know how long
postovulatory follicles are distinguishable from atretic
structures in the ovary of L. opalescens and, as far as we
know, the rate of degeneration has not been determined for
any loliginid. We know from our work on anchovy (Hunter
and Goldberg, 1980; Hunter and Macewicz, 1985a),
although it is not a cephalopod, that postovulatory follicles
are distinguishable from atretic structures in the ovary of
anchovy for about two to three days after spawning when
the water temperature is about 16°C. This means that for
undetected spawning to occur in L. opalescens, the inter-
val between ovulation periods would likely need to exceed
three days. This may be a minimum estimate because L.
opalescens spawn at lower temperatures (9-13 C, Butler2)
than do anchovy. Definitely a laboratory study on the
rate of degeneration is necessary because postovulatory
follicles in fish degenerate slower at lower temperatures
(Fitzhugh and Hettler, 1995). In addition to the absence
of postovulatory follicles, the oviduct must be empty for a
spawning act to be undetected. Undetected ovulation and
spawning seems unlikely because females with multiple
stages of postovulatory follicles were common (87% of 247
mature females), females with only old postovulatory fol-
licles were not detected, and the average life span on the
spawning grounds may only be a few days.
Atretic losses of oocytes are another possible bias in
estimating potential fecundity. Atresia (degeneration and
resorption of an oocyte and its follicle) appears to be a
322
Fishery Bulletin 102(2)
3000
2000
1000
0
CD
>
o
-1000
+
(0
-2000
/
*..
• • T* . I* •• • *
0.3 0.4
0.5
— i 1 1 1 —
0.6 0.7 0.8 0.9
1.C
Mantle condition index (mg/mm2)
3000 1-
2000-
1000-
0
-1000
-2000
• • • V * • • . .
L*J" ^ — ^* *a wm ^ M • • ■
0
0.0006 r
>. 0.0004 -
0.0002
~1 r
2
1 1 1 r
6 8
Gonad weight (g)
10
- 1 1 1
12 14
0.0b
-2000
-1000
1000
2000
3000
Residuals
Figure 13
Residual plots of number of oocytes and ova from the equation
EYD = 378.28e(2 33C + 0 2447°-° 24CGl (Eq. 18) where standing stock of oocytes and
ova (EYD ) are predicted from mantle condition index ( C) and gonad weight (G ).
Bottom panel shows probability density of residuals.
normal part of ovarian maturation in L. oplaescens, as it
is the case for L. v. reynaudii (Melo and Sauer, 1998). Our
evidence for this is that the standing stock of oocytes in
immature female L. opalescens declines sharply as their
ovaries mature (D increases, Fig. 7B). Clearly a narrow
window of opportunity exists for an unbiased estimate
of the potential fecundity of L. oplaescens. If the count
is made too early in the ovarian maturation process, the
count will either be low because extensive primary oogo-
nia production may be still be occurring (64-mm female,
Fig. 7A) or too high because additional oocytes will be
absorbed before the female reaches maturity. If the count
is made too late, it will be impossible to find a female that
has not ovulated. Our selection criteria "presence of yolked
oocytes" (which roughly begins at a oocyte size of about
1.1 mm) filtered out the very high counts of oocytes associ-
ated with immature ovaries.
From the practical standpoint, dealing with atretic
losses that may continue into the spawning period is much
less important for L. opalescens than for L. v. reynaudii
(Melo and Sauer, 1998; Sauer et al., 1999) or L. pealeii
(Maxwell and Hanlon, 2000). In these squid, where the
spawning period may last weeks or months, atresia may
seriously bias potential fecundity estimates. In the pres-
Macewicz et al.: Fecundity, egg deposition, and mortality of Loligo opolscens
323
ent study all atretic losses would be attributed, of course,
to ovulation and spawning but the chances of this being a
major error seem low. Because we counted atretic as well
as normal oocytes, atretic losses would be erroneously
attributed to spawning only if atresia had proceeded to
the point that the atretic structure could not be identified
as that of an oocyte in whole-mount preparations under a
light microscope ( 64x power). The time at stage for atretic
oocytes in L. opalescens ovaries, as well as other squid, is
unknown. The duration of alpha-stage atresia of yolked
oocytes in anchovy is about a week at 16°C (Hunter and
Macewicz, 1985b) and we suspect for the larger L. opal-
escens yolked oocyte that the alpha-stage duration may
be even longer. The disappearance of unyolked atretic oo-
cytes, as an oocyte-like structure that would be counted,
is more difficult to dismiss because so little is known
about this atretic stage and its duration. If our estimate
of the average longevity of spawning female is only about
1.67 days, then atretic losses of even small unyolked oo-
cytes is probably not an important bias. It would be useful
if a way could be found to estimate oocyte resorption rates
in squid although it may be very difficult. It seems more
important to validate our preliminary estimate of the
average longevity of spawning squid, because if true, any
concerns regarding atresia could be dismissed.
Mature females without postovulatory follicles in their
ovaries made up only 6% of the 247 females examined
histologically. The rarity of these females in our collections
reduced the precision of our potential fecundity estimate.
Only thirteen of the fifteen females classed as a mature
preovulatory female were usable for estimating potential
fecundity, further reducing the sample size. Such a small
sample size not only results in a low precision but raises
the concern that the sample may not be representative
of the stock as a whole. The fact that the average total
fecundity of females with high mantle condition from the
catch was close to the predicted value based on the thir-
teen females, indicates that the latter estimate may not be
biased. Clearly a larger sample size is needed, particularly
if egg escapement is used to monitor the fishery. It would
be helpful, in obtaining more samples, if we knew the
reason for the apparent rarity of mature preovulatory L.
opalescens females. One possibility is that females might
pass rapidly from the initial vitellogenesis to ovulation,
perhaps in the course of a single day or some fraction of it,
and ovulation might begin sometime in the evening when
L. opalescens are the most vulnerable to fishing. Another
possibility is that mature preovulatory females aggregate
in regions not heavily fished by either our trawl or the
fishery.
Egg escapement
A practical suggestion from this study is the idea of man-
aging spawning-ground loliginid fisheries by monitoring
the fecundity of the catch and computing the fraction of the
potential fecundity spawned. Monitoring the escapement
of eggs from the fishery is an attractive approach for Loligo
opalescens because costs are moderate, unlike the high
cost for monitoring egg beds that cover many locations
offshore and occur at any time of the year, and because
traditional fishery assessment models are difficult to
apply or inappropriate at the present time (PFMC, 2002).
To proceed with escapement fecundity as a management
tool, it would be necessary to set a target level for egg
escapement and to relate escapement to egg-per-recruit
analysis so that fishing effort could be adjusted to alter
egg escapement rates. Conceptual work along these lines
has been completed (Maxwell3)
As mentioned earlier, as a practical matter in applying
the egg escapement method, one would need to use QSP,
the mean fraction of the potential fecundity escaping (Eq.
1), as a proxy for the more comprehensive and more use-
ful measure of egg escapement Re tmaz, the fraction of the
expected lifetime fecundity deposited (Eq. 12). Obviously,
QSP will always be lower than Re-tm„ because the denomi-
nator of QSP (the fraction ESPIEP) is potential fecundity
which will always be larger than the denominator for
Retmal, which is expected lifetime fecundity (E). Although
quite a different value, QSP is a useful proxy for Re tnai. If
natural mortality (m ) and egg deposition rates (v) are con-
stant, changes in fishing mortality will result in changes
in QSP that are proportional to the change in ReJmiI.
However, changes will not be proportional if either v
or m varies. If there is reason to believe that m and v are
varying significantly, the use of QSP as a proxy for Retm!Lll
should be undertaken with caution.
A point of concern in applying this method is that it may
be difficult to substantially change escapement of eggs by
regulating fishing effort. Our model indicated that egg es-
capement may be relatively insensitive to changes in fish-
ing mortality if natural mortality rates are as high as we
believe them to be. Of equal importance to management is
the need to protect egg beds from damage by nets and to
monitor the catch to prevent any change that might result
in the capture of significant numbers of female L. opal-
escens before they begin to deposit eggs. Thus the fraction
of the catch that is immature females must be monitored
if the stock is managed by using the egg escapement
method. For simplicity, our calculations of escapement
were based on only mature females because immature
females were only 2.6% of the females in the catch
(1998-99) and their inclusion had little effect on param-
eter estimates. Egg escapement would decrease with an
increase in the fraction of immature in the catch. As none
of the fecundity of a captured immature female escapes
the fishery, a relatively small increase in the fraction
of immature animals in the catch can have significant
consequences.
From the standpoint of fishery management, the most
important unanswered question regarding the reproduc-
tive biology of L. opalescens is "how long do they remain on
the spawning grounds?" or the equivalent question "what
3 Maxwell, M. R.. L. D. Jacobson, and R. Conser. Unpubl.
data. Managing squid stocks using catch fecundity in an
eggs-per-recruit model. Southwest Fisheries Science Center,
National Marine Fisheries Service, 8604 La Jolla Shores Dr.,
La Jolla, CA 92037.
324
Fishery Bulletin 102(2)
is the daily natural mortality of the spawners?" Loligo
opalescens have only one spawning period in their life
time (McGowan, 1954; Fields, 1965; Butler et al., 1999)
but how long that period lasts remains unknown. Melo
and Sauer (1999) concluded that the spawning period of
L. v. reynaudii consisted of more than one spawning bout
but neither the number of bouts nor the duration of each
spawning period is known. In a laboratory study of L.
pealeii (Maxwell and Hanlon, 2000), the number of bouts
varied from one to ten, the interval between bouts was
highly variable, and the life span after the first spawn-
ing bout was from 3 to 50 days. Our best guess for L.
opalescens under fishing conditions was an average life on
the spawning grounds of only 1.67 days and a maximum
longevity of about 6 days. These estimates were based on a
simple exponential model, constrained by various proxies
for egg deposition rate, longevity, and the fraction of the
potential fecundity in the catch (the only directly mea-
sured value). We believe that two of our estimates, 36% of
the potential fecundity is deposited in the first 24 hours of
spawning and minimum residual fecundity is about 22%
of the potential fecundity, are on relatively firm ground
but our estimate of the maximum longevity on the spawn-
ing grounds as 6 days is speculative. New information on
mortality is needed because, over a wide range of daily
mortality rates, our model yields values that are consis-
tent with observed average fraction of potential fecundity
in the catch. Because direct measurement of mortality on
the spawning grounds may be difficult, it may be useful
to develop some indirect approaches. For example, a lab-
oratory study could be designed to generate an energy-
based model that converts squid mantle tissue loss to
deposited eggs. This mantle-to-egg conversion rate could
be used to assign an age (time elapsed after first egg depo-
sition) to modes of mantle condition from fishery samples.
Mortality could then be computed by following modes of
mantle condition through time.
Acknowledgments
This study was a cooperative project between the Cali-
fornia Department of Fish & Game (CDF&G) and the
National Marine Fisheries Service (NMFS) from start
to finish. We worked closely with CDF&G personnel
throughout the study with port-sampling data, cruise time,
and partial financial support was provided by CDF&G.
We worked particularly closely with M. Yaremko, A.
Henry, and D. Hanan of CDF&G. J. Welsh assisted in
the fecundity work. Others that contributed include J.
Butler, T. Kudroschoff, N. Smith, A. Preti, K. Lazar,
A. Cossio, and at sea K. Barsky, T. Bishop, S Charter,
R. Dotson, D. Fuller, C. Graff, D. Griffith, P. Hamdorf,
A. Hays, B. Horandy, M. Levy, I. Taniguchi, J. Ugoretz, and
L. Zeidberg. We wish to thank the crews of the research
vessels Jordan and Mako. We especially wish to thank diver
J. Hyde who observed, collected, and photographed squid in
La Jolla Canyon. M. Maxwell and two anonymous review-
ers read the manuscript and provided constructive com-
ments. R. Allen and H. Orr improved our illustrations.
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326
Fishery Bulletin 102(2)
Appendix I
Terms
EP potential fecundity (standing stock of oocytes
in the ovary of mature females prior to spawn-
ing)
ESPl the total eggs deposited on the bottom up to
time t. (t in days)
Ec total number of eggs deposited by mature
females in the catch or total number of eggs
escaped
EM total number of eggs deposited by mature
females prior to death due to natural mortal-
ity
EA total number of eggs deposited by females alive
and not caught by fishery
E total number of eggs that would have been
spawned during a squid's lifetime if no fishery
existed
EY standing stock of oocytes in the ovary
ED standing stock of ova in the oviduct
EYD total fecundity, the sum of both the number of
oocytes in the ovary and ova in the oviduct
EYD tlt stocking stock of oocytes in the ovary plus
those ova in the oviduct after spawning has
begun and up to the elapsed time tk, where tk
ls £ 'max
tmax maximum elapsed time with the time 0 being
the time when mature females are about
to ovulate or total elapsed time (in days) of
spawners on the spawning ground
ER standing stock of oocytes remaining in ovary
at death
m daily adult natural mortality rate
f daily fishing mortality rate for adults
v daily egg deposition rate
Qsr i = EsPt IEp = 1- ervt fraction of potential fecundity
deposited up to time t
e~zl mortality (survival) curve
JV„ number of mature females at time 0
Nr total number of spawners in the catch
Re tk egg escapement rate = ratio of eggs deposited
to total number of egg which would be spawned
if there was no fishery, at a given elapsed time
Ret egg escapement rate up to the maximum
elapsed time Umax)
Appendix II
For any elapsed time tk, formulas for Ec, EM, EA and E:
Ec = EpNJ
EM = EPN0m
1-e
-lm+f)tk ^_e-(m+f+v)t),
m + f m+f+v
1-e
-{m+f)tk -. _ -im+f+v)tk
m + f m+f+v
EA = (EP-EYD.)Nk = AT0e-""+/ "* EP ( 1 - e"1"' )
V -mtJ , m
e 1 e
E = EPN0
The derivation for EA is straight forward and the deriva-
tions for £r, EM, and E, similar among one another, are
as follows:
where
Ec=\ ESP,dC, = J Ep~a- <?"''' )dC,
= Ep~N0jn-e-")e-'m+n'fdt,
C.=N0-^—a-e-""+f")
m + f
is the number of removals of the cohort due to fishing up
to time t (Quinn and Deriso, 1999).
EM=\E~TldDnU=\Ep(\-e-«)dDnU
EpNJ
(m + f)(m + f + u)
where
D„,t=N0-—;(l-
!!!_h _<,-"»*/'")
Macewicz et al.: Fecundity, egg deposition, and mortality of Loligo opa/scens
327
is the number of removals of the cohort due to natural
mortality up to time t (Quinn and Deriso, 1999) and E
(when no fishing takes place):
E=\ ESPjdDt = f E^( 1 - e"1" )dDl
= EpN0\(l-e-l")e'm'mdt,
o
where Dt = N0(l-e-mt) is the number of removals of the
cohort due to natural mortality when no fishing takes
place.
328
Abstract— The dusky rockfish (Se-
bastes ciliatus) of the North Pacific
Ocean has been considered a single
variable species with light and dark
forms distributed in deep and shal-
low water, respectively. These forms
have been subjected to two distinct
fisheries separately managed by fed-
eral and state agencies: the light deep
form is captured in the offshore trawl
fishery; the dark shallow form, in the
nearshore jig fishery. The forms have
been commonly recognized as the light
dusky and dark dusky rockfishes. From
morphological evidence correlated with
color differences in some 400 speci-
mens, we recognize two species cor-
responding with these color forms.
Sebastes ciliatus (Tilesius) is the dark
shallow-water species found in depths
of 5-160 m in the western Aleutian
Islands and eastern Bering Sea to
British Columbia. The name Sebastes
variabilis (Pallas) is resurrected from
the synonymy of S. ciliatus to apply to
the deeper water species known from
depths of 12-675 m and ranging from
Hokkaido, Japan, through the Aleu-
tian Islands and eastern Bering Sea, to
Oregon. Sebastes ciliatus is uniformly
dark blue to black, gradually lightening
on the ventrum, with a jet black peri-
toneum, a smaller symphyseal knob,
and fewer lateral-line pores compared
to S. variabilis. Sebastes variabilis is
more variable in body color, ranging
from light yellow to a more usual tan
or greenish brown to a nearly uniform
dark dorsum, but it invariably has a
distinct red to white ventrum. Syn-
onymies, diagnoses, descriptions, and
geographic distributions are provided
for each species.
The dusky rockfishes (Teleostei: Scorpaeniformes)
of the North Pacific Ocean: resurrection of
Sebastes variabilis (Pallas, 1814) and a
redescription of Sebastes ciliatus (Tilesius, 1813)
James W. Orr
Resource Assessment and Conservation Engineering Division
Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
7600 Sand Point Way NE
Seattle, Washington 98115
E-mail address: James Orr@noaa.gov
James E. Blackburn
Alaska Department of Fish and Game
211 Mission Road
Kodiak, Alaska 99615-9988
Manuscript approved for publication
22 December 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:328-348(2004).
Among the approximately 92 species
of Sebastes found in the North Pacific,
two commercially important species
long identified under the name Sebastes
ciliatus have been taxonomically prob-
lematic. The name S. ciliatus (Tilesius,
1813) has been commonly applied to
specimens considered to represent a
single variable species ranging from
northern Japan to British Columbia
(Barsukov, 1964; Westrheim, 1973;
Shinohara et al., 1994; Mecklenburg et
al., 2002), and the name S. variabilis
(Pallas, 1814) has been treated as a
junior synonym (Jordan and Gilbert,
1881; Eigenmann and Beeson, 1894;
Jordan and Evermann, 1898; Blanc
and Hureau, 1968). Two color forms
within S. ciliatus have been reported
and hypothesized to be distinct species
(Quast and Hall, 1972; Eschmeyer et
al., 1983; Kessler, 1985; Fig. 1). The
typically light-colored form, commonly
known as the light dusky rockfish, is
often found in large aggregations over
the outer continental shelf and upper
slope at depths down to 675 m, and
less frequently in nearshore habitats.
The dark-blue to black form, commonly
known as the dark dusky rockfish, is
found in more shallow habitats from
nearshore rocky reefs to depths no
greater than 160 m.
These forms have been subjected to
two distinct fisheries separately man-
aged by U.S. federal and Alaska state
agencies since 1998. The light-colored
deep form is captured in the offshore
trawl fishery and is the dominant spe-
cies of the pelagic shelf rockfish fisher-
ies complex regulated by the National
Marine Fisheries Service (NMFS).
Specific catch limits are set under the
designation "dusky rockfish." The oc-
casional catch of the dark form in these
offshore waters has also been consid-
ered "dusky rockfish." The dark-colored
shallow form is found commonly in the
nearshore jig fishery regulated by the
Alaska Department of Fish and Game.
The dark form, routinely misidentified
as S. melanops, may comprise up to 259c
of the catch in the "black rockfish" jig
fishery off Kenai Peninsula (Clausen
et al.1) and is managed only as "other
rockfish" bycatch within the fishery.
Early allozyme analyses (Tsuyuki
et al., 1965, 1968) indicated signifi-
cant genetic differences among samples
identified as S. ciliatus. A more detailed
analysis of several Sebastes species
(Seeb, 1986) and a later study focused
1 Clausen, D. M., C. R. Lunsford, and
J. T. Fujioka. 2002. Pelagic shelf
rockfish. In Stock assessment and fish-
ery evaluation report for the groundfish
resources of the Gulf of Alaska for 2002, p.
383-417. North Pacific Fishery Manage-
ment Council, 605 W 4th Ave, Suite 306,
Anchorage, AK 99501.
Orr and Blackburn: Resurrection of Sebastes variabilis and redescription of Sebastes ciliatus
329
Figure 1
(A) Sebastes variabilis (top), UW 43494, 225.2 mm, and S. ciliatus (bottom), UW 43493, neotype, 266.4 mm,
collected at 37 and 25 m depth, respectively, in Lynn Canal near Funter Bay, southeast Alaska. (Bl Sebastes
ciliatus (top), UW 45512, 235.2 mm, and S. variabilis (bottom), UW 45511, 206.2 mm, collected syntopically
at 67 m depth in the northern Gulf of Alaska, 57.38061°N, 154.8009°W. (C) Sebastes variabilis (left), UW
43494, 150.6-225.2 mm, and S. ciliatus (right), UW 43492, 153.7-241.1 mm, collected at 37 and 25 m depth,
respectively, in Lynn Canal near Funter Bay, southeast Alaska. (D) Sebastes variabilis, UW 43251, 390 mm
(top) and 410 mm (bottom), northern Gulf of Alaska, 59.50446°N, 145.2262°W, 135 m depth. (E) Sebastes
mclanops (top), UW 43490, and S. ciliatus (bottom), UW 43484, 313 mm, collected at 25 m depth in Soapstone
Cove, southeast Alaska.
330
Fishery Bulletin 102(2)
//,-m^'s' <£/c£l%ytQ- ^Q ft&*^/!£7<r?7is 7rOC/ zw
B
^/
£%tt2,.„ Sj
• — S .t_// eyes' jfti.
Figure 2
( Ai Pcrca variabilis Pallas, MNHN 8670, lectotype, 343.7 mm. "mari Americam borealum." (B) Epinephelus ciliatus Tilesius,
illustration of holotype after Tilesius (1813), specimen presumed lost.
on S. ciliatus (Westrheim and Seeb2) concluded that the
two color forms were distinct sister species. Seeb's recent
work with microsatellite DNA data has revealed discrete
genetic differences between the two, as well as some evi-
dence for infrequent hybridization (Seeb3). Sequence data
2 Westrheim, S. J., and L. W. Seeb. 1997. Unpubl. manu-
script. Investigation of the Sebastes ciliatus species group.
36 p. Fisheries and Oceans Canada, Pacific Biological Sta-
tion, Nanaimo, BC, Canada V9R 5K6.
3 Seeb, L. W. 2002. Personal commun. Alaska Department
of Fish and Game, 333 Raspberry Road, Anchorage, AK 99518-
1599.
from NADH dehydrogenase subunit regions of the mito-
chondrial genome, however, have not revealed differences
between the two forms ( Lopez4, Gray5), nor have sequence
data from other work on closely related species of Sebastes
(Bentzen et al., 1998; Sundt and Johansen, 1998; Roques
etal., 2001).
4 Lopez, J. A. 2000. Personal commun. Iowa State Univ.,
Ames, IA 50014.
6 Gray, A. 2000. Personal commun. Fisheries Division,
School of Fisheries and Ocean Sciences, Univ. Alaska Fair-
banks. 11120 Glacier Highway, Juneau, AK 99801.
Orr and Blackburn: Resurrection of Sebastes variabilis and redescnption of Sebastes ciliatus
331
In this study, we provide morphological evidence from
examination of about 400 specimens collected throughout
the geographic and bathymetric range of the species to
correlate color differences with meristic and shape differ-
ences. In thus recognizing two species, S. ciliatus and S.
variabilis, previously referred to the name S. ciliatus (Tile-
sius, 1813), we discuss the nomenclatural consequences of
this decision. Both species were originally described (as
Epinephelus ciliatus Tilesius and Perca variabilis Pallas)
on the basis of early Russian collections from along the
Aleutian Islands (Svetovidov, 1978, 1981). The type series
of one species is now represented by a single extant speci-
men (Fig. 2A) and the other by the illustration of a single,
now lost, specimen (Svetovidov, 1978, 1981; Fig. 2B).
Although workers since the turn of the century have as-
sociated the name S. ciliatus with the variably light-col-
ored species (Jordan, 1896; Jordan and Evermann, 1898;
Barsukov, 1964; Orr et al., 1998, 2000; Mecklenburg et
al., 2002), the original description and accompanying il-
lustration (Fig. 2B) appear to describe the uniformly dark
species. We have also identified the remaining syntype
(Fig. 2A) ofPeiea variabilis as the light species. Therefore,
we refer the dark, shallow-water species (the dark rock-
fish) to Sebastes ciliatus (Tilesius, 1813) and resurrect the
name Sebastes variabilis (Pallas, 1814) for the typically-
light, deeper-water species (the dusky rockfish).
Methods and materials
Counts and measurements follow Hubbs and Lagler
(1958), except as noted below. Unless indicated otherwise,
standard length (SL) is used throughout and was always
measured from the tip of the snout. Depth at pelvic-fin base
was measured from the origin of the dorsal fin to the base
of the pelvic fins (at the articulation of the pelvic-fin spine);
depth at anal-fin origin, from the base of the last dorsal-
fin spine to the anal-fin origin; depth at anal-fin insertion,
from dorsal-fin insertion to anal-fin insertion; body thick-
ness, at pectoral-fin base; head thickness, at the posterior
orbital rim; prepelvic- and preanal-fm length, from pelvic-
fin base or anal-fin origin to the tip of the snout; pelvic-fin
to anal-fin length from pelvic-fin base to anal-fin origin;
caudal peduncle dorsal length from dorsal-fin insertion to
caudal-fin base; caudal peduncle ventral length from anal-
fin insertion to caudal-fin base. The small anterior notch
in the orbit between the frontal bone and lateral ethmoid
was excluded from orbit length and snout length measure-
ments. Accessory scales are small scales located beyond
the posterior field of major scales. The swimbladder mus-
culature was examined after dissection according to the
methods of Hallacher (1974). Institutional abbreviations
follow Leviton et al. (1985) and Leviton and Gibbs ( 1988),
as modified by Poss and Collette (1995).
Individuals were identified by body and peritoneum col-
or (see species descriptions below) for grouping in ANOVA
and ANCOVA, as well as for labeling individuals in graphs
of principal components analysis scores. Univariate and
multivariate analyses were conducted by using Statgraph-
ics Plus 4.1 (Manugistics, Rockville, MD) and Splus 2000
(Mathsoft, Inc., Seattle, WA). Differences were considered
significant at P < 0.05.
Arcsine-transformed morphometric ratios (with SL or
head length as denominator) and meristic characters were
tested to meet the assumptions of normality required for
ANOVA. The following characters exhibited normal distri-
butions and did not differ significantly in variance between
species and were subjected to ANOVA: head length, orbit
length, snout length, interorbital width, suborbital depth,
gill-raker length, body thickness, pectoral-fin base width,
pectoral-fin ray length, caudal peduncle ventral length,
predorsal length, spinous dorsal-fin base, soft dorsal-fin
base, and counts of lateral-line pores and gill rakers.
For morphometric characters, significant differences
were also identified by using an analysis of covariance
(ANCOVA) of log-10-transformed measurements with SL
or head length (HL) as covariates when assumptions of
normality and the homogeneity of slopes were satisfied.
The ANCOVA model included species as a factor, SL or HL
as a covariate, and a species/I SL or HL) interaction (e.g.,
HL = C+Species+SL+(SpeeiesxSL)). A residual analysis
was done for each model to determine the appropriateness
of the model. Whenever the interaction was not significant
(at the 5% level), a reduced model was used by dropping
the interaction and forcing the slopes to be the same
(BD=C+Species +SL). This removed the effect of SL and
HL and allowed testing for significant differences between
species. The following morphometric characters met the
assumptions required for ANCOVA: head length, snout
length, interorbital width, gill-raker length, pectoral-
fin base width, pectoral-fin ray length, caudal peduncle
ventral length, predorsal length, spinous dorsal-fin-base
length, and soft dorsal-fin-base length.
On a dataset of specimens with all characters, sheared
principal components analysis (SPCA) for a size-free
analysis (Bookstein et al., 1985) was conducted by us-
ing morphometric characters, and a standard principal
components analysis (PCA) was conducted by using all
meristic characters. Raw morphometric data were log-
transformed and the covariance matrix was subjected
to SPCA, as was the correlation matrix of raw meristics.
Differences between species were illustrated by plotting
scores of sheared PC2 against sheared PC3 and sheared
morphometric PC2 against the standard meristic PCI.
Separate analyses were also conducted on three group-
ings: 1) each species by depth, 2) each species by sex, and
3 ) shallow-water populations ofS. ciliatus and S. variabilis
primarily collected in the vicinity of the Triplet Islands
and Monashka Bay, on the northeast side of the Kodiak
Island Archipelago, and the vicinity of Lynn Canal,
Alaska. Shallow collections were defined as those made at
less than 50 m depth, and deep collections were taken at
depths greater than 50 m.
These plots were also examined for groupings indicative
of geographic differences in body shape and meristics.
Geographic areas were defined as follows: British Colum-
bia, from the Straits of Juan de Fuca to Dixon Entrance;
southeast Alaska, from Dixon Entrance to Chatham
Strait; Gulf of Alaska, from Chatham Strait to the tip of
the Alaska Pennisula; Aleutian Islands and Bering Sea,
332
Fishery Bulletin 102(2)
Table 1
Proportional morphometries and meristics ofSebastes cihatus and S. variabilis from all depths and regions. Morphometric data
are in %SL or %HL. X = statistically significant difference at 0.05 level, as evaluated by ANOVA and ANCOVA. when appropri-
ate; ns = not statistically significant at 0.05 level, n = number offish in sample.
S.ci
liatus
S. varia
nlis
ANOVA ANCOVA
n
Range
Mean ±SD
n
Range
Mean ±SD
Meristics
Dorsal-fin spines
138
12-14
13.0+0.2
194
13-14
13.0 ±0.1
Dorsal-fin rays
138
13-17
15.0 ±0.5
194
13-16
15.0 ±0.4
Anal-fin rays
139
7-9
7.9 ±0.4
195
7-9
7.9 ±0.4
Pectoral-fin rays (left)
138
17-19
18.2 ±0.5
194
17-19
18.0 ±0.3
Pectoral-fin rays (right)
137
16-19
18.2 ±0.4
195
16-19
18.0 ±0.4
Unbranched pectoral-fin
rays ( left )
136
8-10
9.2 ±0.5
195
7-11
9.1 ±0.4
Unbranched pectoral-fin
rays ( right I
108
8-11
9.2 ±0.5
188
7-11
9.1 ±0.5
Lateral-line pores (left)
138
39-50
45.4 ±2.3
188
43-54
48.5 ±1.9
X
Lateral-line pores (right)
125
40-54
45.3 ±2.4
172
42-54
48.5 ±1.9
X
Lateral-line scales
132
44-60
50.6 ±2.7
177
47-63
52.8 ±2.7
Gill rakers
137
32-37
34.8 ±1.1
184
32-37
34.7 ±0.9
X
continued
from the tip of the Alaska Peninsula west and north into
the Bering Sea.
Results
Color
Body color in life and in preservation differs consistently
between S. ciliatus and S. variabilis (Fig. 1; see detailed
description below). In life, S. ciliatus is uniformly bluish-
black to gray, with slight gradual lightening on the belly;
the peritoneum is invariably jet black. In contrast, S.
variabilis varies in background color from golden yellow
to greenish brown to dark gray, with a distinct break
between the darker dorsum and the invariably white to
pink ventrum, particularly at the base of the anal fin; the
peritoneum is gray to black. In S. variabilis preserved for
up to 30 years, the distinct break along the ventrum is
retained and differs from the uniformly dark preserved
color of S. ciliatus. This combination of characteristic
body and peritoneum color was used initially to identify in-
dividuals as either S. ciliatus or S. variabilis as the basis
for univariate statistical analyses.
Meristic characters
Lateral-line pore and gill-raker counts differed signifi-
cantly between S. ciliatus and S. variabilis from all depths
and regions, S. ciliatus having a lower range and mode of
counts (Tables 1-3). In shallow water, only lateral-line
pore counts showed significant differences (Table 4).
Slight clinal variation was evident for lateral-line pores
in S. ciliatus between southeast Alaska collections and
northern Gulf of Alaska material (Table 2). In the PCA,
counts of lateral-line pores, gill rakers, and pectoral-fin
rays were most heavily loaded along the first PC axis,
confirming that S. ciliatus has typically lower lateral-line
pore and gill-raker counts and tends to have a higher pec-
toral-fin ray count (Tables 1-3, 5; Fig. 3B).
Morphometric characters
Among morphometric characters meeting statistical
assumptions for ANOVA or ANCOVA, head length,
interorbital width, suborbital depth, lower-jaw length,
gill-raker length, body thickness, pectoral-fin base width,
predorsal length, and soft-dorsal-fin-base length differed
significantly between S. ciliatus and S. variabilis across
all depths and regions (Table 1). Between shallow-water
S. ciliatus and S. variabilis, all the above characters,
except head length, interorbital width, and predorsal
length, differed significantly (Table 4). No significant dif-
ferences were found in analyses within species by depth
or sex.
In the PCA for specimens collected across all regions
and depths, clusters of S. ciliatus and S. variabilis showed
broad overlap and only slight discrimination among indi-
viduals along the PC2 axis (Fig. 3A). Principal component
2, the primary shape component, described 1.8% of the
total variation, and PCI, the size component having all
loadings positive, described 96.4rr of the variation. Char-
acters loading most heavily along the PC2 axis included
suborbital depth, gill-raker length, orbit length, body
Orr and Blackburn: Resurrection of Sebastes variabilis and redescription of Sebastes ciliatus
333
Table 1 (continued)
S. ciliatus
S. varia
bilis
ANOVA
ANCOVA
n
Range
Mean ±SD
n
Range
Mean ±SD
Morphometries
Standard length
132
83.8-340.0
192
77.7-430.8
Head length/SL
113
28.7-35.5
32.9 ±1.2
129
28.1-36.2
32.5 ±1.2
X
ns
Orbit length/HL
111
21.5-30.6
25.6 ±2.0
121
20.6-33.5
25.6 ±2.1
ns
Snout length/HL
111
18.2-26.0
21.4 ±1.6
121
17.1-27.1
21.4 ±1.8
ns
ns
Interorbital width/HL
111
22.9-29.3
25.9 ±1.3
121
22.5-30.4
26.4 ±1.4
X
X
Suborbital depth/HL
111
4.1-7.8
6.0 ±0.8
121
4.3-8.1
6.2 ±0.7
X
Upper jaw length/HL
111
43.6-51.1
47.4 ±1.5
121
42.7-54.0
47.8 ±2.0
Lower jaw length/HL
105
53.4-60.5
56.5 ±1.7
108
52.8-62.7
58.3 ±2.2
X
Gill raker length/HL
98
11.3-20.7
15.0 ±1.6
110
11.6-19.9
15.5 ±1.7
ns
X
Depth at pelvic-fin base/SL
111
32.5-42.7
37.0 ±1.9
121
29.2-40.9
36.2 ±1.7
Depth at anal-fin origin/SL
111
27.4-35.8
31.2 ±1.7
121
26.7-35.4
30.5 ±1.6
Depth at anal-fin insertion/SL
109
13.8-18.5
15.9 ±1.0
116
13.1-18.0
15.4 ±0.9
Body thickness/SL
111
14.9-22.3
18.0 ±1.2
120
12.9-20.9
17.3 ±1.5
X
Pectoral-fin base width/SL
111
9.5-11.9
10.7 ±0.5
121
9.4-11.2
10.2 ±0.4
X
X
Pectoral-fin ray length/SL
111
24.6-31.8
28.5 ±1.3
121
23.5-31.0
28.2 ±1.4
ns
ns
Pectoral-fin length/SL
111
25.5-33.6
29.8 ±1.5
117
24.2-35.1
29.2 ±1.7
Pelvic-fin ray length/SL
111
20.5-26.0
22.7 ±1.1
119
19.2-29.2
22.0 ±1.5
Pelvic-fin ray/Pelvic-fin spine
111
52.4-67.4
59.9 ±4.3
121
44.9-70.7
59.9 ±5.5
length
Anal-fin spine I length/SL
83
3.6-9.1
5.2 ±0.9
107
3.3-8.8
5.3 ±1.0
Anal-fin spine II length/SL
84
7.5-14.2
10.6 ±1.2
106
5.8-13.6
10.5 ±1.5
Anal-fin spine III length/SL
84
10.0-14.6
12.4 ±1.1
107
9.5-15.6
12.2 ±1.3
Anal-fin ray 1 length/SL
83
15.6-22.5
19.0 ±1.2
97
15.1-21.0
18.2 ±1.3
Anal-fin ray 2 length/SL
84
14.5-23.4
20.2 ±1.2
97
15.3-23.1
19.5 ±1.3
Caudal-fin length/SL
60
10.2-29.4
21.7 ±2.7
74
15.4-26.9
21.2 ±2.3
Caudal peduncle depth/SL
111
9.3-13.7
11.4+0.7
121
9.5-12.2
10.9 ±0.5
Caudal peduncle dorsal
111
11.9-16.2
13.8+0.8
121
12.6-16.4
14.1 ±0.8
length/SL
Caudal peduncle ventral
111
17.6-22.9
20.5 ±1.0
121
17.1-24.3
21.1 ±1.3
ns
ns
length/SL
Preanal length/SL
111
60.0-77.4
68.7 ±2.5
121
59.4-77.9
68.1 ±2.6
Pelvic- to anal-fin length/SL
105
26.1-43.2
32.5 ±3.1
111
25.9-41.7
31.6 ±2.9
Predorsal length/SL
111
28.5-35.4
32.1 ±1.3
121
28.1-35.2
31.8 ±1.3
X
ns
Spinous dorsal-fin-base
111
32.1-43.6
37.2 ±2.1
121
31.6-41.9
37.0 ±2.1
ns
ns
length/SL
Soft dorsal-fin-base length/SL
111
21.9-30.8
26.0 ±1.6
121
21.4-28.7
24.8 ±1.6
X
X
Anal-fin-base length/SL
111
13.9-18.9
16.5 ±1.0
121
13.1-18.4
16.3 ±1.0
Prepelvic-fin length/SL
111
33.5-49.5
39.7 ±2.6
121
34.0-46.5
39.7 ±2.4
thickness, caudal-peduncle dorsal length, and upper-jaw
length (Table 6). No significant regional variation was
observed within the overall PCA.
In the sheared PCA of differences in shape by depth,
both species showed negligible differences within broadly
overlapping clusters of individuals. In the depth analysis,
loadings along the PC2 axis were strongest for suborbital
depth, gill-raker length, and orbit length, and shallower
individuals tended to have a greater suborbital depth,
longer gill rakers, and longer orbit. In the combined mor-
phometric and meristic shallow-water analysis, slight
differences along the morphometric PC2 axis and the
meristic PCI axis reflected longer gill rakers and higher
lateral-line pore counts in S. variabilis. No differences
were found in the PCA comparing sex within species
(Tables 7-8).
334
Fishery Bulletin 102(2)
Table 2
Counts of lateral-1
ne pores and gill
rakers for Sebastes
eiliatus
and S. variabilis by
region.
AI oi
BS
= Aleutian Islands or
Bering Sea; GOA =
Gulf of Alaska; SEAK
= Southeast Alaska
BC
= British Columbia.
Species
Region
Lateral-1
ine pores
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
n
Mean
SD
Sebastes eiliatus
AI or BS
2
3
8
4
8
1
26
44.73
1.66
GOA
1
1
6
7
4
11
8
5
5
3
1
52
45.20
2.22
SEAK
3
3
2
2
4
2
5
3
24
46.75
2.40
Sebastes variabilis
AI or BS
3
4
5
1
7
4
3
27
48.04
1.87
GOA
5
4
14
11
15
13
8
3
1
74
48.68
1.95
SEAK
1
1
3
5
9
5
14
4
2
44
48.75
1.94
BC
1
3
1
2
3
4
1
1
16
48.63
2.25
Region
Gill rakers
32
33
34
35
36
37
n
Mean
SD
Sebastes eiliatus
AI or BS
GOA
SEAK
1
2
1
9
17
1
5
23
6
10
7
13
1
2
3
1
26
51
25
34.04
33.80
34.77
1.04
0.87
0.92
Sebastes variabilis
AI or BS
GOA
SEAK
BC
3
1
1
5
4
1
10
24
18
2
8
35
15
8
2
5
8
6
1
1
25
70
46
17
34.22
34.52
34.61
35.12
1.13
0.80
0.89
0.86
Systematics
Diagnosis
Sebastes eiliatus (Tilesius, 1813)
Dark rockfish
Figs. 1-4; Tables 1-8
Epinephelus eiliatus Tilesius, 1813:406, pi. 16, figs. 1-4
(original description, one specimen: holotype apparently
lost, sex unknown, approximately 413 mm TL, "Oceano
orientali Camtschatcam et Americam alluenti").
Sebastichthys eiliatus: Jordan and Jouy, 1881:8 (in part,
new combination).
Sebastodes eiliatus: Jordan and Gilbert, 1883:658 (in part,
new combination).
Sebastostomus eiliatus: Eigenmann and Beeson, 1894:388
(in part, new combination).
Sebastes eiliatus: Westrheim, 1973:1230 (in part, new
combination).
Sebastes sp. cf. eiliatus: Orr et al„ 1998:26, 2000:26.
Neotype
UW 43493, 1(266.4 mm), Lynn Canal, north of Funter
Bay, 58.2467°N, 134.899°W, 25 m depth, 13 July 1998.
Material examined
A total of 140 specimens, 83.8-340.0 mm, were examined,
including the neotype above. See Appendix for catalog
numbers and locality data.
A species of Sebastes with the following combination of
character states: body uniformly black to dark blue or
gray, particularly at anal-fin base and ventral pectoral-fin
rays; peritoneum jet black; symphyseal knob moderate to
strong; extrinsic swimbladder muscle with anterior fascia
separating sections of striated muscles, otherwise of type I
(a-z) of Hallacher ( 1974 1; lateral-line pores 39-50, lateral-
line scales 44-60; pectoral-fin (PI) rays 16-19; anal-fin (A)
rays 7-9; dorsal-fin (D) rays 13-17; vertebrae 28 (11-12 +
16-17).
Description
D XII-XIV. 13-17; A III, 7-9; PI 16-19, 8-11 simple; lat-
eral-line pores 39-50(54), scales 44-60; gill rakers 32-37
( 10-11 + 22-27 ); vertebrae 28 (11-12 + 16-17). Meristic fre-
quency and statistical data are presented in Tables 2-4.
Morphometric data and statistics are presented in
Tables 1 and 4. Body relatively deep, especially at nape,
depth at pelvic-fin base 32.5-42.7% SL; profile of dorsal
margin of head steep from snout to nape above anterodor-
sal margin of gill slit, flattening to dorsal-fin origin; mouth
large, with posterior end of maxilla extending between
pupil and posterior rim of orbit, maxilla length 43.6-51.1%
HL; symphyseal knob moderate to strong and having blunt
tip, lower jaw length 53.4-60.5% HL; mandibular pores of
moderate size. Cranial spines weak, in large adults cov-
ered by flesh, head smooth. Nasal spine invariably present;
parietal ridge invariably present and small spine typically
Orr and Blackburn: Resurrection of Sebastes variabilis and redescription of Sebastes ciliatus
335
Table 3
Counts of soft-dorsal-, anal-, and pectoral-fin rays for Sebastes ciliatus and S. variabilis by region. AI or BS = Aleutian Islands or
Bering Sea; GOA = Gulf of Alaska; SEAK = Southeast Alaska; BC = British Columbia, n = number offish in sample.
Species
Region
Dorsal-fin rays
13
14
15
16
17
Mean
SD
Sebastes ciliatus
Sebastes variabilis
AI or BS
GOA
SEAK
AI or BS
GOA
SEAK
BC
2
21
3
26
15.04
0.45
4
45
2
52
14.94
0.42
5
14
4 1
24
15.04
0.75
25
3
28
15.12
0.33
7
54
9
70
15.03
0.49
4
40
3
47
14.98
0.39
1
16
17
14.94
0.24
Pectoral-fin rays
Region
17
18
19
Mean
SD
Sebastes ciliatus
Sebastes variabilis
AI or BS
GOA
SEAK
AI or BS
GOA
SEAK
BC
1
19
44
2
16
23
6
65
1
44
15
26
52
24
27
71
47
17
18.19
18.16
18.17
18.17
17.93
18.02
18.12
0.49
0.37
0.56
0.38
0.26
0.25
0.33
Region
Anal-fin rays
Mean
SD
Sebastes ciliatus
Sebastes variabilis
AIorBS
GOA
SEAK
AI or BS
GOA
SEAK
BC
4
21
4
47
1
20
4
19
8
63
5
41
1
15
26
7.88
0.43
51
7.92
0.27
24
8.08
0.41
27
8.00
0.50
71
7.88
0.32
46
7.89
0.31
17
8.00
0.35
present; postocular and tympanic spines absent or obso-
lete in adults (postocular present on at least one side in
23.2% and tympanic present on at least one side of 37.7%
of specimens examined), most often present in juveniles.
Interorbital region wide, 22.9-29.3% HL, strongly convex;
parietal ridges weak, and area between ridges slightly
convex; preopercular spines 5, directed posteroventrally;
two opercular spines, upper spine directed posteriorly,
lower spine directed posteroventrally; posttemporal and
supracleithral spines present; lachrymal spines rounded,
small; dorsal margin of opercle nearly horizontal; lower
margin of gill cover with small spines: posteroventral tip
of subopercle and anteroventral tip of interopercle rugose
or with 1-2 small spines.
Dorsal-fin origin above anterodorsal portion of gill slit;
dorsal fin continuous, gradually increasing in height to
spine IV and decreasing in height to spine XII; spine XIII
much larger, forming anterior support of soft dorsal fin;
membranes of spinous dorsal fin moderately incised, less
so posteriorly; soft dorsal fin with anterior rays longest,
posterior rays gradually shortening. Anal-fin spine II
shorter than III (7.5-14.2 vs. 10.0-14.6% SL), anterior
rays longest on soft rayed portion of anal fin, posterior
rays gradually shortening, posterior margin perpendicu-
lar to body axis or with slight posterior slant, anterior
ray tips directly ventral to or forward of posterior tips,
anterior tip of anal fin typically rounded. Pectoral fins
with ray 10 longest, extending to or slightly anterior to
vent, fin-ray length 24.6-31.8% SL, fin-base to ray-tip
length 24.6-31.8% SL; fin-base width 9.5-11.9% SL. Pel-
vic fins extend about 60% of distance from pelvic-fin base
to anal-fin origin, falling well short of vent, ray length
20.5-26.0% SL, spine length 52.4-67.4%, ray length.
Caudal fin shallowly emarginate, length 10.2-29.4% SL.
Vent positioned below dorsal-fin spine 10, 1.6-5.8% SL
from anal-fin origin.
336
Fishery Bulletin 102(2)
Table 4
Selected proportional morphometries and meristics of Sebastes ciliatus and S. variabilis from shallow-water collections. Mor-
phometric data are in percent standard length (SL) or head length (HL). X = statistically significant difference at 0.05 level, as
evaluated by ANOVA and ANCOVA, when appropriate; ns = not statistically significant at 0.05 level.
S. ciliatus
S. variabilis
Range
Mean ±SD
Range
Mean ±SD ANOVA ANCOVA
Meristics 68
Dorsal-fin rays 13-16
Anal-fin rays 7-9
Pectoral-fin rays (left) 17-19
Lateral-line pores (left) 40-50
Gill rakers 32-37
Morphometries
Standard length 83.8-331.0
Head length/SL 30.5-35.5
Orbit length/HL 21.5-30.6
Snout length/HL 18.2-26.0
Interorbital width/HL 22.9-28.2
Suborbital depth/HL 4.1-7.6
Upper jaw length/HL 43.6-50.4
Lower jaw length/HL 53.4-60.5
Gill raker length/HL 11.8-20.7
Depth at pelvic-fin base/SL 34.0-40.8
Depth at anal-fin origin/SL 27.4-35.8
Body thickness/SL 14.9-21.3
Pectoral-fin base width/SL 9.7-11.8
Pectoral-fin ray length/SL 25.1-31.3
Caudal peduncle depth/SL 9.8-13.7
Caudal peduncle dorsal length/SL 11.9-16.2
Caudal peduncle ventral length/SL 18.2-22.5
Preanal length/SL 62.5-77.4
Predorsal length/SL 29.3-35.4
Spinous dorsal-fin-base length/SL 32.5-41.8
Soft dorsal-fin-base length/SL 22.1-29.6
Anal-fin-base length/SL 14.5-18.9
Prepelvic-fin length/SL 36.4-49.5
49
15.0+0.5
7.9 ±0.4
18.1 ±0.5
45.2 ±2.1
34.3 ±1.1
32.9 ±1.1
25.6 ±2.1
21.3 ±1.6
25.6 ±1.2
5.9 ±0.7
47.3 ±1.5
56.4 ±1.6
15.2 ±1.5
36.7 ±1.5
31.2 ±1.7
17.9 ±1.2
10.6 ±0.5
28.6 ±1.2
11.5 ±0.7
14.0 ±0.8
20.6 ±1.0
68.3 ±2.3
32.2 ±1.2
37.0 ±2.0
26.2 ±1.4
16.5 ±0.9
39.4 ±2.3
14-16
15.0 ±0.4
ns
7-9
8.0 ±0.3
ns
17-19
18.0 ±0.2
ns
42-51
47.9 ±2.0
X
32-36
34.6+1.0
ns
83.3-363.0
30.2-35.4
32.7 ±1.0
ns
23.6-30.0
26.4 ±1.6
ns
18.2-24.0
20.9 ±1.4
ns
23.0-28.8
25.8+1.1
ns
4.5-7.4
6.0+0.6
ns
43.9-54.0
47.3 ±2.0
ns
52.8-60.4
56.6+1.8
ns
13.3-19.9
16.1 ±1.6
X
33.7-38.6
36.2+1.2
ns
27.0-31.7
30.0 ±1.1
ns
12.9-20.9
17.1 ±1.8
X
9.4-11.1
10.2 ±0.4
X
24.8-31.0
28.4 ±1.2
ns
9.7-11.8
10.8 ±0.5
ns
12.6-15.3
13.9 ±0.7
ns
17.1-24.3
21.3 ±1.5
X
64.6-73.5
68.2 ±2.1
ns
28.6-35.2
31.8 ±1.4
ns
33.2-41.6
36.6 ±1.8
ns
21.4-28.7
25.0 ±1.6
X
13.6-18.4
16.4 ±1.0
ns
36.3-46.5
40.3 ±2.6
ns
ns
ns
ns
ns
ns
X
X
ns
ns
ns
ns
ns
ns
ns
X
ns
ns
ns
X
ns
ns
Table 5
Factor loadings for
principal component (PC)
analysis of
meristic characters
for Sebastes ciliatus and S
variabilis
collected in all depths and regions.
PCI
PC2
PC3
Lateral-line pores
-0.6139
-0.1000
-0.4151
Gill raker
-0.5993
0.1360
0.5217
Dorsal-fin rays
-0.2731
-0.5625
0.4739
Anal-fin rays
-0.0138
-0.7389
-0.3954
Pectoral-fin rays
0.4349
-0.3304
0.4180
Lateral body scales with many (ca. 5-7) accessory scales
in posterior field. Maxilla and underside of mandible com-
pletely scaled; suborbital region scaled; branchiostegal
rays scaled.
Gill rakers long, ll.3-20.77r HL. and slender on first
arch, longest raker in joint between cerato- and hypobran-
chials, length of preceding and succeeding rakers progres-
sively shorter; rudiments absent. Pseudobranchs 37-38.
Body color in life and after preservation dark, black to
gray, lighter in deeper water, lightening ventrally on belly
and occasional reddening from base of pectoral fin to base
of anal fin, uniformly dark from soft dorsal fin to anal-fin
base; vague darker mottling tapering from origin of soft
Orr and Blackburn: Resurrection of Sebastes variabilis and redescnption of Sebastes ciliatus
337
0.34 ■
0.32 •
0.30 -
0.28 -
0.26 -
0.24 -
0.22 -
0.20 -
A
CO
O
Q_
C/3
i 1 r 1 1 i
0.45
0.5
0.55
0.6
SPC2
065
0.7
0.75
O
Q.
W
4 -|
3 ■
2
1
0
-1
-2
-3
-4
-5
-3
4
3
2
1
0 ■
-1
-2
-3
-4
-2.5
-1.5
-0.5
0.5
PC1
1.5
2.5
3.5
4.5
0.45 0.5 0.55 0.6 0.65
PC1 (meristic)
0.7
0.75
Figure 3
Plots of sheared ( SPC ) and standard principal component < PC ) scores for
morphometric and meristic characters for Sebastes ciliatus (diamonds)
and S. variabilis (triangles). (A) Morphometric characters only, (Bi
meristic characters only, and ( C ) morphometric ( SPC2 ) versus meristic
characters (PCI).
dorsal fin ventrally and forward narrowing across lateral
line, faint darker mottling also present farther posterior
at soft dorsal-fin base. Head nearly uniformly dark, two
faint bars extending from orbit to preopercle, a faint bar
along anterior margin of maxilla. Median fins uniformly
dark gray to black. Pectoral fins, including lower rays, gray
to black. Pelvic fins dark. Peritoneum jet black; stomach,
pyloric caeca, and intestines pale. See Figure 1 (A-C, E),
and previously published color figures of Kessler (1985.
"S. ciliatus, dark dusky rockfish"), Kramer and O'Connell
(1986; "S. ciliatus, dark"), Kramer and O'Connell (1988,
1995; "S. ciliatus, Kodiak specimen," and "shallow water
specimen"), Orr et al. (1998, 2000; "S. sp. cf. ciliatus, dark
dusky rockfish"), Orr and Reuter (2002; "S. ciliatus, dark
dusky"), and Mecklenburg et al. (2002; "S. ciliatus, dark
phase"). Juveniles in life (Fig. 1C) similar to adults in
general body color, often brassy on breast and head.
Largest specimen examined 340.0 mm (425 mm TL,
412 mm fork length; UW 46068). Maximum size confirmed
470 mm fork length (RACE Division6; Orr, personal observ.).
Distribution and natural history
The range of Sebastes ciliatus based on material exam-
ined extends from the western Aleutian Islands and east-
6 RACE (Resource Assessment and Conservation Engineering)
Division. 2002. Unpubl. data from RACE database. Alaska
Fisheries Science Center, Natl. Mar. Fish. Serv., NOAA, 7600
Sand Point Way NE, Seattle, WA 98115.
338
Fishery Bulletin 102(2)
Table 6
Factor loadings for shea
■ed principal component (SPC)
analysis of morphometric
characters for specimens exam-
ined across all depths and regions
for Sebastes
ciliatus
and S. variabilis.
PC 1
SPC2
SPC3
Head length
0.1526
0.1131
0.0416
Orbit length
0.1853
0.2090
0.0988
Depth at anal-fin origin
0.2564
0.1335
-0.0136
Snout length
0.2452
0.1109
0.0240
Interorbital width
0.5753
-0.8081
-0.0485
Suborbital depth
0.1905
0.1481
0.0675
Upper jaw length
0.1837
0.1394
0.0713
Lower jaw length
0.2332
0.2321
-0.9231
Gill raker length
0.1635
0.0768
0.0840
Body thickness
0.2045
0.1692
0.1404
Pectoral-fin base
0.2119
0.1146
0.1139
Pectoral-fin ray length
0.1551
0.0848
0.0105
Caudal peduncle depth
0.2113
0.1436
0.1757
Caudal peduncle
0.1885
0.1561
0.0262
dorsal length
Caudal peduncle
0.1601
0.0829
0.0773
ventral length
Pre-anal-fin length
0.1313
0.0732
0.0800
Predorsal-fin length
0.1516
0.1063
0.0456
Spinous dorsal-fin
0.1549
0.0976
0.0504
base length
Soft dorsal-fin base
0.1602
0.1271
0.1493
length
Anal-fin base length
0.1671
0.1266
0.1140
Table 7
Factor loadings for sheared principal component (SPCl
analysis of morphometric characters for shallow water
Sebastes ciliatus and S. variabilis.
PCI
SPC2
SPC3
Head length
0.1149
0.0855
0.0497
Orbit length
0.1504
0.1223
0.0408
Depth at anal-fin origin
0.1876
0.1908
0.1111
Snout length
0.1586
0.0886
0.0687
Interorbital width
0.2465
0.1636
-0.0394
Suborbital depth
0.2428
0.1156
0.0024
Upper jaw length
0.5843
-0.8015
0.0042
Lower jaw length
0.1876
0.1565
0.0745
Gill raker length
0.2431
0.1866
-0.9189
Body thickness
0.1782
0.1386
0.0734
Pectoral-fin base
0.2103
0.1889
0.1819
Pectoral-fin ray length
0.2108
0.1308
0.1165
Caudal peduncle depth
0.1550
0.1033
0.0162
Caudal peduncle
dorsal length
0.2126
0.1552
0.1930
Caudal peduncle
0.1854
0.1426
-0.0224
ventral length
Pre-anal-fin length
0.1520
0.1098
0.0381
Predorsal-fin length
0.1499
0.1124
0.0603
Spinous dorsal-fin
base length
0.1516
0.0953
0.0358
Soft dorsal-fin base
0.1642
0.1395
0.1171
length
Anal-fin base length
0.1697
0.1061
0.1310
ern Bering Sea, through the Gulf of Alaska, to southeast
Alaska. Other documented records extend its range south
to Johnstone Strait, British Columbia (Peden and Wilson,
1976; Fig. 4). It is common throughout its range in shallow
rocky habitats, and our material was collected at depths
from 5 to 160 m, its total recorded depth range.
Sebastes ciliatus is commonly collected with S. melanops
by trawl and hook-and-line gear in shallow waters, where
S. ciliatus is commercially fished as part of the "black
rockfish" fishery and has been often misidentified as S.
melanops. In deeper (>100 ml trawls in Aleutian and Gulf
of Alaska waters. S. ciliatus is commonly found in asso-
ciation with S. alutus (Pacific ocean perch), S. polyspinis
(northern rockfish), and S. variabilis (dusky rockfish). Less
frequently, S. uariegatus (harlequin rockfish), S. zacentrus
(sharpchin rockfish), and S. proriger (redstripe rockfish)
are also captured with S. ciliatus. A large (320 mm; UW
47417) S. ciliatus was found in the stomach of a Pacific cod
(Gadus macrocephalus) collected in the Aleutian Islands.
Females captured in summer (May- July) trawl surveys
are most often ripe with eyed larvae. Near-term females
and males were observed in July in shallow waters off
southeast Alaska in contrast to individuals of S. variabi-
Table 8
Factor loadings for
principal
component (PC) analysis of
meristic characters
for shallow water
Sebastes
ciliatus
and S. variabilis.
PCI
PC2
Lateral-line pores
-0.5933
0.1677
Gill rakers
-0.4274
-0.6851
Dorsal-fin rays
-0.5742
-0.0777
Anal-fin rays
-0.3667
0.6191
Pectoral-fin rays
0.0325
-0.3364
lis, which were all immature at this time (Orr, personal
observ.).
Etymology
The specific name ciliatus is derived from the Latin word
"cilium" for "eyelid" or "eyelash" and alludes to the numer-
Orr and Blackburn: Resurrection of Sebastes variabilis and redescnption of Sebastes ciliatus
339
Figure 4
Distribution of Sebastes ciliatus based on material examined (open circles) and recent National Marine Fisheries
Service survey data (closed circles) for the years 1999 to 2002. Each symbol may represent more than one capture.
ous accessory scales (similar to fringing eyelashes) that
are found on the posterior field of the larger scales in most
species of Sebastes (Tilesius, 1813).
Remarks
Tilesius (1813) based his description of Epinephelus cil-
iatus on a single specimen collected in the North Pacific
"bordering Kamchatka and America," probably during
the Krusenstern expedition of 1803-06 (Bauchot et al.,
1997; Svetovidov, 1978, 1981; Pietsch, 1995). Although the
illustration of the specimen was published (Tilesius, 1813;
Fig. 2B), the specimen itself has since been lost, probably
before the transfer of the Kunstkammer collection to the
Zoological Museum of the Academy of Sciences, St. Peters-
burg ( Svetovidov, 1978, 1981). Because S. ciliatus may easily
be confused with other dark-colored Sebastes and S. variabi-
lis, we have herein designated UW 43493, collected in Lynn
Canal of southeast Alaska, as the neotype of S. ciliatus.
The illustration of the holotype of E. ciliatus Tilesius
(1813) depicts a uniformly dark individual of Sebastes, and
most of its reported meristics and other characters are
consistent with both S. ciliatus and S. variabilis. However,
its lateral-line pore count is low at 43, and although falling
well within the range found in the material examined of
S. ciliatus, the count is represented in only one individual
of S. variabilis examined. Along with its low lateral-line
pore count, a moderate symphyseal knob is illustrated,
similar to that of S. ciliatus, excluding its identification
as S. melanops, a common and similarly colored Sebastes
found within the geographic range of S. ciliatus.
The anal-fin posterior margin of the specimen illus-
trated shows a moderate posterior slant, and tips of the
posteriormost rays extend well past those of the anterior
rays. Sebastes ciliatus may have an anal fin with a slight
posterior slant, unlike S. variabilis, but it is never as
pronounced as the illustration indicates. However, this
character is not found in any other dark-colored species of
Sebastes presently known from the Aleutian Islands and
northern Gulf of Alaska west of Kodiak Island. Sebastes
entomelas has an anal fin with a strong posterior slant to
its posterior margin, but the northernmost record of this
species is Kodiak Island (Allen and Smith, 1988; Love,
2002 ; Mecklenburg et al., 2002 ) where it is rare ( RACE Di-
vision6). Sebastes entomelas also has a much higher count
of lateral-line pores (50-60; Love et al., 2002).
One syntype of Perca variabilis was sent by Martin H.
K. Lichtenstein (1780-1857), the director of the Berlin
Zoological Museum in 1813, to Georges Cuvier at the Mu-
seum National d'Histoire Naturelle in Paris, and has been
preserved as MNHN 8670 (Svetovidov, 1981; Fig. 2 A).
Although originally from the collections of Carl Heinrich
Merck (1761-1799; Svetovidov, 1981; Blanc and Hureau,
1968; Bauchot and Desoutter, 1986) and thus contempora-
340
Fishery Bulletin 102(2)
neous with Tilesius's material, this specimen probably did
not serve as the example for Tilesius's (1813) illustration.
The illustration is of the left side of a whole fish, whereas
MNHN 8670 is the dried skin and head of the right side.
Counts and measurements taken from the original descrip-
tion and compared with the specimen indicate that it is
improbable that the left side of this individual was the
subject of the illustration. The counts provided by Tilesius
(1813) include D XIII, (soft rays not given); A III, 8; PI 18;
lateral-line pores 43. MNHN 8670 differs in counts of anal-
fin rays (9) and in lateral-line pores (49). Although the sym-
physeal knob is reduced and the anal-fin margin is strongly
slanted posteriorly in the Tilesius illustration, MNHN 8670
has a strong symphyseal knob and a perpendicular anal-fin
margin with a distinctly pointed tip (Fig. 2, A and B).
Sebastes variabilis (Pallas, 1814)
Dusky rockfish
Figs. 1-3, 5; Tables 1-8
Perca variabilis Pallas, 1814:241 (original description,
three? specimens; lectotype hereby designated, MNHN
8670, dried skin, sex unknown, 343.7 mm. "mari Ameri-
cam borealum"; other syntypes apparently lost).
Sebastes variabilis: Cuvier, in Cuvier and Valenciennes,
1829:547 (new combination).
Sebastichthys ciliatus: Jordan and Jouy, 1881:8 (in part,
new combination).
Sebastodes ciliatus: Jordan and Gilbert, 1883:658 (in part,
new combination).
Sebastosto/nus ciliatus: Eigenmann and Beeson, 1894:388
(in part, new combination).
Sebastes ciliatus: Westrheim, 1973:1230 (in part, new
combination).
Material examined
A total of 253 specimens, 48.0-430.8 mm, including the
lectotype listed above, were examined. See Appendix for
additional catalog numbers and locality data.
Diagnosis
A species of Sebastes with the following combination of
character states: body light yellow to greenish brown to
gray, typically greenish brown, with orange flecks vari-
ously present on sides, particularly light ventrally above
anal-fin base and on ventral pectoral-fin rays; peritoneum
light gray to jet black; symphyseal knob strong; extrin-
sic swimbladder muscle with a single section of striated
muscle, lacking anterior fascia, otherwise of type I (a-z)
of Hallacher (1974); lateral-line pores 43-54, lateral-line
scales 47-63; pectoral-fin rays 16-19; anal-fin rays 7-9;
dorsal-fin rays 13-16; vertebrae 28-29 (11-12 + 16-18).
Description
D XIII-XIV, 13-16; A III, 7-9; PI 16-19, 7-11 simple;
lateral-line pores 43-54, scales 47-63; gill rakers 32-37
110-11 + 22-26); vertebrae 28-29 ( 11-12 + 16-18) (one of
ten specimens with 27 vertebrae, with one caudal vertebra
bearing two neural and two haemal spines). Meristic fre-
quency and statistical data are presented in Tables 2-4.
Morphometric data and statistics are presented in
Tables 1 and 4. Body relatively deep, especially at nape,
depth at pelvic-fin base 29. 2-40. 91 SL: profile of dorsal
margin of head steep to nape above anterodorsal margin
of gill slit, flattening to dorsal-fin origin. Mouth large,
with posterior end of maxilla extending beyond pupil to or
beyond posterior rim of orbit, maxilla length 42.7-54.01
HL; symphyseal knob strong with blunt tip, lower-jaw
length 52.8-62.71 HL; mandibular pores of moderate
size. Cranial spines weak, in large adults covered by flesh,
head smooth. Nasal spines invariably present; parietal
ridge invariably present and small spine typically pres-
ent; postocular and tympanic spines typically absent or
obsolete in adults (weak postocular spines present on at
least one side in 29.71 and weak tympanic spines present
on at least one side in 50.61 of specimens examined) are
typically present in juveniles. Interorbital region wide,
22.5-30.41 HL, strongly convex; parietal ridges weak,
and area between ridges slightly convex; preopercular
spines 5, directed posteroventrally; two opercular spines,
upper spine directed posteriorly, lower spine directed
posteroventrally; posttemporal and supracleithral spines
present; lachrymal spines rounded, small; dorsal margin
of opercle nearly horizontal; lower margin of gill cover
with small spines: posteroventral tip of subopercle and
anteroventral tip of interopercle rugose or with 1 or 2
small spines.
Dorsal-fin origin above anterodorsal portion of gill slit;
dorsal fin continuous, gradually increasing in height to
spine IV or V and decreasing in height to spine XII; spine
XIII much larger, forming anterior support of soft dorsal
fin; membranes of spinous dorsal fin moderately incised,
less so posteriorly; soft dorsal fin with anterior rays lon-
gest, posterior rays gradually shortening. Anal-fin spine
II shorter than III (5.8-13.6 vs. 9.5-15.61 SL), anterior
rays longest on soft rayed portion of anal fin, posterior rays
gradually shortening, posterior margin perpendicular
to body axis or with slight posterior slant, anterior ray
tips directly ventral to posterior tips, anterior tip of anal
fin typically pointed. Pectoral fins with ray 10 longest,
extending to or slightly anterior to vent, fin-ray length
23.5-31.01 SL, fin base to ray tip length 24.2-35.11 SL;
fin-base width 9.4-11.21 SL. Pelvic fins extend about 601
of distance from pelvic-fin base to anal-fin origin, falling
well short of vent, ray length 19.2-29.21 SL, spine length
44.9-70.71 ray length. Caudal fin slightly emarginate,
length 15.4-26.91 SL. Vent positioned below dorsal-fin
spine 10, 2.2-7.01 SL from anal-fin origin.
Lateral body scales with many (ca. 5-7) accessory scales
in posterior field. Maxilla and underside of mandible com-
pletely scaled; suborbital region scaled; branchiostegal
rays scaled.
Gill rakers long, 11.6-19.91 HL, and slender on first
arch, longest raker in joint between cerato- and hypobran-
chials, length of preceding and succeeding rakers progres-
sively shorter; rudiments absent. Pseudobranchs 36-38.
Orr and Blackburn: Resurrection of Sebastes variabilis and redescription of Sebastes aliatus
341
Figure 5
Distribution of Sebastes variabilis based on materia] examined (open circles! and recent National Marine Fisheries
Service survey data (closed circles) for the years 1999 to 2002. Each symbol may represent more than one capture.
Body color in life variable (Fig. ID); adults typically
light, greenish-tan (Fig. IB), often darker gray dorsally
(Fig. ID), rarely lighter yellow overall (Fig. ID); invari-
ably lightening ventrally to pinkish-white on head, belly,
anal-fin base, and caudal peduncle; a clear demarcation
between darker dorsum and light ventrum above anal-fin
base; vague darker mottling tapering from origin of soft
dorsal-fin ventrally and forward narrowing across lateral
line, faint darker mottling also present farther posterior at
soft dorsal-fin base, mottling most evident in tan individu-
als; brown to orange "flecks" present on sides of body on
posterior fields of scales, appearing as darker speckling in
juveniles. Head similar in background color to body, two
prominent bars extending from orbit to preopercle, a prom-
inent bar along anterior margin of maxilla in darker indi-
viduals (these bars obsolete in light individuals). Median
fins and pelvic fins uniformly gray, lighter in light-bodied
individuals. Pectoral fins brown to grayish pink; lower
rays pink. Peritoneum light gray to jet black, typically
dark gray; stomach, pyloric caeca, and intestines pale.
See Figure 1 ( A-D) and previously published color figures
of Kessler (1985; "Sebastes sp., light dusky rockfish"),
Kramer and O'Connell (1986; "S. ciliatus, light"), Kramer
and O'Connell (1988, 1995; "S. ciliatus, light specimen"),
Orr et al. (1998, 2000; "S. ciliatus, light dusky rockfish"),
Orr and Reuter (2002; "light dusky"), Mecklenburg et al.
(2002; "light phase").
Juveniles in life (Fig. 1C) lighter than adults, with dor-
sum light-brown to tan, background covered with orange-
brown speckles, often with distinct dark band at base of
soft dorsal fin; head brassy; ventrum pink on lower jaw.
breast, and base of anal fin, lightening to white on belly.
Largest specimen examined 430.8 mm (527.7 mm fork
length [FL], 541.3 mm TL; UW 44253). Maximum size
reported 590 mm FL (RACE Division6).
Distribution and natural history
Sebastes variabilis is recorded from a single specimen off
Hokkaido, Japan (Shinohara et al., 1994), and from other
specimens collected from the east coast of Kamchatka
to Cape Ol'utorskii (at 60°N) in the western Bering Sea.
along the Aleutian Islands to 60°N in the eastern Bering
Sea, through the Gulf of Alaska south to Johnstone Strait,
British Columbia (Peden and Wilson, 1976; Richards and
Westrheim, 1988; Fig. 5), and to central Oregon (based on
a recently collected single specimen [UW 46575] ). The ear-
lier record of Schultz (1936) and Alverson and Welander
( 1952 ) from Washington at Neah Bay was reidentified by
Westrheim (1968) as S. entomelas.
Although the depth of collection for material examined
ranges from 6 to 370 m, and the species is recorded at
depths to 675 m, large adults are commonly found along
the edge of the continental shelf at depths of 100-300 m,
342
Fishery Bulletin 102(2)
where the species is the target of commercial fisheries in
the Gulf of Alaska. During trawl surveys, it is most com-
monly associated with S. alutus and S. polyspinis, and
at greater depths with S. aleutianus (rougheye rockfish)
throughout its range in Alaskan waters (Reuter, 1999;
Ackley and Heifetz, 2001).
Females and males captured during summer ( May- July )
trawl surveys ranged widely in maturity state. Occasional
ripe females were observed, although most females were
maturing (Orr, personal observ. ). A high percentage of
females caught in trawl surveys during early April off
southeast Alaska were releasing larvae, indicating that
parturition occurs in the spring (Lunsford7). During July
in shallower waters (ca. 40 m) of southeast Alaska, all S.
variabilis collected were immature.
Etymology
The specific name variabilis is presumed to be a reference
by Pallas (1814) to the wide range of body color in the
species.
Remarks
Pallas ( 1814 ) described Perca variabilis from at least three
specimens probably collected by Merck during the 1786-94
Billings expedition to the Russian Far East, including the
Aleutian Islands, eastern Bering Sea, and northern Gulf
of Alaska (Schmidt, 1950; Svetovidov, 1978, 1981; Pierce,
1990). One specimen was more completely described and
used by him to obtain a set of counts and measurements.
The other specimens were used to describe variation in
the species, as in the following excerpt translated by the
authors from the Latin text of Pallas (1814): "Body colored
according to life and sex, varied, sometimes dark blue,
belly white, fins blackish; female red below; those older
wholly red or even purplish...." Pallas (1814) ultimately
based the name P. variabilis on the supposed variability
in color in this species.
Jordan and Evermann (1898) examined an individual
from the Pallas collection, recognized by him as the "sum-
mer variety" of P. variabilis (ZMB 8145). They identified
this "summer variety" as Sebastes aleutianus Jordan and
Evermann (Jordan, 1884, 1885; Jordan and Evermann,
1898), a species easily distinguished from both S. varia-
bilis and S. ciliatus by its full complement of eight pairs
of strong cranial spines. These specimens have since been
lost, probably during the destruction of the Berlin Zoo-
logical Museum during World War II (Paepke and Fricke,
1992). Although Jordan and Gilbert (1883) wrote that
S. proriger was also confounded with S. ciliatus, Jordan
(1885) and Jordan and Evermann (1898) corrected this
statement, noting that only S. ciliatus and S. aleutianus
were included within the material described as E. ciliatus
and P. variabilis by Tilesius and Pallas.
7 Lunsford, C. 2002. Personal commun. National Marine
Fisheries Service, Aukc Bay Laboratory, Alaska Fisheries
Science Center, 11305 Glacier Highway, Juneau, AK 99801-
8626.
Although MNHN 8670 (Fig. 2A) is from the Pallas col-
lection (Svetovidov, 1978, 1981), it is apparently not the
specimen used for the complete description. In his original
account, Pallas (1814) listed the following meristic data
(modified to standard notation): D XIII, 15; A III, 7; PI 17
(8 simple). Although the dorsal-fin ray count is identical
with that of the MNHN 8670 specimen, both anal- and
pectoral-fin ray counts differ. All elements are well pre-
served and easily counted.
Comparisons of proportions are more difficult to inter-
pret because measurements had not been standardized
at the time of the original description. However, of those
measurements that can be readily compared, the following
significant differences were found, providing additional
evidence that this individual was not the specimen used
for the primary description: total length (391.6 mm in
Pallas [1814; "longitudo majoris speciminis"] vs. 414.0 mm
taken from MNHN 8670), head length (101.6 mm ["capi-
tis a summa maxilla ad operculum angulum"] vs. either
96.6 mm [standard head length] or 110.2 mm [head length
to tip of lower jaw]). The specimen used by Pallas for the
detailed meristics and morphometries is presumed lost
(Svetovidov, 1978).
Ayres ( 1854) misidentified S. melanops from the vicinity
of San Francisco Bay as S. variabilis. Giinther (I860) and
Ayres (1862, 1863) placed S. variabilis of Ayres into the
synonymy of S. melanops.
Comparisons
Sebastes variabilis is most similar to S. ciliatus; the latter
is distinguished by its uniformly dark-blue to black color.
Sebastes ciliatus is invariably dark at the base of the anal
fin and on the lower pectoral rays, areas of lighter color in
S. variabilis even in those individuals that have an overall
dark body. The peritoneum of S. ciliatus is always jet black,
unlike the usual gray peritoneum of S. variabilis, which
however may often be dark or occasionally jet black. In
combination with these color differences, a low count of
39-42 lateral-line pores will distinguish S. ciliatus from
S. variabilis, although the total range of counts overlaps
considerably.
The extrinsic morphological features of the swimblad-
der of both S. ciliatus and S. variabilis are of type I (a-z)
of Hallacher (1974) in which the anterior muscle mass
originates from the occipital region of the neurocranium.
attaches to the pectoral girdle near the insertion of Baude-
lot's ligament, passes between the epineural and pleural
ribs of vertebrae 3 and 4, passes ventral to the pleural rib
of vertebrae 5, and continues posteriorly as three tendons
that insert on the pleural ribs of vertebrae 8, 9, and 10.
In S. ciliatus and not S. variabilis, the anterior striated
muscle mass is separated into two sections by a thin fascia,
similar to the condition reported in S. paucispinis alone
among species of Sebastes (Hallacher, 1974). The morpho-
logical features of the complex differ significantly in S.
paucispinis, however, in that the striated muscle does not
attach to the pectoral girdle but bypasses it to insert by a
single tendon into the posterior portion of the swimblad-
der. Only five specimens each of S. ciliatus and S. varia-
Orr and Blackburn: Resurrection of Sebastes variabilis and redescription of Sebastes ciliatus
343
bills were dissected in the present study to examine these
muscles. Additional material should be examined to assess
the intraspecific variability and systematic significance of
this character complex.
Typical habitats of these two species also differ. Adult
S. ciliatus are found in nearshore shallow habitats at
maximum depths of 160 m and are abundant in protected
coves on the outer coast of Alaska. Sebastes variabilis, in
contrast, is found along the continental shelf margin at
depths to 675 m. However, adult S. variabilis have also
been collected in nearshore waters as shallow as 40 m ( UW
43494). In areas of sympatry, such as the inside waters
in Lynn Canal of southeast Alaska and Monashka Bay of
Kodiak Island, S. variabilis is found at greater depths in
stronger current, whereas S. ciliatus is found, often with
S. melanops, among kelp (Macrocystis) on rocky ledges
(Blackburn and Orr, personal observ. ).
Other uniformly dark colored species of Sebastes, such
as S. melanops and S. mystinus, may also be confused
with S. ciliatus and darker individuals of S. variabilis, al-
though both may be distinguished on the basis of color and
morphological features. The body of S. melanops is dark
bluish-black, has black speckling on the dorsum and lat-
eral surfaces, and a distinctly white ventrum (in contrast
with the slightly lighter ventrum of S. ciliatus (Fig. IE]).
Unlike S. ciliatus, in which the peritoneum is jet black, S.
melanops has a white peritoneum. In S. melanops, five or
six faint light blotches slightly larger than the orbit are
present on the dorsum about midway between the lateral
line and the dorsal-fin base. These blotches are especially
prominent underwater, and in Alaska easily distinguish
S. melanops from both S. variabilis and S. ciliatus, which
lack blotches (Lauth8; see color figures of Love, 2002, and
Stewart and Love, 2002). The symphyseal knob in S.
melanops is obsolete, consisting only of a fleshy pad at the
tip of the mandible, unlike the distinct bony knob of S.
ciliatus and S. variabilis. Mandibular pores of S. melanops
are obsolete, as compared with the larger, readily appar-
ent pores of S. ciliatus and S. variabilis. Vertebral counts
also differ, from 28-29 in S. ciliatus and S. variabilis to 26
in S. melanops. Sebastes melanops ranges from southern
California to Atka Island in the Aleutian Islands (Meck-
lenburg et al., 2002) and the southern Bering Sea, where
its presence is documented by a single recent collection
(UW 47037). Most previous reports from the Bering Sea
may be of S. ciliatus.
Sebastes mystinus is also similar to S. ciliatus but may
be distinguished by the four distinct dark bars across its
head and nape contrasting with its general body color of
light mottled bluish-gray. The mouth of S. mystinus is
smaller than that of S. ciliatus, and the maxilla extends
only to the middle of the pupil rather than to the posterior
portion of the orbit as in S. ciliatus. Like S. melanops and
most Pacific Sebastes, S. mystinus has 26-27 vertebrae,
compared to the 28-29 vertebrae of S. ciliatus and S.
s Lauth, R. R. 1998. Personal commun. Resource Assess-
ment and Conservation Engineering Division, Alaska Fisheries
Science Center, Natl. Mar. Fish. Serv., NOAA, 7600 Sand Point
Way NE, Seattle, WA 98115.
variabilis. Sebastes mystinus has been recorded from Sitka
Harbor, Alaska (Kramer and O'Connell, 1995), to Punta
Santo Tomas, northern Baja California (Hobson, 2002).
Earlier reports from Kodiak Island, the Aleutian Islands,
and Bering Sea are undocumented ( Quast and Hall. 1972 ;
Kramer and O'Connell, 1995; Mecklenburg et al., 2002)
and probably refer to S. ciliatus.
Sebastes polyspmis is commonly caught in trawls and
may be confused with S. variabilis, especially when pre-
served. It can be distinguished from S. variabilis by its
modal count of 14 dorsal-fin spines and light (pink or white
when live) oblique band across the lower rays of the pecto-
ral fin, which remains prominent when recently preserved.
In life, the overall color of S. polyspinis is reddish-orange
to pink, overlaid with gray-green mottling and fine green
spots. Evermann and Goldsborough (1907) considered the
then undescribed S. polyspinis within the range of varia-
tion of "S. ciliatus" because at least one lot (USNM 6243)
was misidentified by them as "S. ciliatus." They probably
also confused S. melanops with S. variabilis, or possibly S.
polyspinis, describing the color in life of S. melanops from
Alaska as "olive-brown, blotched with dirty red." Sebastes
melanops never has a trace of red, whereas the most com-
mon color pattern of S. variabilis could be adequately
described by this phrase.
In the western Pacific, two species, the dark-colored S.
taczanowskii and the light-colored S. schlegelll, may be
confused with S. ciliatus and S. variabilis, respectively.
Both may be distinguished from S. ciliatus and S. varia-
bilis by modal counts of pectoral-fin rays (15 in S. tacza-
nowskii and 17 in S. schlegelii vs. 18 in both S. ciliatus and
S. variabilis) and vertebrae (26 in both S. taczanowskii
and S. schlegelii vs. 28-29 in S. ciliatus and S. variabilis).
Sebastes schlegelii may also be distinguished by its typi-
cal dorsal-fin spine count of 12 (vs. 13 in S. ciliatus and S.
variabilis).
Implications for fisheries management
The dusky rockfish (S. variabilis) and the dark rockfish
(S. ciliatus) have been subjected to two distinct fisheries
separately managed by U.S. federal and Alaska state
agencies: S. variabilis is captured in the offshore trawl
fishery; S. ciliatus, in the nearshore jig fishery. Although
the offshore fisheries for dusky rockfish only inciden-
tally catch the dark rockfish and are managed for dusky
rockfish, the nearshore fishery is not managed for dark
rockfish, and instead the species has been routinely mis-
identified as black rockfish (S. melanops). Sebastes ciliatus
has been found to comprise up to 25<7<r of the catch in the
"black rockfish" jig fishery of the northern Gulf of Alaska
(Clausen et al.1).
Several differences in biologically significant param-
eters were evident from specimens examined in our study
and from observations in survey data. The two species
are typically found in different habitats, attain different
maximum sizes, and show differences in reproductive
seasonality. Recognizing the two as distinct species is the
first step towards establishing a biologically based, spe-
cies-specific management scheme.
344
Fishery Bulletin 102(2)
Acknowledgments
We appreciate the early efforts of J. Geil and J. Westrheim
to encourage this research through spirited discussion and
by providing unpublished data, courtesy of Fisheries and
Oceans Canada, Pacific Biological Station. We thank D.
Clausen, C. Lunsford, T. W. Pietsch, D. E. Stevenson, and
M. E. Wilkins for overall reviews and K. Mier for a statisti-
cal review. The care and transportation of specimens from
Alaska is not a small task and we thank the many collec-
tors who made this project possible: fisheries observers W.
Benecki, M. Brown, K. Barber, T. Droz, J. Peeples, and J.
Wiersema; personnel of the AFSC's RACE Division W. C.
Flerx, R. Harrison, R. R. Lauth, G. R. Hoff, M. Martin, N.
W. Raring, J. S. Stark, H. Zenger, and M. Zimmermann.
For support of nearshore field work in southeast Alaska,
we thank J. Fujioka, D. Clausen, and B. Wing. The Uni-
versity of Washington Fish Collection archived most of
the fresh material examined for this study and we appreci-
ate the support of the curator (T. W. Pietsch) and collec-
tions managers (K. E. Pearson and B. W. Urbain). We also
thank the following curators and collections managers
and their institutions for hosting visits for examination
of material or for the loan of specimens: B. Wing ( ABL).
K. Sendall (BCPM), W. Eschmeyer, D. Catania (CAS),
B. Sheiko (KIE). J.-C. Hureau, G. Duhamel, P. Pruvost
(MNHN), D. F. Markle (OSU), and G. D. Johnson. S.
Jewett, and S. J. Raredon (USNM).
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Appendix
Material examined
Sebastes ciliatus Bering Sea: UW 45488, 1(329.7 mm),
56.65°N, 167.8167°W, 100 m depth, 5 February 2001;
UW 22474, 1(221.7 mm), 59.25°N, 177.8167°W, 160 m
depth, 1987. Aleutian Islands: UW 43447, 1(290 mm),
51.2534°N, 179.2689°E, 165 m depth, 26 July 1997; UW
45588, 2(240-380 rami, Aleutian Is., FV Vesteraalen,
1997; ABL 69-13, 2(228.8-250.9 mm), Amchitka I.,
Constantine Harbor, 51.4°N, 179.3667°E, 6 September
1968; UW 46489 (UK T002383), 1(279.7 mm), 51.2707°N,
179.2118°E, 98 m depth, 26 July 1997; UW 45498,
1(318.5 mm), 51.9921°N, 174.1031°W, 93 m depth, 6 July
1997; UW 43039, 4(83.8-206.5 mm), Amchitka I., Con-
stantine Harbor, off Kirilof, 7 December 1961; UW 43423,
2(295.1-315.9 mm), Amchitka I., 51.3833°N, 178.9°E, 88
m depth, 20 April 1993; UW 43436, 12(272-315 mm),
51.7552°N, 175.6726°E, 94 m depth, 1 August 1997; UW
14416, 1(183 mm), Amchitka I., Constantine Harbor,
5 September 1955; UW 43458, 5(263.9-288.6 mm),
51.2707°N, 179.2118°E, 98 m depth, 26 July 1997; UW
4766, 1(189 mm), Atka I., Atka village, 18 August 1938;
UW 46483, 2(230-253 mm), 51.9730°N, 176.0841°E,
78 m depth, 20 July 2000; UW 46484, 2(275-293 mm),
51.9638°N, 176.0288°E, 64 m depth, 20 July 2000; UW
47417, 1(320 mm), Aleutian Is., recovered from stomach
of Gadus macrocephalus. Gulf of Alaska: UW 43242,
6(320-390 mm), 53.7345°N, 165.5425°W, 89 m depth,
25 June 1996; UW 43272, 5(274-325.5 mm), 55.093°N,
157.8048°W, 76 m depth, 10 June 1996; UW 43420,
1(334.7 mm), 55.9042°N, 157.0751°W, 101 m depth, 18
June 1996; UW 45508, 2(242.4-292.6 mm), 55.1056°N,
157.9594°W, 78 m depth, 2 June 1999; UW 45512,
1(235.2 mm), 57.3806°N, 154.8009°W, 67 m depth, 7 June
1999; UW 45509, 1(298 mm), 54.3215°N, 161.8107°W,
72 m depth, 23 May 1999; UW 47412. 1(323.7 mm),
52.8953°N, 168.297°W, 99 m depth, 21 May 2001; UW
46488, 1(270 mm), 56.3686°N, 154.0495°W, 69 m depth, 24
June 2001; UW 46584, 1(295 mm), 55.1056°N, 157.9594°W,
78 m depth, 2 June 1999; UW 46485, 1(320.1 mm),
55.01862°N, 157.882°W, 76 m depth, 8 June 2001. Kodiak
Island area: UW 43059, 1(200.7 mm). Kodiakl.. Monashka
Bay, SW of Trenton Pt., 57.8367°N, 152.4°W, 28 July 1977;
UW 47289, 2( 169-203.7 mm), Kodiak I., Monashka Bay, 5
m depth, 57.8383°N, 152.4283°W, 5 m depth, 31 July 1982;
UW 44035, 2(216.7-274.5 mm), Kodiak I., Monashka
Bay, 57.8367°N, 152.4°W, 18 m depth, 2 August 1982; UW
44036, 11(178.2-263.7 mm), Kodiak I., Monashka Bay,
57.8383°N, 152.4283°W, 12 m depth, 3 August 1982; UW
44045, 19(140.6-307.8 mm), Kodiak I., Monashka Bay,
57.8383°N, 152.4283°W, 15 m depth, 12 August 1982; UW
44049, 1(291.6 mm), Kodiak I., Monashka Bay, 57.8383°N,
152.4283°W, 12 m depth, 11 September 1982; UW 44050,
1(331 mm), NE of Kodiak I., Triplets Is., 57.98°N, 152.48°W.
18 m depth. 1 July 1983; UW 44051, 1(319.7 mm). Kodiak
I., Monashka Bay, 57.8367°N, 152.4°W, 6 m depth, 14
October 1982. Southeast Alaska: ABL 60-7, 1(164 mm),
Kuiu I., Washington Bay, ca. 5 mi W of Petersburg. 2 June
1960; ABL 62-105, 1(224.5 mm), Little Port Walter, SE
tip of Baranoff I.; ABL 68-295, 1(214.1 mm), NW tip of
Lincoln I., ca. 5 mi N of Pt. Retreat, Lynn Canal, 7.5 m
depth, 4 July 1968; ABL 87-15, 1( 111.8 mm), Port Althorp,
58.1317°N, 136.3333°W, 126-146 m depth, 18 July 1982;
UW 43484, 17(202.8-315 mm), Cross Sound, Chicha-
gof I., Soapstone Cove, 58.FN, 136.5°W, 25 m depth, 11
July 1998; UW 43485, 19(124.4-264.7 mm). Lisianski
Strait, 57.925°N, 136.288°W, 10 m depth, 12 July 1998;
UW 43492, 3(153.7-241.1 mm), Lynn Canal, Funter Bay,
58.2467°N, 134.8983°W. 25 m depth, 13 July 1998; UW
22426, 2(134.8-169.4 mm), Alexander Archipelago, Biorka
Channel, S. of Sitka, 33 m depth, 21 February 1982.
Sebastes variabilis Japan: HUMZ 125816, 1(334.0 mm),
Pacific coast off Kushiro, Hokkaido, 42.6833°N, 144.7667°E,
200 m depth, 2 March 1993. Bering Sea: KIE 1277,
1(320.3 mm), east coast of Kamchatka off Cape OTutorskii,
60.4667°N, 171.75°E, 370 m depth, 18 August 1994; KIE
1409, 2(334.5-344.7 mm). Commander Is., Bering I.,
55°N, 166.05°E, 90-120 m depth, 30 April 1996; KIE
uncat, 1(324.5 mm), Karaginskiy Bay, 1 August 1998; UW
43500, 1(314.5 mm), 55.3179°N, 167.5503°W, 147 m depth.
3 July 1998; UW 43499, 1(370 mm), 56.7°N, 163.4°W, 77
m depth, 18 June 1998; UW 43498, 3(330-340 mm).
54.4763°N, 159.6925°W, 4 June 1996; UW 40308,
1(180 mm), 55.36°N, 163.44°W, 84 m depth. 7 May 1990;
UW 40311, 1(187 mm), 55.55°N, 163.75°W, 84 m depth, 3
May 1990; UW 44166, 1(339.3 mm), Alaska, "2-1-92" at
1800 hours; UW 44182, 2(258.2-266 mm). FV Yukon
Challenger, haul 105, 8 March 1993; UW 44253,
1(430.8 mm), Aleutian Is., 52.3°N, 173.8-174.7°W, 106-113
mdepth, lOApril 199LUW 44255, 1(375.7 mm),56.4192°N.
152.853°W, 182 m depth, 24 March 1990; UW 44261,
1(331.1 mm), 57.3333°N. 151.4167°W, 128 m depth; UW
Orr and Blackburn: Resurrection of Sebastes variabilis and redescription of Sebastes ciliatus
347
47411, 1(360 mm), Bering Sea, winter 2001, P. J. Sullivan.
Aleutian Islands: UW 43480, 1(370 mm), 51.2522°N,
179.199°E, 173 m depth, 20 July 1997; UW 43460,
1(340 mm), Aleutian Is., FV Dominator, summer 1997;
UW 43438, 5(330-370 mm), 51.9252°N, 176.3817°W,
122 m depth, 23 July 1997; UW 43455 (KU T002038),
1(275 mm), 51.2707°N, 179.2118°E, 98 m depth, 26 July
1997; UW 45499, 2(327-330 mm), 51.9921°N, 174.1031°W,
93 m depth; UW 45632, 3(83.3-126.1 mm), Amchitka I.,
NE of Sand Beach Cove, 51.5°N, 179°E, 36 m depth, 20
August 1971; UW 45460, 1(98.7 mm), 54.0386°N,
166.6406°W, 85 m depth, 22 May 2000; UW 43441,
2(380-381 mm), 54.17902°N, 166.3255°W, 240 m depth,
12 June 1997; UW 43442, 1(355 mm), 54.0386°N,
166.6572°W, 90 m depth, 13 June 1997; UW 43445,
2(315-340 mm). 54.3773°N, 165.608°W, 90 m depth, 11
June 1997; UW 43459 ( KU T002038), 1(264.2 mm),
51.2707°N, 179.2118°E, 98 m depth, 26 July 1997; UW
43461, 1(330 mm), 53.6905°N, 167.2648°W, 112 m depth.
13 June 1997; UW 43416, 1(290 mm), 54.796°N.
163.2772°W, 89 m depth, 1 June 1996; UW 43443.
1(230 mm), 52.8589°N, 172.4586°E, 146 m depth. 5 August
1997; UW 43444, 1(220 mm), 52.8589°N, 172.4586°E, 146
m depth, 5 August 1997; UW 45588, 2(350-350 mm),
Aleutian Is., FV Vesteraalen, summer 1997; UW 46482,
4(175-225 mm), 52.8280°N. 168.9904°W, 44 m depth, 20
May 2001. Gulf of Alaska: UW 43204, 7(350-420 mm).
55.4327°N, 158.9439°W, 155 m depth. 8 June 1996; UW
43200, 6(320-390 mm), 55.2924°N, 156.6652°W, 114 m
depth, 12 June 1996; UW 43214, 1(190 mm), 57.3175°N,
154.8356°W, 82 m depth, 21 June 1996; UW 43212,
1(300 mm), 54.9351°N, 157.4668°W, 153 m depth, 12 June
1996; UW 43201, 8(290-380 mm), 54.1125°N, 161.7306°W,
111 m depth, 1 June 1996; UW 43203, 8(305-405 mm),
54.1125°N, 161.7306°W, 111 m depth, 1 June 1996; UW
43211, 2(380-410 mm), 54.6806°N, 158.9407°W, 95 m
depth, 8 June 1996; UW 43213, 1(345 mm). 53.9849°N,
163.2663°W, 108 m depth, 30 May 1996; UW 43416,
1(290 mm), 54.7960°N, 163.2772°W, 89 m depth, 1 June
1996; UW 43417, 1(241.4 mm), 55.2898°N, 158.3123°W.
130 m depth. 10 June 1996; UW 43377, 1(356.4 mm),
55.6441°N, 134.9706°W, 202 m depth, 26 July 1996; UW
45587, 4( 325.3-376.2 mm), 55.4351°N, 156.5458°W, 167 m
depth, 15 June 1996; UW 44123, 1(85.3 mm), 57.2128°N.
152.7898°W, 135 m depth, 24 October 1997; KU T3178.
1(348.7 mm). 58.8191°N, 140.3303°W, 185 m depth, 14
July 1999; KU T003215, 1(324.3 mm), 58.8191°N,
140.3303°W, 185 m depth, 14 July 1999; KU T003216,
1(373.9 mm).58.8191°N, 140.3303°W, 185mdepth, 14 July
1999; USNM 32014, 1(240.1 mm), Tolstoi Bay, October
1882; UW 45477, 2(351.5-352.8 mm), 59.1787°N,
149.1194°W, 157 m depth, 29 June 1999; UW 45510,
4(335-370 mm), 58.9658°N, 148.1749°W, 251 m depth, 14
July 1996; UW 45511, 3(206.2-213.4 mm), 57.3806°N,
154.8009°W, 67 m depth, 7 June 1999; UW 46487,
1(333.1 mm), 52.8953°N, 168.297°W, 99 m depth, 21 May
2001; UW 43427, 1(350 mm), 54.2758°N, 161.4326°W, 122
m depth, 3 June 1996; UW 43428, 1(315 mm), 55.9042°N,
157.0751°W, 101 m depth, 18 June 1996; UW 43466,
1(380 mm), 59.4469°N, 140.4849°W, 226 m depth, 30 July
1993; UW 43471, 1(371.7 mm), 58.0895°N, 150.5977°W,
141 m depth, 5 August 1993: UW 43473, 1(342 mm),
59.4469°N, 140.4849°W, 226 m depth, 18 July 1996; UW
22475, 2(240-270 mm), 54.0167°N, 160.8°W, 170 m depth,
4 November 1981; UW 40912, 1(213.6 mm). Prince Wil-
liam Sound, 60.5658°N, 147.5866°W, 70 m depth, 2 Octo-
ber 1989; UW 43214, 1( 187.9 mm), 57.3175°N, 154.8356°W.
82 m depth, 21 June 1996; UW 43251, 8(320-420 mm),
59.5045°N, 145.2262°W, 135 m depth. 17 July 1996.
Kodiak Island area: ABL 66-890, 1(103 mm), Marmot Bay,
Kodiak I., 57.9333°N, 152.1167°W, 1964; UW 44052,
1(215.5 mm), Kodiak; UW 44032, 1(93.4 mm), Cook Inlet,
Kachemak Bay, 59.6°N, 151. 3°W, "<50 m" depth, 8 Septem-
ber 1981; UW 44033, 2(95.7-112 mm), Cook Inlet, Kache-
mak Bay, 59.6°N, 151. 3°W, "<50 m" depth, 10 October
1981; UW 47148, 5(95.5-112 mm). Cook Inlet, Kachemak
Bay, 59.6°N, 151. 3°W. 10 October 1981; UW 44034,
1(363 mm), NE of Kodiak I., Triplets Is., 57.98°N,
152.48°W, 20-24 m depth, 1 July 1982; UW 44037.
1(335 mm), E of Kodiak I., 57.72-57.87°N. 151.8-152.2°W,
crab pot, 18 August 1982; UW 44038, 2(275.3-310 mm),
57.975°N, 151.8433°W, 144 m depth, 19 August 1982; UW
44039, 3(266.7-300.4 mm). Kodiak I., Monashka Bay,
57.8367°N, 152. 4°W. 15 m depth. 31 August 1982; UW
44040. 5(269.7-303.7 mm), Kodiak I., Monashka Bay,
57.8367°N, 152.4°W, 20 m depth, 14 October 1982; UW
44041, 1(281.1 mm), NE of Kodiak I.. Triplets Is., 57.98°N.
152.48°W, 20 m depth, 2 July 1983; UW 43381, 1(340 mm),
Triplets Is., hook and line, 57.98°N, 152.48°W, 34 m depth,
15 July 1993; UW 44042, 2(199.5-215.8 mm), Shelikof
Strait off mouth of Uyak Bay, 57.7°N, 153.92°W, 100 m
depth, 2 April 1984; UW 44043, 12(231.3-271.3 mm),
Shelikof Strait; UW 44044, 2(229.6-257.8 mm), Kodiak I.,
Monashka Bay, jig, 57.8367°N, 152.4°W, 15 m depth. 12
August 1982; UW 44046, 1(302 mm), E of Kodiak I.,
58.5217°N, 151.3333°W, 154 m depth, 21 August 1982; UW
44047, 1(321.7 mm). E of Kodiak I., 58.85°N, 151.8167°W,
113 m depth, 21 August 1982; UW 44048, 1(318.3 mm).
Kodiak I., Monashka Bay, 57.8367°N, 152.4°W, 18 m
depth, 11 September 1982; UW 46486, 1(278.5 mm),
56.6941°N. 151.9115°W, 59 m depth, 27 June 2001; UW
47362, 3(122-219 mm), 56.3686°N, 154.0495°W, 69 m
depth, 24 June 2001. Southeast Alaska: UW 43495,
1(262 mm), Lynn Canal, N of Funter Bay. 58.03°N,
134.8967°W, 40 m depth, 13 July 1998; ABL 66-156,
1(269.4 mm), Barlow Cove, 19 mi NW of Juneau, 58.3197°N,
134.8967°W, 12 February 1967; ABL 68-301, 1(249.8 mm),
Lynn Canal, off reef at N end of Little I., ca. 9 mi N of Pt.
Retreat, 58.5417°N, 135.0433°W, 3 August 1968; ABL 69-
116. 2(77.7-136.3 mm), Chichagof I., Ogden Passage
between Khaz Bay and Portlock Harbor, 57.6333°N,
136.1617°W. 10 September 1969; ABL 69-122.
2(82-82.1 mm), Chichagof I., Icy Strait off SE end of
Pleasant I., 58.3333°N, 135.6333°W; ABL 70-103,
1(173.2 mm), Gastineau Channel, Marmion I., ca. 9 mi. S
of Juneau, 58.2°N, 134.2533°W, 10 July 1970; UW 43494,
11 (150.7-225.2 mm), Lynn Canal, Funter Bay, 58.2467°N,
134.8988°W, 37 m depth, 13 July 1998; UW 44117,
26( 153.8-272.7 mm), Funter Bay, 58.2467°N, 134.8983°N,
40 m depth, 13 July 1998; UW 44118, 5(151.9-190.0 mm),
348
Fishery Bulletin 102(2)
Funter Bay, 58.2467°N, 134.8983°W, 40 m in depth, 13
July 1998; UW 46526, 12(48.0-93.5 mm), Sitka Sound,
Middle I., 57.1°N, 135.45°W, 4 June 2001; UW 48866,
3(78.1-156.7 mm), Alexander Archipelago, Biorka Chan-
nel, S of Sitka, 33 m depth, 21 February 1982. British
Columbia: BCPM 974-0623-001, 5(342-367 mm), Hecate
Strait, Moresby Gully, RV G. B. Reed, 52.31°N, 130.4867°W,
185-199 m depth, 14 September 1974; BCPM 974-416,
1(154.7 mm), Dundas I., Brundige Inlet, reef at entrance
to E arm, 1-5 m depth; BCPM 974-419, 1(124.8 mm),
Dundas Is., Brundige Inlet, just N of island at entrance to
E arm, 54.6043°N, 130.8612°W, 6-15 m depth, 19 June
1974; BCPM 974-434, 2(108.3-113.8 mm), mouth of Brun-
dige Inlet E shore, 8-12 m depth; BCPM 974-447,
2( 168.9-175.6 mm), Welcome Harbour channel, 54.0225°N,
130.6133°W, 6-12 m depth, 2 July 1974; BCPM 974-467,
2(127.9-162.1 mm), off Parkin Islets (E side), 54.6261°N,
130.4639°W, 6-8 m depth, 12 July 1974; BCPM 974-468,
1(120 mm), offNtipofBirniels., 54.6045°N, 130.4508°W,
6-12 m depth, 13 July 1974; BCPM 974-485, 1( 129.9 mm).
off island in Griffith Harbor, 53.6011°N, 130.5486°W, 5-8
m depth, 20 July 1974; BCPM 974-489, 2(145.8-151.5 mm),
Safa Islets, 54.7733°N, 130.6067°W, 6-18 m depth, 28 July
1974. Oregon: UW 46575, 1(355 mm), 44.4°N, 124.783°W.
265 m depth, 17 May 2002.
Significant comparative material examined
Sebastes melanops USNM 342, syntypes. Cape Flattery,
Washington, and Astoria, Oregon; UW 47037, 1(350 mm),
Bering Sea, 55.2333°N, 164.65°W, 2 February 2002; UW
43490, 3(195-230 mm), Cross Sound, Chichagof I., Soap-
stone Cove, 58.1°N, 136. 5°W, 25 m depth, 11 July 1998;
UW 47288, 2(163-182 mm), Kodiak L, Monashka Bay,
5 m depth, 57.8383°N, 152.4283°W, 5 m depth, 2 August
1982.
Sebastes mystinus USNM 27031, syntype, 1(346 mm),
Monterey, California; USNM 27085, syntype, 1(269 mm).
Monterey, California: USNM 26971, syntype, 1(212 mm).
Monterey, California.
Sebastes polyspinis USNM 60243, 2(75.3-141.3 mm),
Alaska, Chignik Bay, 13.6 km S of Tuliumnit Point, 56°N,
RV Alabatross, Sta. 4285, 57-108 m depth, 10 August
1903.
349
Abstract— The dynamics of the sur-
vival of recruiting fish are analyzed as
evolving random processes of aggrega-
tion and mortality. The analyses draw
on recent advances in the physics of
complex networks and, in particular,
the scale-free degree distribution aris-
ing from growing random networks
with preferential attachment of links
to nodes. In this study simulations
were conducted in which recruiting
fish 1) were subjected to mortality by
using alternative mortality encounter
models and 2) aggregated according
to random encounters (two schools
randomly encountering one another
join into a single school ) or preferential
attachment (the probability of a suc-
cessful aggregation of two schools is
proportional to the school sizes). The
simulations started from either a "dis-
aggregated" (all schools comprised a
single fish) or an aggregated initial con-
dition. Results showed the transition of
the school-size distribution with pref-
erential attachment evolying toward
a scale-free school size distribution,
whereas random attachment evolved
toward an exponential distribution.
Preferential attachment strategies
performed better than random attach-
ment strategies in terms of recruit-
ment survival at time when mortal-
ity encounters were weighted toward
schools rather than to individual fish.
Mathematical models were developed
whose solutions (either analytic or
numerical) mimicked the simulation
results. The resulting models included
both Beverton-Holt and Ricker-like
recruitment, which predict recruitment
as a function of initial mean school size
as well as initial stock size. Results
suggest that school-size distributions
during recruitment may provide infor-
mation on recruitment processes. The
models also provide a template for
expanding both theoretical and empiri-
cal recruitment research.
Recruitment as an evolving random process
of aggregation and mortality
Joseph E. Powers
Southeast Fisheries Science Center
National Marine Fisheries Service, NOAA
75 Virginia Beach Drive
Miami, FL 33149
E-mail address: loseph powers@noaa.gov
Manuscript approved for publication
10 December 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:349-365 (2004).
The study of recruitment processes
has traditionally addressed mortal-
ity (predation and starvation) and
the effects of patchiness on mortality
(Vlymen, 1977; Beyer and Laurence,
1980; Hunter, 1984; Rothschild, 1986);
hence the importance of aggregation
and mortality in recruitment processes
of marine fish populations has long
been noted. Ecological processes of
starvation, growth, and predation of
larval fish, coupled with oceanographic
factors show the inherent variability in
these processes (Koslow, 1992; Mertz
and Myers, 1994, 1995; Pepin, 1991;
Rickman et al., 2000; Comyns et al.,
2003). In particular Rickman et al.
(2000) have indicated the importance
of the magnitude of fecundity in the
variability of egg and larval mortal-
ity. Indeed, Koslow ( 1992 ) argued that
fecundity and the associated variability
in egg and larval mortality will limit
our ability to determine stock-recruit-
ment relationships.
Stock-recruitment models have gen-
erally emphasized the static results
of recruitment processes rather than
the dynamics themselves. Indeed, al-
though the classic stock-recruitment
models such as the Beverton-Holt and
Ricker have been related to microscale
processes (Beverton and Holt, 1957;
Ricker, 1958; Paulik, 1973; Harris,
1975), the dynamics at those scales
were not explored, primarily because
there was not a theoretical basis for do-
ing so ( Rothschild, 1986 ). Nevertheless,
there is a need to develop a theoretical
understanding of small-scale inter-
action processes during recruitment,
particularly as they relate to group
formation.
Group-formation ( aggregation of fish
into schools), schooling (shoaling) be-
havior, and the evolutionary motivations
for formation of schools continue to be
important research topics (Pitcher and
Parrish, 1993; Landa, 1998). Schooling
behavior has variously been attributed
to predator-avoidance, predator-attack
dilution, and hydrodynamic and forag-
ing advantages (see Pitcher and Par-
rish, 1993, for a review). One of the first
models for school formation was that of
Anderson ( 19S1 ) in which he empirically
observed skewed distributions in which
small schools were more prevalent than
larger ones. Subsequently, Bonabeau
and Dagorn (1995), Gueron and Levin
(1995), Niwa (1998), and Bonabeau et
al. (1999), developed group-size distri-
bution models. In particular, Bonabeau
et al. (1999) in comparing group-size
distributions of tunas, sardinella, and
buffalo suggested that power-law dis-
tributions may be quite generic. Niwa
(1998) noted that Anderson's original
model allowed for power-law distribu-
tions. Power-laws are termed scale-free
because they exhibit no intrinsic scale.
Similarly, existence of a power-law is
often referred to as "scaling."
Recently, power-law distributions
have arisen in studies of the physics
of small-world and evolving networks
(for example the world wide web, ac-
tor collaborations, scientific citations
[Barabasi and Albert, 1999], biological
cellular networks [Fell and Wagner,
2000], and ecosystem structure [Sole
and Montoya, 2001]). In particular,
Barabasi and Albert (1999) demon-
strated that a randomly evolving net-
work would result in a scale-free degree
distribution if the network is growing
350
Fishery Bulletin 102(2)
(the number of nodes is increasing) and if the new nodes
were linked to existing nodes by preferential attachment.
Preferential attachment (or the "rich-get-richer" phenom-
enon) occurs when a new node is linked to an existing node
with a probability proportional to the number of links al-
ready attached to that node. More formally, the Barabasi
and Albert model is created by adding a new node at each
time step and by randomly linking it to m existing nodes
proportional to the number of links at the existing nodes.
After a large number of time steps, the probability of a node
having k links (the degree distribution) scales as a power-
law P(k)~k '-', where y = 3, independent of m. The Barabasi
and Albert result differs from the classic random network
model of Erdos and Renyi ( 1960 ) in which nodes are linked
randomly to existing nodes, leading to P(k)~exp(-Xk ). Sub-
sequent research has expanded on the Barabasi and Albert
model to examine aging, removal and rewiring of nodes,
removal of links, fitness and attractiveness of nodes, and
local modifications to preferential attachment (see Albert
and Barabasi, 2002, for a review of these developments)
The generic occurrence of scale-free school-size distribu-
tions suggest that modeling of aggregation and mortality
processes using the analogy of random networks may be
fruitful. The approach may provide insight into recruit-
ment dynamics and a theoretical basis for further inves-
tigation. This study attempts to do that and is organized
in the following manner. First, a simulation model of the
recruitment process is developed in which aggregation and
mortality occur based upon some simple rules of prefer-
ential attachment and random attachment. Attachment
rules are presented as metaphors for more complex behav-
iors. Next, analytical models are created that mimic the
simulations, and results of the simulations and analytical
models are compared. Finally, the implications for existing
stock-recruitment models and investigation of recruitment
processes are discussed.
ity is the removal of nodes (fish) and, if there are no more
fish in the school, then the removal of schools. A simulation
model with simple rules of mortality and aggregation was
created to examine the dynamics of these processes.
The simulation model followed individual fish and
schools through a recruitment period, i.e., the passage
of time until an arbitrary time of recruitment. During a
recruitment period fish and schools undergo encounters
of mortality and aggregation. Starting at time r=0 with S
fish, iV,_0 schools and kt t=0 fish in school i U=l,2, . . . , N0),
simulations were conducted by randomly generating an
encounter event (mortality or aggregation!. If the event
was a mortality, then a school was randomly selected by
using the appropriate mortality rate model (;?*. discussed
below). If the size of that school was greater than one,
then that size was reduced by one. If the school size was
equal to one, then the number of schools was reduced by
one and this school was eliminated from the list.
If the event was an aggregation, then two distinct
schools were randomly selected by using the appropriate
aggregation rate model (w, also discussed below). The two
schools were combined, leaving one school whose size was
the sum of the two original ones and one fewer total num-
ber of schools. The probability of an event being a mortality
was ml(m+w) and the converse probability of an aggrega-
tion was l-m/(m+w). Time increments of each event were
computed using At=m~l for mortality events and (mw)~l
for aggregation events. Results at time t were collated into
the number offish surviving to time / (denoted by R, >, the
number of schools, Nr the school size distribution, Pt(k),
and the average school size, k r Note thati?, =Ntkr Simula-
tions were run until there were no fish left.
Encounter rates The encounter rates, m and w, were
based upon random movements in statistical mechanics
(Tolman, 1979) in which the encounter rate (£/) of objects
of type i with objects of type 7 is described by
Methods
U=(G, + GO Dp, {v? + v/)"3,
(1)
Simulation of individuals in ecology and population
dynamics (individual-based models) have become increas-
ingly popular (McCauley et al., 1993). However, it is often
difficult to understand the dynamics of large individu-
ally based models (Pascual and Levin, 1999). Thus, it is
important to obtain models that describe dynamics of
groups that incorporate individual behavior (Flierl et
al., 1999). The models that are developed here include an
individually based model (simulation model) and an ana-
lytical model that describes "mean-field" dynamics of the
individuals behavior.
Simulation model
The recruiting fish of a year class may be modeled as a
network offish in which a fish "links" to other fish to form
schools. (Note that in this context it is assumed that a
"school" includes aggregations consisting of a single fish).
Thus, the process of aggregation is a process of adding
links to nodes (aggregation of schools). Similarly, mortal-
where G, = the size of the detection space at which object
detects object type./';
Z), = the density of objects of type i; and
u, = the velocity (in three-dimensional space) at
which object i moves in the environment.
For these simulations the G parameters were scaled to
one and the velocity parameters (v's) were collapsed into
two encounter rates: ,11 for mortality encounters (scaled to
unity) and a for aggregation encounters.
Mortality rate In the simulations, mortality of fish is
perpetrated by mortality agents. If the mortality agents
randomly encounter schools of fish, then the probability
of a successful mortality (the removal of a fish from the
system) is proportional to the school size k. Under these
conditions Equation 1 reduces to Equation 2 with
G=G,
■UV? +V3. )<={!■■
(2)
m = 2^ENk,
Powers: Recruitment as an evolving random process of aggregation and mortality
351
where E = the density of mortality agents; and
k = the encounter rate of fish with mortality
agents.
Note that on average Equation 2 reduces to m = 2iiElNlkl=
2iiEt Rt = -dRIdt. Hence, if the density of mortality agents
is constant throughout the recruitment period, then mor-
tality is density independent and mortality is proportional
to abundance. An alternative interpretation of Equation 2
is that the mortality agents randomly encounter fish and
that all encounters result in a successful mortality. The
mortality model (Eq. 2) will be referred to as mdl (for den-
sity-independent). It is not expected that mdi is the most
realistic, but rather it provides a basis for comparison.
A second mortality alternative is where mortality agents
randomly encounter schools, whereupon they always per-
petrate a successful mortality: mN = 2iiEtNt. This model,
like mdi, assumes that the density of mortality agents are
constant throughout the recruitment period.
For purposes of simulation, the density of mortality
agents at the onset of the recruitment process was speci-
fied to be unity (£0=1). For the two mortality models, mdi
and mN, this meant that £=1 throughout a simulation.
More realistic density-dependent mortality models are
immediately suggested. The first is a density-dependent
model in which the ratio of mortality-agent density to the
number of schools remains constant throughout the re-
cruitment period, i.e., EtINt remains constant throughout
the recruitment period. This leads to mdN = 2f.iNzk, where
EtINt was set equal to one. In this model the ratio of mor-
tality agents to schools is constant, agents and schools
randomly encounter one another, and the probability of a
successful mortality (given there is an encounter) is pro-
portional to the number offish that are in the school that
is encountered (mortality success is related preferentially
toward larger schools).
A second density-dependent model is where the mortal-
ity agent density is proportional to the number offish (Etl
Rt is a constant set equal to one, mdR=2iiR2=2iiN2k2). In
this model the ratio of mortality agents to the number
of fish in the population is constant; agents and schools
randomly encounter one another; and the probability of a
successful mortality (given there is an encounter) is pro-
portional to the number offish that are in the school that
is encountered (mortality success related preferentially
toward larger schools). Another interpretation of this
model is that agents randomly encounter fish, at which
time the fish suffers mortality at a probability independent
of school-size characteristics.
A third density-dependent model depicts mortality-
agent density proportional to school size (Etlkt is a con-
stant set equal to one, mdk=2\.i Nk'1). In this model the
ratio of mortality agents to mean school size is constant,
agents and schools randomly encounter one another, and
the probability of a successful mortality (given that there
is an encounter) is proportional to the number offish that
are in the school that is encountered. Another interpreta-
tion of this model is that agent density is proportional to
the number of schools, agents encounter schools prefer-
entially according to school size, and the probability of a
successful mortality (given that there is an encounter) is
proportional to the number of fish that are in the school
that is encountered.
Subsequently it will be shown that the first density-
dependent model is related to a Ricker-like stock-recruit-
ment model and the second model is exactly equivalent
to a Beverton-Holt model. Definitions of the mortality
models are summarized in Table 1. Note that in the ini-
tial applications of these mortality models, it is assumed
that a mortality encounter results in mortality of one
fish. More detailed mortality models in which a number
of fish greater than one are removed by mortality may be
implemented in the future. Clearly, these would be more
biologically realistic in many instances. However, the
emphasis of this study is on the possible scaling behavior
of school-size distributions. Barabasi and Albert (1999)
showed that the scaling behavior of a growing random
network is independent of the number of randomly se-
lected links at each time step. With this analogy, simple
increases in mortality per encounter are not expected to
alter the scaling behavior of the school-size distributions.
Therefore, the one-fish-per-mortality-encounter approach
was used in these initial simulations.
Aggregation rate
Similar to mortality-rate encounters, aggregations were
investigated as 1) random attachment of two unique
schools (wN=2aNiN-D) and 2) preferential attachment of
two unique schools i and./' (w =2aN(N-\)klkJ; [Table 1]).
Note, the trivial alternative where there was no attach-
ment, (a=0), results in equivalence between the mortal-
ity models mdN, and mdR\ whereas mdl becomes a simple
proportional mortality rate. Thus, results of models with
o=0 are uninteresting in the context of this study and are
not presented.
Initial conditions Each simulation was conducted with
one of two alternative initial conditions. The first alterna-
tive was one of complete disaggregation in which simula-
tions were initiated with S fish, S schools, and one fish in
each school (NQ=S, kQ=l). The second alternative initial
condition was constructed from the population dynamics
of a typical fish population. The main assertion of this
alternative is that the eggs or larval fish produced by
one female during spawning constitutes one school at the
onset of the recruitment process. Thus, the fecundity per
female at age is a measure of initial school size and the
abundance of females at age is a measure of the frequency
of schools of that size. More precisely, the initial condition
was constructed for a population of females greater than
five years of age (age of maturity), where their fecundity
at age, F ' is proportional to weight at age determined
from a von Bertalanffy growth equation with parameters
K=0.2 and L^ = 10, and an allometric parameter of 3:
(F =1000 [(l-exp(-age( 0.2)))] 3). Abundance at age, Aage,
was computed with an instantaneous mortality rate of 0.2:
[A =Zexp(-0.2(age-5))]. The scalarXwas obtained from
the approximate solution to S =2Fage Aage, where F and A
were integer values and S was the initial number of fish
352
Fishery Bulletin 102(2)
Table 1
Summary of definitons of the mortality models used in this study.
Model
Definition
Mortality rates':
mdi = 2ftNk
m ix = 2fiN2k
mdR = 2fiN2kk
mdk=2ijNkk
mN = 2iiN
density-independent
density-dependent, mortality agents proportional to A''
density-dependent, mortality agents proportional to R
density-dependent, mortality agents proportional to k
random encounters with schools
Aggregation rates:
wN = 2ctN(N-l)
random encounters with schools
wpa = 2aN(N-l)klkJ
preferential attachment of schools i andj
Initial conditions:
Disaggregated
Aggregated
N0 = S,k0=l
(see text and Table 2)
Mean field equivalents usee
in analytical model (see
text):
mdi = 2fiNk m(/v =
2^iNk2
mJR = 2fiN2k2
mM = 2iiNk2 wpa =
2NiN-l)k2
Key to figures of simulation
results
Figure 1: disaggregated
md, Wpa
a = 10-6
S = 106
Figure 2: disaggregated
mJ, WN
« = io-6
S=106
Figure 3: aggregated
"hi, ™pa
a = IO"6
S = 108
Figure 4: aggregated
"IJN Wpa
a =1.5xl0-6
S = 2 x 106
Figure 5: aggregated
mdN wN
«= 1.5xl0-6
S = 2 x 106
1 In all simulations, ft was set equal to 1.
Table 2
The aggreg
ated in
itial school-size
distribution
, when S =
1,000,000
. Per capita female fecundity at
age is a measure of school size,
num
ber of female;
at
age is a measure
of freq
jency of sc
hools. See
text for details
of computation.
School size
Freq
. of schools
Freq. x size
School size
Freq
of schools
Freq. x size
252
348
87,696
857
47
40.279
341
284
96,844
882
38
33.516
427
233
99,491
903
31
27,993
508
190
96,520
920
25
23.000
581
156
90,636
934
21
19,614
596
1
596
946
17
16,082
646
128
82,688
955
14
1.3,370
703
104
73,112
963
11
10,593
751
85
63,835
970
9
8730
793
70
55,510
975
7
6825
828
57
47,196
979
6
5874
Sum
of freq.
x size =
S =
= 1,000.000.
of a simulation. Then one school of an appropriate magni-
tude, M, was added such that the M +^Fll/,vA„.,,, was exactly
equal to S. Note that under this construction the school
sizes in the distribution do not vary with S (except for the
one school of size M), whereas the frequency of schools by
size do. An example of the initial distribution with the use
of this construction is given in Table 2.
Analytical models
Analytical models of aggregation and recruitment are
presented, where the models are developed from first prin-
ciples and the parameters have an interpretation in the
physics and biology of the recruitment process. Hopefully,
the nature of the parameters can guide model selection,
Powers: Recruitment as an evolving random process of aggregation and mortality
353
and the estimates may provide a theoretical framework for
empirical research on recruitment processes.
Noting that R,=Ntkt, the recruitment dynamics depicted
in the simulations may be modeled by using Equations
3-6 in which recruitment is dependent on the particular
mortality and aggregation models that are chosen (m and
w; Table 1):
dR,l = -m = d(N,k, "/dt=(dkl Idf'N, +(dN, I dt"k, (3)
dNJdt
-2aNt{Nt-l)\l
dN, I dt = -w - mxPu
dk,/dt = mft, [( k, - 1)1 ( N, - 1)
-< m - m^Pv )l N,+ wkt /<JV,_i )
(4)
(5)
dPkl Idt = ( mk+lPk+u - mkPKt )INt- wkP,!t I N, k > 1
i-l
+ wYJP,Pk-,INl (6)
= m2PuINt - miPua-Pu >/< AT, -1) k = l
-w1PuINl ,
where Ph , = the proportion of schools with k fish in them
at time t .
Also, mk and wk denote encounter rates appropriate to
schools of size k, whereas unsubscripted m and w denote
mean field dynamics and, thus, the kt t's are replaced by
kt's (see Table 1).
The first term in Equation 4 denotes the reduction in
number of schools due to aggregation events; the second
term denotes a reduction due to mortality events on
schools with one fish in them. Similarly, the first term in
the mean school-size equation ( Eq. 5 ) describes the change
in mean school size due to mortality events on schools
of size equal to one; the second term is due to mortality
events on schools of size greater than one; and the third
term is due to aggregation events. Finally, the first term
in Equation 6 describes the change in probability of school
size k due to mortality; the second term describes loss due
to aggregation; and the third describes gain due to aggre-
gation. Of particular importance is Pl t: when Px , is zero,
the loss of schools occurs only due to aggregation. When
Pj , is positive, then loss of schools is accelerated due to
mortality (Eq. 4).
The goal is to obtain solutions to Equations 3-6 as
functions of a, ju, and the initial conditions. If one can be
assured that there will not be a school composed of one
fish during a particular recruitment period (Pj ,=0), then
Equation 6 is eliminated, the Pj ( terms drop out of Equa-
tions 4 and 5, and a numerical or analytical solution to
the differential equations can be obtained, which is com-
putationally feasible for use in fitting to stock-recruitment
data. For example, when there is preferential aggregation
(w ) and mortality agents are proportional to schools
(mdN), the equations reduce to
dktldt--
ldN
I N, + w k,( Nj_-1)= -2/jNtk, + 2aNtkt3
Analytical solutions were obtained for some of the mor-
tality and aggregation models when P1(=0 throughout
the recruitment process (Appendix 1). In particular for
m„
!Randwpa-
Rt = SHl+2iitS) (7)
Nt=NQ+(a/n"[S-S/e%* %itS"] (8)
^=^/[l+2^S + 2ctfS^].
(9)
which is the Beverton-Holt stock-recruitment model
expanded to include equations for the number of schools
and the mean school size. Interestingly, Equation 9 indi-
cates that monitoring the school-size distribution two or
more times during a recruitment procession would yield
estimates of the stock-recruitment parameters without
having direct measures of the number of surviving fish.
Equation 7 predicts recruitment by using one parameter.
j.1. , the rate of mortality encounters during the recruitment
period. However, spawning stock biomass is often used as a
surrogate for the number of initial stock, S. Thus, another
parameter is needed to convert spawning stock biomass
to S in Equation 7. In that case the recruitment model
becomes Rt = aS/(l+2utaS), where a is another parameter
related to fecundity. The additional parameter will be
needed for all the models discussed here, if spawning stock
biomass is the measure of initial stock.
The assumption that Plt=0 for all t of a recruitment
period may not be justified in all situations. An approxi-
mation was developed (Appendix 2) to be applied when
the initial conditions are disaggregated and when there
is preferential attachment. In this circumstance, the dif-
ferential equation (Eq. 6) when k = l is replaced by
dPu/dt = -wPu/N, + m ( 1 - Pu)INt.
(10)
Results
Simulations
Several hundred simulations were conducted under vari-
ous initial stock sizes (S), aggregation parameters (o), ini-
tial aggregation conditions, and mortality and aggregation
models (m and w). An example set of results are presented
in Figures 1-5 (a key to figures is in Table 1).
A typical example of the evolution of the school-size
distribution is given in Figure 1 for the disaggregated
initial condition, a=10"6, S=106, mortality model mdi and
aggregation model w . In this example both the mortality
and aggregation models exhibit preferential attachment,
and the school-size distribution approaches scale-free be-
havior P(k)~k->, although y evolves over time. Eventually,
a so-called "giant cluster" is formed by the aggregation
process, in which all the fish attach to one school. This has
354
Fishery Bulletin 102(2)
1 ,000.000
o f = 0.1 1
+ f=0.40
» f=0.95
A O
V
\
sw
luminal iih i
School size
-r 1,000,000
-- 5,000,00
(
Figure 1
Simulated dynamics of school-size distributions with mdl as the mortality model
and w as the aggregation model. This simulation started with disaggregated
initial conditions (JVn = Sl, where S=106. The aggregation parameter was oc=10-6.
The top panel shows school-size distributions (in log-log scale) at selected times
(/). The lower panel gives the mean school size (kbar) and school abundance (AM
versus time.
been shown to be an analog of Bose-Einstein condensation
(Bianconi and Barabasi, 2001; Dorogovtsev and Mendes,
2002) and gelation (Krapivsky et al., 2000). Greater mix-
ing rates Cot's) and larger densities (N's) accelerate the
aggregation process and the formation of the giant cluster.
The average size, k, increases over time from the disag-
gregated initial condition until a giant cluster is formed.
The number of schools declines over time because of both
aggregation and the mortality of fish in schools that only
have one fish in them.
When there is random aggregation beginning from a
disaggregated initial condition (a=10-6, S=10K, mdi, wN ;
Fig. 2), the school-size distribution exhibits exponential
behavior P(k)~exp(-/Jt), with A evolving over time. This
is equivalent to the Erdos and Renyi (1960) results for
random graphs. A comparison of Figure 2 with Figure 1
shows the difference between preferential attachment and
random attachment, i.e., the difference between scale-free
and exponential models.
Aggregated initial conditions (Figs. 3-5) result in a
transition from the initial distribution to either scale-
free or exponential distribution. During the transition,
the size of the smallest school gradually becomes smaller
until there is a finite probability of schools with one fish in
Powers: Recruitment as an evolving random process of aggregation and mortality
355
1.000.000 -
o
+
A
+
+•
o ( = 0.03
+ (=0.33
a (=0.62
>.
o
c
B- 1,000 -
1 -
A
O
+
A
O
+
A
O
+
A
-t-
A
+
A
+
A
* — I 1
School size
J3
-r 1.000,000
Figure 2
Simulated dynamics of school-size distributions with mdl as the mortality
model and wN as the aggregation model. This simulation started with disag-
gregated initial conditions (N0 = S), where S=106. The aggregation parameter
was a=10~6. The top panel shows school-size distributions (frequency in log) at
selected times ((). The lower panel gives the mean school size (kbar) and school
abundance (JV) versus time.
them. At this point the reduction in the number of schools
is accelerated because of the mortality of fish that are in
"schools" in which they are the only member, and because
of the loss of schools attributed to aggregation.
Model comparisons
Numerical integration of Equations 3-5 matched the sim-
ulation results (Fig. 6, when P1(=0), indicating that the
mathematical model describes the simulation dynamics.
The numerical techniques are sufficiently efficient to be
used in a curve-fitting context. Evaluations of the approxi-
mation (Appendix 2) indicate that the approximation may
be useful for predictions of recruitment, when compared
with the simulations. However, the components of recruit-
ment, kt and Nr were biased (Fig. 7). Further research is
needed to develop estimates of P1 1 and, more generally,
P(k) under other models and initial conditions.
Recruitment was compared between mortality models
and aggregation models (Fig. 8). If the mortality model
was either mdl or mdR, then the mortality rate was not af-
fected by the school-size distribution: random attachment
and preferential attachment perform equally as well in
terms of survival at a given time. But if mortality encoun-
ters proportional to school density (.mdN) were imposed,
then there were better survival rates with preferential at-
tachment than with random attachment (Fig. 8, A and B).
Conversely, mortality encounters proportional to school
356
Fishery Bulletin 102(2)
o f=0
+ f = 0.35
A f= 1.50
1.000
School size
T 2.000
Figure 3
Simulated dynamics of school-size distributions using mdl as the mortal-
ity model and w as the aggregation model. This simulation started with
aggregated initial conditions (S = 106). The aggregation parameter was
a=10~6. The top panel shows school-size distributions lin log-log scale) at
selected times (t). The lower panel gives the mean school size Uibar) and
school abundance IN) versus time.
size (mdk) led to poorer survival with preferential attach-
ment (Fig. 8, C and D).
Discussion
Koslow (1992), Rickman et al. (2000), and others have
commented on the inherent variability in stock-recruit-
ment data and the limited predictive power of determin-
istic stock-recruitment models. Therefore, there is no
expectation that one could select the models described
here over other stock-recruitment models on the basis of
fits to data. Although the aggregation-mortality models
may be fitted to stock-recruitment data, the real useful-
ness is as a guide to selection of stock-recruitment models
used in management, as a mechanism for integrating
research on recruitment processes, and as a tool for explor-
ing the structure of recruitment variability.
The aggregation-mortality models were introduced
by using an analogy with evolving random networks
( Barabasi and Albert, 1999 ) and were shown to be analyti-
cally equivalent (Appendix 2). Modeled fish are subjected
to competing forces of organization (aggregation) and decay
(mortality), as in a network in which links to nodes in the
network are created, destroyed, and rewired (Albert and
Barabasi. 2002). An important finding of Barabasi and
Powers: Recruitment as an evolving random process of aggregation and mortality
357
o f= 0
+ t=5t
a f= 2f
School size
0002
[
Figure 4
Simulated dynamics of school-size distributions using mJX as the mortal-
ity model and w as the aggregation model. This simulation started with
aggregated initial conditions (S=2xl06). The aggregation parameter was
o=1.5x 10"6. The top panel shows school-size distributions (in log-log scale)
at selected times (t). The lower panel gives the mean school size (kbar) and
school abundance (N) versus time.
Albert (1999) was that scaling of the aggregate-size dis-
tribution was dependent on the type of aggregation, spe-
cifically preferential attachment. Bonabeau and Dagorn
noted the generic occurrence of scaling of aggregation
distributions in nature (Bonabeau and Dagorn, 1995) and
this scaling of aggregation distributions motivated the
development of the models presented here.
The emphasis of the aggregation models was on prefer-
ential attachment and on comparison of model results with
results for models with random attachment strategies. The
preferential attachment rule used in the simulations was
that aggregation rates were proportional to the size of the
school encountered. But, what is meant by preferential
attachment and does preferential attachment occur in
nature? Clearly, a fish, school or mortality agent has no
global knowledge of the proportional size of a school that
is encountered. However, preferential attachment in these
models is a metaphor for aggregation strategies that are
weighted toward larger school sizes. Indeed, studies of
networks have shown that attachment may be proportional
to a power of school size and still produce scale-free prop-
erties (Albert and Barabasi, 2002). Also, network studies
have shown that scale-free distributions occur when a
wide number of attachment criteria are included, such
as the "fitness" of the object being encountered and the
attractiveness of local conditions (Bianconi and Barabasi,
358
Fishery Bulletin 102(2)
1,000 i
0
0
O
O
0
o
o (=0
+ f=5f -6
a f= 1f -6
o
o
o
o
>,
0
<D
o
cr
o
CD
*
o
D
3^j*
o
cr
TMi1
o
CD
o
3
'^MhK*
o
LL
A + AK + ++ HtH-
o
o
0
A + A + +
A *
+ OL + -H-
« A Htt-
e .
400
Icsooz size
1,000 -|
Figure 5
Simulated dynamics of school-size distributions using mdN as the mortal-
ity model and wN as the aggregation model. This simulation started with
aggregated initial conditions (S=2xl06). The aggregation parameter was
ot=1.5x 10~6. The top panel shows school-size distributions (in log-log scalei
at selected times it). The lower panel gives the mean school size ikbar) and
school abundance (N ) versus time.
2001; Calderelli et al„ 2002; Vazquez, 2003). Biological
concepts of fitness, feeding behavior, predator-avoidance
behavior, and habitat suitability appear to fall within
the attachment criteria examined in physics literature.
Oceanographic stability (Myers and Pepin, 1994), assorta-
tive schooling by color patterns (Crook, 1999), chemosen-
sory stimuli (Quinn and Busack, 1985), and larval fitness
indices from RNA/DNA ratios (Pepin, 1991; Suneetha et
al., 1999) may be mechanisms that directly or indirectly
influence aggregation size and, thus, distribution.
The geometry of the school size itself may be sufficient to
produce preferential attachment behavior, as well. In the
models of this study, the detection spaces (G, +Gf in Equa-
tion 1) were set to unity and assumed to be independent of
school size. However, the detection space may be related
to school size. For example, if a school of one fish has a
spheroid detection space around itself with radius equal
to 1, then using the geometry of an aggregation of /<■ fish,
the detection space of the aggregate would be proportional
to kv:\ Alternatively, if the detection space were a two-di-
mensional circle with a radius of 1, then the aggregate's
detection space would be proportional to &"'-'. Substituting
size-dependent detection spaces into the random mortality
and aggregation models would be sufficient to induce pref-
Powers: Recruitment as an evolving random process of aggregation and mortality
359
B
1.000,000 2,000.000
3,000.000 -[
2,000.000 0
Stock size (no. of fish)
1,000,000
■ Mathematical model • Simulation model
Figure 6
Stock-recruitment relationships from the mathematical models (Eqs. 3-5, aggre-
gated initial conditions! compared with simulation results: I Ai density-independent
mortality (mc/l I and preferential attachment (u'l evaluated at 4=1, r<=10". ii = l; (B)
density-dependent mortality proportional to fish imdR I and preferential attachment
(w ) evaluated at t=10~5, a=3 x 10 5, ,n = l; ( C ) density-dependent mortality propor-
tional to schools (rndN) and preferential attachment iw ) evaluated at t=5x 10~4,
a=1.5x 10~6, f(=l; and (D) density-dependent mortality proportional to school size
(mdk) and preferential attachment (w ) evaluated at ^=10-3, a=2x 10_li, ,11 = 1.
erential interaction even when encounters are random:
schools are randomly encountered, but the encounter event
itself is weighted toward larger schools. Thus, the shape of
the detection space may be another mechanism by which
preferential attachment may be exhibited.
In the models presented, it is blithely assumed that
mortality is caused by undefined mortality agents. How-
ever, most larval recruitment research has been directed
at starvation and predation as determinants of recruit-
ment variability (Lasker, 1975; Hunter, 1984; Bailey and
Houde, 1989; Chambers and Trippel, 1997, for example).
The mortality models used here clearly fit within the pre-
dation paradigm: mortality from predation results from
encounters with mortality agents of specific density and
size. Whereas, mortality from starvation ensues from a
lack of encounters with prey agents of sufficient density
and size. In certain situations starvation processes might
be aptly described by the predation-encounter approach
used in this study. However, further research is needed
to evaluate their appropriateness and to develop alterna-
tive modifications to Equations 3-6. A mechanism to do
this may be the inclusion of fragmentation of schools into
the models. In the models as they are now characterized,
new schools are not created, the number of schools only
becomes smaller through either aggregation or through
mortality on schools of a single fish. Fragmentation might
360
Fishery Bulletin 102(2)
1 ,000,000 2,000,000
2.000,000 0
Stock size (no. offish)
Mathematical model • Simulation model
Figure 7
Stock-recruitment relationships determined from the mathematical models (Eqs.
4, 5, and 10, disaggregated initial conditions) compared with simulation models.
(A and Bl Recruitment at r=l with mortality encounters proportional to school size
(mdk) at a=5xl0~" and ,n = l; A is recruitment and B is the mean school size. iC and
D) Recruitment at t=10~5 with mortality encounters proportional to school density
im/vi at o=0.2 and ii=l; C is recruitment and D is mean school size.
occur due to secondary effects of mortality encounters,
as well as other factors such as starvation. For example,
Sogard and Olla (1997) have shown predation-risk and
hunger to be related to group cohesion.
The formation of a giant cluster (a single school en-
compassing all the fish) is an important feature of the
attachment process. The simulations showed that with
preferential attachment the recruitment process passes
through a phase where the size distribution is scale free,
then a critical point is reached where a giant cluster is
being formed, i.e. a single school begins to attract all the
fish. Research on complex networks has shown the condi-
tions for formation of the giant cluster (Aiello et al., 2000;
Albert and Barabasi, 2002). This should be investigated
for the school aggregation models because it is likely that
the mortality models used in the present study would no
longer be appropriate once the giant cluster is formed. In-
deed in some fish stocks, schools may aggregate into giant
clusters on a local scale and then aggregation may stop for
reasons such as juveniles entering a benthic phase. The
resulting distribution of school sizes may be the cluster
distribution across benthic habitats. Spatial limitations
of aggregation are an important feature of individually
based models (Pascual and Levin, 1999). Again, this may
be an important area for research.
What is the benefit of preferential attachment? If mor-
tality encounters are proportional to school density, then
recruitment survival rates are improved when there are
fewer schools for a given number of fish, i.e. when prefer-
ential attachment is employed rather than random attach-
ment (Fig. 8). Perhaps, preferential attachment strategies
are a useful evolutionary hedge against uncertainty in
the nature of the mortality dynamics. Conversely, when
mortality encounters are proportional to school size, then
better survival is achieved when schools are smaller, i.e.
with random attachment (Fig. 8). If mortality by preda-
tors is related to larger schools, or if attainment of prey is
inversely related to larger schools, then more solitary life
Powers: Recruitment as an evolving random process of aggregation and mortality
361
A Mortality encounters proportional to school
r
density; aggregated initial conditons
Mortality encounters proportional to school
80.000 ■
-D density, disaggregated initial conditons
1
0 , 1
C Mortality encounters proportional to school
size; aggregated initial conditons
o if
0
D Mortality encounters proportional to school
size; disaggregated initial conditons
2,000.000
Stock size (no. of fish)
Random attachment
Preferential attachment
Figure 8
Stock-recruitment results with preferential attachment comparer] with random attach-
ment (w versus wN). (A) Recruitment at r=l with mortality encounters proportional to
school density imdN) at a=l(H' and ,«=5xl0 4 with an aggregated initial condition; (Bl
recruitment at r=10~5 with mortality encounters proportional to school density lmdN) at
a=0.2 and ji=1 with a disaggregated initial condition; (C) recruitment at t=l with mortal-
ity encounters proportional to school size (.mdk) at a=10~9 and jt<=5xl0~41 with an aggre-
gated initial condition; (Dl recruitment at t=l with mortality encounters proportional to
school size l»!iM.) at a=5x 10~7 and ti=l with a disaggregated initial condition.
history strategies may evolve. Perhaps, the random ag-
gregation model would be most effective for solitary preda-
tory fish when their mortality is imposed by a mdk-type
model. For fish, this may be more likely to occur at later
life stages than at recruitment. If mortality encounters
are proportional to fish (mrlR), then results are intermedi-
ate and preferential attachment and random attachment
perform equally as well.
The density-dependent mortality models implicitly in-
corporate a predator-prey interaction. Alternative preda-
tor-prey interactions examined were those in which preda-
tor density was proportional to fish, to schools, or to the
number offish within a school (school size) throughout a
recruitment period. In reality mortality is perpetrated by
a variety of agents at many different scales. Some agents
act at the scale of the population (Nk ), some at the scale of
schools (N ), some at the scale of mean school size (k ), and
some at the scale of a local school (£■). The mixture of preda-
tory agents and their densities can cause various kinds of
dynamics including oscillatory, chaotic, and stable behav-
ior (Wilson 1996, Pascual and Levin 1999). Therefore, it is
unlikely that the models in this study, in which predator-
prey ratios are constant, would be predictive of anything
other than average behavior during recruitment. However,
the analytical approach allows changes in the scale of
predator-prey interaction over time. We can model this as
ml=2uNtaktb, where a and b are dynamic (time-dependent)
and, perhaps, correlated. Although we may wish to use
the Beverton-Holt model (a=b=2) or the Ricker-like model
(a=2, b=l) as a representation of average dynamics, it
remains that recruitment variability will be influenced by
the dynamics of the exponents, a and b. Numerical evalua-
362
Fishery Bulletin 102(2)
tion of the differential equations by using random variates
at each time step may be a mechanism to evaluate how
the variability of a and b within a recruitment period are
translated into the variability structure around a stock-
recruitment relationship.
The model formulations used in the present study have
been characterized from the underlying physical pro-
cesses. By doing so, research may be directed at empirical
and experimental measurement of specific stock-recruit-
ment parameters, which opens the models to testing
and verification. Additionally, results indicate that the
school-size distribution contains a rich source of informa-
tion on the mortality and aggregation processes and that
monitoring of the distribution during recruitment could
be useful for understanding recruitment variability and
model structure.
Acknowledgments
I would like to thank the reviewers for their constructive
comments and the National Marine Fisheries Service for
allowing me the opportunity to conduct this research.
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Mortality proportional to fish: mdR
Preferential aggregation: w
Rt
l + 2,uSt
Nt=£ + ^S
kt=R,/N,
ko fi{ 1 + 2[iSt
l + 2/iSr + 2osSV
Mortality proportional to fish: mdR
Random aggregation: wN
"* l + 2/iS<
s
1 ' S-lS-Ve"2*
k,
= Rt/Nt = S-aS-^-2°'
Density-independent: mdl
Preferential aggregation: wpa
R, = Se-2'"
Art= J. _.£_£(!_ e-4/«
^ 2/1
k,=R,/N,--
v-2"'
1_S*o «q_c-4/i/)
2 n
Density-independent: mdi
Random aggregation: wN
Nt =
R, = Se"2'*
S
kt=Rt/Nt = e~2f" (S-iS-^e-'2*)
Appendix 1
Analytical solutions to Equations 3-5 for selected mortal-
ity and aggregation models. Solutions assume that Plt = 0
for all t evaluated and that the number of schools is large.
No analytical solutions were found for (mdN,wpa), (mdN,
Wpa>'OT(mo
•wpa>-
Mortality proportional to schools: mdN
Random aggregation: wN
Rt =Se
-2(1/ J feo_
|s-(S- v?
-2a*
364
Fishery Bulletin 102(2)
N,
S-(S-k0)e'
k, =RtINt =
k^e**
[S-(S-kf))e-2,"\'
Mortality proportional to school size: mdk
Random aggregation: wN
and Albert (1999). Dorogovtsev and Mendes (2000) and
Albert and Barabasi (2002).
When the aggregation model is preferential attachment
(w ) (ignoring for the moment the nonstationarity of N
and P), then the partial differential of a school of size klt
with respect to Rt has been shown by Dorogovtsev and
Mendes (2000) to asymptotically be
dkuim, = P,ik,,IR,),
(AD
where ft, is the net rate of decay per each mortality event,
i.e.,
R,
l + 2pSi-^(S-Ml-e~2°*]
a
fit
l-wpalm.
With specific-mortality models, fi, is
(A2)
Nt =
k,=R,/N,=-
S-iS-k0)e'
S-iS-kpte
-2at
l + 2^t-^S-k0)[l-e~
a
Random mortality encounters: mN
Random aggregation: wN
V i„ \ S <J
Rl=S-£-]n\Z-(e""-l) + l\
a [ko
mdl: p, = l-ial ii)iN, -Dk, = l-ial /j)R,
mdN: p, = l-(a/ n)(Nt-ljktl Nt = l-ial n)k,
mdR: p, = l-ial f.t)iN, -DIN, =l-(a//i)
mdk: P, = l-(a/fi)(Nt -l) = l-(a/p)P, Ik,,
where the approximations on the right assume that the
number of schools is large. The first term of (A2) denotes
the removal of a fish proportional to school size for a mor-
tality event; the second term denotes aggregation events
proportional to school size. If ft, is independent of time
ift,=ft), then Dorogovtsev and Mendes (2000) showed that
under continuum conditions
Pi k )
7 = 1 + 1/ /J.
(A3)
W,=-
2ftf
S-{S-ko)e
k,=R,IN,
Appendix 2
Characteristics of school-size distribution under
preferential attachment
Much of the recent literature on evolving complex net-
works has been directed at determining the degree distri-
bution, i.e., the probability P(k) of a node having k links
(Albert and Barabasi, 2002). When the network grows
or declines proportional to k or when links are rewired
to be proportional to k, then P(k> can be determined by
using continuum theory (Dorogovtsev and Mendes, 2000;
Albert and Barabasi, 2002) leading to scale-free degree
distributions. Therefore, when preferential attachment
and nonrandom mortality are used, then the model may be
couched as a scale-free network in the manner of Barabasi
Equation A3 is equivalent to the results of Dorogovtsev
and Mendes (2000), Krapivsky et al. (2000), and Albert
and Barabasi (2002) and suggest that ft, may be a useful
approximation for determining the power-law tail of the
school-size distribution (Appendix Fig. 1).
The simulation results showed the dynamics of Pkt.
When the aggregated initial condition was imposed, at
the start of the simulations there were no schools with
only one fish in them (P,, = 0). Eventually, as the number
of schools and fish declined, P„ became positive. Finally,
as the distribution became scale-free, -i)Px,l Hk became
negative and remained so throughout the remainder of the
simulation or until a single giant cluster was formed (Ap-
pendix Fig. 1). Conversely, if the initial conditions began
with schools being disaggregated, then dPuldk began as
a negative number and remained so until either a giant
cluster formed or there were no more fish remaining.
An approximation is suggested by the above results
for circumstances when the initial conditions are disag-
gregated and when there is preferential attachment: the
differential equation dP,. , Idt when k = 1 ( Eq. 6 ) is replaced
by
dPuldt
-irPy,IN, + ;?Ml-Pu)/JV,.
(A4)
Powers: Recruitment as an evolving random process of aggregation and mortality
365
1 1 ,000
School size (no. of fish)
Appendix Figure 1
School-size distribution at selected times. (A) School-size
distribution of a simulation starting with a disaggregated
initial condition, S=106, n=10_6, where mortality is density-
independent (»!(/l) and there is preferential attachment (w^).
(B) Distribution starting with an aggregated initial condition,
S=2xl06, «=1.5xl0~6, where mortality is density-dependent
proportional to schools imdN) and with preferential attachment
(w a). The dotted lines are the predictions of y = 1 + 1//3 from
Equation A2, horizontally offset for viewing.
366
Abstract— We examined the diets and
habitat shift of juvenile red snapper
(Lutjanus campechanus) in the north-
east Gulf of Mexico. Fish were col-
lected from open sand-mud habitat
(little to no relief), and artificial reef
habitat (1-m3 concrete or PVC blocks),
from June 1993 through December
1994. In 1994, fish settled over open
habitat from June to September, as
shown by trawl collections, then began
shifting to reef habitat — a shift that
was almost completed by December as
observed by SCUBA visual surveys.
Stomachs were examined from 1639
red snapper that ranged in size from
18.0 to 280.0 mm SL. Of these, 850
fish had empty stomachs, and 346 fish
from open habitat and 443 fish from
reef habitat contained prey. Prey were
identified to the lowest possible taxon
and quantified by volumetric measure-
ment. Specific volume of particular
prey taxa were calculated by dividing
prey volume by individual fish weight.
Red snapper shifted diets with increas-
ing size. Small red snapper (<60 mm
SL) fed mostly on chaetognaths. cope-
pods, shrimp, and squid. Large red
snapper (60-280 mm SL) shifted feed-
ing to fish prey, greater amounts of
squid and crabs, and continued feeding
on shrimp. We compared red snapper
diets for overlapping size classes (70-
160 mm SL) offish that were collected
from both habitats (Bray-Curtis dis-
similarity index and multidimensional
scaling analysis). Red snapper diets
separated by habitat type rather than
fish size for the size ranges that over-
lapped habitats. These diet shifts were
attributed to feeding more on reef prey
than on open-water prey. Thus, the
shift in habitat shown by juvenile red
snapper was reflected in their diet and
suggested differential habitat values
based not just on predation refuge but
food resources as well.
Diet shifts of juvenile red snapper
(Lutjanus campechanus)
with changes in habitat and fish size
Stephen T. Szedimayer
Marine Fish Laboratory
Department of Fisheries
Auburn University
8300 State Highway 104
Fairhope, Alabama 36532
E-mail address: sszedlmas'acesag auburn.edu
Jason D. Lee
Barry Vittor & Associates
8060 Cottage Hill Rd.
Mobile, Alabama 36695
Manuscript approved lor publication
4 November 2003 by Scientific Editor.
Manuscript received 20 January 2004
..1 NMFS Scientific Publications Office.
Fish. Bull. 102:366-375 (200 1 1
Larval red snapper (Lutjanus cam-
pechanus) spend approximately 26 days
in the plankton, prior to metamorpho-
sis and first appearance on benthic
substrate. For the most part the fish
settle on open substrate, where peaks
in recruitment are observed in August
and September, after which they may
move to more structured habitat some-
time within the first year ( Szedimayer
and Conti, 1999). The apparent advan-
tage of this habitat shift would be
increased food resources and protec-
tion from predators. To help clarify the
value of increased food resources on
reef habitats, comparisons of diets from
the two habitats are necessary. Also,
because many fish species shift diets
with increasing size (Sedberry and
Cuellar, 1993; Burke, 1995; Rooker,
1995; Lowe et al., 1996), we need to
distinguish possible ontogenetic diet
differences from shifts that are due to
habitat.
Previous red snapper diet studies
have focused on larger individuals and
on small sample sizes for fish <250 mm
SL (Camber, 1955; Moseley, 1966;
Bradley and Bryan, 1975). Camber
(1955) described the diets of 15 "small
red snapper" from Campeche Banks,
and reported that 14 of the 15 stom-
achs contained small penaeid shrimps.
Moseley ( 1966) described the diets of 45
"juvenile red snapper" collected off the
coasts of Texas, and 28 off Louisiana.
Louisiana fish fed on fishes, shrimps.
detritus, and stomatopods, and Texas
fish fed on shrimps, crabs, and mysid
shrimps.
Perhaps the most comprehensive red
snapper diet study to date has been
that of Bradley and Bryan ( 1975) which
described the diets, by season, of trawl-
collected (open sand-mud habitat) and
hook-and-line reef "rough bottom ar-
eas" fish off the Texas coast. They de-
scribed the diets of 258 open-habitat
and 190 reef red snapper and found
that juvenile red snapper (25-325 mm
FL) were dependent on shrimp, crabs,
and other crustaceans and that adults
(325-845 mm FL) were dependent on
fish, crabs, and other crustaceans.
They described a change in juvenile
red snapper diet as fish size increased,
"young red snapper depend almost
exclusively upon invertebrates," and
showed a gradual increase in verte-
brate prey with growth. However, they
did not separate out the proportions of
their "juvenile" red snapper that were
collected from reef versus open habi-
tat. Thus, the shift from open to reef
habitat is still poorly understood. If and
when this shift occurs and whether this
shift is accompanied with a diet shift
that is independent of fish-size effects
needs to be defined.
The purpose of the present study-
is to describe the diet of red snapper
off the coast of Alabama — from the
juvenile stage (just after settlement I to
one-year old fish. We examined overall
Szedlmayer and Lee: Diet shifts of Lutjanus campechanus
367
ontogenetic shifts in red snapper diet with increasing size
and possible changes in diet with habitat shifts from open
substrate to structured habitat (artificial reefs).
Materials and methods
Red snapper were collected from open-flat substrate (sand
and mud) and reef habitats (artificial reefs; Fig. 1). The
open habitat was located approximately 6 km south of
Mobile Bay, Alabama (30'06'N, 88°03'W), and ranged
in depth from 12 to 20 m. Previous studies showed very
high concentrations of age- 0 red snapper from these areas
(Szedlmayer and Shipp, 1994; Szedlmayer and Conti,
1999 ). The artificial reef habitats were located in the Hugh
Swingle artificial reef area, approximately 20 km south
of Mobile Bay, AL, and ranged in depth from 18 to 23 m
(Szedlmayer and Shipp, 1994; Szedlmayer, 1997).
We collected fish from open substrate by trawl (7.62-m
head rope, 2.54-cm mesh, 2-mm codend mesh). Samples
were taken every two weeks from June to December
1994; however, time between samples was longer in the
winter because of poor weather. Each trawl was fished
for 10 min, and all age-0 and age-1 red snapper collected
were placed on ice, returned to the laboratory, and frozen
for later analysis. Bottom dissolved oxygen, salinity, and
temperature were sampled with a Hydrolab Surveyor II at
each location (Szedlmayer and Conti, 1999).
Prior to diet analysis, red snapper were thawed, weighed
to the nearest 0.1 g, and measured to the nearest 0.1 mm
SL. The whole fish was preserved in 10% formalin if SL
was <50 mm, whereas for larger fish, stomachs were re-
moved and preserved. After 48 hours in formalin, stomach
samples were transferred to 75% isopropyl alcohol.
Concrete block and PVC artificial reefs (1 m3) were
placed in the Hugh Swingle reef area in August 1992
and July 1993 (Szedlmayer, 1997). "Reef is used here for
defining these artificial habitats. Reefs were not sampled
for a minimum of 3 months after placement. Red snapper
were collected from June 1993 through December 1994.
Fish were collected from these reefs by SCUBA divers
first placing a drop net (3.0 m radius, 1.3 cm square mesh)
over the reef and then releasing rotenone into the enclosed
area. Reef fish were placed on ice in the field and trans-
ported back to the laboratory. Approximately 12-18 h
after collection all reef fish were weighed to the nearest
0.1 g and measured to the nearest 1.0 mm. Stomachs were
fixed in 10% formalin, and after 24 h transferred to 75%'
isopropyl alcohol. Red snapper size classes were also esti-
mated by SCUBA visual surveys in July and August 1994.
On each visual survey, divers counted red snapper by 50-
mm size intervals. Bottom dissolved oxygen, salinity, and
temperature were sampled with a Hydrolab Surveyor II
during each survey.
All stomachs were dissected and contents placed in petri
dishes. All prey were counted and identified to the lowest
possible taxon. Volume was calculated by using an adapta-
tion of the method described by Hellawell and Able (1971).
Each prey taxon from each stomach was placed into a glass
well of a known depth. A cover slide was placed on the well,
Mobile
Bay
X
If
FL
Gulf of Mexico
O
Gulf of Mexico
O
o
o
30.00 N
□ □
DnaDnr
0 5 10 Kilometers
80.00 W
Figure 1
Collection sites for red snapper ( Lutjanus campechanus) in the
northern Gulf of Mexico. Open circles are open habitat trawl
sites, and gray squares are 1-m3 concrete or PVC artificial reefs.
depressing the prey taxon to a known depth (e.g., 1 mm).
The prey were video taped with a high-8 Sony camera
and images were digitized with Image Pro 2.0 software
(Media Cybernetics. Silver Spring, MD). Image size was
calibrated to 0.01 mm by a stage micrometer. The surface
area of each preparation was measured by using Image
Pro software. Volume was calculated by multiplying the
surface area by the known depth. Specific volumes for par-
ticular prey taxa were calculated by dividing prey volume
by individual fish weight (mnv'Vfish wt g). Comparisons of
diet shift by increasing fish size were made by grouping
prey taxa into ten prey groups and by calculating specific
volume for 10-mm-size intervals of red snapper.
A dissimilarity index (Bray-Curtis) was calculated
from specific volumes of individual prey taxa, for overlap-
ping size classes of red snapper both within and between
habitats: Bray-Curtis = IW^-Yj/IiY^+Y^), where Y =
specific volume of jth species, and j and k are the samples
being compared (Field et al., 1982). The dissimilarities
were then used in a multidimensional scaling analysis
(MDS; Schiffman et al., 1981). The MDS provided a two-
dimensional "map" of the distances between samples (fish
368
Fishery Bulletin 102(2)
6
4
2
0
8
£ 6
! 4
O
0 2
1 0
O
E 4
E
g 2
! o
o
6 6
C
yj 4
0_
o 2
0
6
4
2
0
Trawls - 1 1
28 Jun-1 Jul
-d
Reefs = 5
25 May-2 Jun
ELi
Trawls = 31
10-19 Jul
Visual
Reefs = 13
1-25 Jul
L
Trawls = 32
31 Jul-12 Aug
Visual
Reefs = !
9 Aug
J_L
Trawls = 26 Reefs = 2
•23 Aug 23 Aug
1 id1
^t Trawlj
Trawls = 32
9 SeP Reefs = 3
6 Sep
JTlhffl
Trawls = 25
25-28 Sep
Reefs = 4
28 Sep-6 Oct
II
Trawls = 25
12-21 Oct
Reefs = 4
19-24 Oct
Jktft^f^n
Trawls = 26
30 Oct-9 Nov
Reefs = 3, 9-18 Nov
^bjMkffl
Trawls = 15
12-16 Dec
Reefs = 6
5-8 Dec
IT>^
Trawls = 26
9-12 Jan
£\
Reefs = 3
25Mar-15 Apr
100 200 100
Standard length (mm)
200
Figure 2
Movement patterns for age-0 red snapper iLutjanus campechanus) from the
northern Gulf of Mexico in 1994. Black bars represent trawl samples, grey bars
represent reef drop-net samples, and white bars represent SCUBA visual surveys
of concrete reefs.
size and habitat type) in Euclidian space based on the
Bray-Curtis index. Thus, comparisons of red snapper diets
were based on all prey taxa, yet independent of capture
habitat and fish size.
Results
In the sampling areas during the summer and fall of 1994,
salinity ranged from 30 to 35 ppt. Dissolved oxygen was
7 ppm in the early summer, decreased to 3 ppm in July and
August, and increased to 7 ppm in the fall. Temperature
was 22°C in June, increased to 28°C in late August, then
dropped to just below 20°C by December. No significant
differences were detected between trawl and reef sites for
these environmental measures U-test, Ps0.05).
Red snapper showed a clear shift in habitat during their
first few months of life (Fig. 2). Fish first recruited to open
habitat at the end of June, at sizes <40 mm SL. Fish con-
tinued to recruit to open habitat until early September, at
which time they were larger ( 30 to 100 mm SL ) and began
shifting to more structured habitat. By mid-October most
age-0 fish had moved to reef habitat. During the initial
settlement no new recruits were collected or visually ob-
served on the artificial habitats (Fig. 2). Overall, only red
snapper <160 mm SL were collected from open habitat,
whereas only red snapper >70 mm SL were collected from
reef habitat. Size overlapped from 70.0 to 160 mm SL be-
tween habitats (Fig. 3).
A total of 1639 red snapper stomachs were analyzed:
570 from open substrate and 1069 from reef habitat. Prey
were found in 789 (48'< ) of the total stomachs examined,
346 (61%) from the open habitat and 443 (41%) from the
reef habitat (Fig. 3). Trawl-collected red snapper were
mostly collected from site one, but sample sizes were also
large (>30 with prey) at two other sites (Table 1). Total red
Szedlmayer and Lee: Diet shifts of Lut/anus campechanus
369
Open Habitat n=346
Reef Habitat n=443
Empty n=850
QD=-
■i~~ r i T i i
60 80 100 120 140 160 180 200 220 240 260 280 300
Size class (mm SL)
Figure 3
A comparison of red snapper {Lutjanus campechanus) length frequencies between
open and reef habitats in the northern Gulf of Mexico. Gray bars = empty stomachs
from both habitats.
Table 1
Number of red snapper (Lutjanus campechanus) stom-
achs sampled in), and number of stomachs containing
prey from open and reef habitat in the northeast Gulf of
Mexico.
Open trawl sites
Reef habitats
n n with prey
n
n with prey
356 223
108
53
45 21
17
5
75 58
198
115
57 33
55
31
37 11
249
71
50
23
14
1
89
45
11
5
209
74
35
10
22
4
12
6
snapper collected from the reefs varied by site (from 11 to
249 fish), but large samples were collected from at least 6
different reefs (Table 1). Large sample sizes were collected
during most months over open habitat, with the exception
of November 1994 (n=12), and for most months (6 out
Table 2
Number of red snapper (Lutjanus campechanus) stomachs
sampled (re), and number containing prey, by month and
year, from open and reef habitat in the northeast Gulf of
Mexico.
Open
habitat
Reef habitat
Month
r
with
Month
n with
and year
n
prey
and year
n
prey
Jul 1994
56
43
Jun
1993
94
50
Aug 1994
169
109
Oct
1993
370
169
Sep 1994
187
98
May
1994
141
37
Oct 1994
97
52
Jun
1994
46
37
Nov 1994
16
12
Aug
1994
41
8
Dec 1994
45
32
Sep
1994
155
86
Oct
1994
76
28
Nov
1994
65
12
Dec
1994
81
16
of 9) from reef sites (Table 2). Only red snapper stomachs
containing prey were used in our analyses.
Red snapper diets showed 55 different prey identi-
fied to the lowest possible taxon. In general, red snap-
per diets were dominated by fish (43%), squid (29.5%),
shrimp (16.4%), and crabs (4.4%; Table 3). Specifically,
the "shrimp" group included Mysidacea (mysid shrimps),
Stomatopoda (mantis shrimps), Penaeidea (penaeid
370
Fishery Bulletin 102(2)
Table 3
Specific volume (mnvVfi
sh weight g) for prey
taxa from red
snapper (Lutjanus compel
ha n us 1. % = percent
specific-voli
lme of total
volume, Habitat = prey
habitat. General prey groups are noted in quotation marks, unid. = unidentified.
Prey taxa
Total volume
Percent
Lowest taxon
Specific volume
Percent
Habitat
Osteichthyes "fish"
5408.2
43.5
unid. fish
3465.9
27.9
Halichoeres spp.
650.4
5.2
reef
Blenniidae
279.2
2.2
reef
Serranidae
278.1
2.2
reef
Serranus subligarius
240.8
1.9
reef
Centropristis ocyurus
207.3
1.7
reef
Engraulidae
117.9
0.9
open
Ophichthidae
100.6
0.8
open
Cynoglossidae
35.2
0.3
open
Triglidae
20.8
0.2
open
Ophichthus sp.
10.8
0.1
open
Cephalopoda "squid"
3665.6
29.5
Loliginidae
3665.6
29.5
open
Natantia "shrimp"
2033.7
16.4
unid. shrimp
544.6
4.4
Sicyoninae
359.6
2.9
reef
Hippolytidae
345.7
2.8
reef
Penaeidae
264.5
2.1
open
Alpheidae
131.1
1.1
reef
Sergestidae
24.2
0.2
open
Luciferinae
22.6
0.2
open
Ogyrididae
8.8
0.1
open
Stomatopoda "shrimp"
Squillidae
221.8
1.8
open
Mysidacea "shrimp"
Mysidacea
109.8
0.9
open
Reptantia "crabs"
550.8
4.4
Portunidae
unid. crab
302.0
143.0
2.4
1.2
mixed
Diogeninae
51.6
0.4
open
Leucosiidae
20.7
0.2
reef
Xanthidae
16.7
0.1
reef
Porcellanidae
7.3
0.1
reef
Chaetognatha
199.6
1.6
Sagitta spp.
199.6
1.6
open
Polychaeta
130.1
1.0
Polycheata
75.4
0.6
mixed
Polychaeta
Onuphidae
34.0
0.3
open
Maldanidae
19.9
0.2
open
Ascidiacea "tunicate"
121.0
1.0
Ascidiacea
121.0
1.0
reef
Calanoida "copepod"
118.2
1.0
Calanoida
113.3
0.9
open
Octopodidae
93.6
0.8
Octopus sp.
93.6
0.8
reef
unid.
79.5
0.6
unid.
79.5
0.6
Amphipoda
13.8
0.1
Amphipoda
9.4
0.1
mixed
Ostracoda
6.1
0.0
Ostracoda
6.1
0.0
open
shrimps), and Caridea (caridean shrimps). In addition,
all Squillidae were probably Squilla empusa, according
to Hopkins et al., (1987). Among fish, many were uniden-
tified due to digestion, but if proportions of unidentified
fish are similar to identified fish, then dominant fish
prey included Halichoeres spp., (5.2c/r ), Blenniidae (2.2%),
and Serranidae (2.2%). Two prey fish were identified to
species: Serranus subligarius (1.9%), and Centropristis
ocyurus (1.7%).
Among the squid taxon, one genus dominated: Lolli-
guncula spp., (29.59! I, but all squid were either L. brevis
or Loligo pealeii (Hopkins et al., 1987). Among shrimp,
dominant taxa included Sicyoninae (2.9%), Hippolytidae
(2.8%), Penaeidae (2.1%), Squillidae (1.8%), and Alpheidae
(1.1%). Among crabs, dominant taxa were mostly Por-
tunidae (2.49; ). Other groups showing greater than 1.0%
included Chaetognatha [Sagitta sp. 1.69J ), and Ascidiacea
or tunicates (1.0%; Table 3).
Szedlmayer and Lee: Diet shifts of Lutjanus campechanus
371
16 48 45 41 37 41 33 35 37 59 67 37 40 37 41 28 28 35 29 13 15 15 5 3
0 20 40 60 80 100 120 140 160 180 200 220 240
Size class (mm SL)
Figure 4
Stomach contents by specific-volume for ten higher taxonomic groups
over 10-mm size classes of red snapper {Lutjanus campechanus) from
both open and reef habitats in the northern Gulf of Mexico. Numbers
on the upper axis are the number of red snapper that contained prey
for each respective size class.
Red snapper shifted diets with increasing size. For red
snapper <60.0 mm SL, diets were dominated by shrimp,
chaetognaths, squid, and copepods. Large red snapper
(60-280 mm SL) shifted to feeding on fish prey, greater
amounts of squid and crabs, and continued feeding on
shrimp (Fig. 4).
The diets of juvenile red snapper changed as they
moved from open to reef habitats. Fish collected had
overlapping sizes of 70.0 to 160.0 mm SL from both open
and reef habitats, and the MDS analysis for this size
range showed a clear separation of diets between the two
habitats (Fig. 5). Two points that were outliers (R75, T155 1
were biased because they represented only one fish each,
and the third outlier (R85) was difficult to explain.
The clear separation of red snapper diets shown by the
MDS analysis can be attributed to several prey shifts that
accompanied habitat shifts. For prey crabs, open-habitat
red snapper diets were dominated by Xanthidae, and
smaller amounts of Paguridae, Portunidae, Diogeninae,
and Pinnotheridae (Fig. 6), whereas diets of red snapper
from reef habitats shifted to a dominance by Portunidae
and Diogeninae ( Fig. 7). For prey shrimp, open habitat red
snapper diets were dominated by Penaeidae and Mysida-
cea (Fig. 8), whereas diets from reef habitats shifted to a
dominance of Sicyoninae, Hippolytidae, Alpheidae, and
Squillidae (Fig. 9). For prey fish, open-habitat red snap-
per diets were dominated by Engraulidae (although most
were unidentified; Fig. 10), whereas diets from reef habitat
clearly reflected prey fish from reef habitats and included
Blenniidae, Serranidae, and three prey fish identified to
genera, Centropristis spp, Halichoeres spp., and Sen-anus
spp. (Fig. 11).
-3-2-1 0 1 2 3
X(unitless)
Figure 5
Multidimensional scaling of diets for red snapper (Lutja-
nus campechanus) based on the Bray-Curtis dissimilarity
index computed for specific volume of prey taxa both within
and between habitats for overlapping size classes (70.0 to
159.9 mm SL). The letter and number accompanying each
point indicates the habitat and size class that each point
represents (e.g., T = trawl, R = reef, 75 = 75 mm SL size
class). Circles were drawn by hand. Axes are unitless.
Discussion
The present study provides a substantial sample size
(ft = 1639) for red snapper diet analysis and a relatively
372
Fishery Bulletin 102(2)
16 48 45 41 37 41 32 30 20 15
6 3 3
"I — I 1 r
Crabs
Open habitat
n
T 1 1 1 1 —
UNIDcrab
l l Paguridae
Xanthidae
Portunidae
Diogeninae
I I Pinnotheridae
a
j=u
t — T — T — T — T — T — T — T — ~l 1 1 f — T
0 20 40 60 80 100 120 140
Size class (mm)
Figure 6
Crab prey from open habitat. Stomach contents by spe-
cific volume over 10-mm size classes of red snapper iLut-
janus campechanus) from the northern Gulf of Mexico.
Numbers on the upper axis are the number of red snapper
that contained prey for each respective size class.
16 48 45 41 37 41 32 30 20 15 8 6 3 3
0 4
0
1 1 1 ' 1 —
UNID shrimp
Lucifennae
Mysidacea
I I Ogyndidae
^^1 Penaeidae
Sergestidae
Sicyoninae
I I Squillidae
"Shrimp"
Open habitat
-
II
1
I
I
I
nW
20 40 60 80 100 120 140
Size class (mm)
Figure 8
"Shrimp" prey from open habitat. Stomach contents by
specific volume over 10-mm size classes of red snap-
per (Lutjanus campechanus) from the northern Gulf of
Mexico. Numbers on the upper axis are the number of red
snapper that contained prey for each respective size class.
5 17 44 59 31 37 34 40 28 28 35 29 13 15 15 5 3
5 3 -
m
E
I I I I 1 I 1 I I 1 I I I
1 1 UNIDcrab
Crabs 1 1 Xanthidae
Reef habitat ^m Portunidae
I I Diogeninae
1 1 Pinnotheridae
fSSg Porcellanidae
|::::::| Leucosiidae
i i i
^E,
"5 2-
>
<u
n.
Specific volume
i
i-i
_
lR.il
1
1
■
r-]
II
u 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
80 100 120 140 160 180 200 220 240
Size class (mm)
Figure 7
Crab prey from reef habitat. Stomach contents by specific
volume over 10-mm size classes of red snapper (.Lutjanus
campechanus) from the northern Gulf of Mexico. Num-
bers on the upper axis are the number of red snapper that
contained prey for each respective size class.
4 -
5 17 44 59 31 37 34 40 28 28 35 29 13 15 15 5 3
— ' 1 ' — I —
"T"
"T"
"Shrimp"
Reef habitat
I I Alpheidae
I I UNID shrimp
I I Hippolytidae
l l Sergestidae
I I Sicyoninae
I I Squillidae
80 100 120 140 160 180 200 220 240
Size class (mm)
Figure 9
"Shrimp" prey from reef habitat. Stomach contents by spe-
cific volume over 10-mm size classes of red snapper iLut-
janus campechanus) from the northern Gulf of Mexico.
Numbers on the upper axis are the number of red snapper
that contained prey for each respective size class.
Szedlmayer and Lee: Diet shifts of Lut/anus campechanus
373
20
15
10
16 48 45 41 37 41 32 30 20 15 8 6
■ I ■ I ■ I
Fish
Open habitat
. I I Cynoglossidae
|^H Engraulidae
1 1 Ophichthidae
I 1 Serranidae
II Synodontidae
1 1 UNIDfish
1 1 Triglidae
i
■,
1
i
i
20
40 60 80
Size class (mm)
100 120 140
Figure 10
Fish prey from open habitat. Stomach contents by specific
volume over 10-mm size classes of red snapper (Lut/anus
campechanus) from the northern Gulf of Mexico. Num-
bers on the upper axis are the number of red snapper that
contained prey for each respective size class.
1b -
—
14 -
CT
-
13 -
<1>
12 -
<
11 -
</)
~
10 -
E
q -
r
8 -
r,
7 -
>,
Cl
b -
<D
R -
t-
3
4 -
5 17 44 59 31 37 34 40 28 28 35 29 13 15 15 5 3
3 -
Fish
Reef
Habitat
Blennndae
Centropristis
Halichoeres
Ophichthidae
Serranidae
Serranus
Triglidae
unid
HI
o
80 100 120 140 160 180 200 220 240
Size class (mm)
Figure 11
Fish prey from reef habitat. Stomach contents by spe-
cific volume over 10-mm size classes of red snapper
(Lutjanus campechanus) from the northern Gulf of
Mexico. Numbers on the upper axis are the number of red
snapper that contained prey for each respective size class.
high percentage of stomachs with food (48%) compared to
past studies. Rooker ( 1995 ) also showed a high percentage
(69%; 312 out of 449 stomachs) of schoolmaster snapper
(Lutjanus apodus) contained prey, when fish were col-
lected from depths similar to those of the our study ( 1 to 27
ml. The higher percentage of stomachs with prey found in
our study compared to past studies of red snapper ( Stea-
rns, 1884; Camber.1955; Moseley, 1966) may be due to the
shallower depths sampled (18 m; DeMartini et al., 1996).
Juvenile red snapper showed feeding patterns similar
to many other marine fishes. After settlement, from ap-
proximately 20 to 60 mm SL, they showed a wide-ranging
diet that included shrimp, copepods, chaetognaths, and
squid. Prey fish were also found in the stomachs of the
smallest red snapper collected (15-20 mm SL) but were
not a dominant component. Sweatman (1993) reported
similar results for the snapper Lutjanus quinquelineatus,
ranging from 24 to 29 mm SL, i.e., piscivorous in the first
few days after settlement. Above 60 mm SL, fish prey
tended to dominate specific volume, but not by feeding less
on shrimp because shrimp continued to be an important
prey. Squid became another dominant component of red
snapper diet at about 100 mm SL and also continued as an
important prey up to 240 mm SL. Unfortunately, sample
size was reduced above 230 mm SL, and it was difficult
to estimate if squid and fish continued as dominant prey
components above these size classes. Sedberry and Cuellar
( 1993 ) reported a similar shift in diets of reef-associated
vermilion snapper (Rhomboplites aurorubens). This spe-
cies shifted from small crustaceans to fishes and cepha-
lopods over a size range similar to that of red snapper in
the present study. Moseley ( 1966 ) reported a "slow transi-
tion from zooplankton to macro animals for red snapper
sizes between 40 and 90 mm" — a transition that probably
included fish prey that he did not specifically identify.
Bradley and Bryan (1975), showed a shift in juvenile red
snapper diets with size (25-325 mm FL). Their smallest
red snapper keyed on invertebrates, then showed a sharp
increase in dependency upon prey fish above 175 mm
FL, when Batrachoididae (toadfish) became a dominant
component. These shifts in diet are important in helping
to identify fish habitat and are potentially key aspects of
early survival.
Red snapper showed two major habitat shifts in their
first year. Juvenile red snapper first settled from the
plankton to benthic substrate near 20 mm SL ( Szedlmayer
and Conti, 1999 ). The present study showed a second shift
from open habitat to reef habitat starting at about 70 mm
SL (Fig. 3). No fish smaller than 70 mm were collected
from the reefs, and smaller red snapper were rarely ob-
served on these reefs from SCUBA visual surveys. No fish
larger than 160 mm SL were caught from the open habitat
but were present on the reefs. This finding suggested that
red snapper had shifted to reef habitat by 160 mm SL but
also may have avoided trawl gear as described earlier for
age-0 red snapper (Bradley and Bryan, 1975) and age-0
summer flounder (Paralichthys dentatus) (Szedlmayer
and Able, 1993). However, no large (150-300 mm) red
374
Fishery Bulletin 102(2)
snapper were observed over open habitat by a SCUBA
visual survey despite our observations that red snapper
are attracted to SCUBA divers. Thus we suggest that a
shift in habitat was more likely the cause of this absence
than trawl avoidance.
The distinct diet shift as red snapper changed habitats
was independent of increasing size and suggested that
different benthic habitats play a critical role in the early
life history of this species. This separation was completely
independent of "a priori" knowledge of sample location and
fish size. For example, the MDS analysis showed almost
complete separation based on habitat rather then fish size
(Fig. 5). These differences between open and reef habitat
were readily apparent when prey taxa were separated
into lower taxonomic categories. For example, fishes such
as Halichoeres spp., Serranus spp., and Centr-op/istis spp.,
were found only in the diets of reef-collected red snapper.
These species are closely tied to reef structure (Nelson
and Bortone, 1996). Prey shrimp also showed distinct
differences in red snapper diets between habitats. Over
open habitat, Mysidacea, Penaeidae, and Sergestidae were
important components. After the shift to reef habitat,
Mysidacea were absent and Penaeidae and Sergestidae
were greatly reduced, and Sicyoninae, Hippolytidae, and
Alpheidae became the dominant shrimp components.
The latter are all families typically associated with reef
habitats (Chance, 1970; Pequegnat and Heard, 1979).
One exception was the increased feeding on Squillidae, an
open habitat crustacean, at the largest size classes of this
study (220-250 mm SL; Fig. 9). For crabs, the separation
was not as clear, because of the dominance of Portunidae,
which can be assigned to both open and reef habitats.
However, increases in reef crabs were still apparent with
habitat shift, i.e., Diogeninae, Porcellanidae, and Leucosi-
idae can all be considered reef prey. Although Bradley and
Bryan (1975) pooled "juvenile" red snapper over open and
reef habitats, they did show a marked increase in fish prey
above 175 mm FL. This increase was almost exclusively
due to Batrachoididae or toadfishes, which are typically
found in reef habitat. We did not observe any toadfish prey
in our juvenile red snapper collections, but its presence in
this earlier study is consistent with present findings show-
ing a shift to feeding on reef-habitat prey.
Red snapper diet shifted to greater percentages of reef-
prey with movement to reef habitat, but with this shift
they also continued feeding on other prey. This flexibility
in feeding habits allows red snapper to take advantage
of prey from wide-ranging habitats. Similar diet shifts
related to habitat shifts have been shown in schoolmaster
snapper, (L. apodus) (Rooker, 1995). The schoolmaster
snapper shifted from nearshore mangroves to coral reef
habitats near 70 mm SL; diets offish s70.0 mm SL were
dominated by crustaceans, particularly amphipods and
crabs. Fish >70.0 mm SL fed on fishes and to a lesser ex-
tent crabs, shrimps, and stomatopods. Similar diet shifts
were also shown for several fish species of Puget Sound.
For example in pile perch {Rhacochilus vacca), striped
seaperch iEmbiotoca lateralis), and quillback rockfish
(Sebastes maliger), the smallest juveniles preyed on open-
habitat plankton and benthic fauna, and medium-size
and larger fish (>121 mm) of all three species shifted their
diets to include reef-associated prey ( Hueckel and Stayton,
1982). However, at larger sizes these three species were
not totally dependent on reef-associated prey.
We have examined red snapper diets based on specific
volume of food. Although many other studies have used
an index of relative importance (IRI; Pinkas et al., 1971:
Cortes, 1997), we were specifically interested in the nutri-
tional value of particular prey, and prey separation into
open-habitat or reef-habitat. With IRIs these separations
would be more difficult to define, e.g., pelagic prey with
high numbers might be considered more important, but
actually provide little nutritional value to red snapper
diets (Macdonald and Green, 1983). Future studies on the
effects of red snapper predation on prey distributions may
be better suited for using IRIs.
In summary, red snapper diets from open habitat
showed prey taxa associated with open sand-mud sub-
strate and the planktonic environment. Open-habitat prey,
such as chaetognaths, are known to be pelagic as well as
benthic, as are sergestid shrimp, calanoid copepods, my-
sids, and stomatopods (Williams, 1968; Manning, 1969;
Gosner, 1978; Stuck et al., 1979; Alldredge and King,
1985; Lindquist et al., 1994 ). Red snapper shifted diets to
reef-associated prey with their habitat shift, and this diet
shift was independent offish size. These diet shifts were
clearly apparent for both fish and shrimp prey but less
so for crab prey. As shown with marine fish species from
Puget sound, red snapper diets from reef habitat were not
restricted to reef-associated prey. For example, squids
were an important prey over both open and reef habitats
in the present study and our findings agree with those
of Bradley and Bryan (1975). The squids Loligo sp., and
Lolliguncula sp. are both abundant in nearshore coastal
waters and are not typically associated with reef structure
(Gosner 1978; Laughlin and Livingston, 1982; Hopkins
et al., 1987). Availability and ease in capture could be a
key as to why squid are important for red snapper over
size ranges of 40 to 240 mm SL. This flexibility in feeding
habits allows red snapper to take advantage of prey from
wide-ranging habitats, but clear shifts to additional reef
prey supports the hypothesis that reef structure provides
new prey resources.
Acknowledgments
We thank Joseph Conti, Kori M. Heaps, and Frank S.
Rikard for help in field collections and invertebrate
identification. This study was funded by NOAA, NMFS.
MARFIN grant number USDC-NA47FF0018-0. This is a
contribution of the Alabama Agricultural Station.
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1995. Feeding ecology of the schoolmaster snapper, Lut-
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1993. Tropical snapper (Lutjanidae) that is piscivorous at
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1997. LHtrasonic telemetry of red snapper, Lutjanus
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376
Abstract— We measured growth and
movements of individually marked
free-ranging juvenile white shrimp
[Litopenaeus setiferus) in tidal creek
subsystems of the Duplin River,
Sapelo Island. Georgia. Over a period
of two years, 15.974 juvenile shrimp
(40-80 mm TL) were marked inter-
nally with uniquely coded microwire
tags and released in the shallow upper
reaches of four salt marsh tidal creeks.
Subsequent samples were taken every
3-6 days from channel segments
arranged at 200-m intervals along
transects extending from the upper to
lower reach of each tidal creek. These
collections included 201,384 juvenile
shrimp, of which 184 were marked
recaptures. Recaptured shrimp were at
large an average of 3-4 weeks (range:
2-99 days) and were recovered a mean
distance of <0.4 km from where they
were initially marked. Mean residence
times in the creek subsystems ranged
from 15.2 to 25.5 days and were esti-
mated from exponential decay func-
tions describing the proportions of
marked individuals recaptured with
increasing days at large. Residence
time was not significantly correlated
with creek length (Pearson = -0.316,
P= 0.684 I, but there was suggestive
evidence of positive associations with
either intertidal (Pearson r = 0.867,
P=0.133) or subtidal (Pearson /-=0.946,
P=0.054) drainage area. Daily mean
specific growth rates averaged
0.009 to 0.013 among creeks; mean
absolute growth rates ranged from
0.56-0.84 mm/d, and were lower than
those previously reported for juvenile
penaeids in estuaries of the southeast-
ern United States. Mean individual
growth rates were not significantly
different between years (/-test, P>0.30)
but varied significantly during the
season, tending to be greater in July
than November. Growth rates were
size-dependent, and temporal changes
in size distributions rather than tem-
poral variation in physical environ-
mental factors may have accounted for
seasonal differences in growth. Growth
rates differed between creeks in 1999
U-test, P<0.015), but not in 1998 (r-test,
P>0.5). We suggest that spatial varia-
tion in landscape structure associated
with access to intertidal resources may
have accounted for this apparent inter-
annual difference in growth response.
Manuscript approved for publication
30 September 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:376-388(20011.
Individual growth rates and movement of
juvenile white shrimp (Litopenaeus setiferus)
in a tidal marsh nursery*
Stacey Webb
Florida Department of Environmental Protection
Water Quality Standards and Special Proiects Program
2600 Blair Stone Road, M.S. 3560
Tallahassee, Floida 32399
E-mail address: stacey fekervcudep state. fl. us
Ronald T. Kneib
UGA Marine Institute
Sapelo Island, Georgia 31327
In 2001, shrimp became the most popu-
lar seafood in the United States when
per capita consumption (1.54 kg) sur-
passed that of canned tuna (1.32 kg)
for the first time in recorded history
(NOAA1). Although 77% of the catch
is from the Gulf of Mexico, commercial
fisheries in Atlantic coastal states of
the southeastern United States also
depend heavily on penaeid shrimp pop-
ulations. Of the three most common
estuarine-dependent penaeid species
(Litopenaeus setiferus, Farfantepenaeus
aztecus, and F. duorarum)2 harvested
in the South Atlantic Bight, white
shrimp Litopenaeus setiferus domi-
nate, comprising >70% of the catch in
the region (North Carolina to the east
coast of Florida) and 75-87% in South
Carolina and Georgia (NMFS:I).
Concerns over the possibility of de-
pleting the resource as early as the
1930s led to intensive studies of the
life cycle (Lindner and Anderson, 1956;
Williams, 1984). The white shrimp has
an annual life cycle that can be divid-
ed into offshore (oceanic) and inshore
(estuarine) phases. Adults spawn in
Atlantic waters in spring and the post-
larvae migrate into estuaries, aided by
flood tides and wind-generated currents
(Lindner and Anderson, 1956; Wenner
et al., 1998). Postlarvae penetrate into
the shallow upper reaches of the nurs-
ery habitat where juveniles achieve a
substantial portion of their adult body
mass before moving into deeper creeks,
rivers, and sounds where they approach
maturity and emigrate seaward to
spawning areas (Muncy, 1984; Wil-
liams, 1984).
Given the commercial importance
and early interest in this species, sur-
prisingly little research has focused on
the juvenile stages within tidal marsh
nursery habitats ( Minello and Zimmer-
man, 1985; Zein-Eldin and Renaud.
1986; Knudsen et al., 1996; McTigue
and Zimmerman, 1998). Seasonal mi-
grations and ontogenetic movements
of white shrimp between coastal ocean
spawning grounds and estuarine nurs-
eries are well known ( Dall et al.. 1990 1.
as are the sometimes extensive migra-
tions of adult shrimp along the Atlantic
coast, primarily to the south during
fall and early winter, and northward in
late winter and early spring (Lindner
and Anderson, 1956; Shipman, 1983).
Within the estuary, juvenile white
■Contribution 921 of the Univerisity of
Georgia Marine Institute, Sapelo Island,
GA.
1 NOAA (National Oceanic and Atmo-
spheric Administration. 2002. Shrim
p overtakes canned tuna as top U.S. sea-
food. Website: http://www.noaanews.
noaa.gov/stories/s970.htm. I Accessed:
28 August 2002.]
- These species were all previously included
in the genus Penaeus, but the subgenera
were elevated to genera by Perez-Farfante
and Kensley (1997).
:! NMFS (National Marine Fisheries
Service). 2002. Unpubl. data. Web-
site: http://www.st.nmfs.gov/stl/commer-
cial/index.html. lAccessed 29 August
2002.1
Webb and Kneib: Individual growth rates and movement of Litopenaeus setiferus in a tidal marsh nursery
377
shrimp, in contrast to other penaeid species, are found
across a wider range of environmental conditions and
habitats (Kutkuhn, 1966) and often make tidal excursions
between subtidal and vegetated intertidal habitats to for-
age (Mayer, 1985; Kneib. 1995; 2000). However, relatively
little is known about movements within subtidal creeks of
the primary nursery areas, and the degree to which indi-
viduals exhibit fidelity to a particular tidal creek drainage
system is unknown.
Direct measurement of juvenile shrimp growth rates
within the nursery have also been rare. Most growth
estimates for free-ranging juvenile shrimp are based on
analyses of size-frequency data, which can be misleading
(Loesch, 1965). Shrimp grow rapidly while in the estua-
rine nursery throughout the summer and early fall, and
juveniles approach adult, or commercially harvestable size
within 2-4 months after immigration to the estuary
(Kutkuhn, 1966; Williams, 1984). Mean absolute growth
rates of 0.7-1.1 mm/d are commonly reported for many
penaeids (Dall et al., 1990). However, growth studies are
difficult to compare because the rate of growth may vary
between years and among seasons, as well as with size,
age, and sex of individuals (Perez-Farfante, 1969). Growth
estimates for Litopenaeus setiferus range widely, from 10 to
65 mm/month (Williams, 1984). Previous estimates were
based on a variety of approaches including experimental
studies in aquaria and ponds (Pearson, 1939; Johnson and
Fielding, 1956), size distributions from tagging studies of
adults (Lindner and Anderson, 1956), length-frequency
distributions of juveniles in field samples (Gunter, 1950;
Williams, 1955; Loesch, 1965; Harris, 1974; Mayer, 1985),
mark-recapture of uniform size ranges of subadults and
adults (Klima, 1974), and mark-recapture of shrimp in
marsh ponds (Knudsen et al., 1996). Many estimates of
growth for small (<80 mm TL) juvenile L. setiferus have
been extrapolated from mark-recapture studies of larger
(>100 mm TL) individuals (Lindner and Anderson, 1956;
Harris, 1974; Klima, 1974). However, there is a paucity
of empirical data on growth rates of small, free-ranging
juvenile white shrimp within natural estuarine nursery
habitats. The purpose of the present study was to provide
reliable data on growth and movements of individual ju-
venile white shrimp within a natural estuarine nursery
environment and to initiate an assessment of spatial
variation in habitat quality in relation to tidal marsh
landscape structure.
Recent innovations in tagging techniques have pro-
duced an effective way to obtain information on individual
organisms through the use of sequentially numbered bi-
nary-coded microwire tags (Northwest Marine Technol-
ogy. Inc. Shaw Island, WA). Microwire tags were first used
in tagging experiments by Jefferts et al. (1963) and have
since been used successfully to tag a variety of crustaceans
including prawns (Prentice and Rensel, 1977), crayfish
(Isely and Eversole, 1998), blue crabs (van Montfrans et
al., 1986; Fitz and Weigert, 1991), and lobsters (Krouse
and Nutting, 1990; Uglem and Grimsen, 1995). Results
of these studies and others generally show that tag reten-
tion rates are high and tagging has little effect on the
growth or survival of the fishes and crustaceans in which
microwire tags have been used. In a laboratory study
involving 240 juvenile white shrimp, Kneib and Huggler
(2001) confirmed that tag retention was high (-98%),
growth rates between tagged and control individuals were
not significantly different, and the best location (based
on tag retention and survival) for tag injection was in the
muscle tissue of the abdomen. This type of tag allows for
identification of individuals because each tag is etched
with a unique number encoded in binary form. In addi-
tion, the tag is completely internal and inconspicuous, thus
eliminating problems associated with external tags (e.g.,
streamer-type tags) that might interfere with molting or
increase predation risk (Garcia and LeReste, 1981; van
Montfrans et al., 1986; Isely and Eversole, 1998).
Materials and methods
Study area
All samples were collected from four tidal creek subsys-
tems associated with the Duplin River on the west side of
Sapelo Island, Georgia. The Duplin River tidal drainage
( -11 km2 ) includes almost 10 km- of tidal salt marsh that is
inundated twice daily by unequal tides with a mean range
of 2.1 m (Wadsworth, 1980). Smooth cordgrass iSpartina
alterniflora) is the dominant vegetation in the intertidal
marshes of this area. Seasonal water temperatures aver-
age between 10°C and 30°C, and salinity is characteristi-
cally polyhaline, ranging from 15 to 30 ppt (Kneib, 1995).
Freshwater flow into the system is intermittent and
originates largely from local upland runoff and indirect
flows by several interconnected tidal channels from the
Altamaha River about 8 km to the southwest (Ragotzkie
and Bryson. 1955).
Tidal creeks included in this study were Post Office
Creek (PO) and Stacey Creek (SO in 1998, and the East
and West forks (EF. WF, respectively) of the upper Duplin
River in 1999 (Fig. 1). Logistical constraints precluded
sampling shrimp populations from more than two creek
systems within the same year, and different pairs of
creeks were chosen in each of the two years to broaden the
spatial coverage of the study. High-resolution black and
white photographs (1:16000 scale) from an aerial survey of
the region in December 1989 were used to measure broad-
scale structural characteristics of the creek systems, in-
cluding areal extent of the intertidal and subtidal portions
of each drainage. The metrics and methods of extracting
the information from the photographs are fully described
elsewhere (see Webb and Kneib, 2002).
Field sampling
Shrimp were collected by cast net along the shallow (<1 m
depth) edges of the subtidal portion of each creek system
during low tide. Preliminary studies showed that 1.52-m
diameter nets with ca. 1-cm mesh size collected the range
of juvenile shrimp sizes (40-80 mm) targeted for mark-
ing in this study. All samples were collected within
2-3 hours of low tide to ensure that the shrimp popula-
378
Fishery Bulletin 102(2)
Figure 1
Map of the salt marsh estuary in the vicinity of Sapelo Island, Geor-
gia, showing locations of the tidal creek subsystems within the tidal
drainage of the Duplin River.
tion was restricted to the tidal creek channels and had no
refuge in the intertidal vegetation. A series of stations, at
intervals of approximately 200 m, was established along
the length of the subtidal portion of each creek from the
upper reaches to the mouth, so that the number of stations
within a creek depended on the navigable length of the
subtidal channel. There were 13 stations in PO, 11 in SC,
9 in EF, and 7 in WF. Salinity, water temperature, and
dissolved oxygen were measured near the surface (<1 m
depth) at the mouth of the tidal creek on each day of
sampling by using a YSI model 85 meter ( YSI, Inc. Yellow
Springs, OH). Juvenile shrimp were marked with uniquely
coded microwire tags (1.1 mm longx0.25-mm diameter,
Northwest Marine Technology [NMT], Inc. Shaw Island,
WA), which were injected into the muscle tissue of the
first abdominal segment. We used a hand-held multishot
injector (NMT) that was designed to cut, magnetize, and
inject sequentially coded tags from a continuous stain-
less-steel wire spool. Each tag was etched with six lines of
binary code that could be read under a microscope (25x)
and translated into a set of numbered coordinates. Only
three of the coded lines were required to identify a unique
individual. A master line contained a distinguishing
sequence code that was necessary to properly interpret
codes on data lines designated D3 and D4. The numeri-
cal values associated with these coded lines were entered
into a sequential tag conversion computer program (GR
[Growth Rate], version 1.3, Northwest Marine Technology.
Inc. Shaw Island, WA) that output the unique tag number
corresponding to those coordinates.
A reference tag was archived for every shrimp marked in
order that the code on either side of the tag injected into a
shrimp was known with certainty. This was necessary to
ensure positive identification of recaptured individuals be-
cause the injector was designed only to cut tags to a known
length (1.1 mm) and did not distinguish between the be-
ginning and end of sequential codes and often cut tags that
included a portion of two adjacent codes. Prior to their re-
lease, marked shrimp were passed across a magnetometer
(NMT) which signaled the presence of the ferromagnetic
tag with an audible tone and flashing light. All shrimp
collected after these marking sessions were scanned in
the same manner and when a tag was detected, it was
removed from the recaptured shrimp, cleaned and read
under the microscope. The two reference tags bracketing
the recovered tag were then located in the archive set to
determine the date, location, and initial length at release
of the marked shrimp. Thus the growth rate, time at large,
and distance between points of release and recapture could
be determined with certainty for individual shrimp.
Webb and Kneib: Individual growth rates and movement of Litopenaeus setiferus in a tidal marsh nursery
379
Shrimp were marked and released only in the upper
reaches of each tidal creek. During the marking process,
small batches of shrimp (<50 individuals) were collected
and held in insulated plastic coolers. Water in the coolers
was exchanged each time a new batch of shrimp was col-
lected. Only active individuals, 40-80 mm total length
(TL, tip of the rostrum to end of the telson) and in appar-
ently good condition, were candidates for marking. The
marking process required a minimum field crew of two
researchers. One measured shrimp and recorded data,
while the other injected tags and released marked shrimp
at the edge of the tidal creek.
We attempted to mark 1000 shrimp during a 3-day pe-
riod in each tidal creek near the beginning of every month
from July to November in both years. It was not possible
to tag shrimp in both creeks simultaneously; therefore
shrimp were marked and released in week 1 during the
first week of the month, then in creek 2 during the second
week of the month. The remainder of the month was spent
collecting marked shrimp (Fig. 2). Inclement weather
and mechanical problems with the tagging equipment
sometimes prevented us from achieving the goal of tag-
ging 1000 shrimp per creek within the first week of each
month. In August 1998, the tag injector malfunctioned on
the first day of tagging in SC and was unavailable for sev-
eral weeks while it was being refurbished. Consequently,
sampling was suspended in SC during that time. Although
the same problem occurred while we attempted to mark
shrimp from the EF in September 1999, we continued
sampling in an attempt to recapture shrimp tagged in
previous months.
A total of 6 sampling events after marking were planned
in each creek per month (Fig. 2). A sample consisted of the
combined contents of 10 haphazard casts of the net along
the edge of the tidal creek within each station per sampling
date. Shrimp populations were usually sampled at 3-day
intervals for 21 days beginning from the midpoint of the
marking period. A consistent exception was the second
sample in the series, which occurred at a 6-day interval to
accommodate the marking effort in the second creek and
to keep the sampling effort consistent in all creeks. Inclem-
ent weather interrupted the sampling schedule on occasion
and when unfavorable conditions persisted for more than 3
days, some of the planned sampling events after marking
were cancelled; some months were represented by fewer
than 6 sampling events. Sampling was terminated when,
as a result of normal seasonal emigration from the nursery
areas, shrimp densities declined to the point that they could
no longer be consistently collected from the tidal creeks by
cast net (19 November 1998 and 21 November 1999).
Catches of marked shrimp from each station were re-
tained in separate plastic bags, placed on ice, and trans-
ported to the laboratory. A subsample of shrimp from each
station (every tenth individual) was measured (TL, mini
to construct size distributions. If a sample included fewer
than 100 shrimp, all were measured. Sex was not deter-
mined. All individuals were scanned for the presence of
tags and when a marked shrimp was detected, it was mea-
sured (TL, mm) before the tag was removed and stored in a
plastic vial for reading at a later date. For each recapture.
Marking —
• ••
•
coo
o
o
• Creek 1
O Creek 2
Postmarking
OOO
sampling
o
10 15 20 25
Days of the month
30
Figure 2
Schedule for monthly marking and postmarking field
schedule for the juvenile white shrimp study.
we recorded date, creek, station of recapture (i.e., distance
from original release site) and size offish.
Daily instantaneous (specific) growth rates (mm/[mm/
d] ) were calculated as
[(In L2- In Lj)/t],
where L2 = total length (mm) of an individual on the date
of recapture;
L1 = initial total length (mm) on the date of tag-
ging; and
t = number of days at large.
Daily absolute growth rates (mm/d) also were calculated
(L2-L1/t) to facilitate comparison with estimates from
previous studies. Displacement (distance moved) was
determined by comparing the location of recapture with
the original location at marking. Residence time within a
tidal creek was determined from a plot of the proportion of
recaptured individuals against time-at -large for each creek
system. First, using the Regression Wizard in the com-
puter program SigmaPlot® (version 8.0, SPSS, Inc. Chicago,
ID, we fitted the data to an exponential decay function:
(y=a x e~bt) ,
where y = the proportion of total recaptures;
t = time at large; and
a and b = the estimated parameters.
Constraints imposed on the fit were a = l (because the
proportion of total recaptures could not exceed 1) and
fe>0 (because this was an exponential decay function).
Mean residence time for shrimp in each creek was then
estimated from the area below the fitted curves describing
the proportion of recaptures with time at large. This was
calculated with the macro function "area below curves"
included in the "Toolbox" menu selection of SigmaPlot®
(vers. 8.0, SPSS, Inc. Chicago, ID which uses the trapezoi-
dal rule to estimate the area under curves.
Statistical analyses
Most of the data analyses used statistical procedures in
version 8.0 of the computer software package Systat®
380
Fishery Bulletin 102(2)
(SPSS, Inc. Chicago, ID. When parametric tests were
performed, residuals were analyzed to determine whether
the data met the required assumptions (Sokal and Rohlf,
1995). Levene's test was used to evaluate conformity to
the assumption of variance homogeneity among groups.
When this assumption was violated, the data were trans-
formed and retested. If the assumptions were still not met,
then an appropriate nonparametric test was applied (e.g.,
Kruskal-Wallis one-way analysis of variance ). Two sample
/-tests were used to compare spatial and temporal varia-
tion in water temperature, salinity, and dissolved oxygen
between creeks within a year and between years. August
was omitted in comparisons of data between creeks in
1998, and between years because sampling in SC was
suspended during August 1998. Regression analyses were
performed to determine whether there were significant
linear relationships between initial shrimp length and
growth rates within each tidal creek. One-way ANOVA
(controlling for the covariate initial length) was used to
test for differences in growth rates between creeks within
each year. A similar approach (controlling for initial size)
was used to test for monthly (seasonal) differences in
growth rate within years. If growth rates did not differ
significantly between creeks, the data were pooled within
year, otherwise creeks were treated separately. Only indi-
viduals at large for a month or less (to ensure that growth
was representative of individual months) were included
in the analyses.
Shrimp at large for fewer than 3 days were excluded
from the statistical analyses to reduce certain antici-
pated biases associated with estimating growth rates.
These included 1) measurement error (assumed to be at
least 1 mm), which would likely represent a substantial
proportion of the growth rate estimate when absolute
change in size was small; 2) increments of growth associ-
ated with molting (Dall et al., 1990), which could either
underestimate growth for shrimp that had been at large
for a short time or had not molted since they were tagged
or overestimate growth if shrimp were recaptured shortly
after the first molt following marking; and 3) size-specific
growth, where shrimp marked at a relatively small size
and smaller shrimp exhibit a higher relative growth, so
that early recaptures could represent larger than average
growth rates.
Results
Physical parameters
Average water temperature, salinity, and dissolved oxygen
(measured at the mouth of each tidal creek) were similar
between creeks within years (see Table 1 in Webb and
Kneib, 2002). In 1998, temperature ranged from 18.9 to
33.4°C, salinity from 18.2 to 28.0 ppt, and dissolved oxygen
from 1.4 to 11.3 mg/L. In 1999, temperature ranged from
15.0 to 33.4°C, salinity from 23.9 to 32.5 ppt, and dis-
solved oxygen from 0.8 to 7.1 mg/L. Temperature followed
expected seasonal patterns each year; mean values were
highest in summer and declined toward autumn. Results
of /-tests with separate variance estimates showed no
significant differences between years in either mean tem-
perature ( = 0.14, df=134.0, P=0.80) or dissolved oxygen
(£=1.82, df=115.9, P=0.07) but mean salinity was sig-
nificantly (£=11.63, df=122.7, P<0.01) higher in 1999 (28.1
ppt) than in 1998 (24.8 ppt). Cumulative rainfall was 83.9
cm/yr in 1998 and 82.9 cm/yr in 1999 (Garbisch4). These
values were indicative of drought conditions because they
were well below the long-term mean annual precipitation
value of ca. 132 cm/yr reported for Sapelo Island between
May 1957 and March 2003 (Southeast Regional Climate
Center5).
Growth
Shrimp collections during recapture efforts ranged from
20,077 to 78,724 individuals, but the proportion of marked
individuals recaptured was low in both years, averaging
just over 1% (Table 1). However, the recaptures included
184 individuals for which growth rates and net movements
within the nursery were known precisely.
Daily absolute growth rates of individuals, which
ranged from 0.25 to 2.5 mm, averaged 0.86, 0.78, 0.84, and
0.61 mm at PO, SC, WF and EF, respectively. The mean
values are on the low end of the range reported in previ-
ous studies of juvenile Litopenaeus setiferus with other
methods and conducted in different locations (Table 2).
Daily specific growth rates were size-dependent in both
years. Negative linear relationships between growth rate
and initial size (i.e., smaller shrimp grew relatively faster)
was the prevalent trend in all creeks (Fig. 3). No sig-
nificant difference (£=1.19, df=74, P=0.237) in growth was
detected between PO and SC, where mean (±SD) specific
(instantaneous) daily growth rates were 0.014 ±0.006 and
0.012 ±0.007, respectively. In 1999, shrimp exhibited sig-
nificantly U=2.12, df=56, P=0.038) higher mean specific
growth rates in the WF ( 0.014 ±0.008) compared to the EF
(0.010 ±0.006) of the Duplin River. The physical environ-
ment was similar at these sites (Webb and Kneib, 2002),
and there was no significant difference (£=1.43, df=81,
P=0.156) in the mean final sizes of shrimp recaptured
from these sites. However, the mean (±SD) initial size of
marked shrimp at EF (61.3 ±8.3) was significantly U=2.20,
df=81, P=0.031) larger than at WF (56.0 ±10.9); therefore
a lower specific growth rate was to be expected at EF.
On a finer temporal scale, seasonal variation in growth
rates occurred in both years, more rapid growth early in
the season, and a general increase in the mean size of in-
dividuals as the season progressed were evident i Fig. 4).
The earlier observation that specific growth rate declined
with size (Fig. 3) opens the possibility that seasonal
variation in growth rates could be explained simply by
4 Garbisch, -J. Unpubl. data. Univ. Georgia Marine Institute
Flume Dock Monitoring Station, NOAA, Sapelo Island Nat ional
Est ua vine Research Reserve. Univ. Georgia Marine Institute.
Sapelo Island, GA 31327.
5 Southeast Regional Climate Center. Unpubl. data. Website:
http://water.dnr.state.sc.us/water/climate/sercc/elimateinfo/
Instmical/historicaLga.html. [Accessed 21 November 20031.
Webb and Kneib: Individual growth rates and movement of Litopenaeus setiferus in a tidal marsh nursery
381
004
0.03
0.02
0.01
% 0.1
EF
r2 = 0.24
P=0.06
40 50
70 80
0.04
PO
r2 = 0.47
0.03
•
•
P=<0.001
0.02
•
£•••
•
•
•
«>v
• • •
--*V
0.01
••.
•
0.00
,
■% . . .
30 40 50 60 70 80 90
30 40 50 60 70 80 90
0.04
0.03
0.02
0.01
0.00
sc
r2 = 0.16
P=0.04
30 40 50 60 70 80 90
Initial size (TL, mm)
Figure 3
Scatter plots and linear regression results for the relationships between individual specific
growth rates and initial sizes of recaptured juvenile shrimp in each tidal creek subsystem:
EF = East Fork of Duplin River, WF = West Fork of Duplin River, PO = Post Office Creek,
SC = Stacey Creek.
Table 1
Monthly summary of the number of shrimp tagged.
number collected
in subsequent
sampling, and the
number of tagged
shrimp
recaptured in each tidal creek.
Collection site and sampling process
July
August
September
October
November
Total
Post Office Creek
Number tagged and released
1004
1077
1025
1000
779
4885
Number collected after tagging
7477
13.851
4730
8384
1298
35,740
Number of tags recaptured
13
16
16
22
1
68
Stacey Creek
Number tagged and released
719
91
804
862
623
3099
Number collected after tagging
5877
0
5466
6376
2358
20,077
Number of tags recaptured
2
0
12
16
3
33
East Fork of Duplin River
Number tagged and released
812
1000
0
1024
1003
3839
Number collected after tagging
23,080
14,490
11,020
14,804
3449
66,843
Number of tags recaptured
7
11
0
4
4
26
West Fork of Duplin River
Number tagged and released
1008
1000
447
696
1000
4151
Number collected after tagging
32,130
17,926
10,954
10,600
7114
78,724
Number of tags recaptured
27
16
3
4
7
57
382
Fishery Bulletin 102(2)
Table 2
Summary of estimated mean
if reported in other units.
daily absolute growth rates
for juvenile Litopenaeus setiferus. Growth rates were converted to mm/d
Reference
Location
Growth rate
(mm/d)
Method and notes
Gunter, 1950
Gulf of Mexico. Texas
0.8-1.3
Size frequency in field samples, juveniles 28-100 mm
Williams, 1955
coastal North Carolina
1.2
Size frequency in field samples, progression of
maximum sizes of juveniles, 32-117 mm
Johnson and Fielding,
1956
Florida
1.3
Pond culture, juveniles
Lindner and Anderson
1956
South Atlantic Bight
and Gulf of Mexico
1.0-1.3
Extrapolated for juveniles 40-80 mm from Walford
plot results using field mark-recapture (disc tags) data
for individuals 70-205 mm
Loesch, 1965
Mobile Bay, Alabama
0.6-1.0
2.2
Size frequency from spring and summer field samples;
progression of maximum sizes of juveniles 50-135 mm
juveniles 15-70 mm
Klima, 1974
Galveston Bay, Texas
1.4-1.8
Extrapolated for juveniles 40-80 mm from Walford
plot results determined from field mark-recaptured
(stain-injected) subadults (117 mm)
coastal Louisiana
1.0-1.3
Extrapolated for juveniles 40-80 mm from Walford
plot results determined from field mark-recaptured
(stain-injected) subadults (120 mm)
Mayer, 1985'
Sapelo Island, Georgia
0.9-1.5
Estimated from modal size-frequency data for
juveniles 20-120 mm
Knudsonetal.. 1996
coastal Louisiana
0.3-0.7
Mark-recapture (injected pigments) of juveniles
45-58 mm (initial size) from coastal marsh ponds
This study
Sapelo Island, Georgia
0.6-0.9
Monthly mark-recapture (coded ferromagnetic tags)
of juveniles 40-80 mm (initial size) from subtidal
creeks
' Mean growth rates reported ir
derived directly from the data
Table 3 of Mayer 1 1985 ) were inconsistent with cohort data in Figure 8 of that thesis; rates reported here were
Doints shown in Figure 8 of Mayer's thesis.
changes in the average size of shrimp within the nursery
over time.
We tested this hypothesis by comparing mean growth
rates among months after controlling for initial length as
a covariate. For these analyses, the 1998 data from PO and
SC were pooled because there was no evidence of a differ-
ence in growth rates between these two creeks; the 1999
data from EF and WF were analyzed separately because
mean growth rates differed between these two systems.
After removing the effect of initial size, there was no sig-
nificant difference among months in 1998, nor in 1999 at
EF, but significant differences in mean growth remained
detectable among months at WF (Table 3). The findings
from WF also were unusual in that the covariate (initial
length) was not a significant factor in the analysis. Post
hoc multiple comparisons (Bonferroni, experiment-wise
<*=0.05) of mean growth rates among months (without
accounting for the covariate) indicated that the specific
growth rate in July (0.021) was significantly greater than
thai in the other months (0.007 to 0.011). This was the
only statistically significant evidence of seasonal varia-
tion in growth apparently not associated with shrimp size
distributions.
With respect to spatial variation in growth rates of ju-
venile shrimp, the most notable observation in this study
was the relatively low mean growth rate observed at EF
compared to the other sites. This difference could have
resulted from the larger mean initial size of individuals
tagged at EF (61.3 mm) compared with those at WF (56.0)
in 1999. However, a similar difference in mean initial sizes
of marked shrimp between tidal creek subsystems (SC,
64.2 mm; PO, 59.6 mm) in the previous year did not result
in a significant difference in growth rates. When we con-
sidered the structural characteristics of each tidal creek at
a landscape level, the EF subsystem had the largest tidal
drainage area (119.5 ha. ) compared to the other sites ( 58.6
to 104.9 ha.), but proportionally less of that area was inter-
tidal drainage. There was a stronger correlation between
mean growth rate (pooled across all individuals within a
creek) and the proportion of the drainage area that was
Webb and Kneib: Individual growth rates and movement of Litopenaeus setiferus in a tidal marsh nursery
383
Table 3
Summary of ANOVA results for the effects of month on specific growth rate of Litopenaeus setiferus after controlling for the
covariate initial length. Only individuals at large between 3 and 32 days were included in the analyses. PO = Post Office Creek;
SC = Stacey Creek; EF = East Fork of Duplin River; and WF = West Fork of Duplin River. Prob. = probability.
1998 (PO and SC)
EF
WF
Source df
F-value Prob.
df
F-value Prob.
df
F-value
Prob.
Covariate (initial size) 1
Month 4
Error 70
30.77 <0.01
1.25 0.30
1
3
11
1.42 0.26
0.74 0.55
1
4
36
1.42
4.32
0.24
<0.01
Oct
(39)
Nov
(15)
Month
Figure 4
Mean daily specific growth rates and mean initial size of
marked and recaptured juvenile white shrimp by month.
Only individuals at large for 3 to 32 days were included.
Error bars are 2 SEs and the number of observations are
given in parentheses below each month.
intertidal (Fig. 5A) than there was between growth and
mean initial size (Fig. 5B) at the landscape level. There
was almost no correlation between proportion of drainage
area that was intertidal and initial mean size of marked
shrimp (Pearson r=-0.18, P=1.0).
Residence time and movement of marked shrimp
Recaptured shrimp were at large for up to 99 days, but
mean residence time for individuals marked in all four
tidal creeks was between 15 and 26 days (Fig. 6). Mean
residence time was greatest at EF and least at SC. During
their time-at-large, net displacement (distance between
mark and recapture sites) of the marked individuals
ranged from 0 to 3000 m , but averaged 258-373 m in all
creeks. There was no evidence of a significant relationship
between time-at-large and mean net displacement (linear
regression F=1.48; df=l,45; P=0.23), but movement was
slightly related to shrimp size, and larger individuals
showed greater displacement (Fig. 7). Variation in resi-
dence time among creek subsystems was not significantly
0.016
A
0.014 •
Pearson r= 0.090 wp #
P=0.10 po«/-
0.012 ■
^^^ • SC
CO
^ 0.010 ■
^-^
g
EF *
S 0.008 I
£ 0.84 0.86 0.88 0.90 0.92
%_ Intertidal area/total drainage area
™ 0.016
B
J 0.014
0.012
A WF
""""■ •— ^* PO
~~-C^_^^ SC A
0.010
Pearson r= -0.55
P = 0.45 A£F
56 58 60 62 64
Mean initial size (TL, mm)
Figure 5
Correlations between mean daily specific growth
rate in each tidal creek (PO=Post Office, SC = Stacey
Creek, EF=East Fork of Duplin River, WF=West
Fork of Duplin River). (A) The proportion of the tidal
drainage area that is intertidal; IB) mean initial size
of marked shrimp.
correlated with length of the creek mainstem (Pearson
r=-0.32, P=0.684), but there was evidence of positive
associations with the amount of intertidal (Pearson
r=0.87, P=0.133) and subtidal (Pearson r=0.95, P=0.054)
drainage areas within each subsystem.
Most shrimp (939r) were recaptured in the same tidal
creek subsystem in which they were originally marked,
but there was some evidence of movement among creeks
and between the subtidal and intertidal components of
the shrimp nursery within creeks. The marked individual
at large for the longest time (99 days) was recaptured
at the same station where it was originally marked (net
384
Fishery Bulletin 102(2)
Mean residence time
(area under each curve)
Post Office Creek (20.4 days)
Stacey Creek (15.2 days)
100
Mean residence time
(area under each curve):
i East Fork (25.5 days)
i West Fork (20.4 days)
40 60
Days at large
100
Figure 6
Estimates of mean residence times of marked shrimp
in (A) tidal creeks sampled in 1998 and ( B ) creeks sam-
pled in 1999. Estimates are based on the area under the
curves describing the proportion of recaptured marked
shrimp in each creek system that still remained to be
captured after the indicated number of days-at-large.
displacements 0 m). In contrast, one shrimp marked at
PO demonstrated a net displacement of 3 km when it was
recaptured at SC after 61 days at large. Nine shrimp (at
large from 18 to 49 days) marked at WF were recaptured
at EF. and two (at large 19 and 45 days) tagged at EF were
recaptured at WF. It was not possible to determine pre-
cisely when these shrimp moved out of the creek in which
they were tagged or how long they were present in the
creek subsystem where they were ultimately recaptured.
For the growth rate analyses, it was assumed that most
growth occurred while the shrimp were in the creek and
where individuals were marked. The mean (±SD) final
size (mm, TL) of individuals that moved between creek
subsystems was significantly (separate variance estimate
<=2.62, df=16.9, P=0.018) larger (78.9 ±7.4) than that of
the group tagged and recaptured in the same subsystem
(71.3 ±13.1); the initial mean size of the two groups was
nearly identical (57.5 ±10.8 and 57.7 ±10.4, respectively).
Two shrimp (at large 7 and 17 days) tagged at EF were
recaptured at high tide in flume weirs located 25 m into
1000
800
600
400
200
F=7.10, df = 1.37
P = 0.01, r2 = 0.16
40 50 60 70 80 90 100 110
Final size (TL. mm)
Figure 7
The effect of shrimp size at recapture on mean dis-
tance between mark and recapture locations (dis-
placement!. Summary results from the linear regres-
sion ANOVA performed on the data are shown. Values
of mean displacement were based on data from 2-11
individuals within each size.
the interior of the intertidal marsh drained by that tidal
creek subsystem. The flume weir samples were part of an
ongoing study (Kneib, unpubl. data) to determine nekton
use of the intertidal marsh surface (see Kneib, 1991, 1997;
Kneib and Wagner, 1994).
Discussion
Growth
Mean growth rates of juvenile white shrimp measured
in this study (0.6-0.9 mm/d) were near the lower end of
the range of estimates previously reported for juvenile
white shrimp along the U.S. Atlantic and Gulf coasts
(Table 2). The principal difference between the present
and previous studies is that the values presented in this
study were based on direct measurements of free-rang-
ing individual juvenile shrimp rather than on extrapola-
tions from batch mark-recaptures of larger individuals
or changes in modal size frequencies. The open nature of
estuarine ecosystems, prolonged seasonal recruitment to
the nursery, and ontogenetic differences in mortality and
movement all may confound the interpretation of size-fre-
quency data (Haywood and Staples, 1993). Given that our
growth values were based on actual changes in the size
of individuals rather than estimated from the apparent
growth trajectories of cohorts, we are confident that the
mean growth rates reported here accurately reflect those
of free-ranging juvenile white shrimp (40-80 mm TL) in
the polyhaline portion of the tidal marsh nursery habitat
of coastal Georgia.
Temporal differences in observed growth rates in this
study may have resulted from either variation in environ-
mental conditions or spatial variation in habitat quality.
Webb and Kneib: Individual growth rates and movement of Litopenaeus setiferus in a tidal marsh nursery
385
Penaeids are most abundant in tidal marsh nurseries
when physical conditions (eg., temperature and salinity)
appear optimal for their growth and survival (Zein-Eldin
and Renaud, 1986), but environmental variability is
characteristic of most estuaries and therefore is an obvi-
ous starting point for explaining observed differences in
shrimp growth among sites or times. Salinity was the
only environmental factor we measured that showed a
significant difference between years but could not be as-
sociated with any interannual difference in mean growth
rates.
Temperature may affect the growth and estuarine dis-
tribution of juvenile penaeids more than salinity (Vetter,
1983), and interactions between salinity and temperature
may have even greater effects than variation in either fac-
tor alone (Zein-Eldin and Renaud, 1986). Mean tempera-
tures throughout our study period (with the exception of
November) in both years were largely within the optimum
range for growth of white shrimp which, in the laboratory,
was reported to be between 25°and32.5°C (Zein-Eldin and
Griffith, 1969). Higher temperatures generally contrib-
ute to faster growth in young penaeids (Perez-Farfante.
1969; Muncy, 1984), and therefore it seems reasonable to
expect seasonal variation in temperature to be reflected
in growth rates. However, this interpretation is con-
founded by the fact that growth rates also are size depen-
dent (Fig. 3, Table 3) and that increases in mean size of
juvenile white shrimp (Fig. 4) occurred while tempera-
ture in the nursery habitat was decreasing from the July
maxima. It seems likely that growth rates of juvenile
white shrimp were robust over the relatively narrow range
of seasonal variation in temperature and salinity observed
in the present study.
Alternatively, differences in growth between certain
sites could be the result of spatial variation in habitat
quality. This variation need not be a function of water
quality, but rather a function of some structural aspect
of the nursery habitat. There was a strong correlation be-
tween mean growth rates and the proportion of tidal creek
drainage area that was intertidal. Only four creek sub-
systems were examined in ours study, and we recognize
that this is an insufficient sample size to justify anything
more than a suggestive hypothesis. However, evidence of
relationships between the amount of intertidal habitat
and penaeid shrimp production (Turner, 1977, 1992), as
well as the amount of intertidal creek edge and juvenile
shrimp abundance in adjacent subtidal creeks (Webb and
Kneib, 2002), supports the contention that intertidal ac-
cessibility is an important component of nursery habitat
quality for juvenile white shrimp. We propose that the
ratio between intertidal and shallow subtidal habitat may
be a key feature of white shrimp nursery habitat quality.
When tidally inundated, the intertidal portion of marsh
creek drainage systems is used extensively by juvenile
white shrimp (Kneib, 1995, 2000), most likely as a rich
foraging area (Kneib, 1997), and the shallow subtidal
portion functions as a low tide refuge and corridor for the
seasonal migration of postlarvae and subadults between
the open estuary and coastal ocean spawning grounds
and the juvenile nursery (Kneib, 1997, 2000).
Movement and residence time
Understanding the causes of broad-scale migration of
penaeids has obvious implications for predicting com-
mercial catches and therefore these causes have been the
focus of research on shrimp movements for decades ( Perez-
Farfante, 1969; Muncy, 1984). However, finer-scale move-
ments, which may affect growth and survival of juvenile
shrimp within the estuary, are not as well known. Emigra-
tion of white shrimp from estuaries is determined by size,
maturity, and environmental conditions (Muncy, 1984),
and size plays a principal role (Dall et al., 1990). In the
South Atlantic Bight, larger white shrimp (>100 mm TL)
begin emigrating from the nursery to commercial fishing
areas in the nearshore coastal ocean in August (Lindner
and Anderson 1956, Shipman, 1983). We collected few
shrimp >100 mm in the tidal marsh creeks, which is con-
sistent with previous observations of ontogenetic migra-
tion to deeper waters. According to growth rates measured
in this study, a shrimp of 40 mm TL would become large
enough to emigrate from the estuary to the coastal ocean
in 2-3 months (i.e., a shrimp tagged at 40 mm TL could
reach 85-108 mm TL in 2.5 months).
The presence of high densities of small juvenile white
shrimp in the upper reaches of Georgia's tidal marsh
creeks (Harris, 1974; Hackney and Burbanck, 1976; Webb
and Kneib, 2002) has supported the contention advanced
by Weinstein ( 1979) that these areas are primary nurser-
ies for juvenile fish and shellfish. However, it has been
unclear whether these aggregations represent stable res-
ident populations or are composed of tidal transients that
constantly migrate among creek subsystems within the
broader estuarine nursery. Young shrimp are known to
move short distances to avoid unfavorable physiochemical
conditions (Hackney and Burbanck, 1976; Dall etal., 1990)
and routinely make tidally mediated excursions between
subtidal and intertidal portions of the nursery to forage
or escape predators (Kneib, 1995, 1997). Our findings
showed that juvenile white shrimp also tended to remain
resident in the upper reaches of tidal creeks where they
were originally tagged until attaining a size ( 80-100 mm )
at which they normally begin to emigrate from the nursery
(Perez-Farfante, 1969).
Although there was some movement between tidal creek
subsystems, the high level of site fidelity demonstrated
by juvenile white shrimp was remarkable given the open-
ness and degree of tidal flux in the Duplin River system
(mean tide range=2.1 m). Data from the chemical analysis
of shrimp tissue composition also suggest limited move-
ments of juvenile penaeids within estuarine nurseries.
Using the stable isotopes of carbon and nitrogen from mus-
cle tissues of pink shrimp (Farfantepenaeus duorarum),
Fry et al. (1999) traced shrimp movements within and
between seagrass and mangrove habitats of southwestern
Florida. They found distinct differences among individu-
als sampled from similar inshore habitat types separated
by small (3-5 km) open water distances, indicating that
individuals remained "resident" in specific portions of the
estuary at least for several weeks. Noting a similar study
in coastal Louisiana, Fry et al. (2003) suggested that
386
Fishery Bulletin 102(2)
small juvenile brown shrimp (Farfantepenaeus aztecus)
are more transient in suboptimal habitat (open bays and
deeper channels) and exhibit less movement upon reach-
ing optimal habitat (ponds and shallow channels).
The only study with which we can directly compare our
findings on residence time and movements was conducted
by Knudsen et al. (1996) near Calcasieu Lake, Louisiana,
where tidal flux was considerably lower (mean tide range
<0.6 m) and the system (marsh impoundments) was less
open than that in the present study. Knudsen et al. (1996)
marked batches of juvenile white shrimp (45-69 mm TL)
by injection of colored pigments and released them into a
pair of 35-ha. impoundments, each connected to the open
estuary through a narrow channel that was fitted with
screen deflectors and traps designed to collect all emigrat-
ing nekton. The mean time from release to emigration of
juvenile white shrimp ranged from 30.2 to 59.9 days. Our
estimates of tidal creek residence time for juvenile shrimp
in Georgia tidal creeks was about half that reported for
impoundments in Louisiana and may be explained by the
differences in tidal flux and openness between the two
systems. However, the values we observed were likely
underestimates of the actual residence period of survivors
within the creeks because they included losses due to mor-
tality as well as emigration.
It seems clear from the studies conducted thus far that
juvenile penaeids, once having entered the estuarine
nursery, tend to remain within a limited spatial range
where they are exposed to local conditions for several
weeks. Our findings also provide evidence of spatial
variation for both residence time and growth rate of ju-
venile white shrimp that is possibly attributable to struc-
tural differences in tidal creek subsystems. We suggest
there may be an optimal value for the ratio of subtidal to
intertidal drainage area within marsh creek systems that
can achieve a favorable balance between suitable habitat
(space) at low tide, which tends to enhance residence time
and density of juvenile shrimp, while providing sufficient
intertidal foraging habitat and predator refugia at high
tide to promote high rates of juvenile shrimp growth and
survival. Spatially explicit information on growth rates
and the extent to which individual shrimp move within
their estuarine nurseries are necessary initial steps to-
ward meeting the challenge of maintaining quality nurs-
ery habitat for a sustainable shrimp fishery and satisfying
other demands associated with human development in
and around estuarine watersheds.
Acknowledgments
Several individuals provided field and laboratory assis-
tance for this project, but we especially thank K. Feeley,
J. Kneib, and J. Spicer for helping on a regular basis.
The primary source of funding was a National Estuarine
Research Reserve System Graduate Research Fellowship
to S. Webb (NA870R0284) (Estuarine Reserves Division,
Office of Ocean and Coastal Resource Management, NOS,
NOAA), and matching funds provided by the University
of Georgia Marine Institute. The Georgia Sea Grant Col-
lege Program contributed funds for the purchase of an
additional tag injector unit, which substantially improved
the effectiveness of the mark-recapture program. The con-
ceptual basis for this project was derived from research
conducted under a grant from the National Science Foun-
dation ( DEB-9629621 ), which also contributed supplemen-
tal student support.
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389
Does the California market squid
(Loligo opalescens) spawn naturally during
the day or at night? A note on the successful use
of ROVs to obtain basic fisheries biology data
John Forsythe
National Resource Center for Cephalopods
University of Texas Medical Branch at Galveston
301 University Blvd
Galveston, Texas 77555-1163
E-mail address: |ohn forsythetg' utmb.edu
Nuutti Kangas
Roger T. Hanlon
Marine Resources Center
Marine Biological Laboratory
Woods Hole, Massachusetts 02543
The California market squid iLoligo
opalescens Berry), also known as the
opalescent inshore squid ( FAO ), plays a
central role in the nearshore ecological
communities of the west coast of the
United States (Morejohn et al., 1978;
Hixon, 1983) and it is also a prime
focus of California fisheries, ranking
first in dollar value and tons landed
in recent years (Vojkovich, 1998). The
life span of this species is only 7-10
months after hatching, as ascertained
by aging statoliths ( Butler et al., 1999;
Jackson, 1994; Jackson and Domier,
2003) and mariculture trials (Yang, et
al., 1986). Thus, annual recruitment is
required to sustain the population. The
spawning season ranges from April to
November and spawning peaks from
May to June. In some years there can
be a smaller second peak in November.
In Monterey Bay, the squids are fished
directly on the egg beds, and the con-
sequences of this practice for conser-
vation and fisheries management are
unknown but of some concern (Hanlon,
1998). Beginning in April 2000, we
began a study of the in situ spawning
behavior of L. opalescens in the south-
ern Monterey Bay fishing area.
The prevailing thought is that the
majority of spawning activity takes
place at night because fishermen have
observed these squids mating under
their bright lights (which are used to
attract and capture squids) and be-
cause television documentaries have
revealed mating and spawning activ-
ity in large aggregations at night. The
scientific literature on reproductive
behavior is sparse. There are some cur-
sory observations of actively spawning
L. opalescens during diver surveys
of egg beds (McGowan, 1954; Fields,
1965; Hobson, 1965; Hurley, 1977).
Some daytime spawning has been
seen both in southern and northern
California but Fields ( 1965 ) and Hixon
(1983) suggested indirectly that most
spawning occurs at night. Shimek et
al. (1984) also suggested night spawn-
ing by L. opalescens in Canada. Other
loliginid squids whose natural behav-
ior has been studied in the field were
found to be daytime spawners (e.g., L.
pealeii, L. vulgaris reynaudii, Sepioteu-
this sepioidea; summarized in Hanlon
and Messenger, 1996).
To help resolve this issue, we con-
ducted three field expeditions (28
April-8 May 2000, 10-17 September
2000, and 16-21 August 2001) using
remotely operated vehicles (ROVs) de-
ployed either from the RV John Martin
(Moss Landing Marine Laboratory) or
the commercial squid FV Lady J. The
ROVs were tethered vehicles with on-
board video cameras and lights. Live
video signals were transmitted by
the tether to shipboard VCRs where
observational data were viewed and
recorded. For the first field trip, a
large S4 Phantom ROV was used; it
was outfitted with a video camera and
zoom lens with tilt capability, and the
video was recorded on Hi8 format video
decks. For the second and third trips,
a smaller S2 inspection-class Phantom
ROV on loan from the NOAA Sustain-
able Seas Expeditions was used; this
ROV had a customized fiber-optic teth-
er and the video data were recorded on
mini-digital video cassettes. Our goal
was to make ROV dives each day from
approximately dawn to dusk and to
make a few comparable all-night sur-
veys. A combination of adverse weather
conditions and technical problems with
the ROVs rarely allowed continuous
video observations. During dives, if
squids were encountered, we used
video to conduct focal animal samples
on females (which were paired) for as
long as squids were present, or as long
as we could keep track of the same
individuals. Unless absolutely neces-
sary to see the squids (for instance at
night or at depths greater than 30 m
in turbid daytime conditions), lights
were not used for video taping in an
effort to minimize their impact on
the mating squids. Squids acclimated
within minutes to the ROVs. After the
expeditions, the videotapes were stud-
ied and the behavioral and biological
data were quantified on a multimotion
playback VCR.
By "mating" we refer to the peculiar
mating behavior of this species that
is unique among loliginid squids. The
male firmly grasps the female from her
ventral side and holds her for minutes
or hours in a "copulatory embrace" in
a nearly vertical position. Both copula-
tion (i.e., transfer of spermatophores)
and deposition of egg capsules occur
in this posture. For example, as the
female exudes a new egg capsule, the
male and female lower themselves in
unison to the egg bed where the female
deposits the egg capsule in the sand.
We have reported elsewhere on egg-
Manuscript approved for publication
20 January 2004 by Scientific Editor.
Manuscript received 25 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:389-392 (2004).
390
Fishery Bulletin 102(2)
No Maling Squids
Mating Squids Present
29Apr00-,
30Apr00
n i May Uli
04May00
OSMayOO
OtSMayOO
07May00
•Wk
^mmm-M
Sunset
b mw?.
wmmmmr*
lOSepOO
12Sep00
USepOO
16SepOO
0000 0200 0400 0600 0800 1000 1200 1400
Time of day (h)
1600 1800 2000 2200 2400
Figure 1
A summary of 154 spawning groups of Lot igo opalescens showing the daily presence or
absence of mating squids on egg beds in Monterey Bay, California. The horizontal bars repre-
sent the time periods when a ROV was on the bottom searching for mating squids during three
different expeditions. Note three occasions in which operations were conducted continuously
through the day and night, and also that spawning ceased at dusk.
laying frequency (Hanlon et al., in press). Only very rarely
did we observe females laying eggs while unattended by a
male; in these cases the female was moribund and laying
her last few egg strands.
Results and discussion
We examined 28 hours of videotape recorded during 50
ROV dives over 18 days (divided into three expeditions).
Figure 1 illustrates the relative presence or absence of
mating Lo//go opalescens throughout 24-hour periods. The
large gaps in the daytime observation record were due to
ROV problems. Although observation times varied daily,
it is clear that normal mating and egg-laying behaviors
were exclusively observed during daylight hours (ca.
0800-1800 hours but with some seasonal variation) and
concluded near dusk. In all instances in Figure 1 where
egg-laying extended into the early evening, these mating
assemblages had formed during daylight hours and per-
sisted slightly past sunset and the number of participating
squids constantly decreased as sunset approached and
passed. Observations were made throughout the night
on three nights. Not only were no mating squids ever
encountered around the egg beds at night, but generally
no squids were encountered at all near the seabed, despite
large aggregations that were present higher in the water
column. Thus the 200-400 watt lights on the ROVs never
induced any artificial spawning behavior because there
were no squids present.
Figure 2 provides some quantification of Figure 1. This
graph is based on 154 spawning groups that were vid-
eotaped and includes all three trips as well as the three
"all night observations" illustrated in Figure 1. We were
studying discrete groups of squids to examine mating dy-
namics and thus were sometimes biased to smaller groups
of squids that could be kept in view. Overall, we observed
that squids were present in greatest numbers in mid to
late afternoon and absent during the night.
Our findings strongly indicate that the extensive egg
beds produced at depths of 20-60 m in southern Monterey
Bay (just beyond the kelp beds) are the result of daytime
aggregations of mating Loligo opalescens. These benthic
aggregations begin forming in the early morning hours
and tend to be larger in the afternoon. Reproductive ac-
tivity begins to wane toward sunset and comes to a near
halt at sunset. We could find no evidence that egg laying
occurs naturally during the night. All observations that
we are aware of (mainly television documentaries) have
occurred in the presence of artificial light sources near the
surface provided either by fishermen or cinematographers.
In the absence of artificial lighting, L. opalescens in South
Monterey Bay does not aggregate into mating and spawn-
ing groups at night. Thus, we conclude that all significant
egg deposition in the Monterey Bay fishery is the result of
daytime aggregations of squids.
NOTE Forsythe et al.: Spawning patterns of Loligo opa/escens
391
Two other ascribed characteristics of L.
opalescens spawning are mass aggregations
at the sea floor and subsequent die-offs after
squids have spawned. Mass aggregations can
be detected by standard fathometers used by
commercial fishermen, who report that mass
aggregations on the sea floor are rare in Mon-
terey Bay. During our ROV operations we en-
countered only one large aggregation, which
occurred on 21 August 2001. We estimated
from our video recordings that there were ap-
proximately 3000-4000 squid in a 50-m2 area
on the sea floor and that intermittent egg lay-
ing was occurring over an area of ca. 2000 m2
during a period of about 3 hours. Collectively,
then, we recorded 154 very small spawning
groups and one large spawning group. There
was no mass die-off during or after this large
spawning aggregation. Instead, we consis-
tently observed in all spawning groups that
females actively broke the embrace of the
paired male and jetted strongly upwards away
from the spawning groups and rejoined large
schools in the upper water column. Thus,
squids that dispersed from the egg beds were
consistently in excellent condition — certainly
not senescent or moribund. These observa-
tions corroborate the results of other studies on loliginid
squids that spawn intermittently (Moltschaniwskyj,
1995; Maxwell and Hanlon, 2000 ). Twice we encountered
large numbers of dead squids on the sea floor in the early
morning, but in both instances the squid fishing fleet
had been working in the same area the night before and
it appeared as though these mortalities were associated
with the purse-seine fishery; there were few eggs in those
localities. McGowan ( 1954 ), Hobson ( 1965 ), and Cousteau
and Diole (1973) reported that squids died after spawn-
ing in S. California. Various Loligo spp. are noted for
flexible reproductive strategies (cf. Hanlon and Messen-
ger, 1996) so it should not be surprising if L. opalescens
occasionally engaged in large reproductive events. Our
data suggest that small groups of squids (20-200 indi-
viduals) generally descend during the day and lay eggs
for several hours before rejoining squids in the water
column. We encourage other researchers to use ROVs or
SCUBA without lights and with stealthy approaches to
determine the natural diurnal spawning of L. opalescens
throughout its range. Given our findings that active sex-
ual selection processes are occurring during the day and
that there is vertical migration between the large schools
of squid in the water column and the small spawning
groups at the substrate, it would be prudent, at the very
least, to restrict daytime fishing directly over egg beds
or to create protected spawning areas in southern Mon-
terey Bay. This strategy would allow the complex mating
system of L. opalescens to be played out without direct
disruption by fishing activity. In such a short-lived spe-
cies, annual recruitment to the population is necessary;
thus sufficient eggs must be laid for each new generation
to ensure a viable living resource.
30 -
n = 1 54 groups
25
-
CO
Q.
=J
o
oi 20
-
en
c
"c
I 15
■
■
Q.
(fi
O
_■
5 10
ll
E
3
■
z
-
5
1
III
III!
o
"'
III
1
Illl
0000 02O0 0400 0600 0800 1000 1200 1400 1600 1800 2000 2200 2400
Time of day (h)
Figure 2
The number of squid spawning groups at the egg beds at different times
of day (data pooled from three expeditions over 2 years; n= 154 groups).
A group is denned as a group of two or more mating pairs. These data
correspond hour by hour with data in Figure 1.
Acknowledgments
We are most grateful for funding on NOAA grant UAF 98
0037 from the National Undersea Research Center (West
Coast). Additional funding was provided by the David and
Lucile Packard Foundation and the Sholley Foundation.
J. Forsythe gratefully acknowledges financial support for
travel from the National Institutes of Health, National
Center for Research Resources (grant P40 RR0102423-
23), and the Marine Medicine General Budget account of
the Marine Biomedical Institute. N. Kangas gratefully
acknowledges financial support from the Academy of
Finland. We thank Sylvia Earle for loan of the Sustain-
able Seas ROV and we appreciate the professional efforts
of Deep Ocean Exploration and Research (DOER) who
supported the ROV operations. We especially thank John
Rummel who helped begin this project, and Brett Hobson
who kept it going at a critical juncture. We are thankful for
expert shipboard assistance from the captains and crew of
the KVJohn Martin and the FV Lady J (especially Captain
Tom Noto). We benefitted from discussions with Bob Leos,
Bill Gilly, Annette Henry, John Butler, Teirney Thies, and
Sue Houghton.
Literature cited
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392
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Jackson, G. D.. and M. L. Domeier.
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event on the size and growth of the squid Loiigo opalescens
off Southern California. Mar. Biol. 142:925-935.
Maxwell, M. R., and R. T. Hanlon.
2000. Female reproductive output in the squid Loiigo pea-
leii: multiple egg clutches and implications for a spawning
strategy. Mar. Ecol. Prog. Ser. 199:159-170.
McGowan, J. A.
1954. Observations on the sexual behavior and spawning
of the squid, Loiigo opalescens, at LaJolla, CA. Cal. Fish
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Moltschaniwskyj, N. A.
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124:127-135.
Morejohn, G. V., J. T. Harvey, and L. T.Krasnow.
1978. The importance of Loiigo opalescens in the food web
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Biological, oceanographic, and acoustic aspects of the
market squid, Loiigo opalescens Berry (C. W. Recksiek
and H. W . Frey, eds.), p. 67-98. Calif. Dep. Fish Game
Fish Bull. 169.
Shimek, R. L., D. Fyfe. L. Ramsey, A. Bergey, J. Elliott,
and S. Guy.
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393
Incidental capture of loggerhead (Caretta caretta)
and leatherback (Dermochelys coriacea)
sea turtles by the pelagic longline fishery
off southern Brazil
Jorge E. Kotas
IBAMA/Acordo Projeto TAMAR-
Instituto de Pesca/CPPM
Programa REVIZEE-SCORE SUL
Rodovia Osvaldo Reis 345 apt. 22 C
Itajaf-SC 88306-001. Brazil
Silvio dos Santos
DTI-CNPq
Programa REVIZEE-SCORE SUL
Rua Ezio Testlni 320
Santos-SP 11089-210, Brazil
Berenice M. G. Gallo
Fundacao Pro-TAMAR
Rua Antonio Athanasio 273
Ubatuba-SP 11680-000, Brazil
Paulo C. R. Barata
Fundacao Oswaldo Cruz
Rua Leopoldo Bulhoes 1480 - 8A
Rio de Janeiro - RJ 21041-210, Brazil
E-mail address (for P. C. R. Barata, contact author):
pbarataigialternex.com.br
back sea turtles by the surface longline
fishery operating off the southern coast
of Brazil, within Brazil's 200 mile
exclusive economic zone (EEZ) and
in international waters, and present
catch-per-unit-of-effort (CPUE) data
and estimates of average probability
of death at capture for these species.
Preliminary results of incidental cap-
tures of sea turtles by longliners dur-
ing one longline trip in this area were
presented by Barata et al.2 In the
present study we provide more detailed
data from additional trips, including
information concerning leatherback
sea turtles, as well as analyses of these
data. To our knowledge, this is the first
detailed report about the incidental
capture of sea turtles by the Brazilian
commercial longline fleet.
Venancio G. de Azevedo
DTI-CNPq
Programa REVIZEE-SCORE SUL
Av. Pavao 1 64
Caraguatatuba-SP 11676-520, Brazil
Incidental capture in fishing gear is
one of the main sources of injury and
mortality of juvenile and adult sea
turtles (NRC, 1990; Lutcavage et al.,
1997; Oravetz, 1999). Six out of the
seven extant species of sea turtles — the
leatherback (Dermochelys coriacea),
the green turtle (Chelonia mydas),
the loggerhead (Caretta caretta), the
hawksbill (Eretmochelys imbricata),
the olive ridley (Lepidochelys olivacea).
and the Kemp's ridley (Lepidochelys
kempii) — are currently classified as
endangered or critically endangered by
the World Conservation Union (IUCN,
formerly the International Union for
Conservation of Nature and Natural
Resources), which makes the assess-
ment and reduction of incidental cap-
ture and mortality of these species in
fisheries priority conservation issues
(IUCN/Species Survival Commission,
1995).
Several studies have examined sea
turtle bycatch by pelagic longline fish-
eries, especially in the North Atlantic
and Pacific oceans (NRC, 1990; Nish-
emura and Nakahigashi, 1990; Tobias,
1991; Bolten et al., 1996; Williams et
al., 1996; Lutcavage et al., 1997), but
little is known about sea turtle bycatch
in the South Atlantic. One of the most
detailed reports on longline incidental
captures in that area is that by Acha-
val et al. (2000), which documents the
incidental capture of loggerhead and
leatherback sea turtles in the south-
western Atlantic by longliners target-
ing swordfish (Xiphias gladius), tuna
(Thunnus obesus), and other related
species. Additional references, some-
times with scant detail, can be found in
Weidner and Arocha ( 1999 ), Fallabrino
et al. (2000), and Domingo et al.1
In this study, we report the inciden-
tal capture of loggerhead and leather-
1 Domingo, A.. A. Fallabrino, R. Forselledo,
and V. Quirici. 2002. Incidental cap-
ture of loggerhead (Caretta caretta) and
leatherback (Dermochelys coriacea) sea
turtles in the Uruguayan long-line fish-
ery in Southwest Atlantic. Presented
at the 22nd Annual Symposium on Sea
Turtle Biologv and Conservation, Miami,
USA, 4-7 April 2002. [Available from A.
Domingo: Direccidn Nacional de Recur-
sos Acuaticos, Constituyente 1497, C.R
11.200, Montevideo, Uruguay.]
Materials and methods
Observations were carried out by three
of the authors (JEK. SS, and VGA)
during three trips aboard Brazil-
flagged commercial longline vessels
based in Itajai, State of Santa Cata-
rina, southern Brazil (Fig. 1). The
trips occurred in 1998, the first (10
sets) between 13 March and 12 April
(summer-fall), the second (13 sets)
between 15 June and 5 July (fall-
winter I, and the third (11 sets (between
28 September and 13 October (spring),
and took place between latitudes
27°30'S and 34°30'S and longitudes
36°00'W and 52°00'W (Fig. 1). The
Barata, P. C. R., B. M. G. Gallo, S. dos
Santos, V. G. Azevedo, and J. E. Kotas.
1998. Captura acidental da tartaruga
marinha Caretta caretta (Linnaeus, 1758)
na pesca de espinhel de superficie na ZEE
brasileira e em aguas internacionais. In
Resumos Expandidos da XI Semana
Nacional de Oceanografia, Rio Grande,
RS, outubro de 1998, p. 579-581. Edi-
tora Universitaria-UFPel, Pelotas, RS,
Brazil. [Available from FURG, Oceano-
logia. Av. Italia, km 8, Campus Carreiros,
C.P 474, Rio Grande, RS 96201-900,
Brazil.!
Manuscript approved for publication
22 December 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:393-399(2004).
394
Fishery Bulletin 102(2)
t — i — i — i — i — i — vr—r
Atlantic Ocean
J.
10 N
40 -
50 S -
Ascension
St. Helena
Tristan da Cunha
South Georgia
N
t
j i i i i i i i i
80 W
20
10
10
20 E
Figure 1
Fishing locations. Numbers 1, 2, and 3 indicate locations of the first, second, and third
longline trips respectively; for each location, one or more sets were performed. Circled
numbers indicate international waters outside the 200-mile Brazilian exclusive economic
zone. The rectangular ocean area is limited by latitudes 25°S and 35°S and longitude 35°W.
The fishing location farthest to the east is about 1320 km (713 nautical miles) from Itajai,
State of Santa Catarina, Brazil, the home port of the fishing vessels.
seabed in this area ranged from the continental shelf
border to abyssal plains, including submarine elevations
(e.g., Rio Grande). Operation depths, ranging from 170 to
4000 m, were obtained from nautical charts.
The first and second trips were aboard the Yamaya III,
a 20.7-m, 325-hp engine, 30-t hold capacity, 10-crew long-
liner, and the third trip was aboard the Basco, a 24.4-m,
330-hp engine, 70-t hold capacity, 11-crew longliner.
The vessels targeted swordfishes, sharks (mainly blue
sharks, Prionace glauca) and tunas (Thunnus albacares,
T. alalunga and T. obesus). Their fishing gear was the
U.S. -style monofilament nylon longline, with 200-
300 m sections between buoys, and each section contained
four to five gangions set 40-60 m apart. Buoy dropper
length ranged between 10 and 20 m, and gangion length
ranged between 13 and 20 m. Each non-offset "J" hook
(Swordfish 9/0) was baited with Argentine shortfin squid
(Illex argentinus) and had a yellow chemical light stick
hung over it. The average number of hooks per set was
1030, 992, and 950 on the first, second, and third trips,
respectively.
On the first and second trips, the mainline was set off the
stern by means of a line shooter so that a marked catenary
was formed between buoys, allowing the hooks to operate
at a greater depth. In this case, the maximum hook depth
may have reached more than 40 m. On the third trip, the
vessel Basco did not use a line shooter, and thus the hook
depth for that trip may have been shallower. The longline
gear was set around 5:30 PM, and was retrieved early in
the morning. The average soak time was 7 h 30 min. For
each set, the date, time, geographical position, number of
hooks, and sea surface temperature were recorded. The
species and condition (i.e., if the animal was alive or dead)
of captured turtles were recorded; specimens with no ap-
parent movement were considered dead.
Incidentally captured loggerhead turtles were taken
aboard and hooks and lines were then removed. Whenever
possible curved carapace length (CCL) and width were
measured, and the turtles were double tagged (inconel
tags style 681, National Band and Tag Co., Newport,
KY), according to Projeto TAMAR's (Projeto Tartaruga
Marinha, the Brazilian sea turtle conservation program)
standard methods (Marcovaldi and Laurent, 1996). In
some cases, it was not possible to bring loggerhead sea
turtles on board the fishing vessel and, because of their
great size, no leatherback sea turtles were brought on
board. On these occasions, the turtles were pulled close to
the boat and the gangions were then cut to free the turtles
with the hooks still attached to them; however the length
of the line remaining on the turtle was not recorded. None
of these turtles was measured or tagged, although some of
the leatherback sea turtles were filmed on video. No addi-
tional data and measurements, other than those presented
in this study, were obtained.
NOTE Kotas et al.: Incidental capture of Caretta caretta and Dermochelys coriacea by the pelagic longline fishery
395
Table 1
Data referring to fishing practices, sea surface temperature CO, and capture of loggerhead and leatherback sea turtles.
CPUE = catch-per-unit-of-effort (number of captured turtles/1000 hooks).
by trip.
Trip
Date
No. of
sets
Average
hooks/set
Average
sea surface
temperature
Loggerheads
Leatherbacks
Alive
(tagged)
Dead
Condition
not recorded
CPUE
Condition
Alive Dead not recorded
CPUE
1
13 Mar 98-
12 Apr 98
10
1030
13.6
84(17)
15
9
10.49
1 —
0.10
2
15 Jun 98-
5 Jul 98
13
992
21.4
28(12)
4
2.48
13 1
1.09
3
28 Sep 98-
13 Oct 98
11
950
18.9
5(5)
_
_
0.48
5
0.48
Total
34
990
117(34)
19
9
4.31
19 1 —
0.59
CPUE (number of captured turtles/1000 hooks) was
calculated separately for each species. Straight carapace
lengths in published data were converted to CCL by us-
ing the formula in Teas (1993) to compare the CCL of
captured loggerhead sea turtles to carapace length data
found in the literature. To assess the significance of the
difference in the proportion of dead loggerhead or leath-
erback sea turtles among trips, exact tests were applied,
because ordinary chi-square tests are not reliable when
expected cell frequencies are too small. The test statistics
were x2 = ^[(Observed - Expected )'2IExpected] , and exact
probabilities were computed for all tables with marginal
frequencies fixed at the observed values (Lindgren, 1993,
p. 376). These probability calculations were performed by
a Turbo Pascal vers. 7 program (Borland International.
Scotts Valley, CA). The confidence interval for overall prob-
ability of death at capture was calculated by the method in
Zar ( 1996, p. 524 ). Ordinary chi-square tests and analysis
of variance (ANOVA) tests followed Zar (1996) and were
carried out with the software Systat vers. 9 (SPSS Inc.,
Chicago, IL). In the statistical tests, type-I error a was
equal to 0.05. In the construction of Figure 2, to avoid
overlapping of data points, the temperatures (but not the
CPUEs) were jittered, that is, a small amount of uniform
random noise was added to the temperature measure-
ments (Cleveland, 1993).
Results
From a total of 34 sets and 33,650 hooks, 145 logger-
head (CPUE = 4. 31/1000 hooks) and 20 leatherback
(CPUE = 0. 59/1000 hooks) sea turtles were captured.
There was a significant difference in loggerhead CPUE
among the trips (chi-square test, x2=137.3, P<0.001), but
the proportion of dead loggerhead sea turtles was not sig-
nificantly different among the trips (exact test, P= 0.656).
The average probability of death at capture for loggerhead
sea turtles for the three trips was 0.140 (95% confidence
interval= [0.086, 0.210]). For leatherback sea turtles, the
Table 2
Curved carapace length (CCL, cm) for loggerhead sea
turtles, by trip.
Sample
Average
Standard
Trip size
CCL
deviation
Minimum
Maximum
1 19
56.9
7.3
46.0
70.0
2 30
57.2
7.5
46.0
68.0
3 5
67.0
5.9
58.0
73.0
Total 54
58.0
7.7
46.0
73.0
difference in CPUE among the trips was significant (chi-
square test, x2=9.76, P<0.01), and the proportion of dead
leatherback sea turtles was not significantly different
among the trips (exact test, P=1.000). The average prob-
ability of death at capture for leatherback sea turtles for
the three trips was 0.050 ( 95r>i confidence interval= [0.001,
0.249]).
The average sea surface temperature (Table 1) was
significantly different among the trips (ANOVA, ;? = 34.
F=55.37, P<0.001). The average temperature on the first
trip was significantly lower than those on the second and
third trips, and the average temperature on the second
trip was significantly higher than that on the third trip
(Tukey's post hoc test). For loggerhead sea turtles, CPUEs
were generally higher on the first trip, which had the
lowest average temperature (Fig. 2). For leatherback sea
turtles, on the contrary, the lowest CPUEs were found on
the first trip, on which only one leatherback sea turtle was
captured (Table 1).
CCLs of captured loggerheads were in the range of
46-73 cm. Detailed loggerhead CCL data are presented in
Table 2. There was a significant difference in average log-
gerhead CCL among the trips (Table 2); the average CCL
on the third trip was greater than those on the first and
second trips (ANOVA, n = 54, F=4.209, P=0.020, Tukey's
396
Fishery Bulletin 102(2)
D
a.
O
25
20
5 -
Caretta
O
O
o
— r-
— l—
15
— r~
25
Temperature (:C)
Figure 2
CPUE (number of captured turtles/1000 hooks I by sea surface temperature (°C) in
each set, by species. Circles = first trip, triangles = second trip, stars = third trip. In
each graph, the dashed vertical line, arbitrarily placed at 16.7 °C, marks a separation
between the temperatures in the first trip and those in the second and third trips
(except for one set in the first trip). Note that the two graphs have different vertical
scales, and that, in the construction of this figure, temperature measurements (but
not the CPUEsl have been jittered (see "Materials and methods" section i.
post hoc test). Although leatherback sea turtles could not
be hauled aboard for measurements, on board observa-
tions and video recordings indicated that they were sub-
adult or adult animals.
Most of the loggerhead turtles were hooked through
their mouths or esophagus, but a small number were
hooked through their flippers or were found to be simply
entangled in the lines. Loggerhead sea turtles taken
aboard had their hooks removed, sometimes in a care-
less way that caused severe injury, and they were then
returned to the sea. Leatherback sea turtles were found
entangled in the lines or hooked either through the flippers
or carapace or through the mouth. Because no leatherback
sea turtle was hauled aboard, we could not tell if any were
hooked in the esophagus.
Discussion
Achaval et al. (2000 ) reported data obtained from nine trips
aboard two different longline vessels operating within the
Uruguayan EEZ and in international waters in the South
Atlantic in different seasons of the year, and employing
different longline methods. Those authors reported that
28 loggerhead and 28 leatherback sea turtles were cap-
tured in 86 sets with 75.033 hooks in zones I and II, that
correspond approximately to the fishing area covered in
this study, yielding a CPUE of 0.37/1000 hooks for both
loggerhead and leatherback sea turtles. For loggerhead
sea turtles, there was a significant difference between our
CPUE (Table 1) and that of Achaval et al. (chi-square test,
X2=226.4, P<0.001 ); whereas for leatherback sea turtles no
significant difference was found i chi-square test, x2=1.97,
P=0.161).
Although the variations in CPUE observed in our study
could be explained by differences in temperatures (Fig. 2),
other physical, spatial, or temporal factors (or a combina-
tion of these factors) could be involved. The trips were car-
ried out at different times of the year (Table 1); the third
trip was more to the south and closer to the coast, and the
first trip had sets more to the east (Fig. 1).
Our estimates of sea turtle mortality at capture may
be lower than the actual mortality rates from longlines
because our estimates do not consider postrelease deaths
derived from 1) wounds caused by hooks removed from
turtles on board, 2) embedded hooks and lines, and 3)
stress caused by capture itself. Other researchers have
also recognized that, because of factors such as these,
there is great uncertainty in the estimates of mortality
levels for sea turtles captured in longline gear (Balazs and
Pooley, 1994; Eckert, 1994).
Captured loggerhead sea turtles were smaller (Table 2 1
than loggerhead sea turtles nesting in Brazil (minimum
CCL = 83.0 cm, average CCL= 103.0 cm, nesting season
1982-83 through nesting season 1999-2000; Projeto
TAMAR3) and in several places in the North Atlantic and
the Caribbean (minimum CCL=75.4 cm, average CCL in
the range of 94.0-105.1 cm; Dodd, 1988). However, logger-
head sea turtles nesting in Cape Verde, in the northeast-
ern Atlantic, are smaller than those nesting in those other
places: minimum CCL = 68.0 cm, average CCL=82.9 cm.
data from 1998 (Cejudo et al., 20001. There is an overlap
between the observed CCL range and that of adult Cape
Verde loggerhead sea turtles (seven loggerhead turtles
out of 54 observed, or 13.0'7f , had a CCL equal or greater
than the minimum Cape Verde CCL), but the average
CCL of the captured loggerhead sea turtles (Table 2 i was
well below that of loggerhead sea turtles nesting in Cape
Verde. We estimate that the captured loggerhead sea
turtles were generally juveniles, although a small number
of them could have been adult turtles. However, size is
3 Projeto TAMAR. 2000. Unpubl. data
Salvador, BA 40210-970, Brazil.
Caixa Postal 2219.
NOTE Kotas et al.: Incidental capture of Caretta caretta and Dermochelys conacea by the pelagic longline fishery
397
not a reliable indicator of maturity or breeding status for
sea turtles (Miller, 1997).
Along the southern coast of Brazil (between latitudes
23°S and 33°S), loggerhead sea turtles stranded or in-
cidentally captured in fishing gear with CCLs as small
as 32.5 cm have been observed (Projeto TAMAR4), but
usually loggerhead sea turtles found in that region have
CCLs greater than 50 cm, most commonly in the range of
60-90 cm (Pinedo et al., 1998; Bugoni et al., 2001; Projeto
TAMAR4 ). Loggerhead sea turtles have also been found in
Uruguay and Argentina (Frazier, 1984; Fallabrino et al.,
2000). Their CCLs in those countries have been reported
to be in the approximate range of 50-115 cm (Frazier,
1984). The loggerhead sea turtles reported here have
an average CCL smaller than that usually observed for
loggerhead sea turtles stranded or captured in southern
Brazil, Uruguay, and Argentina, although most of the
turtles (45 out of 54, or 83%) had CCLs equal to or greater
than 50 cm, that is, they were within the size range for
that region.
Cumulative evidence obtained from genetic and size-
distribution data around oceanic basins, as well as tag
returns, shows that the ontogenetic development of log-
gerhead sea turtles involves a pelagic juvenile stage (Carr,
1987; Musick and Limpus, 1997; Bolten et al., 1998). Trans-
oceanic developmental migrations establishing a link be-
tween juveniles in feeding grounds and hatchlings from
nesting beaches on opposite sides of the ocean basin have
been demonstrated through genetic analysis for the North
Atlantic and North Pacific (Bowenet al., 1995; Bolten et al.,
1998). It has been suggested that a similar pattern may be
expected for the South Atlantic (Bolten et al., 1998), where
loggerhead sea turtles nest in Brazil and possibly in Africa
(Marcovaldi and Laurent, 1996; Fretey, 2001). The inciden-
tal captures reported in our study, indicating the use of the
pelagic environment by juvenile loggerhead sea turtles in
the South Atlantic, support the hypothesis of transoceanic
developmental migrations for those turtles in that ocean.
Future genetic analysis of turtles incidentally captured in
the South Atlantic would help to clarify their natal origin.
For leatherback sea turtles, there are important nesting
grounds in the Atlantic, mainly in French Guiana and Su-
riname in South America, and Gabon and Congo in Africa
(Spotila et al., 1996; Fretey, 2001). Leatherback sea turtles
are known to travel long distances from their nesting
beaches into pelagic waters (Goff et al., 1994; Morreale et
al., 1996; Eckert and Sarti, 1997; Eckert, 1998). Satellite
telemetry data indicate that leatherback sea turtles nest-
ing in eastern South Africa can enter the South Atlantic
(Hughes et al., 1998; Hughes5). In the southwestern Atlan-
tic, leatherback sea turtles have been observed or captured
in Brazil, Uruguay, and Argentina (Frazier, 1984; Pinedo
et al., 1998; Achaval et al., 2000; Fallabrino et al., 2000;
Bugoni etal., 2001).
Some measure of the significance of the three trips re-
ported in the present study in terms of the potential for
turtle capture and mortality in the South Atlantic longline
fishery can be obtained by looking at information concern-
ing the total fishing effort in the study area. In 1999, the
Brazilian longline fleet consisted of 70 longliners (42 Bra-
zilian and 28 leased foreign vessels); among them, 33 ves-
sels were operating out of ports in southern Brazil, in the
states of Sao Paulo, Santa Catarina, and Rio Grande do
Sul. In that year, the total number of hooks of that long-
line fleet (both Brazilian and leased vessels) amounted to
13,598,260 hooks (ICCAT6). However, the southwestern
Atlantic is fished not only by Brazil-based longliners, but
also by longliners from Uruguay, Chile, Japan, Taiwan, and
Spain (Folsom, 1997; Weidner and Arocha, 1999; Weidner
et al., 1999). According to ICCAT's (International Commis-
sion for the Conservation of Atlantic Tunas) CATDIS data
set (ICCAT)7 longliners operating during 1995-97 in the
area delineated by the present study (latitudes 25°S and
35°S and longitude 35°W, or eight ICCAT 5x5° statistical
blocks. Fig. 1) had an average annual catch of tunas and
swordfishes of 6885 metric tons (t) (the total hold capacity
of the vessels on the three trips reported in this study was
130 t). However, due to unreported landings by vessels
flying flags of convenience (FAO, 2001; FAO8) and other
sources, the estimate obtained from ICCAT data should be
considered a minimum estimate of the total annual tuna
and swordfish catch ( ICCAT9 ). Furthermore, because North
Atlantic stocks of swordfishes and some species of tuna are
considered overfished (NMFS10), quota or closure regula-
tions (or both) in the North Atlantic may be driving longline
fleets to the South Atlantic, increasing the risk of incidental
capture of sea turtles there.
In Brazil, sea turtle capture is prohibited by federal
legislation (Marcovaldi and Marcovaldi, 1999), and mea-
sures have been taken to address the problem of inci-
dental capture by longlines and other kinds of fishing
4 Projeto TAMAR. 2000. Unpubl. data. Rua Antonio
Athanasio 273, Ubatuba, SP 11680-000, Brazil.
5 Hughes, G. R. 2002. Personal commun. Ezemvelo KZN
Wildlife, P O Box 13053, Cascades 3202, South Africa.
6 ICCAT (International Commission for the Conservation of
Atlantic Tunas). 2001. National report of Brazil. Report
for biennial period, 2000-2001, part I (2000), vol. 1, English
version, p. 312-315. Calle Corazon de Maria, 8, 28002
Madrid, Spain.
7 ICCAT (International Commission for the Conservation of
Atlantic Tunas). 2002. CATDIS dataset. Calle Corazon de
Maria, 8, 28002 Madrid, Spain. (Available from http://www.
iccat.org.]
s FAO (Food and Agriculture Organization of the United
Nations). 2001. International plan of action to prevent,
deter and eliminate illegal, unreported and unregulated fish-
ing, 24 p. FAO, Rome. (Available from http://www.fao.org/
docrep/003/yl224e/yl224e00.htm.]
9 ICCAT (International Commission for the Conservation of
Atlantic Tunas). 1999. Detailed report for swordfish,
ICCAT SCRS swordfish stock assessment session (Madrid,
Spain, September 27 to October 4, 1999), 176 p. Calle
Corazon de Maria, 8, 28002 Madrid. Spain.
10 NMFS (National Marine Fisheries Service). 2000. 2000
stock assessment and fishery evaluation for Atlantic highly
migratory species, 150 p. U.S. Dep. Commer., NOAA, NMFS.
Highly Migratory Species Management Division, 1315 East-
West Highway, Silver Spring, MD 20910.
398
Fishery Bulletin 102(2)
gear. Since 2001, Projeto TAMAR has been developing and
implementing (through partnerships with other institu-
tions) an action plan whose main objective is to reduce
incidental sea turtle capture, including captures occurring
in the open sea (Marcovaldi et al., 2002). The action plan
includes, among other things, an assessment of fishery-
related sea turtle mortality, the development of mitigation
methods, and a proposal of adequate conservation and
enforcement policies (Marcovaldi et al., 2002). However,
because the longline fleet is composed of vessels from many
nations, the reduction of incidental capture in the open sea
calls for international cooperation ( Eckert and Sarti, 1997;
Trono and Salm, 1999; Crowder, 2000).
The observations reported in this study and the pres-
ence of a sizable longline fleet operating in the southwest-
ern Atlantic indicate 1) the need for research to clarify
habitat use by sea turtles in that part of the ocean (Eckert
and Sarti, 1997; Bolten et al., 1998), 2) the need for contin-
ued research to quantify the impact of longline fishing on
sea turtles in the pelagic realm of that ocean (Balazs and
Pooley, 1994; Eckert, 1994), and 3) the implementation of
conservation measures for sea turtles in that environment.
We suggest the implementation of an International Ob-
servers Program on board longliners operating throughout
the South Atlantic ocean.
Acknowledgments
This note is the result of observations made possible
through an agreement between the REVIZEE Program
(National Program for the Assessment of the Sustain-
able Fishing Potential of the Exclusive Economic Zone
Live Resources, a Brazilian Government program) and
Projeto TAMAR's station at Ubatuba, State of Sao Paulo.
We would like to thank Jose Kowalsky of the Kowalsky
fishing company and Marcelino Talavera (Itajai, State of
Santa Catarina), owners of the vessels Yamaya III and
Basco, respectively, for kindly allowing access to the fish-
ing vessels, and the crew of the two longliners, and also
the fishing research center Centro de Pesquisa e Extensao
Pesqueira do Sudeste-Sul-CEPSUL/IBAMA ( Itajai, State
of Santa Catarina), and particularly Jorge Almeida de
Albuquerque, for making this research possible. We also
thank Larisa Avens and Matthew Godfrey for their gener-
ous reviews of the paper, and the two anonymous referees,
whose suggestions helped to improve our work. Projeto
TAMAR is affiliated with IBAMA (the Brazilian Institute
for the Environment and Renewable Natural Resources),
is co-managed by Fundacao Pro-TAMAR, and officially
sponsored by Petrobras. In Ubatuba. TAMAR is supported
by Ubatuba's municipal government ( Prefeitura Municipal
de Ubatuba). S.S. and V.G.A. were supported by CNPq
(Brazilian National Research Council).
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400
Diet changes of Pacific cod
(Gadus macrocephalus) in Pavlof Bay
associated with climate changes
in the Gulf of Alaska between 1980 and 1995
Mei-Sun Yang
Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
7600 Sand Point Way NE
Seattle. Washington 98115
E mail address mei-sunyangffinoaa gov
The diet of Pacific cod (Gadus mac-
rocephalus) in the area of Pavlof Bay,
Alaska, was studied in the early 1980s
by Albers and Anderson (1985). They
found that the dominant prey spe-
cies were forage species like pandalid
shrimp, capelin iMallotus villosus),
and walleye pollock [Theragra chal-
cogramma). The shrimp fishery in
Pavlof Bay began in 1968 and closed
in 1980 because of low shrimp abun-
dance (Ruccio and Worton1). Survey
data indicate that, during the period
between 1972 and 1997, the abun-
dance of forage species such as pan-
dalid shrimp and capelin declined
and higher trophic-level groundfish
such as Pacific cod increased. There
is a general recognition that a long-
term ocean climate shift in the Gulf of
Alaska has been partially responsible
for the observed reorganization of the
community structure (Anderson and
Piatt, 1999).
Because there has been an appar-
ent shift in the abundance of both
predators and prey in Pavlof Bay, it is
important to understand how trophic
relationships may also have changed.
1 Ruccio, M. P.. and C. L. Worton. 1999.
Annual management report for the shell-
fish fisheries of the Alaska peninsula
area, 1998. In Annual management
report for the shellfish fisheries of the
westward region. 1998. Regional Infor-
mation Report 4K99-49, 312 p. Alaska
Department of Fish and Game, Division of
Commercial Fisheries, 211 Mission Road,
Kodiak, Alaska 99615.
In order to partially address this ques-
tion, stomach samples of Pacific cod
and other groundfishes were taken in
1995. By performing a comparison of
the diet of Pacific cod right after the
climate shift with Pacific cod and other
groundfishes well after the shift, this
analysis may demonstrate how the
relative abundance of prey in the Gulf
of Alaska may have changed.
Methods
Stomachs of Pacific cod, walleye pol-
lock, and arrowtooth flounder (Atheres-
thes stomias) were collected by National
Marine Fisheries Service (NMFS) sci-
entists on board the chartered vessel
FV Arcturus conducting a trawl survey
in Pavlof Bay, Alaska. (Fig. 1) from 5
August to 7 August 1995. The survey
targeted shrimp and used a high-
opening net with small mesh (32-mm
stretched mesh). Each tow was about
1.2 km in length. The average depth of
the 13 hauls where stomachs were col-
lected was 108.9 (±9.5) m with a range
from 90 to 123 m. When a sampled
stomach was retained, it was put in a
cloth stomach bag. A field tag with the
species name, fork length (FL in cm) of
the fish, and haul data (vessel, cruise,
haul number, specimen number) was
also put in the bag. All the samples col-
lected were then preserved in buckets
containing a 10% formalin solution.
When the samples arrived at the labo-
ratory, they were transferred into 70%
ethanol before the stomach contents
were analyzed. In the laboratory, the
stomach was cut open, the contents
were removed and blotted with a paper
towel. Wet weight was then recorded to
the nearest 0.1 g. After obtaining the
total weight for a stomach's contents,
the contents were placed in a Petri dish
and examined under a microscope.
Each prey item was classified to the
lowest practical taxonomic level. Prey
weights and numbers of commercially
important fish were recorded. Stan-
dard lengths of prey fish and carapace
width of crabs were also recorded. The
diet of Pacific cod was summarized to
show the percent frequency of occur-
rence, the percentage by number, and
the percentage of the total weight of
each prey item found in the stomachs.
Stomach contents of walleye pollock
and arrowtooth flounder were ana-
lyzed for comparisons.
Results
Of 130 Pacific cod stomachs analyzed.
129 contained food. Pacific cod sizes
ranged from 40 to 80 cm FL (fork
length); a mean size was 55.4 (SD
±7.2) cm.
Polychaetes, crangonid shrimp, pea
crab, and clams were the most fre-
quently found prey items in Pacific cod
stomachs (Table 1). However, in terms
of weight, eelpouts (zoarcids). Tanner
crab (Chionoecetes bairdi), crangonid
shrimp, hermit crab, and polychaetes
were the most important prey of Pa-
cific cod. Pandalid shrimp, spinyhead
sculpin (Dasycottus setiger), prickle-
backs (stichaeid). Pacific sandlance
(Ammodytes hexapterus), arrowtooth
flounder lAtheresthes stomias), and
flathead sole (Hippoglossoides elasso-
don ) were minor prey.
Invertebrates (mainly crangonid
shrimp, polychaetes, and crabs) were
the principal prey of Pacific cod smaller
than 60 cm (Fig. 2). There were nine
prey categories as shown in Figure 2.
The miscellaneous prey included Si-
puncula, Echiura. fish offal (processed
Manuscript approved for publication
2 I I Vcember 2003 by Scientific Editor.
Manuscript received 20 January 2004
at NMFS Scientific Publications Office.
Fish. Bull. 102:400-405(2004).
NOTE Yang: Diet changes of Gadus macrocephalus associated with climate changes in Pavlof Bay
401
Figure 1
Location of study area in 1980, 1981, and 1995.
100
fish parts like head, tail, pyloric caeca,
etc.), and all other prey organisms not
included in the other eight prey catego-
ries. The importance of fish in the diet
of Pacific cod increased after 60 cm FL.
Walleye pollock were consumed only by
Pacific cod >60 cm FL.
In general, Pacific cod ate prey of small
individual size (Table 2). Tanner crabs
iChionoecetes bairdi) ranged from 4.5
to 42.3 mm carapace width. Eelpouts
ranged in length from 36.2 to 256.6 mm
standard length. Other fish prey ranged
in length from 32.7 to 81.5 mm. Walleye
pollock were consumed by Pacific cod but
were not measurable.
In 1995, when Pacific cod stomachs
were collected in Pavlof Bay, 218 wall-
eye pollock and 80 arrowtooth flounder
stomachs were also collected. Similar
to the results for Pacific cod, pandalid
shrimp and capelin were not important
food of walleye pollock and arrowtooth
flounder either (Fig. 3). These prey each
comprised less than 39c of the total
stomach content weight of walleye pol-
lock and arrowtooth flounder. Instead,
eelpouts, pricklebacks, euphausiids, and walleye pollock
were important food of arrowtooth flounder, and euph-
ausiids (83% by weight) were the main food of walleye
pollock.
N=26
40-49
□ Polychaete
□ Pollock
□ Misc. fish
□ Tanner crab
S Pagurid
□ Other crab
El Pandalid
O Crangonid
□ Misc. prey
50-59
Predator fork length (cm)
60-80
Figure 2
Variations in the main food items of Pacific cod, by predator size, in Pavlof
Bay in 1995. /i=sample size.
Discussion
This study shows that eelpouts
hermit crabs, polychaetes, and
, Tanner crabs, crangonids,
echiuroids were the princi-
402
Fishery Bulletin 102(2)
Table 1
Percent frequency of occurrence (%F), percentage by
number (7cN), and percentage by
weight C7rW) of prey
items of Pacific cod
collected in Pavlof Bay, Alaska, 1995.
Prey name
9c F
%N
%W
Polychaeta (worm)
79.8
11.4
9.2
Gastropoda (snail)
14.0
0.8
0.4
Bivalvia (clam)
55.0
6.1
2.1
Cephalopoda (squid and octopus)
10.1
0.5
2.1
Copepoda
0.8
0.0
0.0
Peracarida Mysidacea (mysid)
31.8
11.5
0.2
Cumacea (cumaceanl
13.2
0.9
0.0
Amphipoda (amphipod)
17.1
1.2
0.0
Euphausiacea leuphausiid)
15.5
10.0
0.7
Natantia (unidentified shrimp)
12.4
0.7
0.1
Caridea (shrimp)
12.4
1.2
1.2
Hippolytidae (shrimp)
17.8
1.2
0.2
Pandalidae (shrimp)
41.1
5.7
2.3
Crangonidae (shrimp)
76.0
18.9
13.3
Reptantia (unidentified crab)
11.6
0.5
1.9
Paguridae (hermit crab)
22.5
1.3
9.5
Decapoda Brachyura (crab)
0.8
0.0
0.1
Hyas sp. (lyre crab)
0.8
0.0
0.9
Hyas lyratus (lyre crab)
1.6
0.1
0.6
Chionoecetes sp. (snow and Tanner crab)
40.3
3.5
13.9
Pinnotheridae (pea crab)
1.6
0.1
0.1
Pinnixa sp. (pea crab)
68.2
8.4
3.2
Sipuncula I marine worm)
0.8
0.0
0.6
Echiura (marine worm)
24.0
1.4
6.6
Ophiuroidea (basket and brittle star)
9.3
0.7
0.1
Chaetognatha (arrow worm)
1.6
0.2
0.0
Rajidae (skate)
2.3
0.1
0.4
Osteichthyes Teleostei (fish)
12.4
1.1
0.6
Nongadoid fish remains
47.3
6.5
2.3
Gadidae (unidentified)
1.6
0.1
0.4
Theragra chalcogramma (walleye pollock)
2.3
0.1
1.4
Zoarcidae (eelpout)
16.3
0.9
14.0
Cottoidei (Sculpim
2.3
0.1
0.2
Dasycottus setiger (spinyhead sculpin)
0.8
0.0
0.2
Stichaeidae (prickleback)
8.5
1.5
0.6
Lumpenus sp. (prickleback)
0.8
0.0
0.0
Ammodytes hexapterus (Pacific sand lance)
0.8
0.0
0.0
Pleuronectidae (flatfish)
2.3
0.2
0.2
Atheresthes stomias (arrowtooth flounder)
1.6
0.1
0.0
Hippoglossoides elassodon (flathead sole)
3.9
0.2
0.5
Unidentified organic material
10.1
0.5
0.6
Unidentified worm-like organism
5.4
0.3
0.5
Fish offal (processed fish parts, e.g., head, tail)
0.8
0.0
8.1
Total prey weight
2715 g
Total stomachs
1.30
Total empty stomachs
1
NOTE Yang: Diet changes of Gadus macrocephalus associated with climate changes in Pavlof Bay
403
D Pacific cod
G Walleye pollock
■ Arrowtooth flounder
Main prey items
Figure 3
Percentage by weight of the main prey in the diet of Pacific cod (n=129), walleye pollock (n=
and arrowtooth flounder <h = 43) collected in Pavlof Bay in 1995.
216)
pal prey of Pacific cod collected in Pavlof Bay in 1995. This
is a large change in diet composition compared with that
observed 15 years earlier (Albers and Anderson, 1985).
In Albers and Anderson's (1985) study, pandalid shrimp,
capelin. and walleye pollock were the main prey of Pacific
cod (Fig. 4). The change in main prey from pelagic prey in
the 1980s to benthic prey in 1995 corresponds to changes
in species abundance trends in nearshore small-mesh
trawl surveys observed by Anderson and Piatt (1999). In
that study, they described that the community reorgani-
zation in the Gulf of Alaska was triggered by a shift in
ocean climate during the late 1970s. They showed that the
abundance of species such as pandalid shrimp and capelin
declined while the abundance of predators such as Pacific
cod, walleye pollock, and flatfish increased between 1972
and 1997.
The mean weight of pandalid shrimp consumed by Pa-
cific cod in 1995 was only 0.5 g/cod. In contrast, the mean
weights of undigested pink shrimp in Pacific cod stomachs
ranged between 4.5 g/cod and 24.4 g/cod during 1980 and
1981. This finding corroborates those of Anderson (2000)
and show that pandalid shrimp abundance continued to
decrease in the late 1990s and Pacific cod abundance con-
tinued to increase during that same period.
The diet of Pacific cod in the present study was also
compared with the diet of Pacific cod in the broader Gulf
of Alaska shelf area (Fig. 5) (Yang and Nelson, 2000). The
values of the percentage by weight of capelin in Pacific cod
stomachs in the Gulf of Alaska in 1990, 1993, and 1996
were similar (all were less than 3%) to that in Pavlof Bay
in 1995. However, pandalid shrimp were an important
Table 2
Mean standard length
or carapace width), standard devi-
ation, and the
size ran
ce of prey
consumed by Pacific cod
in Pavlof Bay 1995.
Mean
SD
Range
No. of
Prey name
i m m I
(mm)
(mm)
individuals
Tanner crab
22.1
10.5
4.5-42.3
70
Zoarcid
86.4
73.5
36.2-256.6
15
Cottid
48.2
9.4
41.8-59
3
Stichaeid
46.9
19.6
32.7-81.5
5
Pacific sand
44.8
0.0
44.8-44.8
1
lance
Arrowtooth
39.1
7.4
33.8-44.3
2
flounder
Flathead sole
58.2
14.4
47.5-80.4
4
food item of Pacific cod throughout the Gulf of Alaska,
comprising from 11% to 15% by weight of the total stom-
ach contents of Pacific cod in the Gulf of Alaska in 3 years
(1990, 1993, and 1996) (Yang and Nelson, 2000). These
values are higher than that in Pavlof Bay (2% by weight).
By comparing the depths of the sampling locations of the
Pacific cod, high percentages of pandalid shrimp were
found in the cod diet in deeper offshore areas of the Gulf
of Alaska in 1990, 1993, and 1996, whereas low percent-
ages of pandalid shrimp were found in cod diet in much
404
Fishery Bulletin 102(2)
shallower areas in the Pavlof Bay area <Fig. 6). From the
shrimp survey data, Anderson (2000) showed that pan-
dalid shrimp occupying inshore and shallower water (e.g.,
Pavlof Bay area) declined to near extinction (<0.1 kg/km)
from 1978 to 1982, while offshore and deepwater pandalid
DAug-80
■ May-81
QSep-81
■ Aug-95
Main prey items
Figure 4
Percentage by volume (for the values in 1980s) and the percentage by weight
(for the values in 1995) of the main prey items of Pacific cod collected in Pavlof
Bay. Alaska.
a
Main prey items
Figure 5
Percentage by weight of the main prey items in the diet of Pacific cod collected
in 1990 (GOA90), 1993 (GOA93), and 1996 (GOA96) in the Gulf of Alaska and
in 1995 (PAV95) in Pavlof Bav.
shrimp species maintained low population levels (>0.1
kg/km ). The data from this study corroborates Anderson's
(2000) results.
Anderson (2000) also reported that during the period
of the decline of pandalid shrimp in inshore waters of the
Gulf of Alaska, the abundance of some
pleuronectids, Pacific cod, and walleye
pollock increased. These species are
predators of pandalid shrimp (Yang
and Nelson, 2000). One hypothesis is
that predators keep pandalid shrimp
populations low. Albers and Anderson
(1985) suggested that cod predation
was one reason for the failure of the
pink shrimp stock to rebuild in Pavlof
Bay. In the Northwest Atlantic. Lilly
et al. (2000) showed that the large in-
crease in shrimp biomass seen in the
1990s was related to the collapse of cod
\Gctdus morhua) populations during the
late 1980s and 1990s in the northeast
Newfoundland shelf. The impact of cod
on Barents Sea shrimp (P. borealis)
was also reported by Berenboim et
al. (2000). They found that when cod
biomass is high, the shrimp frequency
of occurrence in cod stomachs declines;
there is a significant inverse correla-
tion between the abundance of cod and
shrimp.
Tanner crabs consumed by Pacific cod
in this study ranged from 5 to 42 mm
carapace width (CW). In general, the
size of Tanner crabs consumed in-
creases as Pacific cod size increases.
The size range of Tanner crabs con-
sumed by Pacific cod in this study is
similar to that (5-45 mm) found in
Pacific cod stomachs in Albers and An-
derson's ( 1985 ) study and is also similar
to that (1-40 mm) found in Hunter's
(1979) study near Kodiak Island.
Jewett's ( 1978 ) Pacific cod diet study
around Kodiak Island from 1973 to
1976 showed that Tanner crabs were
the most frequent (37%) prey of Pa-
cific cod; pandalid shrimp occurred in
8-10% of the stomachs examined from
1973 to 1975; and walleye pollock were
found in 49r of the stomachs examined.
The importance of Tanner crabs as food
of Pacific cod in Jewett's ( 1978 1 study is
coincident with our study.
This study suggests that there were
substantial differences between the
diets of Pacific cod in Pavlof Bay be-
tween the early 1980s and 1995. In
the 1980s, pandalid shrimp and cap-
elin were the main food of Pacific cod,
whereas benthic species (polychaetes,
NOTE Yang: Diet changes of Gadus macrocephalus associated with climate changes in Pavlof Bay
405
80
Figure 6
Pandalid shrimp consumed by Pacific cod sampled at different bottom depths (m) in
Pavlof Bay in 1995, and in the Gulf of Alaska in 1990, 1993, and 1996.
hermit crabs, Tanner crabs, and eelpouts) were the domi-
nant food in 1995. This change was probably due to the
climate shift from cold to warm in the Gulf of Alaska.
Acknowledgments
I would like to thank Paul Anderson, Troy Buckley, and
Patricia Livingston for reviewing the manuscript and for
their very helpful suggestions. I also want to thank the two
anonymous reviewers for their comments and suggestions.
Literature cited
Albers W. D., and P. J. Anderson.
1985. Diet of the Pacific cod. Gadus macrocephalus. and
predation on the northern pink shrimp, Pandalus borealis,
in Pavlof Bay, Alaska. Fish. Bull. 83:601-610.
Anderson, P. J .
2000. Pandalid shrimp as indicators of ecosystem regime
shift. J. Northw. Atl. Fish. Sci. 27:1-10.
Anderson, P. J„ and J. F. Piatt.
1999. Community reorganization in the Gulf of Alaska fol-
lowing ocean climate regime shift. Mar. Ecol. Prog. Ser.
189:117-123.
Berenboim, B. I., A. V. Dolgov, V. A. Korzhev, and N. A. Yaragina.
2000. The impact of cod on the dynamics of Barents Sea
shrimp (Pandalus borealis) as determined by multispecies
models. J. Northw. Atl. Fish. Sci. 27:69-75.
Hunter, M. A.
1979. Food resource partitioning among demersal fishes
in the vicinity of Kodiak Island, Alaska. M.S. thesis, 120
p. Univ. Washington, Seattle, WA.
Jewett, S. C.
1978. Summer food of the Pacific cod, Gadus macrocepha-
lus, near Kodiak Island, Alaska. Fish. Bull. 76:700-706.
Lilly, G. R., D. G. Parsons, and D. W. Kulka.
2000. Was the increase in shrimp biomass on the North-
east Newfoundland shelf a consequence of a release in
predation pressure from cod? J. Northw. Atl. Fish. Sci.
27:45-61.
Yang, M-S., and M. W. Nelson.
2000. Food habits of the commercially important ground-
fishes in the Gulf of Alaska in 1990, 1993, and 1996.
NOAA Tech. Memo. NMFS-AFSC-112, 174 p.
406
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Volume 102
Number 3
July 2004
Fishery
Bulletin
Contents
Articles
407—417 Abascal, Francisco J., Cesar Megina, and Antonio Medina
Testicular development in migrant and spawning bluefin
tuna (Thunnus thynnus (U) from the eastern Atlantic and
Mediterranean
418-429 Bobko, Stephen J., and Steven A. Berkeley
Maturity, ovarian cycle, fecundity, and age-specific parturition
of black rockfish (Sebastes melanops)
430-440 Brock, Daniel J., and Timothy M. Ward
Maori octopus (Octopus maorum) bycatch and southern rock
lobster (Jasus edwardsii) mortality in the South Australian
lobster fishery
The conclusions and opinions expressed
in Fishery Bulletin are solely those of the
authors and do not represent the official
position of the National Marine Fisher-
ies Service INOAA) or any other agency
or institution.
The National Marine Fisheries Service
(NMFSi does not approve, recommend, or
endorse any proprietary product or pro-
prietary material mentioned in this pub-
lication. No reference shall be made to
NMFS. or to this publication furnished by
NMFS, in any advertising or sales pro-
motion which would indicate or imply
that NMFS approves, recommends, or
endorses any proprietary product or pro-
prietary material mentioned herein, or
which has as its purpose an intent to
cause directly or indirectly the advertised
product to be used or purchased because
of this NMFS publication.
441—451 Dawson, Stephen, Elisabeth Slooten, Sam DuFresne,
Paul Wade, and Deanna Clement
Small-boat surveys for coastal dolphins; line-transect surveys
for Hector's dolphins (Cephalorhynchus hector/)
452—463 Laidig, Thomas E., Keith M. Sakuma, and Jason A. Stannard
Description and growth of larval and pelagic juvenile pygmy
rockfish (Sebastes wilsoni) (family Sebastidae)
464—472 McGarvey, Richard
Estimating the emigration rate of fish stocks from marine
sanctuaries using tag-recovery data
473-487 Roumillat, William A., and Myra C. Brouwer
Reproductive dynamics of female spotted seatrout
(Cynoscion nebutosus) in South Carolina
Fishery Bulletin 102(3)
488-497 Taggart, S. James, Charles E. O'Clair, Thomas C. Shirley, and Jennifer Mondragon
Estimating Dungeness crab (Cancer magister) abundance: crab pots and dive transects compared
Companion papers
498-508 Tollit, Dominic J., Susan G. Heaslip, Tonya K. Zeppelin, Ruth Joy, Katherine A. Call,
and Andrew W. Trites
A method to improve size estimates of walleye pollock (Theragra chalcogramma) and
Atka mackerel (Pleurogrommus monopterygius) consumed by pinnipeds:
digestion correction factors applied to bones and otoliths recovered in scats
509-521 Zeppelin, Tonya K., Dominic J. Tollit, Katherine A. Call, Trevor J. Orchard,
and Carolyn J. Gudmundson
Sizes of walleye pollock (Theragra chalcogramma) and Atka mackerel
(Pleurogrommus monopterygius) consumed by the western stock of Steller sea lions
(Eumetopias /ubatus) in Alaska from 1999 to 2000
522-532 Tollit, Dominic J., Susan G. Heaslip, and Andrew W. Trites
Sizes of walleye pollock (Theragra chalcogramma) consumed by the eastern stock of
Steller sea lions (Eumetopias /ubatus) in Southeast Alaska from 1994 to 1999
533-544 Tremain, Derek M., Christopher W. Harnden, and Douglas H. Adams
Multidirectional movements of sportfish species between an estuanne no-take zone and
surrounding waters of the Indian River Lagoon, Florida
545-554 Wells, R. J. David, and Jay R. Rooker
Distribution, age, and growth of young-of-the year greater amberjack (Seriola dumerili) associated with
pelagic Sargassum
Note
555-560 Hiroishi, Shingo, Yasutaka Yuki, Eriko Yuruzume, Yosuke Onishi, Tomoji Ikeda, Hironobu Komaki,
and Muneo Okiyama
Identification of formalin-preserved eggs of red sea bream (Pagrus ma/or) (Pisces: Spandae) using
monoclonal antibodies
561 Subscription form
407
Abstract— Testis histological structure
was studied in bluefin tuna {.Thunnus
thynnus I from the eastern Atlantic and
Mediterranean during the reproductive
season (from late April to early Junei.
Testicular maturation was investi-
gated by comparing samples from
bluefin tuna caught on their eastward
reproductive migration off Barbate
i Strait of Gibraltar area) with samples
of bluefin tuna fished in spawning
grounds around the Balearic Islands.
Histological evaluations of cross sec-
tions showed that the testis consists of
two structurally different regions, an
outer proliferative region where germ
cells develop synchronously in cysts,
and a central region made up of a well-
developed system of ducts that convey
the spermatozoa produced in the prolif-
erative region to the main sperm duct.
Ultrastructural features of the differ-
ent stages of the male germ cell line are
very similar to those described in other
teleost species. The bluefin tuna testis
is of the unrestricted spermatogonial
testicular type, where primary sper-
matogonia are present all along the
germinative portion of the lobules. All
stages of spermatogenesis were pres-
ent in the gonad tissue of migrant and
spawning bluefin tuna, although sper-
matids were more abundant in spawn-
ing fish. The testis size was found to
increase by a factor of four ( on average )
during migration to the Mediterranean
spawning grounds, whereas the fat
bodies (mesenteric lipid stores associ-
ated with the gonads) became reduced
to half their weight, and the liver mass
did not change significantly with sexual
maturation. Linear regression analy-
sis of the pooled data of migrant and
spawning bluefin tuna revealed a sig-
nificant negative correlation between
the gonad index (IG) and the fat tissue
index (IF), and a weaker positive cor-
relation between the gonad index (IG)
and the liver index (IL). Our analyses
indicate that the liver does not play a
significant role in the storage of lipids
and that mesenteric lipid reserves con-
stitute an important energy source for
gametogenesis in bluefin tuna.
Testicular development In migrant and spawning
bluefin tuna {Thunnus thynnus (L.)) from
the eastern Atlantic and Mediterranean
Francisco J. Abascal
Cesar Megina
Antonio Medina
Departamento de Biologia
Facultad de Ciencias del Mar y Ambientales
Universidad de Cadiz
Av Republica Saharaui
11510 Puerto Real
Cadiz, Spain
E-mail address (for A Medina, contact author): antonio.medina@uca.es
Manuscript submitted 27 April 2003
to Scientific Editor's Office.
Manuscript approved for publication
25 March 2004 by the Scientific Editor.
Fish. Bull. 102:407-417 (2004).
The Atlantic northern bluefin tuna
(Thunnus thynnus thynnus (L.)), is
one of the most commercially valu-
able wild animals in the world. In the
last two decades this species has been
subject to intense over-fishing, which
has caused a decline in both the east-
ern and western populations because
of lowered recruitment (Mather et
al., 1995; Sissenwine et al., 1998).
The bluefin tunas (7! thynnus and T.
maccoyii) are unique among tuna spe-
cies in that they live mainly in cold
waters and move into warmer waters
to spawn (Olson, 1980; Lee, 1998;
Schaefer, 2001); therefore the migra-
tory pattern of these species depends
substantially on reproduction. The
eastern stock of Atlantic bluefin tuna
spawns from June through August in
the Mediterranean Sea. where natural
conditions are apparently optimal for
the survival of offspring. From late
April to mid June, bluefin tuna breed-
ing stocks migrate from the North
Atlantic to spawning grounds in the
Mediterranean (Mather et al., 1995;
Ravier and Fromentin, 2001). A good
understanding of the reproductive
parameters (especially sexual matu-
ration, fecundity, and spawning) of
tunas is of paramount importance for
population dynamics studies and the
management of fisheries that target
tunas. Nevertheless, "a very limited
amount of scientifically useful infor-
mation is available on the reproduc-
tive biology for most tunas" ( Schaefer,
2001). Recent work has increased our
knowledge on the reproductive biol-
ogy of female Thunnus thynnus in
the eastern Atlantic and the Medi-
terranean (Susca et al„ 2000, 2001a,
2001b; Hattour and Macias, 2002;
Medina et al., 2002; Mourente et al.,
2002), but many questions remain
still to be answered regarding male
reproductive activity in this and other
tuna species.
Histological examination of gonads
is a useful tool for assessing the ma-
turity state offish. However, very few
light-microscopy studies have been
published on bluefin tuna and no ul-
trastructural studies of reproductive
organs are yet available. The male
reproductive cycle of T thynnus has
been characterized histologically by
Santamaria et al. (2003), and Ratty
et al. ( 1990 ) and Schaefer ( 1996, 1998 )
have reported valuable histological
descriptions on male and female go-
nads of the Pacific albacore (Thun-
nus alalunga) and the yellowfin tuna
(Thunnus albacares), respectively. In
this article we report biometric and
histological data on male T. thynnus
caught during their reproductive mi-
gration and spawning period in order
to provide further information on the
biological aspects of reproduction for
this species.
408
Fishery Bulletin 102(3)
Materials and methods
Statistical analysis
Samples and condition indices
During the eastward migration, 62 adult male bluefin
tuna weighing between 71 and 273 kg (mean 195.17 kg)
were obtained from the trap fishery in the area of the
Strait of Gibraltar (Barbate. Cadiz, southwestern Spain)
from late April to early June 1999. 2000, and 2001.
Thirty-four mature males, weighing between 19 and
349 kg (mean 115.11 kg), were sampled in June-July
1999-2001 from the purse-seine fleet operating in the
Mediterranean spawning grounds of bluefin tuna off
the Balearic Islands. Whenever possible, the total body
weight (W) was recorded to the nearest kg. When indi-
vidual body weights were not available, W was estimated
from the fork length (LF) measurements (recorded to the
nearest cm), according to the formula: W = 0.000019 x
LF3 (Table VIII in Rodriguez-Roda, 1964). Following
dissection, the liver, testes, and the fat bodies associ-
ated with the gonads were removed and weighed to the
nearest g. The condition of the fish was assessed by three
different indices. The gonad index (gonadosomatic index)
(IG) is indicative of the maturation state and was calcu-
lated as: IG = (WG I W) x 100, where WG = gonad weight.
The liver index (hepatosomatic index) (IL) and fat-body
index (IF) were calculated as IL = (WL I W) x 100, and
Ip- = (WF I W) x 100 (where WL and WF represent liver
and fat-body weights), respectively, and are considered
as good indicators of the metabolic condition and energy
reserves of the fish. All measurements are expressed as
means +SD.
The bluefin tuna specimens used in this study showed
considerable variability in size, especially those caught
by purse seine in Balearic waters, where weight ranged
between 12 and 349 kg. The purse-seine fishery is, in
fact, much less size-selective than are traps, which
seldom catch small bluefin tuna (Rodriguez-Roda, 1964:
Mather et al., 1995). Analysis of covariance (ANCOVA),
with body weight as covariate, was used as the most
suitable method (Garcia-Berthou, 2001) to test interan-
nual differences in the weight of the organs within the
two sampling sites. ANCOVA was likewise applied to
compare the weights of the three organs between both
areas. All data were previously log-transformed to meet
the prerequisites of normality and homoscedasticity
(Zar, 1996). Linear least-squares regression analyses
were performed to test possible correlations between
IG and the two other indices (IL and IF) by using the
pooled data of Barbate and the Balearic Islands. In
the regression between IG and IF, the Balearic samples
corresponding to year 2001 were excluded because the
reduced fat-body size (adipose tissue was almost non-
existent in the mesentery) of these small bluefin tuna
did not permit an accurate weight measurements on
board. The values of the indices were arcsine-trans-
formed prior to the statistical analysis (Zar, 1996). A
P-value <0.05 was considered statistically significant
for all tests.
Results
Histology
For light microscopy, tissue samples from the central
part of the testes were fixed for 48-96 hours in 10%
formalin in phosphate buffer, 0.1 M, pH 7.2. After dehy-
dration in ascending concentrations of ethanol, a part
of each sample was embedded in paraffin wax and the
remainder was embedded in plastic medium (2-hydroxy-
ethyl-methacrylate). Paraffin sections (6 /im thick) were
stained with haematoxylin-eosin, and plastic sections (3
/jm thick) were stained with toluidine blue. These were
examined and photographed on a Leitz DMR BE light
microscope.
For electron microscopy, small fragments of testis were
fixed for 3-4 hours in 2.5% glutaraldehyde buffered with
0.1 M sodium cacodylate buffer (pH 7.2). Following two
30-min washes in cacodylate buffer, they were postfixed
for 1 hour at 4C in cacodylate-buffered 1% osmium
tetroxide, rinsed several times in buffer, dehydrated in
ascending concentrations of acetone, and embedded in
epoxy resin (either Epon 812 or Spurr). Thin sections
(-80 nm thick) were picked up on copper grids, stained
with uranyl acetate and lead citrate, and examined in
a Jeol 1200 EX transmission electron microscope. Ap-
proximate dimensions provided for germ cells are mea-
surements (means ±SD) of the largest cell diameters on
electron micrographs.
Condition indices
ANCOVA did not reveal significant interannual differ-
ences in gonad, liver, and fat-body weight in the samples
of Barbate as well as in those of the Balearic Islands. In
contrast, a strongly significant difference in testicular
size (P<0.0001) was found in comparing data of matur-
ing bluefin tuna from Barbate (migrant tuna) with fully
mature fish from the Balearic Islands (spawning fish).
In fact, as shown in Figure 1, the average I0 was more
than fourfold higher in the Balearic Islands than it was
in Barbate (4.81 ±1.77 vs. 1.12 ±0.57). This finding may
indicate a noticeable increase in sperm production during
reproductive migration to the Mediterranean spawning
grounds. Significant differences between maturing and
spawning tuna were also found in fat-body weight, the
volume of which dropped to about half by spawning
time. Thus, IF fell from 0.36 ±0.24 in migrating fish to
0.16 ±0.12 in spawning fish isee Fig. 1). The liver mass,
however, did not differ significantly (P=0.31> between
the two samples.
Figure 2 illustrates linear regression analysis be-
tween IG and I, , and between IG and IF. A significant
negative correlation (;-'- = 0.34; P<0.0001) was found be-
tween Iq and Ip, indicating that the amount of mesenteric
fat tissue decreases as the gonad matures. In contrast,
there was a positive, though somewhat weak, correlation
Abascal et al.: Testicular development in Thunnus thynnus
409
V?
™i 'G
V////A l|_
c=i If
j&A
Barbate
Balearic Islands
Figure 1
Differences in gonad index (IG)
liver index 1 1, ),
bluefin tuna [Thunnus thynnus) from Barbate and
male tuna from the Balearic Islands.
(r2=0.21; P<0.0001) between IG and IL, which suggests a
slight growth of the liver with sexual maturation.
Histology
The testes of Thunnus thynnus are paired, elongate
organs that appear attached to the dorsal body wall by
a mesentery. The fat body, which is closely associated
with the gonad, consists of a variable amount of adipose
tissue. The testis is composed of a dense array of lobules
converging on the main sperm duct (vas deferens) and
terminating blindly beneath the tunica albuginea at the
periphery ( Fig. 3, A and B). Two distinct zones can be
distinguished in cross sections of the testes (Fig. 3A). At
the outer region, the seminiferous lobules have a thick
wall formed by the germinal epithelium, where germ cells
develop in association with Sertoli cells; the lumina of
the lobules are filled with spermatozoa that have been
released after completion of the spermiogenetic process
(Fig. 3, B and C). As a result of the release of mature
sperm from spermatocysts into the lobule lumina, the
germinal epithelium becomes discontinuous (Fig. 3B).
The transition from the outer to the central region of the
testis is marked by an abrupt change in the configuration
of the testicular lobules, which lose the germinal epithe-
lium and become ducts where lobule function has shifted
from sperm production to sperm storage (Fig. 3C). Thus,
the only sex cells that are found in the central part of
the testis are mature spermatozoa, which fill the swollen
lumina of the lobules. In this zone the testis ducts con-
stitute an intricate network of channels that convey the
spermatozoa produced in the proliferative region to the
main sperm duct (Fig. 3, A and D), which is thick walled
and located in the center of the testis (Fig. 3D).
0,25
A
0,20
o
^ 0,10
o
0,05
•
0,00
0,00 0.05 0.10 0,15 0,20 0.25 0,30 0,35
arcsin[(lG/100)1'2]
0,12 •
B
•
0.10
•
c\j
5- 0.08
o
o
jL 0,06 -
o 0.04 -
03
• >
• • • .^>^» •
• ^"~\^^
0.02
•\.
• ^--^
0,00 0,05 0,10 0,15 0,20 0,25 0,30 0,35
arcsin[(lG/100)"2]
Figure 2
Linear regression between gonad index (IG) and liver
index (ILl I Al, and between gonad index (I,-. ) and fat body
index (IFI (Bi (data were pooled from the two areas). In
B, samples of bluefin tuna (Thunnus thynnus) collected
off the Balearic Islands in 2001 were excluded.
The gametes develop in groups of isogenic cells called
germinal cysts or spermatocysts, where the process of
differentiation is synchronous (Fig. 4). Primary sper-
matogonia are large, single cells (Fig. 4A) that are dis-
tributed all along the germinal epithelium, as is char-
acteristic of the teleost unrestricted testicular type.
Spermatogonia B resulting from successive mitoses of
spermatogonia A are found in small groups, whereas
spermatocytes and spermatids are grouped within larger
spermatocysts (Figs. 3, B and C, 4). The cysts contain-
ing late spermatids and spermatozoa, prior to spermia-
tion, display a particular alveolar appearance due to
the orientation of the spermatid heads facing the lobule
walls and the bundles of fiagella directed toward the
seminiferous lobule lumen (Fig. 4, A, C, and D).
Active spermatogenesis was observed to occur both in
migrant bluefin tuna from the Strait of Gibraltar (Fig. 4,
A and B) and spawning fish from the Mediterranean
(Fig. 4, C and D). In both cases, all stages of the male
410
Fishery Bulletin 102(3)
Figure 3
Light micrographs depicting the histological organization of the bluefin tuna (Thunnus thyn-
nus) testis. iAi Transverse section showing the outer proliferative region (PR) of the testis and
the inner region, which includes the testis duct system (D) and the main sperm duct (MSD).
(B) Peripheral zone of the testis where the distal ends of some tubules i dotted lines! terminate
beneath the tunica albuginea (TA). (C) Transition (dotted line) between the outer region (PR)
of the testis, where the lobules contain developing germinal cysts, and the inner region (Dl,
whose lobule walls enclose only mature spermatozoa. (Dl Main sperm duct iMSDi filled with
a compact mass of spermatozoa that are incorporated (arrowhead) from the testis ducts (D).
Arrows = discontinuities in the germinal epithelium; sc = spermatocytes; sd = spermatids; sg =
spermatogonia; sz = spermatozoa. All samples are from Barbate (A and D, paraffin-embedded
sections stained with haematoxylin-eosin; B and ('. toluidine-blue stained plastic-embedded
sections).
Abascal et al.: Testicular development in Thunnus thynnus
411
L , tf K *.T<£W*. »5r * .'50 ufk
Figure 4
Spermatocysts in the testis proliferative region of bluefin tuna (Thunnus thynnus) from Barbate
(A and B) and the Balearic Islands (C and D). All stages of spermatogenesis are present in both
cases, although spermatid cysts containing late spermatids and spermatozoa (asterisks) are
somewhat more abundant in specimens from the Balearic Islands. Arrow = dividing sperma-
tocytes; sc = spermatocytes; sd = spermatids; sg = primary spermatogonion; sz = spermatozoa.
Plastic-embedded sections (A-D) were stained with toluidine blue.
germ cell line were present in the gonads. In addition,
large amounts of spermatozoa had accumulated in the
central system of ducts and in the main sperm duct,
both of which appear to function as reservoirs of sperm.
In specimens from Barbate, spermatocytes and sper-
matids were abundant (Fig. 4B), whereas in most tuna
collected in the Balearic area spermatids predominated
over spermatocytes. Cysts containing late spermatids
and spermatozoa were particularly common (Fig. 4, C
and D).
412
Fishery Bulletin 102(3)
sgA
sd2
sgA
B^'-V- ^
4/r
Se
(..
A
!."»" ,
■■■':'.'^'
m
/*-■»
•
I
sd3
mc
sgA ^
//
'I
cf
Se
2 urn
Figure 5
Electron micrographs of testicular tissue from bluefin tuna (Thunnus thynnus). i A and Bl over-
views displaying several spermatocyst types, including single primary spermatogonia (sgA).
and clusters of spermatogonia B IsgB), primary spermatocytes iscl I, mid spermatids ( sd2 1. late
spermatids (sd.3), and spermatozoa (sz). The germ cells are surrounded by Sertoli cells (Se).
Arrowheads = perinuclear bodies ("image"); N = nucleus; n = nucleolus; cf = collagen fibers;
mc = myoid cell.
infrastructure
Primary spermatogonia are large, ovoid cells (8.55 ±1.07
jim) whose nucleus (>5 Jim in its largest diameter) shows
diffuse chromatin and a single central nucleolus. The
cytoplasm contains free ribosomes, a few mitochondria,
endoplasmic reticulum cisternae, and several masses
Abascal et al.: Testicular development in Thunnus thynnus
413
of electron-dense perinuclear material ("nuages") that
indicate nucleocytoplasmic transport (Fig. 5, A and B).
Such chromatoid bodies persist throughout spermatogen-
esis until the spermatid stage, but their size and number
is far higher in primary spermatogonia. Spermatogonia
B are grouped in clusters of a few cells. They are per-
ceptibly smaller (6.75 ±0.37 um) than spermatogonia A
and their nucleus contains patchy chromatin (Fig. 5, A
and B).
Spermatocytes form clusters in which the cells are
interconnected by cytoplasmic bridges. Primary sperma-
tocytes (4.84 ±0.45 Jim) show a heterochromatic nucleus
(-3.5 um in diameter) that varies in appearance depend-
ing on the prophase-I stage. The cytoplasm contains
free ribosomes (mostly polysomes), mitochondria, clear
vesicles, and the diplosome (Figs. 5A, 6A). Synapton-
emal complexes are clearly recognizable at pachytene
(Fig. 6A). Secondary spermatocytes are apparently
short-lived cells because they are rare in histological
samples — a finding that suggests that the second meiotic
division is triggered shortly after completion of the first
division. Spermatocytes II are difficult to distinguish
morphologically from early spermatids, although they
are slightly larger (3.31 ±0.47 /jm). The cytoplasm is
more reduced than in spermatocytes I and the nucleus
shows diffuse chromatin forming moderately electron-
dense patches (Fig. 6B).
During spermiogenesis, the spermatid nucleus changes
in shape and decreases in volume as the chromatin con-
denses. In early spermatids (2.39 ±0.28 /Jm) the spheri-
cal nucleus shows a dense chromatin with some elec-
tron-lucent areas (Fig. 6C). Then the chromatin becomes
more homogeneous in mid spermatids (2.56 ±0.21 fim)
(Figs. 5A, 6D), and eventually in late spermatids (1.81
±0.32 /iml condenses into a coarse granular pattern,
whereas the nucleus assumes an ovoid shape and forms
a basal indentation over the proximal segment of the
axoneme (Fig. 6E). Cytoplasmic changes involve elonga-
tion of the flagellum, reduction of the cytoplasmic mass,
and coalescence of the mitochondria into a few large
spherical units located around the proximal portion
of the axoneme. Rotation of the nucleus does not take
place during spermiogenesis, therefore the flagellum
axis remains parallel to the base of the nucleus and
the spermatozoon shows the typical ultrastructure of
teleostean type-II sperm (Fig. 6F).
Discussion
Histologically, the bluefin tuna testis is of the unre-
stricted spermatogonial testicular type found in most
teleosts, where spermatogonia occur along the greater
part of the testicular tubules. In the restricted sper-
matogonial testicular type of the atheriniforms, on the
other hand, the spermatogonia are confined to the distal
end of the tubules, and spermatogenesis proceeds as the
germ cells approach the efferent ducts (Grier et al., 1980;
Grier, 1981). Efferent ducts are generally absent in unre-
stricted spermatogonial testes, so that germinal cysts
form along the testicular tubule length (Grier et al.,
1980; Grier, 1981; Lahnsteiner et al., 1994). However,
in maturing and spawning bluefin tuna a well-developed
network of ducts collects the sperm produced by the ger-
minal epithelium and voids them into the main sperm
duct. The central ducts of the testis are continuous with
the proliferative segment of the testicular lobules, which
lose the germinal epithelium in the innermost region
of the testis and function as sperm storage structures.
This process has been documented in the common snook
iCentropomus undecimalis) (Grier and Taylor, 1998), the
cobia (Rachycentrum canadum) (Brown-Peterson et al..
2002), and the swamp eel (Synbranchus marmoratus)
(Lo Nostro et al., 2003). Grier et al. (1980) showed that
in the atheriniform Fundulus grandis the efferent duct
wall cells derive from Sertoli cells. A system of efferent
ducts has been described in other species of teleosts pos-
sessing testes of the unrestricted spermatogonial type
(Rasotto and Sadovy, 1995; Manni and Rasotto, 1997).
As has been shown in other species of the genus (Ratty
et al., 1990; Schaefer, 1996; 1998), the main sperm duct
of T. thynnus has a thick wall and is located near the
center of the testis, whereas in many other teleosts the
main duct is dorsal (Grier et al., 1980).
Ultrastructural features of bluefin tuna spermatogen-
esis are comparable to those described extensively in
teleosts (for examples of recent literature see Gwo and
Gwo, 1993; Stoumboudi and Abraham, 1996; Quagio-
Grassiotto et al., 2001; Huang et al., 2002; Koulish et
al., 2002; Fishelson, 2003). The primary spermatogonia
are the largest male germ cells and exhibit several
conspicuous perinuclear ("nuage") bodies. After several
divisions they give rise to cysts of secondary spermato-
gonia that enter meiosis to produce successively primary
and secondary spermatocytes. Primary spermatocytes
are abundant, particularly at the pachytene phase, and
are therefore thought to be of long duration. In contrast,
the spermatocyte-II stage is thought to be the shortest
spermatogenetic step, because, as occurs in teleosts in
general, it is the least frequent in histological samples.
Spermiogenesis develops without the occurrence of rotation
of the spermatid nucleus, resulting in a teleostean type-II
spermatozoon (Mattei, 1970), in which the flagellar axis
lies tangential to the nucleus instead of being inserted
perpendicular to its base (Abascal et al., 2002).
Santamaria et al. (2003) divided the testicular cycle of
T. thynnus caught in Mediterranean waters from Febru-
ary to September into five periods. Those developmental
stages are similar to stages 2-6 classified by Grier (1981)
for a generalized teleost annual reproductive cycle. Most
probably, stage 1 (spermatogonial proliferation) occurs
in Mediterranean bluefin tuna between October and
January. More recently, annual histological changes in
the germinal epithelium have been used to identify five
distinct reproductive classes in males of several teleost
species (Grier and Taylor, 1998; Taylor et al., 1998:
Brown-Peterson et al., 2002; Lo Nostro et al., 2003). It
is assumed that the most advanced maturation classes in
males are characterized by the presence of a discontinu-
ous germinal epithelium. According to this criterion, all
414
Fishery Bulletin 102(3)
Figure 6
Electron micrographs of spermatocytes I (A), spermatocytes II (B), early spermatids (C), mid
spermatids (D), late spermatids (E), and spermatozoon (F) from bluefin tuna {Thunnus thynnus).
Arrows = synaptonemal complexes; arrowheads = cytoplasmic bridges between spermatids; ax =
axoneme; c = centriole; cc = cytoplasmic canal; d = diplosome; dc = distal centriole; f = flagellum;
Gc = Golgi complex; m = mitochondria; N = nucleus; pc = proximal centriole.
of the samples examined in the present study correspond
to the mid- and late-maturation stages proposed by Grier
and Taylor (1998), and Taylor et al. (1998). Testes at
these stages become storage organs that are filled with
sperm. The present study encompasses only a short
period of the reproductive cycle, which comprises final
gonad maturation. However, descriptions of the testicu-
lar histology throughout the annual cycle (Santamaria
et al., 2003) appear to indicate that different maturation
classes might be defined in the bluefin tuna based on
histological examination of the germinal epithelium (see
Taylor et al, 1998; Brown-Peterson et al., 2002).
Final sexual maturation involves a considerable in-
crease in testis size, but no apparent remarkable histo-
logical changes, with the exception of a slightly higher
frequency of the most advanced stages of spermatogen-
Abascal et al.: Testicular development in Thunnus thynnus
415
esis in fully mature bluefin tuna. The different testicular
development of maturing and spawning tuna is reflected
by their respective average IG, which was fourfold higher
in spawning fish. An equivalent gonad growth was found
in the females collected in the same samplings (Medina
et al., 2002), indicating a spatiotemporal parallelism in
the gonad maturation cycle and a good synchronization
of the reproductive peak in the two sexes. The matura-
tion schedule differs between the two sexes, however, in
that males are capable of generating mature spermatozoa
while still on migration, whereas females do not appear
to develop fully mature oocytes until they have reached
the spawning grounds (Medina et al., 2002). Therefore,
even though mature spermatozoa can be found in tes-
ticular ducts during prolonged periods throughout the
reproductive cycle, it is unlikely that males are actually
capable of spawning out of reproductive season.
The seasonal IG profile of the bluefin tuna appears
to be similar to that of the pelagic, highly migratory
perciform Rachycentron canadum (Brown-Peterson et
al., 2002), and the swamp eel (Synbranchus marmora-
tus) (Lo Nostro et al., 2003), in which peak Ic; values
occur when the reproductive activity is at a maximum.
A different situation has been reported in the common
snook (Taylor et al., 1998), where the highest IG levels
correspond with the mid maturation class and decrease
during the latter part of the reproductive season. The
biological significance of these different IG profiles in
terms of reproductive strategies is yet unknown because
a very limited number of species have been examined
so far.
Because spermatozoa are by far the most abundant
cells in mature testes, the gonad weight becomes a
good indicator of the quantity of sperm produced by a
fish (Billard, 1986). Therefore, the significant increase
in IG that occurred between samplings off Barbate and
the Balearic Islands would indicate that, during migra-
tion, bluefin tuna can raise several times the volume of
sperm accumulated in the testes. The apparently high
spermatogenetic activity observed in bluefin tuna caught
on the spawning grounds suggests that bluefin tuna
have the ability to regenerate testicular sperm stores.
Continuous sperm production could be important be-
cause external fertilization requires the release of large
amounts of sperm to ensure successful fertilization of
eggs, especially when egg size is small. In addition, it
should be noted that tunas spawn multiple times (June,
1953; Yuen, 1955; Buriag, 1956; Otsu and Uchida, 1959;
Baglin, 1982; Stequert and Ramcharrun. 1995) and
can spawn almost daily throughout the reproductive
season (Hunter et al.. 1986; McPherson, 1991; Schaefer,
1996, 1998, 2001; Farley and Davis, 1998; Medina et
al., 2002).
From histological examination of the sperm ducts,
and based on the amount of sperm present and the
staining of the epithelium, Schaefer (1998) proposed a
spawning interval of 1.03 days for spawning male Thun-
nus albacares throughout the eastern Pacific Ocean.
The spawning rate estimated for reproductively active
females with the postovulatory-follicle method was 1.19
days (Schaefer, 1998), which coincides with the spawn-
ing interval estimated for female T. thynnus around the
Balearic Islands (Medina et al., 2002). Unfortunately,
we could not make a reliable estimation of the male
spawning interval in our samples. Two possible reasons
may account for this failure. One reason is that many
of the samples of gonadal tissue did not include the
main sperm duct. On the other hand, no clear evidence
of spawning was identified by histological examination
of those specimens processed that had sperm ducts. A
plausible explanation for this fact is that recent sperm
release can be detected only within 12 hours after the
spawning event (Schaefer, 1996); hence for male spawn-
ing to be detected the fish would have to be sampled
in a narrow range of times following spawning, which
Schaefer (1996) established between 00.01 and 12.00
hours after spawning for Thunnus albacares. It would
be worth conducting further research on bluefin tuna at
their spawning grounds, by attempting to cover a broad
range of sampling times in order to ensure collection of
specimens shortly after gamete release. In this way, use-
ful information would be obtained on such reproductive
parameters as spawning schedules, fecundity, and the
energy cost of spawning, which are essential for ecologi-
cal assessments of the reproductive potential.
It is noteworthy that male tuna, as small as 20 kg
in weight (-100 cm LF), were caught on the spawning
grounds in our study. They had gonad indices over 5%
and histological features indicative of full maturity.
These observations indicate that the eastern stock of
Atlantic northern bluefin tuna can reach maturity at
age 3 years and thus support conclusions of previous
studies (Rodriguez-Roda, 1967; Hattour and Macias,
2002; Susca et al., 2001a, 2001b; Medina et al., 2002);
western bluefin tuna, on the other hand, mature at an
older age, which has been estimated at 6 years (Baglin,
1982).
Prior to sexual maturation, marine fish generally
accumulate large lipid deposits, primarily triacylgly-
cerols, which are subsequently mobilized to support
gonad development and spawning migration (Bell, 1998).
The major lipid storage sites are the mesenteric tissue,
muscle, liver, and subdermal fat layers (Ackman, 1980).
In bluefin tuna the liver does not appear to play an
important role in lipid storage but is mainly involved
in processing fatty acids mobilized from other bodily
sources (Mourente et al„ 2002). This metabolic pattern
is consistent with our observations of weight modifica-
tions for liver and fat body from maturation through the
spawning period. Although IL increases only slightly
with sexual maturation, IF undergoes a marked decrease
at the time of maximum gonad development. Thus, the
regression analysis of the relationship between IG and IF
shows a significant negative correlation, which reveals a
depletion of mesenteric fat stores as the testes grow. The
occurrence of a similar situation in females (Medina et
al., 2002; Mourente et al., 2002) and in male and female
Thunnus alalunga (Ratty et al., 1990) has led to the con-
clusion that fat-body lipid reserves provide an important
energy source for gametogenesis in tunas.
416
Fishery Bulletin 102(3)
Acknowledgments
This study has been funded by the Spanish government
and the European Union (projects 1FD1997-0880-C05-
04 and Q5RS-2002-01355). The authors wish to thank
two anonymous reviewers for helpful recommendations.
We also thank Pesquerias de Almadraba, S. J. and
Gines J. Mendez Alcala (G. Mendez Espana, S. L.) for
co-operation and assistance. The invaluable technical
assistance of Agustin Santos and Jose Luis Rivero is
greatly appreciated. G. Mourente lent useful help in our
discussion on lipids.
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418
Abstract-From 1995 to 1998. we col-
lected female black rockfish (Sebastes
mt'lanops) off Oregon in order to
describe their basic reproductive life
history and determine age-specific
fecundity and temporal patterns in
parturition. Female black rockfish had
a 50^ probability of being mature at
394 mm fork length and 7.5 years-of-
age. The proportion of mature fish age
10 or older significantly decreased each
year of this study, from 0.511 in 1996
to 0.145 in 1998. Parturition occurred
between mid-January and mid-March,
and peaked in February. We observed a
trend of older females extruding larvae
earlier in the spawning season and
of younger fish primarily responsible
for larval production during the later
part of the season. There were dif-
ferences in absolute fecundity at age
between female black rockfish with
prefertilization oocytes and female
black rockfish with fertilized eggs;
fertilized-egg fecundity estimates were
considered superior. The likelihood
of yolked oocytes reaching the devel-
oping embryo stage increased with
maternal age. Absolute fecundity esti-
mates ( based on fertilized eggs) ranged
from 299,302 embryos for a 6-year-old
female to 948,152 embryos for a 16-
year-old female. Relative fecundity
(based on fertilized eggs I increased
with age from 374 eggs/g for fish age 6
to 549 eggs/g for fish age 16.
Maturity, ovarian cycle, fecundity, and
age-specific parturition of black rockfish
(Sebastes melanops)
Stephen J. Bobko
Steven A. Berkeley
Department of Fisheries and Wildlife
Hatfield Marine Science Center
2030 SE Marine Science Drive
Oregon State University
Newport, Oregon 97365
Present address (for S. A. Berkeley, contact author): Long Marine Laboratory
University of California, Santa Cruz
100 Shaffer Rd
Santa Cruz, California 95060
E-mail address (for S A Berkeley, contact author): stevenab@cats.ucsc.edu
Manuscript submitted 13 March 2003
to Scientific Editor's Office.
Manuscript approved for publication
30 March 2004 bj the Scientific Editor.
Fish Bull. 102:418-429(2004).
Many fish species in the North Pacific
have a long reproductively active life
span, which increases the likelihood
of producing offspring during peri-
ods of favorable environmental condi-
tions. This bet hedging reproductive
strategy reduces the impact of envi-
ronmental variation on reproductive
success (Goodman, 1984; Leaman
and Beamish, 1984; Schultz, 1989).
In species with age-structured spawn-
ing schedules, a broad age distribu-
tion will maximize the length of the
spawning season. The more protracted
the reproductive period, the greater
the likelihood that some spawning
will occur during conditions favorable
for larval survival (Lambert, 1990).
Age-related differences in the timing
of spawning have been observed in
many fishes; usually larger, older fish
spawn earlier (Simpson, 1959; Bage-
nal, 1971; Berkeley and Houde, 1978;
Shepherd and Grimes, 1984; Lambert,
1987), but in some cases younger fish
spawn earlier in the season (Hutch-
ings and Myers, 1993).
Age truncation, an inevitable result
of fishing, can increase recruitment
variability by reducing the length of
the spawning season or by selectively-
removing older, more fit individuals
from the population. Factors that
might affect individual reproductive
success include the number of eggs
produced, the quality of eggs (e.g.,
yolk or oil globule volume), and the
size or health of eggs and larvae. Off
the coast of Oregon, widow rockfish
(Sebastes entomelas) have exhibited
increased absolute fecundity, and
more importantly have increased rela-
tive fecundity, with age (Boehlert et
al., 1982). Individual populations of
shortbelly rockfish (Sebastes jordani),
have been found to produce larvae
with differing lipid and protein com-
positions and consequently potentially
differing rates of survival (MacFar-
lane and Norton. 1999). Zastrow et
al. (1989) reported that striped bass
eggs stripped from wild fish increase
in quality with maternal age due to
increased amounts of proteins and
lipids, although relative concentra-
tions remain unchanged.
Black rockfish ( Sebastes melanops),
like most other rockfish, are long-
lived, moderately fecund livebearers
with long reproductive life spans. Al-
though their longevity and low rate
of natural mortality is presumed to
be an adaptation to allow success-
ful reproduction over their lifespan
despite long periods between favor-
able environmental conditions, it al-
so makes them more susceptible to
overexploitation. The objective of our
research presented in the present
article is twofold. First, we describe
the basic reproductive life history
of black rockfish. with an emphasis
on the ovarian developmental cycle
and maturity schedule. Second, we
investigate age-specific fecundity and
temporal patterns in parturition and
Bobko and Berkeley: Maturity, ovarian cycle, fecundity, and parturition of Sebastes melanops
419
discuss their effect on reproductive success in a
population undergoing truncation of the upper end
of its age distribution.
Materials and methods
We collected female black rockfish during the
months of peak female reproductive development,
November through March, for three successive
years from 1995-96 through 1997-98. Female black
rockfish were primarily obtained from recreational
charter boat landings in Newport, Depoe Bay, and
Charleston, Oregon, in addition to some fish from
commercial landings from Port Orford, Oregon
(Fig. 1). We also collected fish by rod and reel and
spearfishing. When possible, the sex of all avail-
able black rockfish was determined, and females
were staged as immature or mature. Immature
females were measured (FL), and mature females
were returned to the laboratory. On extremely busy
days when numerous charter boats were fishing,
all mature females were collected, but immature
fish were not measured. In total we collected 1643
female black rockfish. Immediately upon return
to the laboratory, we recorded fork length, total
weight when possible (most samples from charter
boats were carcasses only), liver weight, and ovary
weight. Ovaries were assigned a maturity stage
based on macroscopic appearance and preserved in
10% buffered formalin. We initially followed the gross
maturity stage scheme of Nichol and Pikitch (19941 for
darkblotched rockfish ( Sebastes crameri) but ultimately-
abandoned their classification of maturity stages in favor
of the simplified maturity stages reported by Gunderson
et al. (1980) (Table 1). Sagittal otoliths were removed
and stored dry for age determination. All aging was done
by an expert age reader from the Oregon Department of
Fish and Wildlife (ODFW), who used the break-and-burn
technique (Beamish and Chilton, 1982). Ten percent of
the otoliths were randomly selected for a second read-
ing to ensure consistency in interpretation of annuli.
It should be noted that black rockfish ages have not
been validated. However, ages have been validated for
yellowtail rockfish (Sebastes flavidus), a closely related
species (Leaman and Nagtegaal, 1987), by using otoliths;
moreover, the break-and-burn aging method is widely
accepted as valid for aging rockfish (MacLellan, 1997),
and ages thus derived are routinely used in rockfish
stock assessments. Because our sample included all
mature females that we encountered, we used these data
to estimate the age distribution of mature females in
each time period, and the age distribution of parturition
during each time interval.
Histological preparations were made from the ova-
ries of 175 females collected monthly from March 1996
through March 1997 to track seasonal ovarian devel-
opment. Females collected in March 1996 and Novem-
ber 1996 through March 1997 were from our regular
sampling program, whereas fish collected from April
45° 00'N "
42° 50' '
124° 30' 120°00'W
Figure 1
Map of the Oregon coast showing the study area where black
rockfish (Sebastes melanops) were collected.
through October 1996 were obtained from Newport
recreational charter boat landings. Females were ran-
domly selected from each maturity stage observed each
month and from as wide a range of ages as available
(Table 2). Ovaries were embedded in paraffin, sectioned
at 4-5 jjm, and stained with gill-3 haematoxylin and
eosin y solution.
We determined stage-specific fecundity in black rock-
fish for females with unfertilized yolked oocytes (?i=184)
and fertilized eggs (n = 85). Postfertilization ovaries were
very fragile and tended to rupture easily and release
embryos under the slightest pressure. Consequently,
for estimating fecundity for these stages, we used only
fish collected by ourselves so that we were certain that
no eggs or larvae had been released during capture.
To ensure that no eggs were lost after capture, these
fish were immediately placed into plastic bags in order
to retain any eggs that might be extruded before the
ovary could be processed. Ovaries were processed fol-
lowing procedures modified from Lowerre-Barbieri and
Barbieri (1993) to separate eggs and embryos from
connective tissue. Briefly, fixed ovaries were manually
manipulated and rinsed with water through a 1-mm
square mesh sieve, which retained most of the con-
nective tissue, into another sieve with 0.75-mm mesh.
Ovary connective tissue was retained in the coarse
sieve, and freed eggs were collected in the fine-mesh
sieve. Freed eggs were patted dry, weighed (nearest
0.1 g), and three subsamples were collected, weighed
(nearest 0.001 g), and placed in 10% buffered formalin.
420
Fishery Bulletin 102(3)
Table 1
Macroscopic and histological descriptions of stages used to
describe female black rockfish maturity.
Maturity stage
Macroscopic description
Histological description
1 Immature
Small and translucent ovary, pink during months
without sexual activity and yellowish (except for
very small fish) during months with reproductive
activity.
2 Vitellogenesis Ovary firm and yellow or occasionally cream in
color. Large range of size, but all with visible opaque
eggs.
3 Fertilization
4 Eyed larvae
5 Spent
6 Resting
Eggs are golden and translucent. Ovary extremely
large in relation to body cavity. Ovary wall thin and
easily torn.
Eyes of developing embryos visible, giving ovary
an overall greyish color. Ovary fills a large
portion of the body cavity.
Ovary flaccid, purplish-red in color. Eyed larvae
may still be visible.
Ovary again firm and pink in color. Black spots may
be visible.
Oocyte cytoplasm intensely basophilic. Densely
packed oogonial nests and developing oocytes, with
larger oocytes containing small clear vesicles.
Oogonia and developing oocytes still visible, but
ovary dominated by large oocytes with numerous
small red-staining yolk globules.
Fertilized eggs ovulated and found within the
ovarian cavity. Eggs have a single pink-staining
yolk mass and clear oil droplet.
Presence of developing larvae with black pigmented
eyes. Yolk mass absorbed in late-stage larvae, but
oil droplet usually present.
Early-stage oocytes loosely associated. Extensive
network of blood vessels. Possibility of encountering
residual larvae.
Similar appearance to immature fish. Ovary wall
slightly thicker in early summer.
Table 2
Monthly ranges for age, length, and maturity stage of
black rockfish collected off Oregon from March 1996
through March 1997 for histological analysis.
Month
Age (yr
range
FL(mm)
range
Maturity stage
range
n
March
7-25
375-510
1.4-6
10
April
7-18
364-447
1.5-6
12
May
7-13
340-465
1 and 6
15
June
5-13
349-432
1 and 6
15
July
5-13
360-475
1 and 6
14
August
5-11
357-493
1-2,6
15
September
6-16
366-488
1 and 2
12
October
5-16
357-420
1 and 2
11
November
5-11
355-434
1 and 2
16
December
5-14
365-439
1 and 2
10
January
6-17
369-473
1-4
16
February
7-17
378-464
1-5
17
March
6-13
380-467
1,5-6
12
AF = EW
The number of ova in the subsamples were counted and
absolute fecundity was estimated by using the following
algorithm:
issc
ssw
where AF = absolute fecundity, or the total number of
eggs per female;
EW = weight of rinsed eggs (or larvae);
SSCt = subsample count i, where j=l to 3; and
SSWt = subsample weight i, where £=1 to 3.
Relative fecundity (RF), based on gonad-free somatic
weight was estimated by
RF = — —.
TW-GW
where AF = absolute fecundity, or the total number of
eggs per female;
TW = total weight: and
GW = gonad weight.
For our analyses of fecundity, we used only fish in which
the number of eggs or larvae estimated from the three
subsamples had coefficients of variation less than or
equal to 59;, and for prefertilization eggs we used only
females with average egg diameters of at least 450 jj
to ensure inclusion of all developing oocytes. Only one
cohort of developing oocytes is present in the ovary of
Bobko and Berkeley: Maturity, ovarian cycle, fecundity, and parturition of Sebastes melanops
421
5n -i
Maturity stage 2 • Vitellogenic
40 -
Age 8
Collected February 1996
30 -
10 -
o -
i i
' 1
L 1
1 — i —
L i i i i i
50
40
30
20
10
0
0.50 0 55 0 60 0 65 0 70 0 75 0.80 0.85 0.90 0.95 1.00
Maturity stage 3 - Fertilized
Age 8
Collected February 1996
-[ — ' — i — ' — i 1 1 — — ' — — i — —
0 50 0 55 0 60 0.65 0.70 0 75 0 80 0 85 0 90 0 95 100
Oocyte or egg diameter (mm)
Figure 2
Prefertilization- and fertilized-egg-diameter frequency distributions show-
ing a single mode of developing oocytes at both developmental stages.
black rockfish, either during development (stage 2) or
after fertilization (stage 3) (Fig. 2). Analysis of covari-
ance (ANCOVA) was used to test for annual effects in
the relationship between prefertilization fecundity and
age and a maturity-stage effect (prefertilization vs.
fertilized-egg development stages) on both absolute and
relative fecundity at age. We also used ANCOVA to test
for a maturity stage effect in the relationship between
absolute fecundity and fork length. All ANCOVA analy-
ses were conducted by using multiple linear regression
with the function lm in S-PLUS 2000 (MathSoft. Inc..
Seattle, WA).
To predict the probability of a female black rockfish
being mature based on its fork length, we fitted our
maturity-at-length data to a logistic regression. Dur-
ing those months without reproductive activity, late
spring through early fall, it was difficult to distinguish
between immature and mature-resting ovaries. Conse-
quently, only those females collected during the peak
months of reproductive development and from sampling
events where all fish, mature and immature, were col-
lected were included in our analysis. Binary maturity
observations (0=immature, l=mature) and fork length
were fitted to a logistic model by using the function
glm, family = binomial of S-PLUS (S-PLUS 2000). The
model used was
S0+/Jl«.
mFL)=P(Y = \\FL)--
\ + e
00+010. ■
where P(Y=1\FL)
probability of female black rockfish
being mature at size FL; and
/30 and P{ = regression coefficients for the inter-
cept and fork length, respectively.
For functional purposes, the response variable was
interpreted as the percentage of female black rockfish
mature at length. Assuming this relationship of fork
length to maturity had not changed over time, we ap-
plied our logistic model to fork-length data from random
sampling conducted by ODFW during the summers of
1992-2000 to calculate the percentage of female black
rockfish caught by the recreational fishery off Newport
that were mature in each year.
Fork length-at-age data for female black rockfish were
fitted with the von Bertalanffy growth function (VB-
GF) by using the nonlinear function nisi ) in S-PLUS
2000. Age at 50% maturity was calculated by using
our estimate of length at 509i maturity and a VBGF
rearranged to the form
^U', '() ~*~ '
where t
L
|9j = age at 50% maturity;
,,= = asymptotic length;
k = Brody growth parameter;
t0 = age at zero length; and
._ = length at 50% maturity.
Timing of parturition was estimated by microscopi-
cally determining embryo development stages for all
females with fertilized eggs following Yamada and
422
Fishery Bulletin 102(3)
Kusakari's (1991) stages of embryonic development for
kurosoi (Sebastes schlegeli) modified to reflect the gesta-
tion period of 37 days for black rockfish (Boehlert and
Yoklavich, 1984). Gestation period is likely to vary with
water temperature. In determining gestation period,
Boehlert and Yoklavich (1984) held black rockfish in
the laboratory at 9-11 :,C. Mean water temperatures
in our study area during the period of egg and larval
development (December-April) were 10.9°, 10.1°, and
11.4°C in 1995-96, 1996-97, and 1997-98, respectively
(http://co-ops.nos.noaa.gov/data). Even in the strong El
Nino year of 1997-98, nearshore water temperature
during the winter larval development period was only
slightly outside this range. Therefore, we assumed a
37-day gestation period for all years of our study. Us-
ing the Boehlert and Yoklavich (1984) equation; (stage
duration = 0.0452 xstage1 090) we solved for duration at
each stage by adding 5 days to account for the time
between hatching (stage 32) and parturition (also from
Boehlert and Yoklavich, 1984). To calculate the time
until parturition for each stage, we subtracted the pre-
vious stage durations from the total gestation period of
37. For example, at stage 1, parturition would occur in
37 days. At stage 2, parturition would take place in 37
days - stage-1 duration (-2 days) = 35 days.
For each year of our study, estimated parturition
dates for all females in our sample were grouped into
one-week time intervals and further subdivided into
age categories: 6-8: 9-11; 12-14; and >15. These num-
bers were then multiplied by the appropriate value for
age-class-specific fecundity based on fertilized eggs
(Table 3) to estimate relative spawning output by week
for each age class.
Results
Ovarian development
Black rockfish off Oregon exhibited group-synchronous
oocyte development; and females extruded only one
brood of larvae per year (Fig. 2). Based on our observa-
tions of ovarian development from all three years of
this study, parturition took place from mid-January
through mid-March and peaked in February. Following
parturition, unextruded larvae were quickly resorbed
and the ovary lost much of its vascularization. From
April through early August ovaries were in a resting
state and contained oogonial nests and slightly larger
oocytes with a basophilic cytoplasm and a maximum
diameter of 50 jjl. Also present at this time were develop-
ing oocytes ranging from 50 to 150 n in diameter with
small lipid vacuoles surrounding the nuclear membrane.
Yolk deposition (vitellogenesis) began in late August
and was observed through the third week of February.
In the final stages of vitellogenesis. the largest oocytes
were approximately 700 n in diameter and had numer-
ous oil vacuoles and yolk globules throughout the cyto-
plasm. The first female with fertilized eggs (stage 3) was
observed during the second week of January, and stage-3
Table 3
Age group-specific absolute fecundity (based on fertilized
eggs l and age distribution of mature females as a percent-
age of all mature females, used to estimate larval pro-
duction. Calculated from data pooled from 1996 through
1998.
Age group
(yr)
Absolute
fecundity'
Percentage of all mature
females represented
by each age group
6-8
9-11
12-14
15 and older
364,183.5
558,837.1
753,490.7
948,144.3
42.19
38.48
13.94
5.39
' Absolute fecundity for each age group is the estimated fecundity
(based on fertilized eggs) for ages 7. 10, 13, and 16. respectively.
females were observed until the third week of February.
Recently fertilized eggs were approximately 850 ,u in
diameter. The period of parturition as indicated by the
occurrence of ovaries containing eyed larvae extended
from the second week in January through the second
week of March. Spent females were first collected during
the last week of January and were most frequently col-
lected in late February and early March.
Sexual maturity
Parameter values for the length-maturity logistic model
were ft, = -26.73 and ^ = 0.068. The smallest mature
female black rockfish we observed was 345 mm; all
individuals were mature by 450 mm. Fifty percent of
females were estimated to be mature at 394 mm fork
length (Fig. 3). As reflected in our length-maturity logis-
tic model, there was a decreasing trend in the percent
maturity for female black rockfish in recreational land-
ings from ODFW collections from 1992 through 2000
(Fig. 4). The von Bertalanffy parameter estimates for
female black rockfish were Lre = 442 mm, k = 0.33, t0 =
0.75 (Fig. 5). Using these estimates, along with the fork
length at 509c maturity, we estimated the age at 50%
maturity for female black rockfish to be 7.5 years. The
median age of mature females decreased in each col-
lection year from 10 years in 1996 to 9 in 1997 and to
7 years in 1998. In addition, we observed a significant
decrease in the proportion of mature fish age 10 or older
over the three years of our study (Pearson's ^2 = 52.4,
df=2, P<0.001). The proportions decreased from 0.511
in 1996, to 0.318 in 1997, and 0.145 in 1998.
Fecundity
Absolute fecundity for prefertilization female black
rockfish ranged from 482,528 oocytes for a 5-year-old
female to 998,050 oocytes for a 19-year-old female.
The results of ANCOVA (Table 4) over a common age
Bobko and Berkeley: Maturity, ovarian cycle, fecundity, and parturition of Sebastes melanops
423
100
e-26 731+0 068-FL
•^ — • — • — •
P(Y=
UFL) =
• /
1 + g-26 731+0 068-FL
80
• / •
/ •
60
-
•/
40
-
20
-
*^%
U
I
I I I
250
300
350 400
Fork length (mm)
450
500
Figure 3
Logistic regression model for the estimated percentage of sexually mature
female black rockfish as a function of fork length, with associated observed
percent mature at 10-mm length intervals.
range showed no evidence of differences in
slopes among the years 1996-98 (P=0.161).
ANCOVA also showed no significant difference
in elevations (P= 0.632), indicating no annual
effect and allowing one model to be fitted to
the pooled data (Fig. 6). Absolute fecundity
for females with fertilized eggs ranged from
299,302 embryos for a 6-year-old to 948.152
embryos for a 16-year-old. Because of the low
number of females with developing embryos
collected in 1996 and 1998, 19 and 4 females,
respectively, and based on the results of prefer-
tilization females, all data were pooled and
fitted with one model (Fig. 7). Although we
were able to pool the data for all years for
fecundity-age regressions for both prefertiliza-
tion females and fertilized females, there was
evidence of interaction (i.e., unequal slopes)
between stage-specific absolute fecundity and
age (2-tailed t-test, P=0.020) requiring sepa-
rate linear regressions to be fitted to the data
(Fig. 8).
Similar to the ANCOVA results for abso-
lute fecundity, there were no differences in
slopes or elevations for relative fecundity for
prefertilization females for the years 1996-98
(Table 4). Again, based on the results of the
ANCOVA for prefertilization females and due
to the low number of fertilized females collected
and 1998, all relative fecundity data for femal
fertilized eggs were pooled. Unlike the results
•
50"
•
•
40"
•
•
•
•
30"
1
1
•
•
1
1992
1994
1996
Year
1998
2000
Figure 4
Estimated percent maturity for recreationally landed female black
rockfish from Newport, Oregon, based on our logistic regression model
of fork length on maturity. Data were from regular random summer
port sampling conducted by the Oregon Department of Fish and Wild-
life from 1992 through 2000.
in 1996 relation between absolute fecundity and age there was
es with no evidence of interaction (i.e., unequal slopes) between
for the stage-specific relative fecundity and age (2-sided f-test
424
Fishery Bulletin 102(3)
Table 4
Results of analyses of covariance testing for differences in
slopes and
elevations of annua
1 absolute fecundity-age relati
on and
annual relative fecundity-age relation. Response variables
= AF and RF. treatment factors
= year, and covariate
= age.
Source of variation
df
Sum of squares
Mean square
F
P
Absolute fecundity i based on prefertilization oocytes)
Equality of slopes
2
105.347
52,674
1.85
0.161
Error
160
4,564.320
28,527
Equality of elevation
2
168,544
84,272
0.29
0.747
Error
162
3,459,048
288,254
Relative fecundity i based on prefertilization oocytes)
Equality of slopes
2
259.04
129.52
0.58
0.559
Error
160
35,452.22
221.58
Equality of elevation
2
799.52
399.76
1.81
0.166
Error
162
35.711.26
220.44
300
200 "
100
L = 442.02 •( 1 -e1" ° 33 '(a9e"( ° 75 1")
10 15 20
Age (years)
Figure 5
Fork length at age fitted to the von Bertalanffy growth model for female
black rockfish.
(2-tailed i-test, P<0.0001,) of a stage effect
(i.e., unequal elevations) which necessitated
that the data be fitted with a parallel-line
multiple linear regression model (Fig. 10 1.
Temporal patterns in parturition
From 1996 through 1998 we estimated rela-
tive larval production for four age groups:
6-8; 9-11; 12-14: and 15 years and older
(Fig. 11). In each year parturition took place
from mid-January until mid-March, and
older, larger fish extruded larvae earlier
than younger fish. In 1996 and 1997, the
9-11 year-old fish dominated larval pro-
duction, responsible for 60. lQ and 49. 6^ of
all larvae extruded, respectively (Table 5).
In 1998 age 6-8 fish produced the largest
percentage of larvae (65.3%). In all years,
relative larval production was lowest for the
oldest age group (15+), declining to near 0
by 1998.
Discussion
P= 0.096). There was, however, strong evidence (2-tailed
/-test, P<0.001,) of a stage effect li.e., unequal elevations)
which necessitated that the data be fitted with a paral-
lel-lines multiple linear regression model (Fig. 9).
Absolute fecundity for prefertilization female black
rockfish ranged from 443.671 oocytes for a 381-mm-FL
female to 1,135,457 oocytes for a 495-mm-FL female.
For fertilized females, absolute fecundity ranged from
283,618 oocytes for a 381-mm-FL female to 1,073,356
oocytes for a 510-mm-FL female. The results of AN-
COVA over a common size range showed no evidence of
differences in slopes between maturity stages (2-sided
/-test P=0.206). There was, however, strong evidence
Ovarian development for black rockfish in Oregon was
similar to the developmental cycles reported for other
rockfish species (Moser, 1967; Bowers, 1992; Nichol and
Pikitch, 1994) with the exception of seasonal timing
and stage duration. Females underwent vitellogenesis
for up to six months before fertilization, which occurred
from December through February. In all three years,
parturition off the Oregon coast occurred between mid-
January and mid-March and peaked in February. Wyllie
Echeverria (1987) observed similar timing for parturi-
tion of black rockfish off north-central California, with a
peak in February but with parturition occurring through
May.
Bobko and Berkeley: Maturity, ovarian cycle, fecundity, and parturition of Sebastes melanops
425
All female black rockfish. except the
smallest immature females, followed a sea-
sonal cycle in which their ovaries developed
an orange coloring during the months of
reproductive activity — a pattern observed
in olive rockfish (Love and Westphal, 1981).
Similarly, Nichol and Pikitch (1994) ob-
served darkblotched rockfish undergoing
an "immature cycling" and even assigned
these fish a maturity stage. After the re-
productive season, the ovaries of immature
black rockfish once again became pale pink
in color. Because these fish were function-
ally immature and there was no way to
project when they would become sexually
mature, they were combined with those
small, young females undergoing no sea-
sonal ovarian development and were staged
as immature.
Our estimate of fork length at 50% ma-
turity for female black rockfish off Oregon
was similar to the 400 mm estimate re-
ported for north-central California females
(Wyllie Echeverria, 1987), but lower than
the estimate of 422 mm from Washington
(Wallace and Tagart, 1994). Our estimated
age at 50% maturity of 7.5 years was simi-
lar to the estimates of 7.9 and 7 years from
Washington and north-central California,
respectively. McClure (1982) reported that
over 50% of examined female black rockfish
collected off Depoe Bay, Oregon, were ma-
ture by age six. The difference between our
estimate and McClure's was most likely due
to using whole otoliths to age fish, which
resulted in underestimates of age, and
to assigning maturity stages only during
summer months, which we have already de-
scribed as problematic. Both absolute and
relative fecundity increased with age for
female black rockfish in Oregon waters,
although there was a great deal of varia-
tion not accounted for by age. The low r2
values for absolute fecundity regressions
for pre- and postfertilization females (0.25
and 0.45 respectively) are due largely to
the relatively poor correspondence between
age and size (Fig. 5). Black rockfish, like
many slow growing, long-lived fish grow
slowly after sexual maturity. The rate of
growth during their first few years can be
quite variable depending on oceanographic
conditions and food availability. As a re-
sult, young fish can be as large or larger
than much older fish (Fig. 5). Length is a
better predictor of fecundity than age as judged by the
goodness-of-fit of the multiple linear regression model
(Fig. 10; /-2=0.70).
An increase in absolute fecundity with age was ob-
served in both prefertilization and postfertilization
Absolute fecuodity (-10,000)
ro -p* en cd o ro £*
o o o o o o o
1996
• 1997
o 1998
A
• A A
% %
•
0
o •
. : • ' » ^-
° • * 1
. 1 ° •
o • - . ^S^
« o i
1 * •
' i
* 4F(prefertilization) = 298.413 + 36.823 age
P<0.001
r2 = 0.23
U I I I I I I 1 1 I
4 6 8 10 12 14 16 18 20
Age (years)
Figure 6
Scatter plot of black rockfish absolute fecundity (AFl (based on pre-
fertilization eggs) on age by year (1996-98) with a fitted regression line
from pooled data.
140"
_ 120"
o
o
o
° 100-
1 80-
CJ
§ 60-
o
_o
< 40-
20"
1996
• 1997
o 1998
•
•
• !
i
s :
•
•
•
•
:
• •
: y^ •
/ • 8
i i :
t /^(fertilized) = -90,008 + 64,885 age
P< 0.001
r2 = 0,45
0 ' ll ii
4 6 8 10 12 14 16 18 20
Age (years)
Figure 7
Scatter plot of black rockfish absolute fecundity (AF) (based on fertilized
eggs) on age by year (1996-98) with a fitted regression line from pooled
data.
females, but they occurred at different rates. As il-
lustrated in Figure 8, the absolute fecundity for a post-
fertilization 6-year-old black rockfish was only 58%
of the estimated absolute fecundity for a prefertiliza-
tion fish of the same age. By age 15 absolute fecundity
426
Fishery Bulletin 102(3)
140
120
o
o
°. 100
o
~ 80
C
13
O
•2 60
£
3
o
£ 40
<
20
-* — prefertllization
-o— fertilized
10 12 14
Age (years)
16
20
Figure 8
Separate-lines regressions fitted to absolute fecundity (based on pre-
fertilization and fertilized eggs) on age for black rockfish in Oregon.
800"
— ■ — prefertllization
■-o— fertilized
• •
! i
• • •
•
5 600"
O)
cn
03
••Is • •
0
>.
o
§ 400-
• f \ : s
o
_Q)
. ' • i
ro
• 8 °
£ 200-
o o 0
RF = 375.7 + 17.5-age - 106.5'stage
o P< 0.001
^ = 0.27
0 I i i
6 8 10 12 14
16
Age (years)
Figure 9
Parallel-lines model fitted to relative fecundity I based on prefertiliza-
tion and fertilized eggs) on age for black rockfish in Oregon.
estimates for fertilized and prefertilization females were
approximately equal. Yolked oocytes from older females
were more successful in reaching the developing embryo
stage. This may be attributed to higher rates of fertil-
ization, greater viability of embryos, or a combination
of both in older female black rockfish. Regardless of
the mechanism there should have been signs of greater
atresia in the ovaries of young fish, which we did not
observe in our histological preparations. This may have
been due to rapid resorption of unfertilized oocytes or
an artifact of the fragile nature of fertilized ovaries,
which made it difficult to obtain representative histo-
logical preparations. Nevertheless, these results sug-
gest that fecundity in black rockfish is best described
after fertilization, but care must be taken to minimize
embryo loss. These results also suggest that current
Bobko and Berkeley: Maturity, ovarian cycle, fecundity, and parturition of Sebastes melanops
427
estimates of reproductive potential, in which fe-
cundity for prefertilization females is used, may
overestimate actual larval production because
an increasing proportion of the stock consists of
young fish.
We observed a recurring trend of older, larger
fish extruding larvae earlier in the reproductive
season and larval output being increasingly domi-
nated by younger and younger fish. Eldridge et al.
(1991) reported that larger (and most likely older)
yellowtail rockfish {Sebastes flavidus) spawned
earlier in the season than smaller fish — a pat-
tern also reported for darkblotched rockfish (S.
crameri) by Nichol and Pikitch (1994). Reduced
food availability has been suggested as a poten-
tial cause for delayed reproduction in Sebastes for
smaller, younger individuals with high metabolic
requirements for somatic growth (Larson, 1991).
We feel that limiting the amount of energy that
can be spent on reproductive development would
cause lower fecundity or reduced yolk content, but
not necessarily a delay in reproductive develop-
ment that would result in suboptimal timing of
parturition.
Stock assessments rarely consider changes in
population age composition resulting from the
removal of older age classes except to the extent
that total egg and larval production is reduced.
The decreasing representation of mature female
black rockfish age 10 and older in the three years
of our study indicates that age truncation is oc-
curring in black rockfish in Oregon. This trun-
cation not only removes biomass and potential
larval production, but truncation of the upper
end of the age distribution eliminates mature
females with higher fecundity per individual, a
greater success in carrying eggs through to the
larval stage, and an age group that extends the
overall parturition season. Further research is
necessary to explore the controlling mechanisms
of differential reproductive success with age and
to determine how best to incorporate these find-
ings into stock assessment models.
Acknowledgments
Many individuals contributed to the completion of
this study. Tom Rippetoe provided many hours of
expert assistance in all aspects of this research.
Bob Mikus aged all of the adult black rockfish
for this study. We thank him and the Oregon
Department of Fisheries and Wildlife for all their
support. We thank Dan Detman for his help and
time in collecting black rockfish. We also thank
Brock McLeod, Jason Castillo, David Stewart, and
Michael Hogansen for all their help. We are espe-
cially grateful for all those unpaid volunteers who
helped with fieldwork: Joe O'Malley, Mark Amend,
Bill Pinnix, Wolfe Wagman, and Pat McDonald.
160"
/1F = -1 .888,811 +6.122FL -160,053 stage
Absolute fecundity (xio.000)
o o o
r2 = 0 70
. . .*> o
• • 1 ^f
.. . : '••"tt: .• °. °
fi*.\C? ,"8 . = ° • °
o °
• •
••
°^ • .
• o
o
o
— • — prefertilization
o fertilized
365 390 415 440 465 490 515
Fork length (mm)
Figure 10
Parallel-lines model fitted to absolute fecundity (based on prefer-
tilization and fertilized eggs) on age for black rockfish in Oregon.
I I Age 6 - 8
^M Age 9 - 1 1
I I Age 12-14
^mm Age 15 +
^ ^ <e? <eP ^ <eP ^ ^ ^
«£>' & K*' ^' </ t^' #' ^' ^'
Week-month
Figure 11
Percent relative larval production estimated from observations
of larval development and age-group-specific absolute fecundity
(based on fertilized eggs) for all mature females belonging to each
age group of black rockfish collected in Oregon during 1996-98.
428
Fishery Bulletin 102(3)
Table 5
Age group-specific relative larval production for 1996-98
for female black rockfish off Oregon.
Percentage of relative larval production
Age group
1996
1997
1998
6-8
9-11
12-14
15 and older
26.4%
60.1%
11.3%
2.2%
43.1%
49.6%
5.8%
1.5%
65.3%
32.9%
1.8%
0.0%
We thank the charter boat operators in Depoe Bay.
Newport, and Charleston, Oregon, for their kindness,
patience, and cooperation. Only through their assistance
was this research possible. This research was partially
supported by the NOAA Office of Sea Grant and Extra-
mural Programs, U.S. Department of Commerce, under
grant numbers NA36RG0451 (project no. R/OPF-46),
and by appropriations made by the Oregon State legisla-
ture. Additional funding was provided through Hatfield
Marine Science Center scholarships: the 1996 Barbara
Schwantes Memorial Fellowship; the 1997 Mamie L.
Markham Endowment Award; and the 1998 Bill Wick
Marine Fisheries Award.
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430
Abstract— Octopuses are commonly
taken as bycatch in many trap fisher-
ies for spiny lobsters I Decapoda: Pal-
muridae) and can cause significant
levels of within-trap lobster mortality.
This article describes spatiotempo-
ral patterns for Maori octopus i Octo-
pus maorum > catch rates and rock
lobster (Jasus edwardsii) mortality
rates and examines factors that are
associated with within-trap lobster
mortality in the South Australian
rock lobster fishery (SARLF). Since
1983, between 38,000 and 119,000
octopuses per annum have been
taken in SARLF traps. Catch rates
have fluctuated between 2.2 and 6.2
octopus/100 trap-lifts each day. There
is no evidence to suggest that catch
rates have declined or that this level
of bycatch is unsustainable. Over the
last five years, approximately 240,000
lobsters per annum have been killed
in traps, representing ~4% of the total
catch. Field studies show that over
98% of within-trap lobster mortal-
ity is attributable to octopus pre-
dation. Lobster mortality rates are
positively correlated with the catch
rates of octopus. The highest octo-
pus catch rates and lobster mortality
rates are recorded during summer
and in the more productive southern
zone of the fishery. In the southern
zone, within-trap lobster mortality
rates have increased in recent years,
apparently in response to the increase
in the number of lobsters in traps
and the resultant increase in the
probability of octopus encountering
traps containing one or more lobsters.
Lobster mortality rates are also posi-
tively correlated with soak-times in
the southern zone fishery and with
lobster size. Minimizing trap soak-
times is one method currently avail-
able for reducing lobster mortality
rates. More significant reductions in
the rates of within-trap lobster mor-
tality may require a change in the
design of lobster traps.
Maori octopus (Octopus maorum) bycatch and
southern rock lobster (Jasus edwardsii) mortality
in the South Australian rock lobster fishery
Daniel J. Brock
South Australian Research and Development Institute (Aquatic Sciences)
2 Hamra Ave.
West Beach, South Australia 5024, Australia
Present address: Department of Soil and Water
Adelaide University
Adelaide, South Australia 5005, Australia
E-mail address: Brock. Daniel a1 saugov.sa.gov au
Timothy M. Ward
South Australian Research and Development Institute (Aquatic Sciences)
2 Hamra Ave.
West Beach, South Australia 5024, Australia
Manuscript submitted 28 April 2003
to Scientific Editor's Office.
Manuscript approved for publication
2 March 2004 by the Scientific Editor.
Fish. Bull. 102:430-440 (2004).
Fishing traps are used throughout the
world to target a wide range of crusta-
ceans, fishes, and cephalopods. Com-
mercial trap fisheries, especially those
for decapod crustaceans, are often the
most valuable fisheries within a region
(Phillips et al., 1994). Traps are gen-
erally considered to be an efficient
and benign form of fishing because
they appear to cause relatively minor
damage to benthic habitats, can be
designed to target particular species
and size ranges, and produce live
catches in good condition while mini-
mizing bycatch (Miller, 1990).
There are 49 species of spiny lob-
sters (Decapoda: Palinuridae) world-
wide, 33 of which support commercial
trap fisheries. The largest of these
are in Cuba, South Africa, Mexico,
Australia, and New Zealand (Wil-
liams, 1988). The main trap fisher-
ies in Australia are for western rock
lobster {Panulirus cygnus) in Western
Australia and southern rock lobster
(Jasus edwardsii) along the southern
coastline. Octopuses constitute a sig-
nificant component of the bycatch in
both fisheries (Joll1; Knight et al.2) .
In South Australia, J. edwardsii
supports the State's most valuable
commercial fishery. Octopus maorum
is a significant bycatch species and
is thought to be the major cause of
lobster mortality in traps (Prescott
et al.3).
Although the octopus bycatch of the
South Australian rock lobster fishery
(SARLF) is saleable, the commercial
value of this product does not offset
the value of the large number of lob-
sters that are killed in traps by octo-
pus. Many fishermen are convinced
that incidental mortality of octopus
resulting from lobster fishing acts
to control octopus numbers and that
if these rates were reduced, octopus
abundance and levels of within trap
predation would increase.
Despite the prevalence of octopus
bycatch in lobster fisheries, there
have been only a few studies on the
interaction between octopus and lob-
1 Joll, L. 1977. The predation of trap-
caught western rock lobster {Panulirus
Longipes cygnus) by octopus. Depart-
ment of Fisheries and Wildlife, Western
Australia, Report 29, 58 p. (Available
from Department of Fisheries, 168-170
St George's Terrace. Perth, Western Aus-
tralia, 6000.]
- Knight, M. A., A. Tsolos, and A. M.
Doonan. 2000. South Australian
fisheries and aquaculture information
and statistics report. Research Report
Series 49, 69 p. [Available from SARD]
Aquatic Science, 2 Hamra Avenue, West
Beach, South Australia 5022.]
:! Prescott, J.. R. McGarvey, Y. Xiao, and D.
Casement. 1999. Rock lobster. South
Australian Fisheries Assessment Series
99/04, 35 p. [Available from SARDI
Aquatic Science, 2 Hamra Avenue, West
Beach, South Australia 5022.1
Brock and Ward: Octopus bycatch and lobster mortality in the South Australian rock lobster fishery
431
Figure 1
Map of the marine fishing areas (MFAs) of the South Australian rock lobster fishery.
Shading shows the MFAs that were considered in this study and where most fishing effort is
concentrated.
sters in traps (Joll1). Furthermore, there is a paucity of
quantitative data on the impact of fishing on octopus
populations, the proportion of lobster mortality that
is attributable to octopus predation, or the long-term
economic and ecological effects that octopus-induced
mortality may have on lobster fisheries.
In this study, we examined the interaction between
O. maorum and J. edwardsii in the South Australian
rock lobster fishery (SARLF). The objectives were 1) to
determine the number of lobsters and octopus caught
and the number of lobsters killed in traps each year in
the fishery; 2) to describe the interannual and seasonal
patterns in lobster catch rate (CPUEL), octopus catch
rate (CPUE0), and lobster mortality rate (ML); 3) to
examine some factors that may affect lobster mortal-
ity rates; 4) to estimate what proportion of the lobster
mortality is attributable to octopus predation; and 5) to
determine whether the rate of lobster mortality through
octopus predation in traps is size dependent.
Materials and methods
South Australian rock lobster fishery
The SARLF is divided into a northern zone (NZ) and
a southern zone (SZ), each of which is further divided
into marine fishing areas (MFAs) for statistical purposes
(Fig.l). There are 68 and 183 fishermen licensed to oper-
ate in the NZ and SZ respectively. The fishing season
extends from November to May in the NZ and October
to April in the SZ. A quota management system was
introduced in the SZ in 1993, whereas the NZ is man-
aged by gear restrictions and temporal closures.
Total annual catch and effort for the SARLF
Catch and effort data are recorded on a daily basis by all
individual fishermen. Since 1983. a standardized logbook
for recording catch and effort has been used across the
fishery. Data provided by fishermen include MFA fished,
average depth fished, number of trap-lifts, number and
total weight of live lobsters, number of dead lobsters, and
number and total weight of octopus. This information
is stored in a South Australian rock lobster database
that is managed by the South Australian Research and
Development Institute, Aquatic Sciences.
Interannual and seasonal patterns
in CPUEL, CPUEQ, and ML
Although commercial fishing for lobsters occurs along
most of the South Australian coastline, the majority of
effort is concentrated in only a few MFAs. In the NZ
over the last 5 years about 72% of total trap-lifts were
made in MFAs 15, 28, 39, 40, and 49. In the SZ over the
same period 95% of trap-lifts were made in MFAs 51,
55, 56, and 58 (Fig. 1).
432
Fishery Bulletin 102(3)
Data from the database were used to calculate catch
rates of lobsters (CPUEL), octopus (CPUE0), and MLon
an annual and monthly basis for the nine major MFAs
listed above. Catch rates from these MFAs for each
fisherman were calculated according to the formula:
catch rate = catch number/itrap-liftslday). Annual and
seasonal trends in CPUEj , CPUE0, and ML were cal-
culated for each zone and MFA.
Factors that affect within-trap lobster mortality
Potential factors that affect within-trap lobster mortality
were analysed by using a general linear model (type-3
sums of squares) under the assumption that the number
of dead lobsters follows a log-normal distribution.
The number of dead lobsters/trap-lift/day/license
(with a ln+1 transformation) was used as the measure
of lobster mortality. A model of the following structure
was used to examine factors that affect the numbers
of dead lobster:
Dead lobster = License + MFA + Month + Year
+ Effort + Depth + Octopus + Lobster catch
+ Soak-time + I License xYear) + I License xMonth)
+ (YearxMonth) + (YearxMFA) + iSoak-timexYear)
+ < Soak-time xMonth).
In the model. License represents an individual fisher-
man, MFA is the marine fishing area. Month accounts
for seasonal variation and Year accounts for interannual
variation. Effort is the number of trap-lifts/license each
day, Depth is the average depth fished by each License
on a particular day. Octopus and Lobster are the respec-
tive daily catches/license, and Soak-time is the number
of days that the traps remained in the water since the
previous trap-lift.
The interaction terms License xYear and License x
Month account for variations in the catch characteris-
tics of the individual licenses over time that result from
changes in fishing practises and efficiency associated
with different boats, license holders, and skippers. The
interaction terms YearxMonth and YearxMFA account
for variation in the population dynamics of octopus and
lobster over time in different locations that could result
in differential trends in lobster mortality. The inter-
action terms Soak-time xYear and Soak-time xMonth
reflects the change in general fishing strategies over
time. In quota-managed fisheries the average soak-time
will be affected by a number of factors, for example,
that may include price, weather, and the fishermen's
perceived ability to catch their quota.
The analysis was run separately for the SZ (/? = 493,629
traps) and NZ (ra=155,628 traps) because the respective
zones have different fishing seasons and management
structures. The relationship between the number of
dead lobsters and the factors depth, soak-time, and num-
ber of octopuses and lobsters were presented graphically
by the equation:
Lobsters killed in traps <*. factor a,
where a = the parameter estimated by use of the model.
Source of lobster mortality and size-dependent mortality
A sampling program was conducted on three commer-
cial vessels from the SZ during the 2001-02 fishing
season. Five days were spent on each vessel. All lobsters
caught were measured (carapace length, mm), and the
sex (male or female), maturity (mature or immature),
status (dead or alive), and cause of death (octopus or
other) were recorded.
The method used to distinguish between lobsters
killed by octopus or other means followed that of Joll.1
This suitability of this approach was confirmed through
examination of the carcasses of over one hundred lob-
sters killed by octopus in aquarium trials (Brock et
al.4). Lobsters with shells that were partly or completely
separated at the juncture between abdomen and cepha-
lothorax but were otherwise undamaged were deemed
to have been killed by octopuses, whereas lobsters with
shells without this separation and with evidence of bite
marks were deemed to have been eaten by other preda-
tors (fish or cuttlefish).
Anecdotal evidence from fishermen suggests that
larger lobsters are more susceptible to predation than
smaller ones. The effect of CL on the probability of
mortality was examined separately for males and fe-
males by generalized linear modeling. The probability
of mortality at a given size was modeled with a logistic
equation of the form:
P{sex, CL) = l/(l+e-,a+6CL,),
where P(sex, CL) = the probability of a lobster of a
given sex at carapace length CL
being dead; and
a and b are parameters to be estimated.
Results
Estimation of total lobster catch, octopus bycatch,
and lobster mortality
In 1999, there were 1.6 million trap-lifts in the SARLF,
and 70% of this total effort was in the SZ (Fig. 2). The
number of traps-lifts in the SZ declined from 2.2 mil-
lion in 1983 to 1.2 million in 1999 (Fig. 2Ai. In contrast,
fishing effort in the NZ remained relatively consistent
with 406,000 trap-lifts in 1983 and 480, 000 trap-lifts
in 1999 (Fig 2B).
The total annual lobster catch has generally increased
in each fishing zone since 1983 (Fig. 2, A and B).
' Brock, D. J., T. M. Saunders, and T. M. Ward. In review. A
two-chambered trap with potential for reducing within-trap
predation by octopus on rock lobster. Can. J. Fish. Aquat.
Sci., 19 p. lAvailable from SARDI Aquatic Science, 2 Hamra
Avenue. West Beach, South Australia 5022.1
Brock and Ward: Octopus bycatch and lobster mortality in the South Australian rock lobster fishery 433
A
7 -r
6 |<
5
4
3
2
1
0
Southern zone
I lobster — ♦ — trap lifts
\
T 2'5
-- 2
1
05
0
B
7
6
5 +
4
3
2
1
0
Northern zone
I lobster — ♦ — trap lifts
2.5
■■ 2
-- 1.5
1
uxi
-♦-♦-♦
iinlniiilli
i"i"i"i"i"i"i"i"i"i"i"i"i'
0.5
0
1983
1987
1991
1995
1999
1983
1987
1991
1995
1999
1983
1987
1991
1995
1999
1983
1987
1991
1995
1999
Season
Figure 2
Annua] total catch and effort for each zone of the South Australian rock lobster fishery for number of
live lobsters caught (A l, number of trap-lifts used (B). number of dead lobsters caught (C), and number
of octopuses caught (D) (Note: change of scale in D).
In the SZ, the annual lobster catch rose from 3.8 mil-
lion lobsters to a peak of 6.4 million lobsters in 1991
and was 5.4 million lobsters in 1999 (Fig. 2A). In the
NZ, 560,000 lobsters were taken in 1983 compared to
850,000 in 1991 (Fig. 2B).
The total annual octopus catch varied among years in
both zones, but between 70% and 907c of the total octo-
pus catch were landed in the SZ (Fig. 2). The total num-
ber of octopus ranged from 36,000 in 1986 to 109,000
in 1992 (Fig. 2C) in the SZ, and from 4700 octopuses in
1985 to 11,200 in 1998 in the NZ (Fig. 2D).
In 1999, over 226,000 lobsters were killed in traps in
the SARLF (Fig. 2). Since 1983, the mean proportion of
dead lobsters out of the total catch has been approxi-
mately 4%. In the SZ, the number of lobsters killed in
traps has generally increased from 118,000 in 1983 to
196,000 in 1999; a peak of 274,000 dead lobsters oc-
curred in 1992 (Fig. 2C). In the NZ, there has also been
a general increase in the number of lobster killed in
traps each year; 24,000 dead lobsters were recorded in
1983, compared to 31,000 in 1999 and a peak of 39,000
dead lobsters recorded in 1998 (Fig. 2D).
Interannual and seasonal patterns in
CPUEL CPUE0,and ML
Southern zone Mean annual CPUEL in the SZ increased
from 175 to 466 lobsters/I 100 trap-lifts/day) between
1983 and 1999, and the largest increase occurred
between 1997 and 1999 (Fig. 3A). Mean annual CPUE0
ranged from 1.8 to 6.2 octopus/dOO trap-lifts/day) in
1987 and 1992, respectively (Fig. 3C). Mean annual
ML rose from 5 to 17 dead lobster/(100 trap-lifts/day)
between 1983 and 1999 (Fig. 3E). Peaks in both CPUE0
and ML occurred in 1985, 1992, and 1995.
Mean monthly CPUEL declined during the fishing sea-
son from 310 to 164 lobster/(100 trap-lifts/day) between
October and April (Fig. 4A). In contrast, mean monthly
CPUE0 increased from 2.6 to 3.7 octopus/dOO trap-lifts/
day) between October and December and declined to 1.8
octopus/dOO trap-lifts/day) in April (Fig. 4C). Similarly
mean monthly ML increased from 10.7 to 12.8 dead lob-
ster/(100 trap-lifts/day) between October and November
and declined to 6.7 dead lobster/) 100 trap-lifts/day) in
April (Fig. 4E).
434
Fishery Bulletin 102(3)
A lobster
700 ,
Southern zone
Northern zone
maiahmiiii
-i — I — I — I — I — I — I — I — I — I — I — I — i — I — r-
-1 — I — I — I — I — I — I — I — I — I — I — I — I — I — I — I — I
1983 1987 1991 1995 1999 1983 1987 1991 1995 1999
(_ octopus
10 -,
L) octopus
10
— i — i — i — i — i — i — i — i — i — i — i — i — i — i — i — i
1983 1987 1991 1995 1999
6 -I
4
2
0
H#fe^%ftft
t. dead lobster
30
Q- 25
8 20
£ 15
V>
2 10
•o
TO
<D
T3 5
6
2 0
T 1 1 1 1 1 1 1 1 1 1 1 I 1 1— I 1
1983 1987 1991 1995 1999
T 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1983 1987 1991 1995 1999
r dead lobster
30 -,
25 -
20
15
10
5
0
-tfrftttt
T — I 1 — I 1 — I 1 1 1 1 1 1 1 — 1 1 — I 1
1983 1987 1991 1995 1999
Season
Figure 3
Annual catch rates in each fishing zone for lobsters (CPUE, I (A and B), octopus (CPUE, ,i
(C and Dl, and dead lobsters (M[ J iE and F). Error bars are ±SD of mean.
Since 1983, mean annual CPUEL has increased in all
MFAs, and has been consistently higher in MFAs 56
and 58 than in other areas (Fig. 5A). CPUE() has varied
among years but has followed similar trends in different
MFAs with consistent peaks in 1993 (Fig 5C). Prior to
1992, ML was similar among MFAs but after 1992 was
generally highest in MFAs 56 and 58 (Fig. 5E). ML has
increased over time in all MFAs.
Northern zone In the NZ, mean annual CPUEL rose
from 135 to 179 lobsters/( 100 trap-lifts/day) between
1983 and 1991, decreased to 138 lobsters/1 100 trap-lifts/
day) in 1993 and then rose again to 177 lobsters/I 100
trap-lifts/day) in 1999 (Fig 3B). CPUE0 ranged between
1.0 and 2.4 octopus/l 100 trap-lifts/day) in 1987 and 1993
respectively (Fig. 3D). ML ranged from 5.0 to 7.3 dead
lobsters/(100 trap-lifts/day I in 1983 and 1988. respec-
tively (Fig. 3F).
Mean monthly CPUEL declined from 196 to 88 lob-
ster/100 trap-lifts/day between November and May
(Fig. 4B). Mean monthly CPUE0 was reasonably constant
at between 1.43 and 1.7 octopus/100 trap-lifts/day for
the first five months of the season before a decline to 1.0
octopus/100 trap-lifts/day in May (Fig. 4D>. The mean
monthly M, declined from 7.5 to 3.4 dead lobster/100
trap-lifts/day between November and May (Fig. 4Fi.
Since 1983, mean annual CPUEL has been relatively
low and stable in MFAs 15, 28, and 40 but has been
Brock and Ward: Octopus bycatch and lobster mortality in the South Australian rock lobster fishery
435
A lobster Southern zone
600
500
- 400
o
o
s; 300
w
CD
« 200
Oct Nov Dec Jan Feb Mar Apr
octopus
in
% 6
CL
ra 5 -
i *■
~S 3
CD
en o
=3 ^
a.
2 1
o
o
0
Oct Nov Dec Jan Feb Mar Apr
k dead lobster
20
15
1 1 1 1 1 1 1
Oct Nov Dec Jan Feb Mar Apr
B lobster Northern zone
600 -,
500
400
300
200 -
100
0
D
— i 1 1 1 1 1 1
Nov Dec Jan Feb Mar Apr May
octopus
6
5
4
3 -
2
1
0
1 1 1 1 1 1 1
Nov Dec Jan Feb Mar Apr May
15 -
10 ■
5 -
0 -
— i 1 1 1
Nov Dec Jan Feb Mar Apr May
Month
Figure 4
Mean monthly catch rates in each fishing zone for lobsters lCPUEL) (A and Bl, octopus
(CPUE0) (C and Di, and dead lobsters (ML)(E and F). Error bars are ±SD of mean.
higher and more variable in MFAs 39 and 49 (Fig. 5B).
There were large interannual fluctuations in CPUE(1
in each MFA, and these trends were similar among
MFAs (Fig. 5D). ML was highest in MFA 40, where a
maximum of 12.5 dead lobsters/l 100 traps lifts) was re-
corded 1998 and lowest in MFA 15 where the maximum
was 5.2 dead lobsters/100 trap-lifts in 1997 (Fig. 5F).
No clear long-term trends in ML were apparent in any
MFA.
Factors that affect within-trap lobster mortality
Based on the mean square values, the number of octo-
pus had the greatest effect on lobster mortality in both
zones (Table 1, A and B). The number of dead lobsters
increased with both octopus and lobster catches and
with soak-time and decreased as depth increased (Figs.
6 and 7). Based on the relative size of the mean square
values, the factor with the greatest effect on the number
of dead lobsters in the SZ was the number of octopus
caught, followed by soak-time, number of lobsters caught,
and depth. In the NZ, the number of octopus caught was
also the most important factor, followed by the number
of lobsters caught, depth, and soak-time.
Source of lobster mortality and size-dependent mortality
A total of 3627 lobsters from 635 trap-lifts were mea-
sured. In the sample there were 212 lobsters killed in
traps of which 207 (98%) were killed by octopus and 5
436
Fishery Bulletin 102(3)
Southern zone
-i — i — i — i — i — i
1995 1999
octopus
1983
li, dead lobster
- 1 — i — i — i — i — i —
1987 1991
— i — r — i — i — r-
1983 1987
1991
-MFA 51
-MFA 56
1995
-MFA 55
MFA 58
1999
B lobster Northern zone
600
500
400 -
300
200
100
0
1983 1987
D octopus
-1 — I — I —
1991
1995
-T 1 1 1 1 1 1 1 T
1983 1987 1991 1995
>_MFA 15 g MFA 28 a MFA 39
MFA 40 _*_MFA 49
Figure 5
Annual catch rates of the major MFAs in each fishing zone for lobsters (CPUEL) (A and Bi.
octopus (CPUE0i i C and D), and dead lobsters (MLl (E andF).
by other predators. The mean CL of dead male lobsters
was greater than live males (120 ±21.1(SD) vs. 110 ±18.3
(SD) mm, P<0.001). There was no significant difference
in the mean size of live and dead female lobsters. For
both sexes the probability of mortality increased with
size according to the following relationships:
P (ML, males) = i/i+e-(-5.04+o.02CL)
P <ML, females) = m+e-l-*.i&+o.oiCL)m
Above 100 mm CL, the probability of mortality increased
more sharply for male lobsters than for female lobsters
(Fig. 8).
Discussion
Logbook data from the SARLF show that over the last
five years approximately 240,000 lobsters have been
killed in traps each year. Although there are numerous
predators of trapped lobsters — such as seals, conger eels,
and several species of finfish — the impacts of these taxa
appear to be minor compared to the effects of predation
by O. maorum. The field-sampling program conducted in
the SZ in 2001-02 suggested that over 98% of within-
trap mortality was attributable to O. maorum. Although
the sampling program was spatially and temporally
restricted, this finding, in conjunction with the strong
correlations between annual, seasonal and spatial trends
in the CPUE0 and M, , clearly demonstrates that O.
maorum is the major predator of lobsters in SARLF
traps.
The results of this study suggest that about 4</r of the
total annual catch of the SARLF is lost to predation
by O. maorum in traps. Mortality rates attributable to
octopuses in other Australian lobster fisheries range
from \% in the Western Australian fishery for Panulirus
cygnus1 (O. tetricus) to 5% in the Tasmania!) fishery for
Brock and Ward: Octopus bycatch and lobster mortality in the South Australian rock lobster fishery
437
Table T
Results of the general linear model of factors that affect lobster mortality (all data log transformed) for (A) southern zone
(r2=0.62), (B) northern zone (r2=0.38l.
Source
df
Squares
Mean square
.F-value
P>F
Model
Error
Corrected total
5319
483.961
489,280
314,536
194,140
508,677
59.13
0.401
147.41
;0.0001
Source
df
Type-3 SS
Mean square
F- value
P>F
License
MFA
Year
MFAxYear
Month
Effort
Lobster catch
Depth
Octopus
Soak-time
Soak-time x Year
License x Year
License x Month
Year x Month
Soak-time * Month
245
3
17
51
6
1
1
1
1
1
17
3415
1460
94
6
49158.1
9.6
2494.6
233.0
2830.7
229.6
6728.7
1335.0
35930.5
6842.1
286.9
53019.8
5900.2
3760.4
310.2
200.6
3.2
146.7
4.7
471.8
229.6
6728.7
1335.0
35930.5
6842.1
16.9
15.5
4.0
40.0
51.7
500.2
8.0
365.8
11.6
1176.1
572.4
16773.4
3327.9
89568.8
17056.1
42.1
38.7
10.1
99.7
128.9
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
H
Source
df
Squares
Mean square
F-value
P>F
Model
Error
Corrected total
2159
148,731
150,890
39,217
64,713
103,931
18.17
0.435
41.75
<0.0001
Source
df
Type-3 SS
Mean square
F-value
P>F
License
MFA
Year
MFAxYear
Month
Effort
Lobster catch
Depth
Octopus
Soak-time
Soak-time x Year
License x Year
License x Month
Year x Month
Soak-time x Month
95
4
17
68
7
1
1
1
1
1
17
1287
553
95
6
3361.5
174.8
241.2
175.4
317.3
27.1
1299.7
391.3
6305.1
210.8
117.7
7275.6
1170.7
275.9
2.8
35.4
43.7
14.2
2.6
45.3
27.1
1299.7
391.3
6305.1
210.8
6.9
5.7
2.1
2.9
0.5
81.3
100.4
32.6
5.9
104.2
62.3
2987.2
899.3
14491.0
484.4
15.9
13.0
4.9
6.7
1.1
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.3743
438
Fishery Bulletin 102(3)
A depth D soak time
1 ♦ 41
0 8 ■
0.6 -
3 -
*
2-
* •
»
</> 0 4-
***■" '''»»• | M | [J, 1 "
♦
0)
3 0.2 -
■DO 50 100 150 0 5 10 15
-g Depth (m) Soak time (days)
o
o O octopus D lobster
a 5 -,
10 i im
CO
a> 4 -
„♦»♦♦* 8.
^^^^
QC
3 -
♦ ♦**
yS^
2 -
♦ *#
f
♦
♦■
1 -
♦ 2 -,
0 5 10 15 20 0 200 400 600 800
No. of octopuses No. of lobsters
Figure 6
The relative number of dead lobster as a function of lAl depth, iBi soak-time, (C) number of
octopus, and (D) no. of lobsters for the southern zone. Error bars are ±SD of mean.
<D
or.
1 -<
A depth
0 8 -
♦
0.6 -
*
*
0.4 -
"*"~*
0.2 -
50 100 150
Depth (m)
octopus
5
4 -
3
2
1 H
.♦♦
♦ ♦
*♦<
- 1 1 1 1
5 10 15 20
No. of octopuses
4 -,
3.5
3 -
2.5 -
2
1.5 -
1
0 5
0
B
soak time
5 10
Soak time (days)
15
I) lobster
10 -,
100 200 300
No. of lobsters
400
Figure 7
The relative number of dead lobster as a function of (A) depth. (Bl soak-time, (C) number of
octopus, and i Di number of lobsters for the northern zone. Error bars are ± SD of mean.
Brock and Ward: Octopus bycatch and lobster mortality In the South Australian rock lobster fishery 439
0.4 -I
0.35 •
1 °3'
/
2 0 25-
o
°- 0 2 ■
>.
1 0 15-
t:
o 0 1-
0 05 -
male j$
J2jMlsfrm*F*F^^ female
60 80 100 120 140 160 180 200
Carapace length (mm)
Figure 8
Size-dependent mortality of lobsters with respect to
sex.
J. edwardsii (O. maorum), (Gardener5), and a localized
study in the New Zealand fisheries for J. edwardsii
(O. maorum) found the proportion of the lobster catch
killed by octopus to be as high as 10% (Ritchie6). The
estimates of lobster mortality from these other studies
should be treated with caution however because the cur-
rent study is the only one that documents within-trap
lobster mortality from a fishery-wide data set.
The general linear modeling approach that we used to
determine the factors associated with ML has some limi-
tations. For example, the logbook data for the SARLF,
like the monitoring data for most other fisheries, are
not completely independent, and interdependence among
observations can bias estimates of parameters. Simi-
larly, some of the factors in the model, notably CPUEL
and CPUE0 are partially correlated. In addition, the
large number of observations and degrees of freedom
tend to make most factors significant. We considered
all of these issues when interpreting the results of the
analyses and used the mean square (MS) values to rank
the importance of factors.
In both zones, inter- and intra-annual fluctuations
in ML largely reflect the effects of CPUE0 and CPUEL.
The broad trends in annual CPUE0 have largely cor-
responded to those for M, with peaks in both generally
synchronous in both fishing zones. In the SZ, the gen-
eral increase in ML since 1983 appears to result from
the increase in CPUE, which has more than doubled
over this period. This assessment is supported by catch-
rate data from individual MFAs. The two MFAs in the
SZ that have had the greatest increases in CPUEL over
the last 5 years (56 and 58) have also had the highest
5 Gardener, C. 2002. Personal commun. Tasmanian Aqua-
culture and Fisheries Institute, Private Bag 49, Hobart,
Tasmania 7001.
6 Ritchie. L. D. 1972. Octopus predation on trap-caught rock
lobster — Hokianga area, N.Z. September-October 1972. New
Zealand Marine Department. Fisheries Technical Report 81,
40 p. (Available from Ministry of Fisheries, 101-103 The
Terrace, Wellington, New Zealand, 1020.]
corresponding increase in ML. Increases in CPUEL are
likely to elevate ML by both increasing the probability
of octopus encountering traps containing lobsters and
the number of lobsters in traps entered by octopus.
However, ML is also positively correlated with soak-
time, especially in the SZ. This finding is consistent
with patterns observed in the New Zealand fishery for
J. edwardsii6 and reflects the increased opportunities
for octopus predation when pots containing lobsters
remain in the water for longer periods. In the SZ, fish-
ermen return to port each day and choose to fish or not
to fish each day according to factors such as weather
and price; therefore, although a 24-h soak period is still
most common, soak times can range from one to five
days. In the NZ, fishermen remain at sea for extended
periods and consequently soak times longer than 24
hours are rare.
There was considerable variation in the fishery data,
especially in the southern zone. It is likely that much
of this variation is related to the large geographical
extent of the fishery as opposed to fishing practises.
Across the fishery lobster growth rates and subsequent
catch rates vary greatly (McGarvey et al., 1999a). For
example, since 1991, the CPUEL in MFAs 56 and 58
have been twice those of MFAs 51 and 55 in the SZ.
Although the variation in CPUE0 between the zones
has been similar, the higher variability in CPUEL in
the SZ is reflected in the variation in ML.
Data spanning 17 years and covering about 50.000
km2 represent one of the few long-term and large-scale
data sets on the distribution and abundance of an octo-
pus species (Hernandez-Garcia et al., 1998: Quetglas et
al., 1998). The paucity of octopus studies on these scales
reflects the logistical constraints of fishery-independent
surveys of octopus populations and the poor and incon-
sistent methods generally used to record fishery catch
and effort data (Boyle and Boletsky, 1996). The few data
that are available on the distribution patterns of octo-
pus have been obtained mainly from small commercial
fisheries and CPUE(, has been included as a measure
of relative abundance (Defeo and Castilla, 1998; Her-
nandez-Garcia et al., 1998). This approach has proven
useful, but several potential biases must be considered
when CPUE0 data are being interpreted: these include
1) changes in fishing methods and efficiency over time;
2) the distribution pattern (e.g., random or aggregated)
of the species under consideration; and 3) spatiotempo-
ral fluctuations in catchability (Richards and Schnute,
1986; Rose and Kulka, 1999). There are several reasons
why the data from the SARLF may provide a useful
measure of the relative abundance of octopus over these
spatial and temporal scales. Most importantly, the ba-
sic unit of effort in the fishery, the trap, has remained
unchanged since 1983. Furthermore, although O. mao-
rum is retained as bycatch and kills J. edwardsii in
traps, it is neither targeted nor avoided by fishermen,
and fishing effort is thus relatively independent of its
distribution patterns because the economic effects of
both the sale of octopus bycatch and the costs of lobster
predation are relatively small compared to the primary
440
Fishery Bulletin 102(3)
economic driving force for the fishery, the lobster catch
rates, and because the catch rates of octopus are dif-
ficult to predict. In addition, O. maorum is a solitary
animal that tends to be dispersed randomly throughout
areas of suitable habitat (Mather et al., 1985).
The higher total catches and catch rates of both lob-
ster and octopus in the SZ, compared to the NZ, prob-
ably reflect the more extensive reef habitat and more
intense nutrient-enrichment upwelling in this portion
of the SARLF (Lewis, 1981). There have been large
interannual fluctuations in CPUE0 in both zones since
1983. Such fluctuations in population size are common
among other cephalopods, especially squid, and may
result from life history strategies that are characterized
by rapid growth, short lifespan (<two years) and almost
universal mortality after a single spawning event (Boyle
and Boletsky, 1996). Despite these fluctuations, CPUE0
has not declined noticeably in any MFA since 1983,
which suggests that octopus mortality from fishing is
consistent with little impact on octopus populations
since the advent of fishing. This observation and the
poor relationship between octopus catches and effort re-
fute the belief of some SARLF fishermen that incidental
fishing mortality acts to control octopus abundance.
This study, however, did confirm the view of fisher-
men that larger lobsters are killed more commonly by
octopus than are smaller ones. This effect was most
evident for male lobsters, which grow to larger sizes
than females. There could be several reasons for the
size-dependent mortality rates for rock lobsters. For
example, octopus could actively select larger prey, or
large lobsters could be captured more easily than small
lobsters in traps by octopus. Because large lobsters can
be worth more and produce more eggs than smaller
lobsters, the increased mortality rates of large lobsters
suggest that the total economic and ecological impacts
of octopus predation in the SARLF are greater than
indicated by the absolute number of lobsters killed.
Octopus predation of lobsters in traps is a significant
problem in the SARLF. However, the economic effects
vary between the zones. In the quota-managed SZ, ad-
ditional lobsters are harvested to replace those killed
in traps, which increases the time and costs of catch
quotas, and imposes an impact on lobster abundance.
In the input-controlled NZ, where there is no direct
restriction on the quantity of lobsters taken, lobsters
killed in traps represent both a direct economic loss
and an impact on lobster abundance.
Like most fisheries for spiny lobsters, the SARLF is
close to being fully exploited. Reducing rates of octopus
predation provides one option available for increas-
ing the value of the fishery. Some minor reductions in
lobster mortality may be achieved by minimizing soak-
times, especially in the SZ. More significant reductions
in the rates of within-trap lobster mortality may be
achieved by redesigning lobster traps (Brock et al.4).
Acknowledgments
This research was funded jointly by the Fisheries
Research and Development Corporation, South Austra-
lian Rock Lobster Advisory Council, South Australian
Research and Development Institute (Aquatic Sciences),
and the University of Adelaide. The authors thank Thor
Saunders for his support and assistance during the
research. Jim Prescott provided advice for extracting
data from the South Australian Rock Lobster Database.
Yongshun Xiao provided statistical advice and assisted
with the numerical modeling.
Literature cited
Boyle, R. R, and S. V. Boletsky.
1996. Cephalopod populations: definition and dynam-
ics. Phil. Trans. R. Soc. Lond. 351:985-1002.
Defeo, O., and J. C. Castilla.
1998. Harvesting and economic patterns in the artisanal
Octopus mimus (Cephalopodal fishery in a northern
Chile cove. Fish. Res. 38:121-130.
Hernandez-Garcia, V., J. L. Hernandez-Lopez, and J. J. Castro.
1998. The octopus lOctopus vulgaris) in the small-scale
trap fishery off the Canary Islands (Central-East
Atlantic). Fish. Res. 35:183-189.
Lewis, R. K.
1981. Seasonal upwelling along the south-eastern coast-
line of South Australia. Aust. J. Mar. Freshw. Res.
32:843-854.
Mather. J. A., S. Resler, and J. Cosgrove.
1985. Activity and movement patterns of Octopus
dofleini. Mar. Behav. Physiol. 11:301-314.
McGarvey, R., G. Ferguson, and J. H. Prescott.
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441
Abstract — Management of coastal
species of small cetaceans is often
impeded by a lack of robust estimates
of their abundance. In the Austral
summers of 1997-98, 1998-99, and
1999-2000 we conducted line-transect
surveys of Hector's dolphin iCepha-
lorhynchus hectori) abundance off the
north, east, and south coasts of the
South Island of New Zealand. Survey
methods were modified for the use of
a 15-m sailing catamaran, which was
equipped with a collapsible sighting
platform giving observers an eye-
height of 6 m. Eighty-six percent of
2061 km of survey effort was allo-
cated to inshore waters (4 nautical
miles [nmi] or 7.4 km from shore),
and the remainder to offshore waters
(4-10 nmi or 7.4-18.5 km from shore).
Transects were placed at 45° to the
shore and spaced apart by 1, 2, 4, or 8
nmi according to pre-existing data on
dolphin density. Survey effort within
strata was uniform. Detection func-
tions for sheltered waters and open
coasts were fitted separately for each
survey. The effect of attraction of dol-
phins to the survey vessel and the
fraction of dolphins missed on the
trackline were assessed with simul-
taneous boat and helicopter surveys
in January 1999. Hector's dolphin
abundance in the coastal zone to 4
nmi offshore was calculated at 1880
individuals (CV=15.7%, log-normal
95% 01 = 1384-2554). These surveys
are the first line-transect surveys for
cetaceans in New Zealand's coastal
waters.
Small-boat surveys for coastal dolphins:
line-transect surveys for Hector's dolphins
(Cephalorhynchus hectori)
Stephen Dawson1
Elisabeth Slooten2
Sam DuFresne'
Paul Wade3
Deanna Clement2
1 Department of Marine Science
University of Otago
340 Castle Street
Dunedm, New Zealand
E-mail address stevedawsoofastonebow otago acnz
•"Zoology Department
University of Otago
340 Castle Street
Dunedm, New Zealand
3 National Marine Mammal Laboratory
National Marine Fisheries Service
7600 Sand Point Way NE
Seattle, Washington 98115
Manuscript submitted 27 April 2003
to Scientific Editor's Office.
Manuscript approved for publication
3 March 2004 by the Scientific Editor.
Fish. Bull. 201:441-451 (2004).
Several international workshops on
cetacean bycatch problems have stated
that a key impediment to the conser-
vation of coastal and riverine small
cetaceans is the lack of quantitative
data on abundance (e.g., IWC, 1994).
An important reason for this lack of
data is that line-transect surveys are
often conducted from large (>50 m)
vessels (e.g. Barlow, 1988) and hence
are extremely expensive ($US 10,000/
day). Such costs usually put high-qual-
ity surveys such as those conducted
for harbor porpoise in the U.S. (e.g.,
Carretta et al„ 2001) beyond the reach
of less affluent nations. The need for
abundance estimates is especially
great for the coastal and riverine spe-
cies found in Asia, Africa, Australasia,
and South America (Table 1). Several
of these species have apparently small
populations and restricted distribu-
tions, and all suffer from being taken
as bycatch in fishing gear, principally
in gill nets (IWC, 1994). In addition, it
is difficult or impossible for large ves-
sels to work close to shore, in shallow
waters, where some of these species
are most common.
The work described in this contri-
bution had two aims: 1) to adapt ship-
based line-transect methods (e.g.,
Barlow, 1988) to a 15-m catamaran,
and 2 ) to provide an updated estimate
of the abundance of Hector's dolphin
(Cephalorhynchus hectori). Hector's
dolphin, a small delphinid found
only in the inshore waters of New
Zealand, is subject to bycatch in gill
nets throughout its range (Dawson et
al., 2001). At least in the Canterbury
region, and off the North Island west
coast, recent catch levels are clearly
unsustainable (Dawson and Slooten,
1993; Martien et al., 1999; Slooten et
al., 2000; Dawson et al.. 2001). Stud-
ies of mt-DNA indicate that the very
small North Island population is dis-
tinct and that there are at least three
separate populations in South Island
waters (Pichler et al., 1998; Pichler
and Baker, 2000; see also Baker et
al., 2002). At the time of the present
study the only quantitative population
estimate was from a strip-transect
survey conducted in 1984-85 (Daw-
son and Slooten, 1988), in which the
offshore distribution, as well as the
442
Fishery Bulletin 102(3)
proportion of dolphins detected within the strip, was
estimated. A current, more robust estimate is needed
for management. This study describes line-transect
boat surveys conducted to estimate Hector's dolphin
abundance on the north, east, and south coasts of the
South Island of New Zealand.
Figure 1
Photograph of the observer platform on the catamaran Cat
Materials and methods
Vessel choice and field methods
Displacement catamarans are inherently suitable for
inshore surveys because of their resistance to rolling
and their ability to sustain reasonably high cruising
speeds with modest power. We based our
surveys from a 15.3-m sailing catama-
ran (RV Catalyst), which is powered by
two 50-hp diesel engines, and cruises
at 9-10 knots while using <10 liters of
fuel per hour. We fitted a collapsible
aluminum sighting platform (~6 m eye
height; Fig. 1) to increase the resolution
with which observers could measure the
downward angles to sightings (see Lerc-
zak and Hobbs, 1998. for details) and to
allow the observers to see animals far-
ther away. The surveys were conducted
with a crew of six (five observers, one
skipper).
Three people stood on the platform at
any given time; one scanned the surface
waters to the right of the platform, and
the other scanned to the left, and a third
person (the recorder) recorded sightings
dictated by the observers. Sightings
made by the recorder were not used in
our analyses because his or her sight-
\Jj ^ ing effort was unavoidably uneven (the
recorder could not make sightings while
recording another sighting). The record-
er did not point out sightings to observ-
ers. Observers and data recorder rotated
alyst
Table 1
Examples of coastal and riverine species of special conservation concern.
Common name
Scientific name
Habitat
Vaquita
Phoeoena sinus
Northern Gulf of California
Chilean dolphin
Cephalorhynchus eutropia
Inshore coastal Chile
Hector's dolphin
< 'ephalorhynchus hectori
Inshore coastal New Zealand
Commerson's dolphin
Cephalorhynchus commersoni
Inshore coastal Chile, Argentina, Falkland Is, Kerguelen Is.
Heaviside's dolphin
( 'ephalorhynchus heavisidii
Inshore coastal South Africa and Namibia
Peale's dolphin
Lagenorhynchus australis
Coastal Chile. Argentina, Falkland Is.
Finless porpoise
Neoph ocoena phocaenoides
Coastal and riverine Asia and Indonesia
Indo-Pacific humpbacked
Sousa chinensis
Inshore tropical and estuarine habitats in western Pacific
dolphins
and Indo Pacific
Burmeister's porpoise
Phoeoena spinipinnis
Coastal Chile. Argentina, Uruguay. Brazil
Franciscana
Pontoporia blainvillei
Coastal Brazil and Argentina
Indus river dolphin
Platanista minor
Indus River
Ganges river dolphin
Platanista gangetica
Ganges, tiramaputra. Karnphuli, Meghna rivers
Boto
Inia geoffrensis
Amazon River
Tucuxi
Solatia fluviatilus
Coastal and estuarine Atlantic Central and South America
Dawson et al.: Line-transect surveys of Cepha/orhynchus hectori
443
every 30 minutes to avoid fatigue. Although Hector's
dolphins are easily identified from other species, and
group size is typically small (usually 2-8; Dawson and
Slooten, 1988), in order to maintain even sighting effort
on both sides of the trackline, observers did not confer
during a sighting. Sighting information was entered into
a custom-written program on a Hewlett-Packard 200LX
palmtop computer on the sighting platform. Data record-
ed included horizontal sighting angle, downward angle
to sighting (in reticles), species, group size, orientation
of the animals when first sighted, depth, Beaufort sea
state, swell height, glare, GPS fix, date, and time. The
program also recorded survey effort by storing a GPS fix
every 60 seconds. Weather conditions were recorded at
the start of field effort, and whenever they changed.
Observers used reticle- and compass-equipped Fujinon
7x50 (WPC-XL) binoculars to make sightings and to
measure the downward angle from the land, or horizon,
to the sighting. If the former, the corresponding dis-
tance to land was measured with RADAR (Furuno 1720
model), or, if within a few hundred meters of shore,
with a Bushnell lightspeed laser rangefinder (tested
accuracy ±1 m from 12 to 800 m). We calibrated the ac-
curacy of the RADAR by comparison with transit fixes
and laser rangefinder measurements. Sighting angles
were recorded by using angle boards (see Buckland et
al., 1993) in the first season, and thereafter with the
compasses in the binoculars. There were no ferrous
metals or significant electrical fields within 6 m of the
sighting platform.
Navigation was facilitated by the use of a Cetrek 343 GPS
chartplotter with digitized C-MAP charts onto which
transect waypoints were plotted. Depths were measured
with a JRC JFV-850 echosounder (at 200 kHz).
At the start of each survey, several days were spent
training observers at Banks Peninsula, where sighting
rates are high. Training continued until we gained
about 100 sightings (data gathered in this period were
not used in the analyses). An observer manual (avail-
able from authors) specified scanning behavior and
recording methods. To ensure a wide shoulder on the
histograms of perpendicular sighting distances, observ-
ers were instructed to concentrate their effort within
45° of the trackline and to spend less time searching
out to 90°. Observers spent about 85% of the time scan-
ning with binoculars. Regular scans with the naked eye
minimized fatigue and reduced the chance of missing
groups close to the boat. To promote consistency, observ-
ers were asked to re-read the manual at least once a
week throughout the survey.
While the survey was underway, exploratory data
analyses were undertaken to assess data quality. These
analyses showed that in the early stages of the first sur-
vey, observers were rounding angles of sightings close to
the trackline to zero. The use of the angle boards was
modified to minimize this problem, and they were not
used in subsequent surveys. The data from these early
lines were discarded and the survey lines repeated.
Survey effort was restricted to sea conditions of Beau-
fort 3 or less and swell heights of <2 meters. Transect
lines were run down-swell and down-sun to minimize
pitching and effects of glare. Deviations of up to 10° from
the intended course were made if needed to further re-
duce pitching or glare. The inshore end of each line was
surveyed to just outside the surf zone on open coasts,
or until a 2 m depth was reached, or to within 50 m
of rocky shores. All surveys were conducted in passing
mode to minimize the extent of vessel attraction.
Line-transect data were collected in three surveys in
three consecutive summer seasons, each focussing on
a particular coastal area (Fig 2; Motunau to Timaru,
5 January-21 February 1998; Timaru to Long Point,
9 December 1998-16 February 1999; Farewell Spit to
Motunau, 17 December 1999-28 January 2000).
Survey design
In order to obtain a clear picture of density and to mini-
mize variance in encounter rate, Buckland et al. (1993)
recommend placing transects across known density
gradients. Because short-distance, alongshore move-
ments are well-known for Hector's dolphins (Slooten and
Dawson, 1994: Brager et al., 2002) and the dolphins'
density declines sharply with distance offshore (Dawson
and Slooten, 1988), transects were placed at 45° to the
coast. On curved coastlines (within strata) we divided
the coastline into blocks, drew an imaginary baseline
along the coast, and placed lines at 45° to that baseline.
The starting point of the first line along the baseline
was decided randomly; thereafter lines were spaced at
regular intervals according to the sampling intensity
required in that stratum (Fig. 2). Within harbors we
placed lines at 45° to an imaginary line down the center
of the harbor (Fig. 3). The aim of this scheme was to
ensure that, within a stratum, any one point had the
same chance of being sampled as any other.
Survey effort was stratified according to existing data
on distribution, obvious habitat differences, and areas
of intrinsic management interest. In summer, very few
Hector's dolphins are seen beyond four nmi from shore
(Dawson and Slooten, 1988); therefore most sampling
effort was placed in this inshore zone (i.e. 45° lines at
2-, 4-, or 8-nmi spacings, approximately proportional to
density as determined from previous surveys). Within
harbors, transect spacings were either one or two nau-
tical miles. In the offshore zone (from 4 to 10 nmi) we
expected very low densities, and therefore used sparse
transect spacing (-30 nmi apart). It was not our inten-
tion to estimate density in this offshore zone. A subse-
quent aerial survey was found to be better suited for
this purpose (Rayment et al.1).
Our goal was to estimate effective half strip width
(ESW) separately for strata with different exposure
to wind and swell. Hence, in each survey we aimed to
gain sufficient sightings to estimate ESW separately for
harbors or protected waters, and open coasts. To reach
1 Rayment, W., E. Slooten, and S. M. Dawson. 2003. Unpubl.
data. Department of Marine Science, Univ. Otago, P.O. Box
56, Dunedin, New Zealand.
444
Fishery Bulletin 102(3)
172 55'S
N
/ /,
t
X// -' • "'
> '^\\ /
^ -M--
^
(\\ o
'>&°x£ W
„ov- *
Akaroa
(^ yp%%y\
lx^fv>^
^ *#3?
(^NS. o^Jy
J3_5P!§ _>_ -\febO - .2*C -
x/^
/\\ / /A
^ J^-^j,
6 It it
\J\l\
-
wrr
-_T- ; ■
1 km
Figure 2
Map of New Zealand's South Island, showing transect lines and sightings
of Hector's dophins (dots) 1997-2000.
Figure 3
Example of transect layout in harbors 1 1997-
98 Akaroa Harbor transect lines and sight-
ings, showing three replicates I.
Buckland et al.'s (1993) target of 60-80 detections for
robust ESW estimation, in the 1997-98 survey we con-
ducted replicate surveys (with a new set of lines each
time) in the harbors and bays stratum (e.g., Fig. 3).
Low sighting rates in the area surveyed in 1999-2000
would have required unrealistic effort levels to reach
this target; therefore we gained extra sightings from
areas with the same exposure but higher sighting rates
(e.g., data used to calculate ESW for the Marlborough
Sounds were supplemented by data gathered in Akaroa
Harbour by the same observers, in the same summer).
Hence different sample sizes were available to estimate
density and ESW (Table 2). Because observers changed
between surveys, we did not pool sightings across years
for estimating ESW. Strata areas were measured from
nautical charts with a digital planimeter.
Data analysis
Within each stratum, Hector's dolphin abundance (Ns)
was estimated as (Buckland et al., 1993):
Ns=^^. (1)
2LESW
where A = size of the study area;
n = number of groups seen;
S = expected group size;
L = length of transect line surveyed, and
ESW = the effective half strip width.
Because there was no significant relationship between
group size and detection distance, expected group size
was estimated as a simple mean group size.
Dawson et al.: Line-transect surveys of Cephalorhynchus hecton
445
Table 2
Survev effort by stratum.
Number of sightings is the total number made before
truncation
and quality
auditing
see "Vessel
choice and field methods").
Survev effort
No. of
Sightings
Survey zone
Stratum
(km)
sightings
per km
Motunau to Timaru
Banks Peninsula harbors and bavs
223
89
0.399
(1997-98)
Banks Peninsula Marine Mammal Sanctuary (BPMMSi
265
66
0.249
(excluding open coasts)
<4 nmi offshore, to the north and south of BPMMS
174
21
0.121
Offshore (4-10 nmi )
89
4
0.045
Timaru to Long Point
Timaru-Long Point (excluding Te Waewae Bay)
336
13
0.04
(1998-99)
Te Waewae Bay
101
14
0.14
Offshore (4-10 nmi)
106
0
0
Motunau to Farewell Spit
Farewell Spit-Stephens Island
120
0
0
(1999-20001
Marlborough Sounds (including Queen Charlotte Sound i
205
3
0.015
Cape Koamaru-Port Underwood
68
0
0
Cloudy Bay and Clifford Bay
89
13
0.146
Cape Campbell-Motunau
192
0
0.026
Offshore (4-10 nmi I
93
2
0.022
Using the program Distance 3.5 (Research Unit for
Wildlife Population Assessment, University of St. An-
drews, UK), we fitted detection functions to perpendicu-
lar distance data to estimate ESW (note that this value
is derived directly from f(0)). Akaike's information crite-
rion (AIC) was used to select among models fitted to the
data. Models and adjustments were the following: haz-
ard/cosine, hazard/polynomial, half-normal/hermite, half-
normal/cosine, uniform/cosine (Buckland et al., 1993).
Following Buckland et al. (1993), perpendicular sighting
distances were truncated to eliminate the farthest 5% of
sightings and binned manually for /10) estimation.
The coefficient of variation (CV) for the abundance es-
timate was calculated from the coefficients of variation
of each variable element in Equation 1 above (Buckland
et al., 1993):
CV(N5)=JcV-{)]) + CV2(S) + CV2[ESW).
(2)
The CV(n) was estimated empirically as recommended
by Buckland et al. (1993):
CV{n) =
vardi)
(3)
(4)
where var(«) = /.£/,<«, II,-n I L): I ik-\).
lj = the length of transect line i;
nj = the number of sightings on transect i; and
k - number of transect lines.
CV(S) was estimated from the standard error of the
mean group size. CVlESW) was estimated with the
bootstrapping option in Distance 3.5 software. This
process incorporates uncertainty in model fitting and
model selection (Buckland et al., 1993).
Measuring the effect of attraction
Conventional line-transect estimates can be biased as
a result of responsive movement of the target species
and animals on or near the trackline being missed by
observers (Buckland et al., 1993). Buckland and Turnock
(1992) presented a method using co-ordinated boat and
helicopter surveys to quantify and adjust for the com-
bined effects of responsive movements of dolphins to the
boat and to eliminate the bias from observers failing to
see animals on or near the trackline. Their approach is
better suited to the restricted space available on small
boats than to a dual-platform approach (Palka and Ham-
mond, 2001). Additionally, sightings can be made much
farther ahead (reducing the possibility that the animals
have already responded), and the two sighting teams
are totally isolated from each other. For these reasons
we adapted Buckland and Turnock's (1992) approach in
our trials of 1998-99.
Simultaneous boat-and-helicopter surveys were car-
ried out to the south of Banks Peninsula, predominantly
between Birdlings Flat and the mouth of the Rakaia
River. This area was chosen because it displayed rep-
resentative and varying densities.
A Robinson R22 helicopter with pilot and one observer
(ES) followed a zig-zag flight path approximately 1.5 km
in front of the boat, traveling out to 1000 m on either
side of the vessel's trackline at a height of 500 ft ( 152 m)
(Fig. 4). To aid the process of tracking sightings from
the air, sighting positions were marked with Rhodamine
dye bombs.2 The position of the helicopter in relation
Dye bombs consisted of a tablespoon of Rhodamine dye in a
paper cup 2/3 filled with sand. An additional (empty) paper
cup was taped upside down on top of the first cup with
paper-based masking tape. On impact the two cups broke
apart, releasing the sand+dye mix into the water.
446
Fishery Bulletin 102(3)
Figure 4
Schematic diagram of simultaneous helicopter-and-boat
surveys for Hector's dolphins south of Bank Peninsula,
South Island, New Zealand.
to the boat was determined with the boat's RADAR.
The absolute position of the boat was determined to
an accuracy of 2-5 m by differential GPS (Trimble
GeoExplorer; postprocessed). Distances to land were
obtained at the time of sighting with RADAR or during
analysis by using GIS coastline data and the computer
program "SDR Map" (Trimble Navigation, Christchurch,
New Zealand).
Boat observers followed our standard sighting pro-
cedures (see above). On most occasions the helicopter
was outside the field of view of the observers' binoculars
because the observers were scanning the water surface,
and the helicopter was well above what the observers
could sec through the binoculars. When it was within
their view, observers made a conscious effort to remain
unbiased by the movements of the helicopter. On mak-
ing a sighting, the helicopter observer informed an
independent observer located in the cabin (observers
on the platform could not hear communications from
the helicopter observer and vice versa). The helicopter
then hovered briefly above the sighting while a range
and bearing in relation to the boat was taken by RA-
DAR. The helicopter then ceased hovering but tracked
the group of dolphins either until the boat observers
had sighted the group, or the group had passed abeam
of the boat. A second range and bearing were then
taken. Sightings lost by the helicopter observer during
tracking were discarded in our analyses. The indepen-
dent observer, in liaison with the helicopter observer
and boat observers, determined whether the sighting
was a duplicate (i.e., made by both helicopter and boat
observers) by using information on location and group
size. These decisions were checked again in analysis by
inspection of plotted locations of sightings made from
either platform or both platforms.
Following the approach of Buckland and Turnock
(1992), let
gjy) = the probability that a group detected from the
helicopter at perpendicular distance y from the
trackline of the ship is subsequently detected
from the ship;
fs(y) = SsW'H' with ,» = |M "< y)<b
(area under helicopter detection function ).
w - truncation distance for perpendicular distances
y;
nh = number of helicopter detections;
ns = number of ship detections;
nhs = number of detections made from both platforms
(duplicate detections);
f/Jy1 = probability density function fitted to helicopter
detection distances;
f'hJy' = probability density function fitted to duplicate
detection distances as recorded from the heli-
copter;
fix) = probability density function fitted to perpen-
dicular distances recorded from the ship;
L = length of transect line.
A conventional estimate of density of groups, assuming
no responsive movement andglO) = 1 (all animals on the
trackline seen with certainty) is calculated as
IK
nj(0)
2L
(5)
A corrected estimate, allowing for responsive movement
and including an estimate of g(0) is given by
where /s(0) = —
IX
gs(0)
»,./,(())
214(0)'
\™gAy)d)
Ja
",/ 1 ) I
(6)
(7)
(8)
Dawson et al.: Line-transect surveys of Cephalorhynchus hectori
447
A correction factor for abundance estimates of Hector's
dolphin groups can be estimated by
c = DL ID,.
(9)
Using Distance 3.5, we fitted a half-normal model with
cosine adjustments to estimate /10). The half-normal
model was fitted to helicopter data to estimate /",,(0) and
the uniform model with cosine adjustments was used to
estimate fhs(0)- All were selected by using AIC. Potential
model choices were the following: hazard/cosine, hazard/
polynomial, half-normal/cosine, half-normal/hermite
and uniform/cosine (Buckland et al., 1993). Truncation
distance was 640 m for boat sightings, and 1000 m for
helicopter and duplicate sightings. To ensure that only
high-quality data were used to estimate effective half
search widths, sightings for which range (radial distance)
was estimated by eye and those made during Beaufort
sea state >2 were removed before f(0) estimation.
The error for the correction factor (c) was estimated
by bootstrapping on transect lines and applying the
estimation procedure to each of 199 bootstrap data sets.
The standard deviation of the bootstrap estimates was
used as the standard error of c.
Ideally, the correction factor would be estimated sepa-
rately for each survey from separate sets of boat-and-he-
licopter trials conducted in areas of representative den-
sity. Financial and logistical constraints prevented this;
therefore the correction factor estimated in 1998-99 was
applied to each of the line-transect surveys reported in
the present study. We note that this is not uncommon
(e.g., Carretta et al., 2001).
Unbiased abundance estimates were calculated by
N,
"■N,
(10)
The CVs of the corrected abundance estimates (NL,)
were calculated with the following equation (Turnock
et al„ 1995):
CV(NU) = JCV2(£) + CV2(NS),
where CV(c)
5£(r)
(11)
(12)
Upper (Nuc) and lower (NLC) 95% confidence inter-
vals for Nv were calculated by using the Satterthwaite
degrees of freedom procedure outlined in Buckland et al.
(1993). This procedure assumes a log-normal distribu-
tion of Nc, using
NLC = NL. I C, and
Nuc = NUC,
where C = exp \ r, ( 0.025 ) log, 1 +
-[CV(N, >]"
(13)
(14)
The Satterthwaite degrees of freedom (df) for corrected
abundance estimate confidence intervals were calcu-
lated by
Table 3
Summary of variables required for corr
ection factor
(boat-and-helicopter trials)
Parameter
Estimate
Length of transect. L (km)
308
Truncation distance, w (km)
1.0
Number of helicopter detections, nh
58
Number of ship detections, ns
126
Number of duplicate detections, nhs
33
ESW of helicopter (km)
0.532
ESW for duplicates ( km I
0.342
Apparent ESW of boat (kmi
0.268
Apparent density estimate ( groups/km2 1
0.7631
Corrected density estimate (groups/km2)
0.3839
Boat detection probability "near" trackline
0.8861
Correction factor (c)
0.5032
Standard error, SE(c)
0.0912
df=
CV\N, )
Cl'V) CV\NS)
(15)
tf-1
dfs
where B is the number of bootstrap samples, and dfs is
the Satterthwaite degrees of freedom for the uncorrected
abundance estimate, Ns (see Buckland et al., 1993).
The CV of combined abundance estimates (Nai) was
computed by
SEUouih
J{SE\Nm
) + SE-(N,,) + ... + SE-iN.
«)}•
and
SEiloiah
CV{total) = -^-
N, (total)
(16)
(17)
Results
The three line-transect surveys covered 2061 km of tran-
sect, and 231 sightings were used to estimate density
(Table 2). Sighting rates were highest around Banks
Peninsula (Table 3).
The simultaneous boat-and-helicopter surveys indi-
cated that boat observers missed 11.4% of the dolphins
on the trackline, but that strong responsive movement
towards the boat resulted in apparent densities twice as
high as they normally would be (Table 3). If the observ-
ers' attention was drawn to dolphin groups by the posi-
tion of the helicopter, the results of these trials would
be biased. This is unlikely, however, because several
groups sighted by the helicopter observer subsequently
passed within 200 m of the boat and were not seen by
observers. We saw no evidence that the dolphins were
affected by the helicopter.
Detection functions for boat-and-helicopter sightings
(Fig. 5, C and D) are relatively smooth in comparison
448
Fishery Bulletin 102(3)
A
0 50 100 150 200 250 300 350 400 450 500 550 600 650
1 0
08
06
04
02
n
a'
a
-v^^
0 100 200 300 400 500 600 700 800 900 1000
0 50 100 150 200 250 300 350 400 450 500 550 600
0 50 100 150 200 250 300 350 400 450 500 550 600
E
100 700 300 400 S00 600 700
SO 100 ISO 200 2S0 300 3S0 400 4S0 500
Perpendicular distance (m)
Figure 5
Histograms of perpendicular sighting distances, and their fitted detection functions as used to
estimate effective strip width. /; = number of sightings. The fitted model (hazard, cosine, uniform,
or half normal) and any adjustments to it (cosine or none) are given in brackets. (A) 1997-98 har-
bors and bays (n = 71; hazard/cosine); (B) 1997-98 open coasts U?=75; uniform/cosine); (C) 1998-99
open coasts (re=121; half-normal/cosine); (D) 1998-99 helicopter sightings (/i = 58; half-normal i; (Ei
1998-99 duplicate sightings (n = 33; uniform/cosine); (F> 1999-2000 harbors and sounds (ra=70;
hazard/cosinei; (G) 1999-2000 open coasts (n = 89; uniform/cosine).
Dawson et al.: Line-transect surveys of Cepha/orhynchus hecton
449
with those presented in Turnock et al. (1995). The de-
tection function for the duplicate sightings (Fig. 5E) was
more difficult to fit. Given the restricted sample size of
duplicates (n=33), this result is not unexpected.
In the 1998-99 Timaru to Long Point and 1999-2000
Motunau to Farewell Spit surveys, robust estimation
of ESW was facilitated by addition of extra sightings
gained under similar sighting conditions at Banks
Peninsula (Fig. 5, C, F, G). None of the three surveys
showed significant evidence of larger groups being seen
farther away. A broad pattern of abundance declining
to the north and south of the Timaru-Banks Peninsula
area is evident (Fig 2, Table 2). We made six sightings
on 288 km of offshore lines (4-10 nmi offshore), con-
firming that densities in this zone are low.
Information on sea state is usually collected dur-
ing boat line-transect surveys and sometimes used to
poststratify data (e.g.. Barlow, 1995). In our study this
was not advantageous, for three reasons. 1) We avoided
collecting data in conditions with whitecaps; therefore
only a few sightings were collected in Beaufort 3. Hence
variance estimates for this Beaufort state are large. 2)
Differences among Beaufort states for key parameters
such as sighting rate, average group size, and effective
strip width were small and showed overlapping confi-
dence intervals (we concede that statistical power is
low because of reason 1 stated above). Note that data
were pooled in the same way as for ESW estimation.
3) Stratification by Beaufort state does not produce
abundance estimates that match the zones of intrinsic
management interest (e.g., Banks Peninsula Marine
Mammal Sanctuary; Dawson and Slooten, 1993).
Discussion
The catamaran survey platform was a near-ideal vessel
for close inshore surveys. The sighting platform (Fig. 1)
was a relatively inexpensive modification (-US$2000)
that could be dismantled in about 10 minutes to allow
sailing. The vessel's minimal draught allowed coverage
of very shallow areas, which are an important part of the
distribution of Hector's dolphin and many other inshore
cetaceans. Although catamarans are inherently resistant
to rolling, pitching can be a problem when motoring
into a head sea or swell. We minimized this pitching by
arranging lines so they could be run down-swell. The 45°
placement of lines facilitated this reduction in pitching
because it provided two alternative sets of lines (at 90°
to one another). Further, these could be run inshore or
offshore, allowing a choice of four options.
A significant advantage of vessels with low running
costs is that the cost of training is low. We could af-
ford to spend 7-10 days training before each survey.
Further, waiting for weather to improve is inexpensive;
therefore one does not need to gather data in marginal
sighting conditions.
Estimated abundances (Table 4) were not significantly
different from those estimated in the 1984-85 strip
transect survey. Recent mark-recapture estimates of
dolphin abundance at Banks Peninsula in 1996, based
on photo-ID data, differed from the line-transect es-
timate for this area by less than 6% (Gormley, 2002;
Jolly-Seber model allowing different capture probabili-
ties between first and subsequent captures).
Our surveys confirmed previous work showing the
patchy nature of Hector's dolphin distribution (Dawson
and Slooten, 1988). Research at Banks Peninsula on
the alongshore range of individually identified dolphins
has shown a mean alongshore range of about 31 km
(SE = 2.43; Brager et al., 2002). Despite wide-ranging
surveys over 13 years, the most extreme sightings of
any individual were 106 km apart. These data indicate
very high site fidelity and indicate that even small-scale
discontinuities in distribution may be long lasting. Lack
of extensive movement along-shore, and hence limited
contact with neighboring populations, is likely to be
the mechanism by which Hector's dolphin has become
segregated into genetically distinct populations (Pichler
et al., 1998; Pichler and Baker, 2000).
The new abundance data, in combination with the
genetic data indicating segregation of Hector's dolphin
into four populations (Pichler and Baker, 2000) and
modeling work indicating that the species is in decline
in most of its range owing to bycatch in gill nets (Mar-
tien et al., 1999; Slooten et al., 2000), underscore the
urgent need for better information on bycatch rates.
Despite strong evidence of bycatch throughout the
species' range, observer coverage sufficient to estimate
bycatch has been achieved only in one area (Canter-
bury) for one fishing season (1997-98; Baird and Brad-
ford, 2000). During this season six Hector's dolphins
were observed entangled in commercial gill nets (a
further two were caught but released alive), resulting
in a bycatch estimate of 17 individuals (Starr3). One
mortality was observed in a trawl net, but very low
observer coverage prevented any calculations of overall
trawl bycatch (Baird and Bradford, 2000). No attempt
was made to assess bycatch in recreational gillnetting
during this period, but during a more recent summer
(2000-01) five Hector's dolphin mortalities occurred in
gill nets that were probably set by recreational fish-
ermen (Department of Conservation and Ministry of
Fisheries, 2001). It is not reasonable to assume that
all mortalities in recreational gillnets are detected. In
our opinion it is likely that combined commercial and
recreational gillnet bycatch off Canterbury is about
15-30 individuals per year.
Hector's dolphin abundance on the north, east, and
south coasts of the South Island estimated from the sur-
veys reported in the present study is 1880 individuals
(CV=15.7%). Hector's dolphins are more common on the
Starr, P. 2000. Comments on "Estimation of the total
bycatch of Hector's dolphins (Cephalorhynchus hectori) from
the inshore trawl and setnet fisheries off the east coast of
the South Island in the 1997-98 fishing year." Unpublished
paper presented to Conservation Services Levy Working
Group, 28 p. Department of Conservation, P.O. Box 10-420
Wellington. New Zealand.
450
Fishery Bulletin 102(3)
Table 4
Corrected abundance estimates (only strata with sightings are listed I
. Number of sighti
ngs represents only those made in that
stratum and used for density estimation. The number
rsed for estimating
effective half strip width. (ESW) differs because it
includes sightings from extra transects in areas of similar exposure ar
d transects repeal
ed on the same day (
rnd hence
not true
replicates for the purposes
of estimating density).
No. of
ESWim)
N(c)
Lower
Upper
Survey zone
Stratum
sightings
(n,CV%)
rv.
95% CI
95% CI
Motunau to Timaru
Akaroa harbor
56
275
62
32
121
(1997-981
(71,22.6)
(33.9)
Other harbors and bays
8
275
171,22.6)
14
(67.5)
3
79
Banks Peninsula Marine M
ammal Sanctuary
62
261
821
535
1258
iBPMMS) (excluding harbors and bays)
(75, 10.3)
(22.1)
<4 nmi offshore, to the north and south of BPMMS 19
261
300
133
679
175, 10.3)
(36.5)
Timaru to Long Point
Timaru-Long Point (exclud
ng Te Waewae Bay
13
268
310
201
478
(1998-99)
(121, 10.5)
(28.4)
Te Waewae Bay
14
268
(121, 10.5)
89
(32.4)
36
218
Motunau to Farewell Spit
Queen Charlotte Sound
3
214
20
4
111)
(1999-2000)
(70,20.2)
(100.5)
Cloudy and Clifford Bay
13
277
(89,6.1)
162
(55.4)
56
474
Cape Campbell-Motunau
5
277
(89,6.1)
102
(55.2)
34
305
Total
1880
(21.3)
1246
2843
South Island west coast, where an aerial survey of simi-
lar design resulted in an estimate of 5388 (CV=20.6<*;
Slooten et al., in press). Thus Hector's dolphin abun-
dance in South Island waters is estimated at 7268 in-
dividuals (CV=15.8'7r ). The North Island subspecies of
Hector's dolphin, now considered critically endangered
(IUCN4) remains to be surveyed quantitatively.
The new abundance estimates provide an empirical
basis from which to calculate levels of take that would
still allow the currently depleted populations to recover
(e.g., Wade, 1998). These levels of take should be seen
as short-term targets for bycatch reduction in gill and
trawl nets. For the management of Hector's dolphin to
be put on a rational basis, a more comprehensive and
wide-ranging assessment of bycatch, including statisti-
cally robust observer programs in coastal fisheries, is
urgently needed.
nificant contributions to equipment used in the survey-
were made by the New Zealand Whale and Dolphin
Trust and the University of Otago. We are very grateful
for the hard work put in by the other observers: Laszlo
Kiss, Nadja Schneyer, Gail Dickie, Niki Alcock, Lesley
Douglas, James Holborow, Ellie Dickson, Guen Jones,
Will Rayment, and Dan Cairney. Jay Barlow, Jeff Laake,
Anne York, and Debbie Palka shared their thoughts on
survey design and field methods. David Fletcher helped
with aspects of variance estimation. Akaroa Harbour
Cruises provided much appreciated field support. Daryl
Coup wrote the sightings program we used to collect
data in the field. Otago University's Department of
Surveying very helpfully provided the GPS base-station
data for postprocessing our GPS fixes.
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452
Abstract— A developmental series of
larval and pelagic juvenile pygmy
rockfish (Sebastes wilsoni) from cen-
tral California is illustrated and
described. Sebastes wilsoni is a non-
commercially. but ecologically, impor-
tant rockfish, and the ability to dif-
ferentiate its young stages will aid
researchers in population abundance
studies. Pigment patterns, meristic
characters, morphometric measure-
ments, and head spination were
recorded from specimens that ranged
from 8.1 to 34.4 mm in standard
length. Larvae were identified ini-
tially by meristic characters and the
absence of ventral and lateral midline
pigment. Pelagic juveniles developed
a prominent pigment pattern of three
body bars that did not extend to the
ventral surface. Species identifica-
tion was confirmed subsequently by
using mitochondrial sequence data
of four representative specimens of
various sizes. As determined from the
examination of otoliths, the growth
rate of larval and pelagic juvenile
pygmy rockfish was 0.28 mm/day,
which is relatively slow in compari-
son to the growth rate of other spe-
cies of Sebastes. These data will aid
researchers in determining species
abundance.
Description and growth of larval and pelagic
juvenile pygmy rockfish (Sebastes wilsoni)
(family Sebastidae)
Thomas E. Laidig
Keith M. Sakuma
Santa Cruz Laboratory
Southwest Fisheries Science Center
National Marine Fisheries Service, NOAA
110 Shaffer Rd
Santa Cruz, California 95060
E-mail address: torn laidigiS'noaa. gov
Jason A. Stannard
La Jolla Laboratory
Southwest Fisheries Science Center
National Marine Fisheries Service, NOAA
P. O. Box 271
La Jolla, California 92038
Manuscript submitted 9 -June 2003
to Scientific Editor's Office.
Manuscript approved for publication
25 February 2004 by the Scientific Editor.
Fish. Bull. 102:452-463(20041.
Rockfishes (genus Sebastes) form a
diverse group comprising at least 72
species occurring in the northeast-
ern Pacific (Love et al., 2002). Many
of these species represent a substan-
tial portion of the groundfish fishery
off the west coast of North America,
accounting for 20% of the groundfish
landings in California in 2000 (Pacific
Fishery Management Council, 2000).
A few species are relatively abun-
dant but are not harvested because
of their small size. These species play
vital roles in the community ecology,
including providing prey for the larger,
commercially important species. The
pygmy rockfish (Sebastes wilsoni)
having a maximum size of 23 cm total
length, is among these small species
(Love et al., 2002). Pygmy rockfish are
common over sediment and rocky sea-
floor habitats at a depth of 30-274 m
(Stein et al., 1992; Yoklavich et al.,
2000). Stein et al. (1992) observed
that pygmy rockfish were by far the
most abundant fish species off Heceta
Bank, Oregon, and Love et al. (1996)
reported "clouds" of pygmy rockfish
mixed with two other small species,
squarespot rockfish (S. hopkinsi ) and
halfbanded rockfish (S. semicinctus)
off southern California. In Soquel
Canyon in central California, pygmy
rockfish dominated fish assemblages
in rock-boulder habitat at 75-175 m
(Yoklavich et al., 2000).
Accurate identification of larval
stages is critical. Biomass of rock-
fish populations can be estimated
from larval production (Ralston et
al., 2003) and larval and juvenile
abundance studies (Moser and But-
ler, 1987; Hunter and Lo, 1993 I. If
the larval and juvenile rockfish ana-
lyzed in these studies are not correct-
ly identified, it could lead to either
over- or underestimates of biomass
or recruitment potential of a popula-
tion. Identification of young stages
of Sebastes has been accomplished
through rearing studies and through
descriptions based on developmental
series of field-caught specimens of
various sizes (Matarese et al., 1989;
Moser, 1996). Otolith morphologies
have been useful in discerning some
Sebastes species (Laidig and Ralston,
1995; Stransky, 2001). Recently, mo-
lecular methods have proven to be an
effective tool for the identification of
Sebastes larvae (Seeb and Kendall,
1991; Rocha-Olivares, 1998; Rocha-
Olivares et al„ 2000).
In this study, we identify and de-
scribe the larvae and pelagic juveniles
of pygmy rockfish based on morpho-
metries and pigmentation patterns,
and estimate age and growth at two
Laidig et al.: Descriptions and growth of larval and juvenile Sebastes wilsoni
453
developmental stages. Further, we examine otolith ra-
dius at time of larval extrusion to separate pygmy rock-
fish from other similarly pigmented Sebastes specimens.
We also use mitochondrial DNA (mtDNA) sequence
data to identify four putative pygmy rockfish specimens
representing a continuum of late-larval through pelagic
juvenile stages. The molecular results are used to con-
firm identifications based on morphological, meristic,
and pigmentation characters and to assure that the
assembled developmental series is monospecific.
Methods
Specimen collection
Specimens of larval and pelagic juvenile pygmy rockfish
were obtained from research cruises conducted aboard
the NOAA RV David Starr Jordan off central California.
Specimens were collected in midwater (5-30 m) from
mid-May to mid-June, 1990-92, between Bodega Bay
(north of San Francisco) and Cypress Point (south of
Monterey Bay) by using a 26 mx26 m modified Cobb
midwater trawl (12.7-mm stretched-mesh codend liner).
Specimens also were collected during early March,
1992-93, between Salt Point (north of San Francisco)
and Cypress Point with a 5 mx5 m modified Isaacs-Kidd
(MIK) frame trawl with 2-mm net mesh and 0.505-mm
mesh codend. Specimens from the Cobb trawl were frozen
and specimens from the MIK frame trawl were preserved
in 95% ethanol for later analysis.
Meristics, morphometries, and body pigmentation
We examined pigmentation patterns and physical char-
acteristics of 122 pygmy rockfish larvae and pelagic
juveniles. Standard length (SL) was measured for each
individual and sizes ranged from 8.1 to 34.4 mm. Speci-
mens greater than 19.9 mm were identified by using
meristic characters (Chen. 1986; Matarese et al.. 1989;
Moreland and Reilly, 1991; and Laroche1), and pigment
patterns were recorded. Specimens less than 20 mm
were identified initially from pigment patterns from a
series starting with the smallest (8.1 mm SL) identifi-
able individuals with complete fin-ray counts. Counts
of dorsal-, anal-, and pectoral-fin rays, and the number
of gill rakers on the first arch were recorded whenever
possible and subsequently used in identifications. Gill
raker counts were obtained only from fish larger than
15 mm SL.
We measured snout-to-anus length, head length,
snout length, eye diameter, body depth at the pectoral
fin base, body depth at anus, and pectoral-fin length on
16 specimens ranging from 8.1 to 29.6 mm SL, follow-
ing Richardson and Laroche (1979). Head spination was
examined on thirty-three specimens (8.1 to 29.6 mm
1 Laroche, W. A. 1987. Guide to larval and juvenile rock-
fishes (Sebastes) of North America. Unpubl. manuscript,
311 p. Box 216, Enosburg Falls, VT 05450.
SL) that were stained with alizarin red-s. Terminol-
ogy for head spination follows Richardson and Laroche
(1979). In the following descriptions, larval and juvenile
lengths always refer to SL and pigmentation always
refers to melanin.
Otolith examination
Sagittal otoliths were removed from 61 larval and pelagic
juvenile pygmy rockfish (8.1-34.4 mm SL), and growth
increments were counted beginning at the first incre-
ment after the extrusion check (the mark in the otolith
formed when the larvae are released from their mother)
by using a compound microscope at lOOOx magnifica-
tion (see Laidig et al., 1991). No validation of the these
growth increments was performed during the present
study, and none has been conducted by other research-
ers. However, we assumed that these growth increment
counts corresponded to daily ages based on validation
of daily growth increments in other co-occurring rock-
fishes, namely shortbelly rockfish, S. jordani (Laidig et
al., 1991), black rockfish, S. melanops (Yoklavich and
Boehlert, 1987), bocaccio, S. paucispinis, chilipepper,
S. goodei, widow rockfish, S. entomelas, and yellowtail
rockfish, S. flavidus (Woodbury and Ralston, 1991). The
radius of the otolith was measured from the primordium
to the postrostral edge of the extrusion check for com-
parison with similar measurements from other Sebastes
spp. (as reported in Laidig and Ralston, 1995). Transfor-
mation from the larval stage to the pelagic juvenile stage
was ascertained by the presence of accessory primordia
(Laidig et al., 1991; Lee and Kim, 2000).
Molecular confirmation
Total genomic DNA was isolated from skeletal muscle
tissue of four larval and juvenile putative pygmy rock-
fish specimens by using a CTAB and phenol-chloro-
form-isoamyl alcohol protocol ( Winnepenninckx et al.,
1993; Hillis et al., 1996). These four specimens ranged
in length from 15 to 27 mm and had pigment patterns
similar to the fish identified as pygmy rockfish in the
present tudy. Polymerase chain reaction (PCR) ampli-
fications and sequencing of partial mitochondrial DNA
regions (cytochrome b [cyt-6] and control region [CR])
followed the methods of Rocha-Olivares et al. (1999a,
1999b). PCR products were verified on 29c agarose gels
and purified by using a QIAquick™ PCR Cleanup Kit
(Qiagen, Inc., Valencia, CA) following manufacturer
protocols. Complementary strand sequence data were
generated by using ABI PRISM' M DyeDeoxy™ termina-
tor cycle sequence chemistry on an automated sequencer
(Applied Biosystems, Model 377, Foster City, CA).
Cytochrome b sequence data (750 base pairs) from
the four specimens were aligned with (previously gen-
erated) orthologous sequences from 119 individuals
representing 61 species of Sebastes (Rocha-Olivares et
al., 1999b). Species identifications, based on cyt-fo data,
were made by using distance-based cluster analyses in
PAUP v4.0b2 (Phylogenetic Analysis Using Parsimony,
454
Fishery Bulletin 102(3)
version 4, Sunderland, MA) and pairwise comparisons
of sequence divergence (i.e., the number of nucleotide
differences between two individuals expressed as a per-
centage). A secondary data set, which included an ad-
Table 1
Frequency of occurrence ( number of fish i
and pectoral-fin ray counts, and gill ra
122 pygmy rockfish tSebastes wilsoni).
of dorsal-, anal-,
ker counts from
Character
Count
Frequency of
occurrence
Percent
occurrence
Dorsal-fin rays
12
8
7
13
110
91
14
3
2
Anal-fin rays
5
2
2
6
116
95
7
4
3
Pectoral-fin rays
16
5
5
17
92
90
18
5
5
Gill rakers
36
11
14
37
15
18
38
22
28
39
20
25
40
10
13
41
1
1
42
1
1
ditional 450 base pairs of control region sequence, was
generated for the four undetermined specimens and for
a subgroup of known reference species with low levels
of sequence divergence from the four putative pygmy
rockfish specimens ( Puget Sound rockfish [S. empha-
eus], redstripe rockfish [S. proriger], harlequin rockfish
IS. variegatus]. sharpchin rockfish [S. zaeentrus], and
pygmy rockfish). Species identifications, based on this
extended (cyt-fe + CR) data subset, followed analyses
described above.
Results
General development
All 122 fish had completed notochord flexion and pos-
sessed a full complement of segmented fin rays by 8.1
mm. The mode for dorsal-fin ray counts was 13, for
anal-fin rays 6, and for pectoral-fin rays 17 (Table 1).
The mode for gill raker counts was 38, and the range
was 36-42. Anal- and dorsal-fin spines began to develop
between 9.1 and 14.0 mm. Lateral line pores began to
develop at 29 mm, although a full complement (37 to 46
pores) was not reached in our specimens. Morphometric
measurements were taken from 16 individual pygmy
rockfish of 8.1-29.6 mm (Table 2).
Head spination
At 8.1 mm, the postocular, parietal, nuchal, inferior post-
temporal, supracleithral, superior opercular, preopercu-
lars (with the exception of the 2nd anterior), and 1st and
Table 2
Morphometric measurements (in mm) fr
om 16 individual
; of pygmy rockfish tSebastes wilsoni).
Snout-anus
Head
Snout
Eye
Body depth
Body depth
Pectoral-fin
SL
length
length
length
diameter
at pectoral base
at anus
length
8.1
5.2
3.3
0.8
1.3
2.8
2.3
1.5
9.0
5.3
3.0
1.0
1.5
3.0
2.3
1.7
10.8
6.5
4.2
1.2
1.7
3.5
2.8
2.3
12.1
7.0
4.3
1.3
2.0
3.8
2.8
2.5
12.8
7.7
4.8
1.3
2.2
3.7
3.0
2.5
14.2
8.3
4.7
1.3
2.2
4.3
3.5
3.3
15.2
9.2
5.7
1.7
2.0
4.2
3.5
3.5
16.2
9.7
5.2
1.5
2.0
4.5
3.8
3.8
17.5
10.8
6.2
2.0
2.3
5.0
3.8
4.2
18.6
11.5
6.0
2.0
2.7
5.5
4.3
5.0
20.7
12.7
6.2
2.0
2.7
6.2
5.2
5.0
22.3
14.2
6.7
2.2
2.8
6.8
5.7
6.2
23.8
14.5
6.7
2.0
3.2
7.3
6.3
5.9
24.3
14.2
7.0
2.2
2.7
7.0
5.8
6.3
28.9
17.0
8.0
2.6
3.3
8.5
7.3
7.0
29.6
16.9
7.8
2.6
3.5
8.7
7.5
6.9
Laidig et al.: Descriptions and growth of larval and juvenile Sebastes wilsoni
455
2nd inferior and 1st superior infraorbital spines were
present (Table 3). The nasal, pterotic, and 4th superior
infraorbital first appeared at 10.8 mm. At 12.1 mm, the
inferior opercular spine became evident. Between 14.2
and 17.5 mm, the preocular, tympanic, superior postem-
poral, 2nd anterior preopercular. and 3rd superior infraor-
bital spines formed. After 17.5 mm, no further changes
in head spination were noted. The supraocular, coronal,
3rd inferior infraorbital, and 2nd superior infraorbital
spines did not occur on any of the fish examined.
Body pigmentation
At 9.1 mm, pygmy rockfish had no pigment along the
lateral and ventral body surfaces (Fig. 1A, Table 4).
Pigment was heavy on the top of the head and present
on the operculum. The dorsal midline surface had a
few melanophores under the soft dorsal fin. The ante-
rior lower jaw was pigmented on the tip and one to two
melanophores were present on each side of the snout
near the tip. Pigment also was present at the base and
on the distal half of the pectoral fin.
By 14.0 mm, dense pigment along the dorsal midline
stretched from the caudal peduncle to the first dorsal-fin
spine (Fig. IB, Table 4). The only lateral pigment on the
body consisted of a few melanophores along the midline
near the caudal peduncle. The ventral surface, includ-
ing the anal and pelvic fins, remained unpigmented.
Pigment on the pectoral fins had mostly disappeared by
11.0 mm and was rarely observed at 14.0 mm. Opercu-
lar and head pigment increased in density by 14.0 mm.
Pigment along the lower edge of the orbit began to
Table 3
Development of head spi
aes in
individua
pygmy rockfish iSebastc
• wilsoni
). "1'
means spines present and "0" means spines
absent.
Spines
Standard length (mm)
8.1
9.0
10.8 12.1
12.8
14.2
15.2
16.2 17.5
18.6
20.7 22.3 23.8 24.3 28.9 29.6
Nasal
0
0
1
1
1
1
1
1
111111
Preocular
0
0
0
0
0
0
1
1
111111
Supraocular
0
0
0
0
0
0
0
0
0
0
0 0 0 0 0 0
Postocular
1
1
1
1
1
1
1
1
111111
Coronal
0
0
0
0
0
0
0
0
0
0
0 0 0 0 0 0
Tympanic
0
0
0
0
0
0
0
1
1
111111
Parietal
1
1
1
1
1
1
1
1
111111
Nuchal
1
1
1
1
1
1
1
1
111111
Pterotic
0
0
1
1
1
1
1
1
111111
Posttemporal
Superior
0
0
0
0
0
0
1
1
111111
Inferior
1
1
1
1
1
1
1
1
111111
Supracleithral
1
1
1
1
1
1
1
1
111111
Opercular
Superior
1
1
1
1
1
1
1
1
111111
Inferior
0
0
0
1
1
1
1
1
Preopercular
1st anterior
1
1
1
1
1
1
1
1
111111
2nd anterior
0
0
0
0
0
1
1
1
111111
3rd anterior
1
1
1
1
1
1
1
1
111111
1st posterior
1
1
1
1
1
1
1
1
111111
2nd posterior
1
1
1
1
1
1
1
1
111111
3rd posterior
1
1
1
1
1
1
1
1
111111
4th posterior
1
1
1
1
1
1
1
1
111111
5th posterior
1
1
1
1
1
1
1
1
111111
Infraorbital
1st inferior
1
1
1
1
1
1
1
1
111111
2nd inferior
1
1
1
1
1
1
1
1
111111
3rd inferior
0
0
0
0
0
0
0
0
0 0 0 0 0 0
1st superior
1
1
1
1
1
1
1
1
111111
2nd superior
0
0
0
0
0
0
0
0
0 0 0 0 0 0
3rd superior
0
0
0
0
0
0
1
1
111111
4th superior
0
0
1
1
1
1
1
1
111111
456
Fishery Bulletin 102(3)
Figure 1
Developmental series of pygmy rockfish [Sebastes wilsoni) (drawn by authors). (A) 9.1-mm-
SL larva; (B) 14.0-mm-SL larva; iC) 17.5-mm-SL larva; (D) 23.0-mm-SL pelagic juvenile;
I E ) 28.6-mm-SL pelagic juvenile. Arrow marks ventral end of anterior body bar; I F ) 34.4-
mm-SL pelagic juvenile. Note that not all head spines are included in the illustrations.
form in some specimens by 12.0 mm and was visible in
most specimens by 14.0 mm (Fig. IB). Snout pigment
was represented by one or four melanophores. Anterior
lower jaw pigment was heavy and confined to the tip
of the jaw.
By 17.5 mm, the dorsal midline pigment had become
much darker and denser (Fig. IC, Table 4) and extended
from the caudal fin to the head region, except for a gap
where the nape pigment was beginning to form. All
fins were unpigmented. Pigment along the ventral body
midline began to form at 17.5 mm, with a few postanal
melanophores. Lateral midline pigment formed in two
locations. Melanophores near the peduncle increased
anteriorly, and pigment began forming dorsal to the gut
cavity and increased posteriorly toward the peduncle.
A body bar began to form on the lateral surface above
the pectoral fin between the spinous dorsal fin and the
anterior lateral midline pigment. Opercular, eye, and
head pigment all increased in density. Melanophores on
the snout also became more prevalent between the tip of
Laidig et al.: Descriptions and growth of larval and |uvenile Sebastes wilsoni
457
Figure 1 (continued)
the upper jaw and top of the head. Pigment on the tip
of the lower jaw spread posteriorly and became denser
than in smaller specimens.
When the pelagic juveniles reached 23.0 mm, the
dorsal midline pigment was a dark strip extending from
the caudal fin to the head (Fig. ID, Table 4). Nape pig-
ment almost merged with the head pigment, except for
a small unpigmented area below the insertion of the
parietal and nuchal spines. Hypural pigment was pres-
ent distally in all individuals at this size and at larger
sizes (n = 30). Anterior and posterior lateral midline pig-
ment merged to form a continuous line along the body.
The number of melanophores increased on the ventral
body surface, and a few melanophores were present at
the anal-fin ray bases and along the ventral midbody
posterior to the anal fin. The anterior body bar broad-
ened and became more defined. A few melanophores
on the flanks under the soft dorsal fin began to form
a midbody bar. A third body bar began to form on the
caudal peduncle. Pigment on the operculum, top of the
458
Fishery Bulletin 102(3)
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Laidig et al.: Descriptions and growth of larval and |uvenile Sebastes wtlsoni
459
head, and snout also increased in density, and pigment
formed posteriorly along the upper and lower jaws. Me-
lanophores posteriorly around the eye socket increased
in number. The fins remained unpigmented.
Pygmy rockfish 28.6 mm long had dorsal pigment
that stretched continuously from the jaws to the caudal
fin (Fig. IE. Table 4). Pigmentation was heavy along
the dorsal midline, head, and nape. Snout pigmenta-
tion also intensified. More melanophores were present
on the hypural margin. Pigment along the ventral body
surface darkened, especially in the area posterior to
the anal fin. More melanophores were observed at the
anal-fin ray articulations than on smaller specimens.
The three body bars increased in width and length and
were better defined than on smaller specimens. The bar
on the caudal peduncle began to exhibit a rectangular
shape that is characteristic of the juvenile stage. The
midbody bar also took on a rectangular shape, although
the dorsal half was indented. The midbody bar and the
caudal peduncle bars did not reach the ventral midline.
The anterior body bar extended from the spinous dorsal
fin to the vent (see arrow Fig. IE). Anteriorly, the bar
formed a more or less rectangular pattern on the dorsal
half of the body above the pectoral fin. In general, the
lateral body surface became more heavily pigmented,
especially on the dorsal half. The lateral midbody pig-
ment line began to be incorporated into the body bars.
Opercular pigment became denser and merged with
the nape pigment. The area anterior to the nape and
operculum was less pigmented than the surrounding
areas. Pigment along the posteroventral portion of the
orbit became denser than in smaller specimens. A cheek
bar began to form ventral to the eye (as evidenced by
the two melanophores in Fig. IE ). Melanophores formed
along the ventral surface of the lower jaw and covered
the lateral surface of the upper jaw. Pigment began to
develop on the membranes of the spinous dorsal fin,
typically with some unpigmented areas between the
dorsal fin pigment and the dorsal body pigment.
The largest specimen. 34.4 mm, had the densest and
most distinctive pigmentation (Fig. IF, Table 4). Pig-
ment was present on most of the body. Along the dorsal
surface, the pigment formed a complete line from the
tip of the upper jaw to the caudal fin. The number of
melanophores increased along the hypural region, the
postanal ventral midline, and at the anal-fin articula-
tions. The mid- and caudal body bars were rectangular
and still did not reach the ventral midline, leaving an
unpigmented ventrolateral area. The anterior body bar
comprised heavy pigment extending posteriorly between
dorsal-fin spines VIII-XI and the vent, a lighter area
just anterior to this, and another heavily pigmented
area stretching from about dorsal-fin spines III— VI
almost to the middle of the gut cavity. Anterior to this
bar was an area of mottled pigmentation. Pigment was
visible just anterior to the base of the pectoral fin.
Pigment covered both the spinous and soft dorsal fins,
except along the distal edge. All other fins remained
unpigmented. Opercular pigment was dense and merged
with the nape pigment, but these were separated from
40
35
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_c
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55
10
■ /
20 40 60 80 100 120 140 160
Age (days)
Figure 2
Standard length and age of pygmy rockfish i Sebastes
wilsoni) in = 60 1. Solid line indicates predicted values
from linear model.
the head and eye pigment by an area of low pigment
density. Two cheek bars radiated from the lower margin
of the orbit. Pigment occurred along both jaws and cov-
ered the snout and ventral portion of the lower jaw.
Otolith examination
A linear relationship between standard length and age
(as estimated from otolith increment counts) resulted in
a good estimate of growth of pygmy rockfish (slope = 0.28
mm/d; intercept=-5.15 mm; r2=0.91; ?i = 60; Fig. 2). The
radius of the extrusion check ranged from 9.5 to 11.0
^m, averaging 10.5 /jm (SD = 0.29; « = 60). Accessory pri-
mordia first appeared in a 19.8-mm specimen and were
observed in otoliths from all larger specimens. Based on
this character, transition from larval to pelagic juvenile
stage occurs at around 20 mm SL.
Molecular confirmation
Interspecific levels of divergence, calculated among adult
reference species, ranged from 0.13% (rougheye rockfish
[S. aleutianus] vs. shortraker rockfish [S. borealis]) to
9.7% (black rockfish [S. inermis] vs. bocaccio) with an
average of 4.1%. Two of the specimens (FT2 and FT3;
Fig. 3A) were identical to one of the adult pygmy rockfish
references (i.e. 0% sequence divergence i and differed
from the other verified adult pygmy rockfish by a single
nucleotide substitution (0.13% seq. div. ). The remain-
ing two specimens (FT1 and FT4; Fig. 3A) also were
most similar to both adult pygmy rockfish references
(0.13-0.40% seq. div.).
Although all four specimens were most similar to
pygmy rockfish based on cytochrome b data, only a
small number of nucleotide differences separated them
from Puget Sound, redstripe, harlequin, and sharpchin
rockfish (0.27-1.87%; Fig. 3A). A secondary data subset
that included control region sequence (cyt-6+CR) yield-
ed concordant results; all four larval specimens were
460
Fishery Bulletin 102(3)
3.5-
A Cyt-£>
B Cyt-to + CR
3-
•
• •
•
X emphaeus (BU5)
2.5-
X emphaeus (BU6)
• pronger (BS4)
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□ vanegatus (BS5)
0)
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A wilsoni (BT1 1 )
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Larval and juvenile specimens
Figure 3
Percent sequence divergence based on the number of nucleotide differences in iAi
cytochome 6 and (Bi
cytochrome b + control region between the four putative pygmy rockfish I Sebastes wilsoni) specimens
iFT1-FT4i and five closely related reference species of Sebastes, including two a
dult S. wilsoni. Per-
cent sequence divergence was calculated as the number of nucleotide differences
over 750 base pairs
(cyt-6) and 1200 base pairs (cyt-6+CRi.
most similar to pygmy rockfish (0.25-0.83%; Fig. 3B).
Increased levels of interspecific nucleotide variation,
attributable to the faster evolving control region, re-
sulted in more pronounced differences between the four
specimens and the other species of Sebastes within the
subset (range: 0.83-3.00%; Fig. 3B). Additionally, a
distance-based analysis (UPGMA) of haplotypes (cyt-
fr+CR) clustered all four specimens with pygmy rockfish
reference material.
Discussion
Postflexion larval pygmy rockfish can be identified
through a combination of pigment and meristic char-
acters. At approximately 8-10 mm, the larval pigment
pattern is similar to only four of the 30 Sebastes spe-
cies illustrated in the literature that occur within our
geographic area (Matarese et al., 1989; Moser, 1996;
Laroche1): yellowtail (S. flavidus), blue (S. mystinus),
canary (S. pinniger), and sharpchin rockfish. Yellowtail
and blue rockfish can be separated from pygmy rockfish
because they exhibit ventral body and hypural pigment
at this size — pigment that does not show up in pygmy
rockfish until approximately 14 and 15 mm, respectively.
In canary rockfish, the presence of ventral body pigment
and dorsal midline pigment posterior to the soft dorsal
fin (instead of at the base of the soft dorsal-fin rays as in
pygmy rockfish) can help differentiate this species from
pygmy rockfish. Pigmentation patterns of sharpchin
rockfish are very similar to pygmy rockfish at 10 mm;
however, sharpchin rockfish retain pigmented pelvic fins
until 12.7 mm (Laroche and Richardson. 1981). Counts of
anal-fin rays often can be used to differentiate these two
species because pygmy rockfish have six rays and sharp-
chin have rockfish seven rays (Chen, 1986; Matarese et
al., 1989; Moreland and Reilly, 1991; Laroche1!. There
is a small overlap in anal-fin ray counts (approximately
1' i I, and, because of this, 100% certainty of identification
cannot be reached by anal-fin ray counts alone. There-
fore, in order to increase confidence in identifications, a
combination of pigmentation and fin-ray counts should
be employed. After approximately 15 mm. a full comple-
ment of fin rays and gill rakers typically is present and
can be used in combination with pigmentation patterns
to differentiate pygmy rockfish from most other rockfish
species. In these late-stage larvae, only three species
(yellowtail. black (S. melanops), and blue rockfish) have
a pigment pattern that could be confused with pygmy
rockfish (Matarese et al., 1989; Moser, 1996; Laroche1).
Laidig et al.: Descriptions and growth of larval and juvenile Sebostes wilsoni
461
but these patterns can be easily separated by using
meristic characters.
Pelagic juvenile pygmy rockfish have a distinctive
pigment pattern consisting of three body bars that can
be used to discriminate this species from other Sebastes
species. Yellowtail, halfbanded, and redstripe rockfish
are the only species that have a similar three-barred
pigment pattern (Matarese et al., 1989; Moser, 1996;
Laroche1). Yellowtail rockfish can be distinguished by
the lack of cheek bars and the presence of body bars
that extend all the way to the ventral surface. Also, in
yellowtail rockfish, the body bars form at a larger size
than in pygmy rockfish. In halfbanded rockfish, the
most anterior body bar is more densely pigmented than
the other bars and typically forms a diamond shape.
The caudal body bar is much wider and covers the en-
tire peduncle. Redstripe rockfish are the most similar
and are difficult to separate from pygmy rockfish by
using pigmentation alone. However, these two species
can be separated with greater than 90% certainty by
using meristic counts. Pygmy rockfish have a mean
anal-fin ray count of 6 (95% from the present study, and
93% from Laroche1), whereas redstripe rockfish have an
average of 7 anal-fin rays (100% from Chen, 1986; 97%
from Laroche1).
It should be noted that the only illustration of pygmy
rockfish prior to our study was a 35.0-mm pelagic juve-
nile by Laroche,1 which showed several pigment differ-
ences from our specimens of equivalent size. Laroche's
illustrated specimen had only faint body barring, no
cheek bars, and no ventral pigment, whereas all our
specimens had prominent body barring, at least one
cheek bar, and ventral pigment along the anal-fin ar-
ticulations. At this time we cannot determine whether
these differences were due to geographic variability in
pigment patterns (Laroche's specimen probably was
collected farther north than all of our specimens), or
a misidentification of the original specimen illustrated
by Laroche.1
The identification of larval and pelagic juvenile pygmy
rockfish used in our study was confirmed by using DNA
sequence analyses. Previous molecular identifications
and subsequent descriptions of juvenile starry rockfish
(S. constellatus) and swordspine rockfish (S. ensifer)
also were based on mitochondrial cytochrome b data
(Rocha-Olivares et al., 2000). In our study, orthologous
cytochrome b sequence was sufficient for identifica-
tion purposes, particularly for those specimens exhibit-
ing exact haplotype matches to reference adult pygmy
rockfish (e.g., FT2/FT3: 0.0% sequence divergence).
Relatively low levels of interspecific genetic variation
occurred between larval specimens and several refer-
ence species (pygmy, sharpchin. harlequin, and Puget
Sound rockfish, and, to a lesser extent, redstripe rock-
fish). Rocha-Olivares et al. (1999a) used control region
sequence, in addition to cytochrome b, to resolve phy-
logenetic relationships among recently diverged species
of the Sebastes subgenus Sebastomus. In the present
study, the control region sequence was used to increase
divergence levels between species and to aid in insur-
ing correct molecular identifications of specimens FT1
and FT4. Species assignment to pygmy rockfish was
supported by the smallest divergence (based on cyt-6
and cyt-6+CR) from reference pygmy rockfish compared
with the other Sebastes species.
Larval and juvenile pygmy rockfish can also be sepa-
rated from other Sebastes species by comparing the
radius of the extrusion check on their otoliths. Of the
fourteen other Sebastes species or species complexes
with measured otolith extrusion check radii ( Laidig and
Ralston, 1995; Laidig et al., 1996; Laidig and Sakuma,
1998), only four species and two complexes have radii
close to the average extrusion check radii for pygmy
rockfish (10.5 nm, SD = 0.3). Stripetail rockfish (S. saxi-
cola) had an average extrusion check radius (11.6 (im,
SD = 0.5) that was larger than the largest radius for
pygmy rockfish (11.0 (jm). Quillback rockfish (S. ma-
liger) had an average extrusion check radius of 9.1 jim
(SD = 0.1). which was smaller than the smallest radius
for pygmy rockfish (9.5 p.m). Species with extrusion
check radii similar to pygmy rockfish were kelp rockfish
(S. atrovirens) at 10.6 ^m (SD = 0.2), blue rockfish at
10.9 /./m (SD = 1.1), and the copper rockfish (S. caurinus,
extrusion check radius = 10.5 /jm; SD = 0.4) and gopher
rockfish (S. carnatus, extrusion check radius = 10.6 ,um;
SD = 0.3) complexes (see Laidig et al., 1996. for complex
definitions). Of these species, the only one that would be
confused with pygmy rockfish, by pigmentation alone,
would be blue rockfish at small sizes. However, pygmy
rockfish and blue rockfish are easily separated by using
meristic characters.
Growth rates of larval rockfish generally are slow
during the first month of life and increase thereafter
(Laidig et al., 1991; Sakuma and Laidig, 1995; Laidig
et al., 1996). Because the youngest fish in our study
was estimated to be 40 days old, our linear model can
not be used to estimate early larval growth rates. For
pygmy rockfish older than 40 days, the growth rate of
0.28 mm/day was somewhat slower than that observed
for other Sebastes. Woodbury and Ralston (1991) found
that, for fish older than 40 days, growth rates varied
from 0.30 for widow rockfish (S. entomelas) to 0.97 mm/
day for bocaccio. Other species exhibiting slightly faster
growth rates after 40 days of age include stripetail
rockfish (0.37 mm/day; Laidig et al., 1996), grass rock-
fish (S. rastrelliger; 0.36 mm/day; Laidig and Sakuma,
1998), and shortbelly rockfish (S. jordani; 0.53 mm/day;
Laidig et al., 1991). Yellowtail rockfish had a more
similar growth rate, ranging from 0.19 to 0.46 mm/day
(Woodbury and Ralston, 1991). These differences in
growth may reflect genetic variability or responses to
environmental variables. Woodbury and Ralston (1991)
suggested that annual variability in growth rates of
juvenile rockfish was related to year-to-year changes
in environmental conditions, especially temperature.
Boehlert (1981) determined that temperature greatly
affected growth rate of young splitnose rockfish (S. dip-
loproa) in the laboratory. Boehlert and Yoklavich (1983)
observed slower growth rates for black rockfish in colder
temperatures. Lenarz et al. (1991) analyzed the vertical
462
Fishery Bulletin 102(3)
distribution of late larval and pelagic juvenile rockfish
and determined that pygmy rockfish were present on
average in deeper, colder water than that favored by
other rockfish species. This spatial separation of pelagic
juvenile pygmy rockfish and other Sebastes spp. may
explain the slower growth observed in pygmy rockfish.
Acknowledgments
We would like to thank the scientists and crew from
the Southwest Fisheries Science Center (SWFSC) who
collected the samples aboard the NOAA RV David Starr
Jordan. We thank Geoff Moser and Bill Watson (NOAA,
SWFSC) for examining some of our pygmy rockfish
specimens. Reference sequences of Sebastes were gener-
ated and kindly provided by personnel at the Fisheries
Resources Division of the SWFSC, La Jolla, CA (R. D.
Vetter, A. Rocha-Olivares, B. J. Eitner, C. A. Kimbrell,
and C. Taylor). In addition, we thank Mary Yoklavich
for all her valuable comments and all the reviewers who
contributed to this manuscript.
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464
Abstract— A critical process in assess-
ing the impact of marine sanctuaries
on fish stocks is the movement offish
out into surrounding fished areas.
A method is presented for estimat-
ing the yearly rate of emigration of
animals from a protected ("no-take")
zone. Movement rates for exploited
populations are usually inferred from
tag-recovery studies, where tagged
individuals are released into the sea
at known locations and their location
of recapture is reported by fishermen.
There are three drawbacks, however,
with this method of estimating move-
ment rates: 1) if animals are tagged
and released into both protected and
fished areas, movement rates will be
overestimated if the prohibition on
recapturing tagged fish later from
within the protected area is not made
explicit; 2) the times of recapture are
random; and 3) an unknown propor-
tion of tagged animals are recaptured
but not reported back to research-
ers. An estimation method is pro-
posed which addresses these three
drawbacks of tag-recovery data. An
analytic formula and an associated
double-hypergeometric likelihood
method were derived. These two
estimators of emigration rate were
applied to tag recoveries from south-
ern rock lobsters (Jasus edwardsil)
released into a sanctuary and into
its surrounding fished area in South
Australia.
Estimating the emigration rate of fish stocks
from marine sanctuaries using tag-recovery data
Richard McGarvey
Aquatic Sciences, South Australian Research and Development Institute (SARDI)
2 Hamra Avenue
West Beach, South Australia 5024, Australia
E-mail address; mcgarvey nchardia saugovsa gov.au
Manuscript submitted 24 March 2003
to Scientific Editor's Office.
Manuscript approved for publication
5 March 2004 by the Scientific Editor.
Fish. Bull. 102:464-472(20lili
Marine sanctuaries, also known as
marine protected areas (MPAs), ma-
rine reserves, and no-take areas, are
being widely promoted and imple-
mented. Important for assessing the
impact of these "no-take" sanctuaries
(from which fishing has been excluded I
on exploited populations is the rate
of emigration of animals out into the
remaining fished habitat.
The most widely available data for
estimating movement rates of com-
mercially or recreationally exploited
populations are those from tagged
and recovered fish (Hilborn, 1990).
Animals are captured alive, a visible
numbered tag is inserted and they
are released back into the wild. Be-
cause the accuracy of tag-recovery
studies relies on fishermen reporting
recaptured tags, the quality of tag-re-
covery information is lower than that
from a controlled experiment.
Tag-recovery experiments have
three limitations for estimating move-
ment rates of animals — the first two
apply to most tagged populations, the
third applies specifically to emigra-
tion from sanctuaries: 1) times at
large (the numbers of days from when
each animal is tagged and released to
when it is subsequently recaptured
in the fishery) are highly variable; 2)
not all recaptured tags are reported
to researchers by fishermen and this
rate of tag nonreporting is often un-
known; and 3) tag recoveries cannot
be obtained from within sanctuaries
for the simple reason that no fishing
is allowed there.
If this last asymmetry (of recap-
tures from the sanctuary coming only
from tagged animals that emigrate)
is not accounted for in the estimation
model, then the emigration rate out of
the sanctuary will be overestimated.
With previous movement estimators,
tag releases and recaptures from all
strata have been assumed. The aim
of the present article is to develop an
unbiased estimator of emigration rate
from no-take areas by using data of
tag releases both into the sanctuary
and into the fished zone surrounding
it, but where recoveries from nonmov-
ing tagged animals are only possible
from the fished zone. An estimate for
the recovery rate (proportion of fish
recaptured and their tags reported) in
the fished zone was also obtained.
Materials and methods
Tag-recovery data
The data used to estimate the emi-
gration rate from Gleesons Landing
Lobster Sanctuary (Fig. 1) are tag
recoveries from lobsters tagged and
released both inside the sanctuary
and into the fished zone surrounding
the sanctuary. A large South Aus-
tralian lobster tagging program was
undertaken in 1993-96 throughout
South Australian waters. T-bar tags
(Hallprint, Victor Harbour, South
Australia) were inserted into the
ventral muscle at the first segment
of the lobster abdomen. The rate of
tag shedding was estimated from
double tags at between 6fr and 1292
per year (Xiao1) and is incorporated
in the recovery rate.
Xiao Y. 2003. Personal commun.
Aquatic Sciences, South Australian
Research and Development Institute
(SARDI), P.O. Box 120. Henley Beach,
South Australia 5022. Australia.
McGarvey: Estimating emigration rates from marine sanctuaries using tag-recovery data
465
Gleesons Sanctuary and surrounding blocks
| | Yorke Peninsula and outlying blocks
'-,- | Gleesons Landing Lobster Sanctuary
I | Block 33
1 Block 40
Yotke Peninsula
40
39
35 S
Figure 1
Location of Gleesons Landing Lobster Sanctuary (small dark area on the bound-
ary of MFA blocks 33 and 40) along the west coast of the Yorke Peninsula in
South Australia.
As part of this tagging program (Table 1), 3235 south-
ern rock lobsters ijasus edwardsii) were tagged and
released into the "fished zone" surrounding Gleesons
Sanctuary, namely into statistical reporting blocks 33
and 40 (Fig. 1). In January 1994, 413 lobsters were cap-
tured, tagged, and released inside the Gleesons Sanctu-
ary. These lobsters were predominantly in the range of
80-120 mm carapace length (CL), around the size of
maturity of about 100 mm CL; more lobsters below the
legal minimum length (98.5 mm CL) were released in
the fished zone.
Gleesons Landing Lobster Sanctuary (Fig. 1) is an
area where lobster fishing has been prohibited since
1982. It lies along the Yorke Peninsula's western coast
in an area of medium to low lobster catches. In width,
this sanctuary extends 1-2 km from shore to seaward
and runs 7-8 km north-south.
Nearly all tag recoveries were reported by commercial
lobster fishermen who noticed tagged lobsters in their
catch in the course of day-to-day fishing operations. Tag
recoveries of lobsters released into both the sanctuary
and the fished zone were, therefore, only possible from
the fished zone. GPS coordinates, date, and carapace
length were recorded for all tagged and recaptured
lobsters. Longer-range movements from both sanctu-
ary and fished zone were directed southwest towards
the shelf edge.
Prescott et al.2 previously described qualitative fea-
tures of the movement of South Australian Jasus ed-
wardsii: 1) nearly all longer-distance movements were
directed offshore to deeper water and away from the
coast; 2) in order of greater to lesser average distances
moved, were i) immature females, ii) males, and iii)
mature or egg-bearing females, for nearly all five South
Australian regions analyzed; 3 1 movements were largely
restricted to lobsters in a specific length range at time
2 Prescott, J., R. McGarvey, G. Ferguson, and M. Lorkin.
1998. Population dynamics of the southern rock in South
Australian waters. Fisheries Research and Development
Corporation of Australia Report 93/086, p. 23-27. Aquatic
Sciences, South Australian Research and Development Insti-
tute (SARDI), P.O. Box 120, Henley Beach, South Australia
5022, Australia.
466
Fishery Bulletin 102(3)
Table 1
Tag-recovery data from Gleesons Landing lobster sanctuary and the surrounding fishing zone used in estimating yearly move-
ment rates of southern rock lobsters.
Data
Variable
name
Observed number
of lobsters
Number of lobsters tagged and released into the sanctuary
Number of lobsters recovered that had moved (>3 km I from the sanctuary
into the fishing zone
Number of lobsters tagged and released into the surrounding fishing zone
Number of lobsters recovered that had moved (>3 km) within the fishing zone
Number of lobsters ecovered that had not moved (>3 km) within the fishing zone
Nf
NF
NF
NF
413
29
3235
89
277
of tagging, roughly 100-140 mm CL for females, and
100-150 mm CL for males, with a noticeable shift to
smaller sizes for both sexes on the southeast coast of
South Australia where growth and thus size of maturity
are known to be lower; 4) overall, most lobsters in the
fished areas did not move large distances, about 15%
moving more than 5 km; 5) two areas stood out as being
habitats from where significant movement occurred, the
coastal zone off the Coorong and Yorke Peninsula; and
6 ) for Yorke Peninsula, higher than proportional num-
bers of tagged lobsters that moved significant distances
were tagged and released inside Gleesons Sanctuary.
In the present study study, a lobster was classified as
having undergone movement if its measured distance
from point of tagging to point of recapture was greater
than 3 km. This definition of lobster "movement" was
chosen for two reasons. 1) The mean width of MPA
coastal zone to be protected in the currently proposed
state representative system is assumed to be 5 km wide;
that is, it is assumed that sanctuary areas will extend
from the shore outward to sea across the full 3 nmi
(which is about 5 km) of state territorial waters. Thus,
a 3-km movement would represent slightly more than
the mean distance needed for lobsters to leave the state-
protected territorial waters of the reserve and enter wa-
ters open for fishing. This assumption is strengthened
by the knowledge that most longer-range movements of
South Australian rock lobster are directed from inshore
to offshore. 2) According to the geographical features
of the present study, a 3-km movement seaward from
any location in Gleesons Landing Sanctuary would
place the tagged lobster well into the fished zone, i.e.,
it would constitute a movement out of the sanctuary. Of
sanctuary-tagged lobsters, 4 of 33 recaptured lobsters
in the first season after tagging exited the reserve but
moved less than 3 km. These 4 recaptured lobsters were
excluded from the data set. The mean distance moved
by lobsters from the sanctuary was 37.4 km.
Because movement of South Australian lobsters is
directed strongly away from the inshore zone, the im-
migration rate of lobsters back into the Gleesons Land-
ing Sanctuary is likely to be quite low. Moreover, Jasus
edwardsii seek shelter daily and remain on specific
reefs through most of their life (MacDiarmid et al. 1991;
Kelly 2001). Long-distance movements occur rarely
more than once in a lifetime. Thus, in the fishing zone,
where there is a continual removal of adult lobsters
from reef habitat, the on-going creation of new shelter
space is higher than in the sanctuary and thus lobsters
that did stray inshore into the sanctuary would be less
likely to find shelter, further reducing the probability
of migration into the sanctuary. In the estimator pre-
sented below, only the emigration rate (the movement
rate out of the sanctuary) is calculated.
The recapture data included lobsters at large for a
wide range of times, many having been recaptured lon-
ger than one year after tag release. However, to estimate
emigration rate, we sought the proportion of lobsters
emigrating out per year. Therefore, subsets of recapture
data were selected that had a mean time at large of one
year. The temporal distributions of recaptured lobsters
showed distinct modes around 1 year at large (recap-
tures between 0.5 and 1.5 years at large. Fig. 2), and the
number of recaptures in these 1-year modes were used
for estimating yearly movement rate (Table 1).
Some tagged and released lobsters were recaptured
more than once. For these lobsters, the single recapture
was selected and used for which the time at large was
closest to one full year.
Notation
The information on movement in each set of tag releases
is taken to be binary: each recaptured animal is clas-
sified as having moved or as having not moved during
its approximately 1-year time at large (from time of tag
release to time of recapture).
To carry out the movement-rate estimation, it is use-
ful to consider the complete set of four possible outcomes
for each tagged and released animal: 1) it moved and
was recovered after one year (denoted M,R); 2) it did
not move and was recovered after one year (NM.R); 3)
it moved and was not recovered after one year (M.NR);
4) it did not move and was not recovered after one year
(NM.NR). These four possible recapture outcomes ap-
plied to animals tagged and released in both strata,
McGarvey: Estimating emigration rates from marine sanctuaries using tag-recovery data
467
80
60
50
40
20
12
10
8
6
4
2
0J
Fished zone
M
}MM)
0 0
1 — JT-Th-n-i ~
Sanctuary
firm \h
m
0 12 3 4 5 6
Time at large (years)
Figure 2
Histograms over time at large (in monthly bins! of recapture
numbers from the fishing zone iMFA blocks 33 and 40 i and from
the Gleesons Landing Lobster Sanctuary. The diamond mark-
ers indicate divisions between modes at 0.5, 1.5., 2.5, etc. years
at large; recaptures from the sanctuary and fishing zone that
occurred between 0.5 and 1.5 years after release (between the black
diamond markers! identify the subsets of data used to estimate
yearly emigration rate from the sanctuary.
inside and outside the sanctuary. The tag-recovery data
provided direct measures for only three of these eight
possible numbers of recaptures.
We define "not recovered" to include both tagged ani-
mals that were not recaptured, as well as those that
were recaptured by a fisherman but whose tag informa-
tion (notably the location of recapture) was not reported
back to researchers and therefore was not included in
the tag-recovery database.
The movement-rate estimate is given in terms of the
following data inputs: the number of lobsters tagged
and released in li fished and 2) protected zones, and
the numbers recovered that 3) moved (>3 km) or 4) did
not move from the fished zone over one year after tag-
ging, and the 5) number that moved (>3 km) from the
sanctuary in one year.
Superscripts 'F' and 'S' denote fished zone and sanc-
tuary, respectively, for the location of tag release. Let
N^MR and Nfj R denote the numbers of animals that
were recovered after a year and that moved or that did
not move in the fished zone. From animals tagged and
released inside the sanctuary, only the number that
moved and were recovered (A^;/?) is available as an un-
biased measure. In addition, we know the total number
of animals originally tagged and released in the fished
zone and sanctuary, Nj. and N^. Input quantities from
the tag-recovery data set will henceforth be indicated by
a tilde ("): (iV® R iVf. N$MiRj N? R_ N% } (Table 1).
Assumptions
Three assumptions were used to derive an emigration-
rate estimate: 1) The two ways to define an estimate for
the proportion that moved within the fished zone, namely
as a proportion by using only recapture numbers, and
as a proportion over the number originally tagged, can
be set equal. 2) Recapture probabilities of animals that
were tagged and released inside the sanctuary and that
moved are assumed to equal those that were tagged and
released into the fished zone and that also moved. (The
first two assumptions were employed explicitly in steps
2 and 3 below.) 3) A third assumption is implicit in step
2, specifically in the recapture-conditioned movement
proportion in the fished zone (.PjtfR, Eq. 2): recapture
probabilities of animals tagged and released in the
fished zone that moved and of those that did not move
are assumed to be equal. Assumptions 2 and 3 would
both follow from assuming equal recapture probabilities
for all lobsters in the fished zone.
Emigration rate: derivation of the estimate formula
In this section, an emigration-rate formula is derived. It
provides a closed-form estimate of the yearly proportion
of lobsters emigrating out of the sanctuary.
The proportion of animals moving can be estimated
from tag-recovery data in two ways, namely as "tag-
468
Fishery Bulletin 102(3)
conditioned" and "recapture-conditioned" proportions.
A tag-conditioned movement proportion (Eq. li is the
total number of lobsters that moved (>3 km) divided by
the number originally tagged and released. It includes,
in the numerator, all tagged animals that moved, both
those that were recovered, as well as those that were
not recovered. With a recapture-conditioned movement-
rate estimate (e.g., Eq. 2), only counts of recaptured
lobsters are used. The estimate expresses the movement
proportion as the number of tagged animals that were
recaptured and that also moved l>3 km) divided by the
total number recaptured. These two definitions for the
movement proportion will be used to derive an estima-
tion formula in terms of the five data inputs.
Step 1 The derivation begins by writing the estimate
for proportion of lobsters that moved (P|f) in tag-condi-
tioned form:
Ns + Ns
pS _ JV MR T .U..YW
N*
(1)
This estimate of movement rate from the sanctuary is
based on a tag-conditioned proportion because we have
no observations of recaptured lobsters from the sanctu-
ary that did not move (no unbiased measure of NfjMM)
which a recapture-conditioned movement proportion
would have required. However we did have information
about N§fNR, the nonrecovery of tagged animals that
emigrate from the sanctuary into the fished zone. It can
be estimated (steps 2 and 3) with the second assumption
that recovery rate for lobsters moving from the sanctu-
ary equals that of lobsters moving (>3 km) within the
fished zone.
Substituting Equations 2 and 3 into Equation 4 and solv-
ing for NF, XR, the number of lobsters that moved >3 km
within the fished zone but were not recovered, yields
NF = NF
NF
NF +N
1
(5)
Step 3 Assumption 2 permits the derivation of a for-
mula forWS yR. We first define the recovery proportions
of animals that moved within the fished zone (F) as
fF =
I m
NF
'^ MM
Mr +MF
1 v U .XR A * M M
(6)
and from the sanctuary (S) as
fs
I M
Nt
iV.U XR T .V.fl
(7i
Assumption 2, that the recovery rate (necessarily in the
fished zone) for animals that were tagged and released in
the sanctuary and that moved into the fished zone is the
same as for animals that were both released and recap-
tured after moving within the fished zone becomes
fF = fs
I M I M ■
(8)
Substituting Equations 6 and 7 into Equation 8 and
rearranging terms, we have
iy M.XR
Ns (NF + Nf )
N
n;
(9)
Step 2 Under assumption 1, the two ways in which
movement proportion in the fished zone can be defined
(as tag- and recapture-conditioned proportions) are
equated. For fished zone releases, the recapture-condi-
tioned Crc') movement proportion is written
N*
NF +NF
(2)
For the recapture-conditioned estimate formula (Eq. 2),
all three quantities on the right-hand side are given as
data inputs. With only numbers of lobsters recovered, the
formula is, in this sense, conditional on recapture.
The tag-conditioned I7c'» proportion of lobsters moving
>3 km of those released in the fished zone is written
Af^ +NF
,/• ,, _ lyM.R TJVM,.Vfl
NF
The first assumption is
Din _ pf.l
rM ~ rM
(3)
i4i
Step 4 Substituting Equation 5 into Equation 9 and
substituting the result into Equation 1 yields a closed-
form estimation formula for the quantity we seek, the
proportion moving from the sanctuary in one year:
Ps=-
Nf
■ArS
/Vs' ■iNF +Nh )
(10)
Numerical estimator: double-hypergeometric likelihood
method
A likelihood formulation of this estimator was also
constructed. The likelihood function describing a single
tag-recapture experiment is hypergeometric (Seber,
1982; Rice, 1995) because sampling is without replace-
ment. The set of possible outcomes from each of the
two tagging experiments can be formulated as a 2x2
contingency table for the experimental populations of all
lobsters originally tagged and released. The two pairs
of outcomes represented in each contingency table are
"moved" or "not moved" and "recovered" or "not recov-
ered," yielding the four possible outcomes from both sets
of tag releases (see "Notation" section).
McGarvey: Estimating emigration rates from marine sanctuaries using tag-recovery data
469
In this study the data from two interacting tag-recov-
ery experiments were used to generate an estimate of
reserve emigration rate, namely of lobsters tagged and
released into the sanctuary and into the fished zone.
Thus, the product of a pair of linked hypergeometric
probability mass functions, each corresponding to a 2-
way contingency table, is the natural form of the likeli-
hood function for Pfj.
The derivation of Equation 10 was made with two as-
sumptions, namely Equations 4 and 8. Incorporated in
the likelihood, the two assumptions constrain the eight
recapture numbers in the contingency tables. In the
likelihood formulation, a third constraint was needed
which is analogous to assumption 1 but which applies
to sanctuary releases.
The derivation for constructing this likelihood from
a pair of linked hypergeometric probability functions
will proceed by 1) writing out the "raw" contingency
tables in terms of the eight recapture numbers (TV),
as denoted in the "Tag-recovery data" and "Notation"
sections, 2) algebraically re-expressing the elements
of the tables so that the parameter to be estimated is
explicit. 3) imposing the three constraints, and 4) writ-
ing out the likelihood, using the hypergeometric form
for contingency tables.
For the lobsters tagged and released in the sanctuary,
the raw contingency table is
Recovered
Not recovered
Totals
Moved
MS
" M.R
MS
"M.NR
fjS + MS
"M.R * " M.NR
Not moved
MS
"nm.r
MS
"nm.nr
NST-
Totals
MS . MS
" M.R + "NM.R
NST-
ftf.
For the lobsters tagged
in the fished zone
Recovered
Not recovered
Totals
Moved
NF
" Mil
NF
"m.nr
"M.R + "M.NR
Not moved
MF
"NM.R
NF
"nm.nr
Totals
^M.R + ^NM.R
NF-
NF
The two hypergeometric probability mass functions
(pmfsi giving the model-predicted proportion of lobsters
that moved and were recovered, based on the two con-
tingency tables, are written as
* Km)-
N* +N
ly M.R T ly M.NR
NF
N*
-(N +N )
ylyM.R TJV M.NR'
NF
\\
NF
(12)
N +N
ly MR * NM.R )
Because the goal is to estimate the movement propor-
tion, Pft (rather than any specific value of N), this pro-
portion will need to be made explicit in the likelihood
function as the sole freely varying parameter. Substitut-
ing from the definition of Py (Eq. 1), we have
m" = ps . AT* _ MS
lyM.NR 1M iyT lyM.R-
(13)
Substituting for all occurrences of Nfj NR, Equation 11
becomes
p«o=
PmK)(N^(1-P^^
Ni
AT?
N*
Ns + Ns
ly M.R T ly NM.R )
(14)
Writing the full joint-likelihood expression formed by
the product of the two hypergeometric pmfs gives
L =
NF +NF V NF -(NF +Nr )
ly M.R T ly M.NR ly T yly M.ff T ly M.NR '
NF
NF
'
NF
1
NF +NF
{■ly M R ly NM.R )
(Pm-Nt)
(N*-Q.-F*j\
{ K.R J
Ns
\ lyNM.R )
( Nt }
k
K,
+ NS
? T JY NM.R )
As formulated, the value of Nf!M R is still undeter-
mined by data or constraint. A third constraint is
therefore required. As with assumption 1 for the fished
zone (Eq. 4), we apply the assumed equivalence of tag-
and recapture-conditioned proportions to the sanctuary
releases:
ps.rc »>-& /(/Vs +/Vi ) = P '
rM ly M.R ' yly NM.R T ly M.R' *M
-(MS +MS )/ fjs
~Xly MR + IV M.NR" lyT-
P<Nm.r) =
MS . AfS
ly M.R T ly M.NR
Ns
Ms _ i \r> + ms ,
" T W,M.R ^lyM.NR'
Ns
Ms +MS
ly M.R Tiv NM.R I
In this application, Nf,M R is understood as the number
of lobsters that would have been taken if fishing had
1 1 1 1 not been excluded from the sanctuary. Solving for N^M R
yields the third constraint.
MS -IMS .MS)/iMS ,JU* )_MS
ly NM.R ~yly M.R lyT " WV M.R^ly M.NR1 lyM,R'
470
Fishery Bulletin 102(3)
Table 2
Intermediate calculated quantities from the numerical estimation. The equalities of P[jr
and 2.
=P£" and /'(,=/'« state
assumptions 1
Intermediate quantity
Variable name
Estimate
The proportions of lobsters tagged in the fishing zone that moved (>3 km I;
recapture-conditioned <P[jr '") or tag-conditioned iPy'0)
pF.ri_pF.ti
rM ~rM
0.243
Number of lobsters that moved but were not recovered in the fishing zone
ATF
" M.NR
697.7
Number of lobsters that moved from the sanctuary but were not recovered
Ns
iv M.NR
227.3
Number of lobsters that did not move and would have been recovered had
there been equivalent levels of harvesting in the sanctuary
MS
JV. VM.fi
17.7
Recovery proportions (in the fishing zone) — assumed to be equal for lobsters
that moved inside the fishing zone f[: or from the sanctuary
fF-fS
1 M~'M
0.113
without which this numerical estimator did not con-
verge.
The factorial terms in the binomial coefficients of
Equations 12 and 14 are defined only for natural num-
bers. However, in numerical minimization, factorials
must be replaced with continuously varying approxima-
tions because the negative log-likelihood objective func-
tion is minimized by using numerical derivatives. The
factorial z! was extended from natural numbers to the
real line by using the gamma function, T(z+1) and by
using an asymptotic approximation formula for In T(z)
(Eq. 6.1.41 in Abramowitz and Stegun, 1965):
lnr<2) =
1
InO
1, „ 1
z + - ln( 2/r ) +
2 12z
1
1
691
360z!
1
(15)
12602s I68O27 11882!' 360360211 15621
The negative log likelihood was minimized numeri-
cally by using the AD Model Builder parameter estima-
tion software (http://otter-rsch.com/admodel.htm).
Results
The closed-form estimator for the proportion of lobsters
that moved from the sanctuary (P|j) gave an estimate of
0.6206; i.e., about 62% of the lobsters tagged in Gleesons
Sanctuary moved out in one year. The estimate obtained
numerically, by maximizing the double-hypergeometric
likelihood, yielded a value of 0.6212.
The small difference between the analytic and nu-
merical estimates (0.09%) is presumably due to the
use of the numerical approximation for the log-gamma
function by the expansion of Equation 15. The close
agreement suggests that the error introduced by that
approximation is small.
The AD Model Builder parameter estimation soft-
ware allows one to estimate confidence intervals of the
movement-rate estimate in two ways: asymptotically.
as diagonal elements of the covariance matrix, and by
6 -
/"\
5 -
/ \
4-
/ \
3 -
/ \
2 -
/ \
1 -
J \
0-
^^r^
0.4 0 5 0.6 0.7
Estimate values for Pf .
0.8
Figure 3
Profile likelihood (solid line) and asymptotic normal
approximation (dashed line) for the likelihood confidence
range about the estimate of PM.
using a profile likelihood. Confidence intervals for the
emigration rate estimate were thus obtained numerical-
ly from the hypergeometric likelihood by using both the
asymptotic normal approximation and an exact profile
likelihood. These gave 95% errors of 21.2% and 21.5%
of the estimate, respectively. The approximate normal
probability density function and the profile likelihood
probability density function were also plotted (Fig. 3),
yielding close agreement. Asymptotic confidence inter-
vals therefore appear satisfactory for emigration propor-
tion estimates not lying near the bounds of 0 and 1.
Intermediate calculation results (Table 2) included
the recovery rate and movement rate (>3 km) within
the fished zone.
When independent estimates of exploitation rate are
available, typically from stock assessment, the rate of
tag reporting can be calculated from the tag-estimated
recovery rate. The exploitation rate (yearly proportion of
legal-size lobsters harvested) for the recapture year and
McGarvey: Estimating emigration rates from marine sanctuaries using tag-recovery data 471
location of the present study (the 1995 northern zone
rock lobster season) was estimated to be 26% (Ward et
al.3) by using total yearly effort and catches by weight
and number and a vector of weights at age. The tag-re-
covery rate of 11.3% (Table 2) is the estimated propor-
tion of tagged lobsters that were captured and for which
tags were reported. Thus the estimated tag-reporting
rate (of those recaptured) is 0.113/0.26 = 43%. If tag
shedding and natural mortality were also incorporated
as additional causes for nonrecovery, the estimate would
fall in the neighborhood of a 50% tag-reporting rate.
This estimated level of tag-reporting falls within the
range considered probable by fishermen. Thus, the re-
covery-rate estimate falls within a plausible range of
values, adding confidence that the tag-recovery data
are consistent with external estimates of exploitation
rate.
Substantial movement of Jasus edwardsii out of a ma-
rine sanctuary was previously observed in New Zealand
(Kelly and MacDiarmid, 2003) but not in Tasmania
(Gardner and Ziegler4). Long-distance movement of
this genus was also observed in New Zealand (Booth,
1997) but was much less common in Tasmanian Jasus
edwardsii populations (Gardner et al., in press).
Discussion
The emigration-rate derivation above combined recap-
ture-and tag-conditioned movement proportions. Both
ways to define a movement rate were used to constrain
the range of solutions for both analytic and numerical
estimators. Equating these two definitions for movement
proportion reduced the degrees of freedom by 1, thereby
circumventing the absence of a count of recaptured lob-
sters from within the fished zone.
Previous estimators of movement rates among spatial
cells from tag-recovery data have used either tag- or
recapture-conditioned approaches. Hilborn (1990: see
also Quinn and Deriso, 1999) developed a tag-condi-
tioned movement-rate estimator. This estimator gen-
erally requires prior knowledge of the tag reporting
rate. Schwarz et al. (1993) employed data consisting
of simultaneous tag releases and recaptures repeated
over a number of years at the same time each year to
estimate movement, survival, and recovery rates in
each spatial stratum. Schwarz et al. (1993) presented
a general formulation for modeling this multiple yearly
3 Ward, T. M., R. McGarvey. Y. Xiao, and D. J. Brock.
2002. Northern zone rock lobster [Jasus edwardsii) fish-
ery. South Australian Fisheries Assessment Series Report
2002/04b. 109 p. Aquatic Sciences, South Australian
Research and Development Institute (SARDI): RO. Box 120,
Henley Beach, South Australia 5022. Australia.
4 Gardner, C, and P. Ziegler. 2001. Are catches of the south-
ern rock lobster Jasus edwardsii a true reflection of their
abundance underwater? Tasmanian Aquaculture and Fish-
eries Institute Final Report. TAFI (Tasmanian Aquaculture
and Fisheries Institute), University of Tasmania, Private
Bag 49, Hobart TAS 7001, Australia.
tag-recovery data set, extending a series of estimators
for movement and survival (Arnason, 1972, 1973), and
estimated the rate of tag recovery. Brownie et al. (1993)
generalized the estimator of Schwarz et al. to non-Mar-
kovian movement rates. McGarvey and Feenstra (2002),
following Hilborn, used the less costly and more com-
monly available single tag-recovery data employed in
the present study but adopted a recapture-conditioned
approach for estimating yearly movement rates. With
"numbers recaptured" appearing in both the numerator
and denominator, all nonspatially dependent sources of
variation (such as tag reporting and shedding, short-
and long-term tag-induced mortality, and natural mor-
tality) cancel from the predicted recapture-conditioned
likelihood proportions. This procedure permits a cor-
responding reduction in the prior information required
to obtain unbiased movement estimates.
When recapture times vary, movement estimation is
sensitive to spatial differences in mortality rate, no-
tably between tag and recapture cells. Assuming that
the nonreporting rate is unknown, mortality can be
inferred from single tag-release information only impre-
cisely, for example by using mean tagged time at large.
For this reason externally obtained mortality estimates,
typically from stock-assessment models using fishery
data, can be usefully combined with single tag recover-
ies in movement estimation. Hestbeck (1995) showed,
when survival differs by cell, that ignoring the time of
movement between yearly samples could bias movement
estimates. McGarvey and Feenstra (2002) made explicit
the variation in residence time and thus survival in
source (tag-release) and destination (recapture) cells for
each recaptured animal. By using prior knowledge of a
migration season, migration source cell and destination
cell residence times can be approximated as the time
from the date of tag release to an assumed fixed (yearly)
date of movement, and from that date to the date of re-
capture. These residence times are used in exponential
survival factors that differ spatially given externally-
estimated fishing mortality rates in each cell.
For the data set available from Gleesons Landing, all
tagged animals were released during the peak fishing
season (mid-summer). Thus recoveries from the fol-
lowing fishing season had a mean and mode near the
desired one-year-at-large. In future tag-recovery stud-
ies, where a yearly movement rate is sought, a similar
choice for timing of tag releases, namely during the
season of highest fishery catches, should yield a peak in
recaptures a year later. Schwarz et al. (1993) employed
this strategy with their multiple yearly tag-recovery
data sets.
In the estimator presented above, variations in ex-
pected recovery numbers versus time, notably due to sur-
vival, were neglected. The small sample (33 recoveries
between 0.5 and 1.5 years from the sanctuary) and lack
of recaptures from within the sanctuary necessitated
more modest estimation goals. Among data classes avail-
able for movement analysis, notably 1) multiple yearly
tag recaptures by researchers in all cells, 2) multiple
yearly tag recoveries where recapture is by fishermen (or
472
Fishery Bulletin 102(3)
hunters) in all cells, 3) single tag recoveries by fishermen
in all cells, and 4) the data set employed in the present
study of single-tag recoveries by fishermen in one of two
cells, the latter represents the low end in quality and
quantity of information about movement and survival.
A time-dependent approach could theoretically extend
the approach of McGarvey and Feenstra (2002) to make
explicit the residence times of each recaptured indi-
vidual in the fishing zone and sanctuary, respectively,
and thus make explicit differences in the predicted
survival rate before and after movement. However with-
out prior knowledge of when movement took place for
each recaptured lobster, a modified likelihood method
is called for, requiring integration over the probable
movement times between tag release and recapture.
This extension of residence-time-dependent movement
estimators to variable times of movement remains a
topic for future research.
Acknowledgments
I thank Hugh Possingham, Andre Punt, and two review-
ers for comments on the draft manuscript. Lobsters
were tagged and released into Gleesons Landing sanctu-
ary by Greg Ferguson, together with fishermen Lenny
and Murray Williams, under Fisheries Research and
Development Corporation Project 93/086. This work was
supported by the Australian Fisheries Research and
Development Corporation Project No. 2000/195, and by
the South Australian rock lobster industry.
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1997. Long-distance movements in Jasus spp. and their
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653-671.
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1995. Bias in transition-specific survival and movement
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1990. Determination offish movement patterns from tag
recoveries using maximum likelihood estimators. Can.
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473
Abstract— We describe reproduc-
tive dynamics of female spotted sea-
trout (Cynoscion nebulosus) in South
Carolina (SC). Batch fecundity iBFl.
spawning frequency (SF), relative
fecundity (RF), and annual fecundity
(AF> for age classes 1-3 were esti-
mated during the spawning seasons of
1998, 1999, and 2000. Based on histo-
logical evidence, spawning of spotted
seatrout in SC was determined to take
place from late April through early
September. Size at first maturity was
248 mm total length (TL); 50% and
100% maturity occurred at 268 mm
and 301 mm TL, respectively. Batch
fecundity estimates from counts of
oocytes in final maturation varied
significantly among year classes. One-
year-old spotted seatrout spawned an
average of 145.452 oocytes per batch,
whereas fish aged 2 and 3 had a mean
BF of 291,123 and 529,976 oocytes,
respectively. We determined monthly
SF from the inverse of the proportion
of ovaries with postovulatory follicles
(POF) less than 24 hours old among
mature and developing females. Over-
all, spotted seatrout spawned every
4.4 days, an average of 28 times
during the season. A chronology of
POF atresia for water temperature
>25°C is presented. Length, weight
(ovary-free), and age explained 67%,
65%, and 58% of the variability in
BF, respectively. Neither RF (number
of oocytes/g ovary-free weight) nor
oocyte diameter varied significantly
with age. However. RF was signifi-
cantly greater and oocyte diameter
was smaller at the end of the spawn-
ing season. Annual fecundity esti-
mates were approximately 3.2, 9.5,
and 17.6 million oocytes for each age
class, respectively. Spotted seatrout
ages 1-3 contributed an average of
29%, 39%, and 21% to the overall
reproductive effort according to the
relative abundance of each age class.
Ages 4 and 5 contributed 7% and 4%,
respectively, according to predicted
AF values.
Reproductive dynamics of female spotted seatrout
(Cynoscion nebulosus) in South Carolina*
William A. Roumillat
Marine Resources Research Institute
South Carolina Department of Natural Resources
217 Ft. Johnson Rd
Charleston, South Carolina 29412
E-mail address roumillatbiSrnrd.dnr.state.sc.us
Myra C. Brouwer
South Atlantic Fishery Management Council
One Southpark Center, suite 306
Charleston, South Carolina 29407
Manuscript submitted 13 May 2002
to Scientific Editor's Office.
Manuscript approved for publication
19 March 2004 by the Scientific Editor.
Fish. Bull. 102:473-487 (2004).
The spotted seatrout iCynoscion neb-
ulosus) is an estuarine-dependent
member of the family Sciaenidae. Spot-
ted seatrout are year-round residents
of estuaries along the South Atlantic
coast and spawning takes place inshore
and in coastal areas (McMichael and
Peters, 1989; Mercer1; Luczkovich
et. al.2). As in many other sciaenids,
spawning in this species occurs in
the evening (Holt et al, 1985). Male
spotted seatrout have the capacity to
produce "drumming" sounds that are
caused by the contraction of the swim-
bladder by specialized muscles that
are seasonally hypertrophied from the
abdominal hypaxialis muscle mass
(Fish and Mowbray, 1970; Mok and
Gilmore. 1983). Direct involvement of
sound production with spawning has
been shown for this and other sciae-
nids (Mok and Gilmore, 1983; Saucier
et al., 1992; Saucier and Baltz, 1993;
Luczkovich et al.2).
We have collected information on
the spawning behavior of spotted sea-
trout in coastal South Carolina since
1990 (Saucier et al., 1992; Riekerk
et al.3). Spawning aggregations were
located by listening for drumming
sounds from late afternoon until
-2300 h with passive hydrophone
equipment. Spawning activity was
subsequently verified through collec-
tions of newly spawned eggs and by
the rearing of the larvae in the labo-
ratory (Saucier et al., 1992).
Spotted seatrout are group-synchro-
nous spawners with indeterminate fe-
cundity and the protracted spawning
season extends from April through
September along the South Atlantic
and Gulf of Mexico coasts (Overstreet,
1983; Brown-Peterson et al.. 1988;
McMichael and Peters, 1989; Saucier
and Baltz, 1993; Brown-Peterson and
Warren, 2001; Brown- Peterson et al.,
2002; Nieland et al.. 2002, Brown-
* Contribution 539 from the Marine
Resources Research Institute of the
South Carolina Department of Natu-
ral Resources, Charleston. SC 29422-
2559.
1 Mercer. L. P. 1984. A biological and
fisheries profile of spotted seatrout.
Cynoscion nebulosus. Special Scien-
tific Report 40, 87 p. North Carolina
Department of Natural Resources and
Community Development, Division of
Marine Fisheries. Morehead City, NC
28577.
2 Luczkovich, J. J.. H. J. Daniel III and M.
W. Sprague. 1999. Characterization of
critical spawning habitats of weakfish.
spotted seatrout and red drum in Pamlico
Sound using hydrophone surveys. Final
report and annual performance report F-
62-2 and F-62-2, p 65-68. North Caro-
lina Department of Environment and
Natural Resources, Division of Marine
Fisheries, Morehead City, NC 28557.
3 Riekerk. G. H. M„ S. J. Tyree, and W.
A. Roumillat. 1997. Spawning times
and locations of spotted seatrout in the
Charleston Harbor Estuarine System
from acoustic surveys. 21 p. Final
Report to Charleston Harbor Project,
Bureau of Ocean and Coastal Resources
Management, South Carolina Depart-
ment of Health and Environmental Con-
trol, 1362 McMillan Ave., Charleston,
SC 29405.
474
Fishery Bulletin 102(3)
Peterson, 2003; Wenner et al.4). As in other indetermi-
nate spawning fish, annual fecundity in this species is
determined by the number of oocytes released during
each spawning event (batch fecundity) and the number
of spawning events occurring during the course of the
spawning season (spawning frequency!. Early efforts to
estimate fecundity for spotted seatrout did not take into
account the repetitive nature of spawning activities in
this species (Pearson, 1929; Sundararaj and Suttkus,
1962; Overstreet, 1983) and only recently has an effort
been made to coordinate batch fecundities with spawn-
ing frequencies (Brown-Peterson et al., 1988; Brown-
Peterson and Warren, 2001; Nieland et al., 2002). This
procedure is intuitively necessary to estimate the re-
productive output for an entire spawning season and
is made even more useful for fisheries management if
separated by size class or age cohort within a popula-
tion (Prager et al.. 1987; Goodyear, 1993; Zhao and
Wenner5).
An important component of assessment for manage-
ment involves determining the spawning potential ratio
(SPR), a measure of the effect of fishing on the repro-
ductive potential of a stock (Goodyear, 1993). This value
is usually calculated as the ratio of spawning stock
biomass per recruit (SSBR) in the presence of fishing
mortality (F) to the SSBR when F is equal to zero (Ga-
briel et al., 1989; Goodyear, 1993). Spawning potential
ratio is currently used as a biological reference point
for definition of recruitment overfishing (i.e., Vaughan
et al., 1992). The calculation of SPR can be improved,
however, by introducing egg production into the model.
Fecundity is a much better predictor of reproductive po-
tential than female biomass. Moreover, SPR calculations
based on egg production may be more sensitive to the
size-age composition of the spawning stock. However,
accurate annual fecundity estimates for use in stock
assessment do not exist for this or many other species
in need of fisheries management. Therefore, our goal
was to obtain batch fecundity (BF), spawning frequency
(SF), and annual fecundity (AF) estimates for spotted
seatrout by age class.
Materials and methods
Data to address the main objectives of this study were
collected from late April through early September 1998-
1 Wenner, C. A., W. A. Roumillat. J. E. Moran Jr., M. B. Maddox,
L. B. Daniel III, and J. W. Smith. 1990. Investigations
on the life history and population dynamics of marine rec-
reational lishes in South Carolina: part 1. Final Report
F-37, 177 p. Marine Resources Research Institute, Marine
Resources Division, South Carolina Department of Natural
Resources, 217 Ft. Johnson Rd., Charleston, SC 29412
s Zhao, B., and C. A. Wenner. 1995. Stock assessment and
fishery management of the spotted seatrout, Cynoscion nebu-
losus, on the South Carolina coast, 90 p. Marine Resources
K' i arch Institute, Marine Resources Division, South Caro-
lina Department of Natural Resources, 217 Ft. Johnson Rd..
Charleston, SC 29412.
2000 as part of a long term monitoring effort 11991-pres-
ent) to assess the relative abundance of age classes of
recreationally important finfish in South Carolina estu-
aries. The study followed a monthly stratified random
sampling design in three estuarine systems. The Cape
Romain system comprised two strata; Romain Harbor
and northern Bulls Bay. The Charleston Harbor system
contained four strata: the Wando, Cooper, and Ashley
Rivers, and Charleston Harbor. The Ashepoo-Combahee-
Edisto (ACE) Basin system comprised a single stratum
(Fig. 1). The number of sampling sites within each stra-
tum ranged from 23 to 30. A subset of 12-14 sites was
randomly selected each month. Sampling was conducted
only during the daytime ebbing tide (0700-1800 h),
primarily over mud and oyster shell substrates adjacent
to the Spartina alterniflora marsh. At each site, we
deployed a trammel net (182.8 m long by 2.4 m deep;
outer walls: 17.8 cm square (35.6 cm stretch]; inner wall:
3.2 cm square [6.4 cm stretch]) from a rapidly moving
shallow water boat in an arc against the shoreline at
depths ranging from 0.5 to 2.0 m. We disturbed the
water within the site in an effort to frighten fishes into
the entrapment gear. We then hauled the trammel net
back into the boat and removed the catch, which was
kept alive in a 70-liter oxygenated holding tank. Spot-
ted seatrout were measured for total length (TL) and
standard length (SL) and a subsample offish from each
effort (5-10 individuals for each 20-mm size interval per
month) were sacrificed, placed on ice, and transported to
the laboratory for aging and reproductive data.
Specimens were processed in the laboratory 2-12
hours after capture. We recorded standard life-history
parameters (TL, SL, fish weight, gonad weight, sex, and
maturity) for each specimen. The following equation was
used to convert lengths when necessary:
TL = 5.689 + 1.167ISL) (r- = 0.998)
n = 1191.
We removed sagittal otoliths for aging and preserved
sections (<2% by weight) of each ovary in neutral buff-
ered formalin for histological processing. The latter
involved standard procedures for paraffin embedding
and sectioning, and standard hematoxylin and eosin-y
staining (Humason, 1972). Histological sections were
viewed under a Nikon Labophot compound microscope
equipped with a teaching head so that two readers
could interpret sections simultaneously. Maturity
estimation was modified from that of Wenner et al.4
(Table 1).
Size at first maturity was histologically derived by
first evidence of cortical alveoli stage oocytes. To ar-
rive at estimates of 50% and 100% maturity, data were
subjected to PROBIT analysis.
Age determination
The left sagittae were marked with a soft lead pencil
through the core and embedded in epoxide resin. A
transverse section (~0.5-mm thick) was taken through
the core by using a low-speed saw equipped with a pair
Roumillat and Brouwer: Reproductive dynamics of Cynoscion nebulosus
475
80 30W 80 O'W 79 30'W
Figure 1
The three South Carolina estuarine systems (indicated by arrows) where C. nebulosus were collected.
Table 1
Criteria used for microscopic staging of C. nebulosus ovaries. FOM = final oocyte maturation; POF = postovulatory follicle.
Stage
Description
Immature Ovary small in cross section. Early stage with only oogonia evident; later stage with small
(<0.08 mm) primary oocytes, tightly packed. No evidence of early vitellogenesis.
Developing First appearance of cortical alveoli stage oocytes through late vitellogenesis but no evidence of early
FOM (lipid and yolk globule coalescence).
Ripe Ovary containing oocytes demonstrating FOM (lipid and yolk coalescence through hydration).
Mature with day-0 POFs Ovary exhibits POFs <24 h (see Table 2 ). Found at all water temperatures throughout the spawning
season.
Mature with day-1 POFs Ovary exhibits POFs >24 h consisting of closely packed granulosa cells (0.08-0.1 mml. Only
identified in water < 25°C.
Spent Ovary containing alpha- and beta-stage oocytic atresia.
Resting Ovary containing small primary oocytes and oocytes with perinuclear nucleoli (<0.12 mm);
usually some remnants of oocytic atresia.
of diamond wafering blades. The resulting section was was assumed for the process of aging. Spotted seatrout
mounted on a labeled microscope slide and examined deposit an annulus in April or May (Murphy and Taylor,
with a Nikon SMZ-U microscope. A 1 January birth date 1994; Wenner et al.4). Fish in the first three months of
476
Fishery Bulletin 102(3)
Table 2
Criteria used for microscopic staging of C. nebulosus day-0 postovulatory follicles iPOFsl in water temperatures above 25°C.
Measurements represent longest axis of POFs.
POF chronology fin hours)
Description
0-4
5-8
9-12
13-24
Regular arrangement of granulosa-cell nuclei proximal to the basement membrane and
obvious multiple layering as described by Hunter and Macewicz 1 1985 ). 200-300 ^m i Fig. 4Ai.
Early signs of atresia, loss of the obvious layering, hypertrophy of granulosa cells, and a
general compaction with an investment of blood vessels. 180-250 jum (Fig. 4B).
Well-defined lumen separating the internal granulosa cells from the outer wall of granulosa
cells encompassed by theca. 150-200 jum (Fig. 4C).
Lumen reduced primarily by loss of granulosa tissue and proximity of peripheral layers. 130-
175 ^m (Fig. 4, DandE).
the year were aged by the addition of 1 year to the count
of the number of annuli on the thin sections. In April or
May, if the section had a large marginal increment, one
was also added to the annular count. If the marginal
increment was small or if the ring was detectable on the
edge of the otolith section, age was equal to the number
of annuli.
Seasonality
Spawning season for spotted seatrout in South Carolina
was determined by using two techniques. The gonadoso-
matic index (GSI) was calculated as
(GW/OFWT) x 100,
where GW = gonad weight (g); and
OFWT = ovary-free weight (g).
For years prior to this study (1991-97), mean monthly
GSI was obtained for all females by using data from
the South Caroline Department of Natural Resources
inshore fisheries archives (Wenner6). Reproductive sea-
sonality among female spotted seatrout throughout the
year was also examined by using histology (Table 1).
The first evidence of oocytes in final oocyte matura-
tion (FOM) as evidenced by lipid and yolk coalescence;
Brown-Peterson et al., 1988) or the occurrence of post-
ovulatory follicles (POFs) defined the beginning of the
spawning season. To determine the cessation of spawn-
ing, the percent occurrence of females in spawning
condition (ripe and repeat spawners) and those in post-
spawning condition (spent and resting) were obtained
for the months of August and September. To investigate
the condition of females, we examined Fulton's condition
factor (Ricker, 1975) over the spawning season using
linear regression.
6 Wenner, C. 2002. Unpubl. data. Marine Resources Re-
search Institute, Marine Resources Division, South Carolina
Department of Natural Resources, 217 Ft. Johnson Rd.,
i harleston, SC 29412.
Spawning frequency
We obtained samples for spawning frequency ( SFi deter-
mination from 1 May through 31 August 1998, 1999
and 2000. Although samples were routinely collected
throughout the year, only from early May through late
August did we capture enough animals in the appro-
priate reproductive state for SF estimation. Spawning
frequency was calculated as either the inverse of the
proportion of ovaries with day-0 POFs (Hunter and
Macewicz, 1985; Brown-Peterson et al., 1988) or with
oocytes in FOM (Brown-Peterson et al., 1988; Liso-
venko and Adrianov, 1991) among mature and develop-
ing females.
We designated two distinct morphological features
of POFs based on time of specimen capture and water
temperature. We interpreted the largest, least atro-
phied POFs to be <24 h old and termed them "day-0"
POFs (Hunter and Macewicz, 1985). The presence
of day-0 POFs in the ovary indicated that spawning
had occurred the previous night. The second category
comprised smaller POFs, which primarily consisted of
closely packed granulosa cells determined to be >24 h
old.
To complete the chronology of POF atresia we under-
took round-the-clock sampling on 27-28 June and 26
July 2000. During these efforts, sampling continued
beyond routine hours to encompass the period between
dusk and dawn. The histological samples obtained al-
lowed for the calibration of criteria used to age POFs
(Table 2). To determine whether SF varied among
months and age classes, Kruskal-Wallis tests were
used. Because both factors (month and age) were fixed
(model 1). it was not possible to test for their interac-
tion by using a two-way parametric ANOVA without
replication.
As a result of targeting fish for batch fecundity esti-
mates (see below), we had available numerous specimens
with oocytes in FOM with which to establish monthly
SF. However, we knew that these specimens were dis-
appearing from our shallow sampling sites into deeper
spawning areas as the day progressed (Riekerk et al.3),
Roumillat and Brouwer: Reproductive dynamics of Cynoscion nebulosus
All
thus potentially adding bias to our SF estimates. Even
though estimates of SF based on FOM were performed
a posteriori, we chose to report them strictly for com-
parison to other studies with this method. Because
sampling for females exhibiting FOM was accomplished
in a directed fashion, statistical comparisons were not
attempted.
Batch fecundity and relative fecundity
Observations taken over a decade of sampling the
Charleston Harbor estuarine system showed that in
females captured in shallow water (<1.5 m) during the
spawning season, FOM began at about 1200 h (Wenner6).
Similarly, Crabtree and Adams' reported FOM begin-
ning in Florida spotted seatrout at about mid-day. Low-
erre-Barbieri et al.8 found hydrated females in shallow
water in the vicinity of aggregations of drumming males
in deeper water. We also speculated that from mid-
to late afternoon hydrated females moved along the
marsh edge toward deeper water spawning aggrega-
tions (8-25 m). Hydrophone surveys conducted in the
Charleston Harbor area over several years (Riekerk et
al.3; Wenner6) indicated that noise production typically
began around 1800 h and ceased around 2200 h. Because
this behavior has been associated with spawning in this
and other sciaenids (Mok and Gilmore, 1983; Holt et al.,
1985; Saucier et al., 1992; Saucier and Baltz, 1993), we
assumed that spawning began at 1800 h and stopped at
2200 h. Thus we were able to target spotted seatrout in
the mid- to late afternoon specifically to capture females
with oocytes in the late stages of FOM for batch fecun-
dity (BF) estimation. Because we have consistently iden-
tified recently spawned females in shallow areas, they
apparently return to the marsh edge where they once
again become available for capture with our sampling
gear. Our stratified random sampling of estuarine areas
along the coast (described previously) was designed to
representatively sample these recently spawned females
for SF estimation.
We conducted BF sampling during two consecutive
afternoons fortnightly from the middle of April through
the first week of September 1998, 1999, and 2000. We
deployed a trammel net from a shallow water boat as
described above at preselected sites in Charleston Har-
bor in depths ranging from 1.0 to 1.5 meters during the
afternoon (1400-1800 h EDT) high tide.
7 Crabtree R. E., and D. H. Adams. 1998. Spawning and
fecundity of spotted seatrout, Cynoscion nebulosus, in the
Indian River Lagoon. Florida. In Investigations into near-
shore and estuarine gamefish abundance, ecology, and life
history in Florida, p. 526-566. Tech. Rep. for Fed. Aid in
Sport Fish Rest. Act Project F-59. Florida Marine Research
Institute, Department of Environmental Protection, 100
Eighth Ave. SE, St. Petersburg, FL 33701.
8 Lowerre-Barbieri, S. K., L. R. Barbieri, and J. J. Albers.
1999. Reproductive parameters needed to evaluate recruit-
ment overfishing of spotted seatrout in the southeastern
U.S. Final report to the Saltonstall-Kennedy (S-K) Grant
Program (grant no. NA77FD0074), 23 p.
Restricting our sampling to the hours immediately
preceding the evening spawning event ensured that
those females preparing to spawn were available for
capture. Male spotted seatrout, identified by their
drumming sounds, caught during this targeted effort
were measured and released at the site of capture. We
supplemented samples for BF estimation with specimens
from local sportfishing tournaments held during sum-
mer months in the Charleston Harbor area.
We processed samples in the laboratory as previously
described. If ovaries appeared by macroscopic examina-
tion to contain hydrated oocytes, they were fixed in 10%
buffered seawater formalin for potential counts (Hunter
et al., 1985). The appropriateness of these ovaries for
BF counts was subsequently determined by examining
the corresponding histological preparation.
To ensure that only those oocytes destined to be ovu-
lated during the upcoming spawning event were counted,
we chose to use only those oocytes undergoing FOM that
could be easily separated by size from late vitellogenic
oocytes (Nieland et al.. 2002; Lowerre-Barbieri et al.8).
If we observed numerous recent POFs in the histologi-
cal sample, the corresponding whole ovary was not used
for oocyte counts (because their presence indicated that
ovulation had occurred). We reweighed ovaries (approxi-
mately 2 weeks after fixation) to the nearest 0.01 g and
randomly extracted three 130-150 mg aliquots from
eight potential locations in the ovary (each lobe was par-
titioned into quarters lengthwise). We stored subsamples
in 50% isopropyl and counted oocytes under a Nikon
SMZ-U dissecting microscope at 12 x magnification. We
counted each subsample twice by using a Bogorov tray
and a hand-held counter and conducted a third count if
the two initial counts were dissimilar by more than 10%.
We used the mean number of oocytes in each subsample
to calculate mean oocyte density (number of oocytes per
gram preserved ovary weight) and total numbers of oo-
cytes in the ovary. We compared mean oocyte densities
among the four regions of each ovarian lobe and between
the two lobes by using a two-way analysis of variance
(ANOVA). Because our variances were heteroscedas-
tic, we used nonparametric ANOVA (Kruskal-Wallis or
ANOVA on ranks) for comparisons of mean BF among
ages, months, and years. To investigate the relationships
between BF and length, somatic weight (ovary-free body
weight), and age, we used linear regression.
Relative fecundity (RF) was calculated as the num-
ber of oocytes per gram somatic weight (ovary-free).
To select samples for inclusion in RF calculations, we
looked for the presence of nuclear migration in histo-
logical preparations. We used this criterion to ensure
that oocytes of similar morphological dynamics would
be used, minimizing the potential for error. We used
the Kruskal-Wallis test to investigate the effect of age
on RF. Because sample sizes were quite uneven among
months, we chose to compare RF between the beginning
and end of the spawning season (May and August). This
comparison was done by using a Mann-Whitney test.
To corroborate any trends in RF, we also conducted
diameter measurements on the preserved (10% buffered
478
Fishery Bulletin 102(3)
seawater formalin) oocytes. We used a
video camera mounted on a Nikon SMZ-U
dissecting microscope and coupled to a PC
equipped with a frame-grabber and with
OPTIMAS- Image Analysis software (ver-
sion 6, Media Cybernetics, Bothell, WA).
Two readers independently measured the
diameter of approximately 30 preserved
oocytes in each of three subsamples from
27 ovaries. To test for uniformity of size
throughout the ovary, mean oocyte diame-
ters were compared between ovarian lobes
and among subsample locations within
each lobe by using two-way ANOVA. We
also compared mean oocyte diameters
among months and ages by using two-
way ANOVA.
Annual fecundity
Month
Wiley (1996) demonstrated that spot-
ted seatrout in South Carolina estuaries
constitute a single population. Therefore,
we felt justified in calculating monthly
egg production (MEP) by multiplying the
monthly SF (of specimens taken along the
entire coast) by the mean monthly BF (of specimens from
Charleston Harbor). Because not all age-1 female trout
were mature at the beginning of the spawning season,
the fraction of mature age-1 females obtained from previ-
ous work in South Carolina (Wenner6) was used to refine
the MEP estimate. Because the latter was calculated by
using SF obtained from data pooled across years, any
comparison of MEP among years was deemed invalid.
Kruskal-Wallis tests were used to determine whether
MEP varied among months for each age class.
Monthly MEP estimates were summed to arrive at
an annual fecundity (AF) estimate for each age class.
Because the majority of individuals used in this study
were aged 1-3, AF was estimated only for these age
classes. We used linear regression to investigate the
relationship between AF and age and thus predict AF
for spotted seatrout aged 4 and 5. Using these predic-
tions and the relative abundance of each age class in
our samples, we estimated the contribution of each age
class to the annual egg production.
All statistical analyses were conducted with the Sta-
tistical Package for the Social Sciences (version 9.0,
SPSS Inc., Chicago, ID. The level of significance for
all tests was 0.05.
Results
A total of 1038 spotted seatrout ranging in age from
1 to 5 was collected for this study. Because 97% of
these belonged to age classes 1-3 we report reproductive
parameters only for these ages. We examined a total of
941 mature and developing females, ranging in Length
from 248 mm to 542 mm TL, to determine spawning
Figure 2
Mean monthly gonadosomatic index iGSIl for spotted seatrout in South
Carolina for years 1991-2000 (circles). Mean water temperature for
1991-2000 i triangles). Error bars are standard errors, n = 1185.
frequency (569, 285, and 87 for ages 1-3, respectively).
Of these, 135 specimens (12 from sportfishing tourna-
ments) were used to conduct oocyte counts (62, 52, and
21 for ages 1-3. respectively). These fish ranged in
length from 268 to 530 mm TL. Minimum size at first
maturity, as indicated by the presence of cortical alveoli
stage oocytes in histological sections, was 248 mm TL.
Size at 50'/c maturity was 268 mm, whereas 100'; matu-
rity was reached at 301 mm TL. Condition of females, as
indicated by Fulton's condition factor, diminished over
the course of the season (P<0.01, r2=0.24i.
Seasonality
Spawning in the Charleston Harbor area during the
study period began in mid to late April as indicated by
the presence of oocytes in late FOM or POFs in histo-
logical samples. During the study period, mean water
temperatures ranged from 16° to 34°C. Highest tem-
peratures were recorded during July and August for all
three years of the study. The lowest documented water
temperature when spawning began was 20°C. Cessation
of spawning occurred when water temperature was 28°C.
Mean monthly GSI for spotted seatrout captured along
the South Carolina coast since 1991 (Fig. 2) showed a
marked increase from 4.6 in April to 9.4 in May. Mean
GSI in June declined to 6.3 and remained around 5.0 in
July and August. A sharp decline was noted in Septem-
ber to 2.7, the lowest level for the season. Overall, mean
gonadosomatic index (GSI) values followed the seasonal
trend in water temperature (Fig. 2). Percent occurrence
of females in spawning condition as evidenced from
histological examination declined from approximately
87', in August to 12', in September. The percentage of
Roumillat and Brouwer: Reproductive dynamics of Cynoscion nebulosus
479
Spawning
Sampling
Day 0 POFs
• • •
m
A •
•- •
1800 t
2200
0200
0600
t 1000 *
1400
t 1800
Fig. 4 A
Fig. 4B
Fig. 4C
Fig. 4D Fig. 4E
Sampling
Day 1 POFs
Fig. 4F
A
m A
1800
•
2200
0200
0600
Figure
3
1000
1400
1800
Forty-eight-hour chronological time line indicating C. nebulosus spawning time in Charleston
Harbor, SC. Postovulatory follicles (POFs) observed at water temperatures >25 C were termed
day-0 (<24 hours). Day-1 POFs (>24 hours) were observed only at water temperatures <25°C.
Time of capture for specimens in Figure 4 are indicated.
post-spawning females increased from 99r in August to
91% in September. Thus, the spawning season for spot-
ted seatrout in South Carolina extends from late April
through early September.
Spawning frequency
Day-0 POFs were found through 1800 h of the day fol-
lowing a spawning event. Day-1 POFs were first observed
in our routine samples when they were 36-37 hours old
(the second day following a spawning event) only when
water temperatures were below 25°C. Day-1 POFs were
excluded from our analysis of SF because they did not
provide evidence of a previous night's spawning event.
Figure 3 illustrates the time line for POF atrophy in
spotted seatrout from 1-42 h after the onset of spawn-
ing at 1800 h. Because evidence of spawning for the first
12 h was documented only during a period when water
temperatures were greater than 25°C, all of the exam-
ples shown are indicative of atrophy in warmer tempera-
tures (Fig. 4). As indicated in Table 2, there was a time-
dependent deterioration of POFs such that only those
<24 h were detectable at water temperatures >25°C.
Small sample sizes prevented calculation of monthly
SF for each age class by year. Therefore, we pooled
data for all three years of this study to obtain a single
monthly SF estimate by age class (Tables 3 and 4).
The interaction between month and age on SF could
not be statistically tested; however, age-3 fish spawned
more frequently than younger fish (Kruskal-Wallis,
P<0.05) and all seatrout spawned more frequently in
June (Kruskal-Wallis, P<0.05). Peaks in SF observed
for fish ages 2 and 3 in July and August, respectively
(Tables 3 and 4), were not statistically significant.
Monthly SF values based on the occurrence of ova-
ries containing oocytes in FOM are also presented in
Table 3
Spawning frequency (SF) expressed as
the number of
spawnings per month for
C. nebulosus a
ges 1-3 for the
spawning seasons
of 1998
-2000. Numbers in parenthe-
ses repr
esent days
betweer
spawnings. n --
= number offish
in a sample. FOM
= final oocyte maturation; POF = post-
ovulatory follicle.
Age
SF
SF
(yr)
Month
n
FOM method
POF method
1
May
89
4.53(6.85)
4.18(7.42)
June
166
4.53(6.62)
9.40(3.131
July
185
4.68(6.62)
6.54(4.74)
August
129
6.26(4.95)
4.57(6.79)
Total
569
19.9(6.18)
26.34(4.67)
2
May
114
11.5(2.78)
6.80(4.56)
June
79
5.70(5.26)
7.60(3.95)
July
48
0.65(47.62)
9.04(3.43)
August
44
9.87(3.14)
6.34(4.89)
Total
285
30.67(4.011
29.36(4.19)
3
May
46
10.10(3.07)
7.42(4.18)
June
23
5.22(5.75)
9.12(3.29)
July
10
3.10(10.00)
3.10(10.00)
August
8
11.61 (2.67)
11.61(2.67)
Total
87
32.54(2.67)
31.14(3.95)
Overall
941
24.3(5.06)
27.7(4.44)
Table 3. However, statistical comparisons were not fea-
sible because of the nonrandom collection of specimens.
Overall SF was estimated to be once every 4.4 days and
once every 5.1 days with the POF and FOM methods,
respectively.
480
Fishery Bulletin 102(3)
l\»«.
•*•?•*►. .
Ml W
• V
100 um
Figure 4
Photomicrographs of C. nebulosus postovulatory follicles (POFs) showing chronology of atresia
at water temperatures >25°C. (A) 0-4 hours after spawning. (B) 5-8 hours after spawning.
<C) 9-12 hours after spawning, ID, E, F> 13-24 hours after spawning.
Batch fecundity
As expected, we found a significant difference in mean
BF among age classes (ANOVA on ranks, P<0.05). Age-1
spotted seatrout produced an average of 145,452 oocytes
per hatch spawned. Fish aged 2 and 3 spawned an aver-
age of 291,123 and 529,976 oocytes per batch, respec-
tively. Therefore, mean BF was compared among months
Roumillat and Brouwer: Reproductive dynamics of Cynosaon nebulosus
481
Table 4
Fecundity parameters for C. nebulosus ages 1-3 from South Carolina estuaries
BF = batch fecundity in numbe
•s of oocytes;
SF = spawning frequency based on the postovulatory follicle (POF) method and
expressed as the nun
tber of spawnin
is per month :
MEP = monthly egg production = (BF • SFi'i mature. Annual fecundity is
the
sum of mean month
y MEP values
ibr each vear
class and represents the total number of oocytes produced by any given female from 1 May to 31 Aug
jst. Numbers ir
parentheses
indicate sample sizes.
Age (yrl Month Mean BF
SF
'i mature
Mean MEP
1 May 117.760(12)
4.18(89)
78.6
386,897
June 135,403(161
9.40(166)
94.0
1,196,418
July 141,237(16)
6.54(185)
97.0
895,978
August 176.594(18)
4.57(129)
100
807,035
Annual fecundity=3,286,328 oocytes
2 May 280,724(34)
6.80(114)
100
1,908,926
June 307.322(101
7.60(79)
100
2,335,650
July 370.170(1)
9.04(48)
100
3,346,337
August 307,195(7)
6.34(44)
100
1,947,620
Annual fecundity=9,538,533 oocytes
3 May 487,475(131
7.42(461
100
3.617,061
June 519,630(4)
9.12(23)
100
4,739,027
July 765.911(2)
3.1(10)
100
2,374,325
August 590,994(2)
11.61(8)
100
6,861,439
Annual fecundity= 17.591,852 oocytes
Table 5
Monthly relative fecundity (number of oocytes
1998-2000. SD = standard deviation.
/grams ovary-free weight) for C. nebu
losus
ages 1-
-3 for the spawning seasons
Month
Mean
Minimum
Maximum
SD n
May
518.6
223.9
976.1
146.2 46
June
603.2
205.7
1306.1
241.8 20
July
820.9
662.2
1314.4
279.0 5
August
693.6
397.3
1021.8
207.9 12
and years for each age class separately (Table 4). There
were no significant interannual or monthly variations in
mean BF for any of the age classes (age-1: P=0.59, ;; = 62;
age-2: P=0.17, n=52; age-3: P=0.07, n=21). However, BF
analysis for age-2 fish excluded the month of July because
only one two-year-old specimen was captured that month
during the study period. We investigated the relationship
between BF and total length by using linear regression
analysis. After pooling data across years, we found that
total length explained 67% of the variability in spotted
seatrout BF (Fig. 5A). Batch fecundity showed a similarly
strong relationship to female somatic (ovary-free) weight
(Fig. 5B) but did not relate to age as strongly (Fig. 5C).
The equations below describe these relationships:
BF= 2179.65ITL) - 520597
BF = 530.60IOFWT) + 18537.77
BF = 169398. 21( Age) - 30956.33
(r2=0.67) P<0.001
(r2=0.65) P<0.001
(r2=0.58) P<0.001.
Mean MEP was significantly different among months
for age-1 spotted seatrout (Kruskal-Wallis, P<0.05).
Age-1 fish spawned the least number of oocytes in May
and most in June (Table 4). Statistical comparisons
among months for ages 2 and 3 were inconclusive.
Relative fecundity
Relative fecundity among 83 spotted seatrout ages
1-3 ranged from 224 oocytes to 1314 oocytes/g OFWT
(Table 5). Age did not have an effect on relative fecun-
dity (Kruskal-Wallis, P=0.75). We found that spotted
seatrout in South Carolina produced significantly more
oocytes per gram ovary-free weight at the end than at
the beginning of the spawning season (Mann Whit-
ney, P<0.05). Mean oocyte diameters did not vary sig-
nificantly between ovarian lobes or among locations
within each lobe (ANOVA, P=0.28). A comparison among
482
Fishery Bulletin 102(3)
CJ
O
1200 -
BF= 2179.65(71)- 520597 A
X
f = 0.67. P<0.001 •
CO
0)
n = 134
1000 -
o
o
o
800 -
• /
6
% S^
c
% s^
>.
• * /^
c
600 -
•• •• */
3
* ' s/9
400 ■
• > x^rT
o
CO
•• u*wK
200 ■
CO
2
- • T"*
2!
1 — n i i 1 1 i
0 300 350 400 450 500 550
Total length (mm)
O
1400 ■
B
*""
SF= 530 60(O/=WT) + 1853777
Ul
1200 •
f = 0 65. P<0.001
<u
n=133 •
%.
o
o
o
1000 ■
o
6
800 ■
•
c
•
>.
• ■"
■6
600 ■
' •'• ' %l^
^
o
• ^^^"^
J3)
00
n
c
ro
CD
400 -
200 -
' — i r 1 1 1 i
200 400 600 800 1000 1200
Ovary-free body weight (g)
o
1200 -
c
BF= 169398.21(age) - 3095633 ^
X
? = 0.58. P<0 001 •
n = 134
>.
1000 -
o
o
"o
800 -
•
6
•
^
•
>>
i
t5
600 ■
1
o
a>
400 ■
o
1
ro
200 •
•
•
c
ro
5
•
• •
1 2 3
Age
Figure 5
Re
at Kinship between batch fecundity iBF) and total length
(TL) lA), between BF and ovary-free weight (OFWTi (Bi, and
bel
ween BF and age (Cl for C. nebulosus ages 1-3. Linear re-
gression on data pooled for spawning seasons 1998-2000.
months and ages revealed that age had no effect
on oocyte diameter (ANOVA, P=0.82). However,
the effect of month corroborated the pattern of
increasing RF as the spawning season progressed:
oocytes were significantly smaller at the end of
the season (ANOVA, P<0.05).
Annual fecundity
Annual fecundity estimates (summation of MEP)
were approximately 3.2 million. 9.5 million, and
17.6 million oocytes for each age class, respec-
tively (Table 4). The equation below describes the
relationship between AF and age:
AF = 7152762(Age) - 4166620 (r2=0.99> P<0.05.
From this relationship, the predicted AF for
ages 4 and 5 were 24,444,430 and 31,597,190 oo-
cytes, respectively. We expanded AF in relation to
the abundance of each age class in our standard
random samples for the three years of the study.
We estimated that the overall average contribu-
tion from age-1 fish to the reproductive output
for the season was approximately 29% . whereas
fish aged 2 and 3 contributed 39% and 21', of
oocytes, respectively. Ages 4-5 comprised less
than 3% of specimens sampled and contributed
7% and 4% based on predicted AF values.
Discussion
Studies on the reproductive biology of Cynoscion
nebulosus have established group-synchrony and
indeterminate fecundity for this species through-
out its range (i.e. Brown-Peterson et al., 1988;
Brown-Peterson and Warren, 2001; Nieland et
al., 2002; Mercer1 and references therein). Fish
with these features release gametes in several
batches over a protracted spawning season and
annual fecundity is not fixed prior to the onset of
spawning (Wallace and Selman. 1981).
Based on mtDNA variation among spotted sea-
trout, the existence of two populations, one in
the Gulf of Mexico and one in the South Atlantic,
was established by Gold et al. (1999). However,
variations in reproductive parameters have been
suggested among geographic locations within the
Gulf of Mexico (Brown-Peterson et al., 2002).
Wiley (1996) suggested that spotted seatrout com-
prise a single stock in South Carolina: therefore
reproductive parameters presented in the present
study should be applicable only to the spotted
seatrout population inhabiting coastal waters of
this state. Further studies should be conducted
to evaluate the applicability of these parameters
to the entire southeast coast.
Other investigators (Brown-Peterson et al.,
1988; Wieting, 1989; Brown-Peterson and War-
Roumillat and Brouwer: Reproductive dynamics of Cynosc/on nebu/osus
483
ren, 2001; Nieland et al., 2002; Lowerre-Barbieri et al.8)
have used the gonadosomatic index (GSI) to delineate
the spawning season in spotted seatrout. Even though
the GSI provided a good approximation of the spawning
season, histological data alone provided more precise
evidence. Spotted seatrout in South Carolina began
spawning near the end of April of each year and ceased
by early September. Similarly, Lowerre-Barbieri et al.8
reported that the spawning season for spotted seatrout
in Georgia extended from late April to mid-September.
We found histological evidence of initial spawning in
specimens captured in 20°C water, although approxi-
mately 75% of spawning occurred when ambient water
temperatures were greater than 25°C. In laboratory
experiments, Brown-Peterson et al. (1988) found no suc-
cessful spawning in water below 23°C but pointed out
that others (McMichael and Peters, 1989) found eggs
and larvae in 20.4°C water.
We found that females became mature approximately
one full year after their birth. A female born in May of
one year would be reproductively active in May of the
following year. Females born later in the season would
not be mature as the same successive season began;
therefore, not all one-year-old females were mature
when the spawning season began in May, but became
mature before that season ended. This maturity sched-
ule has also been reported for spotted seatrout in Loui-
siana (Nieland et al., 2002). However, Lowerre-Barbieri
et al.8 found that all one-year-old females were mature
in coastal Georgia. A limited sample size or habitat
segregation of mature and immature trout (Lowerre-
Barbieri et al.8) may have contributed to their result.
The size at first maturity for spotted seatrout in this
study was 248 mm TL. This size is comparable to what
others have reported in other areas of the species' range
(Brown-Peterson et al., 1988; Brown Peterson and War-
ren, 2001; Nieland et al., 2002; Mercer1 and references
therein; Lowerre-Barbieri et al.8). Our estimate of size
at 50% maturity (268 mm TL) was larger than what
Nieland et al. (2002) reported for 100% mature trout
in Louisiana (250 mm TL). However, Nieland et al.'s
(2002) statement that animals are 100% mature at 250
mm TL, does not agree with the growth equation they
report for female trout when age = 1. Because we found
size at 100% maturity among female spotted seatrout
in South Carolina to be about 300 mm TL, we wonder
whether Nieland et al.'s (2002) growth equation for
female TL was meant to represent SL. Were this the
case, they might have offered a different rationale for
size at maturity among trout in Louisiana.
Brown-Peterson et al. (1988) and Brown-Peterson
and Warren (2001) reported size at 100% maturity of
356 mm and 309 mm TL (using the SL-TL conversion
found in our "Methods: section) for spotted seatrout in
Texas and Mississippi, respectively. Brown-Peterson et
al. (1988), however, chose a combination of gears that
may not have sampled the trout population in Texas
representatively for size-at-maturity estimation. In Mis-
sissippi, Brown-Peterson and Warren (2001) used a
more appropriate gear for capture of late juvenile and
early adult fish. Our estimate of size at lOO1* maturity
was quite similar to theirs.
Spawning frequency
Determining the number of multiple spawning events
during a single season for individual fish has been prob-
lematic. Initially, there was little understanding of the
reproductive dynamics of spotted seatrout, and BF esti-
mates were reported to represent the output for a whole
season (Pearson, 1929; Sundararaj and Suttkus, 1962;
Overstreet, 1983). Hunter et al. (1985) and Hunter and
Macewicz (1985) developed techniques to overcome these
limitations by providing protocols for the use of hydrated
oocytes in determining BF and SF among group-syn-
chronous species.
To use the techniques of Hunter (1985) and Hunter
and Macewicz (1985) appropriately, it is critical to obtain
a representative sample of the spawning population.
DeMartini and Fountain (1981) and Lisovenko and Adri-
anov (1991) maintained that the relative occurrence of
hydrated oocytes (as determined macroscopically) was an
effective measurement of SF when the spawning popula-
tion was sampled representatively. However, when sam-
pling a species that spawns in aggregations at specific
geographic locations, as do many of the sciaenids, it is
inherently impossible to obtain a statistically representa-
tive sample of the spawning population for SF estimation
based on FOM. Because the window of opportunity is
temporally and spatially constrained, obtaining a sample
that includes all sizes and ages involved is not feasible;
the only choice in this situation is to sample in a directed
fashion. This was the sampling strategy used to target
females for BF counts; the majority of the animals cap-
tured whose oocytes evidenced FOM were obtained in a
nonrandom fashion. Additionally, we assumed that fishes
demonstrating FOM were moving toward deeper water
spawning aggregations and away from our capture gear.
For these reasons, we felt that our SF estimates based
on the proportion of females with oocytes in FOM were
biased and we excluded them from AF estimation. This
is an important matter to keep in mind when comparing
frequencies of spawning based on different methods.
Because obtaining representative numbers of ani-
mals with late-maturing oocytes is not often feasible,
researchers have relied on the relative abundance of
postovulatory follicles (POFs) to calculate SF (Brown-
Peterson et al., 1988; Brown-Peterson and Warren, 2001;
Nieland et al., 2002; Lowerre-Barbieri et al.8). The POF
method lacks the limitations (described above) of the
FOM method. Because the method we chose allowed
us to sample all sizes and ages of fish in the estuary,
obtaining representative numbers of animals with POFs
was accomplished effectively. Therefore, we felt that our
estimates of SF based on the POF method were more
precise and we chose to use them in deriving AF.
The POF method depends on the ability to assess the
disappearance of these structures. Hunter and Macewicz
(1985) systematically sampled captive spawning ancho-
vies to develop histological criteria for POF atrophy in
484
Fishery Bulletin 102(3)
19°C water. Their criteria have been used by others
to estimate rates of POF atrophy in other species and
thereby determine the percentage of a population un-
dergoing spawning over a discrete time period (Brown-
Peterson et al, 1988; Fitzhugh et al., 1993; Taylor et al.,
1998; Macchi and Acha, 2000; Brown-Peterson and War-
ren, 2001; Nieland et al., 2002). However, even though
it has been demonstrated that the rate of POF atresia
depends largely on ambient water temperature (Fitzhugh
and Hettler, 1995), few (Brown-Peterson et al., 1988;
Macchi and Acha, 2000; Nieland et al, 2002) have taken
this into account when establishing the age of POFs for
SF estimations. Our diurnal sampling of reproductively
active spotted seatrout during warm water conditions en-
abled us to establish criteria to accurately estimate the
age of POFs throughout the spawning season. Further-
more, we verified our assessments by sampling around
the clock on two occasions to collect fish over the time
period immediately following a spawning event.
Spotted seatrout ages 1-3 in SC spawned less fre-
quently than those from the Indian River Lagoon, Flor-
ida (Crabtree and Adams7) but both studies showed
that older fish spawned more frequently than younger
animals. Our estimates for spotted seatrout aged 1-3
were 4.7, 4.2, and 4 days, respectively. Trout in these
age classes in Florida were reported to spawn once ev-
ery 4, 2.8, and 2.5 days, respectively. These differences
probably not only reflect the distinct biological environ-
ments of each region but also indicate potential discrep-
ancies in aging methods. No age-specific estimates of
SF are available for other areas in the species' range.
Brown-Peterson and Warren (2001) found SF among
spotted seatrout in Biloxi Bay, MS, to be significantly
lower than that of fish inhabiting the other two areas
included in their study. They suggested that Biloxi Bay
was a less conducive spawning habitat because of sev-
eral factors, including shoreline development and a
reduced amount of aquatic vegetation. However, because
we found that SF varied significantly among age classes
(age-3 fish spawned more frequently), the relative age
composition of fish sampled by Brown-Peterson and
Warren (2001) in the three estuaries might also have
played a critical role in the determination of SF.
Batch fecundity
The best approach for estimating BF is to use only oocytes
in FOM (Hunter et al., 1985; Brown-Peterson et al., 1988;
Brown-Peterson and Warren, 2001; Brown-Peterson et
al., 2002; Nieland et al., 2002; Lowerre-Barbieri et al.8).
When it is not possible to obtain these, BF estimations
can and have been carried out in some species by using
the largest vitellogenic oocytes (Overstreet, 1983; Hunter
et al., 1985; Wieting 1989). These efforts have the poten-
i ill of being less accurate because isolating those oocytes
destined to be spawned is difficult if the latter have
not yet reached final maturation (Nieland et al., 2002).
Inevitably this scenario would result in a nonmeasurable
overestimation of female reproductive output. Brown-
Peterson et al. (1988) and Brown-Peterson and Warren
(2001) used a modification of this approach to estimate
BF of spotted seatrout in Texas and Mississippi, respec-
tively. However, even though the potential existed for
overestimating BF, their estimates fell well below those
presented in the present study, as did those presented
by Nieland et al. (2002) for spotted seatrout ages 2-4 in
Barataria Bay, Louisiana. Mean BF for ages 1-3 (170
thousand, 226 thousand, and 274 thousand oocytes,
respectively) spotted seatrout in Indian River Lagoon,
Florida (Crabtree and Adams7), also differed from those
reported here. Our estimate took into account that not
all age-1 females were mature at the beginning of the
season. Crabtree and Adams,7 however, did not adjust
their estimate to reflect this discrepancy. Moreover, due
to differences in aging methods, their age-1 and 2 cohorts
possibly included ages 2 and 3, respectively. In addition,
in the Florida study as well as in ours, relatively few
numbers of older specimens were examined.
The relationships between BF and length, weight, and
age in the present study were significant and predictive.
Of these, TL exhibited the most predictive relationship.
This fact may explain why age-1 and age-2 spotted
seatrout in Georgia had mean BFs considerably higher
than ours (175 thousand and 407 thousand, respectively;
Lowerre-Barbieri et al.8): the size ranges for age-1 and
age-2 in the Georgia study were greater than ours. To-
tal length seems to be the most reliable predictor of BF
among spotted seatrout in Georgia and SC (Lowerre-
Barbieri et al.,8 this study) and in Louisiana (Nieland
et al., 2002). However, Crabtree and Adams7 found that
BF related best to ovary-free weight among spotted
seatrout in Florida. We found ovary-free weight to be
the second best predictor of BF. Overall, it appeared
that TL and ovary-free weight were better predictors of
BF than age for this species (Brown-Peterson, 2003).
As with SF, monthly egg production (MEP) estimates
for SC spotted seatrout varied throughout the season.
Because BF was not significantly different among
months for any of our age classes, the variation in
MEP resulted directly from the frequency of spawning.
Monthly egg production estimates for age-1 fish were
lowest in May and highest in June because SF was
lowest in May and highest in June. Spawning frequency
is a critical reproductive parameter because it seems
to dictate annual reproductive output (DeMartini and
Fountain, 1981; Brown-Peterson and Warren. 2001;
Crabtree and Adams7); therefore, SF should be carefully
considered, particularly for managed species.
Relative fecundity
We found that relative fecundity (RF), the number of
oocytes per gram of somatic weight, did not show a sig-
nificant relationship with female size. This finding was
expected because dividing fecundity by ovary-free weight
standardizes the values independently of size. However,
this finding was in contrast to that of Brown-Peterson
and Warren (2001). They collected specimens during
the morning only, whereas we sampled ours throughout
the day. This procedure allowed us to examine ovaries
Roumillat and Brouwer: Reproductive dynamics of Cynosc/on nebulosus
485
over the entire range of maturation and to select only
those clearly showing nuclear migration (based on his-
tological observations) ensuring that only oocytes in the
same phase of FOM (Brown-Peterson et al., 1988) were
included in RF calculations. If sampling is conducted
during a time period that is not close to active spawning
(i.e., when oocytes are in different phases of FOM), then
the number of oocytes per gram may be miscalculated.
As with BF, our RF estimates were higher than those
reported for seatrout in the Gulf of Mexico (Brown-
Peterson et al., 1988; Brown-Peterson and Warren,
2001), although spotted seatrout reproductive para-
meters appeared to vary considerably even within the
Gulf of Mexico (Brown-Peterson et al., 2002). This was
attributed to differential environmental conditions or
food availability (or to both) (Brown-Peterson and War-
ren, 2001; Brown-Peterson et al., 2002). The significant
seasonal increase in RF that we observed for spotted
seatrout in South Carolina, however, has not been re-
ported elsewhere. Brown-Peterson et al. (1988) found no
differences in mean monthly RF among spotted seatrout
in Texas. Brown-Peterson and Warren (2001) found sig-
nificantly higher RF values in June than in August. In
both instances, however, a small sample size may have
biased their results.
Comparisons of mean oocyte diameters among months
related the increase in RF to a general decrease in
oocyte size over the course of the season. This phenom-
enon is widespread among marine pelagic spawners,
and scientists have put forth several explanations to
account for it (see Chambers, 1997). Bagenal (1971) sug-
gested that egg size decreased over the spawning sea-
son owing to concurrent increased food availability for
larvae. Others have suggested an inverse relationship
between temperature and egg size (Ware, 1975; Woot-
ton, 1994; Miller et al., 1995) or a seasonal decrease in
egg size that is correlated to the condition of spawning
females (DeMartini and Fountain, 1981; Chambers and
Waiwood, 1996). The latter seems to apply to spotted
seatrout in this study because a diminishing trend
through the spawning season was observed in the con-
dition factor of females.
Annual fecundity
Brown-Peterson (2003) presented AF estimates for spot-
ted seatrout throughout their range. Our estimates were
substantially below those for spotted seatrout in Indian
River Lagoon (Crabtree and Adams7) but approximated
those of Lowerre-Barbieri et al.8 for trout in Georgia. A
possible reason for the higher values in Florida was the
more protacted spawning season in that area (50 days
longer). No comparisons of AF estimates presented in
this study and those of spotted seatrout in the Gulf of
Mexico (Brown-Peterson, 2003) were made because they
were not specific to age classes.
The main impetus behind the present study was to
establish annual fecundity (AF) estimates by age class.
We found that age-1 through age-3 spotted seatrout
occurred abundantly in SC estuaries and that each of
these age cohorts showed unique fecundity dynamics.
The AF for an average age-1 fish was one-third that of
age-2 (-3.28 million vs. 9.5 million). One year-old fish,
however, constituted the majority offish in our samples;
their abundance was twice that of 2-year-olds and seven
times that of 3-year-old fish. Even though the average
age-3 trout produced almost twice as many oocytes dur-
ing the season (17.5 million) as the average age-2 fish,
their reduced abundance in our estuaries made their
overall contribution only half that of 2 year-olds. Ages
4 and 5 were estimated to produce approximately 24.4
million and 31.6 million oocytes per female, respective-
ly; however, the oocyte production by the predominant
age groups overshadowed theirs. When analyzed in re-
lation to the occurrence of the other age classes in our
estuaries, age-2 fish contributed the greatest number of
fertilizable oocytes to the environment (39%).
Reliable fecundities based on age and on length are
optimal for stock assessment models (Williams9). This
study provided AF estimates for three age classes that
can be used in age-based models for the spotted seat-
rout population in South Carolina. Annual fecundity
estimates based on length, however, have not been at-
tempted even though length appears to be the best pre-
dictor of fecundity in spotted seatrout (see references in
Brown-Peterson, 2003). Further analyses to investigate
the relationship between egg production and fish length
for each month of the spawning season would allow for
more precise management efforts based on individual
length-based estimates of AF.
Acknowledgments
We thank members of the Inshore Fisheries Section of
the South Carolina Department of Natural Resources for
assisting in field data collection throughout this study
(C. Wenner, J. Archambault, H. von Kolnitz, W. Hegler,
E. Levesque, L. Goss, C. McDonough, C. Johnson, A.
Palmer). C. Wenner, H. von Kolnitz, and E. Levesque
conducted age assessments. Histological processing was
provided by C. McDonough, R. Evitt, A. Palmer, and
W. Hegler. Assistance with oocyte counts was provided
by C. McDonough, T. Piper, K. Maynard, and R. Evitt.
Data management was coordinated by J. Archambault,
C. Wenner, E. Levesque, and three anonymous reviewers
provided helpful suggestions on the manuscript. Funding
for this study was provided by the National Marine Fish-
eries Service under MARFIN grant no. NA77FF0550.
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Abstract— Dungeness crabs {Cancer
magister) were sampled with commer-
cial pots and counted by scuba divers
on benthic transects at eight sites
near Glacier Bay, Alaska. Catch per
unit of effort (CPUE) from pots was
compared to the density estimates
from dives to evaluate the bias and
power of the two techniques. Yearly
sampling was conducted in two sea-
sons: April and September, from 1992
to 2000. Male CPUE estimates from
pots were significantly lower in April
than in the following September; a
step-wise regression demonstrated
that season accounted for more of
the variation in male CPUE than
did temperature. In both April and
September, pot sampling was signifi-
cantly biased against females. When
females were categorized as oviger-
ous and nonovigerous, it was clear
that ovigerous females accounted for
the majority of the bias because pots
were not biased against nonovigerous
females. We compared the power of
pots and dive transects in detecting
trends in populations and found that
pots had much higher power than dive
transects. Despite their low power, the
dive transects were very useful for
detecting bias in our pot sampling and
in identifying the optimal times of
year to sample so that pot bias could
be avoided.
Estimating Dungeness crab (Cancer magister)
abundance: crab pots and dive transects compared
S. James Taggart
Glacier Bay Field Station
Alaska Science Center
U.S. Geological Survey
3100 National Park Rd.
Juneau, Alaska 99801
E-mail address |im_taggart(S!usgsgov
Charles E. O'Clair
National Marine Fisheries Service
Auke Bay Laboratory
11305 Glacier Highway
Juneau, Alaska 99801
Thomas C. Shirley
Juneau Center, School of Fisheries & Ocean Sciences
University of Alaska Fairbanks
11120 Glacier Highway
Juneau, Alaska 99801
Jennifer Mondragon
Glacier Bay Field Station
Alaska Science Center
U.S. Geological Survey
3100 National Park Rd.
Juneau, AK 99801
Manuscript submitted 13 March 2000
to Scient ific Editor's Office.
Manuscript approved for publication
25 March 2004 by the Scientific Kditor.
Fish Bull. 102:488-497 (2004)
Reliable population assessments are
fundamental to the management and
conservation of commercially har-
vested crabs. Many crab populations
are sampled with commercial crab
pots to estimate population trends, to
set harvest quotas, or to differentiate
natural population fluctuations caused
by anthropogenic changes to the eco-
system. Pots are used, for example, to
assess the population status of blue
crabs, Callinectes sapidus (Abbe and
Stagg, 1996), red king crabs, Para-
lithodes camtschaticus (Zheng et al.,
1993), snow crabs, Chionoecetes opilio
(Dawe et al., 1996), and southern king
crabs, Lithodes santolla i Wyngaard
and Iorio. 1996).
The Dungeness crab (Cancer ma-
gister) fishery began in southeastern
Alaska in 1916 and has been charac-
terized by large fluctuations on an-
nual and decadal scales tOrensanz
et al., 1998). Large variation in the
Dungeness crab harvest is not unique
to Alaska; similar fluctuations have
been documented in California and
their causes are the subject of an on-
going debate (Higgins et al., 1997a.
1997b). It is not clear whether the
processes that cause fluctuations in
California are the same as those re-
sponsible for oscillations in Dunge-
ness crab abundance in Alaska.
Most of the Dungeness crab fisher-
ies in Alaska are managed by regu-
lating the size and sex of the crabs
caught, and, in some places, the sea-
son of the harvest. In southeastern
Alaska, legal harvest is restricted to
males with a carapace width greater
than or equal to 165 mm (excluding
the 10th anteriolateral spines) and the
season is timed to avoid sensitive life
Taggart et al.: Estimating abundance of Cancer magister
489
58°30'N.
^s 20'
t r
135°50' 135 4n\\
Figure 1
Map of study area showing eight study sites in or near Glacier Bay in southeastern
Alaska.
history periods such as mating and molting (Kruse,
1993; Orensanz et al., 1998). Pre- and postseason stock
assessment surveys using crab pots were initiated in
southeastern Alaska in 2000 (Rumble and Bishop,
2002). The purpose of the latter management strategy
is to assess the abundance of legal-size males before the
fishing season, to estimate harvest rates, to define the
timing of male and female mating and molting and to
determine growth rate by tagging crabs.
The usefulness of surveys with pots for Dungeness
crab population assessment, however, depends on the
accuracy of these surveys in measuring population pa-
rameters. Factors that can bias catch per unit of effort
(CPUE) and size-frequency estimates for Dungeness
crabs are pot soak-time (Miller, 1974; High, 1976; Got-
shall, 1978; Smith and Jamieson, 1989); freshness of
bait (High, 1976; Smith and Jamieson, 1989); pot design
(Miller, 1974; High, 1976; Smith and Jamieson, 1989);
and agonistic interactions among conspecifics inside
and at the entrance of pots (Caddy, 1979; Smith and
Jamieson, 1989). Smith and Jamieson (1989) developed
a standardized model to compensate for the effect of
agonistic interactions, age of bait, and escapement.
They also concluded that researchers could minimize
these biases by measuring CPUE with standardized
surveys with short soak times. These studies measured
sampling bias with pots by comparing catch in pots
among various experimental treatments. Opportunities
for comparing surveys with pots to direct measures of
abundance are rare. In our study, we compared the bias
and power of CPUE estimates from surveys with pots to
independent measures of abundance conducted by scuba
divers on benthic dive transects.
Methods
Study area
The study area included eight sites in southeastern
Alaska, near Glacier Bay: North Beardslee Islands
(58°33'N 135°54'W), South Beardslee Islands (58°30'N
135°55'W), Berg Bay (58°31'N 136°13'W), Bartlett Cove
(58°27'N 135°53'W), Gustavus Flats (58°23'N 135°43'W),
Secret Bay (58°29'N 135°56'W), inner Dundas Bay
(58°27'N 136°31'W), and outer Dundas Bay (58°21'N
136°18'W) (Fig. 1). All study sites were located within
Glacier Bay National Park and Preserve, with the excep-
tion of Gustavus Flats, which was located adjacent to the
Park boundary in Icy Strait.
Glacier Bay is a large (1312 km2) glacial fjord system
with high sedimentation rates of clay-silt particles from
streams and tidewater glaciers (Cowan et al., 1988).
The primarily unconsolidated rocky coastline is highly
convoluted with numerous small bays. Dungeness crabs
can be found throughout Glacier Bay; however the ma-
jority of the population are found in the lower 40 km of
the estuary where our sites were located (Taggart et al.,
2003 ). The shallow water in and around our study sites
was primarily characterized by mud bottom, but sand,
pebble, cobble, and shell substrates were also common
(Scheding et al., 2001).
490
Fishery Bulletin 102(3)
Table 1
Sampling dates for yearly
Sample size (n) is listed for
spring and fall pot and dive surveys of Dungeness crabs (Cancer magister)
pots and dives for each sampling event.
in
Glacier Bay, Al
iska.
Year
Spring
sampling
Fall
sampl
ing
Pots
it
Dives
n
Pots
n
Dives
n
1992
7-12 April
248
7-12 April
69
17-22 Sept
250
17-22 Sep.
75
1993
20-27 April
350
20-27 April
105
23-28 Sept
250
23-28 Sep.
75
1994
20-27 April
350
23 April-1 May
105
13-18 Sept
249
13-18 Sept.
75
1995
19-26 April
350
23 April-1 May
105
9-14 Sept
236
15-19 Sept.
75
1996
15-21 April
350
22-28 April
105
13-18 Sept
242
19-23 Sept.
73
1997
17-22 April
300
23-28 April
115
14-19 Sept
298
20-25 Sept.
120
1998
—
—
—
—
9-14 Sept
296
16-21 Sept.
91
1999
—
—
—
—
9-14 Sept
299
17-22 Sept.
107
2000
—
—
—
—
9-14 Sept
297
18-23 Sept.
60
Sampling dates
Sampling was conducted biannually, in April and Sep-
tember, from 1992 to 1997 and annually, in September,
from 1998 to 2000 (Table 1). The spring and fall sam-
pling periods were selected to coincide with crab life
history events and to avoid sampling during commercial
fishery operations. April sampling was scheduled to
occur before larval hatching in May- June (Shirley et
al., 1987) and before the summer commercial fishing
season from 15 June to 15 August. September sampling
began after the end of the fishing season (15 August)
and ended before the beginning of the winter harvest
(1 October to 30 November).
During 1992, the study sites were sampled with pots
(referred to as "pot sampling") and by divers (referred to
as "dive sampling") concurrently (Table 1). In 1993 and
1994, sampling was conducted on nearby study sites
and the dive sampling usually one day ahead of the
pot sampling. For logistical reasons, starting in 1995.
we separated the pot sampling and the dive-transect
sampling into two separate research cruises. The pot
sampling was conducted on the first cruise and the
dive sampling occurred on the second cruise; pot and
dive sampling were separated at each location by 2 to
12 days.
Sampling with pots
Crabs were sampled with commercial crab pots (0.91 m
in diameter, 0.36 m tall, with 5-cm wire mesh). Escape
rings were sealed with webbing on each pot to retain
smaller crabs. Pots were baited with hanging bait com-
prising salmon, cod, or halibut (depending on availabil-
il nd bait jars that were filled with chopped herring
and squid. We found that cod was predictably available;
therefore from 1996 on, we consistently used cod for
hanging bait. Pots were soaked for 24 hours.
Within each study site, we set 25 pots in shallow
water (0-9 m) and 25 pots in deep water (10-25 m).
Each day we set 50 pots in one of the study sites and
retrieved the 50 pots that had been set the previous day
at one of the other study sites. The pots were set along
strings parallel to shore at intervals of approximately
100 m. Within each study area, the strings of pots were
located in prime Dungeness crab habitat determined
by a local fisherman. We placed the pots at the same
locations during subsequent sampling events by using
a GPS (Rockwell PLGR+) with an accuracy of ±3 m. We
estimate that the pots were set within 20 meters from
the original waypoints. Water depth (standardized to
mean lower low water), set and retrieval time, and GPS
location were recorded for each pot. Water temperature
and salinity profiles were measured at each study site
during each sampling period with a SEABIRD SBE-19
Profiler.
As the pots were retrieved, we counted and identified
all organisms. For all Dungeness crabs we recorded the
sex, carapace width, shell condition, and damage to
appendages. For female crabs we also recorded repro-
ductive status. Carapace width was measured to the
nearest millimeter immediately anterior to the 10th
anterolateral spine with vernier calipers (Shirley and
Shirley, 1988; Shirley et al.. 1996). All organisms were
returned to the water at the location where they were
caught. A potential problem with returning the crabs
to the water near the site of capture is the possibility
that crabs could be resampled in subsequent pots, which
would bias the catch per unit of effort. Beginning in
April, 1995, all crabs collected in the South Beardslee
Islands and Berg Bay were tagged with a sequentially
numbered, double-T Floy tag (Floy Tag and Manufactur-
ing Company, Seattle, WA) inserted along the postero-
lateral margin of the epimeral suture. Tags placed in
this location are retained through ecdysis (Smith and
Jamieson, 1989). Of the 5226 crabs tagged, only a single
Taggart et al.: Estimating abundance of Cancer magister
491
crab was recovered during the same sampling event.
Thus, the probability of resampling crabs by returning
them to the water was very low.
Sampling by divers
Divers using scuba equipment censused crabs on 15
to 20, 2x100 m belt transects within each study site.
Approximately one day of sampling was required at
each study site. The dive transects were conducted per-
pendicular to the shoreline and they extended from the
shallow subtidal (0 m, mean lower low water) to 18 m
depth or to the end of the 100 m transect, whichever
came first. Divers did not go below 18 m depth in an
effort to reduce nitrogen accumulation in divers' blood
and to reduce the surface intervals required between
transects. From 1992 to 1997, transect locations were
randomly selected in the same areas as the crab-pot
sampling. The random locations selected in 1997 were
resampled during the following years of the study.
Divers counted all Dungeness crabs located within
1 m of each side of the transect. An effort was made to
locate buried crabs by swimming close to the bottom
and looking for irregularities in the bottom or protrud-
ing crab eyestalks. Each crab was examined and the
following were recorded: legal males >165 mm carapace
width), sublegal males (<165 mm carapace width), ovig-
enous females, and nonovigerous females.
Data analysis
For each year, we calculated the average pot CPUE for
each site by reproductive class (males, nonovigerous
females, and ovigerous females). The number of pots
sometimes deviated from 50 when a pot was lost or when
the degradable cotton string securing the pot lid broke
(range: 44-50 pots). The number of crabs counted on
dive transects was averaged for each reproductive class
by site for each year. All dive transects were conducted
perpendicular to shore; thus the transects crossed the
shallow habitat where the shallow string of pots was
set and terminated at 18 m which was the center of
the depth we targeted for the deep pot set. Because the
deep pot set was at or slightly beyond the deep end of
the transect, we may have sampled more crabs from
deepwater habitats than from the shallower transects.
However, we did not think this was a significant bias
because we sampled crabs from a relatively large area.
We, therefore, pooled the pots from both depth strata
for analysis.
We tested for differences between April and Septem-
ber for the pot CPUE data and the dive density data
with paired f-tests. CPUE and density data were not
normally distributed; therefore we transformed the
data with a square-root transformation [Y=JiY + 3/8)]
for statistical analyses (Zar, 1996). These analyses were
conducted for males, nonovigerous females, and oviger-
ous females. Because seasonal increases in water tem-
perature could drive differences in CPUE between April
and September, we calculated mean water temperatures
by averaging the water temperatures at the 5 m and
15 m depths at each site and year. This analysis was
limited to years and sites where we collected samples
in both April and September (1992-97, from five sites:
North Beardslee Islands, South Beardslee Islands, Berg
Bay, Bartlett Cove, and Gustavus Flats). We assessed
how CPUE was influenced by two independent vari-
ables, water temperature and season, with stepwise
regression. Because CPUE declined from 1992 to 1997
(Taggart et al., in press), we controlled for year so that
it would not confound our analysis.
In order to assess sampling bias between pots and dive
transects, the percentages of females (females/all crabs),
nonovigerous females (nonovigerous females/all crabs),
and ovigerous females (ovigerous females/all crabs) were
calculated for each site and sampling time. We also com-
pared the percentage of the male population that was
legal size (legal-size male crabs/all male crabs) from the
pots and from the dives. The percentage estimates from
the pot data were compared to estimates from the dive
transects with a paired sign test (Zar, 1996). If percent-
age estimates for pot data were unbiased when compared
to estimates from dive data, the pot percentage esti-
mates would have an equal chance of being higher or
lower than the percentage estimates for the dive data.
Because small sample sizes exaggerate percentage com-
parisons, we excluded samples where the total number
of crabs collected was less than 25 crabs/site.
The power of pots and dive transects to detect trends
in populations was compared with Monitor, a power
analysis program (Gibbs and Melvin, 1997; Gibbs,
1998). For our analyses, we varied the number of tran-
sects and pots, compared males and nonovigerous fe-
males, and varied the duration of the study. For all
analyses the following input parameters of the model
were held constant: "survey occasions" = annual, "type"
= linear, "significance level" = 0.05, "number of tails" =
2, "constant added" = 1, "trend variation" = 0, "round-
ing" = decimal, "trend coverage" = complete, and "rep-
lications" = 10,000.
To estimate power, the model requires "count" and
"variance" for each plot across years for at least three
years. Pot and transect data collected from 1992 to
1998 from five sites (North Beardslee Islands, South
Beardslee Islands, Berg Bay, Bartlett Cove, and Gusta-
vus Flats) were used for these analyses. The data were
limited to September to avoid seasonal bias. The aver-
age across years was calculated for each transect and
each pot. These averages were input into the model's
variable called "plot count." For each pot and transect
a linear regression was calculated among years (CPUE
vs. year for pots; density vs. year for dive transects)
and the residual mean square was the "plot variance"
variable (Thomas and Krebs, 1997).
To estimate the effect of sample size on power we set
the "number [surveys] conducted" to four and limited
the analysis to males. We varied the number of "plots"
(pots and transects). For pots, we randomly selected
subsamples of the 250 pots and ran simulations from
25 pots to 250 pots in 25-pot increments. The number
492
Fishery Bulletin 102(3)
of dive transects for which data were collected for mul-
tiple years was 75. For simulations with a sample size
less than 75, we randomly subsampled the data in the
same manner as we did with pots. For simulations with
sample sizes greater than 75, we amplified the samples
with simple bootstrapping to obtain samples from 100 to
250 transects in 25-transect increments (Wonnacott and
Wonnacott, 1990). For each sample size, we modeled
three annual rates of change (0.02, 0.03, and 0.05).
To evaluate how study duration affects power, we lim-
ited the analysis to males, varied study duration ("num-
ber [surveys] conducted") from two years to 12 years in
two-year increments, and compared three annual rates
of change (0.02, 0.03, and 0.05) for both pots and tran-
sects. To hold effort constant between the two sampling
techniques, we set the pot and transect sample size to
the number we could accomplish in a five-day research
cruise (250 pots and 75 transects).
To explore the relationship between annual trend in
population and power, we held effort constant (250 pots
and 75 transects) and varied the annual trend (from
-0.10 to +0.10 in 0.01 increments) for both males and
nonovigerous females. It was not possible to conduct a
power analysis for ovigerous females because a large
proportion of the pots and transects had no ovigerous
female crabs.
Results
The pot CPUE estimates for males, nonovigerous females,
and ovigerous females was significantly different in
April than in the following September (Fig. 2, A, C, and
E). Male and nonovigerous female CPUE was higher in
September (Fig. 2, A and C) and ovigerous female CPUE
was lower in September (Fig. 2E). In contrast, April den-
sity estimates from dive transects were not significantly
different from the following September density estimates
for males (Fig. 2B). Dive density estimates for nonovig-
erous females were higher in September than in April
(Fig. 2D); density estimates for ovigerous females were
lower in September than in April (Fig. 2F).
When we tested the influence of temperature and
season on male CPUE with stepwise regression, season
was selected first; temperature was not selected because
it did not have a significant additional effect (Table 2).
Because no significant difference was found between
the April and September density estimates from dive
transects (Fig. 2B), we did not conduct a stepwise re-
gression for the dive data.
Percentage estimates of females from sampling with
pots were lower than percentage estimates from dive
transects for a significant number of samples for both
April and September (Fig. 3Ai; therefore pots were bi-
ased against sampling females. When females were
split by reproductive status, no bias was detected for
sampling nonovigerous females with pots (Fig. 3B).
In contrast, the percentage estimates for ovigerous fe-
males remained biased and the magnitude of the bias
increased (Fig. 3C). To test potential sampling bias
co 2.5 •
3.25
2.75 ■
2.25
O 1.5 •
1.75
2.75
2.25
P=0.40
P=0.04
0.75
1.75
3.75
2.75 \
2.75
P=0.04
April
September
April
September
Figure 2
Within-year paired comparisons by site of catch in
pots (left column) and density on dive transects (right
column) for: (A and B) male Dungeness crabs {Cancer
magister); (C and D) nonovigerous female crabs; and
(E and F) ovigerous female crabs. Catch and density
data were transformed with a square-root transforma-
tion. P-values indicate results from paired /-tests and
significant results show differences between April and
September. Lines on the graphs are parallel if measure-
ments at sites were consistently higher or lower in April
and September.
related to crab size, we compared the proportion of
the male population that was legal size sampled with
pots and dives (Fig. 4). There was no significant bias
when pots and transects were compared with a sign
test (April. P>0.999; September, P=0.06).
CPUE estimates from pots had a higher power than
density estimates from dive transects for the same
sample size (Fig. 5). Because more time is required
to conduct a dive transect than to set and pull a crab
pot, the power of transects compared to pots was even
lower when effort was incorporated into the analysis
(Fig 6). The power can be increased for both pots and
Taggart et al.: Estimating abundance of Cancer magister
493
Table 2
Stepwise regression results of CPUE (male crabs/pot)
versus three independent variables (year, season, and
temperature).
Step
Model
parameters r2
P-value
( parameter 1
1
2
3
Year 0.1493
Year and month 0.5589
Year, month. 0.5589
and temperature
0.001 (year)
0.04 (month I
0.98 (temperature)
transects by increasing the study duration or increasing
the amount of change in the population that the study
is attempting to detect (Fig. 6). Although pots had more
power than dive transects, there was only slightly more
power to detect change in abundance of male crabs
versus nonovigerous females (Fig. 7).
Discussion
For male Dungeness crabs, the density estimates from
the dive transects showed no difference between April
and September (Fig. 2B). The male CPUE estimates
from pots, however, were consistently lower in April than
in the following September (Fig. 2A). Because feeding
rates of Dungeness crabs are correlated with tempera-
ture (Kondzela and Shirley, 1993), we thought that tem-
perature was likely to explain the differences in CPUE
between April and September. We found, however, that
season had a larger effect than temperature (Table 2).
This result suggests that seasonal factors other than
temperature influence catchability. Stone and O'Clair
(2001) followed the seasonal movements of Dungeness
crabs in a glacial estuary in southeastern Alaska and
reported that mean movement of male crabs was lower
during the spring than in the late summer and fall. It
is possible that our spring sampling schedule coincided
with low male activity and male crabs were less likely to
encounter a bait plume and be attracted to a pot. These
results indicate that if pots are used for sampling, late
summer and early fall is the time of year to conduct
population assessment surveys of male crabs. Similar
seasonal differences in CPUE have also been described
for edible crabs (Cancer pagurus) and American lobsters
(Homarus americanus) (Bennett, 1974). These data dem-
onstrate the importance of controlling for season when
comparing CPUE among years or sites.
The proportion of large crabs caught in pots increased
with longer soak time for Dungeness crabs in British
Columbia (Smith and Jamieson, 1989) and red king
crabs in Britstol Bay, Alaska (Pengilly and Tracy,
1998). We found no bias when we measured the legal-
size proportion of the male population caught in pots
and compared it to the proportion sampled on dives
1
0.8 -I
0.6
0.4 -I
0.2
0
1
0.8
i A
April P<0.0001 /
Sept. P<0.0001 /
/ @
O ' A
/ ° O
»/i*AA
/O n A ~
/ a4o o
A
<3$»#
/ u
'
1 1 1 i
0.4-
0.2-
B
April P=0.17
Sept. P=0.49
' A
0.6 9 o
o
i>4.
O " Oft /A
*«0«' *A
0°A^
a
* A
A AA
o
O April
A September
0-
i-i c
0.8
0.6
0.4
0.2
0*
April P<0.0001
Sept. P<0.0001
O
o
cr
o
0 0.2 0.4 0.6 0.8 1
Percent crabs on transects
Figure 3
The percentage of (A) female Dungeness crabs
(C. magister). (B) nonovigerous female crabs,
and (Ci ovigerous female crabs estimated from
pots and from dive transects. The dashed line
in each graph has a slope of 1: thus half of the
data points should be above and half should be
below the dashed line if percentage estimates
for dives and pots are unbiased. Pot and dive
transect data for each sex class and season
were compared with a paired sign test and
P-values are reported.
(Fig. 4). We expect, however, that the bias observed in
British Columbia and Bristol Bay would occur for our
study sites if the soak time of pots were increased.
494
Fishery Bulletin 102(3)
O April
A September
(P>0.999)
(P=0.06)
1.0
0.8
0.6
CD CD
Q- E
• 0A\f
i,
02OA
O
A.
°^°
O
o
A
O
A
' C*°J
0D
0.2
0.4 0.6 0.1
1.0
Percent legal-size
male crabs on transects
Figure 4
The percentage of male crabs of the
Dungeness crab (C. magister) popu-
lation that were legal size (>165 mm)
estimated from pots compared to the
percentage of male crabs estimated
from dive transects. Data from pots
and dive transects were compared for
each season with a paired sign test
and P-values are reported.
0.8
06
g
o
0.2
Pots Transects
-o- •*■ 0 05 change/year
003 change/year
50
100 150
Sample size (n)
250
Figure 5
Relationship between power and sample size (/!) in comparing
catch from pots and density on dive transects for male Dungeness
crabs (C. magister) at three levels of population change.
In both April and September, pot sampling was signif-
icantly biased against females (Fig. 3A). When females
were categorized as ovigerous and nonovigerous, it was
clear that ovigerous females accounted for the major-
ity of the bias because pots were not biased against
nonovigerous females (Fig. 3B). Similar results have
been found for a closely related species, Cancer pagurus;
female C. pagurus readily enter pots when they are in
a nonovigerous reproductive state but are rarely cap-
tured when they are ovigerous (Bennett, 1995). Move-
ment studies of Dungeness crabs tagged with sonic
transmitters have demonstrated that ovigerous females
move less frequently and move slower than males or
nonovigerous females (O'Clair et al., 1990). Thus, one
explanation for the bias against ovigerous female crabs
is that their restricted movements make it less likely
they will be able to locate and become entrapped in
pots. In addition to being less mobile, ovigerous females
may be less attracted to bait than nonovigerous crabs.
In controlled feeding experiments, ovigerous females
had lower feeding rates than nonovigerous females, and
ovigerous females took longer to begin feeding (Schultz
et al., 1996; Schultz and Shirley, 1997 i. Therefore, ovig-
erous females may be less responsive to the bait plume
from a pot.
The estimate of nonovigerous females from both pot
CPUE and dive transect density increased from April
to September (Fig. 2, C and D). As with males, the in-
crease in CPUE for nonovigerous females may be partly
due to an increase in catchability in September. How-
ever, the fact that the density estimates from dives also
increased suggests that the number of nonovigerous
females actually increased between April and Septem-
ber. This explanation is supported by the decrease in
ovigerous crabs from April to September for both CPUE
(Fig. 2E) and density estimates (Fig. 2F i.
The low catchability of ovigerous females makes it
problematic to monitor relative abundance of females
or changes in sex ratio through time. However, be-
cause pots were not biased against nonovigerous fe-
males (Fig. 3), the solution may be to estimate the rela-
tive abundance of females by sampling after females
hatch their eggs and before they extrude a new clutch
of eggs in the fall. In southeastern Alaska, most females
are nonovigerous in late July and early August (Stone
and O'Clair, 2001; Swiney et al., 2003); therefore this
would be the optimal time of year to sample females
or to measure sex ratio of Dungeness crab populations.
Unfortunately, this timing coincides with the summer
commercial fishing season, which could bias sampling
if there was "competition" between survey pots and
commercial pots.
For both males and females, the power analyses of
the pot and dive data indicated that for most population
assessment applications it would be extremely difficult
to conduct enough dive transects to obtain sufficient
statistical power. Even if it were possible to conduct
as many dive transects as pot samples, the power of
a dive transect was still lower than that of a pot; the
higher power of the pots was due to lower variance
among pots. Pots work by attracting crabs with a bait
plume; thus the area and number of crabs sampled is
Taggart et al.: Estimating abundance of Cancer magister
495
0 6-
04-
0.2
Pots Transects
(n=250) (n=75)
-O- -•- 0 05 change/year
-O ♦ 0 03 change/year
•V- -T- 0 02 change/year
0 2 4 6 8 10
Study duration (years)
12
Figure 6
Relationship between power and study duration in comparing catch from
crab pots and density on dive transects for male Dungeness crabs (C.
magister) at three levels of population change. To hold effort constant,
we set the sample size (n ) to the number of pots and dives that could
be accomplished in five days.
1 1
0.8-
0.6-
53
s
o
Q_
04-
\ \\ II ff ^ots Transects
0.2-
\ \\ // J ("=250) (n=75)
>. » 3 y ~D~ "*" Males
w^\ A?f -^- •+. Nonovigerous females
-.C
12 -0.1
-0 08-0.06-0 04-0 02 0 0 02 0.04 0.06 0.08 0 1 0.12
Trand (change/year)
Figure 7
Relationship
between power and trend in population in comparing catch
in crab pots
and density on dive transects for male and nonovigerous
female Dung
eness crabs iC. magister).
larger with pots than with transects and the variance
with pots is lower.
Despite their low power, the independent measures
of abundance provided by dives helped us identify bias
in our Dungeness crab survey method. Our analysis of
these two techniques demonstrates that it is possible
to avoid most biases with pots if sampling is conducted
at optimal times of year. Similar comparisons could be
conducted in other areas to identify sampling biases so
that they could be minimized and important param-
eters, such as abundance, size, and sex ratio, could be
monitored effectively.
496
Fishery Bulletin 102(3)
Acknowledgments
This long-term study was made possible by the support of
a large number of people. J. de La Bruere made the field
work efficient and enjoyable through his expert ability
to operate the RV Alaskan Gyre. We thank A. Andrews
for large efforts during the field work, data manage-
ment, and analysis. G. Bishop, C. Dezan, E. Hooge, P.
Hooge, E. Leder, J. Luthy, J. Nielsen, C. Schroth, D.
Schultz, L. Solomon, and K. Swiney each participated
in the project for several years. The manuscript was
improved by comments from E. Mathews, E. Knudsen,
and three anonymous reviewers. We thank M. Jensen,
J. Brady, T. Lee, M. Moss, and S. Rice for their contin-
ued support. We especially thank the large number of
unnamed graduate students, faculty, state and federal
agency researchers — over 70 people total — who gener-
ously donated their time and efforts to this long-term
project. This project was funded by the United States
Geological Survey and the National Park Service.
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498
Abstract— The lengths of otoliths and
other skeletal structures recovered
from the scats of pinnipeds, such as
Steller sea lions iEumetopias juba-
tus), correlate with body size and
can be used to estimate the length
of prey consumed. Unfortunately,
otoliths are often found in too few
scats or are too digested to usefully
estimate prey size. Alternative diag-
nostic bones are frequently recovered,
but few bone-size to prey-size cor-
relations exist and bones are also
reduced in size by various degrees
owing to digestion. To prevent under-
estimates in prey sizes consumed
techniques are required to account for
the degree of digestion of alternative
bones prior to estimating prey size.
We developed a method (using defined
criteria and photo-reference material)
to assign the degree of digestion for
key cranial structures of two prey
species: walleye pollock (Theragra
chalcogramma) and Atka mackerel
(Pleurogrammus monopterygius). The
method grades each structure into one
of three condition categories; good,
fair or poor. We also conducted feeding
trials with captive Steller sea lions,
feeding both fish species to determine
the extent of erosion of each structure
and to derive condition-specific diges-
tion correction factors to reconstruct
the original sizes of the structures
consumed. In general, larger struc-
tures were relatively more digested
than smaller ones. Mean size reduc-
tion varied between different types
of structures (3.3-26.3%), but was
not influenced by the size of the prey
consumed. Results from the observa-
tions and experiments were combined
to be able to reconstruct the size of
prey consumed by sea lions and other
pinnipeds. The proposed method has
four steps: 1) measure the recovered
structures and grade the extent of
digestion by using defined criteria
and photo-reference collection; 2)
exclude structures graded in poor con-
dition; 3) multiply measurements of
structures in good and fair condition
by their appropriate digestion correc-
tion factors to derive their original
size; and 4) calculate the size of prey
from allometric regressions relating
corrected structure measurements to
body lengths. This technique can be
readily applied to piscivore dietary
studies that use hard remains of
fish.
Manuscript submitted 28 April 2003
I" Scientific Editor's Office.
Manuscript approved for publication
25 March 2004 by the Scientific Editor.
Fish. Bull. 102:498-508(2004).
A method to improve size estimates of
walleye pollock (Theragra chalcogramma) and
Atka mackerel (Pleurogrammus monopterygius)
consumed by pinnipeds: digestion correction
factors applied to bones and otoliths
recovered in scats
Dominic J. Tollit '
Susan G. Heaslip1
Tonya K. Zeppelin2
Ruth Joy'
Katherine A. Call2
Andrew W. Trites1
1 Marine Mammal Research Unit, Fisheries Centre
University of British Columbia, Room 18, Hut B-3
6248 Biological Sciences Road
Vancouver, British Columbia, Canada, V6T 1Z4
E-mail address (for D. J Tollit): tollit 5zoology.ubc.ca
2 National Marine Mammal Laboratory
Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
7600 Sand Point Way NE
Seattle, Washington 98115
Prey skeletal remnants from stom-
ach samples and more recently from
fecal (scat) samples are widely used
to determine what pinnipeds eat
(Pitcher, 1981; Olesiuk et al., 1990;
Tollit and Thompson, 1996; Browne
et al., 2002). Prey can usually be
identified from taxon-specific hard
remains, the sizes of which often cor-
relate with the length and mass of
the prey (Harkonen, 1986; Desse and
Desse-Berset, 1996). In the past, sag-
ittal otoliths were commonly used to
estimate prey size (Frost and Lowry,
1981) but were recognized to erode or
become completely digested (Prime
and Hammond, 1987; Harvey, 1989).
Thus, otolith measurements likely
underestimated sizes and numbers
of fish ingested (Jobling and Breiby,
1986), thereby preventing a reliable
assessment of overlap of prey con-
sumed with catch taken by commercial
fisheries (Beverton, 1985). Accurate
estimates of size of prey consumed by
pinnipeds are also important in order
to understand foraging behavior and
to explain spatial and temporal vari-
ability in diet composition.
There are at least three potential
ways to deal with the effect of diges-
tion on estimates of prey size. One is
to measure only relatively uneroded
otoliths and assume that eroded oto-
liths are from the same size fish as
uneroded otoliths (Frost and Lowry,
1986; Bowen and Harrison, 1994).
Another is to apply a single species-
specific digestion coefficient or correc-
tion factor (DCF), derived from feed-
ing experiments with captive seals
fed fish of known sizes and using
measurements of all the eroded oto-
liths recovered in the scats produced
(Prime and Hammond, 1987; Harvey,
1989). The third is to estimate and
correct for the degree of digestion
(based on defined losses of morpho-
logical features) of each recovered
otolith by using estimates from ref-
erence material (Sinclair et al.. 1994;
Antonelis et al., 1997) or by applying
condition-specific DCFs derived from
fish fed in captive seal feeding studies
(Tollit et al„ 1997).
Of the three approaches to correctly
estimate prey size from skeletal re-
mains, there is the assumption with
To Hit et al.: A method to improve size estimates of Theragra chalcogramma and Pleurogrammus monopterygius
499
the use of only uneroded otoliths that recovery and the
degree of digestion is independent of otolith size, result-
ing in a potentially biased fraction. For certain species
it can also result in a notable reduction in sample size
because relatively few otoliths pass through the gut
in good condition. The second approach of applying
mean species-specific DCFs is an improvement to not
accounting for size reduction (Laake et al., 2002); how-
ever, there is the assumption with this approach that
all structures are reduced in size by the same amount.
Consequently, mean fish mass may be overestimated if
such correction factors are applied to relatively undi-
gested otoliths, or they may be underestimated if ap-
plied to very digested otoliths (Hammond et al., 1994;
Tollit et al., 1997). The third method accounts for the
intraspecific variation in size reduction caused by di-
gestion, reduces systematic error (see Hammond and
Rothery, 19961. yields estimates of mass that compare
favorably to those fed to captive animals (Tollit et al.,
1997). and hence may well be the most promising ap-
proach to reconstructing prey size.
The dramatic decline of the western population of
Steller sea lions (Eumetopias jubatus) in the 1980s
(Loughlin et al., 1992; Trites and Larkin, 1996) has
prompted a number of studies to determine what they
eat and the extent of dietary overlap (prey consumed)
with catch taken by commercial fisheries. Stomach con-
tents analysis was used to determine diet until the late
1980s when scat analysis became the preferred method
(e.g., Pitcher, 1981; Frost and Lowry, 1986; Sinclair and
Zeppelin, 2002). However, unlike in stomachs, there is
an overall sparsity of otoliths in Steller sea lion scats
(Sinclair and Zeppelin, 2002) and, therefore there is a
need to also use other skeletal structures to describe
the size of prey consumed.
The following outlines a method (using defined crite-
ria and photo-reference material) to assign the degree
of digestion for otoliths and alternative key skeletal
structures of walleye pollock (Theragra chalcogramma)
and Atka mackerel (Pleurogrammus monopterygius)
recovered from scats. We also present the results of
a feeding study with captive Steller sea lions used to
determine the extent of erosion and to derive condition-
specific digestion correction factors to reconstruct the
original sizes of the pollock and Atka mackerel struc-
tures consumed. Finally, we combine these DCFs with
newly developed regression formulae that estimate fish
length to derive a more accurate method of estimating
size of pollock and Atka mackerel consumed by Steller
sea lions and other pinnipeds (see Zeppelin et al., 2004,
this issue; Tollit et al., 2004, this issue).
Materials and methods
Experimentally derived digestion correction factors
Feeding experiments were conducted with two 3-year-
old female Steller sea lions: Steller sea lion 1 (SSL11
[ID no. F97HA], mean mass 129 kg; steller sea lion
2 [SSL2] [ID no. F97SI], mean mass 150 kg) between
October 2000 and April 2002 at the Vancouver Aquarium
Marine Science Centre. Over the experimental period,
the sea lions were fed pollock for 52 days in 16 separate
feeding experiments, and Atka mackerel for 31 days
in 5 separate feeding experiments, at between -4-8%
of body mass per day. Fork length (FL) and weight of
all fish were measured to ±0.1 cm and ±1 g. Sea lions
were fed meals of pollock of three size categories (small,
28.5-32.5 cm FL; medium. 33.5-38.7 cm FL; large,
40-45 cm FLi and meals of Atka mackerel of one size
category (30-36 cm FL). Fish of one particular size cat-
egory were fed either as a single meal or as a seven-day
block of meals. Full details of a typical experimental
protocol can be found in Tollit et al. (2003). Size ranges
for any category offish fed within separate experiments
were usually <3 cm. Fecal material was collected until no
other remains of experimental meals were found (7 days
after feeding), and was washed through a 0.5-mm sieve
to remove hard parts. Each animal was maintained on
whole Pacific herring (Clupea pallasi) between experi-
ments at ~6'7( body mass per day.
The strong relationship between fish size and otolith
size also exists for other skeletal structures (Desse and
Desse-Berset, 1996). Thus, we quantified the types and
numbers of the prey structures recovered in the scats
of free-ranging Steller sea lions (from the collections
of Trites et al.1 and Sinclair and Zeppelin, 2000) and
selected seven of the most commonly occurring struc-
tures for pollock and Atka mackerel. These were the
sagittal otolith (OTO), as well as the interhyal (INTEl,
hypobranchial 3 (HYPO), pharyngobranchial 2 (PHAR),
angular (ANGU), quadrate (QUAD), and the dentary
(DENT). The structures selected also had particular
morphological features that seemed to be relatively
resistant to digestion and could effectively be used to
estimate fish size (Figs. 1 and 2, Table 1).
Concurrent with our feeding study, we measured
selected structures (Figs. 1 and 2) from randomly
subsampled fresh fish and combined these data with
unpublished NMFS data to generate allometric regres-
sion formulae relating structural measurements to fish
length (see Zeppelin et al., this issue). Fork lengths
(±0.1 cm) and weights (±1 gl of an extended subsample
of pollock (8.3-47.7 cm FL) were measured to generate
an appropriate regression formula for estimating fish
mass from fork length estimates. All selected structures
are located in the cranium as illustrated in Zeppelin et
al. (2004, this issue). Naming offish structures follows
Rojo (1991).
Initial inspection of selected structures found in scats
from the wild revealed high intraspecific variation in
the degree of digestion, ranging from no apparent size
reduction to about a 60% size reduction (heavily digest-
ed material). Consequently, we extended the condition-
Trites, A. W., D. G. Calkins, and A. J. Winship. 2003. Un-
publ. data. Marine Mammal Research Unit, Fisheries
Centre, University of British Columbia, Hut B-3, 6248 Bio-
logical Sciences Road, Vancouver, B.C., Canada, V6T 1Z4.
500
Fishery Bulletin 102(3)
Figure 1
Photographs showing the changes in morphological features in seven cranial structures of walleye pol-
lock iTheragra chalcogramma) resulting from digestion. Within each section of the figure three condi-
tion categories (good, fair, and poor) are represented from left to right for (A) interhyal (INTEi. iBi
hypobranchial 3 (HYPOl, (Ci pharyngobranchial 2 (PHARl, (D) angular (ANGU), lE i quadrate (QUAD),
(F) dentary (DENTi and (G) sagittal otolith (OTO). Key features used in classification are labeled (see
Table 1 for details), and the measurements taken to calculate fish length (solid line between dashed lines i.
specific DCF technique described by Tollit et al. (1997).
We began by examining the external morphological
features and surface topography of selected structures
from undigested fish (<12 cm to >53 cm) and compared
these with the topography of the same structures recov-
ered from scats collected from wild and captive animals
"To Hit et al.: A method to improve size estimates of Theragra chakogramma and Pleurogrammus monopterygius
501
Figure 2
Photographs showing the changes in morphological features in seven cranial structures of Atka mack-
erel (Pleurogrammus monopterygius) resulting from digestion. Within each section of the figure three
condition categories (good, fair, and poor) are represented from left to right for (A) interhyal (INTE),
(B) hypobranchial 3 (HYPO), (C) angular (ANGU), (D) quadrate (QUAD), (E) dentary (DENT) and
(F) sagittal otolith (OTO). Key features used in classification are labeled (see Table 1 for details) and
measurements taken to calculate fish length (solid line between dashed lines).
(Figs. 1 and 2). The morphological features used to as-
sess level of digestion showed no differences in relative
shape, structure, or in proportion across the size range
of fresh fish examined. We then devised a criteria-based
method to assign a condition category to each structure
depending on the degree of digestion. These criteria
502
Fishery Bulletin 102(3)
take into account only the loss of size to the relevant
feature being measured to estimate fish length (Figs.
1 and 2).
The grading criteria for otoliths (OTO) were based
on the condition categories developed by Sinclair et
al. (1996) to investigate prey selection by northern fur
seals (Callorhinus ursinus). As seen in Sinclair et al.
(1996) and other studies (Frost and Lowry, 1986; Tollit
et al., 1997), external features such as lobation and the
general shape and definition of the sulcus were found in
our study to be good indicators of the degree of otolith
digestion. For the remaining cranial bones, digestion
indicators included the loss of definition or breakage
of defined structural features such as the horns and
ridge (QUAD), hammerhead and stock (DENT), swan
neck, notch and ridge (INTE), honeycomb and crown
iPHAR), cap, neck, and head (ANGU) and tube and
cone (HYPO). We used changes in the described condi-
tion-category criteria (see Table 1 for full details) in
tandem with photo-reference material (Figs. 1 and 2) to
classify all structures into one of three digestion grades
or condition categories: "good", "fair," or "poor."
Hard parts recovered from feeding experiments were
sorted, and all selected cranial structures were as-
signed a condition category and measured with cali-
pers to within ±0.01 mm. Because otoliths were often
chipped or partly broken lengthwise, both length and
width were measured. To test our grading technique, an
independent observer (T.Z.) reassigned a random sub-
sample of each condition category of pollock structures
(n = 158) in a blind test.
On initial investigation, high intraspecific variation
was observed within the selected structures assigned in
poor condition in our feeding study with captive Steller
sea lions. Consequently, structures in poor condition
were not used to calculate DCFs for this category. Our
basis for exclusion was supported by the work of Sin-
clair et al. (1994) and Tollit et al. (1997). Captive sea
lions in our study occasionally regurgitated prey in the
swim tank. Recovered structures that we considered to
have been regurgitated were excluded from DCF calcu-
lations (i.e., vertebrae still articulated, bones that had
flesh attached or that were of a size to exclude passage
through the pyloric sphincter).
Mean reduction (MR) in the metric of each structure
(s) recovered from our feeding experiment was estimated
for each remaining condition category (c) according to
MR
T
xlOO,
where the mean size of egested structures (E) of each
condition category was calculated from measurements
of those recovered from the captive feeding experiments.
and the mean size of each ingested structure (/.) was
estimated from the fork length of fish fed by using
inverse predictions of the regression formulae derived
from fresh material (Zeppelin et al., 2004, this issue).
Mean ingested size was estimated by using bootstrap
simulations (1000 runs) that randomly sampled with
replacement and selected the median (500th value I from
the sorted bootstrapped values (Reynolds and Aebischer,
1991).
For pollock, mean reduction for each condition cat-
egory was compared across size ranges by using a Krus-
kal-Wallis analysis of variance. A significance level of
P<0.0056 was set based on the Bonferroni adjusted
probability for nine multiple comparisons (Siegel and
Castellan, 1988). Failing to find any significant differ-
ences resulted in pooling the data from each size range
to calculate specific condition category MR values. Con-
dition category DCFs were calculated for each selected
structure as / JESC except for PHAR structures of Atka
mackerel because too few elements were recovered from
the scats of captive animals.
Estimating confidence limits around digestion
correction factors
We used a bootstrap simulation to estimate upper and
lower bounds of the 95% confidence interval (CI) given
that the DCF is a ratio of two means (Reynolds and
Aebischer. 1991 1. This technique allows different sources
of error to be combined or partitioned. There were two
major sources of error associated with calculating DCFs
(Tollit et al., 1997). The first were those associated with
the regression formulae used to calculate the mean size
of structure ingested from the original fish fed. and the
second were those associated with the errors around the
mean size of egested structure (i.e., resampling errors).
We assessed errors associated with the regression
formulae using a parametric bootstrapping procedure
(Manly, 1997) that involved regressing structure size
against fork length. This was repeated 1000 times and
95% confidence intervals were taken as the 25th and
975th values of the sorted bootstrapped regression coef-
ficient values. Results were compared to those computed
analytically by using the resultant standard error (Eq.
17.23 in Zar, 1984) and were found to be consistent (see
Zeppelin et al., 2004, this issue).
We estimated resampling errors related to the vari-
ability in digestion of egested structures by repeatedly
selecting n structures, at random, with replacement from
the original sample set of n egested structures. Mean
egested size was recalculated in this way 1000 times,
as were a mean DCF and 95% CI as described above.
Both regression and resampling errors were combined in
sequence to derive overall 95% CIs around DCFs.
Our recommended procedure for applying our DCFs to
cranial structures recovered from scats collected in the
wild has four steps: 1) measure the recovered structures
and grade the extent of digestion using defined criteria
and photo-reference collection; 2) exclude structures
graded in poor condition; 3) multiply measurements of
structures in good and fair condition by their appropriate
digestion correction factors to derive their original size;
and 4) calculate the size of prey from allometric regres-
sions relating corrected structure measurements to fish
fork lengths (see also Tollit et al.. 2004, this issue).
"To Hit et al.: A method to improve size estimates of Theragra cha/cogramma and Pleurogrammus monopterygius
503
Results
A relatively objective method to estimate the degree of
digestion of dominant structures of pollock and Atka
mackerel was derived by using defined criteria (Table 1)
and photo-reference material (Figs. 1 and 2). Condition-
specific digestion correction factors (and derived confi-
dence intervals) calculated for each structure augmented
our method of estimating size of prey from bones and
otoliths recovered in scats, as well as potentially from
bones and otoliths taken from stomach contents.
Mean reduction (MR) in the size of pollock DENT
and QUAD in good condition and ANGU, HYPO, IN-
TE, OTO, and PHAR in fair condition were between
12.2-18.5%, and larger values were found for QUAD
(22.8%) and DENT (24.7%) in fair condition (Table 2).
Our overall 95% confidence intervals were generally
symmetrical and converted to a mean range of ±2.2%
(±0.5, SD) around MR values. Mean DCFs ranged be-
tween 1.14 and 1.33, and lower bounds of 95% CIs ex-
ceeded 1.11 in all instances, confirming that egested
structures of these condition categories were significant-
ly smaller than the size at which they were ingested
(Table 2). Partitioning errors showed that resampling of
egested structures was the major source of error (>73%
across structures) within the overall total. Our overall
95% CIs resulted in a maximum total error of ±1.7 cm
around an estimated mean of 40 cm for pollock.
Mean reduction in the size of Atka mackerel struc-
tures varied more widely (3.3-26.3%), leading to DCFs
ranging between 1.03 and 1.36. QUAD in good condition
provided the smallest DCF, and DENT in fair condition
the largest. Overall, our 95% CIs converted to a mean
range of ±2.4% (±0.6) around MR values, and all lower
95% CI bounds exceeded 1.0 (Table 2). As seen when
errors were partitioned for pollock, errors owing to resa-
mpling of egested structures were the major source of
error (>83'7t across structures) within the overall total
for Atka mackerel. Our overall 95% CIs resulted in a
maximum total error of ±1.2 cm around an estimated
mean of 40 cm for Atka mackerel.
With the exception of the two largest skeletal struc-
tures (DENT and QUAD, Table 2), some selected struc-
tures (INTE, HYPO, PHAR, ANGU, and OTO) occurred
in scats with no clear loss in size or loss of morphologi-
cal features related to digestion. For these five struc-
tures, we ascribed the condition category good and as-
signed a DCF of 1.0 (i.e., no correction for partial size
reduction due to digestion required).
Of the 158 structures in our blind test, 141 (89.2%)
were assigned identical condition categories. Of the
remaining 17 structures, 11 (65%) were noted as be-
ing borderline between categories. Angulars (ANGU)
accounted for the majority (-60%) of all differences,
with all but one re-assigned in good condition as op-
posed to fair condition. On review, differences in as-
signing angulars were mainly the result of differences
in opinion on what constituted a well-defined and sharp
point (Fig. 1, Table 1). Clarification through the addi-
tional use of reference material (including both pristine
structures and examples of each condition category) is
advised, particularly for angulars. Comparison of the
same 158 bones between two observers (D.T. and S.H.)
using the same structure reference collection resulted
in assigning more than 93% (147/158) of structures to
an identical category.
The regression formula for estimating pollock mass
(M) from fork length (FL) estimates was best described
by using an exponential equation (M=0.0051 xFL3n,
n = 981. r2 = 0.987).
Discussion
The size of prey consumed by pinnipeds can usually be
reliably estimated from otoliths recovered in scats if
partial digestion is accounted for (Tollit et al., 1997).
However, otoliths from Steller sea lion scats are often
found in too few numbers, or are too digested or broken
to be useful (Sinclair and Zeppelin, 2002; Tollit et al.,
2004, this issue). It was, therefore, necessary to use
alternative skeletal structures to estimate the size of
prey selected by Steller sea lions. Zeppelin et al. (2004,
this issue) documented good relationships (r2=0.78-0.99)
between the size of selected alternative structures and
fork length for pollock and Atka mackerel. However,
all skeletal structures are susceptible to digestion in
the stomach (our study, and Murie and Lavigne, 1986).
Thus, techniques are required to account for the degree
of digestion of alternative structures prior to estimating
prey size.
Reductions in the size of otoliths during passage
through the digestive tract of pinnipeds have been
widely reported (e.g., da Silva and Neilson, 1985; Prime
and Hammond. 1987; Harvey, 1989; Tollit et al., 1997).
Similarly, we found significant reduction in the sizes of
all selected cranial structures from pollock and Atka
mackerel. Size reduction also showed great variability.
Relatively small structures were found with no obvious
loss in size due to digestion, but were also frequently
heavily eroded.
The degree of digestion on different otoliths and
bones may be related to species, size of fish (Bowen,
2000). or even its shape, but seems to be random in any
one meal (Murie and Lavigne, 1986). Degree of diges-
tion likely depends on a range of factors such as meal
size, meal frequency, meal composition, and method of
consumption. In the face of these multiple factors we
feel our method for classifying the degree of digestion
into one of three condition categories is practical and
relatively objective. However, our technique does not
consider potential biases of enumeration associated
with smaller prey being more susceptible to complete
digestion than relatively larger prey, or of individual
fish being counted more than once if all multiple struc-
tures are used. Nevertheless, resolution to these biases
have been advocated (see Tollit et al., 1997; Laake et
al., 2002; Tollit et al., 2003; Tollit et al., 2004, this is-
sue). The category selections chosen with our criteria
showed good agreement among independent observers.
504
Fishery Bulletin 102(3)
Table 1
Distinctive external morphological features for defining the degree of digestion (condition category) as good(G), fair (F), and poor
(Pi for selected cranial structures of walleye pollock and Atka mackerel. Features are given in order of importance. See Table 2
for definition of structure codes and Figure 1 and 2 for illustrations. WP = walleye pollock.
Species and
structure code Category Distinctive external morphological features
Walleye pollock
INTE
HYPO
PHAR
ANGU
QUAD
DENT
OTO
G 1) Retains characteristic shape, notably the ridge and swan neck. 2) Both ends show no damage
(except for the loss of the point and minor nicks) and do not affect length measurement.
F li Ridge and swan neck clearly defined. 2) One end can show limited damage with <159c reduction.
Minor nicks on opposite end acceptable, if there is no further loss in length measurement.
P 1) Loss of characteristic shape, with ridge or swan neck (or both) ill defined. Body of structure
contains holes. 2) Both ends show clear damage.
G 1) Retains characteristic shape, with cone ~2x the length of the tube. 2) Tube end and area 1 show no
damage (except for minor nicks) and do no affect the total length measurement. 3) Cone end angled
when viewed from the front elevation (back elevation shown in Fig. 1).
F 1) Tube end or area 1 shows limited damage (cone end no longer angled) clearly preventing an
accurate length measurement.
P 1) Both tube end and area 1 show damage, and a general loss of characteristic shape evident.
G 1) Retains characteristic shape, notably a raised spout, honeycomb, and crown. 2) Crown clearly
projects above honeycomb (front elevation) and is intact at area 2. 3) Clear projection of honeycomb
(back elevation — see area 3). 4) No affect on measurement.
F 1) No clear projection of honeycomb at area 3 or crown shows damage at area 2 (preventing an
accurate width measurement). 2) Crown or spout (or both) can show minor damage.
P li Characteristic shape lost, often only honeycomb present. 2) Honeycomb smooth, crown heavily
eroded with areas 2 and 3 eroded or damaged. 3) Both ends show clear damage.
G 1) Point sharp and well defined with no impact to measurement. 2) Area 4 in good condition and
angled curve complete. 3) Neck present, but with minor damage. 4) Material of cap continues to point
tip.
F 1 ) Point no longer extensive or sharp or area 4 damaged and poorly defined. 2 ) Neck usually present,
but with wear.
P 1 ) Characteristic shape lost with neck often absent. 2 ) Point heavily eroded. 3 ) Area 4 shows damage
or no definition.
G 1) Groove defined from all angles and observable with the naked eye. 2) Horns rounded. 3) Angle of
area 5 is clearly curvilinear. 4) Evidence of ridge and spike often observable.
F 1) Groove unclear, forming only an indisctinct notch. 2) Horns have lost rounded definition and may-
be pointed or worn on one side. 3) Ridge and spike often only residual.
P 1) Horns pointed, notch absent. 2) Ridge and spike often absent. 3) Angle of area 5 flattened.
4 1 Unable to determine side with assurance.
G 1) Hammerhead retains rounded end elevation features (note: both sides are not exactly symmetrical),
allowing full width measurement. 2) Material in addition to the stock may be present. 3) Stock
clearly curved from side elevation. 4) Width and breadth of "rounded" stock similar.
F 1) Hammerhead shows erosion on one side, affecting full width measurement. 2) Breadth of stock
reduced, but not flattened.
P li Hammerhead eroded and flattened with both sides showing erosion. 2) Breadth of stock flattened,
stock less rounded and less robust. 3) Unable to determine side with assurance.
P 1) Sulcus and scalloping (on most margins) well defined, and no obvious reduction in size due to
digestion. 2) Able to determine side. 3) Inside strongly convex, retains characteristic shape.
F 1) Sulcus worn but shows definition. 2) Able to determine side. 3) Scalloping worn but shows no
reverse scalloping.
P 1) Unable to determine side. 2) Scalloping worn completely smooth and reverse scalloping present.
3) Clearly broken, worn, flattened, and unable to obtain an accurate measurement.
continued
"To Hit et al.: A method to improve size estimates of Theragra chalcogramma and P/eurogrammus monopterygius
505
Table 1 (continued)
Species and
structure code
Category
Distinctive external morphological features
Atka mackerel
INTE
HYPO
ANGU
QUAD
DENT
OTO
G Like that of walleye pollock (WP) (except no point), with ridge, neck and notch clearly defined.
F li Ridge present, but shows signs of wear. 2) Swan neck shows wear resulting in a "horseshoe" shape.
3 1 Notch shows only minor wear or chipping and does not prevent accurate measurement.
P 1) Loss of characteristic ridge and neck with body worn (may contain holes). 2) Both neck and notch
show clear damage.
G 1) Cone rounded and complete, tube complete, retains characteristic shape. 2) Minor nicks on cone
and tube may be present but do not impact total length measurement.
F Cone worn, loss of rounded shape, and area 1 shows minor chipping or damage or tip of tube is broken
or clearly chipped.
P 1) Cone body and area 1 show major wear, chips, and breaks. 2) Tube broken or absent entirely,
unable to measure length.
G Like WP. additionally cap rounded and head shows only minor wear.
F Like WP, additionally 1) cap worn with loss of shape. 2) Head worn, chipped, and often has holes,
3) Ridge on dorsal side above neck worn smooth.
P Like WP. additionally 1 ) head shows major damage, wear, breaks, and holes, 2 ) Difficult to determine
side with confidence.
G It Horns rounded and in good condition, with angle between horns clearly curvilinear. (Note: Horns
are of unequal size and shape and one side is more robust, rounded, and sloped.) 2 1 Evidence of ridge
and spike observable. 3) Definition of left and right sides is easily achievable.
F 1) Horns have lost rounded definition and may be pointed or worn on one side, making distinction
between sides difficult. 2) Ridge and spike often only residual.
P Like WP, additionally no distinction between horns easily achievable.
G Like WP (except no hammerhead), additionally 1) head retains characteristic features, tooth sockets
present, 2) Ventral side of head a defined point.
F Like WP, additionally 1) head eroded or chipped with tooth sockets noticeably worn, 2) Point on
ventral side of head eroded or chipped.
P Like WP, additionally head eroded or flattened with point often heavily eroded or badly chipped,
accurate measurement unattainable.
G 1 1 Rostrum not chipped or broken. 2 ) Sulcus clearly defined, as are anterior and posterior colliculums.
3 ) Scalloping on antirostrum and posterior end clearly distinguishable. 4 ) No obvious wear or chipping
with no obvious reduction in length (width). 5) Cristae of antirostrum forms a well-defined ridge.
F 1) Rostrum shows some wear but remains unbroken and retains characteristic shape. 2 1 Sulcus
still has definition despite wear, shown as a uniform channel, anterior and posterior colliculums
indistinct. 3) Cristae and scalloping on antirostrum and posterior end worn smooth.
P 1 ) Rostrum or posterior end broken or worn to such a degree that accurate measurement cannot be
obtained. 2) Sulcus difficult to distinguish or worn smooth. 3) Cristae and scalloping on antirostrum
and posterior end worn completely smooth. 4) Side cannot be easily obtained.
Nevertheless, we recommend that a hands-on reference
collection be used.
The procedure we recommend to estimate fish length
after classification involves excluding structures
considered heavily digested (condition category poor)
and applying specific condition-category DCFs (Ta-
ble 2) to the remaining structure prior to calculating
fish length from allometric regressions (see Tollit et
al., 2004, this issue). The exclusion of structures in
poor condition was necessary because of the large and
variable size reduction observed in this category. Our
technique uses changes noted in the morphological
features of the structures themselves and is therefore
not specific to Steller sea lions. Because structures
are likely to erode in a predictable manner whatever
the species of the stomach they are held within, it
seems probable that they can also be classified into
a particular condition category for use with DCFs.
Consequently, our technique may be appropriate to
marine piscivore dietary studies where prey size needs
506
Fishery Bulletin 102(3)
Table 2
Condition-specific digestion
correction factors (DCFs) for selected cranial structures of walleye pollock and Atka mackerel with
associated condition categories good (G) and fair (F
). Lower and upper
bounds of the 95^
confidence intervals (CIs) were calcu-
lated by using bootstrap ret
ampling procedures.
Structure
CI
Species and structure
code
Grade
n
DCF
SD
Lower
Upper
Walleye pollock
Interhyal
INTE
F
54
1.1423
0.054
1.1168
1.1714
Hypobranchial 3
HYPO
F
22
1.1658
0.063
1.1343
1.1970
Pharyngobranchial 2
PHAR
F
39
1.2109
0.067
1.1717
1.2566
Angular
ANGU
F
85
1.2065
0.103
1.1670
1.2462
Quadrate
QUAD
G
20
1.2272
0.039
1.2025
1.2512
F
27
1.2958
0.074
1.2623
1.3280
Dentary
DENT
G
17
1.1950
0.074
1.1546
1.2337
F
31
1.3285
0.071
1.2941
1.3649
Otolith (length)
OTOL
F
37
1.1593
0.059
1.1400
1.1788
Otolith (width)
OTOW
F
49
1.2107
0.089
1.1901
1.2419
Atka mackerel
Interhyal
INTE
F
37
1.0729
0.089
1.0374
1.1085
Hypobranchial 3
HYPO
F
23
1.1361
0.040
1.1160
1.1568
Angular
ANGU
F
40
1.1361
0.097
1.1053
1.1700
Quadrate
QUAD
G
23
1.0343
0.053
1.0070
1.0597
F
23
1.0886
0.078
1.0551
1.1213
Dentary
DENT
G
34
1.2068
0.098
1.1666
1.2466
F
37
1.3563
0.143
1.3063
1.4119
Otolith (length)
OTOL
F
109
1.1691
0.109
1.1459
1.1921
Otolith (width)
OTOW
F
115
1.2062
0.104
1.1837
1.2277
to be determined from partially digested prey hard
remains.
Experimentally derived pollock DCFs were deter-
mined from three distinct size ranges of fish (28.5-45
cm FL), but the degree of erosion for each structure
within each condition category did not show any sig-
nificant differences across this range. We also found the
relative shape, structure, and proportion of the morpho-
logical features used to estimate erosion were consistent
for both smaller and larger fish. We therefore believe
DCFs can be used for fish outside of the experimental
size range of this study. Average size reduction varied
between different pollock structures (12.2-24.7%) and
also between condition categories, as they did for Atka
mackerel (Table 2). We determined that pollock otoliths
in fair condition were reduced by 149J in length, close to
the 20% value estimated from reference material (Sin-
clair et al., 1994). Our criteria for defining a condition
category of fair for pollock otoliths equates to a grade
between low amounts and medium amounts of diges-
tion as defined by Tollit et al. (1997) for Atlantic cod
(which has a similar looking otolith). Our value of 14%
lies midway between those determined for cod otoliths
graded low and medium.
Jaw bones (DENT) were by far the largest structure
used in our study but do not appear to pass through
the pyloric sphincter without some level of digestion.
Usually only the hammerhead and stock (representing
less than a third of the whole structure) are recov-
ered in scats. The large size accounts for the relatively
greater percent mean reduction and hence higher DCF
of DENT structures graded either in good or fair con-
dition (Table 2). Although quadrates (QUAD) are also
relatively large structures with a projecting ridge that
is often much reduced when found in scats, we found
QUAD structures of Atka mackerel recovered in scats
from field studies and captive sea lion studies in rela-
tively better condition than those of pollock, leading
to differences in grading criteria and resulting DCFs
(Tables 1 and 2). Part of the reason may be that the
horns on a pollock QUAD project widthwise more than
those of Atka mackerel, presenting a greater surface
area for digestive erosion of the structural feature that
is measured to estimate size (Fig. 1).
Our overall 95^f confidence intervals around DCFs
were generally narrow (Table 2), highlighting the tight
fit of the regression formulae used and the benefits of
partitioning the data into specific categories. Our boot-
strap analysis suggests that resampling errors were
the major source of error in calculating DCFs. Future
research should concentrate on improving sample sizes
for data on percentage size reduction of bones for each
Tollit et al.: A method to improve size estimates of Theragra chalcogramma and Pleurogrammus monopterygius
507
category, rather than on improving regression formulae.
For both prey species, QUAD in good condition and
OTO in fair condition, in addition to pollock INTE in
fair condition and Atka mackerel HYPO in fair condi-
tion, provided the most reliable estimates of prey size
(Table 2). DENT in fair condition, particularly for Atka
mackerel, provided the least reliable estimate of prey
size (Table 2). Measurement error was relatively insig-
nificant, but attention should be taken when measuring
ANGU and HYPO (Tollit et al., 2004, this issue).
Companion studies by Tollit et al. (2004, this issue)
and Zeppelin et al. (2004, this issue) demonstrate the
feasibility of applying DCFs to structures other than
otoliths and the need to consider the degree of diges-
tion to correctly estimate the length of prey eaten by
pinnipeds and other piscivores. Applying appropriate
digestion correction factors will lead to more refined
estimates of consumption (mass of prey) by marine
mammals, as well as the extent of potential overlap
(length of prey) with the length of fish caught by com-
mercial fisheries.
Acknowledgments
Funding was provided to the North Pacific Universities
Marine Mammal Research Consortium by the National
Oceanographic Atmospheric Administration and the
North Pacific Marine Science Foundation. We would
like to thank the marine mammal trainers and staff of
the Vancouver Aquarium Marine Science Centre, the
contribution of personnel of the UBC Marine Mammal
Research Unit of the UBC EM facility, J. L. Laake for
statistical advice, T. J. Orchard, C. J. Gudmundson, S. J.
Crockford, M. Wong, E. H. Sinclair, and two anonymous
reviewers. We would also like to express gratitude to the
organizations and companies that have donated fish to
the project. Work was undertaken in accordance with
UBC Animal Care Committee guidelines.
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C. J. Gudmundson.
2004. Sizes of walleye pollock (Theragra chalcogramma i
and Atka mackerel (Pleurogrammus monopterygius) con-
sumed by the western stock of Steller sea lions (Eume-
topias jubatus) in Alaska from 1998 to 2000. Fish.
Bull. 102:509-521.
509
Abstract— Prey-size selectivity by
Steller sea lions lEumetopias juba-
tus) is relevant for understanding
the foraging behavior of this declin-
ing predator, but studies have been
problematic because of the absence
and erosion of otoliths usually used
to estimate fish length. Therefore,
we developed regression formulae to
estimate fish length from seven diag-
nostic cranial structures of walleye
pollock (Theragra chalcogramma)
and Atka mackerel (Pleurogrammus
monopterygius). For both species,
all structure measurements were
related with fork length of prey (r2
range: 0.78-0.99). Fork length (FL)
of walleye pollock and Atka mackerel
consumed by Steller sea lions was
estimated by applying these regres-
sion models to cranial structures
recovered from scats (feces) collected
between 1998 and 2000 across the
range of the Alaskan western stock
of Steller sea lions. Experimentally
derived digestion correction factors
were applied to take into account loss
of size due to digestion. Fork lengths
of walleye pollock consumed by Steller
sea lions ranged from 3.7 to 70.8 cm
(mean=39.3 cm, SD = 14.3 cm, n = 666l
and Atka mackerel ranged from 15.3
to 49.6 cm (mean = 32.3 cm, SD =
5.9 cm, rc = 1685). Although sample
sizes were limited, a greater propor-
tion of juvenile (<20 cm) walleye pol-
lock were found in samples collected
during the summer (June-September)
on haul-out sites (64^ juveniles, ;;=11
scats) than on summer rookeries (9%
juveniles, n = 132 scats) or winter
l February-March) haul-out sites
(3% juveniles, n = 69 scats). Annual
changes in the size of Atka mackerel
consumed by Steller sea lions cor-
responded to changes in the length
distribution of Atka mackerel result-
ing from exceptionally strong year
classes. Considerable overlap (>51%)
in the size of walleye pollock and Atka
mackerel taken by Steller sea lions
and the sizes of these species caught
by the commercial trawl fishery were
demonstrated.
Sizes of walleye pollock
(Theragra chalcogramma) and Atka mackerel
(Pleurogrammus monopterygius) consumed by
the western stock of Steller sea lions
(Eumetopias jubatus) in Alaska from 1998 to 2000
Tonya K. Zeppelin'
Dominic J. Tollit2
Katherine A. Call1
Trevor J. Orchard3
Carolyn J. Gudmundson'
E-mail address: Tonya Zeppelin ifflnoaa gov
1 National Marine Mammal Laboratory
Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
7600 Sand Point Way NE
Seattle, Washington 98115
2 Marine Mammal Research Unit
Fisheries Center, Room 18, Hut B-3
University ot British Columbia
6248 Biological Sciences Road
Vancouver, British Columbia, Canada V6T 1Z4
3 Department of Anthropology
University of Toronto
100 St. George Street
Toronto, Ontario, Canada M5S 3G3
Manuscript submitted 28 April 2003
to Scientific Editor's Office.
Manuscript approved for publication
25 March 2004 by the Scientific Editor.
Fish. Bull. 102:509-521 (2004).
The western stock of Steller sea lions
(Eumetopias jubatus) in the Gulf of
Alaska and the Bering Sea has experi-
enced dramatic and continued declines
since the mid-1970s (Loughlin et al„
1992; Loughlin and York, 2000). It is
likely that changes in prey availabil-
ity linked to commercial fisheries and
large-scale oceanographic changes are
among the reasons for the continued
decline (Loughlin and Merrick, 1989;
NRC, 1996). The diet of the western
stock of Steller sea lions has been
recently assessed (Sinclair and Zep-
pelin, 2002), but discrete selection of
prey by size has not been described.
The size of prey is relevant for under-
standing the foraging behavior of the
predator as well as the ecological role
of the prey (e.g., mortality at a given
life history stage). In the case of the
Steller sea lion, prey-size selectivity is
particularly important for understand-
ing spatial and temporal changes in
diet and is needed for making fishery
management decisions.
Size of fish prey consumed by ma-
rine mammals has been estimated
by using sagittal otoliths recovered
from stomach and more recently scat
samples (Pitcher, 1981; Frost and
Lowry, 1986; Browne et al., 2002).
Significant relationships have been
demonstrated between fish fork length
(FL) and otolith length (Templeman
and Squires, 1956; Frost and Low-
ry, 1981; Harvey et al., 2000). The
use of otoliths to describe the size of
prey taken by Steller sea lions has
proved useful in data collected from
stomach samples (e.g., Pitcher, 1981;
Calkins and Goodwin1). However, few
1 Calkins, D. G., and E. Goodwin. 1988.
Unpubl. report. Investigation of the
declining sea lion population in the Gulf
of Alaska, 76 p. Alaska Department of
Fish and Game, 333 Raspberry Road,
Anchorage, Alaska, 99518-1599.
510
Fishery Bulletin 102(3)
otoliths are recovered from Steller sea lion scat, and
measurements of otoliths recovered from scats likely
underestimate prey size because of partial erosion
from digestion (Prime and Hammond, 1987; Del-
linger and Trillmich, 1988; Harvey, 1989). Because
of the impracticality of collecting stomachs and the
low number and poor quality of otoliths found in
scats, alternative methods are needed to accurately
describe the size of prey consumed by Steller sea
lions.
Archaeological studies routinely use skeletal struc-
tures other than otoliths to estimate either fish
length or mass (Keys, 1928; Casteel, 1976; Owen
and Merrick, 1994; Desse and Desse-Berset, 1996).
Wise 11980) used a regression offish length on ver-
tebrae length to estimate prey size from scat samples
of otters (Lutra lutra) and mink tMustela vison).
The regression approach relies on the assumption
that the overall size of a given fish and the size of
skeletal structures are highly correlated. This as-
sumption has been substantiated for cranial and
skeletal structures other than otoliths in various
North Pacific fish species (Orchard, 2001). Thus, the
use of cranial structures appear to be a viable alter-
native to the use of otoliths for studying prey size of
Steller sea lions.
Walleye pollock (Theragra chalcogramma) and At-
ka mackerel (Pleurogrammus monopterygius) rank
among the top prey items of Steller sea lions (Sin-
clair and Zeppelin, 2002) as well as being valuable
in the U.S. commercial fishery (NMFS, 2003). We
estimated fork length for these two primary prey
species from scats collected between 1998 and 2000
across the range of the Alaskan western stock of sea
lions. Fish length was estimated by using regres-
sion formulae relating bone or otolith measurement
to fork length for seven cranial structures found in
sufficient quantities and in good and fair condition in
scat samples. Experimentally derived digestion cor-
rection factors (Tollit et al., 2004b, this issue) were
applied to bone and otolith measurements to account
for loss of size due to erosion. The methods developed
here proved to be an effective tool to estimate size of
prey selected by Steller sea lions and are applicable
for other marine mammal diet studies particularly
where otoliths are highly eroded.
Materials and methods
Development of regression formulae
Fork-length to bone and otolith-length regression
equations were developed for seven cranial struc-
tures from walleye pollock and Atka mackerel. Bones
and otoliths were selected according to species-specific
features, predictability in condition, and prevalence
in scats. Bones included the angular (ANG), quadrate
(QUAD), interhyal (INTE), dentary (DENT), pharyn-
gobranchial 2 (PHAR), and hypobranchial 3 (HYPO)
A Walleye pollock
Pharyngobranchial #2
Quadrate
Interhyal
B Atka mackerel
Otolith
I
Hypobranchial #3
Pharyngobranchial #2
Interhyal
Otolith
Figure 1
Illustrations of the various planes for bone and otolith
measurements used to solve the bone-length to fish-length
regression equations for (A) walleye pollock and (Bl Atka
mackerel. The structures from the right side of the body
are shown for all structures except for quadrates.
(Fig. 1). Fork length regressions were developed for sagit-
tal otolith length (OTOL), as well as for width (OTOW)
measurements. All selected cranial structures were
paired (having a left and right side) which allowed for
enumeration of prey species. Only right-sided bones and
otoliths were used to develop the regression equations.
Zeppelin et al.: Sizes of walleye pollock and Atka mackerel consumed by Eumetopias jubatus
511
In symmetrical fishes such as walleye pollock and Atka
mackerel the left and right otoliths are mirror images
of each other (Harkonen, 1986). We compared the left
and right-sided measurements for all seven structures
using a subsample of the structures used to develop the
regression equations. There was no significant difference
for either walleye pollock (paired Ntest, P<0.05, /? = 13 for
HYPO, 15 for QUAD, and 14 for all other structures) or
Atka mackerel (paired t-test, P<0.05, ra=14 for OTOS
and 17 for all other structures).
Fish specimens used for regressions were collected
from the Gulf of Alaska and Bering Sea. Standard
length (SLi was converted to fork length for walleye
pollock (when fork length was not available for a small
number of otoliths included in the regressions) by using
the following equation: FL = 0.40+1. 07(SL) (Wilson2).
We chose to use FL over SL for the regressions because
all fish were in good condition, thus allowing for ac-
curate measurements. Additionally, FL is the standard
used for commercial fishery and survey data by the
National Marine Fisheries Service for direct compari-
sons. A partial analysis of these data was previously
reported in Orchard (2001). We expanded the data set
reported in Orchard (2001) to reflect the size range of
bones found in Steller sea lion scats and included only
fish specimens collected within our study area.
Linear regression models were fitted for most cranial
structures by using the following equation:
Y= a+ PX,
where Y = the fork length of the fish;
X = the measurement of the cranial structure;
and
a and P are constants that define the regression
formula.
However, some cranial structures provided a better fit
with the following quadratic regression equation:
Y = a + PX + pX2.
The strength of the relationship of the regression models
was assessed by using a coefficient of determination
(r2).
Erosion is a potential source of bias when estimating
prey body size from digested otoliths (Prime and Ham-
mond, 1987; Dellinger and Trillmich, 1988; Harvey,
1989). We used condition-specific digestion correction
factors (DCFs) developed by Tollit et al. (2004b, this
issue) to correct for the high degree of variation in the
erosion of cranial structures. DCFs were obtained from
feeding experiments on captive juvenile Steller sea lions
by using a subsample of fish collected for the regres-
sion analysis (Tollit et al., 2004b, this issue). Selected
cranial structures from three size groups of pollock
2 Wilson, M. 2003. Persona] commun. Alaska Fisheries Sci-
ence Center, Natl. Mar. Fish. Serv., NOAA. Seattle, WA.
(28.5-45.0 cm FL) and one size group of Atka mackerel
(30-36 cm FL) were used to develop the DCFs.
Estimation of size of walleye pollock and Atka mackerel
consumed by Steller sea lions in the Bering Sea and
Gulf of Alaska
Steller sea lion scats were collected from 1998 to 2000
along most of the U.S. range of the Alaskan western stock.
Scats were collected from rookery (breeding) and haul-
out (nonbreeding) sites in summer (June-September)
and haul-out sites in winter (February-March). We
assumed that scats collected on summer rookery sites
primarily represent the diet of adult females because
adult males present on rookeries usually fast during
this time. Juveniles of both sexes come ashore on rook-
eries during summer and undoubtedly are represented
in the data, but to a lesser degree than adult females.
Scats from juvenile Steller sea lions are more likely to
be sampled on haul-out sites during summer, where
juveniles make up the greatest proportion of individuals.
Scats collected on summer haul-out sites or any winter
site presumably represent a greater cross-section of
ages and sexes than collections from rookeries during
summer.
Scats were rinsed through nested sieves of 4.8-, 1.4-,
0.7-, and 0.5-mm mesh. Bones and otoliths were iden-
tified to the lowest possible taxon by using reference
collection specimens. All recovered otoliths and selected
bones identified as either walleye pollock or Atka mack-
erel were given a condition grade based on the degree of
erosion (Tollit et al., 2004b, this issue). In general, cra-
nial structures considered in "good" condition had little
or no erosion, "fair" were moderately eroded (generally
up to about 20%), and "poor" were heavily digested
(Tollit et al., 2004b, this issue). All structures that were
given a condition grade of "good" or "fair" were identi-
fied as being from the left or right side and measured
to the nearest 0.01 mm with digital calipers. Cranial
structures graded as "poor" were not measured and ex-
cluded from further analyses because of high observed
intraspecific variation (Tollit et al., 1997; Tollit et al.,
2004b, this issue).
Fork-length estimates with and without DCFs applied
were calculated for each cranial structure and for all
structures combined. Otoliths were treated separate-
ly because most diet studies currently rely on otolith
length to estimate fish fork length. Ninety-five percent
confidence intervals around all mean size estimates
were calculated by using parametric bootstrapping pro-
cedures (Manly, 1997) in which error associated with
the regression equation and resampling error resulting
from variability within correction factors, and variabil-
ity in scats were taken into account. Full details of the
bootstrapping procedure are presented in Tollit et al.
(2004b, this issue).
The same fish may be represented by multiple cranial
structures within a scat; therefore, in order to avoid
pseudoreplication. we selected a minimum number of
individuals (MNI; Ringrose, 1993) for each scat sample.
512
Fishery Bulletin 102(3)
Table 1
Relationship between bone measui
•ement and fish fork length (FL) in
millimeters. For
each equation
the number of bones mea-
sured In), coefficient of determination (r2), standard error of the regression coefficient (SE and SE2for
quadratic regression coef-
ficients), range offish lengths and
mean of fork lengths are g
ven. All measurements are given in millimeters.
Species
Structure code
Regression
r2
ii
SE, SE2
Range of FL
Mean FL
Walleye pollock
INTE
FL = 49.78* + 5.12
0.98
49
1.12
83-477
201.61
HYPO
FL = 43.14* + 14.12
0.99
49
0.78
83-477
231.58
PHAR
FL = 80.19a- + 19.43
0.95
51
2.58
83-477
204.37
ANGU
FL = 59.25* +15.27
0.96
44
1.82
83-477
208.75
QUAD
FL = 89.47* + 6.77
0.99
59
1.32
83-477
203.92
DENT
FL = 108.46x- 1.52
0.99
60
1.75
83-477
206.61
OTOL
FL = 0.50*2 + 15.74* +
13.3
0.99
504
0.68, 0.34
49-530
187.35
OTOW
FL = 2.32*2 + 44.74* +
3.73
0.99
508
1.54,0.19
49-530
188.66
Atka mackerel
INTE
FL = 57.38* + 95.57
0.86
106
2.26
185-500
355.37
HYPO
FL = 38.58* 80.64
0.95
105
0.85
185-500
355.62
PHAR
FL = 81.32* + 70.40
0.91
107
2.48
185-500
354.90
ANGU
FL = 58.38* + 73.86
0.91
105
1.85
185-500
355.34
QUAD
FL = -8.90*2 + 129.38*
+ 9.16
0.96
108
7.07,0.96
185-500
354.69
DENT
FL = -7.10*2 + 115.83*
-21.68
0.94
108
7.08, 0.73
185-500
354.69
OTOL
FL = 62.54* +24.24
0.83
165
2.19
185-500
349.82
OTOW
FL= 188.19* -77.71
0.78
170
7.71
185-500
350.09
Minimum number of individuals for each species in
each scat was estimated by counting species-specific
sided elements and choosing the greatest number of left
or right elements. If more than one structure had the
same number, the structure with the highest r2 value
in its regression on fork length (Table 1) was selected
as a representative length estimate for that fish. If an
equal number of left and right bones were present, right
bones were selected.
Temporal variation in size of walleye pollock and
Atka mackerel consumed by Steller sea lions
Temporal differences were assessed by grouping fish
into stage-class categories. Stage-class categories were
defined for pollock as follows: juvenile or 1-year-old
fish (<20 cm FL), adolescent (20.1-34 cm FL), subadult
(34.1-45 cm FL), and adult (>45.1 cm FL; Dorn et al.,
2001; Smith, 1981; Walline, 1983). Walleye pollock sub-
adults are likely 3-4 years old, of which -50% have
matured and recruited into the fishery, whereas adults
are sexually mature fish, likely 5 years or older. Stage-
class categories for Atka mackeral were defined as fol-
lows: juvenile up to 2-year-old fish (<30 cm), adolescent
or 3-year-old fish (30.1-35.2 cm), subadult or 4-year-old
fish (35.3-45 cm), and adults (>45.1 cm; Lowe et al.,
2001; McDermott and Lowe, 1997). Atka mackerel ado-
lescents are -50% sexually mature and adult-size fish
are fully mature.
A chi-squared contingency test was used to test for
differences in the proportion offish stage-classes occur-
ring in scats among rookeries and haul-out sites, years,
and seasons by using corrected fork-length estimates
from all cranial structures (S-PLUS 2000, Mathsoft,
Inc., Cambridge, MA). To avoid pseudoreplication, we
used presence or absence of cranial elements of a stage
class in a scat particilarily because multiple elements
from the same stage-class within a sample may not be
independent (Hunt et al., 1996). By using presence-
absence data we also avoided the problems associated
with the variability in passage and recovery rates of
different size structures (Tollit et al., 1997). Because
sample sizes were small, juvenile and adolescent wall-
eye pollock stage classes and recruiting adult and adult
Atka mackerel stage classes were combined for seasonal
comparisons among years. Fisher's exact test was used
for comparisons when samples sizes for any stage class
were less than 5 (S-PLUS 2000, Mathsoft, Inc., Cam-
bridge, MA).
We obtained size composition data from commercial
bottom trawls of walleye pollock and Atka mackerel
from the NMFS North Pacific Groundfish Observer Pro-
gram. Data were divided into winter (January-April I
and fall (August-November) seasons and compared
with our seasonal scat data (February-March and
June-September). The percentage of overlap in sizes
of fish caught by the commercial groundfish fishery
with sizes of fish consumed by Steller sea lions was
calculated by comparing size-frequency distributions.
Two-cm size bins were used for the overlap calculation
and Steller sea lion prey-size data were rounded to the
nearest integer to be consistent with the fishery data.
Zeppelin et al.: Sizes of walleye pollock and Atka mackerel consumed by Eumetopias lubatus
513
Results
Regression formulae
A total of 517 pollock and 191 Atka mackerel samples
were used to develop the regression equations of bone
and otolith measurement to fork length. The sample size
and range of fish lengths used for the regressions varied
between species and cranial structures (Table 1). No
clear indications of sample size required for regression
analysis are currently provided in the literature; how-
ever, Owen and Merrick (1994) recommend a minimum
sample size of 30-40. Sample sizes used to develop equa-
tions presented here ranged from 44 to 508.
In general, linear models were used for regression
equations; however, several cranial structures were
best fitted with a quadratic model. For both species,
all structures were strongly related to fork length (r2
range: 0.78-0.99; Table 1). The regressions encompassed
the majority of sizes of bones and otoliths found in Stell-
er sea lion scat samples for this study. However, a small
proportion of walleye pollock bones from scats were
larger than those used to develop the regressions.
Frost and Lowry (1981) developed otolith linear re-
gression equations for walleye pollock from the Bering
Sea using a double-regression approach that produced
an inflection point at 10 mm. We examined the double
regression approach but found a higher degree of corre-
lation using a quadratic regression model. We compared
the results of our model with Frost and Lowry 's (1981)
model and found that estimated fork lengths of walleye
pollock differed less than 2 cm across the length range
in our samples.
Estimation of size of walleye pollock and Atka mackerel
consumed by Steller sea lions in the Bering Sea
and Gulf of Alaska
A total of 714 scats from 39 sites contained 3646 selected
cranial elements from either walleye pollock or Atka
mackerel. Of those, 212 scats contained 666 walleye
pollock cranial elements with a condition grade of either
"good" (ft =236) or "fair" (n = 430). The minimum number
of individual pollock per scat ranged from 1 to 18 with
a mean of 1.6 (SD = 1.7). For Atka mackerel, 379 scats
contained 1685 skeletal elements with condition grade
of either "good" (;?=755) or "fair" (rc=930). The minimum
number of individual Atka mackerel per scat ranged
from 1 to 14 with a mean of 1.9 (SD = 1.6).
The mean fork length of walleye pollock consumed by
Steller sea lions in the Bering Sea and Gulf of Alaska es-
timated from uncorrected otoliths found in scats was 23.7
cm (SD=12.0; « = 88). Application of the DCF increased
the mean estimate to 28.4 cm (SD=14.75; rc=88). The size
distribution estimated from corrected otoliths had three
modes: a major mode around 32 cm and minor modes
around 5 cm and 13 cm (Fig. 2A). Confidence intervals for
all grade-corrected estimates can be found in Table 1.
The mean fork length of walleye pollock estimated
from all seven structures was 39.8% greater than the
mean estimated from otoliths alone. The uncorrected
mean was 33.1 cm. Applying the DCF increased the
mean length of walleye pollock by 18.7% to 39.3 cm
(paired t test, ?665=37.9, P<0.001). Mean grade-corrected
size estimates for cranial structures other than otoliths
ranged from 34.5 cm (PHAR) to 47.2 cm (HYPO) and
95% confidence intervals ranged from 25.2 to 50.6 cm
(Table 2). The condition-specific DCFs increased length
estimates between 6.8% (HYPO) and 28.3% (DENT).
The size distribution estimated from all grade-corrected
structures had three modes: a major mode around 44 cm
and minor modes around 5 cm and 15 cm (Fig. 2A).
The mean fork length of Atka mackerel consumed by
Steller sea lions in the Bering Sea and Gulf of Alas-
ka estimated from uncorrected otoliths was 30.3 cm
(SD=4.0; n=117). Application of the DCF increased the
mean estimate to 34.7 (SD = 4.8; n=U7).
The mean fork length of Atka mackerel estimated
from all structures (30.7 cm; SD = 5.9 cm, corrected
32.3 cm; SD = 5.9 cm, rc=1685, paired t test, f1684=39.1,
P<0.001) was similar to the mean estimated from oto-
liths (6.9% less without a DCF and 1.3% less with a
DCF; Fig. 2B). Mean grade-corrected size estimates
for structures other than otoliths ranged from 26.6 cm
(QUAD) to 34.2 cm (INTE) and 95% confidence inter-
vals ranged from 24.0 cm (DENT) to 35.0 cm (INTE;
Table 2). Use of the condition-specific DCFs increased
length estimates between 2.1% (INTE) and 24.0%
(DENT). Fork length estimates for all structures did
not include PHAR because too few were recovered in
scats in the feeding studies of captive Steller sea lions
to develop a correction factor.
When mean prey size was calculated by using MNI,
the mean corrected and uncorrected size estimate of
both walleye pollock and Atka mackerel differed by less
than 0.2 cm from estimates derived by using all struc-
tures. There was little difference in the standard devia-
tions or distributions when MNI estimates were used
compared with all structures (Table 2). Unsurprisingly,
the use of MNI estimates did substantially reduce the
sample size (336/666 for walleye pollock and 722/1685
for Atka mackerel).
Spatial and temporal variation in size of pollock and
Atka mackerel consumed by Steller sea lions
No statistical difference was found in the proportion of
pollock stage classes among years on summer rookery
sites (P=0.29, ^2 = 4.9, df=3) or winter haul-out sites
(P=0.10; Fisher's exact test). Scats were collected only
on summer haul-out sites during 2000. Although sample
sizes were limited, we found significant differences in
the proportion of pollock stage classes between summer
rookery and haul-out scats (P=0.02; Fisher's exact test)
and between summer and winter haul-out sites (P=0.018;
Fisher's exact test) for year 2000. A greater proportion
of juvenile pollock were found on summer haul-outs
(64%' juveniles, n=ll scats) than on summer rookeries
(9% juveniles, n = 132 scats) or winter haul-out sites (3%
juveniles, n = 69 scats, Fig. 3). No statistical difference
514
Fishery Bulletin 102(3)
Walleye pollock
All structures
MNI
8
6 1
n = 666
No DCFs
DCFs
applied
— i — i — i — i — i — i — i —
0 10 20 30 40 50 60 70 80 0 10 20 30 40 50 60 70 80
Estimated fork length (cm)
B Atka mackerel
All structures
1NI
No DCFs
DCFs
applied
0 10 20 30 40 50 60 70 80 0
i — i — r
10 20 30 40 50 60 70 80
Estimated fork length (cm)
Figure 2
Relative frequency histograms of the estimated fork length of <A> walleye pol-
lock and iB) Atka mackerel consumed by Steller sea lions. Fork lengths were
predicted from cranial structures in good and fair condition. Comparisons
were made on the application of correction factors (DCFs) which account for
digestion and for using minimum number I MNI I estimates as a selection tech-
nique versus using all structures. Otoliths (black bars) are stacked beneath
all other structures (gray bars).
was found in the proportion of stage classes between
summer rookery (9.09% juvenile; 20.45% adolescent:
53.03$ subadult; 65.15'^ adult) and winter haul-out
(2.90% juvenile; 21.74r; adolescent; 57.97% subadult;
46.38% adult) sites for all years combined (P=0.32,
*2=2.3, df=2).
Zeppelin et al.: Sizes of walleye pollock and Atka mackerel consumed by Eumetopias jubatus 515
Table 2
Estimated mean fork length of walleye pollock and Atka mackerel consumed by Steller sea lions based on selected structures
with or without application of condition-specific digestion correction factors (DCFsl. Data sets exclude all structures graded as
heavily digested. Remaining total sample sizes of elements in1) are given along with proportion of grade "good" structures (n«).
For data sets where DCFs were applied, 95'r confidence intervals (95% CI) were estimated by using bootstrap resampling pro-
cedures (Tollit et al., 2004b, this issue).
Species
Structure code
DCF
/!'
Mean FLlcml
SDlcm) Range (cm)
95% CI
Walleye pollock
Atka mackerel
INTE
HYPO
PHAR
ANGU
QUAD
DENT
OTOL
All
INTE
HYPO
ANGU
QUAD
DENT
OTOL
All
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
60
60
38
38
23
23
136
136
134
134
187
187
88
88
666
666
601
601
238
238
488
488
161
161
80
80
117
117
1685
1685
0.45
0.45
0.55
0.55
0.61
0.61
0.40
0.40
0.34
0.34
0.37
0.37
0.03
0.03
0.35
0.35
0.58
0.58
0.42
0.42
0.45
0.45
0.37
0.37
0.28
0.28
0.06
0.06
0.45
0.45
43.7
47.0
44.2
47.2
32.2
34.5
36.1
40.2
35.1
44.5
28.6
36.7
23.7
28.4
33.1
39.3
33.5
34.2
31.1
32.9
30.2
31.8
25.3
26.6
22.5
27.9
30.3
34.7
30.7
32.3
8.0
8.5
7.2
7.8
14.3
14.8
8.4
9.0
12.0
15.3
11.8
15.1
12.0
14.8
12.4
14.3
5.0
5.1
4.8
5.5
4.7
5.1
5.4
5.6
7.7
8.0
4.0
4.8
5.9
5.9
16.7-
16.7-
30.5-
34.9-
9.7-
10.9-
10.6-
10.6-
9.4-
11.9-
3.1-
3.7-
4.6-
4.6-
3.1-
3.7-
19.5-
19.5-
18.8-
19.3-
17.3-
17.3-
14.8-
15.3-
13.0-
17.7-
21.2-
21.2
13.0-
15.3-
59.4
65.9
60.4
62.7
53.1
5.3.1
55.3
60.6
■57.8
■70.8
-57.2
■70.2
46.8
-57.1
60.4
-70.8
46.8
49.6
46.2
48.3
43.0
■46.1
40.6
-41.4
-38.7
■44.1
-40.6
-47.0
■46.9
-49.6
44.9-49.8
44.5-50.6
25.2-44.5
38.5-42.4
38.8-49.6
30.3-42.4
17.0-32.4
35.9-42.4
33.4-35.0
32.4-34.6
31.7-33.3
25.1-28.4
24.0-33.0
33.5-35.8
31.7-33.4
Significant differences were found in the proportion
of Atka mackerel stage classes between 1998 and 1999
on summer rookery sites (P=0.05, x2 =6.0, df=2 ) and
winter haul-out sites (P=0.01, ^ = 9.9, df=2) and be-
tween 1998 and 2000 winter haul-out sites (P=<0.01,
Fisher's exact test). Significant seasonal differences
were found only in 1998 (P=0.03, r = 7.1, df=2) which
may be the result of the small sample size in winter
2000. In summer and winter, annual differences in
size of Atka mackerel consumed by Steller sea lions
corresponded to changes in the length distribution of
Atka mackerel resulting from exceptionally strong year
classes in 1995 and 1998 (Lowe et al., 2001). The 1995
year class is represented as a mode around 30 cm in
1998 (3-year-old fish), 35 cm in 1999 and >40 cm in
2000 (Fig. 4). The 1998 year class is represented most
clearly as 2 year olds (mode 20-25 cm) in summer 2000
(Fig. 4). Strong annual modes found in our data match
those recorded in surveys of Atka mackerel in the Ber-
ing Sea and Gulf of Alaska (Lowe et al., 2001).
For walleye pollock and Atka mackerel there was no
difference in the mean size of fish caught by the com-
mercial fishery among years (P>0.4, one-way ANOVA).
There was a significant difference (P<0.05, one-way
ANOVA) in the size of fish caught between seasons.
This difference is likely due to aggregations of spawning
adult fish caught during the roe fishery. In the winter
there is a 56% overlap between the size of fish caught in
the commercial pollock fishery and those taken by sea
lions and a 54% overlap in the size taken by the Atka
516
Fishery Bulletin 102(3)
25 -
20
15
10 -\
5
0
Winter 1998
ns = 5
n = 8
25
20
15
10
5
0
0 102030405060 7080
25 -
20 -
15 -
10
5
0
Summer 1998 (rookey)
n, = 81
n„ = 226
0 1020304050607080
Winter 1999
ns = 24
n =46
Winter 2000
ns = 40
n =96
0 1020304050607080
0 1020304050607080
Summer 2000 (rookery)
ns = 24
a, = 81
Summer 2000 (haul-out)
ns= 1 1
n„ = 77
l
j
I l! I. .
0 1020304050607080
0 1020304050607080
0 1020304050607080
Estimated fork length (cm)
Figure 3
Relative frequency histograms of the estimated fork length of walleye pollock consumed by Steller sea lions
across seasons and years for rookeries and haul-outs. Fork lengths are predicted from corrected cranial struc-
tures in good and fair condition. Sample sizes for cranial elements inel and scats (ra ) are provided. All winter
sites are considered haul-out sites.
Winter 1999
ns = 48
n =218
Winter 2000
ns = 13
n„ = 32
-
1
" 1
0 10 20 30 40 50
Summer 1998
_ ns = 201
ne = 965
0 10 20 30 40 50
Summer 1999
ns = 44
n =193
0 10 20 30 40 50
Summer 2000
n, = 35
n . = 142 J
0 10 20 30 40 50
0 10 20 30 40 50
Estimated fork length (cm)
0 10 20 30 40 50
Figure 4
Relative frequency histograms of the estimated fork length of Atka mackerel of
consumed by Steller sea lions by season and year. Fork lengths are predicted from
corrected cranial structures in good and fair condition. Sample sizes for cranial
elements (ne) and scats (ns) are provided. All summer sites are rookeries and winter
sites are haul-out sites.
Zeppelin et al.: Sizes of walleye pollock and Atka mackerel consumed by Eumetopias jubatus
517
12-1
A Walleye pollock
Overlap 68%
10-
SSL, n=666
■ trawl. n=92133
8-
6 -
4 -
ll
2-
I III I
ll..
n -
10
20
30
40
- 25
20
B Atka mackerel
50 60 70
Overlap 53°o
80
15
10
SSL. n=1685
■ trawl. n=92877
ill
.III
1.
10 20 30
Estimated fork length (cm)
40
50
Figure 5
Relative frequency histograms of the estimated fork length of wall-
eye pollock and Atka mackerel consumed by Steller sea lions (SSL)
compared with relative frequency histograms offish caught by the
walleye pollock and Atka mackerel commercial trawl fishery.
mackerel fishery. In the summer the overlap in size of
fish consumed by sea lions and the size of fish caught
in the pollock fishery is 67% and there is a 51% overlap
in the size of fish caught in the Atka mackerel fishery.
When seasonal data were pooled, overlap between the
size of fish caught in the commercial fishery and the
size of fish consumed by sea lions was 68% for walleye
pollock (Fig. 5A) and 53% for Atka mackerel (Fig. 5B).
Discussion
Regression formulae
Regressions of cranial structure measurement on fish
fork length with the use of multiple structures was
an effective tool for estimating size of fish consumed
by Steller sea lions. Sample sizes of measurable prey
remains from scats were enhanced by using a number
of cranial structures in addition to otoliths. Body size
estimates of only 13.2% of the pollock and 6.9% of the
Atka mackerel prey in this study were based on otoliths
alone. Fork-length estimates can be considered accurate
regardless of which structure was used in the estimate
because all r2 values were high (range: 0.78-0.99). Like-
wise errors associated with the application of DCFs
were consistent across structures (Tollit et al., 2004b,
this issue). Confidence intervals around size estimates
generally overlapped across structures; however, it was
not surprising that different structures yielded slightly
different mean sizes because different bones can origi-
nate from different scats.
The use of multiple cranial structures may also re-
duce bias resulting from variability in recovery and
passage rates of structures from different species or
sizes of fish (Pierce and Boyle, 1991; Browne et al.,
518
Fishery Bulletin 102(3)
2002; Tollit et al., 2003). Even after applying a DCF,
the estimated mean size of walleye pollock based on
otoliths was 10.9 cm smaller than the mean size esti-
mated by using all cranial structures. Because walleye
pollock otoliths are relatively large and have a different
composition than other cranial structures, the larger
otoliths may be regurgitated, fully digested, or crushed
by rocks in the stomach and not pass through in scat as
readily as smaller otoliths or other cranial structures,
thereby reducing their occurrence in scat and use in
generating prey-size estimates. Atka mackerel otoliths
are much smaller at older ages in relation to walleye
pollock, which may explain why the size of prey esti-
mated from otoliths was similar to the size estimated
from other cranial structures.
The use of DCFs for all structures, including otoliths,
to account for erosion increased mean size estimates
for both walleye pollock (33.1 vs. 39.3 cm FL) and Atka
mackerel (30.7 vs. 32.3 cm FLi. The relatively small
increase in the corrected size of Atka mackerel re-
flects that the structures from this species were found
in better condition than those from pollock (Table 2),
as well as that correction factors were found to be
species-, structure-, and condition-specific (Tollit et
al., 2004b, this issue). Overall, our results emphasize
the importance of using appropriate condition-specific
DCFs. Other studies with captive sea lions have also
demonstrated that grade-specific DCFs can reduce sys-
tematic error and increase precision of body mass es-
timates (Tollit et al. 1997). For walleye pollock, there
was no significant difference in the degree of erosion
across the three size ranges for each structure within
each condition category (Tollit et al., 2004b, this issue).
We assume the DCFs can be used for fish outside of
this size range because the relative shape, structure,
and proportion of the morphological features are con-
sistent for both smaller and larger fish (Tollit et al.,
2004b, this issue). Further research is necessary to
test whether there are differences across the size range
for Atka mackerel.
Size of walleye pollock and Atka mackerel consumed by
Steller sea lions in the Bering Sea and Gulf of Alaska
In general, Steller sea lions on summer rookery and
winter haul-out sites consumed primarily subadult and
adult-size walleye pollock and Atka mackerel year-round
in 1998-2000. Steller sea lions typically forage near
shore, in shallow water (<50 m) and at night (Raura-
Suryan et al., 2002; Loughlin et al., 2003). Likewise,
adult walleye pollock migrate vertically to shallower
depths during the night (Smith, 1981). Adult-size Atka
mackerel also are commonly found in nearshore coastal
areas during their spawning season (Zolotov, 1993).
Juvenile walleye pollock were found in relatively high
numbers only in scats collected on summer haul-out
sites. Scats collected from summer haul-out sites likely
represent a larger proportion of juvenile Steller sea li-
ons than those collected on summer rookery or winter
haul-out sites. Previous studies indicate t hat juvenile
sea lions (<4 years old) consume smaller walleye pollock
than adult sea lions (Pitcher, 1981; Frost and Lowry,
1986; Merrick and Calkins, 1996). Juvenile walleye pol-
lock are often found at shallow depths in bays and near
shore habitat (Smith, 1981). Likewise, Loughlin et al.
(2003) reported that juvenile Steller sea lions are typi-
cally shallow divers and frequently make short range
foraging trips (<15 km). Additional scat collections on
summer haul-out sites are necessary to determine more
conclusively prey-size selectivity for juvenile Steller sea
lions.
Annual changes in the size-frequency distribution of
Atka mackerel consumed by Steller sea lions followed
changes in the size distribution of Atka mackerel re-
sulting from exceptionally strong year classes. Merrick
and Calkins (1996) also showed that the size of prey
consumed by Steller sea lions can reflect the size dis-
tribution of the fish population. From the mid-1990s on,
only 1999 was a strong recruitment year for walleye
pollock in the Gulf of Alaska (Dorn et al., 2001), but we
did not find a significantly greater proportion of juvenile
fish eaten by Steller sea lions in 2000 than in 1999 or
1998 perhaps because sufficient numbers of larger size
fish were available in regions where walleye pollock
were consumed.
Historical studies of Steller sea lion prey size have
primarily been based on measurements of walleye pol-
lock otoliths found in stomach samples but often with-
out application of correction factors for erosion (Pitcher,
1981; Merrick and Calkins, 1996; Calkins. 1998). Prey-
size estimates based on stomach contents will likely
differ from estimates derived from scats because of
differences in digestion rates and breakage ( Jobling and
Breiby, 1986 i. However, results of studies examining
the variability in prey size with sample type are vari-
able. Sinclair et al. (1996) suggested that in northern
fur seals (Callorhinus ursinus), another otariid, small
otoliths tend to flush through the digestive system more
quickly than larger ones, resulting in a possible bias in
scats towards smaller otoliths. In contrast, experiments
with captive sea lions have shown that smaller otoliths
are recovered in lower relative frequencies than are
larger ones (Tollit et al.. 1997). Frost and Lowry (1980)
found no significant difference between the size of oto-
liths obtained from stomach and intestines of ribbon
seals. Overall, we believe useful comparisons of prey
size consumed by Steller sea lions can be made between
our study and earlier studies.
Steller sea lions have been reported to consume a
wide size range of walleye pollock. However, in most
prior studies a larger proportion of juvenile fish were
found than what we estimated from scats. Otoliths from
stomach samples collected from 1975 to 1978 in the
Gulf of Alaska contained primarily juvenile age pollock
(mean FL=29.8cm; SD= 11.6; Pitcher, 1981). Undigested
otoliths from stomach samples collected between 1975
and 1981 in the Bering Sea also contained mostly juve-
nile fish (mean FL=29.3 cm) but had a distinct mode of
adult-size pollock (48 cm FL: Frost and Lowry. 1986).
Likewise, 43 stomach samples collected between 1985
Zeppelin et al.: Sizes of walleye pollock and Atka mackerel consumed by Eumetopias jubatus
519
and 1986 in the central Gulf of Alaska contained pri-
marily juveniles (mean FL=25.4 cm; SD = 12.4) and had
a weak mode of adult-size fish (39-43 cm; Merrick and
Calkins, 1996; Calkins and Goodwin1). Mostly adult-size
fish were found in stomachs recovered from Steller sea
lions caught in trawl nets in the central Gulf of Alaska
11983-84; Loughlin and Nelson, 1986) and in stomach
samples collected from 1994 to 1995 in Japanese waters
(Goto and Shimazaki, 1998). However, in both these
studies the samples of prey size may have been biased
by the selectivity of the fishing gear for larger fish.
Using identical methods to those of our study, Tollit
et al. (2004a, this issue) estimated the size of wall-
eye pollock consumed by the eastern stock of Steller
sea lions between 1994 and 1999. The average size of
walleye pollock consumed, estimated from all grade-
corrected structures (mean=42.4 cm; SD = 11.6), was
similar to the average size found in our study of the
western stock of Steller sea lions. Furthermore, Tollit
et al. (2004a, this issue) also found a greater occur-
rence of adult pollock in scats collected on rookery sites
than from scats collected on haul-out sites. However,
Steller sea lions from the western stock consumed a
greater proportion of juvenile and adolescent fish and
less adult fish than those from the eastern stock dur-
ing summer (June-July) and similar-size fish were
consumed on haul-out sites in winter (March) in both
regions. Neither study indicated the high occurrence
of juvenile walleye pollock reported in the 1970s and
1980s. The greater occurrence of juvenile walleye pol-
lock in historical studies may be a result of prey avail-
ability or differences in sampling methods.
By examining the relative size-frequency distributions
of prey selected by Steller sea lions and those taken
in the commercial trawl fishery, we found considerable
overlap (689r walleye pollock and 53% Atka mackerel).
Likewise, high levels of potential overlap in size were
found between walleye pollock selected by Steller sea
lions from the eastern stock and caught by the small
commercial fishery bordering Southeast Alaska (Tollit
et al., 2004a, this issue). The extent of overlap through-
out the range of Steller sea lions between the size of
prey consumed by sea lions and the size of fish targeted
and taken by the pollock and Atka mackerel trawl fish-
eries could result in competition between fisheries and
foraging sea lions if resources are limited.
Acknowledgments
Fish specimens for the regression equations were pro-
vided by the National Marine Fisheries Service, the
University of Victoria, and the University of British
Columbia bone reference collections. Fish remains were
identified by Pacific Identifications, Victoria, BC. We
thank J. Laake, A. York, and R. Joy for statistical advice,
K. Chumbley, E. Sinclair, and S. Crockford for help in
initiating the study, A. Browne and M. Wilson for wall-
eye pollock otolith data, and S. Heaslip for graphics and
laboratory assistance. Reviews by E. Sinclair, S. Melin,
W. Walker, B. Robson, and three anonymous reviewers
greatly improved this manuscript.
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522
Abstract— Lengths of walleye pollock
i Theragra chalcogramma I consumed
by Steller sea lions (Eumetopias
jubatus) were estimated by using
allometric regressions applied to
seven diagnostic cranial structures
recovered from 531 scats collected
in Southeast Alaska between 1994
and 1999. Only elements in good and
fair condition were selected. Selected
structural measurements were cor-
rected for loss of size due to erosion
by using experimentally derived
condition-specific digestion correc-
tion factors. Correcting for digestion
increased the estimated length of
fish consumed by 23% , and the aver-
age mass offish consumed by 88%.
Mean corrected fork length (FLl of
pollock consumed was 42.4 ±11.6 cm
(range = 10. 0-78.1 cm, n=909). Adult
pollock (FL>45.0 cm) occurred more
frequently in scats collected from
rookeries along the open ocean coast-
line of Southeast Alaska during June
and July (74% adults, mean FL = 48.4
cm l than they did in scats from haul-
outs located in inside waters between
October and May (51% adults, mean
FL = 38.4 cm). Overall, the contribu-
tion of juvenile pollock (<20 cm) to
the sea lion diet was insignificant;
whereas adults contributed 44% to
the diet by number and 74% by mass.
On average, larger pollock were eaten
in summer at rookeries throughout
Southeast Alaska than at rookeries
in the Gulf of Alaska and the Bering
Sea. Overall it appears that Steller
sea lions are capable of consuming
a wide size range of pollock, and the
bulk offish fall between 20 and 60 cm.
The use of cranial hard parts other
than otoliths and the application of
digestion correction factors are fun-
damental to correctly estimating the
sizes of prey consumed by sea lions
and determining the extent that these
sizes overlap with the sizes of pollock
caught by commercial fisheries.
Sizes of walleye pollock (Theragra chalcogramma)
consumed by the eastern stock of Steller sea lions
(Eumetopias jubatus) in Southeast Alaska from
1994 to 1999
Dominic J. Tollit
Susan G. Heaslip
Andrew W. Trites
Marine Mammal Research Unit, Fisheries Centre
University ol British Columbia
Room 18, Hut B-3, 6248 Biological Sciences Road
Vancouver, British Columbia, Canada, V6T 1Z4
E-mail (for D J Tollit). tollitia'zoology ubc ca
Manuscript submitted 28 April 2003
to Scientific Editor's Office.
Manuscript approved for publication
25 March 2004 by the Scientific Editor.
Fish. Bull. 102:522-532(2004).
The dramatic decline of the western
population of Steller sea lions (Eume-
topias jubatus) in the 1980s (Loughlin
et al., 1992; Trites and Larkin, 1996)
prompted a number of studies to deter-
mine what they eat and the extent of
overlap of the fish consumed by Steller
sea lions and fish caught by commer-
cial fisheries. The eastern population
of sea lions (east of longitude 144°)
located mainly in Southeast Alaska
and British Columbia gradually
increased as the western population
declined (e.g.. Calkins et al., 1999),
permitting insightful comparative
studies to be undertaken (e.g., Mer-
rick et al., 1995; Milette and Trites,
2003). Possible explanations for the
different population trends include
ocean climate, competition with fish-
eries, predation, and the amount or
the sizes of pollock in the diets of sea
lions in the two regions (Loughlin
and York, 2000; Benson and Trites,
2002; NRC, 2003; Trites and Don-
nelly, 2003; Calkins and Goodwin1;
Loughlin and Merrick-).
Reliable estimates of prey size are
important not only to investigate prey
selectivity and the extent of overlap
in size of prey with size of the same
species caught by commercial fisher-
ies and by other marine piscivores
but are also vital for accurately as-
sessing prey numbers, biomass, and
total consumption (Beverton, 1985;
Ringrose, 1993; Laake et al., 2002).
One means of estimating prey size is
to measure hard parts recovered from
fecal remains and to apply allometric
regressions relating fork length to
the size of otoliths (Frost and Lowry,
1981) and other bones (Zeppelin et al.,
2004, this issue). However, the extent
of digestion incurred by both otoliths
and bones as they pass through the
digestive tract must be accounted for
to ensure that prey size is not un-
derestimated (Tollit et al., 2004, this
issue). Application of these two steps
is integral to correctly estimate the
size of prey consumed by Steller sea
lions and other pinnipeds.
The goal of our study was to esti-
mate the size of walleye pollock (Ther-
agra chalcogramma) consumed by
Steller sea lions in Southeast Alaska
between 1994 and 1999 by using
new methods outlined by Tollit et al.
(2004, this issue) and Zeppelin et al.
(2004, this issue). Previous size esti-
mates for this region of Alaska are
based on the analysis of only eight
stomachs collected in 1986 i Calkins
1 Calkins, D. G., and E. Goodwin. 1988.
Unpubl. report. Investigation of the
declining sea lion population in the Gulf
of Alaska, 76 p. Alaska Department
of Fish and Game, 333 Raspberry Rd,
Anchorage, AK 99518.
2 Loughlin, T. R., and R.L. Merrick.
1989. Comparison of commercial har-
vest of walleye pollock and northern sea
lion abundance in the Bering Sea and
Gulf of Alaska. In Proceedings of the
international symposium on the biology
and management of w-alleye pollock.
Nov. 14-16, 1988, Anchorage, AK, p.
679-700. Alaska Sua Grant KVp Sil-
01. LIniv. Alaska Fairbanks, Fairbanks.
AK
To Hit et al.: Sizes of walleye pollock consumed by Eumetopias /ubatus
523
58 N
56
A
50
Petersburg
" 14-
15
fh. r
50
Kilometers
Pollock trawl
19 ' Dixon ,lsherV
Entrance
138 W
134
130
Figure t
Location of Steller sea lion (Eumetopias jubatus) haul-outs and rookeries visited during
1994-99 to collect scats containing pollock hard remains. Symbols: haul-outs in inside
waters (•), haul-outs in outside waters (©), haul-outs where scats were not collected or
sites at which no pollock hard remains were found (O), rookeries ■ and cities (*i.
and Goodwin1). We sought to compare the sizes of pol-
lock consumed in the 1990s with these earlier samples,
as well as with the sizes consumed by the declining
population of sea lions in the Gulf of Alaska and Ber-
ing Sea during the 1970s and 1980s (e.g., Pitcher, 1981;
Merrick and Calkins, 1996) and between 1998 and 2000
(Zeppelin et al., 2004, this issue). We also wanted to
evaluate the use of digestion correction factors (DCFs)
and skeletal structures other than otoliths to estimate
prey size, and to compare the different size estimates
for fish consumed by sea lions in Southeast Alaska
with sizes of fish caught by a nearby commercial trawl
fishery.
Materials and methods
Estimating sizes of pollock consumed
Scats that contained pollock hard remains were collected
from four rookeries and 16 haul-outs from both inside
and outside waters of Southeast Alaska between 1994
and 1999 (Fig. 1 and Table 1). Scats from three haul-
outs and four rookeries in outside waters were collected
from May through October 1994-99, but most were
collected from June and July. Scats from inside waters
were collected at 13 haul-outs located in the straits
and sounds between Juneau and Petersburg, Alaska
(56.8-58.6°N, 132. 8-134. 9°W) (Fig. 1). The majority of
these "inside" scats were collected from Frederick Sound
(Fig. 1) between October 1995 and February 1997. Most
were collected in the winter and spring, but some were
collected in the summer of 1999 (Trites et al.3). In gen-
eral, the haul-out sites visited to collect scats were those
with relatively high numbers of animals across South-
east Alaska (Calkins et al., 1999; Sease et al., 2001).
Scats were washed and sieved (0.5 mm) and hard
remains were identified by Pacific IDentifications Inc.
(Univ. of Victoria, Victoria, B.C.). Seven commonly
3 Trites, A. W., D. G. Calkins, and A. J. Winship. 2003. Unpubl.
data. Marine Mammal Research Unit, Fisheries Centre,
University of British Columbia, Room 18, Hut B-3. 6248 Bio-
logical Sciences Rd., Vancouver, B.C., Canada, V6T 1Z4.
524
Fishery Bulletin 102(3)
Table 1
Steller sea lion scat collection sites in Southeast Alaska, as illustrated in Figure 1, giving details
of the type (HO=haul-outl. fish
element sample size
irir), and the estimated corrected mean fork length Imean FL, cm)
of walleye pollock
based on seven cranial
structures found in
scats at each site.
Region
Site no.
Site name Type
"/
Mean FL
SD
Inside waters
1
Benjamin Island HO
11
39.7
13.9
2
Dorothy Island HO
3
38.6
13.6
3
Circle Point HO
31
45.1
13.7
4
Point League HO
37
42.9
9.9
5
Sunset Point HO
196
37.4
10.3
6
Sail Island HO
36
35.5
10.0
7a
W Brother Island HO
8
40.9
14.7
7b
SW Brother Island HO
152
37.1
9.9
8
Turnabout Island HO
34
47.8
11.0
9
Yasha Island HO
19
44.8
5.3
10
Sukoi Islets HO
14
26.9
7.8
11
Horn Cliffs HO
19
44.3
12.7
12
Liesnoi Island HO
7
31.8
10.2
Outside waters
13
Cape Cross HO
7
45.3
3.0
14
Timbered Island HO
5
39.3
8.7
15
Point Addington HO
1
53.5
—
16
Graves Rock Rookery
49
42.9
7.7
17
White Sisters Rookery
33
43.4
9.6
18
Hazy Islands Rookery
54
45.4
8.7
19
Forrester Islands Rookery
193
51.4
10.0
occurring, robust, and diagnostic pollock structures
were removed from all scats containing pollock (see
Tollit et al., 2004, this issue). All were from the cra-
nium region (see Zeppelin et al., 2004, this issue) and
included the sagittal otolith (OTO), as well as the inter-
hyal (INTE), hypobranchial 3 (HYPO), pharyngobran-
chial 2 (PHAR), angular (ANGU), quadrate (QUAD),
and the dentary (DENT). Each individual fish element
was assigned one of three condition categories (good,
fair, or poor) and was measured three times (±0.01 mm)
at a specific location to calculate a mean estimate (see
Tollit et al., 2004, this issue).
Fork lengths of pollock eaten by Steller sea lions in
Southeast Alaska were first estimated by applying al-
lometric regressions (Zeppelin et al., 2004, this issue)
to otolith lengths (OTOL) without correcting for par-
tial digestion (see Pitcher, 1981; Merrick and Calkins,
1996). We also measured and substituted otolith width
(OTOW) when otoliths were broken lengthwise. We then
applied appropriate DCFs and regression formulae to
otoliths assigned in good and fair condition (Tollit et
al., 2004, this issue). Finally, we applied allometric
regressions (Zeppelin et al., 2004, this issue) to all ele-
ments of the remaining six cranial structures (bones)
assigned to good or fair condition categories to provide
estimates of fish size across structures both with and
without applying the appropriate DCFs (Tollit et al.,
2004, this issue). Structures in poor condition were
excluded because of large intraspecific size variation
noted from feeding experiments with captive sea lions
(see also Sinclair et al.. 1994; Tollit et al., 1997; Tollit
et al., 2004, this issue).
To incorporate the major sources of error in our
method, we calculated confidence intervals (95^r) for
fork-length estimates. First, we applied a random
bootstrapped regression equation, followed by a boot-
strapped correction factor applicable to each selected
structure (see Tollit et al., 2004, this issue). For the
five structures (INTE, HYPO. PHAR, ANGU, and OTO)
in good condition for which Tollit et al. (this issue)
recommended a DCF of 1.0 (no correction), we drew
bootstrapped values from a discrete declining triangu-
lar probability distribution (hj ranging from 1.0 to 1.05
(to simulate a limited degree of digestion). Finally, we
bootstrapped individual scats at random, by selecting
n scats with replacement from the original sample size
n (to account for resampling variability across scats)
and included only selected elements within those ran-
domly bootstrapped scats. Bootstrap randomizations for
these steps were done 1000 times and 959! confidence
intervals were taken as the 25th and 975,h values of the
sorted bootstrapped values.
Finally, consideration was also given to whether
an individual fish might be represented by different
structures within a single scat. We therefore compared
length estimates using all structures with those esti-
To Hit et al.: Sizes of walleye pollock consumed by Eumetopias jubatus
525
mated with the minimum number of individuals (MNI)
technique (Ringrose, 1993; Browne et al., 2002). This
technique is used to select structures within each scat
that preclude pseudoreplication or double counting of
fish. Within each scat, the structure with the great-
est MNI was selected, and right-sided structures were
selected over left-sided structures if both sides were
found in equal number because right-sided structures
are used in regression formulae. If two structures had
the same MNI estimate, then selection was made on
the structure with the larger regression determination
coefficient, r2 (OTO-W>OTO-L>QUAD>DENT>HYPO>
INTER>ANGU>PHAR ).
Geographical and temporal variation in sizes of
prey consumed
All elements from the seven cranial structures in good or
fair condition were used to compare size of pollock con-
sumed by Steller sea lions in Southeast Alaska between
regions (inside haul-outs versus outside rookeries), across
years and across rookeries (with rookery data collected
in June and July), and across months (with data col-
lected from inside haul-outs). Biologically meaningful
differences in FL of pollock were assessed by grouping
corrected lengths into stage-class categories (juvenile
or 1-year-old fish FL<20 cm; adolescent 20<FL<34 cm;
subadult 34<FL<45 cm; and adult FL>45 cm) (Smith,
1981; Walline, 1983; Dorn et al., 2001). Adults were
considered to be mature fish >5 years old and targeted
by fisheries (Smith, 1981). Subadults were likely 3 or
4 years old, of which only a proportion had matured or
were targeted by the fishery. To avoid the possibility of
pseudoreplication in our chi-squared comparisons, we
used only the presence or absence of structures of each
stage class in a scat because individual fish eaten by a
sea lion may have come from an age-specific school and
were therefore not independent (Hunt et al., 1996). Pres-
ence-absence data was chosen over MNI data because
the former greatly reduces potential concerns regarding
size-dependent recovery of cranial structures (Tollit et
al., 1997). With the exception of our regional comparison,
data from juvenile and adolescent stage-classes were
pooled because of the low sample sizes of juvenile fish. A
Fisher's exact test was used as an alternative test to chi-
square comparisons when counts for a stage-class group-
ing were <5 (S-PLUS 2000, Mathsoft Inc., Seattle, WA).
Overlap of prey size with size of fish caught by fisheries
To assess the impact of using the new methods described
and to compare the size of pollock consumed by sea lions
with the size of pollock typically caught by fisheries, we
obtained randomly subsampled size-frequency landing
data from the Canadian commercial pollock fishery in
Dixon Entrance (1993-1999) (Saunders4). This area is
4 Saunders, M. 2002. Unpubl. data. Fisheries and Oceans
Canada, 3190 Hammond Bay Road, Nanaimo, B.C., Canada,
V9T 6N7.
115-135 km SE of the Forrester Island rookery on the
southern border of Southeast Alaska (Fig. 1).
Results
Sizes of pollock consumed
The traditional method of estimating prey size from
otoliths alone was not satisfactory because most otoliths
were in poor condition (86%, ra=247) or were broken
lengthwise (>89%) (or were both broken and in poor
condition). Cranial bones, on the other hand, occurred
in higher numbers than otoliths and were therefore more
useful for estimating prey size (Table 2).
Sixty-one percent of scats (1215 of 1987) collected
from Southeast Alaska (1994-99) contained pollock
remains, with an average MNI of 1.57 ±1.66 individual
pollock per scat (range: 1-37 individuals). Many scats
contained hard parts that were not useful for estimat-
ing prey size (e.g., gill rakers), leaving 531 scats (26%)
with measurable selected structures. Of these, 303 scats
contained 1746 elements in good (n = 225), fair (n = 684).
and poor condition (« = 837).
Applying digestion correction factors had a consider-
able effect on the estimated length and mass of fish
consumed, and on the proportion that were deemed
to be adults (Fig. 2). The estimated lengths of pollock
calculated from all structures graded in good or fair
condition (without accounting for digestion) was 34.4
±9.7 cm (ra=909, modal range: 32-40) (Table 2, Fig. 2).
Lengths increased by 23% on average when appropri-
ate DCFs were applied to each structure to account for
the observed degree of digestion (mean FL = 42.4 ±11.6
cm, modal range: 44-52, 95% CI = 41. 0-43.9) (paired
t-test, i908=67.1, P<0.001). A DCF of 1.0 (no correction
required to account for digestion) was applied to 62 ele-
ments in good condition, resulting in a mean fork length
of 39.6 ±11.9 cm estimated from those bones.
The size-frequency distribution of pollock consumed by
sea lions also varied significantly following the applica-
tion of DCFs (Kolmogorov-Smirnov, KS = 176.2, P<0.001)
and led to an increase in the proportion of fish thought
to have been adult (>45 cm FL) from 16% to 44%. This
result in turn reduced the proportion of fish thought
to have been subadults (29%), adolescents (25%), and
juveniles (<2%, <20 cm FL) (Fig. 2). The size range of
pollock eaten ranged widely regardless of whether DCFs
were applied (10-78 cm) or not (10-64 cm). When we
calculated fork lengths using only elements selected
according to MNI criteria, the means increased by just
0.5 cm for corrected and by just 0.3 cm for uncorrected
lengths, with near identical standard deviations and
distributions (Fig. 2) (Kolmogorov-Smirnov, uncorrected
KS = 0.33, P=0.89, corrected KS = 0.032, P=0.91).
The use of all otoliths regardless of digestion state
resulted in a mean fork length that was only about
half of that derived by using all structures corrected
for digestion (Table 2). Excluding otoliths in poor con-
dition significantly reduced sample size (Table 2) but
526
Fishery Bulletin 102(3)
Fable 2
Estimated mean
fork length
mean
FL, cmi of
walleye pollock consumed by Stellei
sea lions.
Values were determined by using
selected
cranial
structui
es w
ith or
without the application
of condition-specific di
gestion
correction factors
DCFs
. Data sets
exclude
all struc
ures gr
aded
in poor condition
(with the exception of data sets marked w
th
an asterisk l. Fi
ih element sample
sizes (n,-
are given along
with
propo
'tion of elements assign*
d condition category good ing).
When DCFs were applied
95ri confi-
dence intervals (95<~t CI i
were
estimated by using bootstrap
resampling I see "Materials and methods").
Structure code
DCF
n
ng
Mean FL
SD
Range
95% CI
INTE
No
37
0.35
44.0
8.0
28.0-54.5
Yes
37
0.35
48.0
9.3
31.9-62.2
45.0-52.2
HYPO
No
47
0.19
35.3
8.9
19.0-52.0
—
Yes
47
0.19
39.8
10.1
19.0-60.4
36.7-43.6
PHAR
No
20
0.25
38.1
8.5
20.4-50.3
—
Yes
20
0.25
43.7
9.5
20.4-56.1
39.9-48.4
ANGU
No
207
0.16
34.0
10.2
10.0-62.8
—
Yes
207
0.16
39.4
11.4
10.0-63.2
37.4-41.5
QUAD
No
238
0.36
33.1
10.4
14.0-63.8
—
Yes
238
0.36
41.9
13.2
17.3-78.1
39.5-44.7
DENT
No
326
0.24
34.9
8.1
11.0-63.0
—
Yes
326
0.24
45.1
9.8
14.7-75.3
43.3-46.8
OTOL
No
10
0.10
30.6
13.8
14.2-54.8
—
Yes
10
0.10
36.6
17.6
16.7-67.2
27.0-51.1
OTOL or OTOW
No
34
0.03
27.2
16.1
10.8-54.8
—
Yes
34
0.03
33.7
12.8
13.3-67.2
29.5-39.5
All structures
No
909
0.25
34.4
9.7
9.8-63.8
—
Yes
909
0.25
42.4
11.6
10.0-78.1
41.0-43.9
OTOL*
No
27
0.04
23.3
11.9
7.9-54.8
—
OTOL or OTOW"
No
247
<0.01
20.2
9.7
5.0-58.0
—
increased our estimate of fork length by approximately
.'!.'!'< Applying grade-specific DCFs increased these es-
timates by another 19% (to 36.6 cm) for otolith length
and by 24% (to 33.7 cm) for a combination of otolith
length and width (Table 2). All six remaining struc-
tures in good or fair condition provided larger corrected
mean length estimates than did otoliths alone, but 95%
confidence intervals derived from otoliths did overlap
with other structures (Table 2). The smaller estimate
provided by otoliths may reflect that >83% of grade
corrected otoliths (n = 34) came from the inside haul-
out sites, where animals seem to eat smaller fish (see
following section). On the other hand, large pollock
otoliths were observed to have been regurgitated in
feeding studies on captive sea lions and also may be
more easily crushed by rocks often found in the stom-
achs of Steller sea lions (Tollit et ah, 2003). Regres-
sion formulae used in our study to predict pollock FL
from otolith length were similar to those of Frost and
Lowry (1981) for juvenile fish (<10 mm otolith length)
but led to smaller fish size estimates (—1—1.7 cm) over
the range of 30-50 cm.
The lengths of the biggest fish (corrected mean
FL = 48.0 cm) were estimated from measurements of
INTE (Table 2), the structure with the lowest DCF.
Dentary bones (the most abundant structure recov-
ered) predicted mean (Table 2) and modes (FL 44-
50 cm) similar to those predicted from all structures.
Applying DCFs increased our length estimates by be-
tween 9% (INTE) and 29% (DENT) (paired r- tests, all
P<0.001). Overall, corrected fork length estimates from
elements in good condition were similar to those from
elements in fair condition (Mann-Whitney U, P=0.47),
but multiple comparisons indicated a significant differ-
ence (P<0.05> between condition categories for INTE
and DENT (lengths were estimated to be longer from
elements graded in fair condition).
Repeat measurements of individual elements were
all within 0.04 mm of the mean, and 88.9-99.5% were
within 0.02 mm. The highest variability was associated
with ANGU, HYPO, and PHAR with 88.9%, 91.7%, and
94.9% of their respective measurements falling within
0.02 mm. A 0.02-mm measurement difference corre-
sponded to only a 0.1-0.2 cm difference in fish length,
depending on the structure used.
Small differences in estimates of fork lengths can
have large effects on estimated body mass (given the
exponential mass-length relationship, see Tollit et al.,
2004, this issue) and can increase the mean mass of
fish by more than sixfold depending on which method
is used to estimate body length (all otoliths and no cor-
rection versus condition-corrected structures). The ap-
"To Hit et al.: Sizes of walleye pollock consumed by Eumetopias jubatus
527
All structures MNI
8 ■
■ Otoliths n
d Other
bones r r
n = 909
I
n = 478
6 "
n.
lU
4 ■
ill
J
No DCFs
Percent relative frequency
^ a> 03 o i\3
_A
.. . Irun
f
^n
Ii
k
n- f
Ik
DCFs
applied
2 "
o ■
__jLi...
kn>,„
r, rlR. L II
II k„
h — r~ i i i i i i i i i i
0 10 20 30 40 50 60 70 80 0 10 20 30 40 50 60 70 80
Estimated fork length (cm)
Figure 2
Relative frequency histograms of the estimated fork length of walleye pollock (Theragra
ehalcogramma) predicted from seven cranial structures in good and fair condition.
Otoliths (black bars) are stacked beneath all other selected structures (gray barsl.
Comparisons were made with the application of digestion correction factors (DCFs)
to take account of partial digestion and with the use of a selection technique (MNI)
versus using all structures present in scats.
plication of our DCFs to all structures in good and fair
condition increased the estimated mean mass of pollock
consumed by 88% (from a mean of 388 g to 731 g).
Thus, although we estimate that 44% of the number of
pollock eaten by Steller sea lions were adults, based on
length, their contribution, based on weight, increased
to 74%. In contrast, the contribution of juvenile fish (in
terms of mass) dropped to <0.1% (compared to <2% by
number).
Geographical and temporal variation in sizes of
pollock consumed
More pollock elements in good and fair condition were
recovered from inside haul-outs (?? = 567) than from sites
on the outside coastline (n = 342) (Table 1). Upon investi-
gation, we found the size of pollock consumed by Steller
sea lions varied over time and across regions (Fig. 3).
In particular, the frequency of occurrence of pollock
stage classes differed significantly in the scats of sea
lions resting at rookeries on the outside coastline of
Southeast Alaska in summer (mean FL=48.4 cm, n = 328,
modal range: 44-50 cm, 95% CI = 46.5-50.2, ns=126
scats) compared to those collected between October and
May at haul-outs in the waters of the inside passages
(mean FL = 38.4 cm, /; = 499, modal range; 30-34 cm,
95% CI=36.9-40.3, ns=168 scats) (^=45. 2, P<0.001).
Scats from these inside haul-outs contained a greater
diversity of stage classes, and there was an equal prob-
ability of any given scat containing adults (51.2%), sub-
adults (47.6%). and adolescents (53.0%), but a far less
probability of containing juveniles (6.5%). In contrast,
the pollock found in scats from the outside rookeries
contained mostly adults (73.8%) and fewer occurrences
of the remaining three stage classes (38.1%, 9.5%, and
3.2%. respectively). Notably, the stage-class compar-
ison of summer 1999 with scats from inside versus
outside waters was not significant (Fishers exact test,
P=0.11).
Similar proportions of each pollock stage class were
found in scats collected between years (Forrester,
Fisher's exact test, P=0.54; Hazy, Fisher's exact test,
P=0.16), and between rookeries (1994 only, Fisher's ex-
act test, P=0.57; all years, Fisher's exact test, P=0.22).
Scats from inside haul-outs collected in spring 1996
contained comparatively smaller fish than in other
months and years examined (Fig. 3). However, there
were no significant monthly differences in the pro-
portions of age classes from October 1995 to Febru-
ary 1997 (*2 = 16.52, P=0.28) or when all monthly data
(June and July 1999) were included from inside haul-
outs (/=23.4, P=0.10).
528
Fishery Bulletin 102(3)
Rookeries (outside) Haul-outs (inside)
80-
F H W G
94 95 96 97 98 99 94 98 99 94 94
o
0
95 96 97 99
Oct Dec Mar Apr May Nov Feb Jun Jul
60-
E
o>
c
0
£ 40-
o
"O
CD
I
(
> 8
1
V
--
0 I
o o |
o oo oo h
o
Adult
Subadult
1
1
o
Correc
|\J
o
i i
1 o ° 1
■. ,8
r
8 .
Adolescent
§ o
0
o
Juvenile
ty=42 29 35 59 9 18 17 18 19 33 49
n,=108 56 76 62 69 75 50 35 33
0-
ns=19 13 10 26 3 10 9 10 9 6 11
ns=33 22 20 19 28 22 23 10 14
Figure 3
Box plots of corrected fork length of walleye pollock iTheragra chalcogramma) across
months and years for haul-outs and rookeries in Southeast Alaska (Forrester Island. F;
Hazy, H; White Sisters, W; Graves Rock. G). Box widths correspond to relative sample
sizes for numbers offish elements in,) and numbers of scats (ns) are also provided, and
stage-class categories are illustrated. Gray areas represent 95% confidence intervals.
the whiskers bound 1.5x the interquartile range I boxes), the circles denote outliers, and
the stars (*) denote extremes.
Overlap of size of pollock consumed by Steller sea lions
with size of pollock caught by the fisheries
The Canadian commercial pollock trawl fishery in Dixon
Entrance between 1993 and 1999 landed mostly (93%)
adult fish (mean FL = 52.2 ±5.9 cm, «=2103, modal range:
48-54 cm). The majority (79%) of scats containing pol-
lock from the Forrester Island rookery in June and July
also contained remains of adult pollock (mean corrected
FL=51.4 ±10 cm, a? = 192, modal range: 46-52 cm, ns=81
scats). Percentage overlap based on a comparison of
size-frequency distributions totaled 75.1% for those fish
eaten around Forrester Island and 52.1% for all fish
eaten. However, the estimated overlap would have been
assumed incorrectly to be half these values if DCFs had
not been applied to the selected digested otoliths and
bones (i.e., 36.7% overlap at Forrester and 24.1% for all
areas combined). Clearly overlap levels would have been
further underestimated if structures in poor condition
had been included in our analyses.
Discussion
Only 57% of the scats (303 of 531) that contained suit-
able pollock remains had structures that were in good
enough condition to be measured reliably. Numbers of
elements in good or fair condition (rc = 909) averaged
three per scat, and a very small fraction of these con-
sisted of otoliths (<4%). The most numerous structures
were DENT, QUAD, and ANGU (Table 1). This finding
is inconsistent with feeding trials with captive Steller
sea lions where otoliths were found to be the most com-
monly occurring structure (Cottrell and Trites, 2002;
Tollit et al., 2003).
Different structures yielded somewhat different mean
sizes of pollock, although 95% confidence intervals gen-
erally overlapped, ranging between 37 and 52 cm for
bones (Table 2). Such discrepancy is not surprising
given that different bones originate from different scats
and possibly different fish (even within a single scat).
Our comparison of estimates with all structures versus
MNI selections indicates that the potential effect of
double counting (and measuring) fish within a single
scat is likely negligible with large sample sizes (Fig. 2).
Although the use of all-structure data to estimate fish
length results in a greatly increased sample size, there
remains an underlying assumption that all structures
are affected equally by digestion. Tollit et al. (2004,
this issue) found no significant difference in the degree
of erosion across the three size ranges (28.5-45.0 cm
FL) for each structure within each condition category.
Tollit et al.: Sizes of walleye pollock consumed by Eumetopias /ubatus
529
They also found that the relative shape, structure, and
proportion of the morphological features used to es-
timate erosion were consistent for both smaller and
larger fish. We therefore assumed that the DCFs in that
study could be used reliably for the fish in our study
outside of the experimental size range in which they
were considered.
Applying DCFs increased mean fork length estimates
by 23% (from 34.4 to 42.4 cm) on average and resulted
in adult fish contributing 44% to the sea lion diet by
number and 74% by mass. The contribution of juvenile
fish was insignificant. Applying valid correction factors
clearly provides better insights into prey-size selection
and consequently niche overlap. It should also lead to
more precise estimates of mass of prey consumed and
the number of prey within a scat (Ringrose, 1993; Tollit
et al., 1997; Laake et al., 2002).
Over 61 species of prey were identified in the diet of
Steller sea lions in Southeast Alaska from 1993 to 1999
(Trites et al.3). The most common prey were walleye pol-
lock, Pacific herring (Clupea pallasi). Pacific sand lance
(Ammodytes hexapterus), salmon iOncorhynchus spp.),
arrowtooth flounder (Remhardtius stomias), rockfish (Se-
bastes spp.), skates {Raja spp.), and cephalopods. During
summer, gadids (most of which were pollock) made up
27% of the diet, and increased to 49-62% of the diet at
other times of the year (Trites et al.3), confirming that
pollock are a significant component of the diet.
Steller sea lions consumed a wide size range of pollock
in Southeast Alaska; the bulk of fish fell between 20 and
60 cm and peaked between 44 and 52 cm (Fig. 2). The
contribution of juvenile fish (<20 cm) was insignificant.
The only historical data to compare with these results
are those from the stomach samples of eight Steller sea
lions collected from Southeast Alaska in 1986 (Calkins
and Goodwin1). Pollock lengths backcalculated from all
otoliths found in the stomachs were generally shorter
(mean FL = 25.5 ±10.4 cm, range; 4. 8-55. 7cm, n = 80)
than our estimates from multiple structures found in
scats collected during the 1990s (mean FL = 42.4 ±11.6
cm, range: 10.0-78.1 cm, n = 909). It should be noted
that we derived our estimates after removing heavily
eroded structures and applying DCFs, whereas Calkins
and Goodwin1 did not account for partial digestion.
However our estimates of pollock length would have
been similar to those of Calkins and Goodwin1 if we
had used only otoliths and had not corrected for diges-
tion (Table 2). Although Frost and Lowry (1980) found
no significant difference between the size of otoliths
obtained from stomachs and intestines of ribbon seals,
underestimates of fish size determined from otoliths
from stomach samples will depend on the time since
ingestion (i.e., on the extent of digestion).
One possible explanation for the virtual absence of ju-
venile pollock in the scats we examined is that the rela-
tively smaller structures of smaller fish were more likely
to be completely digested, and were therefore underrep-
resented in the scats (Tollit et al., 1997; Bowen, 2000).
However, juvenile pollock otoliths and bones were found
in large numbers in a number of scats collected from
the western stock (Zeppelin et al., 2004, this issue).
Clearly, the potential for underestimating smaller fish
depends heavily on the balance between relative re-
covery rates and the number of different size fish con-
sumed in a meal. For example, if an animal needs to
eat 5 kg a day, then it would have to consume 195 15.5-
cm pollock, but less than ten 41-cm pollock. Given that
large pollock bones are at least three times more likely
than small bones to pass through the digestive tract
(Tollit et al., 2003; D. J. Tollit, unpubl. data), the sheer
numbers of small pollock in this example would lead
to a conclusion that smaller fish were more important
numerically, when in fact they were equally important.
Conversely, the relative proportion of large fish is likely
to be overestimated if ten large and ten small pollock
are consumed together. The generally low number of
structures per scat provides little information to assess
this balance. Hence we must assume that our results
are representative and unbiased.
Steller sea lions in Southeast Alaska did not seem to
eat fish over 65 cm. Whether or not sea lions do not tar-
get large fish, or whether large fish are harder to catch
and handle, or are encountered at a lower rate is not
known. However, large fish could be under-represented
in scats if large fish cannot be swallowed whole, and
head skeletal parts are lost while the fish is torn apart
on the surface (Olesiuk et al., 1990; Wazenbock, 1995)
or if bone regurgitation is size specific.
Regional, geographical, and temporal variation in sizes of
pollock consumed
Stomach samples collected in 1975-78 and 1985-86 in
the Gulf of Alaska contained substantial numbers of
juvenile pollock, as well as larger fish (mode: 39-43 cm).
In 1985, the distribution of sizes consumed by sea lions
around Kodiak Island appeared to mimic that of the pol-
lock population (Merrick and Calkins. 1996). However,
juvenile sea lions ate significantly smaller and relatively
more juvenile pollock than adult sea lions. Stomachs
from the Gulf of Alaska contained an average of 49 pol-
lock (1975-78) and 72 pollock (1985) compared with 1.6
pollock per scat in Southeast Alaska. In the Bering Sea,
90 stomachs were examined between 1975 and 1981 by
using only non-eroded otoliths, and these also contained
mainly (76%) juvenile pollock (mean FL=29.3 cm), but
also some adult fish (Frost and Lowry, 1986).
Between 1998 and 2000, Steller sea lions across the
range of the western population in Alaska consumed
pollock averaging 39.3 ±14.3 cm (range: 3.7-70.8 cm,
Zeppelin et al., 2004, this issue). This finding suggests
that sea lions may have been less reliant on juvenile
pollock than they were during the 1970s and 1980s.
Apparent differences may reflect differences in pollock
year-class strength, and thus differences in the domi-
nant size classes that were available to be consumed.
However, Zeppelin et al. (2004, this issue) reported
that the size distribution of walleye pollock consumed
by Steller sea lions between 1998 and 2000 did not ap-
pear to fluctuate with year-class strength, unlike the
530
Fishery Bulletin 102(3)
sizes of Atka mackerel {Pleurogrammus monopterygius)
consumed in western Alaska.
Comparing samples collected at rookeries from the
eastern and western populations reveals that sea lions
in the western stock ate significantly greater numbers
of smaller pollock and fewer adults in summer than sea
lions in Southeast Alaska (Zeppelin et al., 2004, this is-
sue; and our study). However, both eastern and western
stock sea lions using haul-outs in March (winter) ate
similar size pollock. Adult pollock occurred more fre-
quently in scats collected from rookeries along the open
ocean coastline of Southeast Alaska during June and
July (74% adults) than they did in scats from haul-outs
located in inside waters between October and May (51%
adults). Scats collected at rookeries can be considered to
be from adult female sea lions and to a lesser extent from
adult males, whereas those collected at haul-outs during
other times of the year contain a more diverse mix of age
groups, including greater numbers of younger sea lions.
Thus it is uncertain whether observed size differences
in pollock between these two groups are seasonal or due
more to size preferences of different aged animals. Lim-
ited support for the former comes from the similar size
pollock observed in the scats between the two groups in
June and July of 1999. Overall, however, it is unknown
whether the consumption patterns observed are a result
of an actual size selection of prey or if they result from co-
incidental distributions of sea lions and prey-size classes.
Some pinnipeds may select prey of particular sizes (Sin-
clair et al., 1994) and may encounter difficulties if they
cannot switch to other sizes or species if the abundance
of preferred prey is reduced. Fine-scale studies are now
being undertaken to address such uncertainties.
There are few assessments of pollock stock size for
the 1990s in Southeast Alaska (Martin, 1997). However
the biomass is believed to have been low compared to
other regions of Alaska. Juvenile pollock are known to
congregate in the shallow inside waters of Southeast
Alaska during winter (Sigler0) but are also known to
occur in significant numbers in the summer in waters
shallower than 200 meters on the outer coastline (Mar-
tin, 1997). Recruitment of 1-year-old fish was found to
be high during acoustic studies in 1994 and 1999 in the
Gulf of Alaska (Guttormsen et al., 2003).
Steller sea lions using rookeries in Southeast Alaska
consumed mainly adult pollock between 1994 and 1999
and showed no evidence of tracking any abundant age
class of pollock. However, the trend in increasing length
estimates for inside haul-outs after 1995 (Fig. 3 1 does
suggest that sea lions might be tracking a particu-
lar age class of prey. Certainly a greater range of age
classes were consumed at these haul-outs (Fig. 3).
Scientific trawls in 1996 indicated that the larger pol-
lock on the outside coastline occurred generally in wa-
ters 201-300 m deep during daylight hours (Martin,
B Sigler, M. F. 2003. Unpubl. data. Auke Bay Lab, National
Marine Fisheries Service. 1 L305 Glacier Highway, Juneau.
AK 99801.
1997) and that smaller pollock were present in shallower
depths. Larger pollock tend to disperse and move to
shallow waters to feed at night (Smith, 1981). Thus, the
observed crepuscular and nighttime foraging by lactating
Steller sea lions (Higgins et al., 1988; Trites and Porter,
2002) would be a logical foraging strategy to capture
adult pollock. Other important factors, in addition to
depth, that likely influence size selection include prey
density and spatial distribution in relation to rookeries
and haul-outs. Given both the greater mass and energy
content of adults compared with juveniles (Perez, 1994;
Anthony et al., 2000), the selection of adults would be an
energy efficient strategy — all other things being equal.
Overlap in sizes of pollock consumed by Steller sea lions
and sizes of pollock caught by fisheries
There was no commercial fishery for pollock in South-
east Alaska during the 1990s. However, a small fishery
occurred in nearby Dixon Entrance, B.C., that might
indicate sizes that could have been caught in Southeast
Alaska if a fishery had occurred. Overlap in sizes of
pollock caught by the B.C. fishery with those taken by
Steller sea lions further north (our study) more than
doubled after applying digestion correction factors (from
24% to 52%). Similarly, high levels of overlap were also
found between the sizes of pollock consumed by the
western stock (1998-2000) and those caught in the
same region by fisheries (after our DCFs were applied to
structures recovered from scats — Zeppelin et al., 2004.
this issue). A high degree of overlap in size highlights
a potential conflict between fisheries and sea lions, but
this overlap cannot be considered indicative of competi-
tion unless the resource that fisheries and sea lions seek
is limited across the space and time in question (Krebs
and Davies, 1991).
Conclusions
Our study provides the first substantial description of
the size of pollock eaten by Steller sea lions in South-
east Alaska. It also shows the benefits of using bones
other than otoliths to estimate the sizes of prey eaten
by Steller sea lions, and the importance of correcting
for degree of digestion. Accurately reconstructing the
sizes of bones and otoliths recovered from scats has a
significant bearing, in turn, on accurately determining
the mass of prey consumed, and on the extent of overlap
of sizes of prey consumed and sizes of the same resource
caught in commercial fisheries.
We found that Steller sea lions in Southeast Alaska
consumed a large proportion of adult pollock and few
juveniles between 1994 and 1999. Although greater
proportions of juvenile and adolescent pollock were con-
sumed over the same period, during the summer in the
Gulf of Alaska and Bering Sea, larger size fish still were
the most abundant prey item in the diet of sea lions.
A comparison of these estimates with the lengths of pol-
lock consumed during the 1970s and 1980s shows that
"To Hit et al.: Sizes of walleye pollock consumed by Eumetopias jubatus
531
Steller sea lions can consume a wide range of different
size pollock (4-78 cm). Whether or not these differences
in sizes of pollock consumed between regions and de-
cades reflect differences in availability, size preferences,
or year-class strength is not known and requires further
study primarily with fine-scale data from scientific sur-
veys and concurrent scat collections.
Acknowledgments
Funding was provided to the North Pacific Universities
Marine Mammal Research Consortium by the National
Oceanographic Atmospheric Administration and the
North Pacific Marine Science Foundation. We would
like to thank the contribution of personnel of the UBC
Marine Mammal Research Unit, ADF&G, T. K. Zep-
pelin, K. A. Call, A. J. Winship, E. H. Sinclair, and
two anonymous reviewers. We are also grateful to J. L.
Laake and R. Jov for statistical advice.
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533
Abstract— We examined movement
patterns of sportfish that were tagged
in the northern Indian River Lagoon,
Florida, between 1990 and 1999 to
assess the degree of fish exchange
between an estuarine no-take zone
iNTZ) and surrounding waters. The
tagged fish were from seven spe-
cies: red drum (Sciaenops ocella-
tus); black drum (Pogonias cromis);
sheepshead (Archosargus probato-
cephalus); common snook iCentropo-
mus undecimalis); spotted seatrout
(Cynoscion nebulosus); bull shark
{Carcharhinus leucas); and crevalle
jack (Caranx hippos). A total of 403
tagged fish were recaptured during
the study period, including 65 indi-
viduals that emigrated from the NTZ
and 16 individuals that immigrated
into the NTZ from surrounding waters
of the lagoon. Migration distances
between the original tagging location
and the sites where emigrating fish
were recaptured were from 0 to 150
km, and these migration distances
appeared to be influenced by the prox-
imity of the NTZ to spawning areas
or other habitats that are important
to specific life-history stages of indi-
vidual species. Fish that immigrated
into the NTZ moved distances rang-
ing from approximately 10 to 75 km.
Recapture rates for sportfish species
that migrated across the NTZ bound-
ary suggested that more individuals
may move into the protected habitats
than move out. These data demon-
strated that although this estuarine
no-take reserve can protect species
from fishing, it may also serve to
extract exploitable individuals from
surrounding fisheries; therefore, if
the no-take reserve does function
to replenish surrounding fisheries,
then increased egg production and
larval export may be more important
mechanisms of replenishment than
the spillover of excess adults from the
reserve into fishable areas.
Multidirectional movements of
sportfish species between an estuarine
no-take zone and surrounding waters
of the Indian River Lagoon, Florida
Derek M. Tremain
Christopher W. Harnden
Douglas H. Adams
Florida Fish and Wildlife Conservation Commission
Florida Marine Research Institute
1220 Prospect Avenue, Suite 285
Melbourne, Florida 32901
Email Derek Tremainia fwcstate-fl. us
Manuscript submitted 12 May 2003
to Scientific Editor's Office.
Manuscript approved for publication
20 January 2004 by the Scientific Editor.
Fish. Bull 102:533-544 (2004).
Fishery reserves or no-take sanctu-
aries, defined as areas where all
fishing activities are prohibited, are
increasingly proposed as an addi-
tional measure to traditional fishery
management practices for protecting
fish populations from overexploita-
tion (PDT, 1990; Bohnsack and Ault,
1996). The American Fisheries Soci-
ety recently issued a policy statement
on the protection of marine fish stocks
at risk of extinction and supported the
development of large marine reserves
to protect and rebuild vulnerable popu-
lations (Musick et al., 2000). Although
reserves have been established pri-
marily in reef or coastal marine habi-
tats, the potential to apply similar
management strategies in estuarine
systems may also be possible (Johnson
et al., 1999; Roberts et al., 2001).
Reserves in estuarine areas may
help protect exploitable fishery spe-
cies. Increases in species' sizes and
densities within these reserves may
also enhance adjacent fisheries by two
separate mechanisms. Johnson et al.
(1999) found that an existing estua-
rine no-take sanctuary on Florida's
central east coast protected popula-
tions of larger, spawning-age sport-
fish species. As a result, they sug-
gested that protection of populations
in no-take sanctuaries could also lead
to the replenishment of surrounding
fisheries through increased egg pro-
duction, larval export, and juvenile
recruitment. Additionally, mark-re-
capture data have demonstrated that
large juvenile and adult fishes emi-
grate from estuarine protected ar-
eas to surrounding waters (Bryant
et al., 1989; Funicelli et al., 1989;
Johnson et al., 1999; Roberts et al.,
2001; Stevens and Sulak, 2001) and
these data have been used to suggest
that spillover of excess adult fish
from estuarine reserve areas can di-
rectly supplement nearby fisheries.
Roberts et al. (2001) concluded that
the abundance of International Game
Fish Association based on line-class-
record catches in the vicinity of the
estuarine no-take sanctuary on Flor-
ida's east coast resulted indirectly
from protection and spillover of large
adults to outlying waters.
It has also been suggested that re-
serves protect areas of undisturbed
habitat (PDT, 1990), either by design
or through cessation of destructive
practices, and reserves are common-
ly established in areas of pristine,
productive, or otherwise important
habitats required by the species be-
ing protected (e.g., Russ. 1985). Fur-
thermore, studies have shown that
protecting fishery species can indi-
rectly change the overall community
structure (Cole and Keuskamp, 1998)
and, under certain circumstances,
can increase primary and secondary
productivity (Sala and Zabala. 1996;
Babcock et al., 1999). The influence
of habitat quality on fish movements
in relation to protected areas has not
been investigated; however, reserve
habitats that offer potential advan-
tages in the form of improved habitat
quality (Chapman and Kramer, 1999)
534
Fishery Bulletin 102(3)
or increased food and habitat availability could be ex-
pected to attract, or at least retain, individuals that
immigrate to the reserves from surrounding unpro-
tected habitats. Reserve areas that attract and retain
exploitable individuals from surrounding habitats at
higher rates than they replenish the surrounding habi-
tats could be considered to be sinks in terms of their
ability to directly supplement adjacent fisheries through
spillover of exploitable-size individuals. Fish emigration
from reserve habitats and the replenishment of nearby
fisheries is a commonly predicted benefit of harvest re-
serves (see reviews in Roberts and Polunin, 1991. and
Rowley, 1994). However, there are currently no studies
that simultaneously examine emigration and immigra-
tion in relation to estuarine reserves or that document
the extent to which reserve areas may also function to
withdraw individuals from surrounding fisheries. With-
out an assessment of net exchange, the interpretation of
reserve benefits with respect to replenishment cannot
be properly evaluated.
The National Aeronautics and Space Administration
(NASA) closed a portion of the Indian River Lagoon at
the Merritt Island National Wildlife Refuge (MINWRi
on Florida's east coast for security purposes in 1962. A
direct result of this closure was the effective creation of
an estuarine no-take zone that remains to the present
time. The proximity of this no-take zone to productive
estuarine fisheries provided an opportunity to examine
sportfish movements in the area with mark-recapture
methods. Johnson et al. (1999) first documented sport-
fish migrations out of this no-take sanctuary, and in a
related study, Stevens and Sulak (2001) provided more
complete descriptions of movement patterns of indi-
vidual species; each of these studies provided evidence
that the restricted habitats protected fish populations
and that adult sportfish egressed into surrounding wa-
ters open to fishing. However, because all tagged fish
originated from within restricted habitats, in neither of
these studies was it possible to consider the potential
for the movements of fish into protected areas from
surrounding waters. Therefore, we (sponsored by tin-
Florida Fish and Wildlife Conservation Commission-
Florida Marine Research Institute [hereafter referred to
as FMRII Fisheries-Independent Monitoring Program)
tagged fish species throughout the northern Indian
River Lagoon system, including both the MINWR no-
take zone and the surrounding lagoon waters, from
1990 to 1999. We investigated the relationship between
sportfish egress and ingress in relation to the MINWR
no-take zone and offer a quantitative foundation for
the discussion of net fish movements into or away from
protected estuarine habitats.
central east coast of Florida between Ponce de Leon
Inlet in Volusia County and Jupiter Inlet in Palm Beach
County. The lagoon is composed of three relatively iso-
lated basins: Mosquito Lagoon, the Indian River proper,
and the Banana River i Fig. 1). These three basins main-
tain hydrological connections with each other through
narrow man-made channels at Haulover Canal and
the Merritt Island Barge Canal (shown on Fig. 2) and
through a natural channel at the southern end of the
Banana River. Hydrodynamie exchange and fish passage
between the lagoon and the Atlantic Ocean occur pri-
marily through five inlets, which are concentrated in the
southern half of the system. The hydraulic lock system
located at Port Canaveral provides only an intermittent
opportunity for exchange between the IRL and Atlantic
Ocean. Gilmore et al. (1981) and Mulligan and Snelson
(1983) have provided detailed descriptions of the lagoon
and its habitats.
The no-take zone (NTZ) created by NASA and MIN-
WR is located at the northern terminus of the Banana
River basin of the lagoon. An earthen causeway defines
the southern boundary of this no-access security area
and contains only two openings that permit fish to mi-
grate to and from adjacent waters. Much of the natural
shoreline and saltmarsh habitats in the lagoon have
been altered for mosquito control purposes. However,
actual shoreline habitats surrounding MINWR — in-
cluding the NTZ, the northern Banana River basin,
the northern Indian River basin, and Mosquito La-
goon— remain relatively undeveloped in comparison to
the urban shoreline development in the southern IRL.
Detailed descriptions of the habitat composition within
the NTZ and surrounding study area were provided by
Johnson et al. (1999).
Data collection
Fish were tagged as part of several related FMRI proj-
ects (stratified-random, fixed-station, and directed sam-
pling designs) in the northern IRL between 1990 and
1999 (FMRI1). In most cases, tagging was conducted
opportunistically on healthy fish following capture in
multipanel monofilament gill nets, nylon trammel nets,
nylon haul seines, or on hook and line. In other cases,
projects were designed specifically to assess tag-recap-
ture information (Murphy et al., 1998). Because of the
focus of our sampling programs in this area, the major-
ity of our tagging efforts occurred north of Sebastian
Inlet within the Indian and Banana River basins of
the lagoon. A small percentage of tags were placed in
fish captured south of Sebastian Inlet or in Mosquito
Lagoon. Overall, our sampling collections in the NTZ
Materials and methods
Study area
The Indian River Lagoon (IRL) is a shallow barrier
island estuarine system spanning 25.3 km along the
1 FMRI (Florida Fish and Wildlife Conservation Commis-
sion). 1999. Florida Marine Research Institute. Fisheries-
independent monitoring program, 1999 annual data summary
report In-house Report. Florida Fish and Wildlife Conser-
vation Commission. Florida Marine Research Institute. LOO
Eighth Ave. S.E., St. Petersburg, Florida, 33701.
Tremain et ai.: Sportfish species movements in relation to an estuarine no-take zone
535
\ 80°30'W
. Ponce Jt Leon Inlet
mi 00' \\
\1I\WR No-take Zone (NTZ)
upper Banana River I BR i
Atlantic
Ocean
GulfoJ
l/l'Wl 0
29° 00' N-
28 JO' N-
28 OO'N-
Sebasritjn Inlet
Ft. Pierce Inlet
27 in \
Florida
Atlantu
Ocean
Si Lucielnlet
27"00'N
Palm Bead
County
Figure 1
Map of Florida and the Indian River Lagoon study area.
accounted for approximately 20% of our total sampling
efforts and averaged approximately 1-2 days/month over
the study period.
Fish were tagged by inserting 50-mm, 70-mm. or
100-mm Hallprint dart tags (Halprint Ltd., Victor Har-
bor, South Australia) into the dorsal musculature; the
plastic dart was lodged beneath the pterygiophores
of the dorsal fin. Each tag contained a visible exter-
nal streamer with a unique alphanumeric code and
instructions for anglers to contact us with recapture
information in order to collect a reward (five dollars
or equivalent). Information recorded at the time of ini-
tial tagging included the tag number, species tagged,
date, location (latitude and longitude i, and fish length
(standard, fork, and total lengths as appropriate for
the species). Recapture information on tagged fish was
collected through August 2000 from angler reports
and from fish recaptured during FMRI sampling ac-
tivities. Because of public-access prohibitions, recap-
ture information from inside the MINWR NTZ was
gathered exclusively through FMRI sampling efforts.
Data requested for recaptured fish included the same
information as that recorded at initial tagging; however,
in several cases, length or precise location information
returned from anglers was considered to be unreliable,
which prevented accurate statistical comparisons of
relationships involving recapture lengths or distances
traveled. Therefore, reported length data are limited to
initial tagging information only (total length; TL). To
prevent problems with pseudoreplication for individuals
recaptured on multiple occasions, we included only the
initial tag recovery data in our calculations of recapture
percentages.
Overall patterns offish migrations, including general
recapture locations and direction of movements into
or away from the NTZ, were described by using data
536
Fishery Bulletin 102(3)
A
B
!';;:;"" rb Egress
Catul
s Ingress
\
" R
B
TR
Merritt Island
B* ^-^.
National Wildlife
f \
1 No-take ]
Reflige /^^ ^\
| No-take j
V zone /
Kr R V J
R
y zone J
b Rft;
V y
r R :r Cape
R R Cape
Canaveral
B Canaveral
Cocoa Sr i}
•
Cocoa
R
8B Por,
Barge Cona/ Canaveral
H
H
R
2R R
Co
D
3
P6
R 2R
•
•
Melbourne
Melbourne
R
%
also one "S" and one "J"
-.
approximately 75 km south
in the St. Lucie River
\s
3RH
/ /«
Sebastian Inlet
Figure 2
(A) Recapture locations of tagged fish that migrated out of the Merritt Island
National Wildlife Refuge no-take zone. (B) Original tagging locations offish that
migrated into the Merritt Island National Wildlife Refuge no-take zone. R = red
drum, B = black drum, S = common snook, H = sheepshead, T = spotted seatrout,
J = crevalle jack, K = bull shark. Numbers before species codes (letters) indicate
the number of individuals of that species that were captured at that location.
from all available recapture sources. In contrast, we
calculated migration rates exclusively from the recap-
ture data collected during FMRI sampling activities.
Although this procedure excluded tag-return data from
recreational anglers, it permitted a quantitative assess-
ment of recapture rates based on standardized FMRI
col lection gear, comparable sampling effort, and lOO'*
tag reporting rates. We resolved potential problems
related to differences in habitat characteristics and
sampling intensity by including only data from the NTZ
and a fishable area of a similar size and habitat type
in the adjacent Banana River (BR, Fig. 1). This BR
zone corresponded precisely to the sampling zone used
for population comparisons in Johnson et al. (1999),
denoted as "FBR" (fished Banana River) in that study.
Species that did not contribute any FMRI recapture
information in either of these two areas were excluded
from our analyses. Tag recovery and migration rates
were calculated separately for the NTZ and BR. For our
purposes, "migration" was defined as a directional fish
movement across the NTZ boundary from the original
tagging location, and we made the assumption that
the migration patterns of recaptured fish represented
the migration patterns of the overall population. Rela-
Tremain et al.: Sportfish species movements in relation to an estuarine no-take zone
537
Table 1
Summary of tagging and recapture data for seven of the most common sportfish species tagged by FMRI scientists
ern Indian River Lagoon study area. Locations where tag and recapture data were collected are separated into the
(NTZ) and the surrounding waters of the Indian River Lagoon (IRL).
in the north-
no-take zone
Species
No-take zone
Indian River Lagoon
Total no.
offish
tagged
Total no.
recaptured
and percent
recaptured
Tagged
inside
NTZ
Recapture
location
Tagged
outside
NTZ
Recapture
location
NTZ
IRL
NTZ
IRL
Bull shark (Carcharhinus leucas)
1
1
24
1
25
2(8.0)
Common snook (Centropomus undecimalis)
104
1
9
406
32
510
42(8.2)
Crevalle jack ( Caranx hippos I
55
1
59
1
114
2(1.8)
Sheepshead tArchosargus probatocephalus)
597
6
520
26
1117
32(2.9)
Spotted seatrout (Cynoseion nebulosus)
193
2
171
1
3
364
6(1.6)
Black drum (Pogonias cromis)
637
4
8
831
9
32
1468
53(3.6)
Red drum (Seiaenops ocellatus)
720
30
40
1344
6
190
2064
266(12.9)
Total
2307
37
65
3355
16
285
5662
403)7.1)
tive migration rates were calculated as the percentage
of recaptured fish that migrated from their original
tagging location. These migration rates and their re-
ciprocal (retention rates) were compared between the
NTZ and the BR to determine the relative potential for
sportfish movements into or away from protected habi-
tats. Chi-square contingency tests for frequency data
(with Yates's correction for small sample sizes) were
used to test the hypothesis that recapture location was
independent of the tagging location.
Results
A total of 5951 fish of 27 species were tagged during
FMRI sampling within the IRL between September 1990
and December 1999. However, because 95% of these fish
were represented by only seven species (Table 1), which
included all fish that migrated across the reserve bound-
aries, only these seven species were considered further
in our analyses. Red drum (Seiaenops ocellatus) was
the most commonly tagged species (n=2064), followed
by black drum (Pogonias cromis, n = 1468), sheepshead
(Archosargus probatocephalus, /? =1117 ), common snook,
(Centropomus undecimalis, n = 510), spotted seatrout
(Cynoscion nebulosus, /; = 364), crevalle jack (Caranx
hippos, n=114), and bull shark (Carcharhinus leucas,
n=25). Approximately 41% (n=2307) of these fish were
tagged inside the boundaries of the NTZ. The remain-
der (« = 3355> were tagged in the surrounding lagoon.
Through August 2000, 403 tagged fish (7.1% of total)
were recaptured and reported either by FMRI staff
sampling in the lagoon or by the public. Overall recap-
ture rates were highest for red drum (12.9%), followed
by those for common snook (8.2%), bull shark, (8.0%),
black drum (3.6%), and sheepshead (3.0%).
Tagged fish were generally representative of the larg-
er mobile members of the species and encompassed the
legally exploitable size ranges for species with man-
agement restrictions (Table 2). For species except the
bull shark and red drum, mean lengths of fish tagged
inside the NTZ exceeded those of fish tagged outside
the NTZ.
Approximately 25% (n = W2) of the 403 total recap-
tured fish were fish originally tagged inside the NTZ
(Table 1). Thirty-seven of these fish were also recovered
inside the NTZ. including three red drum that were
subsequently recaptured on multiple occasions in the
protected area. The remaining 65 recaptured fish were
caught after emigrating to outlying waters, including
one red drum that was recaptured a second time outside
the NTZ. Species that migrated out of the NTZ were
red drum (n = 40, mean TL = 643 mm, SD = 135 mm),
common snook (;? = 9, mean TL = 570 mm, SD = 97 mm),
black drum (n = 8, mean TL = 845 mm, SD = 88 mm),
sheepshead (n = 6, mean TL = 398 mm, SD = 38 mm),
bull shark (n = l, TL=789 mm), and crevalle jack (n = l,
TL = 628 mm). Recapture distances ranged from 0 km
immediately outside the NTZ to approximately 150 km
south in the St. Lucie River estuary, but recaptured
fish were more abundant closer to the NTZ (Fig. 2A).
Most of the recaptured fish were concentrated in areas
of high fishing pressure, such as causeways, inlets, and
waters near the boundary of the NTZ. Collectively, fish
that emigrated from the NTZ did not appear to show a
bias for any one direction of movement: recaptured fish
were found both northward in the Indian River and
southward throughout both the Indian River and Ba-
nana River basins of the lagoon. For individual species,
red drum that emigrated were distributed throughout
the lagoon system and coastal habitats, whereas black
drum were predominantly recaptured in the northern
538
Fishery Bulletin 102(3)
Table 2
Total length ITL)
and the outlying
size ranges (in mm) and le
ndian River Lagoon study
gal size
area.
limits (
as of August 2000) foi
tagged sportfish species
from the no-take zone
Species
No-take zone
Indian
River Lagoon
Legal size limits
Mean(SD)
min
max
MeanlSDl
min
max
(mm TL)
Bull shark
789( — i
789
789
974(135)
684
1180
None
Common snook
570(106)
330
844
506(138)
227
944
660-8641+ lover)
Crevalle jack
486(140)
305
720
443(113]
264
720
None
Sheepshead
398(68)
235
614
365(76)
171
594
305 minimum
Spotted seatrout
415(129)
185
754
335(111)
212
678
381-508 (+ 1 over)
Black drum
786(129)
249
1156
742(240)
225
1135
356-610 ( + 1 over)
Red drum
613(166)
308
1245
624(229)
203
1210
457-686
estuarine portion of the study area. Sheepshead and
common snook were recaptured primarily to the south
at inlets or in the adjacent Atlantic coastal waters out-
side the lagoon.
The remaining 75% (« = 301) of the total recaptured
fish were from fish originally tagged outside the NTZ
(Table 1). The majority of these (/!=285) were also re-
covered in outlying waters, including 16 red drum and
1 sheepshead that were subsequently recaptured on
multiple occasions. Sixteen fish were recaptured after
they had immigrated into the reserve. These recaptured
fish were from three sciaenid species: predominantly
black drum in = 9, mean TL = 907 mm, SD = 66 mm) and
red drum ln = 6, mean TL = 656 mm, SD = 170 mm), but
also one spotted seatrout (TL=420 mmMFig. 2B). The
longest migration distances into the NTZ were up to 75
km for red drum and spotted seatrout tagged in south-
ern Mosquito Lagoon and the northern Indian River
basins. All black drum that immigrated into the NTZ
were tagged in the adjacent Banana River basin.
A relatively large number of red drum, common snook,
and sheepshead that were tagged inside the NTZ or in
the outlying waters were recaptured in close proximity
(0 to 2.75 km distance) to inlet habitats. Recaptured
red drum from inlet habitats (n = 45, mean TL=647 mm,
SD = 135 mm) peaked during September through No-
vember. Recaptured common snook from inlet habitats
(n=13, mean TL = 598 mm, SD = 111 mm) were distrib-
uted throughout much of the year but peaked in late
fall. Few common snook were recaptured from inlet
spawning habitats during the peak summer spawning
months (June-August) when their fishery was closed.
Recaptured sheepshead from inlet habitats («=8, mean
TL = 373 mm, SD = 53 mm) were concentrated in the
winter and early spring.
Estimated migration rates were calculated by using
only those fish that were tagged and recovered from
FMRI sampling in the NTZ and the immediately ad-
jacent upper Banana River (BR). The number of fish
tagged in the NTZ (n=1654) was approximately 1.7
times the number tagged in the BR (/(=965) (Table 3);
however, the overall recapture rates of fish that were
originally tagged in each of these two areas were equal
(2.4%). Black drum and red drum made up the majority
of tagged and recaptured fish in both areas and were
the only species recaptured that had migrated both into
and away from the NTZ in this comparison. For total
sportfish (all species pooled), there was a significant
relationship between the tagging location and the direc-
tion offish movements (fh 005=13.8, P=0.0002). A total
of 40 fish originating from the NTZ were recaptured,
but that number included only 2 fish (one red drum
and one black drum) that emigrated to the BR (5%
overall migration rate). In contrast, 23 fish originat-
ing in the BR were recaptured overall, including 12
that immigrated into the NTZ (52% overall migration
rate). Species-specific migration rates were highest for
black drum, and relative immigration rates (90%) were
higher than emigration rates (25"7<). For this species,
the frequency of immigration and emigration were sta-
tistically independent of tagging location (xZi 005=0.01.
P=0.9039), which is probably due to the low number of
recaptures offish tagged inside the NTZ (Table 3). For
red drum, relative immigration rates (27%) were also
higher than emigration rates (3%), but in this case,
there was a significant relationship between fish move-
ments and tagging location (^ ,, (ia=20.58, P<0.0001).
Common snook, spotted seatrout. and sheepshead were
also recaptured by FMRI scientists in these compari-
sons, but none of these recaptured fish represented
evidence of migrations across the NTZ boundary from
their original tagging location.
Discussion
This study demonstrated both the emigration and immi-
gration of sportfish species across the boundaries of an
estuarine no-take zone (NTZ). Legal-size large juveniles
and adults of six of the recreationally valuable species
tagged within NTZ boundaries — red drum, black drum,
common snook, sheepshead, bull shark, and crevalle
Tremain et al.: Sportfish species movements in relation to an estuarine no-take zone
539
Table 3
Summary of tag and recapture
and the adjacent fished waters
included in calculations of tota
data from only the Florida Marine Research Institute sampl
of the Banana River (BR). Species that did not contribute
s or of migration percentages.
ing efforts in the no-take zone ( NTZ )
any recapture information were not
No-take zone
Total
Percent that
migrated
Banana River
Total
Percent that
migrated
No. of
fish tagge
No. fish
recaptured
No. of
fish tagged
No. fish
recaptured
i NTZ
BR
NTZ
BR
Red drum
720
32
1
33
3.3
176
3
8
11
27.3
Black drum
637
3
1
4
25.0
495
9
1
10
90.0
Common snook
104
1
0
1
0
62
0
1
1
0.0
Spotted seatrout
193
2
0
2
0
121
0
0
0
—
Sheepshead
597
0
0
0
—
232
0
1
1
0.0
Totals
1654
38
2
40
5.0
965
12
11
23
52.2
Tag recovery (% )
2.4
2.4
jack — were documented to migrate out of the protected
area. Johnson et al. (1999) and Stevens and Sulak (2001)
also observed many of these same species emigrat-
ing from no-take zones within the same refuge system
during the late 1980s, although the species with the
highest recapture rates in their studies (common snook)
differed from the current study (red drum). This differ-
ence may reflect an increase in the popularity of the red
drum fishery on Florida's east coast during the current
study period. Since 1989, when the recreational red
drum fishery reopened under strict management regula-
tions, there has been a significant increase in both the
total red drum landings on the Atlantic coast and in the
estimated number of fishing trips made by anglers seek-
ing or catching red drum each year (Murphy2). Tagging
studies in estuarine areas of the Everglades National
Park have previously documented emigrations of striped
mullet (Mugil cephalus), gray snapper (Lutjanus gri-
seus), and spotted seatrout away from protected habitats
(Bryant et al., 1989; Funicelli et al., 1989). Recent stud-
ies suggest that fish moving out of protected areas in
the IRL may help to replenish nearby fisheries and may
contribute to trophy fisheries in the surrounding system
(Johnson et al., 1999; Roberts et al., 2001).
In our study, overall emigration rates were low, but
many of the fish that emigrated from the estuarine NTZ
moved comparatively large distances. The egress pat-
terns of exploitable species may affect both the species'
potential for protection and the degree to which fisheries
located adjacent to protected reserves will be enhanced
(DeMartini, 1993). In coastal marine and tropical reef
systems, where the large majority of reserves have been
established, long-distance movements greater than a
2 Murphy, M. D. 2002. A stock assessment of red drum.
Seiaenops ocellatus, in Florida: status of the stocks through
2000, 32 p. Florida Fish and Wildlife Conservation Com-
mission Report, Melbourne, FL.
few kilometers by demersal fishery species are limited
to a very small percentage of individuals (Beaumar-
iage, 1969; PDT, 1990 and references therein; Rowley,
1994), and the direct supplementation of nearby fisher-
ies by exploitable species appears to be highly localized
(Buxton and Allen, 1989; Russ and Alcala, 1996). The
majority of fish that emigrated from the NTZ were
recaptured between 10 and 75 km from the boundary,
but fish were also recovered as far as 150 km from the
NTZ boundary. Our observations on migration distances
and recapture locations corresponded well with those
reported from previous studies of fish movements out
of this same reserve system (Johnson et al., 1999; Ste-
vens and Sulak, 2001). although maximum recapture
distances in earlier studies were even greater.
Many of the fish that emigrated from the NTZ — such
as red drum, common snook, and sheepshead — were
recaptured at inlet locations or in the nearshore coastal
waters at sizes that were large enough to include re-
productively mature adults (Murphy and Taylor, 1990;
Render and Wilson, 1992; Taylor et al., 2000). The
seasonality of inlet-associated recaptures was consistent
with the seasonality of documented spawning and move-
ment patterns for these species. In Florida, red drum
typically spawn in nearshore coastal waters during
the fall (Murphy and Taylor, 1990), although spawning
within the IRL has also been documented (Johnson
and Funicelli, 1991). Spawning by common snook may
occur year-round on Florida's east coast (Gilmore et al.,
1983), but most spawning takes place between May and
October in or near major inlets to the Atlantic Ocean
(Taylor et al., 1998). The limited number of common
snook recaptured from inlet spawning habitats dur-
ing the peak summer spawning season (June-August)
was likely due to the fishery being closed during those
months. Sheepshead move offshore with the onset of
cool weather in the late fall (Gunter, 1945; Kelly, 1965),
and spawning likely occurs in offshore waters during
540
Fishery Bulletin 102(3)
the spring (Springer and Woodburn, 1960; Jennings,
1985; Tucker and Barbera, 1987). In the northern por-
tion of the IRL, where the NTZ is located, the closest
access to the coastal environment is through two inlets
located approximately 75 km (Sebastian Inlet) and 100
km (Ponce de Leon Inlet) swimming distance away or
through an intermittent lock opening at Port Canaveral
approximately 12 km to the south. In order to reach
nearshore or tidal-pass spawning habitats, species must
first migrate to these locations. The coincidence of tag
recoveries from these areas during identified spawning
or migration periods likely indicated that the relatively
long movement distances we observed resulted from a
combination of geographical, environmental, and bio-
logical factors, including the proximity of the NTZ to
habitats that are important for specific life-history re-
quirements of individual species. From a management
viewpoint, these relationships can affect the spatial
extent of species' migrations in relation to protected
habitats, as well as the degree of protection provided to
individuals that are migratory, and should be consid-
ered carefully in the design of estuarine reserves.
This study documented the ingress of exploitable es-
tuarine sportfish species into protected habitats and
demonstrated that these movements can also cover sub-
stantial distances. Species moving towards the NTZ
traveled distances of at least 10-75 km. The original
tagging locations of these fish were distributed through-
out the northern Indian and Banana rivers and southern
Mosquito Lagoon, which paralleled the primary region
of our tagging efforts. Whether or not fish from more
southerly locations in the IRL system would migrate
into the NTZ is largely unknown because of the lack
of tagging effort in those areas. However, for tropical
species such as the common snook, permit (Trachinotus
falcatus), gray snapper, and others whose abundances
increase seasonally in the northern lagoon habitats dur-
ing the warmer months (Tremain and Adams, 1995), it
seems probable that seasonal movements could bring
them into contact with the protected habitats. In such
cases, these species would benefit only temporarily from
fishing protection until their return migrations made
them again vulnerable to capture. In contrast, species
observed migrating into the NTZ that typically have a
high degree of site fidelity during specific life-history
stages, such as the red drum (Beaumariage, 1969; Ad-
ams and Tremain. 2000), black drum (Murphy et al.,
1998), and spotted seatrout (Moffett, 1961), should de-
rive greater long-term benefits from reserve protection
following immigration into protected areas.
Tagging studies that examine the transfer of fishery
species between reserve and outlying habitats are rare,
and we have found only one recent study on any fishery
species, the American lobster (Homarus americanus\,
that investigated the effects that multidirectional spe-
cies migrations may have upon protective reserve func-
tions (Rowe, 2001). Studies in which fish movements
have been examined, in both estuarine and marine
protected areas, have focused exclusively on fish egress
from reserve habitats (Bryant et al., 1989; Buxton and
Allen, 1989; Funicelli et al., 1989; Holland et al., 1996;
Zeller and Russ, 1998; Johnson et al., 1999. Stevens
and Sulak, 2001) or on home ranges of species associ-
ated with reserve habitats (Eristhee and Oxenford.
2001; Starr et al., 2002). In the present study, we simul-
taneously examined both egress and ingress of sportfish
in relation to a no-take reserve and the surrounding
unprotected waters, and the results provide a starting
point to quantitatively discuss the relationship between
fish emigration and immigration, as well as the implica-
tions of such movements to the resulting functions of
replenishment to or withdrawal from nearby estuarine
fisheries. When all recapture sources were considered,
the ratio of migrating to nonmigrating individuals was
much higher for fish tagged inside the NTZ (1.58) than
for those tagged outside the NTZ (0.05); this ratio im-
plies that there is a spillover effect from the reserve.
However, this difference is less apparent when measured
against the large disparity between recapture effort
from inside the NTZ (12-24 FMRI sampling days/year
+ 12-24 angler days/year) and recapture effort from the
surrounding lagoon waters of Brevard County (50-100
FMRI sampling days/year + 114,000-181,000 angler
days/year [FMRI. unpubl. data]). Furthermore, this
direct comparison assumes that recapture potential was
the same in protected and unprotected areas, which is
unlikely given the differences between the primary re-
capture gear used in scientific research activities inside
the reserve (nets) and the gear used in recreational an-
gling outside the reserve (hook and line). There were no
reliable estimates of sportfish species landings available
for the limited study region that could have enabled
us to intercalibrate for these differences; therefore.
we limited further comparisons to only data recovered
through FMRI sampling activities in the northern Ba-
nana River basin. This limitation came at the expense
of important tag-recovery data collected by anglers or
collected from more outlying areas of the lagoon but
permitted a more quantitative comparison of migra-
tion potential that focused comparisons on immediately
adjacent areas where the effects of spillover would most
likely be realized (Buxton and Allen, 1989; Russ and
Alcala, 1996). In these comparisons, a disproportionate
number of fish were tagged inside the NTZ, but overall
tag-recovery rates for fish originating in both the NTZ
and the adjacent Banana River were equivalent. This
finding indicated that tagged individuals from both
areas were equally susceptible to recapture. However,
there were substantial differences in the migration
patterns of fish between the two areas. In the vicinity
of the NTZ, the relative potential for overall sportfish
migrations (primarily for red drum and black drum,
which provided the greatest quantity of tag recovery
data) towards the NTZ from unprotected habitats (52%)
was greater than the potential for migrations out of the
NTZ (5%).
Two potential limitations must be considered when
comparing these migration rates. First, it is possible
that recreational fishing in the upper Banana River
could have reduced the number of tags available to FM-
Tremain et al.: Sportfish species movements in relation to an estuarine no-take zone
541
RI sampling activities outside the NTZ, leading to lower
tag recovery rates from this area. However, several fish
from the Banana River study area were recaptured on
multiple occasions — a common occurrence in this region
where fish are caught and released in fishing practices.
Although there is some postrelease cryptic mortality
associated with catch-and-release practices, these re-
leases likely limited the effects of local fishing on our
analyses. Second, our assumption that the migration
patterns of recaptured fish represented the migration
patterns of the overall population may not be valid if
the respective length frequencies were not also equally
represented. The use of multiple gear types and sam-
pling strategies to collect fish for tagging increased the
likelihood that the length frequencies of species in our
collections represented the available population. Report-
ed recapture length frequencies closely approximated
the population length frequencies in our collections for
red drum, black drum, and sheepshead but over-repre-
sented the frequency of larger individuals for common
snook and spotted seatrout. Because red drum and
black drum were the principal species that displayed
multidirectional migration patterns, we considered the
potential for size bias to be minimal in our comparisons
of estimated ingress and egress rates.
Ultimately, a determination of the net result of these
migration patterns, in terms of replenishment to or
withdrawal from adjacent fisheries, would require ac-
curate assessments of species population abundances
that were beyond the scope of this study. If there are
large enough differences in population densities across
the NTZ boundary, either as a result of increased pro-
duction inside the reserve or high fishing mortality
outside, then the relatively low emigration rates that we
observed could still result in a net export of exploitable
individuals to fished populations in surrounding waters.
In trammel-net collections from this same reserve dur-
ing the late 1980's, Johnson et al. (1999) estimated
that in the protected habitats, relative abundances of
red drum populations were 6.3 times greater and of
black drum were 12.8 times greater than the relative
abundances of these populations in adjacent unpro-
tected areas. More recent shoreline haul-seine data
from 1997-2000 show that these abundances were only
1.8 times greater for red drum and 1.5 times greater
for black drum (FMRI, unpubl. data). To what extent
the difference in abundance estimates between these
two temporally separate studies is related to fish move-
ments, to stringent changes in management regulations
that have occurred, or to the difference in sampling
methods used is undetermined. However, if we consider
the more recent population level differences between the
NTZ and adjacent waters, then the emigration and im-
migration rates observed in the present study indicate
that there is a potential for more substantial move-
ments by these species towards protected habitats than
away from them.
One limitation of tag-recapture data is that such data
provide only a snapshot view of overall fish movements,
and the whereabouts of tagged individuals between
the time of tagging and recapture are unknown. It
is possible that the movements we observed for red
drum and black drum in the vicinity of the NTZ were
simply instantaneous views of a more complex series of
movements between the NTZ and adjacent waters. One
possibility is that these movements could be related
to daily or seasonal home ranges that extend across
reserve boundaries. Studies that attempt to quantify
home ranges for these species at any temporal scale
are limited. Carr and Chaney 1 1976 1 followed a single
red drum, which was fitted with an ultrasonic trans-
mitter, for up to two days after releasing it into the
Intracoastal Waterway near St. Augustine, Florida.
During that time, fish movements were oriented against
the direction of tidal flow but remained within 2 km
of the release point. Adams and Tremain (2000) found
that large juvenile red drum repeatedly used or were
continually associated with a 2-km section of a northern
IRL tidal creek for periods of up to 18 months. Tag-
ging studies from estuarine waters generally indicate
that the majority of red drum and black drum do not
make substantial movements from their release sites,
although some individuals are capable of migrating up
to several hundred kilometers (Beaumariage, 1969:
Osburn et al. 1982; Music and Pafford, 1984; Murphy et
al., 1998i. During the present study, 20 red drum were
recaptured on multiple occasions; however, none of these
fish exhibited movements that could provide evidence
for home ranges that overlapped the NTZ boundar-
ies. Another possibility for the movement patterns we
observed is that they are related to population equilib-
rium adjustments that occur when the relative attri-
butes of the NTZ and surrounding areas change with
respect to each other. For example, beginning in 1990
and coinciding with the onset of the present study, the
Banana River adjacent to the NTZ (including much of
our BR study area) was closed to motorized boat traffic.
Although the area remained open to fishing, it became
considerably more difficult to access by fishermen. If
this limitation resulted in lower fishing pressure (i.e.,
predation) and fewer habitat disturbances, then the
relative habitat value and rates of migration into this
area may have increased during that time. There are
no quantifiable estimates of migration rates prior to
this study for comparison, but our results do not dem-
onstrate an equilibrium adjustment toward potentially
higher quality BR habitats during our study period. If
species movements are not equilibrium adjustments,
but rather are driven by an attraction to or retention
within habitats that offer protective benefits, then ul-
timately reserve habitats should become saturated.
Predicted equilibrium population sizes for queen conch
iStrombus gigas) and spiny lobster (Panulirus argus)
were achieved in just three years after the effective
creation of a Caribbean reef harvest refuge, but models
suggested that relatively minor changes in refuge area
and boundary condition (i.e., permeability) could result
in major population-level responses by exploited species,
depending upon dispersal dynamics and habitat avail-
ability (Acosta, 2002). The estuarine no-take zone at
542
Fishery Bulletin 102(3)
MINWR has been in effect for approximately 40 years,
presumably long enough for fish populations to reach
equilibrium levels, yet we observed a net movement of
fish into protected habitats over the past decade.
A wide range of factors interact to determine the
distributions of large mobile fish in the IRL, where
physical environmental conditions (salinity, inlet dis-
tance, temperature, etc.) have a primary influence on
the species' distributions over a lagoon-wide scale, and
where species responses to biological variables (sea-
grass cover, depth, seasonality, etc.) act secondarily to
influence distributions at smaller scales (Kupschus and
Tremain, 2001). The specific mechanisms that lead to
the greater ingress rates into the NTZ for red drum and
black drum in the present study cannot be determined
from our data. Possibilities include a behavioral attrac-
tion to the NTZ due to the interrelated influences of
habitat preference, spawning, and social structure, or
due to potentially higher retention rates after migra-
tion into the reserve. Red drum and black drum were
routinely observed foraging in large schools within both
the NTZ and surrounding waters, which suggested that
food resources were available in each of these habitats;
however, there are few studies that have attempted to
quantify differences in resource availability between
these areas. Johnson et al. (1999) described the habitat
characteristics of their study areas within the same re-
serve system but found that protection from fishing, and
not habitat difference, was the primary factor contribut-
ing to differences in the abundance of sportfish species
between fished and unfished areas. The availability of
suitable spawning habitats within the NTZ may also
attract red drum and black drum to the reserve habi-
tats. We observed indications of reproductive behavior
by both of these species inside the NTZ that is common
among members of the drum family, including concen-
trations of drumming fish (Mok and Gilmore, 1983)
and repeated side-to-side contact among individual fish
(Tabb, 1966) in the presence of ripe and running males.
Although we did not directly observe these behaviors
for either species outside of the NTZ, black drum and
red drum are documented to spawn elsewhere within
the IRL system (Mok and Gilmore, 1983; Johnson and
Funicelli. 1991) and we cannot automatically presume
that suitable spawning habitats do not also occur in the
surrounding waters. If there is a behavioral attraction
to protected habitats, then the subsequent retention of
individuals that have immigrated into these areas may
be prolonged by the limited boundary permeability of
this reserve, which contains only two potential egress
pathways back into the adjacent waters. In order to ful-
ly understand the protective functions of this estuarine
reserve and others, it will be important to identify the
biological, behavioral, and physical mechanisms that
influence species movements in relation to the reserve
boundaries.
The opportunistic nature of our tagging efforts within
the design of a larger sampling program precluded sta-
tistically valid sample replication, and only one reserve
and adjacent fished area were examined; therefore,
the results of this study should not be generalized to
other areas. Still, the IRL is typical of other bar-built
estuaries where access by estuarine fishes to coastal
waters through passes or inlets may be limited, and
it is reasonable to expect that the geographical, en-
vironmental, and biological processes that influence
species movements in the IRL would also be important
in other estuaries of similar structure. Studies show-
that no-take areas in estuarine systems can have an
effect on species' abundances and size distributions
within these protected areas and may indicate that
these areas protect species from the effects of fishing
pressure (Johnson et al., 1999; FMRI unpubl. datai.
Whether or not these areas will actually increase fish
abundance in adjacent waters or benefit surrounding
fisheries through direct supplemental replenishment of
exploitable species is less evident. Certainly, some indi-
viduals will migrate out of protected areas in response
to environmental, biological, or physiological stimuli,
and these individuals may contribute to trophy fisheries
in surrounding waters (Roberts et al.. 2001); however,
our data indicated that within estuaries, reciprocal
movements over relatively large distances into protected
areas also occur and have the potential to extract ex-
ploitable individuals from surrounding fisheries. The
overall impact of such withdrawals on these fisheries
will depend on the degree of retention following migra-
tions into protected areas. If retention rates are high,
then increased egg production, larval export, and juve-
nile recruitment may be more important mechanisms
for replenishment of nearby fisheries than spillover of
exploitable species, but production and export will be
limited unless reserves encompass spawning or nursery-
habitats (or both) that will support long-term protection
and population growth. For estuarine-dependent coastal
species that support estuarine fisheries, the benefits
obtained within protected areas will be determined,
in part, by their specific life-history characteristics,
movement patterns, and the reserve design. Although
the establishment and study of reserves in marine or
coastal systems has increased in recent years, research
on the effects of protected no-take reserves in estuarine
habitats is still in its infancy. Information on the daily,
seasonal, or annual movement patterns of estuarine-
resident or estuarine-dependent coastal species is neces-
sary for understanding and designing effective reserve
areas in these habitats.
Acknowledgments
We wish to thank the crewmembers and volunteers at
FMRI's Indian River Field Laboratory for collecting data
and assisting in this study and the many fishermen who
willingly provided us with recapture information. We
are grateful to U.S. Fish and Wildlife Service personnel
for providing access to sampling areas within restricted
areas of the Merritt Island National Wildlife Refuge.
This paper benefitted from reviews by R. Cody. J. Col-
vocoresses, L. French, J. Leiby, R. Paperno, J. Quinn,
Tremain et al.: Sportfish species movements in relation to an estuarine no-take zone
543
T. Tuckey, and F. Vose, and two anonymous reviewers.
This work was supported in part by funding from the
Department of Interior, U. S. Fish and Wildlife Service,
Federal Aid for Sport Fish Restoration Grant Number
F-43, and by the State of Florida Recreational Saltwater
Fishing License monies.
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545
Abstract— Patterns of distribution
and growth were examined for young-
of-the-year (YOY) greater amberjack
{Seriola dumerili) associated with
pelagic Sargassum in the NW Gulf
of Mexico. Seriola dumerili were col-
lected off Galveston, Texas, from May
to July over a two-year period (2000
and 20011 in both inshore (<15 nauti-
cal miles [nmijl and offshore zones
(15-70 nmi). Relative abundance of
YOY S. dumerili (32-210 mm stan-
dard length) from purse-seine col-
lections peaked in May and June,
and abundance was highest in the
offshore zone. Ages of S. dumerili
ranged from 39 to 150 days and hatch-
ing-date analysis indicated that the
majority of spawning events occurred
from February to April. Average daily
growth rates of YOY S. dumerili for
2000 and 2001 were 1.65 mm/d and
2.00 mm/d. respectively. Intra-annual
differences in growth were observed;
the late-season I April I cohort expe-
rienced the fastest growth in both
years. In addition, growth was signifi-
cantly higher for S. dumerili collected
from the offshore zone. Mortality was
approximated by using catch-curve
analysis, and the predicted instan-
taneous mortality rate (Z) of YOY S.
dumerili was 0.0045 (0.45%/d).
Distribution, age, and growth of young-of-the-year
greater amberjack {Seriola dumerili)
associated with pelagic Sargassum
R. J. David Wells
Jay R. Rooker
Texas A&M University
Department ol Marine Biology
5007 Avenue U
Galveston, Texas 77551
Present address (lor R. J, D Wells): Coastal Fisheries Institute
Louisiana State University
Baton Rouge, Louisiana 70803
E-mail address (for R J D Wells) rwells4@lsu.edu
Manuscript submitted 9 December 2002
to Scientific Editor's Office.
Manuscript approved for publication
2 March 2004 by the Scientific Editor.
Fish. Bull. 102:545-554 (2004).
Recruitment of marine fishes is highly
variable and closely linked to early
life events (Houde, 1996; Cole, 1999).
Early life survival is dependent upon
several biological and environmen-
tal factors including spawning time,
prey availability, predation pres-
sure, growth, and physical transport
mechanisms (Bricelj, 1993; Schnack
et al., 1998). Recruitment success
is commonly assessed by examining
patterns of relative abundance (Sano,
1997), whereas estimates of growth
and mortality are commonly used to
index recruitment potential (Rilling
and Houde, 1999; Rooker et al., 1999).
Early life growth and mortality are
linked because fishes with high growth
rates often exhibit decreased size-spe-
cific predator vulnerability (Meekan
and Fortier, 1996). As a result, esti-
mates of juvenile abundance, growth,
and mortality provide insight into
patterns of nursery habitat quality
and thus may be used to delineate
essential fish habitat (EFH) (Pihl et
al., 2000; Sullivan et al, 2000).
Greater amberjack ( Seriola dumer-
ili) is a reef-associated species with
a circumglobal distribution in sub-
tropical and temperate waters (Ma-
nooch and Potts, 1997a). In the Gulf
of Mexico, S. dumerili is the largest
carangid and supports important
recreational and commercial fisher-
ies (Thompson et al., 1999). Owing
to increased fishing effort and land-
ings, S. dumerili in the Gulf are cur-
rently assessed as overfished (NOAA,
2000). Consequently, detailed life his-
tory information is needed to effec-
tively guide fishery management of
this valuable resource. To date, avail-
able life history data on S. dumerili
have almost entirely been based on
assessments of subadults and adults
(Manooch and Potts, 1997a, 1997b;
Thompson et al.1). Despite the impor-
tance of early life processes, data on
juvenile or young-of-the-year (YOY)
S. dumerili are limited to qualitative
surveys of pelagic Sar-gassum (Bor-
tone et al., 1977; Settle, 1993).
The National Marine Fisheries Ser-
vice has recently designated Sargas-
sum as essential fish habitat (EFH)
of several coastal migratory species
including S. dumerili (NOAA, 1996).
In response, the goal of this study
was to examine the distribution and
growth of S. dumerili associated with
pelagic Sargassum mats in the NW
Gulf of Mexico. Specifically, objectives
of this research were to quantify spa-
tial and temporal patterns of habitat
use by S. dumerili and to determine
age, hatching-date, growth, and mor-
tality of S. dumerili by using otolith-
based techniques.
Thompson, B. A., C. A. Wilson, J. H.
Render, M. Beasley, and C. Cauthron.
1992. Age, growth, and reproductive
biology of greater amberjack and cobia
from Louisiana waters. Final report
NA90AA-H-MF722, 77 p. Marine Fish-
eries Initiative (MARFIN) program.
National Marine Fisheries Service,
NOAA, St. Petersburg, FL.
546
Fishery Bulletin 102(3)
96 00' W 95
i i
50' W
94 : 40'W
i
94
00'W
93-20'W
i
30
00' N"
/ ^STUDY *
\ I
"7 SITE ;v
\
Louisiana
29
20' N"
Galveston. TX
Inshore
zone y
Offshore
,'T----
zone
/"
28c
40' NJ
^)r^ >"■--
_ .. ~ t~
'; /'
28
00' N-
20 m depth contour
t
N
25 km
Figure 1
Map of sampling locations along the Texas Gulf coast for
S. dumerili. Inshore (<15 nautical miles) and offshore (>15
nautical miles I zones off Galveston, TX, are shown.
Materials and methods
Field collections
Seriola dumerili associated with pelagic Sar-gassum mats
were collected off Galveston, Texas, from May to July
over a two-year period (2000 and 2001) (Fig. 1). Inshore
(<15 nautical miles |nmi]) and offshore (15-70 nmil
zones were sampled to evaluate the potential importance
of physiochemical conditions because inshore waters off
the coast of Texas are heavily influenced by estuarine
processes (Smith, 1980; Sahl et al., 1993). Replicate
samples (3-5 per trip) in both the inshore and offshore
zones were collected monthly by using a larval purse
seine (20 m long x 3.3 m deep, 1000-pm mesh). The purse
seine was deployed into the water as the boat encircled a
randomly chosen mat. The seine was pursed, the Sargas-
sum was discarded, and fishes were tunneled into the
codend, collected, and frozen on dry ice. Distribution and
abundance were expressed as relative abundance, and
catch per unit of effort (CPUE) represented the number
of fishes per purse-seine collection. In addition, a small
number of YOY S. dumerili were collected with hook-
and-line for age and growth information only. Standard
lengths (SL) were measured to the nearest 0.1 mm, and
weights to the nearest 0.1 g before otolith extraction.
GPS locations and mat volume (lengthx widthxdepthi
were recorded at each sample location. Environmental
parameters measured included sea surface temperature,
salinity, and dissolved oxygen. Daily sea surface tem-
perature data were also taken from NOAA buoy 42035,
22 nmi offshore of Galveston, TX.
Otolith procedures
Sagittal otoliths were extracted from S. dumerili. Oto-
liths were measured to the nearest 0.001 mm and
weighed to the nearest 0.0001 g. Left or right sagittae
were randomly selected and mounted in epoxy resin
(Spurr, 1969). Once mounted, a Buehler isomet low-
speed saw equipped with a diamond wafering blade
was used to transversely cut embedded otoliths. Otolith
sections were then attached to petrographic slides with
Crystalbond thermoplastic cement. Type A alumina
powder 1 0.3 fim) and 400- and 600-grit sandpaper were
used to grind both sides of the otolith, and a polishing
cloth was used for final preparations.
Age was determined by counting growth increments
along the sulcus from the core to the outer margin by
using a Nikon Labophot-2 light microscope and Opti-
mas 6.2 image analysis software (Media Cybernetics,
Silver Spring, MD). Because of the difficulty of enu-
merating some inner increments near the otolith core,
a relationship between age and otolith radius of several
clear specimens was used to predict the number of
increments within the unclear region. Age was deter-
mined by adding the correction factor to the increment
count from the first identifiable increment to the otolith
margin (Rooker and Holt, 1997). Correction factors
consisting of mure than five days were applied to 499r
Wells and Rooker: Distribution, age, and growth of young-of-the-year Senola dumerili
547
of the fishes and the average correction accounted for
9.5% of the actual age estimate. Otolith readings with
correction factors accounting for more than 20% of the
predicted age were not used for estimates of growth.
The following correction factor was used
Age (d) = 2.88 x otolith radius (jUm) - 0.096
(r2 = 0.88, n=20).
Additionally, all otolith counts were repeated twice
to ensure adequate precision. Differences in readings
of more than 20% were not incorporated into growth
estimates.
Daily deposition of growth increments on sagit-
tal otoliths was validated by using wild S. dumerili
(re=14, 136-193 mm SL). Fishes caught in the wild
were brought into the laboratory and placed in a cir-
cular holding tank (1.71 m diameterx0.75 m depth)
for 48 hours. Fishes were then placed in a separate
tank containing 80 liters of seawater with 100 mg/L of
alizarin complexone for two hours (Thomas et al., 1995)
and returned to the circular holding tank. Individuals
were fed approximately 10% of their body weight daily.
Fishes marked with alizarin were removed from the
tank after 5 (;? = 5), 10 (n=5), and 15 (n=4) days. The
number of otolith increments between the alizarin mark
and outer edge were then counted for daily increment
verification. Otolith slides were coded so that all read-
ings were blind.
Hatching dates were determined for all individuals
by subtracting daily age from date of capture. An age-
specific mortality adjustment was made for individuals
because larger S. dumerili have spent more time in
the early life stages and hence individuals from these
cohorts have experienced greater cumulative mortality.
Because of the limited number of individuals in 2001,
the mortality correction was calculated only for year
2000 collections and applied to hatching-date distribu-
tions in 2000 and 2001. Age-specific mortality adjust-
ments were made according to the method described by
Rooker and Holt (1997).
Growth and mortality of S. dumerili were estimated
by using otolith-derived ages. Daily growth rates were
estimated by using the linear growth equation
SL - slope (age) + y-intercept
and were reported as mm/d. Length-at-age data were
also fitted with curvilinear growth models (von Ber-
talanffy, Laird-Gompertz). Percent variation in length
explained by age for both curvilinear models was slightly
better at times than the percent variation in length
explained by age for the linear model; however, certain
model parameters (i.e. LJ were biologically unrealistic
and thus the linear model was deemed more appropri-
ate. Moreover, when possible, L_ values were used to
model length-at-age data and the nonlinear models were
essentially linear over the limited size range examined.
Mortality estimates for year 2000 S. dumerili were
determined by using a regression on the decline in log(>-
transformed abundance on age. A regression coefficient
(slope) was used to predict the instantaneous mortality
rate:
\r\N, = ln7V0 - Zt,
where Nt = abundance at age t (expressed in days);
N0 = an estimate of abundance at hatching;
and
Z (slope) = the instantaneous mortality coefficient.
Mortality estimates were based upon 10-day cohort
groupings. Individuals <40 days old were not included
in the mortality regression because of an ascending
catch curve and because there were too few individuals
>139 days old in our sample — probably owing to gear
avoidance or emigration (or both). Therefore, only S.
dumerili between 40 and 139 days (45-192 mm) were
used to estimate mortality.
Data analysis
Effects of location and date on CPUE and size estimates
were examined by using a two-way analysis of vari-
ance (ANOVA). Levene's test and residual examination
established if the homogeneity of variance assumption
was met. Normality was evaluated by plotting residuals
versus expected values. Abundance data were log (.v+1)
transformed when necessary to normalize data and
reduce heteroscedasticity. Tukey's honestly significant
difference ( HSD ) test was used to determine a posteriori
differences among means. Comparisons of spatial and
temporal variation in growth were performed by using
analysis of covariance (ANCOVA). Prior to ANCOVA
testing, the homogeneity of slopes assumption was exam-
ined using an interaction regression (Ott, 1993). If no
significant interaction was detected, ANCOVA models
were used to test for differences in length-at-age (y-
intercepts) (Ott, 1993). Statistical analysis was car-
ried out by using SYSTAT 8.0 (SYSTAT Software Inc.,
Richmond, CA), and significance was set at the alpha
level of 0.05.
Results
Environmental conditions
Average temperatures from May to July ranged from
27.9 to 30.1°C in 2000 and from 24.5 to 30.4°C in 2001
(Fig. 2). Mean temperatures over the sampling period
were 29.2°C and 27.9°C for 2000 and 2001, respectively.
Zonal differences occurred: the inshore zone averaged
28.7°C (±0.3) in 2000 and 28.1°C (±0.9) in 2001, and
the offshore zone averaged 29.8°C (±0.3) in 2000 and
27.6°C (±0.9) in 2001. Similar to temperature trends,
mean salinity was higher in 2000 (34.6%< ) than in 2001
(31.9%o) (Fig. 2). Average salinity values gradually
increased from an average of 31.5%o in May to 37.2%r in
July of 2000. A large drop in salinity occurred during
548
Fishery Bulletin 102(3)
mid-summer of 2001, from 37.6r/ic in May to
25.7'7<c in June (owing to tropical storm Allison)
and rose to 32. 3^ in July. Salinity values were
lower and more variable within the inshore zone,
ranging from 29f« to 37^ (33.4%« average) in
2000 and from 15%c to 37%o (average 28.87« ) in
2001. In contrast, the offshore zone exhibited
higher and more stable salinity values, ranging
between 337fc and 38f;< (36%< average) in 2000,
and between 287« and 36%f (34.97« average)
in 2001. Temperature and salinity values are
likely to be influenced by variation in precipita-
tion between years. Precipitation from January
through July of 2000 (14.29 inches) was half that
of 2001 (29.92 inches) and well below the 30-year
average of 22.17 inches (National Weather Ser-
vice, Dickinson, TX). Dissolved oxygen content
was similar between years; values decreased
throughout the summer months and were higher
within the inshore zone.
Spatial and temporal distribution
A total of 181 YOY S. dumerili was collected
from 42 purse seines over the two-year study
period. CPUE values were fourfold higher in
2000 than in 2001. averaging 6.38 (±3.0) and
1.50 (±0.8) per seine, respectively (Fig. 3A).
A significant year effect indicated that rela-
tive abundance was higher in 2000 (P= 0.019).
Additionally, CPUE values were higher in the
offshore zone in both years (Fig. 3, B and C).
However, no significant zonal difference existed in abun-
dance between the inshore and offshore zones in 2000
(P=0.063) or 2001 (P=0.058). Temporal patterns indi-
cated S. dumerili was highly abundant in May and June,
declining in July in both years (Fig. 3A). A significant
seasonal effect occurred for 2000 when highest relative
abundance occurred in June with a CPUE of 16.2 (±0.8)
(Tukey HSD, P<0.05).
Size comparison
Sizes of S. dumerili ranged from 33 to 210 mm SL
(mean 125 mm SL ±3.8). Juveniles greater than 100
mm accounted for 68% of the total catch, whereas indi-
viduals less than 50 mm accounted for only 15%. Size
differences of S. dumerili were observed between 2000
(average 125.5 mm) and 2001 (average 141.5 mm); sig-
nificantly larger S. dumerili were collected from the
offshore zone in 2001 (P=0.001). A significant interaction
(yearxmonth) occurred that indicated that the magni-
tude of size differences was variable over time. Sizes
were also significantly different between zones in 2000;
larger individuals were collected within the offshore zone
(P=0.025). No zonal comparison was performed for 2001
because few individuals were collected from the inshore
zone. In addition, a trend existed within both years:
mean sizes significantly increased from May to June,
then decreased in July (Tukey HSD, P<0.05).
40 -
A Temperature 2^°
- 40
35 -
30 -
A Buoy temperature e>~-~~^'^
O Salinity a — - — ■
- 35
- 30
25 -
^*<^*~~
- 25
20 -
15 -
^^^^^
- 20
£ 2T
- 15
10 -
- 10
o 5-
- 5
U i i i i i i \j uj
2? Jan Feb Mar Apr May June July =
CO ^
CD
if 40 -
A Temperature n ^UUl
"40 i
H 35 -
A Buoy temperature ^v
- 35
30 -
O Salinity \. -^^L
- 30
25 -
Jr-—***^^
- 25
20 -
^^~
- 20
15 -
tr-——*^^^
~ 15
10 -
- 10
5 -
- 5
0
0
■ i i i i i
Jan Feb Mar Apr May June July
Month
Figure 2
Environmental conditions from January to July of 2000 and
2001. Average temperature (°C) and salinity ('«) values. Open
triangles represent temperature data from NOAA buoy 42035,
located 22 nautical miles offshore of Galveston, TX.
Hatching-date distribution
Hatching-date distributions for S. dumerili were pro-
tracted in both 2000 and 2001. Fishes collected in 2000
exhibited hatching-dates from 29 January to 25 May
(117 days), whereas those collected in 2001 hatched
from 11 January to 30 May (139 days) (Fig. 4). In 2000,
over 80% of the fishes appeared to result from spawning
events in March and early April. The adjusted distri-
butions from the age-specific mortality correction for
both 2000 and 2001 were indistinguishable from those
without the correction.
Age and growth
Results of the age-validation exercise indicated that
juvenile S. dumerili deposit otolith increments on a
daily basis (Fig. 5). Average increment counts at day
5, 10, and 15 were 4.8 (±0.2 SD), 9.2 (±0.4), and 14.0
(±0.7), respectively. A relationship between the observed
versus expected increments was described by the follow-
ing equation:
Observed increments - 0.92 (expected increments) + 0.14
(r2=0.95)
where days after staining represent expected increment
count.
Wells and Rooker: Distribution, age, and growth of young-of-the-year Senola dumenli
549
Validation of daily growth increments has been ob-
served in a similar study involving juvenile (0-60
days) Seriola quinqueradiata (Sakakura and Tsuka-
moto, 1997).
Age of S. dumerili was similar between years; es-
timated ages ranged from 41 to 150 days (35 to 210
mm SL) in 2000 and from 35 to 120 days (33 to 198
mm SL) in 2001 (Fig. 6). Interannual differences in
growth were observed: 2000 (1.65 mm/d). 2001 (2.00
mm/d) (ANCOVA, slope, P<0.001) (Fig. 7). A signifi-
cant cohort effect was also observed; the late-season
(April) cohort experienced the fastest growth (ANCO-
VA, slopes, P<0.001) (Fig. 8). Average cohort-specific
growth rates of S. dumerili spawned in February,
March, and April of 2000 were 0.85 mm/d, 1.15 mm/d,
and 2.76 mm/d, respectively. In addition, a signifi-
cant difference in growth was observed for S. du-
merili collected from inshore (1.55 mm/d) and offshore
(1.65 mm/d) zones of 2000 (ANCOVA, slope, P<0.001)
(Fig. 9). Again, the lack of individuals within the in-
shore zone in 2001 precluded a comparison between
zones for that year.
Mortality
Owing to the limited number of S. dumerili collected
in 2001, a single catch curve was developed for the
2000 year class, and the mortality coefficient (Z) was
0.0045 (0.45%/d) for individuals between 40 and 139
days (Fig. 10). Cumulative mortality was estimated
for the 100-day period (40-139 days), resulting in an
overall mortality of 36%.
20
15
10
5
0
1 A
□ 2000
■ 2001
MAY
JUNE
JULY
40 "
UJ 30 -
B
□ Offshore
■ Inshore
z>
CL
O 20-
T
10 -
o-
1
MAY
JUNE
JULY
o -
8 -
6 -
c
4 J
2 "
U
□ Offshore
■ Inshore
r^i^
MAY
JUNE
Months
JULY
Figure 3
Relative abundance (number per purse seine) (±1 SE)
of S. dumerili collected in association with Sargassum
mats: (A) 2000 and 2001: (B) 2000 by zones; (C) 2001
bv zones.
Discussion
The size range of S. dumerili collected in association
with Sargassum ranged from approximately 30 to 210
mm (SL), and these sizes are similar to those reported in
other studies investigating fish assemblages associated
with pelagic Sargassum. Bortone et al. (1977) collected
several small S. dumerili (12-72 mm SL) in the eastern
Gulf, whereas individuals collected in the western Atlan-
tic by Dooley (1972) ranged from 13 to 108 mm (SL).
Cho et al. (2001) found juvenile S. dumerili (35-120 mm
TL) associated with drifting Sargassum in the western
Pacific. Additionally, Sakakura and Tsukamoto (1997)
collected over 200 juvenile Japanese amberjack (S. quin-
queradiata) (18-114 mm TL) associated with pelagic
Sargassum in the East China Sea. Results of the present
study and others indicate that pelagic Sargassum mats
in the NW Gulf of Mexico serve as nursery habitat for
S. dumerili.
The limited size range of S. dumerili associated with
pelagic Sargassum indicates that a shift in habitat use
may occur at approximately 5-6 months of age. Indi-
viduals greater than 210 mm (SL) have not been found
in association with pelagic Sargassum, and larger S.
dumerili (ca. 300 mm TL) are relatively common in the
recreational headboat fishery in the Gulf of Mexico (Ma-
nooch and Potts, 1997a). As a consequence, S. dumerili
may transition from a pelagic to a demersal existence
at the late juvenile stage (between 200 mm SL and
300 mm TL). Pipitone and Andaloro (1995) found a shift
in the diet of S. dumerili, from a diet predominately
consisting of crustaceans toward one of fish >200 mm
(SL), further supporting this hypothesis.
Seriola dumerili abundance was greater in the off-
shore zone than the inshore zone throughout the sam-
pling period. These patterns of habitat use are consis-
tent with earlier information that indicates S. dumerili
is an offshore species (Hildebrand and Cable, 1930).
The proximity to spawning grounds may contribute to
the observed spatial patterns because S. dumerili are
known to spawn in offshore areas (Fahay, 1975). Physi-
ological preferences may also contribute to the domi-
nance of S. dumerili in the offshore zone. In our study,
salinity values were higher in the offshore zone but
more variable within the inshore zone, suggesting that
freshwater inflow influences conditions within the in-
shore zone. Chen et al. (1997) determined that optimum
salinity conditions for S. dumerili larvae were between
32%<r and 35%t, and larvae remained inactive below a
salinity of 30%<r. Zonal differences in temperature and
dissolved oxygen were also observed. Tzeng et al. (1997)
550
Fishery Bulletin 102(3)
6-
5 "
4
3
2
7-
6
5 •
4
3
2
1
0
2000
r- t- cy
,- -r- CM
CO U">
l- i- CM
2001
T- T- C\J
t- r> ■* *-
CO Rl <- CM
t- *- CN
CO CO CO
Hatching date
Figure 4
Hatch-date distributions of S. dumerili associated with Sargassum mats
in 2000 and 2001.
16 i
£
14 -
/ &
f* /
12 -
/ 0
CD
S/
E 10 -
tft/
cd
'/rV
CJ
''/
£ 8 -
'/ °
o
CD c
a ° -
ty
E
&y
3
Z 4 -
/ Increments (expected)
2 -
/ O Increments (observed)
u I I I I I I 1 1
0 2 4 6 8 10 12 14 16
Days after staining
Figure 5
Linear regression of age verification for S.
dumerili. Circles and solid line represent the
number of daily increments observed after
staining, and dotted line represents the number
of increments expected.
attributed the distribution of fishes from nearshore to
offshore stations to environmental factors, season, and
life history strategies. Furthermore, the combination of
available resources (i.e. food and habitat), seasons, and
physiochemical tolerances may account for the observed
spatial patterns of habitat use.
Temporal patterns of size-specific habitat use showed
similar trends between years and appeared to be relat-
ed to spawning season. Relative abundance of small S.
dumerili was highest early in the season (May), declined
in June, and further increased late into the season
(July) for both 2000 and 2001. Nevertheless, small juve-
niles were collected during the entire collection period,
which suggests that S. dumerili spawning in the NW
Gulf is protracted. Previous studies have found that
S. dumerili spawn throughout the spring and summer
months ( March- July) (Marino et al., 1995; Cummings
and McClellan, 1996). In addition, Fahay (1975) sug-
gested, on the basis of larval collections in the western
Atlantic, that spawning occurs in the winter. Despite
the limited duration of our collection efforts, our results
are consistent with these findings with 63% of year-
2000 S. dumerili and 36f> of year-2001 fish resulting
from spring spawning events. The remaining individu-
als were spawned January through early March.
Growth estimates indicated that S. dumerili have
rapid growth throughout early life stages. Based on
linear growth models, average growth of S. dumerili
was 1.45 mm/d — an estimate similar to that of Manooch
and Potts's (1997b) study in the Gulf (average growth of
1.17 mm/d for age-1 individuals). However, growth com-
parisons may be invalid because their study estimated
growth based on counts of annuli and no temperature
Wells and Rooker: Distribution, age, and growth of young-of-the-year Senolo dumerili
551
data were presented. Because of the lack of studies
investigating growth of YOY S. dumerili, we compared
our estimates to those in Sakakura and Tsukamoto's
(1997) study of YOY S. quinqueradiata where growth
rates were estimated at 1.3 mm/d. Average temperature
in their study was 21.2°C, which was considerably lower
than the average during our study (28.6°C) and may
account for their slower growth rates.
Variation in growth of S. dumerili was observed and
rates were significantly higher in the offshore zone
and greater for the late season cohort. Differences in
water temperature may be partly responsible for ob-
served differences in growth. Planes et al. (1999) sug-
gested that spatial differences in growth of juvenile
sparid fishes were a result of water temperature and
currents. The proximity between zones in this study
may have masked differences in hydrography; however,
temperatures were higher in the offshore zone (29.8°C,
CV=0.03) than in the inshore zone (28.7°C, CV=0.04),
and warmer temperatures were likely contributing to
faster growth rates in offshore waters. Intra-annual
(cohort-specific) growth patterns indicated that the late-
season cohort had the fastest growth. Similar to trends
between zones, temperature was lowest for the slowest
growing cohort (early season) and highest for the fast-
est growing cohort (late season). Although temperature
may affect early life growth of S. dumerili, differences
in growth may be attributed to other factors such as
prey availability and predator activity (Houde, 1987;
Paperno et al., 2000; Plaganyi et al., 2000). Moreover,
a clear distinction exists in the size classes of YOY S.
dumerili in comparisons of growth rates and these dif-
ferences likely contribute to the observed results.
The mortality rate of YOY S. dumerili associated with
pelagic Sargassum was estimated at 0.45 %/d for fishes
4-1
2-
0-
8"
6"
2000
4-
2 r
...M„.
- f "
.-d-Lo-n
2001
mm
^ w n n
Age class (days)
Figure 6
Age-frequency distribution of S. dumerili collected in
association with Sargassum in 2000 and 2001.
collected in 2000. These findings are well below similar
studies investigating mortality of YOY individuals. Nelson
(1998) calculated a mortality estimate of 2.1-2.3^/d for
pinfish in three different bay areas in the eastern Gulf of
Mexico. In addition, Deegan (1990) estimated YOY men-
haden mortality between 1.7 and 2.1'S/d in the northern
250"
,' a
200"
A
t&y^u D
E
A°£a$
$ffi^°
~X 150 -
a Lt^PSjaKi-
CT
J^r
0>
■Vx D
"D
/y
ffl 100 -
/?
"D
C
ns
CO
*P D
50 -
/Z&
fSS -B- 2000
SL= 1.65Mge)-15.33
r2=0.86
-A- 2001
Si. = 2.00(/lc;e)-37.32
r = 0 95
0
1 '
' ' '
0 20 40
60 80 1 00
Age (days)
Figure 7
120 140 160
Age-length relationship
of S. dumerili determined with linear
growth curves for inters
nnual comparison.
552
Fishery Bulletin 102(3)
250 "
Standard length (mm)
O en O
o o o
s.*£ o
a/ -&- February SU 0 85(4ge)+65.12
MT° i2 = 0.34
50 -
Djfl
Van ~°~ March SL = 1 1 5(4ge)+40 69
r = 0.55
-a— April SL=2 76(Age)-80 48
^=0 95
1 '
I t i
0 20 40
60 80 100 120 140 160
Age (days)
Figure 8
Age-length relationship
of S. dumerili determined with linear
growth curves for a com
parison of cohorts of different hatching
dates in 2000.
250 "
200 -
E
P
s'
/
y
/ a
_□
0 n & B}flO
Standard length (
en o oi
o o o
^JSsS —*- Inshore SL = 1 55{Age)-\2 11
'rffi' f = 0.74
-a- Offshore SL = 1.65(/*ge)-15.33
o ■
^ = 086
0 20 40 60 80 100 120 140 160
Age (days)
Figure 9
Age-length relationship of S. dumerili determined with linear
growth curves for a comparison of zones in 2000.
Gulf. These studies included estuarine-dependent spe-
cies and consisted of smaller individuals. Because our
estimates were limited to age 40-139 d individuals, the
lack of smaller fishes precluded any mortality estimates
of younger S. dumerili. These estimates provide baseline
information on mortality of YOY S. dumerili; however,
more detailed studies will be needed to adequately de-
termine mortality rates of YOY S. dumerili.
Based on observed patterns of distribution and
growth in the NW Gulf of Mexico, early life survival of
S. dumerili may depend on pelagic Sargassum. Results
of this study suggest that S. dumerili are associated
with this habitat over a limited size range and exhibit
rapid growth during the first six months. Addition-
ally, S. dumerili were more abundant and exhibited
higher growth in offshore areas where potential spawn-
ing may occur. Thus, Sargassum appears to provide
nursery habitat for YOY S. dumerili, and may influ-
ence the recruitment potential of this valuable fishery-
species.
Wells and Rooker: Distribution, age, and growth of young-of-the-year Senola dumerili
553
Log.W = 1 506-0 0045(4ge)
x r =0.315
"i i.o -
CD
■D
C
CD
* 0.5 -
en
O
_l
♦
♦
O OO OOOOOOOO o O OOO
i-c\jcr>"^-mcDr--.oocr)oi-CMco-^-ir)
Age (days)
Figure 10
Mortality curve of S. dumerili based upon regression plot of loge
abundance on age of individuals collected in 2000.
Acknowledgments
We thank J. Harper, M. Lowe, B. Geary, J. Turner,
and J. Wells for their assistance in the field. Fund-
ing for this project was provided by The Aquarium at
Moody Gardens (grant 479005 to JRR). Top Hatt char-
ters provided boat time offshore, and Kirk Winemiller
and Jaime Alvarado offered constructive criticism and
suggestions.
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555
Identification of formalin-preserved eggs of
red sea bream iPagrus major) (Pisces: Sparidae)
using monoclonal antibodies
Shingo Hiroishi
Yasutaka Yuki
Eriko Yuruzume
Faculty of Biotechnology
Fukui Prefectural University
1-1 Gakuen-cho
Obama City, 917-0003 Fukui, Japan
E-mail address (for S Hiroishi), hiroishi@fpu.ac.|p
Yosuke Onishi
Tomoji Ikeda
Hironobu Komaki
Kansai Environmental Engineer Center
1-3-5 Azuchi-cho, Chuo-ku
Osaka City, 541-0052 Osaka, Japan
Muneo Okiyama
Ocean Research Institute
University of Tokyo
1-15-1 Minamidai, Nakano-ku,
Tokyo, Japan
Catches of important commercial fish
such as red sea bream, fiat fish, and
yellowtail are decreasing in Japan.
In order to sustain these species it is
especially important that their distri-
bution and biomass at all life stages
are known. However, information on
the early life stages of these species is
limited because identifying the eggs
and larvae of such fish is sometimes
extremely difficult.
Mito (1960, 1979) and Ikeda and
Mito (1988) developed methods for
identifying pelagic fish eggs based on
morphological features. However, their
methods have limitations because
many unidentified eggs have similar
features. In addition, eggs are usu-
ally fixed in formaldehyde solution
just after collection in the field. This
procedure may alter several egg char-
acteristics and therefore prevent iden-
tification (Ikeda and Mito, 1988), or
make identification difficult when the
egg diameter measures 0.8-1.0 mm
because so many kinds of eggs fall in
that range. Thus, an alternative iden-
tification method would be useful.
Effective genetic analyses for iden-
tifying fish eggs or larvae (or both)
have been developed by Graves et al.
(1989), Daniel and Graves (1994),
and Shao et al. (2002). However,
their methods may have limitations
if samples are preserved in formal-
dehyde for several years or if DNA
must be extracted from numerous
samples. In addition, we are lacking
the DNA sequences for many species
sequences that are necessary for iden-
tifying eggs in the field.
We have successfully produced
monoclonal antibodies to differenti-
ate harmful marine phytoplankton
species from morphologically simi-
lar harmless species (Hiroishi et
al., 1988; Nagasaki et al., 1991b;
Sako et al., 1993; Vrieling et al.,
1993; Hiroishi et al., 2002) as well
as Microcystis, a toxic fresh water
bloom-forming cyanobacteria (Kondo
et al., 1998). These antibodies were
obtained from a culture supernatant
solution of hybridoma cells that was
produced by a cell fusion procedure
between myeloma cells and antibody-
producing spleen cells. The specific
antibodies described above could be
used to detect and quantify harmful
bloom-forming microorganisms that
react with the monoclonal antibod-
ies and that secondarily react with
fluorescein isothiocyanate conjugated
goat anti-mouse Ig(G+M) antibody.
With fluorescence microscopy with
B-exciting light, yellowish fluorescein
coronas around the cells of the toxic
species were observed, confirming a
positive reaction. These antibodies
can recognize different molecules
distributed on the cell surface, even
when the organisms have similar
morphological features. One of the
molecules distributed on Chattonella
was determined to be glycoprotein
(Nagasaki et al., 1991a). This method
would help us to differentiate small
marine organisms like fish eggs.
Red sea bream (Pagrus major)
(Table 1) eggs can easily be distin-
guished from those of other sparids
also found in Japan, such as Acan-
thopagrus latus, by differences in egg
size and spawning seasons, and from
those of Evynnis japonica by differ-
ences in spawning seasons (Ikeda
and Mito, 1988; Kinoshita, 1988;
Hayashi. 2000). However, eggs of
some sparids, such as Aeanthopagrus
schlegeli, Sparus sarba, and Dentex
tumifrons are extremely difficult to
distinguish from eggs of P. major.
Therefore, we developed monoclonal
antibodies that allow P. major eggs
to be clearly identified by immuno-
staining, thus differentiating them
from other similar sparids.
This technique may be a useful
new tool for identifying fish eggs.
Here, we report a method for identi-
fying P. major eggs using monoclonal
antibodies developed to react specifi-
cally with the eggs.
Materials and methods
Eggs of P. major were obtained from
adult female fish that had spawned in
Manuscript submitted 4 April 2003
to Scientific Editor's Office.
Manuscript approved for publication
2 March 2004 by the Scientific Editor.
Fish. Bull. 102:555-560 (20041.
556
Fishery Bulletin 102(3)
Table 1
Characteristics of Sparidae distributed in Japan.
Egg oil globule
Suborder
Species
Distribution
Spawning season
Egg size (mmi
size (mm)
Pagrinae
Pagrus major
South of Hokkaido I Coastal)
Mar-May
0.90-1.03
0.19-0.25
Evynnis jappon ica
South of Hokkaido (Coastal)
Oct-Dec
0.89-0.98
0.19-0.21
Sparinae
Acanthopagrus schlegi
li South of Hokkaido (Coastal)
Mar-Jun
0.83-0.91
0.20-0.22
Acanthopagrus latus
South Japan (Coastal)
Oct-Nov
0.76-0.81
0.2
Sparus sarba
South Japan (Coastal)
Apr-Jun
0.88-0.92
0.19-0.22
Denticinae
Dentex tumifrons
South Japan (Oceanic)
May-Jun
0.90-0.93
0.19
isolation tanks at several sea farming centers described
in Table 2. Immediately after collection, fish eggs were
fixed in a solution of 57c formaldehyde to sea water solu-
tion and stored. Before use, the eggs were thoroughly
washed with distilled water and suspended in phosphate
buffered saline (PBS) solution.
Monoclonal antibodies were developed according to
the methods of Kdhler and Milstein (1975), Garfre and
Milstein (1981), and Hiroishi et al. (1984, 1988): 0.5 mL
of egg suspension (200 eggs/PBS solution from Fukui
Prefectural Sea Farming Center, Obama City, Fukui
Prefecture) was mixed with 0.5 mL Freund's complete
adjuvant (Nacalai Tesque, Inc., Kyoto, Japan). The mix-
ture were then injected subcutaneously into BALB/c
female mice (4 weeks of age). The female mice received
second and third injections at 2-week intervals. For the
final immunization, P. major eggs collected in the sea
farming center of Kansai Environmental Engineering
Center Co. (Miyazu City, Kyoto, Japan) were injected
into the mouse after being emulsified with Freund's
incomplete adjuvant (Nacalai Tesque, Inc.). Three days
after the final immunization, the spleens of the mice
were removed and passed through a mesh (mesh size:
100 urn). The spleen cells obtained by this procedure
were fused with the myeloma cell line X63-AG8.653
at a ratio of 10:1 with 50% polyethylene glycol. After
cell fusion, hybrid cells were incubated in a selective
hypoxanthine-aminopterin-thymidine medium (Kohler,
1979; Garfre and Milstein, 1981).
The reactivity of the antibodies produced by the hy-
bridomas was then determined. Eggs fixed with 57c
formaldehyde in seawater were washed with PBS solu-
tion in a 96-well plate. Throughout the experiments,
the principal eggs used were from the Fukui Prefec-
tural Sea Farming Center. Normal horse serum solution
(200 jUL), diluted 100-fold with PBS, was added to the
wells to prevent any nonspecific reactions. After incuba-
tion at room temperature for 20 minutes, the eggs were
washed with 200 pL of PBS. After removing the PBS,
200 fih of the hybridoma culture supernatant solution
was added to the wells and incubated at room tempera-
ture for 30 minutes. After washing with PBS (100 /jL),
biotinylated horse anti-mouse IgG (100 pL) was added
to the wells and incubated at room temperature for 20
minutes. After the incubation, VECTASTAINR ABC re-
agent (avidin DH + biotinylated horseradish peroxidase/
PBS, 100 jjL) was added according to the direction of
VECTASTAINR Elite ABC kit (ABC Mouse IgG Kit, Fu-
nakoshi Co., Tokyo, Japan). After immunostaining the
eggs were observed by stereoscopic microscopy ( SMZ-2T,
Nikon Co., Tokyo, Japan). In a positive reaction, the
surface of the fish egg was stained brown as a result
of the oxidation of 3,3'-diaminobenzidine (substrate)
by horseradish peroxidase bound to the egg surface by
the antibody.
Unidentified pelagic fish eggs from open water were
collected by using a plankton net (MTD net, NGG54
with mesh size of 0.344 mm, Rigo Co., Tokyo, Japan)
from Wakasa Bay (Fukui Prefecture, Japan) in May
1997. They were fixed with 59c formaldehyde in sea
water, either immediately or after incubation in seawa-
ter in finger bowls at 20°C for 24 hours, and identified
by careful observation as described by Ikeda and Mito
(1988) and Ikeda et al. (1991). The fixed eggs were
transferred to net wells (mesh size 200 ^m, diameter 24
mm, Corning Incorporated, Corning, NY) and washed
with 10 mL of distilled water three times. Then the
eggs in the netwells were immersed in 100 mL of PBS
in a polystyrene tray (Corning Incorporated, Corning,
NY) for 5 minutes. The egg suspension was placed into
the wells of a six-well plate and incubated with 10 mL
of normal horse serum solution for 20 minutes. After
incubation, the eggs were incubated with 10 mL of MT-1
antibody solution (hybridoma culture supernatant) and
then incubated with 10 mL of biotinylated horse anti-
mouse IgG. The subsequent procedure was performed
as described above.
The immunoglobulin subclass of monoclonal antibod-
ies was determined according to the directions of the
mouse monoclonal antibody isotyping kit (Amersham
Pharmacia Biotech Co., Uppsala, Sweden) as follows:
3 mL of monoclonal antibodies solution (hybridoma
supernatant solution) obtained in this study was added
to 0.3 mL of horseradish peroxidase-conjugated anti-
mouse IgG in the kit. An isotyping stick in the kit
was incubated with the above solution at room tern-
NOTE Hiroishi et al.: Identification of Pagus ma/or eggs using monoclonal antibodies
557
perature for 15 minutes. Then
the stick was washed with 0.1%
Tween 20/PBS, and incubated
with 4-chloro-l-naphthol solution
(substrate of horseradish peroxi-
dase in the kit) containing 0.1%
H202 at room temperature for
15 minutes. The immunoglobu-
lin subclass of the monoclonal
antibodies was determined by
observing the positions of bands
that appeared on the stick.
Results and discussion
After cell fusion, hybridomas
were grown in 42 wells of 96-
well plates. Supernatant solu-
tions of the cultures were used
for the immunostaining assay
to select hybridomas producing
antibodies reactive to P. major
eggs. After the assay, positive
reactions were observed in six
wells. These hybridomas were
cloned by the limiting dilution
method, and finally three clones
producing monoclonal antibod-
ies reactive with P. major were
obtained. Those antibodies were
named MT-1, MT-2, and MT-3.
The subclass of all antibodies
was IgGj. Specificity of the anti-
bodies was examined by using
the eggs shown in Table 2. As a
result, the antibodies were reac-
tive with all the P. major eggs
in both the early and late stages
(before or after tail-bud stage),
but not with eggs of other species
(Table 3, Fig. 1). Thus, it becomes
possible to identify P. major eggs.
The immunostaining assay took
2.5 hours.
The oldest eggs of P. major (20
April, 1995) could react with the
antibodies obtained as clearly
as the recently collected eggs
of P. major, indicating that egg
samples preserved for up to 7
years could be analyzed by this
method.
The method was also success-
ful with 102 eggs collected from
Wakasa Bay (Table 4), which
had been immediately fixed with
5% formaldehyde in seawater.
Among them, only 11 eggs were
identified as Callionymoidei spp.
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558
Fishery Bulletin 102(3)
(type II). The remaining 91 unidentified eggs were di-
vided into three groups (types I, III, and IV) based on
diameters. Of these 91, 51 type-II eggs reacted with
MT-1. This finding is compatible with the possibility
that the eggs were P. major, because the size was simi-
lar to that of P. major and each contained a single oil
globule of a similar size (Tables 1 and 4). Another 43
eggs were collected from another area of Wakasa Bay
(Table 5). None of the eggs fixed just after collection
Table 3
Reactivity of monoclonal antibodies to fish eggs. + repre-
sents positive reaction; - represents negative reaction.
Reactivity
Egg no.
Species
MT-1 MT-2 MT-3
1
Pagrus major
+
2
+
3
+
4
+
5
+
6
+
7
+
8
+
9
Acanthopagrus schlegeli
-
10
-
11
-
12
-
13
-
14
Acanthopagrus latus
-
15
Sparus sarba
-
16
Dentex tumifrons
-
17
Paralichthys olivaceus
-
18
-
19
-
20
-
21
Engraulis japonica
-
were morphologically identifiable. But, after incuba-
tion at 20°C for 24 hours until the late stage, all six
eggs identified as P. major were reactive with the an-
tibody MT-1, whereas the others were not. These find-
ings strongly suggest that the method developed in this
study is useful for identifying P. major eggs in seawater.
Although only late stage eggs were used in this experi-
ment, early stage eggs are also detectable because the
antibody recognized both stages of P. major eggs from
several sea farming centers (Table 2).
Compared to genetic analysis of fish eggs, this method
has the advantage of being able to assay many eggs
simultaneously without the need to separate individual
eggs in tubes and without extracting DNA from the in-
dividual egg in each tube. Further, this method works
with formalin-fixed eggs, whereas extraction of DNA
from formalin-fixed material is problematic. Plankton
samples from field studies are typically fixed in forma-
lin-seawater solution.
There was no problem obtaining a large amount of
the monoclonal antibody required when identifying P.
major eggs. The antibody can be easily obtained by
large-scale cultures of hybridoma cells. About 50 mL
of antibody solution was obtained after two weeks of
cultivation. There was no technical problem assaying 43
or 102 eggs from natural waters. However, one assay of
a field sample cost about 20 U.S. dollars. To keep costs
down an assay kit cheaper than the VECTASTAINR
Elite ABC kit is needed when a large number of field
samples are analyzed.
Acknowledgments
We would like to thank the following sea farming centers
and universities for providing the fish eggs used in this
study: Fukui Prefectural Sea Farming Center; Kyoto
Prefectural Sea Farming Center; Faculty of Agriculture,
Kyushu University; Osaka Prefectural Fisheries Station;
Sea Farming Center of the Japan Sea-Farming Associa-
tion; Fisheries Laboratory of Kinki University. We also
thank Jeffrey M. Leis, Australian Museum, Sydney,
Australia, for his kind advice during the writing of this
manuscript.
Table 4
Reactivity of monoclonal antibody MT-1 to the pelagic eggs fixed with formaldehyde just after collection from Wakasa Bay.
O.G. diameter = oil globule diameter
Fish egg type
Egg diameter imm)
O.G. diameter imm)
Reactivity (%)
( positive egg no./ total egg no.)
I
II
III
IV
0.72-0.79
0.75-0.82
0.81-1.02
1.07
0.16-0.19
no oil globule
0.19-0.28
0.21
0(0/2)
0(0/11)
58(51/88)
0(0/1)
NOTE Hiroishi et al.: Identification of Pagus ma/or eggs using monoclonal antibodies
559
Figure 1
Reactivity of monoclonal antibody MT-1 to fish eggs detected by immunos-
taining. (A) Pagrus major (positive reaction); (B) Pagrus major (negative
control reaction without primary antibody); (C) Acanthopagrus shlegeli;
(D) Sparus sarba; (E) ParaUchthys olivaceus; (F) Engraulis japonica.
Bar represents 1 mm. Only the P. major eggs stained brown and showed
a positive reaction.
Table 5
Reactivity of monoclonal antibody MT-1 to the pel
agic eggs reared for 24 hours
after collection from Wakasa Bay.
Egg
Species
Reactivity (%) (positive egg no. /total egg no.)
Fish
Pagrus major
Acanthopagrus shlegeli
ParaUchthys olivaceus
Triglidae sp.
Konosirus punctutus
Soleoidei sp.
Englauris japonicus
100(6/6)
0(0/8)
0(0/1)
0(0/1)
0(0/2)
0(0/7)
0(0/13)
Decapod
Enploteuthidae sp.
0(0/5)
560
Fishery Bulletin 102(3)
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Mito, S.
1960. Keys to the pelagic fish eggs and hatched larvae
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Nagasaki, K, A. Uchida, S. Hiroishi, and Y. Ishida.
1991a. An epitope recognized by the monoclonal antibody
MR-21 which is reactive with the cell surface of Chat-
tonella marina type II. Fish. Sci. 57:885-890.
Nagasaki, K, A. Uchida, and Y. Ishida.
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Sako, Y, M. Adachi, Y Ishida, C. Scholin, and D. M. Anderson.
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antibodies to Alexandrium species. In Toxic phytoplank-
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Shao, K.-T, K.-C. Chen, and J.-H. Wu.
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Vrieling, E., A. Draaijer, L. Van Zeiljl, W. Gieskes, and
M. Veenhuis.
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cytometric appearance and identification of immuno-
chemical labeled marine dinoflagellates. J. Phycol.
29:180-188.
Fishery Bulletin 102(3)
561
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Volume 102
Number 4
October 2004
Fishery
Bulletin
Contents
Articles
563-580 Calambokidis, John, Gretchen H. Steiger, David K. Ellifrit,
Barry L. Troutman, and C. Edward Bowlby
Distribution and abundance of humpback whales
(Megaptera novaeangliae) and other marine mammals
off the northern Washington coast
581-592 Danilewicz, Daniel, Juan A. Claver, Alejo L. Perez Carrera,
Eduardo R. Secchi, and Nelson F. Fontoura
Reproductive biology of male franciscanas
(Pontoporia bloinvillei) (Mammalia: Cetacea) from
Rio Grande do Sul, southern Brazil
593-603 Fischer, Andrew J., M. Scott Baker Jr., and Charles A. Wilson
Red snapper (Lut/anus campechanus) demographic structure in
the northern Gulf of Mexico based on spatial patterns
in growth rates and morphometries
The conclusions and opinions expressed
in Fishery Bulletin are solely those of the
authors and do not represent the official
position of the National Marine Fisher-
ies Service 'NOAAi or any other agency
or institution.
The National Marine Fisheries Service
NMFS i does not approve, recommend, or
endorse any proprietary product or pro-
prietary material mentioned in this pub-
lication- No reference shall be made to
NMFS, or to this publication furnished by
NMFS. in any advertising or sales pro-
motion which would indicate or imply
that NMFS approves, recommends, or
endorses any proprietary product or pro-
prietary material mentioned herein, or
which has as its purpose an intent to
cause directly or indirectly the advertised
product to be used or purchased because
of this NMFS publication.
604-616 FitzGerald, Jennifer L, Simon R. Thorrold, Kevin M. Bailey,
Annette L. Brown, and Kenneth P. Severin
Elemental signatures in otoliths of larval walleye pollock
(Theragra chalcogramma) from the northeast Pacific Ocean
617-633 Gaughan, Daniel J., Timothy I. Leary, Ronald W. Mitchel
and Ian W. Wright
A sudden collapse in distribution of Pacific sardine
(Sardinops sagax) off southwestern Australia enables
an obiective re-assessment of biomass estimates
634-647 Griffiths, Shane P., Ron J. West, Andy R. Davis,
and Ken G. Russell
Fish recolonization in temperate Australian rockpools:
a quantitative experimental approach
Fishery Bulletin 102(4)
648-660 Hesp, S. Alexander, Ian C. Potter, and Sonja R. M. Schubert
Factors influencing the timing and frequency of spawning and fecundity of the goldlined seabream
(Rhabdosargus sarba) (Spandae) in the lower reaches of an estuary
661-670 Maxwell, Michael R., Annette Henry, Christopher D. Elvidge, Jeffrey Safran, Vinita R. Hobson,
Ingrid Nelson, Benjamin T. Tuttle, John B. Dietz, and John R. Hunter
Fishery dynamics of the California market squid (Loligo opalescens), as measured by satellite remote sensing
671-681 Murray, Kimberly T.
Magnitude and distribution of sea turtle bycatch in the sea scallop (Placopecten magellamcus) dredge fishery
in two areas of the northwestern Atlantic Ocean, 2001-2002
682-692 Snover, Melissa L, and Aleta A. Hohn
Validation and interpretation of annual skeletal marks in loggerhead (Caretta caretta) and
Kemp's ridley (Lepidochelys kempii) sea turtles
693-710 Stehlik, Linda L, Robert A. Pikanowski, and Donald G. McMillan
The Hudson-Raritan Estuary as a crossroads for distribution of blue (Callmectes sapidus),
lady (Ovalipes ocellatus), and Atlantic rock (Cancer irroratus) crabs
711-722 Stevens, Melissa M., Allen H. Andrews, Gregor M. Cailliet, Kenneth H. Coale, and Craig C. Lundstrom
Radiometric validation of age, growth, and longevity for the blackgill rockfish (Sebastes melanostomus)
723-732 Tolan, James M., and David A. Newstead
Descriptions of larval, preiuvenile, and |uvenile finescale menhaden {Brevoortia gunteri) (family Clupeidae),
and comparisons to gulf menhaden (6. patronus)
733-739 Uchikawa, Kazuhisa, John R. Bower, Yasuko Sato, and Yasunori Sakurai
Diet of the minimal armhook squid (Berryteuthis anonychus) (Cephalopoda: Gonatidae) in the northeast
Pacific during spring
740-749 Weinberg, Kenneth L, Robert S. Otto, and David A. Somerton
Capture probability of a survey trawl for red king crab (Paralithodes camtschaticus)
Notes
750-756 Kerstetter, David W., Jeffery J. Polovina, and John E. Graves
Evidence of shark predation and scavenging on fishes equipped with pop-up satellite archival tags
757-759 Vladimir V. Laptikhovsky
Survival rates of rays discarded by the bottom trawl squid fishery off the Falkland Islands
760 Acknowledgment of 2004 reviewers
761 2004 indexes
770 Subscription form
563
Abstract— We examined the summer
distribution of marine mammals
off the northern Washington coast
based on six ship transect surveys
conducted between 1995 and 2002,
primarily from the NOAA ship
McArthur. Additionally, small boat
surveys were conducted in the same
region between 1989 and 2002 to
gather photographic identification
data on humpback whales iMegap-
tera novaeangliae) and killer whales
(Orcinus orca) to examine movements
and population structure. In the six
years of ship survey effort. 706 sight-
ings of 15 marine mammal species
were made. Humpback whales were
the most common large cetacean spe-
cies and were seen every year and a
total of 232 sightings of 402 animals
were recorded during ship surveys.
Highest numbers were observed in
2002, when there were 79 sightings of
139 whales. Line-transect estimates
for humpback whales indicated that
about 100 humpback whales inhab-
ited these waters each year between
1995 and 2000; in 2002, however, the
estimate was 562 (CV=0.21) whales.
A total of 191 unique individuals were
identified photographically and mark-
recapture estimates also indicated
that the number of animals increased
from under 100 to over 200 from 1995
to 2002. There was only limited inter-
change of humpback whales between
this area and feeding areas off Oregon
and California. Killer whales were
also seen on every ship survey and
represented all known ecotypes of the
Pacific Northwest, including southern
and northern residents, transients,
and offshore-type killer whales. Dall's
porpoise iPhocoenoides dalli) were the
most frequently sighted small ceta-
cean; abundance was estimated at
181-291 individuals, except for 2002
when we observed dramatically higher
numbers (876, CV=0.30i. Northern
fur seals (Callorhinus ursinus) and
elephant seals iMirounga angustiros-
tris) were the most common pinnipeds
observed. There were clear habitat
differences related to distance off-
shore and water depth for different
species.
Manuscript submitted 25 September 2003
to the Scientific Editor's Office.
Manuscript approved for publication
4 June 2004 by the Scientific Editor.
Fish. Bull. 102:563-580 i2004).
Distribution and abundance of humpback whales
(Megoptera novaeangliae)
and other marine mammals
off the northern Washington coast
John Calambokidis
Gretchen H. Steiger
David K. Ellifrit
Cascadia Research Collective
Waterstreet Building
218V2 West Fourth Ave.
Olympia, Washington 98501
E-mail address (for J Calambokidis) calambokidis@cascadiaresearch.org
Barry L. Troutman
Washington Dept of Fish and Wildlife
600 Capitol Way
Olympia, Washington 98501
C. Edward Bowlby
Olympic Coast National Marine Sanctuary, NOAA
115 Railroad Ave E, Suite 301
Port Angeles, Washington 98362
Marine mammals have had an impor-
tant role in the history of the Olympic
Peninsula for centuries. Many species,
including sea otters ( En hydra lutris).
harbor seals iPhoca vitulina), hump-
back whales (Megaptera novaean-
gliae), and gray whales iEschrichtius
robustus) were hunted by the Makah
tribe (Swan, 1868; Huelsbeck, 1988).
Much later, modern whalers targeted
humpback whales in this region from
stations at Bay City, Washington
(1911-25, Scheffer and Slipp, 1948).
and southern Vancouver Island, Brit-
ish Columbia (1905-43, Gregr et al.,
2000). A small aboriginal hunt for
gray whales resumed in these waters
in 1998, and the Makah killed one
gray whale in May 1999. Since the
end of commercial whaling, marine
mammals have been afforded protec-
tion under the Marine Mammal Pro-
tection Act of 1972. In addition, the
waters off the northern Washington
coast were designated as the Olympic
Coast National Marine Sanctuary in
1994.
A number of studies have docu-
mented marine mammals in this re-
gion. Some surveys of broader areas
have included the waters off north-
ern Washington (Von Saunder and
Barlow, 1999; Brueggeman1; Green
et al.2). Species-specific studies also
1 Brueggeman, J. J. 1992. Oregon and
Washington marine mammal and sea-
bird surveys. Final report of OCS
Study MMS" 91-0093 by Ebasco Envi-
ronmental, Bellevue, Washington, and
Ecological Consulting, Inc., Portland.
Oregon, for the Minerals Management
Service (MMS), 445 p. MMS, Pacific
OCS Region, U.S. Dept. of Interior.
770 Paseo Camarillo, Camarillo. CA
93010.
2 Green, G. A., M. A. Smultea, C. E. Bowlby.
and R. A. Rowlett. 1993. Delphinid
aerial surveys in Oregon and Washing-
ton offshore waters. Final report for
contract 50ABNF200058 to the National
Marine Mammal Laboratory, National
Marine Fisheries Service, 100 p. Nat.
Mar. Mamm. Lab., NMFS, 7600 Sand
Point Way NE F/AKC3, Seattle, WA
98115.1
564
Fishery Bulletin 102(4)
have been conducted on harbor porpoise iPhocoena pho-
coena; Barlow et al., 1988; Osmek et al., 1996; Calam-
bokidis et al.3) and, to a limited degree, on humpback
whales ( Calambokidis et al., 1996, 2000) and gray
whales (Darling, 1984; Green et al., 1995; Shelden et
al., 2000; Calambokidis et al., 2002). Studies on pin-
nipeds and sea otters have also been conducted in this
region (Jeffries et al., 2003; Jameson et al., 1982, 1986;
Kvitek et al. 1992, 1998; Bowlby et al.4).
Information on humpback whales is of particular
interest because they were the primary species hunted
by whalers off Washington in the early 1900s. Since
then, little has been known about their movements and
distribution in this region. Photo-identification research
has helped define the movements and stock structure of
the humpback whales feeding off California (Calamboki-
dis et al., 1990. 1996, 2000). Calambokidis et al. (1996)
suggested that a demographic boundary exists between
humpback whales that feed off the coasts of California,
Oregon, and Washington and humpback whales feeding
farther north off British Columbia and Alaska. The
identity and degree of interchange of the whales that
feed in this boundary area have been unclear.
Similarly for killer whales, photo-identification stud-
ies have revealed much about whale groups that fre-
quent the inland waters of Washington and British
Columbia (Bigg et al., 1990; Ford et al., 1994). Very
little is known about their occurrence off the coast, in
particular, about the "offshore" groups that are believed
to be a distinct race (Ford et al., 1994) that are seen
primarily offshore but occasionally also enter inland
waterways.
We report here on the summer distribution of marine
mammals off the northern Washington coast based on
six ship line-transect surveys conducted between 1995
and 2002. These surveys were initiated to understand
marine mammal distribution and abundance in the
newly designated Olympic Coast National Marine Sanc-
tuary, as well as to collect information on seabirds,
oceanographic conditions, and juvenile fish. Each ship
survey was conducted between mid-June and late July.
Density estimates were made for the two most common
species: humpback whales and Dall's porpoise. In ad-
dition, photo-identification data gathered during these
ship surveys and from supplemental small boat surveys
:i Calambokidis, J., J. C. Cubbage, J. R. Evenson, S. D. Osmek,
J. L. Laake, P. J. Gearin, B. J. Turnock, S. J. Jeffries, and R.
F. Brown. 1993. Abundance estimates of harbor porpoise
in Washington and Oregon waters. Report to the National
Marine Mammal Laboratory. National Marine Fisheries Ser-
vice, 55 p. Nat. Mar. Mamm. Lab., NMFS, 7600 Sand Point
Way NE F/AKC3, Seattle, WA 98115.
4 Bowlby, C. E., B. L. Troutman, and S. J. Jeffries. 1988. Sea
otters in Washington: distribution, abundance, and activ-
ity patterns. Final report to National Coastal Resources
Research and Development Institute, Hatfield Marine Sci-
ence Center, 2030 S. Marine Dr., Newport, Oregon 97365,
131 p. Cascadia Research Collective, Wash. State Dept. of
Wildlife, Olympia, WA.
within the same area between 1989 and 2002 provided
information on humpback and killer whale movements
and stock structure.
Materials and methods
Ship surveys
Generally, ship surveys covered the area between the 20-m
isobath and the landward margin of the continental shelf
i200-m isobath) from the entrance to Strait of Juan de
Fuca to the mouth of the Copalis River to include the
boundaries of the Olympic Coast National Marine Sanc-
tuary (Fig. 1). Although the northern extent of these
waters is off southern British Columbia (Vancouver
Island), the entire overlapping region will be referred
to as northern Washington.
Fourteen east-west tracklines were selected, follow-
ing permanent tracklines established by the NOAA
ship Miller Freeman in 1989. Tracklines were spaced
at 5-nmi intervals and were surveyed each year ex-
cept in 2002, when only ten lines were surveyed (four
southernmost lines were not included). Extra ship time
allowed for replicate surveys of the northern survey
legs in 1995, a short offshore extension of two lines
in 1996 and 2000 (up to 17 nmi in 1986), the addition
of three short east-west lines off southern Vancouver
Island around La Perouse Bank in 1997, and one ad-
ditional line that was surveyed south of the study area
in 2000 (Fig. 1).
Ship surveys were conducted over a two-week period
in late-June and July 1995, 1996, 1997. 1998, and 2000
(Table 1). In 2002, a shorter, one-week survey was done
in mid-June. The marine mammal ship surveys were
conducted by a single primary observer from the vessel's
flying bridge (the sighting platform) with a viewing
height of 10 m above the water level. All surveys were
conducted from the NOAA ship Mc Arthur (55 m) except
during 2000, when the naval ship Agate Passage (33 m)
was used. From these platforms, the primary observer
scanned a 180-degree arc encompassing the area ahead
of the ship and abeam to either side. Observers used
reticle binoculars when possible and obtained measure-
ments of distance to a sighting derived from the angle
below the horizon (measured with graded reticles in the
binoculars) and the known platform height. For sight-
ings where the species could not be determined by the
observer, animals were identified to a general taxonomic
level (e.g., unidentified pinniped).
Photo-identification surveys
In addition, photo-identification data were examined that
had been gathered within the survey area. Research-
ers took photographs directly from the survey ship, or
from a Zodiac rigid-hulled inflatable that was launched
when animals were sighted. In 1996, the last two days
of vessel time on the McArthur were used to photograph
whales for identification.
Calambokidis et al.: Distribution and abundance of marine mammals off the northern Washington coast
565
1 26°0'0"W
1
125:'0'CrW
I
Vancouver
Island
Barkley
Sound
N 3 lines only in 1997
La Perouse
Bank
t
Swiftsure
Bank .
Strait of
Juan de Fuca
Cape
Flattery
Olympic
Peninsula
Sanctuary Boundary
Figure 1
On-effort ship survey tracklines (horizontal lines) off the northern coast of Wash-
ington between 1995 and 2002. The Olympic Coast National Marine Sanctuary
boundary is delineated and labeled. Dashed and dotted lines show three northern
lines surveyed only in 1997, the western extension of two lines surveyed only in
1996, and the southern four lines missed in 2002.
In addition, dedicated photo-identification surveys
were conducted by Cascadia Research scientists us-
ing a 5.3-m Novurania rigid-hulled inflatable that was
launched from nearby ports and operated in areas
where whales were concentrated. Photo-identification
data in the present study includes data collected off
the northern Washington coast between 1989 and 2002
(Table 2). It also includes photographs contributed by
other researchers and boat operators taken in the area
during this time (Table 2).
Generally, photographs were taken with Nikon 8008
35-mm cameras equipped with 300-mm Nikkor telepho-
to lenses. High-speed black-and-white film (Ilford HP
5+) was pushed IV2 stops so that exposure times were
generally 1/1000 or 1/2000 of a second. Identification
photographs were taken with standard procedures used
566
Fishery Bulletin 102(4)
Table 1
Summa
ry
of ship survey
effort off
northern Washin
gton (does
not include small boat
surveys).
Dates of effort
No. of
nmi on
Year
Start
End
legs
Effort (h)
effort
Ship
Observers
1995
21 Jul
27 Jul
10
46
546
Mc Arthur
Troutman. Ellifrit
1996
28 Jun
5 Jul
14
46
540
Mc Arthur
Troutman, Ellifrit
1997
9 Jul
18 Jul
17
52
513
Mc Arthur
Troutman, Ellifrit
1998
25 Jun
4 Jul
14
55
572
McArthur
Troutman, Quan
2000
16 Jun
24 Jun
14
60
589
Agate Passage
Rowlett, Nelson
2002
12 Jun
18 Jun
10
32
315
McArthur
Troutman, Douglas
All years
291
3075
Table 2
Photo-identification effort off the
coast of
northern
Washington
bet
ween
1989 and 2002.
These
data
include whales identified
from the ship or
small boats launched from the sh
ip, dedicated small boat surveys,
and
opportunistic photographs taken by
others. Unique =
number of different animals.
Days IDs obtained
Humpback whales identified
Other sources of photographs
Year No
First
Last
No.
Unique
No.
of mothers No
of calves
1989 1
lOct
1 Oct
1
1
0
0
1990 3
25 Aug
6 Sep
10
10
1
1
Balcomb/Bloedel'
1991 4
23 Aug
4 Sep
14
13
0
0
Balcomb/Bloedel'
1993 1
15 Jul
15 Jul
3
3
0
0
1994 3
25 Jun
15 Jul
20
16
0
0
G. Ellis.- R. Baird
1995 7
14 Jul
25 Jul
50
35
4
2
S. Mizroch3
1996 9
29 Jun
6 Oct
55
34
1
0
1997 9
13 Jul
18 Oct
25
23
2
0
1998 19
28Mav
16 Oct
71
48
1
1
V. Deeke, B. Gisborne
1999 28
20 May
20 Oct
103
60
2
0
B. Gisborne
2000 12
2 Jun
4 Oct
56
40
2
1
B. Gisborne
2001 15
8 Jun
5 Oct
59
41
2
1
SWFSC.J B. Gisborne
2002 9
13 Jun
5 Sep
41
32
0
0
Total 120
508
356
15
6
Unique
191
; Center for Whale
Research, P.O. Bo>
1577, Fn
day Harboi
, WA 98250.
2 Dept. of Fisheries and Oceans, Pacific Biological Station
Nanaimo, BC
, V9T 6N7,
Canada.
3 National Marine
Mammal Laboratory, NMFS
7600 Sand Point Way NE, Seattle,
WA 98115.
4 Southwest Fisheries Science Center
8604 La
lolla Shores Dr., La Jolla
CA 92037.
in past research (Calambokidis et al., 1990). For hump-
back whales, photographs were taken of the ventral
side of the tail flukes. For killer whales, the dorsal fin
and surrounding saddle-patch area were photographed
from both sides.
Photographs of individuals were first compared to
those identified in the same region. To analyze inter-
change with other regions, we compared these individu-
als with existing catalogs to obtain sighting histories.
For humpback whales, a catalog was used of over 1000
humpback whales identified since 1986 along the West
Coast. The regions used for comparison were Oregon,
northern California (Oregon-California border to Pt.
Arena i, northern central California (Pt. Arena to north
of Monterey Bay), southern central California (north
of Monterey Bay to Pt. Conception! and southern Cali-
fornia (southern California Bight). For killer whales,
whales were matched to existing catalogs (Bigg et al.,
1987; Ford et al., 1994; Black et al., 1997). All iden-
tifications and group determinations were confirmed
by one of the authors tDKEi or Graeme Ellis (Dept. of
Fisheries and Oceans. Nanaimo. British Columbia).
Calambokidis et al.: Distribution and abundance of marine mammals off the northern Washington coast
567
Data analysis
For ship surveys between 1995 and 2000, position and
oceanographic data (including depth, sea surface tem-
perature) logged by the ship's computer were later rec-
onciled with the sighting and effort data recorded by
the observers. Sighting positions were analyzed for each
species for water depth, distance from shore, distance
from shelf edge (200-m depth contour) and sea surface
temperature. Data analysis and mapping were conducted
by using a geographic information system (GIS) with
Arclnfo software (ESRI, Redlands, CA). Data from the
shorter 2002 ship survey were included in the summary
of sightings but were not available for the analyses of
sightings related to oceanographic features.
Line-transect analysis to determine density and abun-
dance was conducted for the two species with more than
30 sightings (humpback whales and Dall's porpoise).
We used the program (Distance, version 3.5, Research
Unit for Wildlife Population Assessment, University of
St. Andrews, St. Andrews. UK) to conduct analyses.
For these analyses, we used only effort and sightings
from the regular east-west transect lines and did not
include on-effort data from opportunistic lines or cross-
tracks. We included sightings made by secondary as
well as the primary observer. Although whales were
reportedly seen out to 6 nmi, we truncated the sight-
ings at 3 nmi for humpback whales and 2.5 nmi for
Dall's porpoise. For humpback whales we included 16
sightings of unidentified whales (unidentified mainly
because of distance). These were probably humpback
whales because the only other large whales that were
seen in the surveys were a few gray whales seen close
to shore. Distance position data were incomplete for 13
of the 188 whale sightings and 14 of 82 Dall's porpoise
sightings; for these the missing value was randomly
selected from the observed measurements.
The Distance program was used to select the best
model for sighting probability in relation to distance off
the transect. We allowed the program to select among
models (half-normal, uniform, hazard-rate, and nega-
tive exponential) and varying numbers of adjustment
terms (cosine and simple polynomials) based on lowest
Akaike's information criterion (AIC) score. All years
were pooled for the model of sighting probability, but
encounter rate and group size were calculated by year.
An adjustment to group size was calculated if there
was a significant group size bias with distance from
the track line, which was not the case for humpback
whales but was present in some years (1996 and 1997)
for Dall's porpoise.
Area was calculated for abundance estimation based
on the zone covered by the regularly scheduled transect
lines covered in most years (study area was considered
to encompass waters 2.5 nmi north of the northernmost
line and 2.5 nmi south of the southernmost line). The
only annual adjustment for area was for humpback
whales in 2002. Surveys in that year did not cover
the southern end of the study area (because of limited
ship time), an area with a typically lower abundance
of whales. To avoid extrapolating the higher density
of whales from the northern portion of the study area
to this region, we excluded this missed area from the
abundance estimates.
Estimates of abundance for humpback whales were
also calculated by using capture-recapture models (Se-
ber, 1982; Hammond, 1986). We used identifications
obtained in pairs of adjacent years taken from 1994 to
2002 to generate Petersen capture-recapture estimates.
The Chapman modification of the Petersen estimate
(Seber, 1982) was used because it was appropriate for
sampling without replacement (Hammond, 1986).
Results
In total, there were 706 sightings of 2467 animals over
the six ship surveys combined (Table 3). Fifteen differ-
ent marine mammal species were seen: nine cetacean
species, five pinniped species, and the sea otter were
identified. Each year, 9 to 12 different species were seen,
except in 2002 when only six species were observed.
This 2002 survey, although shorter than those of the
other years, showed a dramatic change in the species
diversity and numbers of animals. We saw many more
humpback and Dall's porpoise than in previous years.
We also noted the absence of six regularly observed spe-
cies: harbor porpoise, gray whales, Pacific white-sided
dolphins (Lagenorhynchus obliquidens), Risso's dolphin
(Grampus griseus), harbor seals, and California sea lions
iZalophus californianus).
Humpback whales
Of the large cetaceans, humpback whales were the most
common species seen; there were 232 sightings of 402
animals during ship surveys (Table 3). Largest numbers
of humpback whales were seen in 2002, when there
were 79 sightings of 139 individuals during the one-
week survey. Group sizes ranged from 1 to 8 animals
(mean=1.7, SD=1.1). Only six calves were recorded from
the ship surveys — probably because it was difficult to
identify calves at the distance at which most sightings
were made. Of these six sightings of mothers with calves,
four sightings were outside the primary areas where
other humpback whale groups were seen.
Sightings were concentrated in the northern part of
the study area between Juan de Fuca Canyon and the
outer edge of the continental shelf, an area known as
"the Prairie" (Fig. 2). A small area east of the mouth of
Barkley Canyon and north of the Nitnat Canyon where
the water depth was 125-145 m had a high density of
sightings in all years. A smaller number of humpback
whales were also seen on Swiftsure Bank. Sightings in
2002 were not only more numerous but more broadly
distributed; sightings were recorded in the areas de-
scribed above and also farther south and closer to shore
than those seen in previous years.
Line-transect estimates for humpback whales were
very consistent in the first five surveys (1995 to
568
Fishery Bulletin 102(4)
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Calambokidis et al.: Distribution and abundance of marine mammals off the northern Washington coast
569
Figure 2
Locations (by year) for humpback whales (Megaptera novaeangliae) seen during ship
surveys off the northern Washington coast between 1995 and 2002.
2000, Table 4, Fig. 3). The encounter rate of groups
(0.046-0.053 sightings per nmi), density (0.034-0.050
whales per nmi2), and abundance (85-125 individuals)
were similar among these years. These data indicate
that about 100 humpback whales used the study area
during this period.
The sighting rate of humpback whales was dramati-
cally higher in 2002 than in all previous years and
was reflected in the line-transect estimates (Fig. 3).
Estimated density (0.23 whales per nmi2) was more
than four times higher than any previous year. Apply-
ing this density to only the reduced area surveyed in
2002 (1953 instead of 2505 nmi2) still yielded much
higher estimates of abundance (562, CV=0.21) than in
any previous year. These higher abundance estimates
could not have been an artifact of random variation; the
lower bound of the 95% confidence interval for the 2002
estimates was well above the upper confidence interval
of any of the previous years (Table 4).
Of the humpback whales photographed during small
boat surveys off the northern Washington-BC border
between 1989 and 2002, 508 individuals were success-
570
Fishery Bulletin 102(4)
Table 4
Results
of line-transeet analysis for h
umpback whales off northern Wash
ngton. C
n-effort sight
ngs of b
umpback
and un-
identified large whales
made during regular transects ( not including deadheads [areas
between transect lines
and opportunistic
sightings) within 3
nm
of ship
were used. Best detection model fit (AIC scores) was a negative exponential w
th 1 cosine adjust-
ment yielding /'l 0) =
1.0E
. Effect
ve strip
width was 0.95
nmi w
ith CV=0.09.
Survey effort
953 Conf. int.
Sightings
Encounter
Group
Density
Area
Estimated
Year
/!
lines
nmi
rate
size
(per nmi2)
(nmi2)
abundance
CV
lower
upper
1995
23
58
438
0.053
1.48
0.041
2505
102
0.33
54
193
1996
24
59
474
0.051
1.54
0.041
2505
103
0.33
55
193
1997
26
92
493
0.053
1.62
0.045
2505
112
0.3
63
199
1998
20
62
432
0.046
1.40
0.034
2505
85
0.31
47
155
2000
23
70
504
0.046
2.09
0.050
2505
125
0.32
67
234
2002
72
43
305
0.236
1.81
0.224
1953
562
0.21
375
841
Total
188
384
2646
fully identified of which 191 were unique individuals
i Table 2). Of these 191, 83 (44%) had been seen in this
area in more than one year within this time period. The
proportion of animals seen more than one year changed
over the course of the study ( Fig. 4). The proportion of
whales identified each year that had been seen in others
years decreased annually (Fig. 4, regression r- = 0.63,
P=0.002); the most dramatic drop occurred between
1998 and 1999.
Photographs of humpback whales documented animal
movements within the study area and provided some
insight into possible reasons for the high sighting rates
during the 2002 ship surveys. On two occasions, the
same humpback whale was identified on different days
in a slightly different area and represented a duplicate
600 -1
• •♦- ■ Line-transect
♦
— ■ — Capture-recapture
500 ■
,'
400 -
.'
O
§ 300-
c
200 -
100 -
■ m '-•♦---'
■ '
l<)')4 IW5 1996 1997 1998 1999 2000 2001
.' 2 2003
Year
Figure 3
Line-transect Idashed line i and capture-recapture
(solid line)
estimates for humpback whale iM. noracannliae)
abundance
between 1995 and 2002.
sighting of this animal from the ship survey. It is pos-
sible that shifting humpback whale distribution during
the course of the 2002 survey could have occurred in
a manner that resulted in the same animals being
encountered multiple times and that elevated the sight-
ing rate and line-transect abundance estimate (Fig. 3).
We cannot test this hypothesis because other animals
may have shifted in a manner that they avoided being
detected at all.
Abundance of humpback whales from capture-re-
capture models yielded estimates of 89 to 343 whales
(Table 5, Fig. 3). These estimates tended to increase
over the course of the study from a low of 89 whales
for 1994-95 to a high of 343 for 2000-2001 and 230
for 2001-2002 (regression r2 = 0.60, P=0.02). There was
fairly good agreement between the capture-re-
capture and line-transect estimates until 2002
(Fig. 3).
A total of 17 of the 191 (9%) whales that we
identified off northern Washington had also
been photographed off California and Oregon
(Table 6). Interchange of whales seen off north-
ern Washington and other feeding areas to the
south decreased as distance among feeding ar-
eas increased. About 10% (10 of 105) of the
whales that were identified off Oregon were
also photographed off northern Washington.
This rate of matching dropped below 3% (8 of
313) off northern California and continued to
decrease to no interchange seen for whales pho-
tographed off southern California.
The proportion of whales that were seen in
areas to the south appeared to change over
the course of the study. From 1989 to 1998,
when resighting rates between years within
our study area were highest, we also had a
higher proportion of interchange with feeding
areas to the south (13 of 109 whales or 12%).
From 1999 to 2002, after resightings within
our region decreased, there was also a decrease
Calambokidis et al.: Distribution and abundance of marine mammals off the northern Washington coast
571
Table 5
Estimates of humpback
Each estimate was base
whale abundance
d on the identificat
Est
ions
) off northern Washington obtained
obtained (n) in each of two adjacent
with the Petersen
years.
capt
are-recapture
model.
Period
Sample 1
Sc
mple 2
Match
Est.
CV
Year
n
Year
n
1994-
-95
1994
14
1995
35
5
89
0.27
1995-
-96
1995
35
1996
34
11
104
0.19
1996-
-97
1996
34
1997
21
7
95
0.24
1997-
-98
1997
23
1998
48
6
167
0.28
1998-
-99
1998
48
1999
60
13
213
0.19
1999-
-2000
1999
60
2000
31
14
129
0.16
2000-
-01
2000
40
2001
41
4
343
0.36
2001-
-02
2001
41
2002
32
5
230
0.32
in the proportion of these whales that had also
been seen off California and Oregon (7 of 136
whales or 5%). This difference falls just short
of statistical significance (j2 = 3.71, P<0.10) but
is in the reverse direction from what would be
expected if immigration from the south were to
increase over time.
Between 1989 and 2002, 15 different mothers
were seen with 16 calves (one mother seen with a
calf in two different years). Mothers with calves
represented 4.2% of the individual whales iden-
tified each year ( 15 of 356 unique annual iden-
tifications. Table 2). For each year only a small
proportion of the calves were identified because
calves raise their flukes less often.
Killer whales
One other large cetacean species (killer whales)
was also seen every year; there were a total of
14 sightings of 124 animals from ship surveys
(Table 3). Three of these sightings were of large
groups between 20 and 35 animals, and the
rest were in groups fewer than ten (14 sight-
ings, mean = 8.9, SD = 11.2). Killer whales were
widely distributed across different habitats; there
were sightings of animals both close to and far
from shore and in fairly shallow and deep water
(Fig. 5).
All three ecotypes of killer whales (namely,
1) southern and northern residents, 2) transients, and
3) offshore residents) were observed off the northern
Washington coast. Of the 15 groups identified pho-
tographically between 1989 and 2002, there were
sightings of animals from the southern resident (2
groups), northern resident (3), transient (5) and off-
shore (3) groupings (Table 7). Other sightings appeared
to be northern residents (1) and offshore (1) animals
but the quality of the photographs were too poor for
■B 80<r
i1
5
■D
2091
X %y % \ x % x \ \ \ \ %
Year
Figure 4
The proportion of humpback whales (M. novaeangliae) seen
in more than one year during annual surveys off northern
Washington from 1989 to 2002.
us to be certain. Large groups of killer whales (20-40
animals) were seen on five occasions during small boat
surveys.
Dall's porpoises
Dall's porpoises were the most frequently sighted small
cetacean; there were 115 sightings of 406 animals and
Dall's porpoises were observed every year (Table 3). No
572
Fishery Bulletin 102(4)
Table 6
Number of humpback
whales
identified in
different regions along the U.S. west coast and the number and percentage of these
that matched with northern Washington
For northern Washington, we report the number of
whales that were seen in that
region in more than one year.
No. of
No. of matches
% of whales that
Region
individuals
with N. Wash.
match with those in N. Wash.
Northern Washington
191
83
43.5%
Oregon
105
10
9.5%
N. California
313
8
2.6%
N. Centra] California
921
13
1.4%
S. Central California
666
3
0.5%
S. California
303
0
0.0%
Table 7
Summary of killer wh
lie sightir
gs off north
ern Washington between 1989
and 2002 where identifiable photographs were
taken.
No. of
animals
Lat.
Long.
Date
estimated
°N
°W
Community
Pod or ID Comments
13 Sep
89
3
48 23.0
124 48.5
Resident — southern
L10, L28.L41
15 Jul
94
4
48 20.9
125 20.0
Transient
CA195
25 Jul
95
7
47 49.8
124 59.5
Transient
CA195
26 Jul
95
8
47 53.7
125 03.3
Transient
CA20.CA27
17 Mar
96
6
46 58.2
124 15.7
Resident — southern
L26, L83 outside Grays Harbor
31 Mar
96
7
46 55.0
124 09.7
Transient — probably
T50? Grays Harbor entrance
5 Jul
96
3
48 13.1
124 55.0
Transient
T185
6 Jul
96
40
48 26.7
125 43.2
Resident — northern
C, D. Gls. G12s
15 Jul
97
30
48 19.4
125 09.5
Offshore
18 Jul
97
10
48 18.3
125 23.6
Offshore
CA105
10 Aug
97
8
48 21.0
125 34.6
Transient
T36, T99, T36A?, T137?
27 Aug
98
40
48 28.0
125 17.0
Offshore
044.030, 031,0172,
014, 0158, 0218
10 Oct
99
30
48 22.0
125 38.1
Resident — northern
111
18 Jun
00
20
48 03.8
125 04.3
Probably resident — northern
not southern residents
6 Sep
01
12
47 01.8
124 46.6
Resident — northern
G12s, G17s, G29s
Table 8
Results of line-transect analysis for Dall's porpoise
off northern
Washingt
Dn. All on
-effort sightings
during
regular
transects
(not incluc
ing deadheads [areas between transect li
nes] and opportunistic
sight ingsi
within 2.5 nmi
of the s
lip were
included.
The best detection model fit lAIC scores)
was the hazard rate with
no cosine adjustment, yielding /"(0) =
2.60. Effective strip width
of 0.38 nmi with CV=
0.12. The
group size for 96-97
was adjusted to account for a significant group size bias with dist
a nee from
the trackline.
Survey
effort
95r; Conf. int.
Sightings
Encounter
Group
Density
Area
Estimated
Year
n
lines
nmi
rate
size
per nmi'-)
(nmi-)
abundance
CV
lower
upper
1995
16
58
438
0.037
2.25
0.100
2505
268
0.32
143
501
1996
14
59
474
0.030
2.65
0.102
2505
255
0.32
138
472
1997
13
92
493
0.026
2.28
0.078
2505
197
0.38
95
405
1998
9
62
432
0.021
2.67
0.072
2505
181
0.49
72
453
2000
13
70
504
0.026
3.46
0.116
2505
291
0.42
132
644
2002
17
43
305
0.056
4.82
0.350
2505
876
0.3
487
1576
Total
82
384
2646
Calambokidis et al.: Distribution and abundance of marine mammals off the northern Washington coast
573
126°0'0"V\
i
125'0'0"W
1
Other Large Cetaceans
•
Minke Whale
Vancouver
■
Gray Whale
490'0"N-
Island
A
Killer Whale
-49"0'0"N
Barkley
Sound
La
Perouse
Bank
A
Swifl
Bg
sure
Dk
▲
Strait of
^ 1 Juan de Fuca
Cape
■ lattery
^^-—-^^ A
^--^Prairie
AR' n'fl'M —
c/
* A •
V
\ 6®
A
Olympic
. Peninsula
A •
-48°0,0,,N
ho U U IN
^V/
A
i ^IM
A
■
■
i
i.
Sanctuary Boundary
N
47"0'0"N-
' 1 1
-47°0'0"N
Figure 5
Locations of other large cetaceans seen during ship surveys off the northern Wash-
ington coast between 1995 and 2002.
calves were recorded during the surveys. Dall's porpoises
were widely distributed in the study area but were not
as commonly seen in more shallow coastal waters or in
the southern portion of the study area (Fig. 6). Group
size ranged between 1 and 12 individuals (mean=3.5,
SD = 2.2). Harbor porpoises were observed each year
(except 2002) and there were a total of 38 sightings for
the entire study period. Group size ranged between 1
and 6 individuals except for one sighting of a group of 20
animals (mean=2.3, SD = 3.1). The distribution range for
harbor porpoises was more restricted to coastal waters
and showed only a small overlap with the distribution
range for Dall's porpoises (Fig. 6).
Line-transect analysis allowed estimation of Dall's
porpoise density and abundance (Table 8). Similar to
those for humpback whales, results for Dall's porpoises
were fairly consistent for the first five surveys (1995
to 2000): annual abundances were estimated between
181 and 291. For 2002, the encounter rate and corre-
sponding density and abundances increased dramati-
574
Fishery Bulletin 102(4)
126°0'0"W
125'0,0"W
i
Small Cetaceans
•
Risso's Dolphin
Vancouver
■
Northern Right Whale Dolphin
■KV'A'fV'M —
Island
A
Pacific White-sided Dolphin
4y U U N~
*
Dall's Porpoise
Barkley
Sound
+
Harbor Porpoise
La Perouse
Bank
Swiftsure
Bap1'
* * *
I
•
*
*
*+* + *»*
* *
Strait of
\* *****
*A*
* * * >*
V*^— -<A *+
-^^F'rairie *
* * a*+* ** i
'S^-f *+ *
*
* +*
*
* * *
*Ak , j Juan de Fuca
A . Cape
" Flattery
+
>5
>*
** A* **
**
<**
* Olympic
48'0'0"N-
+
\*
4
"*
*
• *
Peninsula
* AA±
A
•
**
A
A
•
A*
*
**
"1
» +
* £*
T *
** +
*
* \
•
+++
t
A 1
* * -H-
■H-
+
N
Sanctuary Boundary
47 O'ff'N-
1 1
r-
Figure 6
Locations of small cetaceans seen during ship surveys off the northern Washington
coast between 1995 and 2002.
cally yielding an estimated abundance of 876 porpoises
(CV=0.30, Table 8). Confidence intervals for some of the
annual estimates overlapped among years.
of 28 occasions. All but one of these sightings were of
a single animal. Elephant seals were seen in all years
except 1998 and 2002.
Pinnipeds
Pinnipeds were not as frequently observed as cetaceans
• Table 3, Fig. 7). The two most pelagic species observed
in this region, northern fur seals and elephant seals,
were the most commonly seen pinnipeds. Northern fur
seals were observed every year except 2002 on a total
Habitat differences
A number of broad habitat patterns emerged for differ-
ent groups of species based on their association with
water depth and distance from shore during the ship
surveys from 1995 to 2000 (Table 9, data were not avail-
able for 2002). Five species were seen in shallow waters
Calambokidis et at: Distribution and abundance of marine mammals off the northern Washington coast
575
125=0'0"W
I
Vancouver
Island
Barkley
Sound
Pinnipeds
• Northern Fur Seal
■ Northern Sea Lion
* Sea Otter
a Elephant Seal
+ Harbor Seal
♦ California Sea Lion
La Perouse
Bank
Strait of
I Juan de Fuca
Cape
Flattery
Olympic
Peninsula
1
Sanctuary Boundary
Figure 7
Locations of pinnipeds and sea otters {Enhydra lutris) seen during ship surveys off
the northern Washington coast between 1995 and 2002.
(<100 m). Gray whales and sea otters were seen in the
shallowest water of all species with average water depths
of just 20 and 22 m. respectively; they also were the only
two species for which sightings averaged less than 10 km
from shore. The three other species — harbor porpoise,
California sea lions, and northern sea lions (JEumetopias
jubatus) — were seen in slightly deeper waters (averag-
ing 34 to 91 m) and farther from shore (averaging 11 to
23 km). The five species that were predominantly found
at mid-shelf depths (mean depths at 100-200 m) were
humpback whales, killer whales, Dall's porpoises, harbor
seals, and minke whales (Balaenoptera acutorostrata).
Species seen far from shore (>40 km) and also in deepest
waters (>200 m) included Pacific white-sided dolphins,
Risso's dolphins, elephant seals, and northern fur seals.
All of these species are known to feed along the conti-
nental slope or off the shelf.
Distances from the shelf break for different species
did not fall into as clear a pattern as water depth and
distance from shore (Table 9). This disparity may be
the result of the varied habitat (with canyons cutting
through the study area) and the lack of much effort off
576
Fishery Bulletin 102(4)
Table 9
Summary of habitat and oceanograph
ic parameters
for si
jhtings
of different species during ship
surveys
from 1995 to 2000.
Distance fr
om
Distance from
Sea surface
Species
Water depth
iml
shore (km I
shelf l km)
temp. (°C)
n
Mean
SD
n
Mean
SD
7f
Mean
SD
n
Mean
SD
Baleen whales
Humpback whale
153
144
87
153
43.8
14.9
153
8.4
6.7
101
13.9
1.6
Gray whale
5
20
8
5
5.0
2.0
5
26.1
8.1
5
14.4
1.9
Minke whale
3
106
67
3
41.2
27.7
3
8.0
6.5
3
16.1
0.9
Unidentified large whale
21
189
280
21
40.5
18.4
21
8.0
7.3
18
15.4
1.3
Unidentified whale
1
197
—
1
36.3
—
1
0.1
—
1
13.0
—
Odontocetes
Dall's porpoise
90
167
118
90
40.1
14.9
90
5.6
5.5
72
14.3
1.7
Harbor porpoise
38
58
70
38
16.3
15.6
38
17.2
11.6
29
13.9
1.7
Pacific white-sided dolphin
24
689
505
24
65.6
25.7
24
8.3
8.7
20
15.0
0.8
Northern right-whale dolphin
1
259
—
1
16.2
—
1
0.7
—
Risso's dolphin
9
552
310
9
55.4
21.4
9
4.9
5.2
8
14.4
1.3
Killer whale
12
148
58
12
28.8
15.0
12
5.9
4.7
7
14.1
1.1
Unidentified delphinid
19
219
253
19
37.4
17.4
19
5.7
6.7
19
14.5
1.5
Pinnipeds and otters
Harbor seal
15
102
154
15
17.3
11.0
15
15.5
12.0
14
14.2
1.4
Elephant seal
20
466
370
20
46.2
18.5
20
3.8
5.0
16
14.7
1.8
California sea lion
4
91
74
4
22.8
15.2
4
9.3
14.2
1
13.9
—
Steller sea lion
4
34
18
4
11.3
5.4
4
18.5
6.6
3
13.6
0.4
Northern fur seal
22
382
349
22
47.1
17.1
22
3.1
3.7
21
14.3
1.4
Sea otter
3
22
1
3
8.9
0.5
3
25.5
18.1
3
12.6
0.4
Unidentified pinniped
13
170
144
13
30.5
18.4
13
8.0
8.1
11
14.5
1.9
All sightings
457
205
251
457
39.1
20.1
457
8.4
8.4
352
14.3
1.6
the continental shelf. Despite most of our effort being on
the continental shelf, the presence of several deep can-
yons in addition to the shelf edge, resulted in all species
being an average of less than 11 km from the 200 m
depth contour. The average surface water temperature
for species that were seen also varied and was likely
both a function of distance from shore and association
with upwelling areas (Table 9). Sea otters were seen in
the coldest waters (12.6°C) where they are predominant-
ly found. Among the more offshore species, humpback
whales, tended to be seen in colder waters (13.9°C) than
most other offshore species, probably because of their
association with offshore upwelling areas.
Discussion
Although humpback whales were the most abundant
large cetacean seen in our study, their numbers of a
few hundred still appear to be substantially lower than
numbers found prior to whaling. Commercial hunting
of humpback whales occurred in the 1900s from coastal
whaling stations in northern California, Washington,
and British Columbia. In these areas, thousands of
humpback whales were killed over a relatively short
time period (less than 10 years) before catches dropped
precipitously with the depletion of the population. At
the south end of our study area, 1933 humpback whales
were taken from a station at Bay City (in Grays Harbor),
Washington, from 1911 to 1925 (Scheffer and Slipp,
1948). To the north, 5638 humpback whales were taken
from British Columbia stations from 1908 to 1967, of
which 60f'f (3393) were taken from 1908 to 1917 from the
two southernmost whaling stations on Vancouver Island
closest to our study area (Gregr et al., 2000; Nichol et
al., 2002). Additionally, 1871 humpback whales were
taken from two stations in northern California from
1919 to 1926 (Clapham et al., 1997). Although these
hunts encompassed areas larger than our study area,
the number killed in short periods dwarfs even the sum
of our abundance estimates for Washington and British
Columbia and the estimate of under 1000 whales esti-
mated in the 1990s for California. Oregon, and Wash-
ington (Calambokidis and Barlow, 2004). Moreover,
humpback whales have not returned to some of the
areas where they were once found prior to commercial
Calambokidis et al.: Distribution and abundance of marine mammals off the northern Washington coast
577
whaling; humpback whales were commonly observed in
the inside waters of Washington and British Columbia
(Scheffer and Slipp, 1948; Webb, 1988) and have not
returned to these areas in any numbers (Calambokidis
and Steiger, 1990).
The distribution of humpback whales within our study
area was not uniform and indicated that some specific
areas were important feeding habitat for this recovering
species. The region between the Juan de Fuca Canyon
and the shelf edge (the Prairie) — the mouth of Bark-
ley Canyon and Swiftsure Bank — was the area where
humpback whales were concentrated. In monthly aerial
surveys in 1989-90 by Green et al.,5 there were only a
total of 13 sightings of 25 humpback whales along the
entire Washington coast between July and September.
Over half of those sightings were in the Prairie area.
Our line-transect estimates revealed that about 100
humpback whales inhabit the northern Washington
coast waters each summer; substantially more (over
500), however, were present in 2002. Although this is a
small number compared to estimates of just under 1000
humpback whales for California, Oregon, and Wash-
ington (Calambokidis and Barlow, 2004), our study
area encompasses a relatively small area and reflects a
high density of animals. Additionally our line-transect
estimates were not corrected for any missed animals;
therefore they are probably biased slightly downward.
Despite the relatively high density of humpback
whales in this region, the photographic identification
data indicated that a relatively small number of indi-
viduals use the area consistently. Both the line-transect
and the photographic identification data (increasing
capture-recapture estimates, as well as decreased pro-
portions of animals sighted multiple years) showed that
the number of whales using this region has increased in
recent years. The growing number of whales in this re-
gion could be either the result of births or immigration
into this area. Births alone could not account for this in-
crease, especially because the proportion of whales that
were mothers with calves seen in this region was not
high. There did not appear to be a shift in distribution
of animals from areas to the south because interchange
with those areas dropped from 1999 to 2002. The most
likely explanation for these changes is that there was a
shift of animals from feeding areas from the north into
this region beginning in the late 1990s.
This interchange of humpback whales with feeding ar-
eas to the south provides new insight into the structure
of humpback whale feeding aggregations. In a study
that examined interchange rates of humpback whales
6 Green, G. A., J. J. Brueggeman, R. A. Grotefendt, and C.
E. Bowlby. 1992. Cetacean distribution and abundance
off Oregon and Washington, 1989-1990. In Oregon and
Washington marine mammal and seabird surveys (J. J.
Brueggeman, ed. I, 100 p. Final report of OCS Study MMS
91-0093 by Ebasco Environmental, Bellevue, Washington,
and Ecological Consulting, Inc., Portland, Oregon, for the
Minerals Management Service, Pacific OCS Region, U.S.
Dept. of Interior, 770 Paseo Camarillo, Camarillo, CA
93010.
along the west coast, Calambokidis et al. (1996) iden-
tified northern Washington as a demographic bound-
ary between the whales feeding area along California,
Oregon, and Washington and those to the north. The
larger sample reported here shows the same general
pattern of decreasing interchange with distance from
a feeding area as that reported previously for whales
off California (Calambokidis et al., 1996). The decreas-
ing rate of interchange with distance among feeding
areas does not allow for a clear demarcation between
feeding areas, however, as suggested by Calambokidis
et al. (1996). Although humpback whales demonstrate
site fidelity to specific feeding locations, their feeding
aggregations may not have clear boundaries and may
occupy overlapping ranges.
The commercial whaling data also tended to support
the existence of somewhat discrete feeding areas off the
west coast of the United States and British Columbia.
Commercial whaling resulted in the depletion of hump-
back whales off British Columbia by 1917, whereas the
numbers taken off Washington and California did not
decline until the mid-1920s (Scheffer and Slipp, 1948;
Clapham et al., 1997; Gregr et al, 2000).
The relatively small proportion of mothers with calves
identified in our study is consistent with findings off
California and Oregon (Steiger and Calambokidis,
2000). Steiger and Calambokidis reported reproductive
rates along the California, Oregon, and Washington
coasts that are lower than those reported for other re-
gions in southeastern Alaska and the North Atlantic
(Clapham and Mayo, 1987, 1990; Baker et al., 1992;
von Ziegesar et al., 1994). In aerial transect surveys,
no humpback whale calves were seen among the 68
humpbacks observed off the Oregon and Washington
coasts in 1989-90 (Green et al.5). If geographic segre-
gation is occurring by humpback mothers and calves,
as was suggested by Steiger and Calambokidis (2000),
this northern region is not the area where mothers and
calves are congregated. It is interesting to note, how-
ever, that mothers and calves were distributed around
the periphery of the main feeding region — a finding that
suggests that a more local segregation may be occurring.
A bias in sampling would occur if large concentrations of
whales are targeted and mother with calves feeding on
the perimeter of these groups were underrepresented.
In contrast to humpback whales, no other large ror-
quals (blue, fin, or sei whales) were observed during
any of our ship or small boat surveys. Likewise, these
species were absent in other recent surveys of Wash-
ington waters (Wahl, 1977; Von Saunder and Barlow.
1999; Shelden et al., 2000; Green et al.5), although
they were seen in surveys farther offshore in surveys in
July 1994 (Thomason et al.6). Fin whales were common
,; Thomason, J., M. Dahlheim, S. E. Moore, J. Braham, K.
Stafford, and C. Fox. 1997. Acoustic investigations of
large cetaceans off Oregon and Washington: NOAA ship
Surveyor (21 July-1 August 1994), 27 p. Final report by
the National Marine Mammal Laboratory, 7600 Sand Point
Way NE F/AKC3, Seattle. WA 98115.
578
Fishery Bulletin 102(4)
in Washington waters in the early 1900s when they
were the second most commonly killed species by Bay
City whalers (Scheffer and Slipp, 1948). Blue and sei
whales were less common, although they were present
historically (Scheffer and Slipp. 1948). Although Bay
City whaling stations (in Grays Harbor, Washington)
were closed after humpback whales were depleted, se-
rial depletion of whale populations continued off British
Columbia waters, beginning with humpback and blue
whales, then with fin and sperm whales, and finally
with sei whales (Gregr et al., 2000).
No sperm whales or beaked whales were seen during
our surveys, although our study area did not include the
deeper waters where we would expect to find these spe-
cies. Most of the sperm whales (90%) seen by Green et
al.5 off Washington and Oregon were present in deeper
offshore waters outside of our study area.
The other cetacean species not seen in our surveys
that have been reported to occur off Washington his-
torically included northern right whale (Eubalaena
japonica), pygmy sperm whale iKogia breviceps), false
killer whale iPseudorea er-assidens), short-finned pilot
whale (Globicephala macrorhynchus), and striped dol-
phin (Stenella coeruleoalba) (Scheffer and Slipp, 1948).
Sightings of northern right whales throughout the east-
ern North Pacific are scarce; there have been only a
small number of sightings since the 1960s (Brownell
et al., 2001). Several of these sightings, however, have
been off the northern Washington coast (Fiscus and
Niggol, 1965; Osborne et al., 1988; Rowlett et al., 1994).
The primary reason for the paucity of sightings in the
eastern North Pacific in recent decades is due to the il-
legal take of 372 right whales in the early to mid-1960s
by the USSR (Brownell et al., 2001; Doroshenko7).
Although some small cetacean species such as Pacific
white-sided dolphins and Risso's dolphins were sighted
frequently on our surveys, they were not as common
as in some previous surveys (Green et al.5), probably
because our coverage was concentrated in shallower
waters inside the shelf break. In contrast to our find-
ings of a number of species seen near the shelf edge.
Wahl (1977) reported that most marine mammal species
off central Washington tended to be in either inshore
or in deeper offshore waters and only killer whales and
Dall's porpoises regularly used the slope waters (13-
45 km offshore).
It is difficult to make abundance estimates of Dall's
porpoise because of their proclivity to approach ships
(Buckland and Turnock, 1992). If they begin to ap-
proach the ship before the observer sights them, the es-
timate is biased upwards, which would be the case with
our estimate. Our estimate would also have a downward
bias because we did not attempt to adjust for animals
missed even if they were on the track line.
Doroshenko, N. V. 2000. Soviet whaling for blue, gray,
bowhead and right whales in the North Pacific Ocean.
1961-1979. In Soviet whaling sata (1949-1979), p.
96-103. Center for Russian Environmental Policv. Vavilov
St. 26, Moscow 117071, Russia.
All three types of killer whales (residents [both
northern and southern], transients, and offshore type)
were identified in the waters off northern Washington.
These sightings are interesting because of concerns
about killer whale populations, especially the southern
resident community that has declined in recent years.
Although killer whales have been intensely studied in
inside waters of the Pacific Northwest, little has been
known about their use of outside waters, where they
may spend large portions of their lives. Little is known
about the offshore type of killer whales, which is be-
lieved to be a distinct race of killer whale that has only
recently been described. These whales are believed to
be found usually in large groups along the continental
shelf but also have been seen in inland waters (Ford et
al., 1994; Dahlheim et al., 1997). All three sightings of
the offshore form were just west of the Juan de Fuca
canyon on the Prairie; the closest sighting to shore was
37 km (30 animals on 15 July 1997).
Acknowledgments
We are grateful to those who assisted with this study.
This work was supported by the Olympic Coast National
Marine Sanctuary and Southwest Fisheries Science
Center (Jay Barlow, COTR). Many people contributed
to this study. Jennifer Quan, Richard Rowlett, Anne
Nelson, and Annie Douglas worked on the ship surveys.
We thank the ship personnel on board the McArthur and
Agate Passage. Researchers who helped with small boat
work included Joe Evenson and Todd Chandler. Photo-
graphs of whales from this area were also contributed by
L. Baraff, R. Baird, P. Bloedel, V. Deeke. P. Ellifrit, G.
Ellis, J. Evenson, B. Gisborne. B. Halliday, H. Hunt, S.
Mizroch, K. Rasmussen, J. Wilson and SWFSC research-
ers. Permission to survey in Canadian waters was given
by the Dept. of Fisheries and Oceans. Lisa Schlender,
Kristin Rasmussen, and Annie Douglas organized and
conducted the photographic matching with the help of
many interns at Cascadia Research. DKE and Graeme
Ellis identified the killer whales; Oscar Torres assisted
with the photographic matching. Data analyses and
mapping were conducted with the help of Scot McQueen
at ESRI and Tom Williams.
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581
Abstract — The reproductive biology
of male franciseanas iPontoporia
blainvillei), based on 121 individu-
als collected in Rio Grande do Sul
State, southern Brazil, was studied.
Estimates on age, length, and weight
at attainment of sexual maturity are
presented. Data on the reproductive
seasonality and on the relationship
between some testicular characteris-
tics and age. size, and maturity status
are provided. Sexual maturity was
assessed by histological examina-
tion of the testes. Seasonality was
determined by changes in relative and
total testis weight, and in seminifer-
ous tubule diameters. Testis weight,
testicular index of maturity, and
seminiferous tubule diameters were
reliable indicators of sexual maturity,
whereas testis length, age, length,
and weight of the dolphin were not.
Sexual maturity was estimated to be
attained at 3.6 years (CI 957c = 2.7-
4.5) with the DeMaster method and
3.0 years with the logistic equation.
Length and weight at attainment of
sexual maturity were 128.2 cm (CI
95<£ = 125.3-131.1 cm) and 26.4 kg (CI
95^=24.7-28.1 kg), respectively. It
could not be verified that there was
any seasonal change in the testis
weight and in the seminiferous tubule
diameters in mature males. It is sug-
gested that at least some mature males
may remain reproductively active
throughout the year. The extremely
low relative testis weight indicates
that sperm competition does not occur
in the species. On the other hand,
the absence of secondary sexual char-
acteristics, the reversed sexual size
dimorphism, and the small number
of scars from intrassexual combats in
males reinforce the hypothesis that
male combats for female reproductive
access may be rare for franciscana.
It is hypothesized that P. blainvillei
form temporary pairs (one male copu-
lating with only one female) during
the reproductive period.
Reproductive biology of male franciseanas
(Pontoporio blainvillei) (Mammalia: Cetacea)
from Rio Grande do Sul, southern Brazil*
Daniel Daniiewicz
Grupo de Estudos de Mamiferos Aquaticos do Rio Grande do Sul (GEMARS)
Rua Felipe Nen, 382/203
Porto Alegre 90440-150, Brazil
Present address: Laboratono de Dinamica Populacional-Pontilicia Universidade Catolica do
Rio Grande do Sul (PUCRS)
Av. Ipiranga, 6681
Porto Alegre 90619-900, Brazil
Email address (for D Daniiewicz): Daniel. Danilewicza1 terra com br
Juan A. Claver
Alejo L. Perez Camera
Area Histologia y Embnologia Facultad de Ciencias Vetermarias
Universidad de Buenos Aires
Ar Chorroarin 280 C1427CWO
Buenos Aires, Argentina
Eduardo R. Secchi
Laboratono de Mamiferos Mannhos, Museu Oceanografico "Prof. Eliezer C. Rios"
Fundacao Universidade Federal do Rio Grande, Cx P. 379
Rio Grande 96200, Brazil
Nelson F. Fontoura
Laboratono de Dinamica Populacional-Pontificia Universidade Catolica do
Rio Grande do Sul (PUCRS)
Av. Ipiranga, 6681
Porto Alegre 90619-900, Brazil
Manuscript submitted 4 October 2002
to the Scientific Editor's Office.
Manuscript approved for publication
18 May 2004 by the Scientific Editor.
Fish. Bull. 102:581-592 (2004).
The franciscana (Pontoporia blainvil-
lei) is a small dolphin endemic to the
coastal waters of the southwestern
Atlantic Ocean. The distribution of
this species ranges from Golfo Nuevo
(42°35'S; 64°48'W), Chubut Province,
Argentina (Crespo et al., 1998) to
Itaunas (18°25'S; 30°42'W), Espirito
Santo, southeastern Brazil (Moreira
and Siciliano, 1991) (Fig. 1).
The franciseanas coastal habitat
makes it vulnerable to being caught
as incidental catch in gill nets and
trammel nets throughout most of the
species range (e.g., Praderi et al.,
1989; Corcuera et al., 1994; Secchi et
al., 2003). Because of its vulnerability
as bycatch, the franciscana has been
considered the most impacted small
cetacean in the southwestern Atlantic
Ocean (Secchi et al., 2002). In the
Rio Grande do Sul coast, southern
Brazil, this species has been subject
to an intense bycatch in gill nets for
at least three decades (Moreno et al.,
1997; Secchi et al., 1997; Ott, 1998;
Ott et al., 2002). The annual mor-
tality of franciseanas in this region
was estimated to range from several
hundred up to about a thousand indi-
viduals (Ott et al., 2002). Simulations
^Contribution 012 from the Grupo de
Estudos de Mamiferos Aquaticos do Rio
Grande do Sul (GEMARS), Rua Felipe
Neri, 382/203, Porto Alegre 90440-150,
Brazil.
582
Fishery Bulletin 102(4)
Figure 1
Map of the study area showing the locations along the southern coast of Brazil
where franciscanas were caught as bycatch between 1992 and 1998.
studies on the effects of incidental captures on francis-
canas in Rio Grande do Sul were carried out by using
available data on vital rates, stock size, and bycatch
estimates (e.g., Secchi, 1999; Kinas, 2002). All these
studies showed that there is a decline in franciscana
abundance in this region.
Although the reproductive biology of the female fran-
ciscanas have been studied in detail in Uruguay (Ka-
suya and Brownell, 1979; Harrison et al., 1981), Rio
Grande do Sul (Danilewicz et al., 2000; Danilewicz,
2003), and Rio de Janeiro (Ramos, 1997), there are few
data about male reproduction. Kasuya and Brownell
(1979) presented information on male reproduction for
Uruguay, although their small sample size precluded
them from estimating age and size at attainment of
sexual maturity.
In the Rio Grande do Sul coast, franciscanas are
known to reproduce seasonally; births occur from Oc-
tober to early February (about 75"7r from October to De-
cember). Because the gestation period was estimated to
last about 11.2 months, mating and conception may take
place between November and early March I Danilewicz,
2003). Seasonal changes in testicular size and activity
have been used to infer or corroborate mating seasons
in some cetacean species (e.g., Neimanis et al., 2000 I.
Nevertheless, it is not known if male franciscanas also
undergo seasonal changes in the testicular activity.
In this study, we describe the reproductive biology of
male franciscanas from Rio Grande do Sul and present
evidences for the species' mating system.
Materials and methods
Sampling procedures
Data and samples collected from 121 specimens inci-
dentally caught (889c) or beached (12%) along the Rio
Grande do Sul coast between 1992 and 1998 were used
for the analysis on reproduction of male franciscanas.
The sampling of the incidentally caught animals was
carried out through the monitoring of the commercial
fishery fleet from Rio Grande (32°08'S; 52°05'W) and
Tramandai/Imbe (29°58'S, 50°07'W). Stranded dolphins
were sampled from systematic beach surveys conducted
in an area with an extension of 270 km of sandy beaches,
between Torres (29°19'S, 49°43'W) and Lagoa do Peixe
(31°15'S, 50°54'W).
Not all information could be collected from each car-
cass; therefore sample sizes varied among parameters.
Standard length (SL, n = 118) was measured by following
the guidelines established by the American Society of
Mammalogy (1961). The animals were weighed (rc = 97)
and teeth were extracted and preserved dried or in a
1:1 mix of glycerin and alcohol (70%). Testes and epi-
didymis were removed and fixed in 10'> formalin.
Age determination
Age was estimated by counting the growth layer groups
(GLGs) in thin, longitudinal sections of teeth (ra=47).
The teeth were decalcified in nitric acid or in RDO
Danilewicz et al.: Reproductive biology of male Pontopona blainvillei from Rio Grande do Sul, southern Brazi
583
(a commercial mixture of acids) and sectioned on a freez-
ing microtome. The 15-20 fim sections were stained with
Mayer's hematoxylin and mounted on microscope slides
with Canadian balsam or in glycerin. Poor and off-center
sections were discarded in favor of new preparations.
Three readers counted independently the number of
growth layer groups in both the dentine and cementum.
When reader estimates differed, the sections were reex-
amined together and a best estimate was agreed upon.
In this study, we considered one GLG to represent one
year of age, which is the accepted model for the francis-
cana (Kasuya and Brownell, 1979; Pinedo, 1991; Pinedo
and Hohn; 2000).
Reproduction
In the laboratory, the testes were separated from the
epididymis, weighed to the nearest 0.01 g (n = 107), and
measured in three dimensions (length and two diam-
eters perpendicular to each other in the middle of the
testis) to the nearest 0.1 mm (;? = 104). The mean of
these two diameters was called mean testis diameter.
The weight of one of the gonads could not be recorded on
some occasions (« = 8) and we assumed that both testes
had the same weight. Then, relative testis weight was
determined as the ratio of the combined testis weight to
the animal weight.
A 1-cm3 subsample of each testis from the central
portion of the organ was removed and examined by
using standard histological preparations. The tissue
was embedded in paraffin, sectioned in 4-10 fim thick
slides through a manual microtome, and stained with
hematoxylin and eosin (H&E). Male sexual maturity
status was determined by examining the testicular
sections at a magnification of lOOx. In this study, we
followed the classification criteria suggested by Hohn
et al. (1985):
1 Immature — seminiferous tubules containing main-
ly spermatogonias. Abundant interstitial tissue
present between the seminiferous tubules and lu-
men totally closed.
2 Pubertal — seminiferous tubules containing sper-
matogonias and spermatocytes. Less interstitial
tissue present between the seminiferous tubules
than in immature animals. The lumen is partially
opened.
3 Mature — seminiferous tubules containing sper-
matogonias, spermatocytes, spermatids and, in
many cases, spermatozoa. Interstitial tissue al-
most nonexistent between the seminiferous tu-
bules. The lumen is totally opened.
The diameters of ten random circular seminiferous
tubules were measured for each specimen (« = 93) with
a scale present in the lens of the microscope in order
to calculate the seminiferous tubule mean diameter. A
maturity index (MI) was calculated as the ratio of the
combined testes weight by the combined testes length
aw/iL).
An analysis of the variation along the year of the val-
ues of relative and combined testes weight, and seminif-
erous tubule mean diameter, was employed to assess re-
productive seasonality. Values of these parameters were
compared between months when mating and conception
occur ("reproductive months": November-March) and
months when they not occur ( "nonreproductive months":
April-October). In order to increase the sample size of
mature animals collected in reproductive months, data
on testes weight from mature male franciscanas from
Uruguay were included in the analysis (data supplied
by Kasuya1).
The mean age at attainment of sexual maturity (ASM)
was estimated through the DeMaster (1978) method and
the logistic regression.
The DeMaster (1978) equation computes the mean
as
ASM = £a(/Q -f^),
where fa = the fraction of sexually mature animals in
the sample with age a;
j = the age of the youngest sexually mature
animal in the sample; and
k = the age of the oldest sexually immature
animal in the sample.
The variance of the DeMaster method estimate is cal-
culated as
k
variASM)=^[ifaa-fa)/Na-D],
«=j
where N = the total number of animals aged a.
The logistic regression approach fits a sigmoid curve
representing the probability that a franciscana of age
a is sexually mature to the distribution of sexually
mature and immature animals by age as
Y = l/(l+e°+/,v) or In (1/1-1) = a + bx,
where x = the age of the dolphin;
b = the slope of the regression; and
a = the intercept.
To obtain the age when 50% of the animals are sexu-
ally mature (Y=0.5), the last equation is simplified as
ASM = -alb.
Mean length and weight at sexual maturity was also
estimated by the DeMaster (1978) method, by substitut-
ing age for length and weight, respectively. The meth-
od was slightly modified, as suggested by Ferrero and
Walker (1993), and was calculated as
1 Kasuya, T. 1970-73. Unpubl. data. Teikyo University of
Science and Technology. Uenohara, Yamanashi Prefecture,
409-0193, Japan.
584
Fishery Bulletin 102(4)
Cmax
LSM= X Uft-ft-i),
Cmin
where Cmax = the length or weight class of the largest or
heaviest sexually immature animal;
Cmin = the length or weight class of the smallest
or lightest sexually mature animal;
L = the lower value of the length or weight
class t; and
ft = fraction of mature animals in the length
or weight class t.
The specimens were pooled into length and weight inter-
vals of 4 cm and 4 kg, respectively.
The estimated variance of this method is also modi-
fied and is calculated as
var(MS) = M>2 £ [(/; (1 -/",)/ A^, -l].
(x=33.6 mm), respectively. The weight and length of the
right testes ranged from 0.17 to 9.98 g (.v=2.62 g) and
from 17.9 to 60.0 mm (.v=34.5 mm), respectively. The
relationship of testes weight and testes length resulted
in significant regression (P<0.0001) and correlation
<r2=0.91; F=823.9; P<0.0001; y=0.000012x333). The male
with the heaviest relative testes weight was 141.6 cm in
length and 31.2 kg in weight, and its combined-testes
weight was 20.1 g, which is 0.064% of its total weight.
The mean of the relative testes weight from 23 mature
males was 0.036% of their total weight.
The testes of the franciscana are characterized by a
high lateral symmetry. There was no statistically dif-
ference in weight (£=-0.09; P=0.93; n=ll) and length
(*=-0.4; P=0.69; « = 100) between testes of the same
animal. A strong correlation was found between left
and right testes length (6 = 0.95; F=1073.0; r2 = 0.92;
P<0.0001; ra=100; y = 1.232 x095) and between left
and right testes weight (6 = 0.99; F=7262.8; r2 = 0.99;
P<0.0001; ra=71; y = 1.02.v1 °i, where x and y represent
values of the left and right testis, respectively.
where N: = the number of specimens in the length or
weight class f; and
w = the interval width, a constant equal to 4 in
these cases.
For estimating age, length, and weight at sexual matu-
rity, pubertal animals were grouped together with imma-
ture animals.
Results
The weight and length of the left testes ranged from
0.23 to 10.42 g (.r=2.60 g) and from 15.7 to 59.7 mm
§ 200 -i
yi
A _^_ ' A
<» 175-
A &- — A~^ A
3
J3
Aaa a, ■&
3 150 ■
-^'"~&A
tfl
^** — ' A
Zi
2 125-
0)
_D/-D
•p 100 -
□ y^
E
/S m
(D
ofs
en
D^Jn D
S 50-
/£] □
a>
E
ra 25 -
73
c
0)
5 0 2 4 6 8 10 12 14 16 18 20 22
Combined testes weight (g)
Figure 2
Relationship between combined-testes weight and mean seminiferous
tubule diameter in immature (open boxesi, pubertal (filled boxes), and
mature (triangles) male franciscanas (Pontoporia blainvillei) from Rio
Grande do Sul (re=59).
Seminiferous tubule diameter
A nonlinear regression demonstrated positive allometry
(6>0.333) of the seminiferous tubule diameter to the
combined testicular weight (6 = 0.39; 95% CI=0.35-0.44)
(Fig. 2), and a strong correlation between these two vari-
ables (F=343.6; r2 = 0.86; P<0.0001; y=59.4.x° 39).
The relationship between the seminiferous tubule di-
ameter and testes length is shown in Figure 3 and the
relationship between the seminiferous tubule diameter
and standard length is shown in Figure 4. In immature
males, there was almost no increase in the seminif-
erous tubule diameter with the increase of standard
length (0.26 jim/cm) and total weight (0.5 ^m/kg). In
mature males, however, seminiferous tu-
bule diameter was significantly correlat-
ed with standard length (6 = 1.06; F=4.4;
r2 = 0.18; P=0.048; y = 1.4775.v-43.572)
and there was no correlation with total
weight (6 = 0.23; P=1.28; r2=0.07; P=0.27;
y = 1.6132.\-+108.54).
The differences of the seminiferous tu-
bule mean diameters were statistically
significant between immature, pubertal,
and mature male franciscanas (ANOVA,
Fs=255.4; df=87; P<0.001).
Combined-testes weight and length,
and sexual maturity
There was almost no increment in mass
of the combined-testes weight in imma-
ture dolphins. An increment of only about
2.0 g in the combined-testes mass was
observed in animals of 70.0 to 125.0 cm in
length. For dolphins about 120.0-130.0 cm
in length, the combined-testes mass sud-
denly increased (Fig. 5), indicating the
Danilewicz et al.: Reproductive biology of male Pontopona blainvillei from Rio Grande do Sul, southern Brazil
585
attainment of sexual maturity. The rate of
testes-mass gain was 0.05 g/cm for imma-
ture and 0.28 g/cm for mature dolphins.
All animals with combined-testes weight
higher than 5.0 g were sexually mature,
and this finding may indicate that this
parameter can be used as a reliable indi-
cator of sexual maturity in male fran-
ciscanas from Rio Grande do Sul (Table
1). However, the large variation in testes
weight after the attainment of sexual
maturity precludes a correlation between
testes mass and standard length.
Although testes length increases pro-
gressively as standard length increases
(Fig. 6), there is no abrupt increase in
testes length at the moment of attain-
ment of sexual maturity, as observed in
the testes mass. A nonlinear regression
(exponential) best fits this relationship
(y =4. 5444 e0.0163.vi. As opposed to testes
mass, there is a considerable overlap in
the values of testes length of immature,
pubertal, and mature franciscanas (Table
1), which makes testes length a less reli-
able predictor of sexual maturity than
testes mass.
Age, length, and weight at sexual maturity
Forty-seven specimens in the sample pro-
vided information on age and reproduc-
tive status (35 immature or pubertal, and
12 mature). The oldest immature animal
was 5 years old and the youngest mature
was 2 years old (Table 1). Average age at
attainment of sexual maturity was esti-
mated to be 3.6 years by the DeMaster
method (SD = 0.47; 95% CI =2.7-4.5) and
3.0 years by the logistic equation Y = 1/(1+
eo.74-2 23i) The age structure of the sample
studied is presented in Figure 7.
Sexual maturity in relation to standard
length was estimated for 110 males. The
smallest mature and the largest immature
males were 120.5 and 137.5 cm long, respectively. The av-
erage length at sexual maturity was 128.2 cm (SD=1.49;
959r CI=125. 3-131.1 cm). Sexual maturity in relation to
total weight was estimated for 90 males. The lightest
mature and the heaviest immature males were 20.3 and
29.7 kg, respectively. The average weight at sexual matu-
rity was 26.4 kg (SD = 0.88; 95% 01=24.7-28.1 kg).
Index of testicular maturity
The differences of the mean index of testicular maturity
between immature (0.03), pubertal (0.04), and mature
(0.11) dolphins were statistically significant (ANOVA,
Fs=210.0 df=101, P<0.001). There was almost no overlap
in the values of this index between mature specimens
225 -I
~ 200
of 17S
E c
fS 150'
E c/>
i O 125'
f E too.
c
° 50 -
A
A A^&— - & —
^ A A A
A
■ A
16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62
hnsrns hnlers (ww)
Figure 3
Relationship between testes length and mean diameter of seminifer-
ous tubules in immature (open boxes), pubertal (filled boxes), and
mature (trianglesi male franciscanas (Pontoporia blainvillei i in Rio
Grande do Sul (ra=54). Data from pubertal animals are not included
in the curves.
5 g
205 ■
A
185 -
165 -
145 -
A 3
A^ AAA A^
A1 A A A
A A A
A
A
125 ■
*f»
105 -
85 ■
65 ■
45 ■
D
D
rjPrP
D
1
is?
crP^1
25 -
70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160
itanoaro lentth (nm)
Figure 4
Relationship between standard length and mean diameter of seminif-
erous tubules in immature (open boxes), pubertal (filled boxesl. and
mature (trianglesi male franciscanas (Pontoporia blainvillei) in Rio
Grande do Sul l;i=91>.
and immature and pubertal specimens (Table 1). All
males with an index value higher than 0.07 were sexu-
ally mature. These results indicate that the index of
testicular maturity is a very good indicator of sexual
maturity for franciscanas.
Reproductive seasonality
The null hypothesis that the combined and relative testis
weight would be higher in the months when the females
are reproductively active is rejected. No increase in the
testes weight was observed during the months when
most mating occurs (Fig. 8). There were no statistically
significant differences in the combined-testes weight
(ANOVA, Fs=2.28; df=34; P=0.48; n=35) and relative
586
Fishery Bulletin 102(4)
£
o
O
V a
nnj
60 70 80 90 100 110 120 130 140 150 160
Standard length V;ma
Figure 5
Relationship between standard length and combined-testes weight in
immature (open boxes), pubertal (filled boxes), and mature (triangles)
male franciscanas ^Pontoporia blainvillei) in Rio Grande do Sul (tt=79).
Data from pubertal animals are not included in the curves.
testes weight (ANOVA, Fs=2.42; df=29;
P=0.76; /? = 30) between reproductive and
nonreproductive months.
The analyses of the variation in the
diameter of the seminiferous tubules
throughout the year also did not indicate
that the testes undergo seasonal changes.
However, it is important to view this re-
sult with caution because the sample size
of mature males (and therefore the infor-
mation on tubules diameter collected in
reproductive months) was small (n=3).
However, the presence of spermatids or
spermatozoa (or both) in the seminiferous
tubules may be also regarded as a direct
evidence of testicular activity. Three ma-
ture males (119<-) in the sample presented
seminiferous tubules with spermatids or
spermatozoa (or both) and were collected
in nonreproductive months (May, June,
and August). Although the epididymis of
Table 1
Summarized information on age
length
mass, and testicul
ar characteristics for ma
e franciscanas iPontoporia
blainvillei) in the
Rio Grande do Sul at different sexual m
aturity stages.
Characteristics and maturity state
;?
Mean
Standard deviation
Range
Age (years)
Immature
31
1.29
1.01
0-5
Pubertal
4
2.0
0.82
1-3
Mature
12
3.8
1.14
2-6
Standard length (cm)
Immature
62
111.2
13.62
70.0-137.5
Pubertal
7
118.5
9.75
107.8-132.5
Mature
37
133.7
7.71
120.5-155.0
Total mass (kg)
Immature
53
19.0
5.6
4.95-29.7
Pubertal
6
21.4
4.62
17.1-28.0
Mature
30
29.9
5.22
20.25-41.5
Mean diameter of seminiferous t
ubules
(/./m)
Immature
54
69.6
12.2
50.0-105.0
Pubertal
6
95.0
19.2
74.5-121.2
Mature
33
154.1
21.7
113.0-197.0
Combined testes mass (g)
Immature
63
1.59
0.84
0.33-4.78
Pubertal
7
2.73
1.28
1.30-4.8
Mature
37
10.24
3.94
4.27-20.08
Testes length (mm)
Immature
62
27.2
4.9
15.7-35.5
Pubertal
7
32.6
6.2
25.0-41.0
Mature
35
45.4
5.6
31.6-59.7
Index of testicular maturity
Immature
61
0.03
0.01
0.01-0.06
Pubertal
7
0.04
0.01
0.02-0.06
Mature
36
0.11
0.03
0.05-0.18
Danilewicz et al.: Reproductive biology of male Pontoporia blainvillei from Rio Grande do Sul, southern Brazil
587
a subsample of 10 mature males were
examined histologically, we did not find
any sign of spermatozoa.
Discussion
The high bilateral uniformity in tes-
ticular weight and length presented
by the franciscana is a characteristic
shared with many other cetacean spe-
cies. Studies on the striped dolphin,
Stenella coeruleoalba (Miyazaki, 1977),
the common dolphin, Delphinus delphis
(Collet and Saint Girons, 1984), the
sperm whale, Physeter macrocephalus
(Mitchell and Kozicki, 1984), and the
dusky dolphin, Lagenorhynchus obscu-
rus (van Waerebeek and Read, 1994),
among others, demonstrate the same
pattern of testis symmetry. Given the
similar dimensions of both testes in
franciscanas, it is possible to extrapo-
late the combined-testes weight by
weighing only one testis without intro-
ducing bias in the analysis. It is recom-
mended, however, that the weight of
the testes should be presented without
the epididymis weight, as it was pre-
sented in the most extensive compara-
tive study on the subject (Kenagy and
Trombulak, 1986).
There is a negative allometry of the
seminiferous tubule diameter in rela-
tion to testis length, standard length,
and total weight. This pattern is ac-
centuated in immature males, in which
the tubule diameters remain almost
unchanged with the increase of the
other variables. The lack of values for
tubule diameters in the testes weight
interval (2.5-6.0 g) and testes length
interval (34-42 mm) just before the
attainment of sexual maturity (Figs.
2 and 3) indicates that the increase in
tubule size in relation to sexual matu-
rity must occur very quickly, probably
when the tubules are between 85 and
125 urn in diameter.
Attainment of sexual maturity
Length and weight at attainment of
sexual maturity of male franciscanas
in Rio Grande do Sul are very similar
to those values estimated in previous
estimates for Uruguay (Table 2). In con-
trast to the present study, Kasuya and
Brownell (1979) calculated mean length
at sexual maturity for Uruguay as the
65 -
60 ■
CO
E 55.
E
< 50-
'2 «
* c a <,, -0,0163*
y= 4,5444e
r! = 0.72 A .
A ^ 4 A &/* A
<
O) 35 ■
c/1
8) 30-
n
25
20
° DEh 3- — ° □
65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160
atcnecre Ignhth Ydma
Figure 6
Relationship between standard length and testes length in immature (open
boxes), pubertal (filled boxes), and mature (triangles) male franciscanas
(Pontoporia blainvillei) in Rio Grande do Sul i;; = 99l.
60 -I
50-
o
c
CD
g "»■
CD
<
CD 30-
O
CD
EC
1
10-
. 1
1 I ■ . _
0 year 1 year
2 years 3 years 4 years 5 years 6 years
Figure 7
Age structure of male franciscanas (Pontoporia blainvillei ) collected in
Rio Grande do Sul (n=48).
Figure 8
Relationship between month and relative testes weight in mature male
franciscanas (Pontoporia blainvillei) (7j=31) (l = January, 12 = December;
filled boxes=the nonreproductive months, open boxes=reproductive months).
Bars indicate 25^ and 75% percentiles.
588
Fishery Bulletin 102(4)
Table 2
Comparison between average age, weight, and length at
sexual maturity between male and female franciscanas
from Rio Grande do Sul and Uruguay. The means of the
animals from Rio Grande do Sul were estimated by using
the DeMaster method (modified! and those from Uruguay-
were estimated by using a linear regression to determine
the moment when 50(7( of the animals are mature.
Rio Grande do Sul
Uruguay'
Males Females2
Males Females
Age
Weight (kg)
Length (cm)
3.6 3.7
26.6 32.6
127.4 138.9
2-4 2.7
25.0-29.0 33.0-34.0
131.4 140.3
' Data from Uruguay were compiled from Kasuya and Brownell
11979'
2 Data from Damlewicz (2003).
length where 50r* of the dolphins were mature through
a linear regression. Applying this same approach, a LSM
of 125.4 cm was estimated for Rio Grande do Sul — a
value still very similar to the Uruguay estimate. Male
franciscanas attain sexual maturity at less length and
weight than do females in Rio Grande do Sul (Danile-
wicz, 2003), as observed previously in Uruguay (Kasuya
and Brownell, 1979) and Rio de Janeiro (Ramos et al.,
2000).
This is the first estimate of mean age at sexual ma-
turity presented for male franciscanas. Kasuya and
Brownell (1979) could not calculate ASM for Uruguay
because of their small sample size («=25). Nevertheless,
Kasuya and Brownell suggested that sexual maturity
is attained when males are between 2 and 4 years of
age. Franciscanas from Rio de Janeiro were considered
mature when they were older than 2 years of age and
larger than 115.0 cm in length (Ramos et al., 2000).
However, histological analysis of the testes was not
performed and Ramos et al. employed indirect methods
to determine sexual maturity. Nevertheless, despite the
uncertainties produced by the use of different criteria
to determine sexual maturity, it was evident that there
was substantial difference in the size at maturity be-
tween males from Rio de Janeiro and those from Rio
Grande do Sul and Uruguay. This difference is probably
the result of the well-known distinct growth patterns of
the franciscanas from these two regions (Pinedo, 1991)
and does not necessarily reflect an early attainment
of sexual maturity in males from the Rio de Janeiro
population.
The trade-off between growth and reproduction is
the best-documented phenotypic trade-off in nature
(Stearns, 1992) and has been studied in a wide range
of taxa. Because animals from Rio de Janeiro invest
less in growth than do animals from Rio Grande do
Sul, it is still an open question whether the francisca-
nas from the Rio de Janeiro have higher reproductive
rates or start reproducing earlier than those from Rio
Grande do Sul.
The oldest male and female franciscana ever aged
were 16 and 21 years-old, respectively (Kasuya and
Brownell, 1979; Pinedo, 1994). These ages contrasts
with the age distribution found in the present study,
where the oldest specimen analyzed was 6 years old.
Similar to what is observed in catches for several other
small cetacean species (e.g.. Hector's dolphins — Slooten
and Lad, 1991; harbor porpoise — Read and Hohn. 1995),
a general feature of incidental catches for these spe-
cies is the high entanglement rate of immature ani-
mals. In all fishing communities studied in Argentina,
Uruguay, and Brazil, a large proportion (>50%) of the
specimens caught were less than three years old (e.g.,
Kasuya and Brownell, 1979; Corcuera et al.. 1994; Ott,
1998; Di Beneditto and Ramos, 2001). Although the
precise reason for biased catch rates towards imma-
ture individuals is not well understood, it could be a
combination of factors, including the imbalanced age-
structure of local populations (where there are fewer
older individuals because of an extensive history as
bycatch) and a behavior-related higher vulnerability to
bycatch for immature individuals (i.e., juveniles can be
more inquisitive and have less ocean experience so that
they rove into the area increasing the chances of being
entangled). The typically low proportion of old animals
in bycatches may explain the characteristics of the data
used in this study.
Index of testicular maturity
An index of testicular maturity may be very useful
in studies where it is necessary to know the sexual
maturity of a large sample of animals without the need
of histological analysis, which is time consuming and
requires expertise. Although Hohn et al. (1985) recom-
mended the investigation of the applicability of this
indirect index of sexual maturity for male cetaceans,
the research on this subject has shown no progress. To
date, the index of sexual maturity has been calculated
only for the common dolphin, Delphinus delphis (Collet
and Saint Girons, 1984), and from the pantropical spot-
ted dolphin, Stenella attenuate! (Hohn et al., 1985). For
both species, this index distinguished satisfactorily the
mature from the immature and pubertal dolphins. Given
the results presented, we also recommend the use of the
index of testicular maturity as an alternative, nonhisto-
logical method, to determine the sexual maturity of male
franciscanas. Males with index values lower than 0.05
can be safely classified as immature, and males with
index values above 0.08 can be classified as mature. It is
recommended that for animals with intermediate values
their testes be analyzed histologically so that their
reproductive status may be determined definitively.
Besides making intra- and inter-populational com-
parisons possible, the index of testicular maturity also
permits interspecific comparisons because size differ-
ences between species are eliminated. The mean index
of testicular maturity of mature franciscanas (0.12) is
Danilewicz et al.: Reproductive biology of male Pontoporia blamvillei from Rio Grande do Sul, southern Brazil
589
considerably lower than mature pantropical spotted
dolphins (1.9) (Hohn et al., 1985). This difference is
a consequence of the relatively small increase of the
testes weight of male franciscanas when sexual matu-
rity is attained. Although male spotted dolphin show
a marked increase of about 25-fold in testes weight at
this moment, franciscanas show an increment in testes
weight of about ninefold only.
Reproductive seasonality
The reproductive activities in male mammals are usually
restricted to the periods when the females are in estrus
(Lincoln, 1992). Reproductive seasonality in males has
been reported for several cetacean species and popula-
tions through the identification of temporal variations
in the testes weight and histological characteristics. In
species where the reproductive period is restricted for
a few months, as with the dusky dolphin (Lagenorhyn-
chus obscurus) and the harbor porpoise (Phocoena pho-
coena), the testes weight presents marked fluctuations
accompanying the reproductive period (Read, 1990; van
Waerebeek and Read, 1994; Neimanis et al., 2000). Even
in species with a diffuse reproductive period (i.e., with
more than one peak for births per year) as in the case
of dolphins of the genus Stenella in the tropical Pacific,
it was possible to detect seasonal variation in the male
reproductive rhythm (Perrin et al., 1976, Hohn et al.,
1985).
Because of the known seasonality for births for fran-
ciscana (Kasuya and Brownell, 1979, Harrison et al.,
1981, Danilewicz, 2003), it would be expected that the
males would accompany the female rhythm, decreas-
ing or even ceasing testicular activity in autumn and
winter months. Kasuya and Brownell (1979) examined
the seasonal change in testes weight in the months of
January, June, and December. From our knowledge of
the species' reproduction period, testes weight would
be expected to be higher in December and January.
However, the authors could not confirm this predic-
tion and attributed the lack of seasonality to the small
sample size of mature animals. Nevertheless, the lack
of seasonality, even when the testes weight of the ma-
ture males from Rio Grande do Sul are included, may
indicate what is occurring in the population, and not be
a bias introduced by a small sample size.
In species that possess small testes, as in the case of
the franciscana, the variation in the testicular activity
may be better reflected by changes in the diameter of
the seminiferous tubules and the rate of spermatogen-
esis rather than by changes in the testes weight. Nev-
ertheless, the preliminary results about these charac-
teristics (mature males with spermatids or spermatozoa
[or both] in the seminiferous tubules in nonreproductive
months and little monthly variation in the diameter
of the seminiferous tubules) also do not support the
hypothesis of a male reproductive seasonality. The com-
bination of results presented here indicates that testicu-
lar activity is not completely interrupted in all males
within the population, and that at least some of them
may remain capable of fertilizing females during the
year. This conclusion is supported by the observation
of pregnancies outside the normal gestation season and
that the births resulting from these pregnancies were
estimated to take place in September and in late March
(Danilewicz, 2003).
The hormone and sperm production by the testes dur-
ing periods when the females are not able to reproduce
may represent an unnecessary energetic expense by
the male (Dewsbury, 1982) and may be an explanation
for the period of reproductive inactivity for males of
several mammal species. In species with large relative
testes weight, the maintenance of high levels of sperm
production in the testes is a considerable energetic cost
for the individual. However, as discussed earlier, this
is definitely not the case for the franciscana. For this
reason, we suggest that the small energy investment
in producing sperm all over the year, due to the small
testicular mass, may be an evolutionary advantage for
male franciscanas in case of the appearance of off-sea-
son reproductive females.
Franciscana reproductive strategy
Although important advances in the knowledge of fran-
ciscana behavior in the wild have been made (e.g., Bor-
dino et al., 1999; Bordino, 2002), there is no information
on the species' reproductive behavior and its mating
strategy remains unknown. Relative testis weight,
sexual size dimorphism, and secondary sexual charac-
teristics may provide indirect clues regarding mating
strategy in franciscana and are discussed below.
Relative testis weight In mammals, there is a func-
tional relationship between relative testis weight and
the species' mating system (Kenagy and Trombulak,
1986). Testes are relatively small in species presenting
monogamy or extreme poliginy (several females + few
males), i.e., where a male copulates with all females of a
group or harem. Comparative studies have demonstrated
that males tend to be larger than females and show
secondary sexual characteristics in species present-
ing extreme poliginy. On the other hand, the relative
testis weight is high and the sexual size dimorphism is
reduced or nonexistent in species where several males
copulate with only one estrus female (polyandry). In
this case, the evolution for a large testis is attributed
to the sperm competition in a system where different
males attempt to fertilize the same female and where a
higher copulatory frequency and higher levels of sperm
production are required (Harcourt et al., 1981; Kenagy
and Trombulak, 1986).
Using the data on 133 mammal species, Kenagy and
Trombulak (1986) presented a function describing the
relationship between body weight and combined-testes
weight without epididymis. Applying their equation
for the adult male franciscanas, we discovered that
mature franciscanas have testes 3 to 12 times lighter
than expected (mean = 6 times) for a mammal of its
body weight. Indeed, among the 133 species analyzed,
590
Fishery Bulletin 102(4)
the relative testes weight of the franciscana is heavier
than that of gorilla {Gorilla gorilla), humpback whales
(Megaptera novaeangliae), and fin whales iBalaenoptera
physalus), indicating that sperm competition does not
occur in franciscanas.
Sexual size dimorphism Males are larger than females
in most mammal species. Nevertheless, the reversed
sexual size dimorphism (RSSD) (i.e., females are larger
than males) is more common than previously thought
and has been documented for 12 out of the 20 orders of
mammals (Ralls, 1976, 1977). Among the odontocetes,
four (Ziphidae, Pontoporiidae, Phocoenidae, and Delph-
inidae) out of the eight families present RSSD.
Although sexual selection may be the main reason
why males are the larger sex in most mammal species,
it has been systematically refused as an explanation in
the cases where females are the larger sex (Ralls, 1976,
1977; Andersson, 1994). In species with RSSD, females
do not mate with many males, they are not dominant,
and are not more aggressive than males of the same
species. Moreover, they do not show secondary sexual
characteristics associated with intrasexual selection
(e.g., horns in Artiodactyla and large canine teeth in
Primates). Therefore, the occurrence of RSSD in mam-
mals may be explained more satisfactorily by natural
selection (Andersson, 1994).
Slooten (1991) proposed an interesting hypothesis
for the occurrence of RSSD in cetaceans, suggesting
that a minimum size may be necessary for a newborn
cetacean to survive. In odontocetes, the smallest mean
sizes at birth are about 70-80 cm. Because the size of
the newborn is directly related to the size of the moth-
er, in species of small dimensions the females would
suffer a selective pressure to be a larger size, so that
they could produce offspring with the minimum viable
size. This hypothesis is reinforced by the fact that most
of the odontocete species with RSSD (e.g., Pontoporia
blainvillei, Cephalorhynchus hectori, Cephalorhynchus
commerssoni, Phocoena phocoena, Phocoena sinus) are
the smallest species within the group. Moreover, spe-
cies presenting RSSD also have larger relative size at
birth than the other species within the taxonomic group
(Ralls, 1976).
The degree and direction of SSD (sexual size dimor-
phism) in mammals is the result of the difference of
the sum of all selective pressures affecting the female's
size and the sum of all selective pressures affecting the
male's size (Ralls, 1976). Thus, it is very probable that
more than one factor may act selectively on animals
of both sexes in Pontoporia, molding the degree and
direction of SSD. We propose that the requirement of
a neonate minimum viable size (70-80 cm in length)
is one of the main selective pressures acting on female
franciscanas. It is important to emphasize that other
factors may also be influencing SSD in franciscana,
and in some species it was evident that different selec-
tive pressures could affect body size in opposing direc-
tions in males and females and in different age classes
(Grant, 1986; Andersson, 1994). Among the factors that
may be simultaneously acting on franciscana body size
are intrinsic genetic and physiological limitations, and
the requirement of maintaining an optimum size for the
species' ecological niche.
Secondary sexual characteristics The presence and
intensity of secondary sexual characteristics in males
is a more precise indication of the degree of intrasexual
selection than is body size (Andersson, 1994). In odonto-
cete males, these characteristics are present in the form
of "weapons," such as the tusk of the narwhal (Monodon
monoceros) and the teeth in species of the genus Gram-
pus, Physeter, Berardius, Hyperoodon, and Mesoplodon
used in male-male combats (MacLeod. 1998). In spe-
cies of these genus, the teeth were reduced in number,
enlarged in size, and their form was modified (specially
in males of Ziphiidae). The teeth of these species also
lost their function in feeding because of a diet comprising
almost exclusively cephalopods and were used uniquely
in intrasexual combats. There is no evidence that the
same evolutionary process occurred in male francisca-
nas because their teeth are very small and numerous
(around 200), their diet is primarily fish, and the number
of combat scars is apparently low. These characteristics
support the hypothesis that male-male combat must be
very rare or even nonexistent in franciscanas.
The sexual features presented in this study (extremely
low testis weight, reversed sexual size dimorphism, ab-
sence of secondary sexual characteristics in males, and
a low number of scars in males) indicate the absence of
sperm competition in the franciscana, and these features
differ drastically from those characteristics of odonto-
cete species where males combat each other for copula-
tion. This finding may indicate that franciscanas form
temporary reproductive pairs during the reproductive
period, where a male pairs and copulate with only one
female. Recently, Valsecchi and Zanelatto (2003) pro-
vided molecular evidence suggesting that franciscanas
may travel in kin groups that include mothers with their
calves and the father of the youngest offspring. The au-
thors also suggested that male franciscanas may prolong
their bond with their reproductive partner, providing
some form of paternal care. For a better understanding
of franciscana social structure and mating system, the
following suggestions are proposed: 1) an increase in the
efforts of behavioral studies of free-ranging francisca-
nas; 2) quantification of the intraspecific teeth scars in
franciscanas of different sexes and reproductive status
in order to confirm the absence of intrassexual aggres-
sions among males; 3) investigation of the relationship
of relative testis weight, SSD. and reproductive strate-
gies in cetaceans, by phylogenetic methods (see Harvey
and Pagel. 1991) to understand the evolution of these
characters in this group.
Acknowledgments
This study could not be made without the cooperation
and friendship of the fishermen from Tramandai/Imbe
Danilewicz et al.: Reproductive biology of male Pontopona blainvillei from Rio Grande do Sul, southern Brazil
591
and Rio Grande. Many people collaborated in the collec-
tion and necropsy of the dolphins, and the authors wish
to thank Paulo Ott, Ignacio Moreno, Marcio Martins,
Glauco Caon, Larissa Oliveira, Manuela Bassoi, Alexan-
dre Zerbini, Luciana Moller, Luciano Dalla Rosa, Lilia
Fidelix, and numerous volunteers for helping in this
task. Gonad histology was partially done in Laboratorio
de Histologia e Embriologia Comparada of Universi-
dade Federal do Rio Grande do Sul and we thank Sonia
Garcia and Nivea Lothhammer for their instructions
and encouragement on this subject. Paulo Ott, Enrique
Crespo and Silvana Dans participated in the age deter-
mination procedures. Part of the age determination was
also done in the Rio Grande and the first author thanks
Cristina Pinedo and Fernando Rosas for their instruc-
tion. The authors also thanks Norma Luiza Wiirdig,
Iraja Damiani Pinto (CECLIMAR-UFRGS), and Lauro
Barcellos (Director of the Museu Oceanografico) for their
constant logistical support and for encouraging marine
mammal studies in southern Brazil. Marcio Martins,
Ignacio Moreno, Luiz Malabarba, and Monica Muelbert
reviewed an early draft of this paper. We wish to thank
Renata Ramos and three anonymous reviewers for their
suggestions regarding the manuscript. Financial support
was given by Cetacean Society International, Fundacao
O Boticario de Protecao a Natureza, The MacCarthur
Foundation, World Wildlife Fund, CNPq, UNEP, Yaqu
Pacha Organization, and Whale and Dolphin Conser-
vation Society. This paper is part of the first author's
M.S. thesis, and The Coordenagao de Aperfeicoamento
de Pessoal de Nivel Superior (CAPES) has granted
him a graduate fellowship. The Conselho Nacional de
Desenvolvimento Cientifico e Tecnologico of the Brazilian
Government (CNPq) has granted graduate fellowships
to E.R. Secchi (Grant no. 200889/98-2).
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593
Abstract— Red snapper (Lutjanus
campechanus) in the United States
waters of the Gulf of Mexico ( GOM )
has been considered a single unit
stock since management of the spe-
cies began in 1991. The validity of this
assumption is essential to manage-
ment decisions because measures of
growth can differ for nonmixing popu-
lations. We examined growth rates,
size-at-age, and length and weight
information of red snapper collected
from the recreational harvests of Ala-
bama (n=2010), Louisiana (re=1905),
and Texas (re=1277) from 1999 to
2001. Ages were obtained from 5035
otolith sections and ranged from one
to 45 years. Fork length, total weight,
and age-frequency distributions dif-
fered significantly among all states;
Texas, however, had a much higher
proportion of smaller, younger fish.
All red snapper showed rapid growth
until about age 10 years, after which
growth slowed considerably. Von Ber-
talanffy growth models of both mean
fork length and mean total weight-
at-age predicted significantly smaller
fish at age from Texas, whereas no
differences were found between Ala-
bama and Louisiana models. Texas
red snapper were also shown to differ
significantly from both Alabama and
Louisiana red snapper in regressions
of mean weight at age. Demographic
variation in growth rates may indicate
the existence of separate management
units of red snapper in the GOM. Our
data indicate that the red snapper
inhabiting the waters off Texas are
reaching smaller maximum sizes at
a faster rate and have a consistently
smaller total weight at age than those
collected from Louisiana and Alabama
waters. Whether these differences are
environmentally induced or are the
result of genetic divergence remains
to be determined, but they should be
considered for future management
regulations.
Red snapper (Lutjanus campechanus)
demographic structure in the northern
Gulf of Mexico based on spatial patterns
in growth rates and morphometries
Andrew J. Fischer
Coastal Fisheries Institute
School of the Coast and Environment
Louisiana State University
Baton Rouge, Louisiana 70803-7503
E-mail address: afische g Isu edu
M. Scott Baker Jr.
Coastal Fisheries Institute
School of the Coast and Environment
Louisiana State University
Baton Rouge, Louisiana 70803-7503
Charles A. Wilson
Coastal Fisheries Institute and
Department of Oceanography and Coastal Sciences
School of the Coast and Environment
Louisiana State University
Baton Rouge, Louisiana 70803-7503
Manuscript submitted 6 May 2003
to the Scientific Editor's Office.
Manuscript approved for publication
19 April 2004 by the Scientific Editor.
Fish. Bull. 102:593-603 12004).
Red snapper {Lutjanus campechanus)
in the United States waters of the Gulf
of Mexico (GOM) are heavily exploited
by both recreational and commercial
fishermen (Wilson and Nieland, 2001;
Shirripa and Legault1). Harvest, how-
ever, has not proceeded without det-
rimental affects on the population.
Commercial landings have declined
substantially from 6048 metric tons (t)
in 1964 to 1207 t in 1990; recreational
landings exhibited similar declines
from 1937 t in 1981 to 481 t in 1990
(NMFS'2). In 1991, harvest restrictions
including reef fish permits, seasonal
fishing, fish quotas, creel limits, and
minimum size limits were placed upon
the red snapper fishermen by the Gulf
of Mexico Fishery Management Council
(GMFMC3) to increase the spawning
potential ratio to 20%, which is indic-
ative of recovery. These regulations
have also been adopted for state waters
in Alabama, Louisiana, and Texas.
Despite the management actions, GOM
red snapper remain overfished (Good-
year4; Schirripa and Legault1).
1 Shirripa, M. J., and C. M. Legault.
1999. Status of the red snapper in the U.
S. waters of the Gulf of Mexico; updated
through 1998, 44 p. + appendices. Con-
tribution rep. SFD-99/00-75 from Sus-
tainable Fisheries Division. Miami
Laboratory, Southeast Fisheries Science
Center, National Marine Fishery Ser-
vice, 75 Virginia Beach Drive, Miami,
FL 33149-1099. [Not available from
NTIS],
2 NMFS (National Marine Fisheries
Service). 2003. Fisheries Statistics
and Economics Division. Website: www.
nmfs.noaa.gov.
3 GMFMC (Gulf of Mexico Fishery Man-
agement Council). 1991. Amendment
3 to the reef fishery management plan
for the reef fish resources of the Gulf
of Mexico, 38 p. Gulf of Mexico Fish-
ery Management Council, 3018 N. U.S.
Hwy 301 Suite 1000, Tampa, FL. 33619-
2272. [Not available from NTIS],
4 Goodyear, C. P. 1995. Red snapper in
U.S. waters of the Gulf of Mexico. Stock
assesment report MIA-95/96-05, 171 p.
Miami Laboratory, Southeast Fisheries
Science Center, National Marine Fish-
eries Service, 75 Virginia Beach Dr.,
Miami, FL, 33149-1099. [Not available
from NTIS].
594
Fishery Bulletin 102(4)
96c
94c
92 ;
90
88 : 86 : 84
82 ;
80
32°
?
/> ^M, — ,
30°
Fourchon,
Daulphin Island, AL ,
28°
7*
LA
26°
S Port Aransas
TX
-**-^
24°
N
400
0
400
800 Kilometers
A
22°
32
30
28
26
24
22
96
94°
92°
90
88° 86°
84
82 =
80
Figure 1
Map of the northern Gulf of Mexico showing the three red snapper iLutjanus campecha-
nus) sampling locations.
An underlying assumption crucial to a fishery man-
agement plan is that the fish species being managed
is a unit stock (Gulland, 1965). A stock is defined as
the part of a fish population that is under consideration
as an actual or potential resource (Ricker, 1975). Since
management began in 1991, red snapper in the north-
ern GOM have been considered a unit stock. Genetic
studies to date have shown that there is little evidence
to dispute this assumption (Camper et al., 1993; Gold
et al., 1997, Heist and Gold, 2000). On the other hand,
tag-recapture studies indicate that red snapper have
the capacity to move great distances, making it pos-
sible for separate stocks to develop (Patterson et al.,
2001).
The validity of an assumption of a single stock of red
snapper is essential to management decisions because
measures of growth, natural mortality, reproductive
capacity, and recruitment can differ among nonmix-
ing populations. Should separate red snapper stocks
exist, management plans would have to be enacted
for each defined stock in order to follow federal guide-
lines. Even if a single large red snapper stock exists,
management should be sensitive to both the diversity
of habitats and user groups within the species area of
occurrence. Because red snapper are arguably the most
important recreational and commercial offshore fishery
from Florida to southern Texas, every effort should be
undertaken to develop the most effective and productive
management plan.
The objective of this study was to evaluate the stock
structure of GOM red snapper based on growth rates
and size-at-age information. We hypothesized that red
snapper sampled from across the northern GOM would
be indistinguishable in their growth rates and size at
age — a uniformity indicative of a single unit stock.
Methods and materials
Red snapper were collected from the recreational har-
vests of 1999, 2000, and 2001 from the northern GOM
at Dauphin Island, Alabama, at Port Fourchon, Louisi-
ana, and at Port Aransas, Texas (Fig. 1). A maximum
of 75 fish were randomly selected and sampled from
the daily catch of each charter boat or head boat while
the captains and deck hands cleaned fish. These fish
were not selected by size. Larger individuals (>6.8 kg)
were opportunistically sampled from spear fishing and
hook-and-line fishing tournaments in Alabama and
Louisiana. In addition, a number of smaller fish (<406
mm. <457 mm during summer 1999) were randomly
sampled during red snapper tagging cruises in Alabama.
Morphometric measurements were recorded I fork length
[FL] in mm, total weight [TW] in kg, and eviscerated
body weight |BW| in kg), sex was determined by macro-
scopic examination of gonads, and both sagittal otoliths
were removed, rinsed, and stored in coin envelopes until
processed. Fish weights were not recorded for 1999 Texas
samples.
A transverse thin section (containing the core) was
taken from the left sagittal otolith of each individual.
Sections were made with the Hillquist model 800 thin-
sectioning machine equipped with a diamond embedded
wafering blade and precision grinder (Cowan et al.,
1995). When the left otolith was unavailable, the right
otolith was sectioned. Examinations of otolith sections
were made with a dissecting microscope with transmit-
ted light and polarized light filter at 20x to 64x mag-
nification Opaque annulus counts were made along the
ventral side of the sulcus acousticus from the core to
the proximal edge (Wilson and Nieland. 2001). Annulus
counts were performed by two independent readers (AJF
Fischer et al.: Demographic structure of Lutjanus campechanus in the northern Gulf of Mexico
595
and MSB) without knowledge of either date of capture
or morphometric data. The appearance of the otolith
section edge condition was coded as opaque or translu-
cent after Beckman et al. (1989). Annuli were counted a
second time when initial counts disagreed. In instances
where a consensus between the two readers could not be
reached, annulus counts of the more experienced reader
(AJF) were used. Between-reader differences in annulus
counts were evaluated with the coefficient of variation
(CV), index of precision (D) (Chang, 1982), and average
percent error (APE) (Beamish and Fournier, 1981). The
periodicity of opaque zone formation was verified for
each sampling location with edge analysis after Wilson
and Nieland (2001). Ages of red snapper were estimated
from opaque annulus counts and capture date with the
equation described by Wilson and Nieland (2001):
Day age= -182 + (opaque increment count
((»;-!) x 30) + d,
365) +
where m = the ordinal number (1-12) of month of cap-
ture; and
d = the ordinal number (1-31) of the day of the
month of capture.
The 182 days subtracted from each age estimate are to
account for the uniform hatching date assigned for all
specimens (Render, 1995; Wilson and Nieland, 2001).
Age in years was assigned by dividing day age by 365.
Fork length-TW relationships were fitted with lin-
ear regression to the model FL = a TWb from log1(l-
transformed data for Alabama, Louisiana, and Texas
specimens. Analysis of covariance (ANCOVA) was used
to compare slopes and intercepts among sampling lo-
cations (SAS, 1985). Variability in age. FL, and TW
frequency distributions of red snapper were compared
among states with the Komolgorov-Smirnov two-sample
test (Tate and Clelland, 1957).
Growth of red snapper was modeled for FL and TW
with the von Bertalanffy growth equations. Because
of differences in sample population size among states,
weighted mean FL and mean TW at age were fitted for
each state with nonlinear regression in the forms:
FL, = LJ1 -e'-*"11)
TW, = Wjl-el-'''"'!)''.
where FL, = FL at age t\
TW, = TW at age /;
L„ = the FL asymptote;
W„ = the TW asymptote;
k = the growth coefficient;
t = age in years; and
b = exponent derived from our length-weight
regressions (SAS, version 5, 1985, SAS
Inst, Cary, NO.
Because of a lack of smaller individuals in all sample
populations, no y-intercepts for t0 were specified and
models were forced through 0. Larger individuals and
Table 1
Numbers of red snapper (Lutjanus camped
lanus)
sampled
from recreational sources by stai
e and year.
State
Males
Females
Jnknown
sex
Total
Alabama
1999
434
396
5
835
2000
355
415
7
111
2001
189
209
0
Total
398
2010
Louisiana
1999
367
339
31
737
2000
399
397
8
804
2001
160
179
25
Total
364
1905
Texas
1999
268
293
14
575
2000
278
284
22
584
2001
52
56
10
Total
118
1277
juveniles selectively sampled by size were excluded from
the models to more accurately reflect a random sample.
Likelihood ratio tests (Cerrato, 1990) were used to test
for differences among states in models and in growth
parameter estimates. Differential growth was evalu-
ated for red snapper in the first 10 years of life when
somatic growth is most rapid (Szedlmayer and Shipp,
1994; Patterson et al., 2001; Wilson and Nieland, 2001).
Linear regressions of mean FL and mean TW at age for
fishes aged 1 to 10 years were compared among states
with analysis of covariance (ANCOVA) and tested for
homogeneity of slopes.
Results
During the three-year study period, 5192 red snapper
were sampled from the recreational harvest of the north-
ern GOM (Table 1): 642 individuals from fishing tourna-
ments, 71 undersize fish from tagging cruises, and 4479
random samples from recreational catches. The samples
included 2502 males, 2568 females, and 122 individu-
als of undetermined sex. The resultant male-to-female
ratios were 0.96:1 for Alabama, 1:0.99 for Louisiana,
0.94:1 for Texas, and 0.97:1 for all states combined. A
chi-square test indicated no significant difference in
the number of males to females (j2=0.78, P=0.38). Fork
lengths ranged from 237 to 916 mm (Fig. 2A). Speci-
mens from Alabama ranged from 237 to 916 mm FL,
Louisiana specimens ranged from 282 to 913 mm FL,
and Texas specimens ranged from 266 to 846 mm FL.
The FL frequency distributions of the random samples
were different among all states (AL and LA, maximum
difference (MD)=5.26; AL and TX, MD = 51.86; LA and
TX, MD = 51.77)(Fig. 2A).
596
Fishery Bulletin 102(4)
30 ->
25
20
15
10
n ,nnM
DAL
■ LA
DTX
tlk^^idirftr^.,.
125 250 300 350 400 450 500 550 600 650 700 750 800 850 900
Fork length (m)
50
45
40
35
30
25
20
15
10
5
0
B
:;
IV ryfk .ryryry r* n .rim m ri r. . . .fl
5 6 7
Total weight (kg)
10
>10
Figure 2
Distributions of (A) fork length in mm (/! = 5177) and (B) total weight in
kg (n = 4531l for red snapper (Lutjanus campechanus) sampled from the
1999-2001 recreational harvests of Alabama. Louisiana, and Texas.
Total weights of all fish sampled ranged from 0.11
to 17.35 kg (Fig. 2B). Specimens from Alabama ranged
from 0.22 to 15.42 kg TW, Louisiana specimens were
0.42 to 17.35 kg TW, and Texas specimens ranged from
0.33 to 9.42 kg TW. Total weight-frequency distributions
(in 0.5 kg increments) differed significantly between all
states (AL and LA, MD = 5.37; AL and TX, MD = 53.68;
and LA TX, MD = 52.28)(Fig. 2B). Significant differ-
ences in red snapper FL-TW regression models were
detected among states (ANCOVA test of homogeneity of
slopes, F5 4522=23.36; P<0.001; r2=0.98; ANCOVA test
for equal intercepts, F5 4522=22.77, P<0.001, r2=0.98);
therefore, separate models were fitted for each state.
The resultant equations were
AL TW= 1.51 x 10-"' iFL:,,i:i)
(F1;1965=102740; P<0.0001; r2=0.98);
TX TW = 2.88 x 10-5 (PL2-92)
LA TW = 1.02 x 10-r' iFL
')
^1;
= 13345; P<0.0001; r2=0.95).
(P
1;1856
=77981; P<0.0001; r2=0.98);
Ages were obtained from 5035 transverse otolith sec-
tions. Thirty fish had otolith sections deemed unread-
able by both readers. The age estimates determined by
the two readers were evaluated for reader agreement,
precision, and average percent error for first and sec-
ond readings of otolith sections by sample year. Table 2
gives APE, CV, D. percentage agreement (O), and per-
centages of differences in age estimates (±1, 2, and 3
years). The readers agreed on age estimates for 4053
otoliths (80.5%) after the initial reading. Re-examina-
tion of the 982 otolith sections for which annulus counts
differed produced agreement for 5007 individuals.
We compared the timing of opaque annulus formation
among red snapper sample sites by plotting the monthly
occurrence of maximum and minimum proportions of
opaque otolith edges. Sample limitations of red snapper
in Texas, however, prevented meaningful comparisons of
Fischer et al.: Demographic structure of Lut/anus campechanus in the northern Gulf of Mexico
597
opaque annulus formation for this state. However, mini-
mum proportions of opaque edges during the months of
April through October may indicate that red snapper
from Texas form an opaque annulus during the winter
months. Proportions of opaque edges for Alabama and
Louisiana were essentially the same: maximum propor-
tions of opaque edges during the months of February
and March followed by a decrease to minimum propor-
tions during the months of May through November
(Fig. 3). These findings are consistent with previous
age and growth studies on red snapper in the northern
COM (Patterson et al, 2001; Wilson and Nieland, 2001),
indicating that the formation of one opaque annulus in
the winter months is followed by the formation of one
translucent annulus in summer. Annulus-based age
estimates of red snapper from the northern GOM have
also been validated to 55 years with otolith radiocarbon
chronologies based on accelerator mass spectrometry
14C measurements (Baker and Wilson, 2001).
Red snapper ages ranged from 1 to 45 years and the
majority (90%) of individuals were between 2 and 6
years (Fig. 4). Alabama fish ranged from 1 to 35 years
(re=1985), Louisiana fish ranged from 2 to 37 years
(n=1864). and Texas fish ranged from 1 to 45 years
(rc=1186). Modal ages were 4 years for Alabama and 3
years for Louisiana and Texas red snapper. We found
significant differences among age-frequency distribu-
tions from all states (AL and LA, MD = 9; AL and TX,
MD = 33.84; and LA and TX, MD=24.84). Texas had a
much higher proportion of younger individuals; 63% of
sampled fish were aged at 3 years or less compared to
only 30% of Alabama and 39% of Louisiana fish aged
at 3 years or less.
Red snapper growth was modeled from weighted mean
FL at age and mean TW at age by using the von Berta-
lanffy growth equation (Fig. 5, A and B). Resultant von
Bertalanffy growth equations were
Table 2
Differences between two readers in average percent error
(APE).
?oefficient of variation (CV), index of
precision (D).
and in percentages of agreement ( O ) for counts of opaque
annuli
in red snapper
(Lutjanus campechanus) otoliths
after fi
rst and second
readings for each
sample year.
«=number of otoliths sa
mpled.
Year
1st reading
2nd reading
1999 in
=2100)
APE
0.483
0.499
CV
0.014
0.0008
D
0.010
0.0006
O
89.48%
99.43%
±1
8.62%
0.48%
±2
1.19%
0.095%
±3
0.71'.
2000 (n
=2069)
APE
0.487
0.499
CV
0.034
0.0006
D
0.024
0.0004
O
73.79f;
99.47%
±1
22.49',
0.53%
±2
1.78%
±3
1.93%
2001 in
= 866)
APE
0.459
0.498
CV
0.032
0.0005
D
0.023
0.0003
O
74.73*
99.42^
±1
22.06%
0.58%
±2
2.27%
±3
0.94%
ALFL. = 839(1 -e1-0381"1)
(F, 15= 2824.9; P<0.0001; r2=0.95);
LAFL„ = 847.8(1 - e'-° •25"")
(F1; 13=5024.4; P<0.0001; r2=0.76);
TXFL„ = 778.2(1 - e<-o.49tt)>)
(F1;19=1452.1; P<0.001; r2=0.85);
AL TW
17.05(1 -e
(-0.15inii3.03
(F1;15=457.9; P<0.0001; r2=0.89);
LA TW_._ = 12.61(1 - ec-o.32(»))3.03
(F114=122.02; P<0.0001; ;-2 = 0.18);
TX TWrr, = 8.89(1 - e'-0-21"")2 84
(F1;12= 613.01; P<0.0001; r2=0.96).
Models of mean red snapper FL at age for Alabama and
Louisiana were markedly similar with likelihood ratio
tests indicating no significant differences between red
snapper from the two states (Table 3). However, the
Texas model differed from both Alabama and Louisiana
models. The Texas model displayed significant differ-
ences from the other models in both Lm and in k. A
comparison of the models of mean TW at age indicated
no significant differences between Alabama and Loui-
siana red snapper (Table 3). Differential growth in TW
was found when comparing Alabama and Louisiana with
the Texas model; significant differences were manifested
in both WM and in k. The model failed to converge for
estimating a common value of k for both Louisiana and
Texas.
We recognized that the larger red snappers from
Louisiana might bias the data; therefore we compared
growth for fish from 2 to 10 years of age — a time pe-
riod when red snapper have demonstrated rapid linear
growth (Szedlmayer and Shipp, 1994; Patterson et al.,
2001; Wilson and Nieland, 2001). Linear regressions
of mean FL at age for all individuals 2 to 10 years
(Fig. 6A) were compared among states. We found no
significant differences among states (ANCOVA test of
homogeneity of slopes, F2;28=2.7; P=0.08; ANCOVA test
for equal intercepts, F2.28=0.52; P=0.6).
598
Fishery Bulletin 102(4)
Mean TW at age was also examined among states for
red snapper 2 to 10 years in age as above (Fig. 6B). No
significant differences were found between Alabama and
Louisiana (ANCOVA test of homogeneity of slopes, F117=
0.1; P=0.75; ANCOVA test for equal intercepts, F1;'17=
0.26; P=0.66 for intercepts). However, a significant
difference between slopes was detected when compar-
ing Alabama and Texas red snapper (ANCOVA test of
homogeneity of slopes, F1;16=19.68; P<0.0007; ANCOVA
test for equal intercepts, F1;16=2.74; P<0.12). The same
was found when comparing slopes for Louisiana and
Texas red snapper I ANCOVA test of homogeneity of
Figure 3
Marginal increment analysis of red snapper {Lutjanus campecha-
nus) otoliths for specimens from Alabama (n = 1985l, Louisiana
(n = 1864), and Texas <n = 1186>.
45 -,
40 ■
J
DAL
35 -
■ LA
£. 30 -
DTX
Frequency
o en
|
-
15 -
n
10 -
1
5 -
JJ
1
flflr^m-rm.^ . _ r».
o -
1
2 3
4 5 6 7 8 9 10 11 12 13 14 15 >15
Age (yr)
Figure 4
Age distri
butions for red snapper (Lutjanus campechanus) sam-
pled from
the 1999-2001 recreational harvests from Alabama,
Louisiana
, and Texas.
slopes, Fl 16=9.62; P<0.008) but not when comparing
intercepts' (Fh 16 = 0.64; P<0.44).
Discussion
Demographic variations in growth rates and in size-
frequency distributions may indicate the existence of
isolated management units of red snapper in the north-
ern GOM. The recreational harvests of Alabama and
Louisiana red snapper were dominated by individuals
ranging from 375 to 425 mm FL, whereas the majority
of Texas fish (69%) were 375 mm FL or less. It
was within this size range (375-400 mm FL)
that the significant differences in red snapper
among states were detected. The FL distribu-
tion of red snapper sampled in Texas also dif-
fered from those for Alabama and Louisiana;
there were very few large fish represented in
the Texas sample population, partly because
fishing tournaments (where larger individuals
are targeted) were not sampled in Texas. Signifi-
cant differences in TW frequencies among states
were also detected at approximately 1 kg (the
approximate weight of a red snapper 375-400
mm FL); 86% of Texas fish weighed 1 kg or less,
compared to only 27% of Alabama fish and 28%
of Louisiana fish in this size range.
One factor possibly contributing to the modal
size class difference was the type of fishing
vessel used to catch the fish. The majority of
Texas specimens I~95fr<) were sampled from
headboats; whereas Louisiana and Alabama
fish were obtained almost exclusively from char-
terboats. This is not to say that charterboats
were purposely excluded from the Texas sur-
vey. On the contrary, red snapper were sampled
from any and all available recreational fishing
parties at the three individual sampling loca-
tions. Differences in modal size and number of
red snapper caught per person onboard charter-
boats versus headboats may be inconsequential
considering that both trip types used similar
gear and targeted similar or the same fishing
locations. It should be noted however that in
the Texas study area, charterboats routinely
frequented a wider array of fishing spots (rigs,
hardbottom. wrecks, etc.) than did headboats,
which typically return to the same few rigs and
large structures over and over again iTolan 5),
Our von Bertalanffy growth models on
FL at age showed that red snapper from all
three states exhibit a pattern of rapid, linear
growth to approximately 10 years, after which
maximum theoretical (asymptotic) FL is soon
Tolan, J. 2003. Personal commun. Texas Parks
and Wildlife Department, Resource Protection, 6300
Ocean Dr., Corpus Christi, TX 78412.
Fischer et al.: Demographic structure of Lut/anus campechanus in the northern Gulf of Mexico
599
Table 3
Chi-square if), degrees of freedom (df ), and P-values for likelihood ratio tests for comparing FL and TW von Bertalanffy growth
models and parameters among sample locations (states). AL= Alabama; LA= Louisiana: and TX=Texas. n/a=not available.
r
df
P
r
df
p
AL-LA
FL model
2.54
1,28
0.11
TW model
2.15
1,29
0.14
FL model
5.14
1,34
0.023
TW model
38.8
1,27
4.7x10"
AL-TX
LA-TX
k
FL model
13.67
1,34
0.0002
21.53
1,34
3.48xl0"6
5.8
1,32
0.015
k
TW model
21.3
1,27
3.9x10"
37.8
1,27
7.97xl0-10
16.77
1.26
4.2xl0"5
10.16
1,32
0.001
15.1
1,26
0.001
k
9.8
1,32
0.002
n/a
n/a
n/a
reached and growth in length becomes negligi-
ble. This pattern of rapid growth was similar to
that reported in previous studies (Szedlmayer
and Shipp, 1994; Manooch and Potts, 1997;
Patterson, 1999; Wilson and Nieland, 2001).
However, our models predicted smaller L r and
higher values of It. Because of the minimum
size limits on the recreational fishery, very few
fish under age 2 years (>300 mm FL) were in-
cluded in our sample populations. We forced our
models through t0 = 0 to more accurately pre-
dict juvenile growth, which in turn increased
our estimates of k. In addition, we had a much
larger sample population that included more
older, larger fish than most of the previously
cited studies. These larger fish pulled the curve
down, driving the lesser estimations of LM. The
lack of significant differences in growth param-
eters between the Alabama and Louisiana mod-
els supports the findings of previous research,
which indicates that Alabama and Louisiana
red snapper grow at similar rates and reach
comparable sizes (Patterson et al., 2001). How-
ever, values of LM for Texas red snapper were
significantly smaller than parameters predicted
for Alabama and Louisiana red snapper. In-
terestingly, Texas had a value of k that was
significantly larger then that for Alabama and
Louisiana and this would indicate that Texas
fish obtain a smaller maximum theoretical FL
but reach it at a faster rate then fish from Ala-
bama and Louisiana.
Von Bertalanffy growth models of mean
weight at age produced similar results, in-
dicating that Texas red snapper obtain sig-
nificantly smaller maximum theoretical TW
than fish from Alabama and Louisiana. Fish
sampled from tournaments were excluded from
all growth models to more accurately reflect
30 35 40 45
B
15 ■
12 -
0 5 10 15 20 25 30 35 40 45
Age (yr)
Figure 5
Observed (A) mean fork length (mml at age and (B) mean total
weight (kg) at age for red snapper iLutjanus campechanus) from
Alabama, Louisiana, and Texas. Plotted lines are weighted von
Bertalanffy growth functions fitted to the data.
600
Fishery Bulletin 102(4)
growth of a random population. Tournament anglers
target large fish, possibly the fastest growing individu-
als at a given age, and their catches may bias growth
estimates (Ottera, 1992; Vaughan and Burton, 1993;
Goodyear, 1995). Without these tournament fish, how-
ever, the Alabama red snapper TW model did not reach
an asymptote. Therefore the growth parameters for
that model were poorly estimated. Notwithstanding,
Alabama and Louisiana models did not differ signifi-
cantly. Estimates of Wm and k predicted for Louisiana
red snapper were slightly larger than previously re-
ported for fish from the Louisiana commercial and
recreational catches (Render, 1995). Although the Texas
model predicted a value of Wc. that was significantly
less than those for both Alabama and Louisiana red
snapper, Texas had a growth coefficient (k) that was
larger then that for Alabama. It appears that, as in the
length models, Texas fish reach a smaller theoretical
maximum weight but at a faster rate than Alabama
fish. Louisiana fish attained maximum weight at a
faster rate than Alabama or Texas red snapper. Our
growth models indicate that although Texas red snap-
900
800
E
E
700
600
*—
c
CD
500
400
O
u.
300
200
100
0
12
10
A
j
A
X
'. ^T^'
r \_
• AL
1
LA
XTX
— i
10
B
01 23456789 10
Age (yr)
Figure 6
Scattergram with linear regression lines for relationships
(A) between age (yr) and mean fork length (mm) and (B) age
(yr) and mean total weight (kg) for red snapper (Lutjanus
campechanus) aged 1 to 10 years from the 1999-2001 rec-
reational harvests of Alabama. Louisiana, and Texas. Krror
bars represent standard deviations from the mean.
per grow in mass at a faster rate than Alabama fish.
Texas red snapper are consistently smaller at age and
reach smaller maximum sizes than those from Alabama
and Louisiana and that there is a veritable difference
in size at age and growth rates among regions. Similar
demographic variations in growth rates among popula-
tions have been previously noted for other marine fish
species of the South Atlantic and GOM, such as gray
snapper (Johnson et al., 1994; Burton 2001), and king
mackerel (DeVries et al, 1990; DeVries and Grimes,
1997).
Linear regressions of mean FL and mean TW at age
for red snapper aged one to 10 years indicated that only
TW was significantly different among sample regions.
Texas red snapper were shown to differ significantly
from both Alabama and Louisiana red snapper in re-
gressions of mean weight at age. Although comparisons
of FL at age for all regions were not significantly differ-
ent, Texas fish were significantly smaller in mass (TW)
at age than fish from Alabama and Louisiana. This
difference was observed in all age classes.
Our research efforts indicate that there is mounting
evidence for discrete differences in size at age
and in overall growth rates between red snapper
sampled from the north central GOM (Louisiana
and Alabama) and the southwest GOM (Texas).
Texas red snapper are clearly reaching smaller
maximum sizes and are consistently smaller (TWi
at age than those collected from Louisiana and
Alabama waters. Although the reasons behind
these differences remain uncertain, logic indicates
that factors such food availability, habitat prefer-
ence, and actual population size may cause these
differences between regions.
The more productive, nutrient-rich waters of
the Mississippi River and north-central GOM off
Louisiana and Alabama may be more conducive
to faster growth than the less fertile waters off
Texas. Approximately 70-80% of GOM fishery
landings come from the waters surrounding the
Mississippi River delta (Grimes, 2001). The west-
ern GOM (including the sampling area of Port
Aransas, TX) is devoid of a contributing river sys-
tem anything remotely similar to the Mississippi
River. Draining 43% of the continental United
States, the Mississippi River is the largest river
system in North America and provides an enor-
mous amount of nutrient-laden fresh water to the
shallow continental shelf of the northern GOM.
Although the mechanics by which the Mississippi
River enhances fishery production remain uncer-
tain. Grimes (2001) postulated that the discharge
from the Mississippi primarily influences recruit-
ment m the plume field. Increased growth rates
associated with the Mississippi River plume com-
pared with other regions of the GOM have been
noted for a number of species, such as gulf menha-
den (Warlen, 1988), king mackerel (DeVries et al.,
1990), striped anchovy (Day, 1993), and yellowfin
tuna (Lang et al., 1994).
Fischer et al.: Demographic structure of Lut/anus campechanus in the northern Gulf of Mexico
601
In addition to increased food availability off of the
north-central GOM, the amount and condition of pre-
ferred habitat may have some effect on the observed
differences in growth rates for Texas and those for
Louisiana and Alabama. Approximately 95"% of all
Louisiana fishes sampled in this study were harvested
from waters surrounding nearshore (<50 km) oil and
gas platforms. Similarly, about 95% of all Alabama
fishes sampled were caught over artificial reef sites.
The fact that there was no detectable difference in size
at age and overall growth rates between Louisiana and
Alabama red snapper therefore is not surprising, given
the similarity in the habitats sampled and the proxim-
ity of both locations to the Mississippi River discharge
plume. Texas was the only area in which samples were
routinely obtained from natural hard bottoms (40%),
as well as from oil and gas platforms and artificial
reefs (60%). Given that more than half of the Texas
specimens were captured in the waters immediately
surrounding artificial structures (i.e., oil and gas plat-
forms), we can assume that habitat type is not be the
sole source for the observed differences in growth rates
among regions.
Despite the current acceptance of a unit stock hypoth-
esis for GOM red snapper, the species is not, and to our
knowledge never has been, uniformly distributed across
the northern GOM. The fishery for red snapper began
in northwest Florida approximately 20 years before the
Civil War (Collins, 1887) and during that time period
was centered between Mobile, AL, and Fort Walton, FL
(Camber, 1955). One hundred years of landings data
indicate that the fishery, and possibly the population,
has undergone a major shift from the natural outcrop-
pings of the West Florida Shelf to oil and gas platforms
of the north-central portion of the GOM (Shirripa and
Legault1). Fishery-dependent data indicate that cur-
rently there is a center of abundance of red snapper off
southwest Louisiana and a second, smaller center off
Alabama (Patterson et al., 2001; Goodyear4; Shirripa
and Legault1). Patterson et al. (2001) stated that Loui-
siana and Alabama accounted for 32.6% and 11.4%,
respectively, of the combined recreational and commer-
cial GOM landings from 1981 to 1998. This is especially
surprising for Alabama, considering that its coastline
accounts for only 3% of the GOM coastline from the
Texas-Mexico border to the southern tip if Florida (Pat-
terson et al., 2001).
Red snapper have never been reported to be plentiful
in Texas waters, despite the availability of suitable hab-
itat in the form of natural hard bottom and the cur-
rent high concentration of oil and gas platforms. In a
historical report on red snapper fishing in the GOM,
Camber ( 1995 ) reported that although a few red snap-
per were taken from the "Galveston Lumps" or the
"Western" fishing grounds off Texas, the fishery never
fully developed in this region during the latter part of
the nineteenth century. Commercial landings for red
snapper from the GOM indicated that Texas accounted
for approximately only 18% of the total catch during
the time period 1981-95 (Goodyear6). In a recent fish-
ery-dependent survey of recreational headboat discards
and landings in Texas coastal waters, red snapper less
than the minimum legal size (15 inches) made up 64%
of the catch (Dorf. 2000). In the latter study, Galveston,
Port Aransas, and Port Isabel were surveyed to canvas
a large portion of the Texas coast. Discard-to-landing
ratios were as high as 211:1 in the waters off Galveston
and were possibly indicative of the paucity of legal-size
red snapper in Texas waters. Of the three sampling
locations. Port Aransas had the lowest discard-to-land-
ing ratio (5.2:1) and the largest mean fish length and
weight (387 mm, 0.9 kg) — length and weight data that
are consistent with a 3-yr-old fish from our Texas (Port
Aransas) specimens. The majority of Texas fish (63%)
were aged at 3 years or less. Age distribution, along
with FL and TW distributions, may indicate that red
snapper are being harvested from Texas waters just
as they reach legal size. Given the vast differences
in historical landings data between the northern and
southwest GOM, the highly disproportionate discard-
to-landing ratio reported for headboats in Texas wa-
ters (Dorf, 2000), and the large number of young fish
sampled in Texas, it is not inconceivable to speculate
that there are fewer red snapper available for harvest
in Texas waters.
Demographic variation in growth rates may indicate
the existence of separate management units of red snap-
per in the GOM. Our data indicate that the red snapper
inhabiting the waters off Texas are reaching smaller
maximum sizes at a faster rate, but are consistently
smaller (TW) at age than those collected from Louisi-
ana and Alabama waters. Whether these differences are
environmentally induced or result from genetic diver-
gence remains to be determined. The more productive,
nutrient-rich waters of the Mississippi River and north-
central GOM off Louisiana and Alabama may be more
conducive to faster growth than the less fertile waters
off Texas. Fishing pressure and its effects on population
size may also be leading to the observed differences in
growth rates. Fishery-dependent landing data and dis-
proportionate discard-to-landing ratios in Texas waters
loosely support the concept that fewer red snapper are
available for harvest in the southwest GOM. Regardless
of the cause, the existence of demonstrable demographic
differences argues for the delineation of multiple red
snapper management units in the GOM.
Acknowledgments
Funding for this research was provided by the U.S.
Department of Commerce Marine Fisheries Initiative
(MARFIN) program (grant number NA87FF0424). We
6 Goodyear, C. P. 1996. An update of red snapper harvest
in U.S. waters of the Gulf of Mexico. Report MIA-95/96-
60, 21 p. Miami Laboratory, Southeast Fisheries Center,
National Marine Fisheries Service. 75 Virginia Beach Dr.
Miami, FL., 33149-1099. [Not available from NTIS].
602
Fishery Bulletin 102(4)
thank Forrest Davis, John Gold, Jessica McCawley,
Linda Richardson, Jim Tolan, Melissa Woods, Candace
Aiken, and many others for help with sampling red snap-
per. We also thank Josh Maier and Brett Blackman for
otolith sectioning. We thank Steve Tomeny and his boat
captains and crew (Port Fourchon, LA), as well as all
boat captains and crews in Dauphin Island, Alabama,
and Port Aransas, Texas, for graciously allowing us to
sample fish from their charter fishing vessels. We also
thank Yvonne Allen for providing the map in Figure 1.
Finally we would like to thank Dave Nieland for time
spent fielding questions concerning statistical analysis
and for a constructive review of this manuscript.
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604
Abstract— The population struc-
ture of walleye pollock \Theragra
chalcogramma) in the northeastern
Pacific Ocean remains unknown.
We examined elemental signatures
in the otoliths of larval and juvenile
pollock from locations in the Bering
Sea and Gulf of Alaska to determine
if there were significant geographic
variations in otolith composition
that may be used as natural tags of
population affinities. Otoliths were
assayed by using both electron probe
microanalysis (EPMA) and laser
ablation inductively coupled plasma
mass spectrometry iICP-MS). Ele-
ments measured at the nucleus of
otoliths by EPMA and laser abla-
tion ICP-MS differed significantly
among locations. However, geographic
groupings identified by a multivariate
statistical approach from EPMA and
ICP-MS were dissimilar, indicating
that the elements assayed by each
technique were controlled by sepa-
rate depositional processes within the
endolymph. Elemental profiles across
the pollock otoliths were generally-
consistent at distances up to 100 fim
from the nucleus. At distances beyond
100 /im, profiles varied significantly
but were remarkably consistent
among individuals collected at each
location. These data may indicate
that larvae from various spawning
locations are encountering water
masses with differing physicochemical
properties through their larval lives,
and at approximately the same time.
Although our results are promising,
we require a better understanding of
the mechanisms controlling otolith
chemistry before it will be possible
to reconstruct dispersal pathways of
larval pollock based on probe-based
analyses of otolith geochemistry.
Elemental signatures in otoliths of
pollock may allow for the delineation
of fine-scale population structure in
pollock that has yet to be consistently-
revealed by using population genetic
approaches.
Elemental signatures in otoliths of
larval walleye pollock (Theragra chalcogramma)
from the northeast Pacific Ocean*
Jennifer L. FitzGerald
Simon R. Thorrold
Biology Department, MS 35
Woods Hole Oceanographic Institution
Woods Hole, Massachusetts 02543
E-mail address (for J L. FitzGerald): ifitzgerald awhoi edu
Kevin M. Bailey
Annette L. Brown
NOAA Alaska Fisheries Science Center
7600 Sand Point Way NE
Seattle, Washington 91185
Kenneth P. Severin
Department of Geology and Geophysics
University of Alaska Fairbanks
P.O. Box 755780
Fairbanks, Alaska 99775-5780
Manuscript submitted 4 August 2003
to the Sceintific Editor's < X'fice.
Manuscript approved for publication
28 May 2004 by the Scientific Editor.
Fish. Bull. 102:604-616(20nl
The "stock" concept is a central tenet
of modern fisheries science because it
represents the fundamental manage-
ment unit of marine fisheries (Begg
and Waldman, 1999). This emphasis,
in turn, places a premium on accu-
rate identification of groups of fish
whose population statistics are largely
independent of other groups. However,
stock identification has often proved
problematic in marine fishes. For
instance, the stock structure of wall-
eye pollock {Theragra chalcogramma*
across the North Pacific Ocean has
been a topic of investigation for many
years. Early studies were based on
phenotypic characteristics of pol-
lock, such as meristics and morpho-
metries (Serobaba. 1977; Hinckley,
1987; Temnykh, 1994). Other studies
have focused on genotypic markers,
such as DNA and allozyme analyses
(Grant and Utter, 1980; Mulligan et
al., 1992; Shields and Gust, 1995).
These approaches resulted in only the
broadest characterization of pollock
stock structure but have been able
to distinguish populations from the
eastern and western Pacific (Bailey et
al., 1999). Quasi-isolated subpopula-
tions may be at least demographicallv
isolated on smaller spatial scales. For
instance, within the Gulf of Alaska,
spawning pollock aggregate at specific
locations in Shelikof Strait, Prince
William Sound, and in the Shumagin
Islands region (Bailey et al., 1999).
However, the extent of larval dis-
persal from the spawning sites and
the degree of spawning site fidelity
of adult pollock to these locations
remains unknown.
The difficulties associated with de-
termining stock structure in fishes
are essentially the same ones that
currently limit our ability to deter-
mine population connectivity in ma-
rine systems (Thorrold et al.. 2002).
Tag-recapture studies using tags have
limited applicability in the case of
pollock. Adults are located deep in
the water column and are sensitive
to barotrauma during the process of
being caught, brought to the surface,
and tagged. Traditional population
genetic approaches may be similarly
Contribution 11219 from the Woods Hole
Oceanographic Institution. Woods Hole,
MA 02543.
Fitzgerald et al.: Elemental signatures in otoliths of larval Theragra chakogramma
605
ineffective because of the low level of exchange required
to maintain genetic homogeneity, at least over ecological
time scales, and the low level of genetic drift associated
with large populations (Waples, 1998; Hellberg et al.,
2002). However, preliminary studies have indicated that
otolith geochemistry may prove to be a useful natural
tag of population structure in walleye pollock (Severin
et al., 1995). Otoliths are accretionary crystalline struc-
tures located within the inner ear of teleost fish. They
are formed through concentric additions of alternating
protein and aragonite layers around a central nucleus.
The use of otoliths as natural geochemical tags is con-
tingent on the metabolically inert nature of the otolith
and the fact that once deposited, otolith material is
neither resorbed nor metabolically reworked (Campa-
na and Neilson, 1985; Campana, 1999). The chemical
composition of otoliths also reflects to some degree the
physicochemical characteristics of the ambient water
(Bath et al., 2000). If the water where pollock reside
has distinct oceanographic characteristics, then many of
the elements incorporated into the otoliths should differ
among locations. Migrations between water masses at
some age will, therefore, be recorded in the chemical
composition of the otolith at the appropriate daily incre-
ment. Natural geochemical signatures in otoliths may
therefore be useful markers of environmental history
throughout the life of the individual and in turn, fish
stock composition (e.g., Campana et al., 1995).
The use of geochemical signatures in otoliths as natu-
ral tags requires accurate and precise assays of otolith
composition. Electron probe micro-analysis (EPMA) has
been commonly used for probe-based analyses of otolith
chemistry (Gunn et al., 1992). However, detection lim-
its of approximately 100 ,ug/g limit the technique to a
relatively small number of minor elements in otoliths,
including Na, CI, K, and Sr (Campana et al., 1997).
Most of the elements measured by EPMA are probably
controlled by physiological rather than environmen-
tal factors, which may limit their usefulness in stock
identification studies (Campana, 1999). Nonetheless, a
number of researchers using EPMA have reported geo-
graphic differences in otolith chemistry (e.g., Thresher
et al., 1994). More recently, attention has focused on
inductively coupled plasma mass spectrometry (ICP-MS)
to assay elements that are typically below the detection
limits of EPMA. Laser ablation ICP-MS uses focused
Nd:YAG or excimer lasers to ablate specific locations on
the otolith. The vaporized material is then swept up by
a carrier gas into a plasma torch and analyzed by mass
spectrometry. Limits of detection of the technique are
typically on the order of 0.1-l^g/g, allowing for quan-
tification of several elements that cannot be assayed by
using EPMA including Mg, Mn, Ba, and Pb (Thorrold
et al., 1997; Thorrold and Shuttleworth, 2000). These
observations led Campana et al. (1997) to conclude that
EPMA and laser ablation ICP-MS were complementary
and that there is little overlap in the elements that are
accurately measured by the two techniques. Yet few
studies of otolith geochemistry have attempted to use
both approaches on the same samples.
The objectives of this study are to determine if larval
walleye pollock from different geographic localities can
be distinguished based on elemental signatures in their
otoliths. By analyzing sagittal otoliths with both EPMA
and laser ablation ICP-MS, we hoped to identify greater
differences among locations than would have been pos-
sible by using either technique in isolation. If success-
ful, the study may provide a powerful tool for determin-
ing stock structure and tracing migration pathways of
walleye pollock in the north Pacific. These data could
then be used by managers of one of the world's largest
single species fisheries to direct the sustainable harvest
of this considerable natural resource.
Materials and methods
All fish used in the study were collected in the spring and
summer of 1999 from Alaska Fisheries Science Center
research cruises in the Bering Sea and Gulf of Alaska
(Fig. 1, Table 1). Fish of birth year 1999 were collected
within three months of spawning time to minimize the
likelihood of larval transport from other regions. In the
case of the Yakutat samples, fresh juvenile pollock were
removed from Pacific cod guts. Samples were collected
only when the pollock were readily identifiable and
heads were intact. Otoliths showed no visible sign of
degradation from digestive processes. Juvenile pollock
were frozen whole and transported to the laboratory for
otolith removal.
Otoliths were removed from the fish and mounted on
petrographic slides in LR White resin (acrylic, hard-
grade). Larval otoliths were ground on one side to
expose the nucleus by using 500-grit paper and were
polished with 0.25-um grit diamond paste. Juvenile
otoliths were ground and polished in the sagittal plane
on both sides to maximize clarity of the nucleus during
microanalysis.
Electron probe microanalysis
After having been polished, the otoliths were cleaned
with Formula 409® and coated with a 30-nm layer
of carbon. They were subsequently analyzed with a
Cameca SX-50 electron microprobe equipped with four
wavelength dispersive spectrometers. A 15keV, 10 nA,
4-/jm diameter beam was used for all analyses. Counting
times, standards, detection limits, and analytical errors
are summarized in Table 2. Although Mg was analyzed
in all otoliths, in most cases it was below detection
limits and was therefore not used in the statistical
analysis.
Laser ablation ICP-MS
After having been ground and polished, otolith sections
were decontaminated before elemental analysis by using
laser ablation ICP-MS. Sections were rinsed in ultra-
pure water, scrubbed with a nylon brush in a solution
of ultrapure H,,0, triple rinsed with ultrapure 1%HN03,
606
Fishery Bulletin 102(4)
•;"-
North
Bering
Sea
1$'
■"\T7
60N
Bristol 15V"^C'
bay • j *?p*
Prince
William
Sound
-55N
SE Bering
Sea
*>•..
Shelikof
Strait
^ A
Yakutat
•**>&*
160W
I
Figure 1
Locations of sampling sites for larval and juvenile walleye pollock (Theragra chalcogramma
the Gulf of Alaska and Bering Sea.
) in
sonified for 5 minutes in ultrapure H90, and finally triple
rinsed again with Milli-Q water. The section was dried
under a positive flow hood for 24 hours and stored in a
polyethylene bag.
Elemental analyses were conducted with a Finnigan
MAT Element2 magnetic sector field ICP-MS and Mer-
chantek EO LUV266X laser ablation system (Thorrold
and Shuttleworth, 2000). Instrument set-up was simi-
lar to that outlined by Giinther and Heinrich (1999).
An Ar gas stream was used to carry ablated material
from the laser cell to the ICP-MS. The carrier gas was
then mixed with the Ar sample gas and a wet aerosol
(1% HN03) in the concentric region of the quartz dual
inlet spray chamber. The wet aerosol was supplied by
a self-aspirating PFA micro-flow (20 /./L/min) nebulizer
attached to a CETAC ASX100 autosampler. Diameter
of the 266-nm laser beam was nominally 5 j.im, repeti-
tion rate was 5 Hz, and the scanning rate was set at
5 /im/sec.
A typical run for an individual otolith consisted of a
blank sample (l%HNO:! only), a standard sample, five
laser samples, and then another blank and standard.
The number of laser samples in a run ranged from 5
to 15, depending upon the size of the otolith. All laser
runs began with a 70 fim x 70 /.im raster, centered on
the otolith nucleus. The laser software was then used
to trace out concentric lines, 720 /jm in length and ap-
proximately 40 /jm apart, which followed the contour
of individual growth increments from the raster to the
otolith edge. This approach produced reasonably high
spatial resolution (30-50 u,m) for life history scans
across otoliths while allowing sufficient acquisition time
to maintain measurement precision.
We examined Mn/Ca, Sr/Ca, and Ba/Ca ratios in the
pollock otoliths by monitoring 48Ca, 55Mn, 86Sr, and
138Ba. Quantification followed the approach outlined
by Rosenthal et al. (1999) for precise element/Ca ra-
tios using sector field ICP-MS (Thorrold et al., 2001).
Quality control was maintained by assaying a dissolved
aragonite standard (Yoshinaga et al., 2000) every five
samples. The standard was introduced at the appropri-
ate time by moving the autosampler probe from the
solution containing the 1% HNO;j to the standard solu-
tion, while maintaining the carrier gas flow through
the ablation cell. Elemental mass bias was calculated
by reference to known values of the standard, and a
correction factor was then interpolated and applied to
the laser samples bracketed between adjacent standard
measurements. Average u; = 40) within-run precisions
(RSD) of the standard measurements were all less than
1% (Mn/Ca: 0.16%, Sr/Ca: 0.16%, and Ba/Ca: 0.33%).
Long-term (5-month) estimates of the standard mea-
surements (n=40), again uncorrected for changes in
mass bias over time, were less precise (Mn/Ca: 5.6%,
Sr/Ca: 3.7%, and Ba/Ca: 5.6%). However, laser samples
were corrected for changes in mass bias by using the
laboratory standard. Precision of the technique was ap-
proximately 1% for all the ratios that we measured.
Statistical analyses
All elemental data were initially examined for nor-
mality and homogeneity of variance by using residual
analysis (Winer, 1971) and were found to conform to
the assumptions of ANOVA without the need for data
transformation. We therefore assumed that require-
Fitzgerald et al.: Elemental signatures in otoliths of larval Theragra cha/cogramma
607
Table 1
Location, collection
date, standard length range
(mm), and sample
sizes
(n) of larval
and juvenile walleye pollock iTheragra
chalcogramma)
capt
ured from the southeast Bering Sea (SE Bering)
North Bering Sea
I N Ber
ing), Bristol Bay. Shelikof Strait.
Prince William
Sound (PWSi, and Yakutat, and analyzed by laser ablation ICP-MS (ICP-MS) and electron probe microanalysis
(EPMA).
Area
Date
SL range (mm)
n (total)
in ICP-MS ) n (EPMA)
SE Bering
23 May-27 July 1999
5.3-42.2
117
8 30
N Bering
18-23 July 1999
15.6-30.7
45
9 25
Bristol Bay
22-24 July 1999
85.1-135.7
75
11 28
Shelikof
27-28 May 1999
3.6-7.9
46
25
PWS
7 July-19 August 1999
35.2-66.0
11
4 6
Yakutat
15 July,1999
—
50
6 24
Table 2
Counting times for each element itime
seconds], standards, limits of detection [LOD.
7rweight, 99<7f
confidence limits] and ana-
lytical errors
1 Error. '/c weight.
1 stand
ird deviation]) for electron probe
microanalysis (EPMA). Detection limits
and
analytical
errors were calculated by following the procedures of Scott et al. (19951.
N/A =
not applicable.
Element
Time
Standard
LOD
Error
Na
60
Halite ( CM Taylor)
0.029
0.023
Mg
60
OsumilitelUSNM 143967)
0.019
0.022
P
60
Apatite (Wilberforce)
0.036
0.027
S
60
Gypsum (CM Taylor)
0.023
0.017
CI
46
Halite 1 CM Taylor)
0.027
0.015
K
46
OsumilitelUSNM 143967)
0.019
0.012
Ca
20
CalciteiNMNH 136321)
N/A
0.245
Sr
120
Strontianite (Smithsonian R-10065)
0.036
0.019
merits for the MANOVA were also met by the data.
Among-location differences in the elemental composition
of larval pollock in specific regions of the otoliths were
compared by using one-factor multivariate analysis of
variance (MANOVA) and one-factor analysis of variance
(ANOVA). We treated location as a fixed factor in both
MANOVA and ANOVA tests. Because of difficulties col-
lecting pollock larvae, we were unable to achieve equal
replication of sites within locations. We therefore pooled
samples from collections within a location by randomly
selecting fish from each location for subsequent analysis.
However, the lack of replication at the within-location
level necessarily restricted our ability to draw general
conclusions concerning spatial variability in otolith
composition beyond the samples analyzed in the pres-
ent study. All a posteriori comparisons among locations
were performed by using Tukey's honestly significant
difference (HSD) test (experimentwise error rate = 0.05).
Multivariate differences in elemental signatures from
the MANOVA were visualized by using canonical dis-
criminant analyses (CDA). All analyses were conducting
by using the SAS statistical program (SAS, version 6,
1990, SAS Inst. Inc., Cary, NO.
Comparisons of elemental profiles across otoliths were
made with repeated measures ANOVA. We tested the
following null hypotheses: 1) there was no variation in
trace element profiles across individual otoliths (i.e.,
from the nucleus to the edge), 2) there were no differ-
ences in mean element concentrations among locations,
determined by averaging data across individual otolith
profiles, and 3) there were no differences in the pat-
tern of element profiles across otoliths among locations.
Otolith profiles with missing values were removed, and
therefore we were able to use MANOVA for the repeated
measures analysis. The multivariate approach to re-
peated measures is generally more conservative than
univariate repeated measures analysis. However, the
multivariate test does not assume sphericity of orthogo-
nal components, requiring only that the data conform to
multivariate normality with a common covariance ma-
trix for individual larvae at each location (Littell et al.,
1991). The approach still requires that adjacent points
on the trajectories be equidistant. Therefore samples
from EPMA were assigned to a distance category at
intervals of 15 ftm (0 //m, 15 fim, 30 /.im , 45 /jm, 60 f/m,
75 /im, and 90 j/m) across the otolith, to a distance of
90 ^m from the nucleus. Samples were averaged when
more than one measurement was available within a
distance category. Laser ablation ICP-MS samples were
assigned to a distance category at intervals of approxi-
608
Fishery Bulletin 102(4)
Table 3
EPMA results of one-factoi
ANOVA l degrees
of freedom |df]; sums of squares [SS]
mean square
[MS]) at two positions (0-
20 ,um and 20-45 pm from the nuc
leus) in otoliths of larval
walleye pollock (Theragra c
hal
■ogramma i
collected from six locations:
three locations in the Berin
I Sea
southeast B
;ring Sea [SB]; North Bering Sea |NB]
Br
stol Bay [BB] I and three in the Gulf of
Alaska (Prince William Sound [PW]; Shelikof Strait [SH]-
and Yakutat |YK1
***= sign
ficant at a
= 0.05; ns = nonsignificant.
A posteriori
multiple comparisons
among locat
ons were conducted by using Tukey's hone
3tly significant difference ( HSD I. Loca-
tions are ordered I left to right I from lowest to highest concentrations, and lines link locations that are not significantly different
(experimentwise error rate =
= 0.05)
Element
Source
df
SS
. MS
F
P<F
Tukey's HSD
0-20 nm
Na
Location
Error
5
113
24.7
34.1
4.9
3.0x10-1
16.37
PW BB YK NB SB SH
P
Location
Error
5
113
18.3
27.7
3.7
2.5xl0-i
14.93
BB SH NBSB PWYK
S
Location
Error
5
113
2.0
8.8
3.9x10-1
7.8xl0-2
5.04
**v
PW BB NB YK SH SB
CI
Location
5
10.2
2.0
3.93
***
PW NB BB YK SB SH
Error
113
58.6
5.2xl0-i
K
Location
Error
5
113
2.4
13.51
4.8x10 i
1.2x10-1
4.01
*=*-:-
SH NB SB PW BB YK
Sr
Location
Error
5
113
7.1
24.1
1.4
2.1x10-1
6.66
***
YK NB BB SH PWSB
20-45 pm
Na
Location
Error
4
93
15.9
13.9
4.0
1.5xl0-i
26.66
*##
BB PWYK SB NB
P
Location
Error
4
93
14.9
20.3
3.7
2.2x10-1
17.07
***
BB NB SB PW YK
S
Location
Error
4
93
1.1
5.7
2.8xl0-i
6.1xl0-2
4.62
BB PW SB NB YK
CI
Location
Error
4
93
8.4x10-
12.1
1 2.1x10'
1.3x10-1
1.61
ns
PW SB NB BB YK
K
Location
Error
4
93
1.9
7.7
4.7x10-'
8.3x10-2
5.65
***
NB PW BB SB YK
Sr
Location
Error
4
93
9.0x10-
5.6
1 2.2x10-1
6.0x10-2
3.75
***
NB YK BB PW SB
mately 40 |im (nucleus, 40-80 Jim, 80-120 ^m, 120-160
urn, and 160-200 fim) across the otolith, to a distance
of 200 ^m from the nucleus.
Results
Electron probe microanalysis
A total of six elements (Na, P, S, CI, K, and Sr) were
quantified in the otoliths of pollock larvae by using
EPMA. Average concentrations of the elements ranged
from approximately 4 mg/g (otolith weight) for Na to
less than 1 mg/g for CI, S, and K. We found significant
differences in the elemental composition both among
sampling locations and across positions on the oto-
liths. Multivariate analyses of elemental signatures
revealed significant differences among locations from
samples 0-20 urn from the nucleus (M ANOVA; Pillai's
trace=1.18; F30 ,560=5.74; P<0.0001), and 20-45 fim from
the nucleus (MANOVA; Pillai's trace = 1.47; F.,
, = S,Sli;
P<0.0001l.
Analysis of variance and Tukey's HSD a posteriori
multiple comparison tests identified the individual ele-
ments contributing to differences in the multivariate
signatures among locations. All six elements showed
significant differences among locations at 0-20 /tm from
the otolith nucleus (Table 3). Multiple comparisons for
each of the elements indicated relatively subtle differ-
ences among locations. Phosphorus concentrations were,
however, significantly higher in samples from Yakutat
than any of the other locations. Results of the ANOVA
from samples at distances 20-45 j<m from the nucleus
were generally comparable with samples closer to the
nucleus (Table 3). Although only CI showed no signifi-
cant variation among locations (Table 3), multiple com-
parisons of mean values for each element revealed little
geographic patterns among locations. Note that Shelikof
Strait samples were removed from this analysis because
of a small sample size in this distance category.
Fitzgerald et al.: Elemental signatures in otoliths of larval Theragra chakogramma
609
o
.A
ft
a
ft
o
o
ft
ft
ft + o
o
ft
\*t%K*
o
4-2024
D ft ft o
ft M°
ft
ft
* o
< * a
° *
ft #A*° ^o
ft o°
> *>■* *° *o * *
_•' " O . " A 4 .»-*
II ' t o ° *4 » •
•4-20246
Canonical variate 1
Figure 2
Plot of first two canonical variates con-
trasting multivariate elemental sig-
natures in otoliths of walleye pollock
(Theragra chalcogramma) determined
by using electron probe microanaly-
sis, at 0-20 (im from the nucleus (A)
and 20-40 Jim from the nucleus (B).
Larvae were collected from the North
Bering Sea (▲), southeast Bering Sea
(O), Bristol Bay IB), Shelikof Strait
!♦), Prince Wiiliam Sound lO>. and
Yakutat (ft).
■ »\
J8 o -
° . °
0OA
* * i
*tAcf
H
- ■ A. °
. ^ A V
-3-113
Canonical variate 1
Figure 3
Plot of first two canonical variates
contrasting multivariate elemental
signatures in otoliths of walleye pol-
lock (Theragra chalcogramma) deter-
mined by electron probe microanalysis
at 0-20 /im from the nucleus iAi and
20-40 jim from the nucleus IB). Larvae
were collected from the North Bering
Sea (A), southeast Bering Sea (O). and
Bristol Bay ■
We used CDA to visualize multivariate differences
among locations in reduced dimensional space. Three
groups were readily discernible in a plot of the first two
canonical variates (Fig. 2). Samples from the North Ber-
ing Sea, the southeast Bering Sea, and Shelikof Strait
formed one group separated from Yakutat, Bristol Bay,
and Prince William Sound samples along the first ca-
nonical variate. The second canonical variate separated
Yakutat samples from Bristol Bay and Prince William
Sound individuals. Elemental signatures at 20-45 jum
from the otolith nucleus were distributed similarly in
canonical space to samples from the otolith nucleus
(Fig. 2). Three groupings were apparent in the canoni-
cal plot, and Bering Sea larvae were separated from
Bristol Bay and Prince William samples on canonical
variate one, and Yakutat samples were separated from
all other locations on canonical variate two. We then
conducted a similar analysis with only samples from
the southeast and North Bering Sea and Bristol Bay.
Elemental signatures of larvae from the Bering Sea
separated from Bristol Bay on canonical variate one.
The southeast Bering Sea samples separated from the
North Bering Sea along canonical variate two, although
not as clearly as with the elemental signatures from the
Bering Sea and Bristol Bay (Fig. 3).
Elemental profiles across otoliths varied significantly,
as determined by repeated measures ANOVA, among
the five locations for Na, P, S, and Sr (Table 4). Both
S and Sr concentrations declined from high values at
the nucleus to significantly lower values towards the
edge of the otolith (Fig. 4). Repeated measures ANOVA
also provided a test of the differences among locations
when data were averaged over the otolith profiles. Sig-
nificant differences among locations were detected for
610
Fishery Bulletin 102(4)
a.
5.5
5
45
4
3.5
3
25
2
1.5
1
05
0
1.5
I 5 $
I I J
E.
u
i i
llfl
f i
E_
to
2.5
E 15
0 15 30 45 60 75 90
0 15 30 45 60 75 90
Distance from nucleus (mm)
Figure 4
Profiles of elemental concentrations, determined by electron probe
microanalysis, from the nucleus out to a distance of approximately
90 Jim in the otoliths of larval walleye pollock iTheragra chal-
cogramma) collected from the North Bering Sea (A), southeast
Bering Sea (O), Bristol Bay (■), Prince William Sound (O), and
Yakutat ("I. Individual points are mean ( + SE) values grouped
at 15-f/m intervals.
five elements (Sr, K, S, P, and Na). Finally, the interac-
tion term (positionxlocation) in the repeated measures
ANOVA tested the hypothesis that the shape of the
elemental profiles differed among locations. There was
a significant interaction between profile and location
for K.
Laser ablation ICP-MS
We quantified Mn/Ca, Sr/Ca, and Ba/Ca ratios in the
otoliths of larval walleye pollock using laser ablation
ICP-MS. Both Mn and Ba were found at trace levels in
otoliths, with average values of approximately 3 jimo}/
mol and 6 umol/mol, respectively. Strontium was present
in the otoliths at an average concentration of approxi-
mately 2.2 mmol/mol. A MANOVA detected significant
differences among locations from a raster centered on
the nucleus (MANOVA; Pillai's trace = 0.85; Flz99=3.26;
P<0.0005), and from the average values of lines 40-80
pm from the nucleus (MANOVA; Pillai's trace = 0.99;
F1299=4.1;P<0.0001).
Univariate ANOVA and a posteriori multiple compari-
sons by using Tukey's HSD revealed that Mn/Ca, Sr/Ca,
5 -
B
5 -
0
o
0 -
-"*dy ■
■
■ ■
5 -
5 -
■
-4-2024
deamahcei eenhe(Jg
Figure 5
Plot of the first two canonical
variates contrasting multivari-
ate elemental signatures in oto-
liths of walleye pollock iTheragra
chalcogramma) determined with
laser ablation ICP-MS, at 0-40 fan
from the nucleus (A) and 40-80
fim from the nucleus (Bi. Larvae
and juveniles were collected from
the North Bering Sea (At, south-
east Bering Sea (O). Bristol Bay
■ Prince William Sound (♦), and
Yakutat ( I.
and Ba/Ca ratios varied significantly among locations
at the otolith nucleus and at positions 40-80 um from
the nucleus (Table 5). Samples from the North Bering
Sea had consistently lower Sr/Ca and Ba/Ca ratios than
those from the southeast Bering Sea at both positions.
However, we noted only subtle differences among the
Gulf of Alaska and Bristol Bay samples.
We found a total of three groupings in canonical plots
of multivariate elemental signatures from the otoliths of
larval walleye pollock (Fig. 5). Samples from the North
Bering Sea and Bristol Bay were separated along ca-
nonical variate one. A third grouping, including larvae
from the southeast Bering Sea, Prince William Sound,
and Yakutat, clustered together in the center of the
canonical plot. Samples from the nucleus and 40-80
fim outside the nucleus showed very similar geographic
patterns.
Repeated measures ANOVA detected significant dif-
ferences in both Mn/Ca and Ba/Ca profiles from the nu-
Fitzgerald et al.: Elemental signatures in otoliths of larval Theragra chalcogramma
611
Table 4
EPMA results from repeated-measures ANOVA of elements
profiles across otoliths
from walleye pollock
Theragrc
chalcogramma)
larvae collected at five locations
in the Ber
ing Sea and the Gulf of Alaska.
With
in-subject effects
(pr
ofile and
profilexlocationl
tested bv
using MANOVA (Pillai's trace I, and between sub
ects effect (location I te
sted by using ANOVA I degrees of freedom [df]:
sums of s
quares [SS]; mean squares [MS])
** = significant at a = 0.05; ns
= nonsignificant.
Element
Source
df
Pillai's trace or SS
MS
F
P<F
Na
Profile
Profile* location
6,41
24, 176
4.9x10"'
5.3X10-1
6.67
1.12
ns
Location
4
43.8
10.9
10.35
***
Error
46
48.7
1.1
P
Profile
Profile < location
6,40
24, 172
3.0x10-'
4.6x10-'
2.91
0.93
***
ns
Location
4
55.0
13.8
8.07
***
Error
45
76.8
1.7
S
Profile
Profile y location
6,41
24, 176
3.6x10"'
5.3x10"'
3.92
1.12
***
ns
Location
4
3.8
9.6x10-1
4.56
***
Error
46
9.7
2.1x10"'
CI
Profile
Profile x location
6,39
24, 168
1.8x10-'
3.7x10-1
1.41
0.72
ns
ns
Location
4
8.0
2.0
1.6
ns
Error
44
55.3
1.3
K
Profile
Profile* location
6,41
24, 176
8.3xl0-2
8.5xl0-i
0.62
1.98
ns
Location
4
4.3
1.1
2.61
*#*
Error
46
19.1
4.1x10-'
Sr
Profile
Profile x location
6,40
24, 172
4.5x10-'
7.7x10-'
5.51
1.72
ns
Location
4
6.4
1.6
3.96
***
Error
45
18.2
4.0x10-'
Table 5
Laser ablation ICP-MS results of one-factor ANOVA (degrees of freedom [df]; sums of squares [SS]; mean square [MS]) at two
positions (0-40 /im and 40-80 /im from the nucleus) in walleye pollock (Theragra chalcogramma) otoliths collected at five loca-
tions: the southeast Bering Sea [SB], North Bering Sea (NB), Bristol Bay (BB), Prince William Sound (PW), and Yakutat (YK).
**= significant at a = 0.05; ns=nonsignificant. Multiple comparisons among locations were conducted by using Tukey's honestly
significant difference (HSD). Locations were ordered (left to right I from lowest to highest ratios; lines link locations that were
not significantly different (a=0.05).
Element
Source
df
SS
MS
P<F
Tukev's HSD
0-40 fim (nucleus)
Mn/Ca
Locations
4
19.3
4.82
3.5
Error
33
45.5
1.38
Sr/Ca
Locations
4
1.07
0.27
3.43
Error
33
2.58
0.08
Ba/Ca
Locations
4
219
54.8
3.35
Error
33
540
16.4
40-80 fun
Mn/Ca
Locations
4
30.7
7.68
3.24
Error
33
78.3
2.37
Sr/Ca
Locations
4
0.99
0.25
3.70
Error
33
2.21
0.07
Ba/Ca
Locations
4
397
99.2
5.50
Error
33
595
18.0
PW
NB
SB
YK BB
NB
YK
BB
PW SB
NB
BB
PW
YK SB
NB
PW
SB
YK BB
NB
YK
PW
BB SB
NB
BB
PW
YK SB
612
Fishery Bulletin 102(4)
■Si 3
0
3.2
"5 2.8
o
■o
2.4
1.6 J
30
20
10
O
0 60 100 140 180
aartdneg Yrre nuelgur Yeea
Figure 6
Profiles of elemental ratios, deter-
mined with laser ablation ICP-MS,
from the nucleus out to a distance
of approximately 200 /.mi in the oto-
liths of larval and juvenile walleye
pollock iTheragra ehaleogramma)
collected from the North Bering
Sea (A), southeast Bering Sea
(O), Bristol Bay (■), Prince Wil-
liam Sound lOl, and Yakutat I ■■ >.
Individual points are mean (±SE)
values grouped at 40-jAm intervals.
cleus out to a distance of approximately 200 jjm in the
walleye pollock otoliths (Fig. 6, Table 6). The univariate
test of location, averaged over the individual otolith
profiles, was significant for both Sr/Ca and Ba/Ca. We
also found significant interactions between profile and
location for Mn/Ca, Sr/Ca, and Ba/Ca ratios (Table 6).
Manganese values increased from the nucleus to the
otolith edge at all locations, indicating that the signifi-
cant interaction was generated by the observation that
the profile from the North Bering Sea was considerably
flatter than profiles from Bristol Bay and southeast
Bering Sea. Strontium trajectories were more dynamic;
profiles from some locations increased from the nucleus
to the edge (Bristol Bay and Prince Williams Sound),
4.5
3.5-
' I
li'f'Mi1
* ft ft
ft ft ft ft ft ft ft
z
CO
O
CO
O
O
* ft
HHf
.
. I
ft!
*;****
tp
0 6 10 14 18 22 26 30 34 38 42 46 50 54 58
Distance from nucleus (mm x 10'2)
Figure 7
Profiles of elemental ratios, determined by using
laser ablation ICP-MS. from the nucleus out to a
distance of approximately 600 fim in the otoliths of
juvenile walleye pollock (Thuragra ehaleogramma)
collected from Bristol Bay ■ and Yakutat i I.
Individual points are mean (± SE) values grouped
at 40-;/m intervals.
profiles from other locations decreased (North Bering
Sea and Yukatat), and a single location (southeast Ber-
ing Sea) showed no obvious trend. Finally, profile varia-
tions in Ba/Ca ratios among locations were dominated
by a sharp increase in Ba/Ca ratios across the otoliths
in the southeast Bering Sea samples. Profiles were ef-
fectively horizontal for the other four locations.
Otoliths in walleye pollock collected from Bristol Bay
and Yakutat were significantly larger than those from
the other four locations. We were, therefore, able to con-
duct extended profiles in these otoliths out to a distance
of approximately 600 fim (Fig. 7). After starting at
similar values at the nucleus, Mn/Ca and Sr/Ca profiles
from the two locations quickly diverged and appeared
to vary largely independently over the remaining time
periods. The Ba/Ca profiles also appeared to be vary-
ing independently between the two locations, although
the relative magnitude of differences between the two
locations was smaller than for either Mn/Ca or Sr/Ca
profiles.
Fitzgerald et al.: Elemental signatures in otoliths of larval Theragra chalcogramma
613
Table 6
Laser ablat
on ICP-MS results from repeated-measures ANOVA of elementa
profiles
across otoliths
from walleye pollock l Ther-
agra chalcogramma l larvae collected at fi
ire locations
in the Bering Sea and the Gulf of Alaska.
Within-subject effects I
profile and
profile x location) were tested by using MANOVA iPillai's trace), and between subject
s effect
location) tested by using ANOVA
(degrees of freedom [df]; sums of squares
[SS]; mean
squares [MS]). *** = significant at a = 0.05; ns
= nonsignificant
Element
Source
df
Pillai's trace or
SS
MS
F
P<F
Mn/Ca
Profile
4,30
3.0 x 10"1
17.1
***
Position x location
16, 132
7.4 x 10"1
1.9
***
Location
4
1.99 x 102
49.7
2.49
ns
Error
33
6.61 x 10"2
20.1
Sr/Ca
Profile
4.30
2.18 x lO"1
2.09
ns
Position x location
16, 132
9.19 x 10"1
2.46
***
Location
4
1.05 x 101
2.62
6.02
***
Error
33
1.44 x 101
0.44
Ba/Ca
Profile
4,30
6.92 x 10"1
16.83
***
Position x location
16, 132
1.04
2.9
***
Location
4
5.83 x 103
1459
15.25
***
Error
33
3.16 x 103
95.6
Discussion
Quantifying dispersal pathways of larval fishes in
marine environments is a difficult proposition. Marine
fishes typically produce on the order of lCH-lO6 eggs in
a single spawning episode. These propagules are quickly
dispersed in large volumes of seawater, making recovery
of marked individuals difficult even if it were possible to
introduce an artificial tag into the larvae at the time of
spawning I Jones et al., 1999). Natural geochemical sig-
natures in otoliths offer a useful alternative to artificial
tagging approaches (Thorrold et al.. 2002). The technique
relies upon the assumption that larvae spawned at any
given location retain a unique elemental or isotopic sig-
nature in their otoliths that can be recovered some time
afterwards, and that variations in otolith geochemistry
are sufficient to distinguish among geographic locations
of interest. We found that elemental signatures in the
otoliths of larval walleye pollock differed significantly
geographically and with ontogeny. Samples at specific
points on the otoliths, at the nucleus, and shortly after
hatching, showed very similar patterns of variability,
suggesting that the technique will likely be a robust
method for identifying natal origins of walleye pollock
after suitable groundtruthing of known spawning loca-
tions (e.g., Thorrold et al., 2001; Gillanders, 2002).
Elemental signatures in the otoliths of the larval
pollock were assayed by using EPMA and laser abla-
tion ICP-MS. Campana et al. (1997) noted that the two
techniques were largely complementary in terms of ele-
ments that could be reliably assayed, and indeed only
Sr was able to be quantified by both instruments in our
study. Patterns of geographic variability presumably
reflected the elements that were used in generating the
multivariate signatures produced by each instrument.
Elemental signatures from the EPMA data clustered
into a Bering Sea group that included Shelikof Strait
but excluded Bristol Bay, a coastal grouping that in-
cluded Bristol Bay and Prince William Sound, whereas
samples from Yakutat were separated from all other
locations. Although sample sizes were smaller for the la-
ser ablation ICP-MS assays, the data identified a group-
ing of locations in multivariate space that included the
southeast Bering Sea, Prince William Sound, and Ya-
kutat, whereas samples from both the north Bering Sea
and Bristol Bay were separated from each other and the
other locations. The observation that locations did not
cluster into similar geographic groupings was probably
a function of different mechanisms of elemental incor-
poration in otoliths. Elements assayed by ICP-MS in the
present study substitute for Ca in the aragonitic lattice,
and are believed to primarily reflect ambient physico-
chemical differences among natal locations (Bath et al.,
2000; Milton and Chenery, 2001; Bath Martin et al,
2003). However, with the exception of Sr, the elements
assayed by EPMA are likely under physiological regula-
tion and therefore probably do not directly reflect either
water chemistry or temperature (Campana, 1999). In
either case, the application of elemental signatures in
otoliths as natural tags of natal origins requires only
that the signatures allow accurate classification of the
natal origins of an unknown fish. A final caveat is nec-
essary because it remains possible that preservation
effects, particularly for labile elements that are not
incorporated into the aragonite lattice, may also have
contributed to at least some of the differences among
locations (Milton and Chenery, 1998; Proctor et al.,
1998). If present, such effects would clearly confound
attempts to use elemental signatures as a natural tag
of natal origins (Thresher, 1999).
It is important to note that although EPMA and laser
ablation ICP-MS provided complementary information
614
Fishery Bulletin 102(4)
on elemental composition, the spatial scale on which
the data were gathered was different. Our laser ablation
ICP-MS method required that we ablate a 70 /im x 70
/jm raster, or a 720-/im line, in order to enable sufficient
time to generate precise estimates of otolith composition.
The EPMA analysis was less destructive than laser ab-
lation ICP-MS, and therefore it was possible to sample
individual points at a much finer spatial resolution
(~5 fim), albeit with considerably less sensitivity and pre-
cision. For instance, using EPMA we were able to sam-
ple five points across a transect ending approximately
90 urn from the nucleus. In contrast, only a single ras-
ter could be sampled along this profile with laser abla-
tion ICP-MS. Although the diameter of laser probes
is approaching that of EPMA, ICP-MS is unlikely to
match the spatial resolution of EPMA without further
development of truly simultaneous mass analyzers such
as time-of-flight ICP mass spectrometry (Mahoney et
al., 1996). However, we were able to program the laser
probe to trace out growth increments once the otolith
radius had reached 120 fim and we found that the total
length of a daily ring was approximately 700 /jm. This
finding, in turn, allowed us to construct elemental pro-
files at reasonable spatial resolution across the otoliths
of larval pollock without sacrificing instrument preci-
sion by limiting acquisition times. Although it has not
been used before with otoliths, our approach provides
significant advantages over previous methods of using
a raster to create elemental profiles (e.g., Thorrold et
al., 1997; Thorrold and Shuttleworth 2000).
Previous work on pollock otolith chemistry was some-
what successful at distinguishing fish from locations
in the Bering Sea and the Gulf of Alaska. Severin et
al. (1995) used EPMA to sample the outer margin of
otoliths from juvenile pollock collected along the Alaska
Peninsula in the Gulf of Alaska and in Bristol Bay. We
generated elemental profiles across otoliths from the
nucleus out to approximately 90 /im for the EPMA sam-
ples, and up to 600 /mi for the laser ablation ICP-MS as-
says. The profiles revealed some interesting differences
between the elements assayed by each instrument. For
instance, only one of the elements (K) from the EPMA
analysis showed a significant interaction between pro-
file and location, yet significant profile x location interac-
tions were detected for Mn/Ca, Sr/Ca, and Ba/Ca ratios
with laser ablation ICP-MS. We were also struck by
the similarity of profiles from individuals sampled at
the same location, as evidenced by the size of standard
errors around mean values at specific distances across
the otolith. For instance, the extended profiles from pol-
lock collected in Bristol Bay and Yakutat show indepen-
dent patterns of variation for all three elements from
the nucleus out to 600 /jm. Taken together, these data
indicate that larvae from several spawning locations
are indeed encountering water masses with differing
physicochemical properties through their larval lives,
and at approximately the same time. We lack, however,
a sufficient understanding of the mechanisms control-
ling otolith chemistry to be able to relate the profiles
to specific properties of different water masses in the
study area. This knowledge will be necessary before it
is possible to reconstruct dispersal pathways of larval
pollock based on probe-based analyses of otolith geo-
chemistry. Nonetheless, the among-location variability
in elemental profiles revealed by both instruments is
encouraging and justifies further investigations of oto-
lith geochemistry in larval pollock.
Past attempts at identifying stock structure of wall-
eye pollock in the North Pacific Ocean based on genetic
techniques have been inconclusive (Bailey et al., 1999).
In the most recent study, Olsen et al. (2002) were un-
able to distinguish between pollock from the Kamchat-
ka Peninsula and several locations within the Gulf of
Alaska based on three polymorphic microsatellite loci.
Allozyme and MtDNA markers showed significant differ-
ences between North American and Asian populations,
and among Gulf of Alaska locations. These data were
difficult to reconcile because both markers showed tem-
poral instability within locations. Adult tagging studies
shed little light on the population structure of pollock
because they address questions of repeat spawning,
whereby adult fish return to the same area to spawn in
subsequent years, rather than homing to natal spawn-
ing locations (Tsugi, 1989). It has proved impossible,
except in rare circumstances (Jones et al., 1999), to
artificially mark larvae before they are dispersed from
spawning grounds, and therefore natural geochemical
tags remain the most promising avenue for determining
natal origins in walleye pollock. The ability to determine
natal origins of individual fish is critical in the case of
migratory marine fishes because it allows quantification
of population connectivity through straying of adults as
well as through larval dispersal (Thorrold et al.. 2001).
These data, in turn, identify the spatial extent of fish
stocks that are demographically isolated or alternatively
provide connectivity rates that are necessary to param-
eterize spatially explicit models if the species is usefully
viewed as a metapopulation (Hanski and Gilpin, 1997;
Smedbol and Wroblewski, 2002).
In summary, the elemental composition of otolith
material deposited during early larval life in walleye
pollock differed significantly among locations in the
Gulf of Alaska and Bering Sea. These results imply that
the larvae originated from different spawning locations,
not that they constitute separate stocks. Nonetheless,
these data represent the necessary first steps in using
elemental signatures in otoliths as natural tags of natal
origins in walleye pollock. Elemental profiles across
otoliths were also unique to specific locations, suggest-
ing that individuals collected at a location had expe-
rienced similar environmental conditions throughout
their larval lives. This observation raised the possibility
of reconstructing larval dispersal pathways based on
high-resolution sampling of otolith chemistry. Although
further work is needed to understand the processes
influencing elemental uptake in pollock otoliths, we sug-
gest that the potential information available from such
studies would be invaluable for effective management
of commercial pollock fisheries (Bailey et al., 1999). The
approach appears to be particularly appropriate for in-
Fitzgerald et al.: Elemental signatures in otoliths of larval Theragra chalcogramma
615
vestigating the potential existence of fine-scale popula-
tion structure throughout the species range. Significant
fine-scale population structure has been linked to the
failure of northern cod stocks to recover from exploita-
tion, even in the face of fishing moratoriums (Frank
and Brickman, 2000; Hutchings, 2000). Analogous de-
mographic processes acting in northern cod populations
are clearly possible in walleye pollock, given the phyolo-
genetic and life history similarities between the two
species. The structure of pollock stock complexes within
the major basins of the North Pacific Ocean remains,
therefore, a critical gap in the knowledge necessary for
the sustainable management of one of the world's larg-
est marine fisheries.
Acknowledgments
This work was funded by North Pacific Marine Research
Program to KMB, SRT and KPS, and was supported in
part by NSF grants OCE-9871047 and OCE-0134998 to
SRT. We thank the MACE, FOCI and groundfish task
scientists who collected samples, and C. Latkoczy for
assistance with the laser ablation ICP-MS analyses. This
is Fisheries-Oceanography Coordinated Investigations
collection number 0471-00A-0.
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Bath, G. E., S. R. Thorrold, C. M. Jones, S. E. Campana, J. W.
McLaren, and J. W. H. Lam.
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Begg, G. A., and J. R. Waldman.
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617
Abstract — Fishery-independent esti-
mates of spawning biomass (Bsp) of
the Pacific sardine {Sardinops sagax)
on the south and lower west coasts of
Western Australia (WA) were obtained
periodically between 1991 and 1999
by using the daily egg production
method (DEPMl. Ichthyoplankton
data collected during these surveys,
specifically the presence or absence
of S. sagax eggs, were used to investi-
gate trends in the spawning area of S.
sagax within each of four regions. The
expectation was that trends in Bsp and
spawning area were positively related.
With the DEPM model, estimates of
Bsp will change proportionally with
spawning area if all other variables
remain constant. The proportion of
positive stations (PPS), i.e., stations
with nonzero egg counts — an objec-
tive estimator of spawning area — was
high for all south coast regions during
the early 1990s (a period when the
estimated BSP was also high) and
then decreased after the mid-1990s.
There was a decrease in PPS from
the mid-1990s to 1999. The particu-
larly low estimates in 1999 followed a
severe epidemic mass mortality of S.
sagax throughout their range across
southern Australia. Deviations from
the expected relationship between
BSP and PPS were used to identify
uncertainty around estimates of Bsp.
Because estimation of spawning area
is subject to less sampling bias than
estimation ofBsp, the deviation in the
relation between the two provides an
objective basis for adjusting some esti-
mates of the latter. Such an approach
is particularly useful for fisheries
management purposes when sampling
problems are suspected to be present.
The analysis of PPS undertaken from
the same set of samples from which
the DEPM estimate is derived will
help provide information for stock
assessments and for the management
of purse-seine fisheries.
A sudden collapse in distribution of
Pacific sardine (Sardinops sagax)
off southwestern Australia enables
an objective re-assessment of biomass estimates
Daniel J. Gaughan
Timothy I. Leary
Ronald W. Mitchell
Ian W. Wright
Western Australian Marine Research Laboratories
Department of Fisheries
West Coast Drive
Waterman, Western Australia 6020, Australia
E-mail address (for D J Gaughan): dgaughan Sfish wa govau
Manuscript submitted 5 December 2002
to the Scientific Editor's Office.
Manuscript approved for publication
27 April 2004 by the Scientific Editor.
Fish. Bull. 102:617-633 (2004).
As a stock of small pelagic fish de-
creases, biomass assessment becomes
problematic because of such factors
as patchy distribution (Fletcher and
Sumner, 1999) and continuing high
catchability as a result of the schooling
behavior of some fish (Uphoff, 1993). In
these circumstances, ichthyoplankton
surveys can provide a useful means of
estimating spawning biomass, Bsp.
for some pelagic fish species. Mangel
and Smith (1990) used a technique
that assessed the presence or absence
of sardine (Sardinops sagax) eggs in
a known spawning area. They found
that changes in adult biomass were
more accurately predicted by using
presence-absence of eggs in sampling
surveys than mean egg abundance
because of misleading results arising
from the spatial patchiness of eggs. In
their presence-absence analysis, the
spatial distribution of eggs is the key
determinant of Bsp estimates and is
used in a model with a series of other
parameters to provide an estimate
of Bsp (Mangel and Smith, 1990).
Although this technique provides
an objective indication of stock size
that is not subjected to the inherent
problems in estimating BSP with the
daily egg production method (DEPM,
e.g., Ward et al., 2001), the modeling
requires substantial prior knowledge
of adult and egg production param-
eters. More recently, Zenitani and
Yamada (2000) developed an optimal
relationship between Bsp and spawn-
ing area for the Japanese sardine
(Sardinops melanostictus) using a
nonlinear model that assumed patchy
egg distribution. In their case, bio-
mass was estimated by using virtual
population analysis with catch-at-age
data from the commercial fishery.
The purse seine fishery for Sar-
dinops sagax in Western Australia
(WA) operates along the south coast
around the port regions of Esperance,
Bremer Bay, and Albany; and on the
lower West Coast in the regions of
Fremantle and Dunsborough (Fig. 1).
A level of spatial distinctness among
adult Sardinops populations neces-
sitates that three south coast regions
and the west coast region be managed
as separate fisheries (Gaughan et al.,
2002). Unlike the case with Japanese
sardine (Zenitani and Yamada, 2000),
it has not been possible to estimate
the Bsp of Sardinops in each fish-
ery in WA using only an age-based
approach. Although Gaughan et al.
(2002) considered the catch-at-age
data for the WA Sa?-dinops fisheries
to be reasonable, the data span a rel-
atively short time series, commenc-
ing in 1988 at Albany and Bremer
Bay and later at the other regions.
Therefore, both age-structure data
and estimates of spawning biomass
(Bsp) obtained with the DEPM have
provided the biological basis for
managing the Sardinops fisheries in
WA for over a decade (Fletcher,
1991, 1995; Fletcher et al., 1996,
618
Fishery Bulletin 102(4)
114°
116°
118°
J Fremantle
•Dunsborough
If" Bremer Ba
Albany
Figure 1
Map of southwestern Australia showing Pacific sardine fishing ports. North of Dunsborough to
Fremantle constitutes the west coast fishery and the other regions constitute the south coast
fishery. WA = Western Australia, SA = South Australia.
19961; Cochrane2). A population model that integrates
age-structure information and DEPM-derived estimates
of Bsp (BSp.DEPM) has recently been developed by Hall
(2000) for each of the three south coast regions.
Although the DEPM is able to provide relatively ro-
bust estimates of BSP for a variety of species (Alheit,
1993; Hunter and Lo, 1997), it is not without problems
(Cochrane, 1999; Ward et al., 2001). The Bsp_DEPM es-
timates for Sardinops in WA are presented at Manage-
ment Advisory Committee (MAC) meetings and, in turn,
are provided to the relevant government minister. The
Bsp DEPM estimates therefore undergo critical scrutiny
by industry representatives. The shortcomings of the
DEPM (e.g., sensitivity of precision for small sample
sizes) are well understood by the members of the man-
agement committee; industry recognizes that onshore
infrastructure and fleet capacity must be matched to
long-term average Bsp and that industry should not
capitalize at levels that require maximal stock sizes to
meet financial expectations. Inasmuch, a level of conser-
vatism has been adopted by the Management Advisory
Committee when setting quotas. Nonetheless, the accu-
1 Fletcher, W. J., K. V. White. D. J. Gaughan, and N. R.
Sumner. 1996. Analysis of the distribution of pilchard
eggs off Western Australia to determine stock identity and
monitor stock size. Final Report to Fisheries Research and
Development Corporation. Project No. 92/95. 109 p. De-
partment of Fisheries, Government of Australia, 168-170
St. Georges Tee, Perth, WA 6000, Australia.
2 Cochrane, K. L. 1999. Review of Western Australia pil-
chard fishery, 12-16 April 1999. Fisheries Management
Paper 129, 32 p. Department of Fisheries, Government
of Western Australia, 168-170 St. Georges Tee, Perth, WA
6000, Australia.
racy of estimates has been a contentious issue; industry
members typically believe that the scientific advice
presented often underestimates the BSP. Likewise, wide
confidence intervals around biomass estimates introduce
doubt in the minds of industry members regarding the
reliability of scientific advice, which can therefore stall
the implementation of management measures. However,
the lack of a formal and objective means of dealing with
suspect and imprecise Bsp _DEPM estimates (e.g., because
of problems with sampling spawning fish) has previ-
ously not been rigorously addressed.
Following the progression along the southern WA
coast in early 1999 of a mass mortality of Sardinops,
estimates of the quantity killed at Albany appeared
to be very low (Gaughan et al., 20001. That is, very-
few dead Sardinops were found in comparison to the
other regions where fisheries occur. Mortality rates
for Esperance and Bremer Bay were 69. 6rA and 74.59f
of the Bsp, respectively, whereas that for Albany was
estimated to be only 2.4'7f . Estimates of the mortality
rate of Sardinops in South Australia (SA. Fig. 1) for
the same epizootic event were independently found to
also be around 70* (Ward et al., 2001). The inconsis-
tency with Albany could not be attributed to different
weather conditions; the weather conditions at Albany-
were similar to those at Esperance and Bremer Bay and
would be expected to result in equally visible evidence
of mortality. Gaughan et al. (2000) contended that the
true epizootic mortality rate of Sardinops in Albany was
similar to that for the other regions, but that the very
low mortality estimate was likely seen as such in view
of the previous overestimation ofBsp-
In this study we aimed to address the problem of poor
precision, while also developing a technique to identify-
particularly poor estimates of BSPmDEPM, i.e., those for
Gaughan et al.: Distribution of Sardinops sagax off southwestern Australia
619
Table 1
Estimates of s
Dawning biomass (metric tonsl of Sardinops sagax obtained by
usi
ng the daily
egg production
method (S^p.qjpv1
for each of four
regions in southwestern Australia.
In those cases where data were sufficient to estimate a coe
fficient of variation
(CV). the range around the Bsp DEPM estimate (Min
./Max.! was caleu
lated as ±
1 standard deviation (SDl; otherwise, the 8Sn Mp u
range was calculated by using assumed (AS ) values for one or more
oftheDEPM
parameters
see text). The
lumbers of adult S.
sagax and plan
kton samples used in these calculations are shown.
Year
Mm. "sp-depm
Max.
CV
±1SD
Adult n
Plankton n
Albany
1991
12,088 19,300
30,700
—
AS
10
41
1992
9006 16,994
24,981
0.44
±1SD
10
31
1993
16,402 23,432
30,4620
0.30
±1SD
9
61
1994
15,440 31,330
55,000
—
AS
10
107
1995
7720 17.544
27,368
0.56
±1SD
10
83
1997
13,018 18,597
24,176
0.30
±1SD
27
94
1999
0 89
531
4.99
±1SD
2
263
Bremer Bay
1992
12,000 19,280
79,000
—
AS
—
25
1993
16,170 44,010
63,608
—
AS
—
32
1994
15,700 28,458
42,500
—
AS
—
102
1999
2161 4156
6150
0.48
±1 SD
3
256
Esperance
1993
14.326 32, 252
61,800
—
AS
5
50
1994
10,700 20,080
40,100
—
AS
—
150
1995
10,900 31,900
45,647
—
AS
6
105
1999
3454 17,396
31,793
0.80
±1SD
8
257
West coast
1993
14,500 41,250
78,000
—
AS
—
55
1994
3100 8714
29,000
—
AS
—
133
1996
43,300 60,228
77,200
0.28
±1 SD
4
96
1998
9112 18,985
28,951
0.52
±1SD
28
240
1999
3948 5275
6651
0.25
rtlSD
4
396
which accuracy was suspect. However, because of the
small size of the fishery and the difficulty in secur-
ing additional research funds, no fishery-independent
method of estimating biomass other than the DEPM
was undertaken. We recognized that this study could
not, therefore, unequivocally determine whether or not
any improvement in accuracy had been achieved; there-
fore, we focused on improving the consistency between
available data sets (in terms of the broader economic
environment) in order to improve the decision-making
process for what is a small-scale fishery.
We examine the relationship between relative trends
in the B
SP-DEPM
and spawning area of Sardinops in each
of four regional fisheries. We propose a method of using
the relationship between spawning area and egg pres-
ence-absence data as an indicator of Bsp that is simpler
than the methods of Mangel and Smith (1990) and
Zenitani and Yamada (2000). We specifically chose to
keep the retrospective analysis simple in recognition of
data limitations, i.e., short time series and low numbers
of samples for some DEPM surveys. In particular, our
analyses did not rely on substantial knowledge of vari-
ous parameters associated with estimating BSPDEPM.
This investigation (an objective re-assessment of Sar-
dinops Bsp DEPM) was undertaken because of the con-
trast provided by the significant collapse in distribu-
tion, coupled with the sudden and substantial decrease
in Bsp DEPM that followed mass mortality in 1998-99.
Although problems in obtaining accurate BSP estimates
with the DEPM will not be resolved by the present
study, greater consistency between indicators of the
magnitude of Bsp and the development of a transparent
and objective technique to identify apparent discrepan-
cies between the two will facilitate better management
of this key pelagic resource.
Methods
Estimates of spawning biomass with the DEPM
The estimates of Bsp used in this study (Table D were
obtained by using the DEPM, which relies on ichthyo-
plankton surveys to estimate egg production and tem-
porally concurrent samples of adult fish to estimate the
adult parameters of fecundity, sex ratio, and weight.
620
Fishery Bulletin 102(4)
The egg and adult data were subsequently combined in
the DEPM model (Parker, 1985), as follows, to estimate
spawning biomass:
B
SP DEPM
<APWk)/<SFR),
where A = spawning area;
P = egg production (numbers of eggs before
losses due to mortality);
W = weight of adult fish;
k = conversion factor to bring the various units
to a value in metric tons;
S = spawning fraction; the proportion of females
that spawn per day;
F = fecundity; number of eggs produced by a
female; and
R = ratio of females to males by weight.
The DEPM provides a point estimate of spawning
biomass, with upper and lower statistical bounds. In
those individual surveys where all parameters could be
estimated, estimates of coefficient of variation (CV) for
B,
were undertaken by using the delta method
to sum the CV of the component parameters (Parker,
1985). In turn, the CV was used to provide an estimate
of variability around the point estimate; specifically, we
used ± 1 standard deviation to indicate the upper and
lower bounds around the point estimates. In several
surveys, particularly when the DEPM was initially be-
ing applied in WA, few adult samples meant that val-
ues for adult parameters (spawning fraction, sex ratio,
fecundity, weight) could not be estimated and therefore
a CV for the final estimate of Bsp DEPM could likewise
not be estimated. Although sex ratio and weight could
be reasonably estimated from the regular sampling of
commercial catches around the survey period and fecun-
dity could be estimated from a relatively small sample
(e.g., 70-100 fish), estimating the spawning fraction was
more difficult. In this latter case, the upper and lower
bounds for the Bsp DEPM estimate were not based on a
statistical measure but rather on what were thought to
be likely low and high values of spawning fraction, re-
spectively, for Sardinops from other surveys in WA and
elsewhere (e.g., Alheit, 1993, Fletcher et al. 1996). Prior
knowledge of likely Bsp DEPM values when applying the
DEPM, specifically for the purpose of providing expert
management advice, has recently been used successfully
for Sardinops in South Australia (Ward et al. 2001).
Adult samples
Twenty DEPM surveys were conducted between 1991
and 1999 to identify stocks and to estimate spawn-
ing biomass of Sardinops of southwestern Australia
(Fletcher et al., 1996a, 1996b; Fletcher et al.3; senior
author's unpubl. data). The surveys were performed
during the peak spawning months for Sairlinops off the
west coast, Albany, Bremer Bay, and Esperance regions.
The timing of the DEPM survey cruises in each region
was based on gonadosomatic indices for samples obtained
from commercial catches, as described in Gaughan et al.
(2002). The aim was to obtain samples from 35 catches
of adult fish, as recommended by Alheit (1993), but
this number was never achieved and in some cases no
samples were obtained (Table 1). For each catch sampled,
the ovaries from 15-50 females were immediately placed
in 10% formalin and subsequently prepared histologi-
cally for microscopic examination. The remainder of the
subsample was processed to obtain mean female weight
and sex ratio by weight. Mature ovaries were retained
for estimation of fecundity.
Plankton sampling and estimation of egg production
Plankton sampling extended from nearshore waters
to the edge of the continental shelf (Fig. 2). Sampling
stations were generally spaced uniformly, typically 2-4
nautical miles apart, along transects perpendicular to
the shore. Analysis of Sardi/iops egg distribution from
surveys conducted in the early 1990s indicated that
these surveys sufficiently covered the distribution of
the spawning stock (Fletcher and Tregonning, 1992;
Fletcher et al., 1994), and later geostatistical analyses
of Sardinops egg distribution patterns confirmed that
the spacing of transects and stations were adequate to
effectively represent the spatial distribution (Fletcher
and Sumner, 1999). The earlier surveys were used to
refine the spatial range of subsequent surveys. The
number of plankton samples taken in each survey has
generally increased since the early 1990s (Table 1).
Sardinops eggs were collected by using vertical tows
that allowed the water column to be sampled from a
maximum depth of 70 m to the surface; Fletcher (1999)
showed that Sardinops eggs off southern Australia are
typically restricted to the upper 70 m. Bongo nets with
diameters of either 60 or 26 cm and constructed of
either 500- or 300-micron mesh were used; the change
to smaller nets was made to reduce sample volume and
hence sorting time, whereas the change to smaller mesh
was made to increase efficiency in capturing yolksac
larvae; these changes did not affect the sampling ef-
ficiency for Sardinops eggs. Tow speed was standard-
ized at 1 m/s. All samples were collected between 0630
and 1800 hours and immediately preserved in 5-10%
formalin and seawater.
Plankton samples were examined under a dissecting
microscope. Sardinops eggs were identified, classified
into 12 developmental stages (White and Fletcher4), and
1 Fletcher W. J., B. Jones, A. F. Pearce, and W. Hosja. 1997. En-
vironmental and biological aspects of the mass mortality of
pilchards (Autumn 1995 1 in Western Australia. Fisheries
Research Report, Fisheries Department Western Australia
106, 115 p. Department of Fisheries, Government of West-
ern Australia, 168-170 St. Georges Tee. Perth, WA 6000.
Australia.
4 White. K. V.. and W. J. Fletcher. 1998. Identifying the
developmental stages for eggs of the Australian pilchard.
Sardinops sagax. Fisheries Research Division WA. Fisher-
ies Research Report 103, 21 p. Department of Fisheries,
Government of Western Australia. 168-170 St. Georges Tee,
Perth, WA 6000. Australia.
Gaughan et al.: Distribution of Sard/nops sagax off southwestern Australia
621
Table 2
Correlations between
1) proportion of positive stations (PPS) and pr
jportional spawning areE
(PSA) and 2)
PPS
and estimated
spawning area (km2)
result
ng from surveys of Sai
•dinops sagax eggs
at four regions in
southwestern Austra
lia.
PPS
is the pro-
portion of the total number
jf plan
kton sampling stations that contai
ned at least one S.
sagax
egg that had been
spawned on the
previous night. PSA
is the
propoi
tion of the total
survey area that
consisted of spawning area. The values for
spav
ming area
are also provided.
Survey
PPS
PSA(%)
Correlation I
Area (km-)
Coi
relation II
Albany
Jul
Jul
Jul
Jul
Jul
Jul
91
92
93
94
95
97
0.46
0.58
0.52
0.60
0.33
0.19
37
51
36
60
28
21
1806
2686
2391
6672
1977
2224
Jul
99
0.15
1
0.94
107
0.68
Bremer Bay
Jul
Jul
Jul
92
93
94
0.61
0.72
0.70
64
67
71
2807
2809
4474
Jun
99
0.12
12
0.99
908
0.86
Esperance
Jul
Jul
Apr
93
94
95
0.50
0.57
0.61
44
73
36
5715
9796
5277
May 99
0.09
3
0.81
7840
0.83
West coast
Jul
Jul
Aug
93
94
96
0.53
0.30
0.23
62
38
16
8012
5199
2202
Aug 98
0.10
7
1835
Aug
99
0.12
10
0.98
1836
0.96
counted. Estimation of egg production was undertaken
by fitting a negative exponential model (Picquelle and
Stauffer, 1985) and was derived from the y-axis inter-
cept of the regression model, representing time 0. The
number of stages used to fit the model depended on the
egg abundance for each stage; the best fitting model
was chosen visually from an iterative sequence of fits.
The best fit was not necessarily that with the smallest
CV but rather that which intuitively did not violate our
understanding of natural mortality rates as determined
from the literature. For example, the slope of the regres-
sion model must be negative and egg mortality rates
should fall within the broad range of 0.9-3.9/d (e.g.,
Smith et al., 1989).
Estimation of spawning area
According to water temperatures during each survey and
the stage of egg development, Sardinops eggs were deter-
mined to have been spawned either the previous night
("day-1") or two nights previous ("day-2") as described
by Fletcher et al. (1996). The total survey area was esti-
mated by constructing a polygon around all stations. The
spawning area was defined as the area in which day-1
Sardinops eggs were found (Fletcher et al., 1996a). The
areas of the polygons around stations that had day-1
eggs, referred to as positive stations, were summed to
estimate the spawning area for each zone. When positive
stations occurred on the margin of the sampling area,
polygons for these positive stations were drawn as for the
embedded positive stations, but the areas of these poly-
gons were extended by a standardized amount beyond
the sampling areas (Wolf and Smith, 1986).
The proportion of positive stations (PPS) was calcu-
lated for each survey. The proportion of the survey area
(PSA) that consisted of spawning area was also evalu-
ated in each case. PPS and PSA were positively corre-
lated at each region (Table 2); this result was expected
and indicated that PPS provides a realistic representa-
tion of changes in spawning area. The relationships
between PPS and the areal estimates of spawning area
were not as strong, but these latter estimates suffered
as potential predictors of biomass in our study because
of the large differences in numbers of plankton samples
collected between surveys (Table 1). PPS is thus not
only an objective measure but can also be considered
as an index of spawning area.
Modeling of spawning biomass
The collapse in distribution of Sardinops at each of four
locations in southern Western Australia in 1999 is shown
by the decline in spawning area (Fig. 2). The importance
of this collapse in providing contrast for model fitting
in otherwise poor data sets (few points with either flat
or clumped distributions) is evident from linear fits of
622
Fishery Bulletin 102(4)
Albany
t
1991
1992
-..' ■ **"'.'•
1993
1994
^»^
. ;/:
1?
1995
1997
••-' .■'■■
■■:■:
1999
Figure 2
Sardinops sagax spawning area (distribution of eggs spawned on the night previous
to sampling) from ichthyoplankton surveys conducted between 1991 and 1999 for
Albany, Bremer Bay. Esperance, and west coast regions.
Gaughan et al.: Distribution of Sardinops sagax off southwestern Australia
. 623
Bremer Bay
1184
1189
119 4
119.9
120 4
34
t
N
34 5
35
1992
1993
1994
— ■'•■■
1999
1204
Figure 2 (continued)
BSP.DEPM against PPS for the south coast locations
(Fig. 3). Because we wished to examine the relationship
between trends in DEPM-based estimates of Bsp and
PPS with the aim of improving estimates of Bsp, the
development of an appropriate model is described here
from first principles, followed by a selectivity analysis
of error variance to choose the optimal estimator of Bsp.
Given that we did not have a means of assessing the level
of accuracy of the "adjusted" estimates, and the aim was
therefore to improve consistency between data sets for
the purpose of enhancing the decision-making process,
our criteria in choosing an optimal estimator was to
624
Fishery Bulletin 102(4)
Esperance
120 5 121 1215 122 122 5 123 123 5 124
t
N
1993
•
1994
1995
. ;%
1999
Figure 2 (continued)
minimize variance. In terms of improving management
of the Sardinops fisheries in southwestern Australia,
we considered this approach appropriate because of the
relatively conservative exploitation rates that have been
adopted by the Management Advisory Committee.
considered the following general relationship between
Bsp DEPM and PPS holding over time:
(B
SP-DEPM
i, = cx0 (PPS,)'- + a, + er
Hi
Model selection
The procedure used in the present study was to first
invoke a general model and then use the data to drive
a simplification process in order to avoid a specification
error. Thus, for each of the fishery regions, we first
where A is common for all areas, aQ and a2 are area
specific constants, and the error term e, is independent,
homoscedastic and normal with a mean of zero. This
model was chosen specifically in order to be amenable
to Taylor series expansion during the simplification
process. In satisfying dimensional and conservational
Gaughan et al.: Distribution of Sardinops sagax off southwestern Australia
625
West Coast
114.5 115 1155 116
N
^ , 1993
1994
1996
1998
...
1999
1145 115 1155
Figure 2 (continued)
arguments, a, must be zero; therefore the above family
of models reduces to
(Bspdepm\ = a0(PPS,)^ + e,
(2)
An attempt to fit the linear regression model, composed
of the natural logarithms of either side of the above rela-
tion, to the observed data was unsuccessful because of
heterogeneity of error variance.
Direct estimation of model II with a nonlinear regres-
sion procedure gave estimates of A that were near 1 and
with large standard errors on account of the small size
of the data sets. However, residual diagnostics were sat-
isfactory. Because the observed PPS values fell between
626
Fishery Bulletin 102(4)
1990 1992 1994 1996
O 04
Q.
O
a.
0.2
O 04
CL
O
1998 2000
Bremer Bay
1990 1992 1994 1996 1998 2000
Esperance
1990 1992 1994 1996 1998 2000
West coast
1994 1996
Year
PPS
Figure 3
Pints of the proportions of positive stations (-•-) and BSP.DEPM estimates (--■--) for the four Sardinops
sagax fisheries in southwestern Australia. The right-hand panel shows linear fits of the relationship
between proportion of positive stations and BSP.DEPM estimates.
Gaughan et al.: Distribution of Sardinops sagax off southwestern Australia
627
Table 3
Parameter estimates for two models (III and IV, see text for details) of Sardinops sagax spawning biomass, including tests for
zero coefficients, at each of four regions in southwestern Australia.
Model III
Model IV
Albany
SE of estimate: 6011
Bsp
SE of Bsp
((22)
P-level
Albany
SE of estimate: 6343
BSP
SEo{Bsp
((23)
P-level
Intercept -4597.15
PPS 56.780.19
2419.94
6638.90
-1.90
8.55
0.070661
1.91E-08
PPS 45,910.11
3552.36
12.92
4.96E-12
Bremer Bay
SE of estimate: 4016
BSP
SE of Bsp
r( 14)
P-level
Bremer Bay
SE of estimate: 3994
BSP
SE of BSP
((18)
P-level
Intercept -1436.88
PPS 45,341.85
1573.94
3638.2
-0.91
12.46
0.37674
5.75E-09
PPS 42,784
2308.30
18.53
9.47E-12
Esperance
SE of estimate: 4639
BSP
SE ofBsp
r(20)
P-level
Esperance
SE of estimate: 10,214
BSP
SEo{Bsp
((21)
P-level
Intercept 15,840.52
PPS 17,790.27
1751.38
4097.73
9.045
4.34
0.000317
1.66E-08
PPS 48,377.13
5095.09
9.49
4.76E-09
West coast
SE of estimate: 15,280
Bsp
Intercept 5316.10
PPS 63,192.69
West coast
SE of estimate: 15,330
SEofBgp ((32)
4826.58 1.10
23,161.29 2.73
P-level
0.278929
0.010251
PPS
BSP
84,615.52
12,615.76
r(33l
6.71
P-level
1.22E-07
zero and one, and A was also close to 1, model II was
able to be recast in a more tractable form by using the
Taylor series expansion of the RHS of model II about
PPS = 1, leading to the relationship
iB.sp.pps»/= <x0PPS, + S+et,
(3)
where the expected value of 8 is approximately
-0.25a„(A-l). Details of the derivation are provided in
Appendix 1.
Fitting the regression model III to the DEPM-based
estimates of Bsp gave the estimated coefficients shown
in the left hand column of Table 3. Residual diagnostics
showed that model III was satisfactory. Because none
of the intercept terms were significantly different from
zero, the parsimonious model
{BSP-pps)t= a0(PPS)t + et
(4l
was fitted, giving the results in the right hand column
of Table 3. Residual diagnostics were also satisfactory
for these models.
Optimal estimation of spawning biomass
We now have available two unbiased estimates of Bsp:
estimator 1 (i.e., Bsp _DEPM) with associated error e'.
which has an expected value of 0 and variance Var(e')
= rjj2; and estimator 2 (i.e., Bsppps) which model IV
of the previous section fitted to the values of Bsp _DEPM
with error e, which had an expected value of 0 and
variance Var(e) = o~2. Thus estimator 2 can be seen to
be unbiased and with full error term (e+e). In order to
obtain an optimal predictor, i.e., with minimum vari-
ance, of spawning biomass *>Bsp 0 „„„,„/), we considered
the weighted average of the two estimators above:
Bsp-Optimai = (("'' estimator 1 + (1-wO estimator 2),
with weight w: 0<«'<1.
We must choose the weight w of estimator 1 in order
to minimize the variance ( Var(Bsp 0 „,„„„/)) of the esti-
mator B.Sp.0p,„„o/.
Var(Ssp.oP,„„n/» = Var(B»e+(l-w)(e+e'))
= Varie +{l-w)e I
= Var(e) + ( l-u;)2Var(e') + 2( 1-w i
covariance(e.e')
= a2+il-w)'2al2+2(l-wtc><71p
where p = correlation between e and e'. For Var (Bsp
Optimal t° be a minimum, the w derivative must be zero,
yielding
628
Fishery Bulletin 102(4)
0.4 0.6
DEPM weighting
Figure 4
The relationship between error variance between the two estimators for spawn-
the optimally weighted estimate of Bsp (i.e., B
SPOPTIUAL
). Error variance is
shown for a range of error correlations from r = -0.9 to -0.2.
0 = ( 1-w ) <JX + ap,
which requires iv = 1 + opl o~v
In the event of p = -axla, Bsp .0pllmal will have w =
0, i.e., the optimal estimator will just be estimator 2
alone.
The limited sample information available indicates
that c7j is approximately equal to ex, which we therefore
assume in order to simplify the next analysis. Because
BSp_ppS is based on estimates of PPS, which can be
estimated with more confidence than Bsp DEPM, it must
be expected that often, if not always, Variance! BSPmPPS)
< Variance(Bsp.D£PW).
i.e., Var(e+e') < Var(<?) + f , for small £ >0;
i.e., a2 + ct,2 + 2p ct,ct< a- + e;
i.e., 2p < (-rjj- + e)laxa.
This requires p < -0.5 when crl = a, and e is small. This
relation has an important role in our decision of what
is the best estimator.
In Figure 4 the error variance for the estimator Bsp
optimal 's shown for various DEPM weightings and a
theoretical range of error correlations (i.e., between e
and e) from r = -0.9 to -0.2. Our aim was to choose a
DEPM weighting that provides minimal error variance
along the most stable regions of the suite of error cor-
relation curves, i.e., where the error correlation curves
are flattest. The error correlation curves from -0.4 to
-0.7 were the most stable and across these the DEPM
weightings from 0.3 to 0.7 had the smallest error vari-
ance. Therefore we choose 0.5 as our preferred DEPM
weighting, which lies centrally within a stable part of
the range of theoretical error correlations.
Results
The decline in spawning area in each region (Fig. 2)
corresponded to declines in Bsp DEm ( Table 1), which in
turn were reflected by the Bsp .optimal estimates (Fig. 5).
We recognize that imbalance in the intensity of samples
between years poses a problem for the interpolation of
data between sampling stations but we contend that the
collapse in distribution observed is of sufficient contrast
to be a reliable reflection of the estimated 709f decrease
in Sardinops biomass that resulted from the 1998-99
epidemic (Gaughan et al., 2000; Ward et al., 2001). Note
that we have used Albany (Fig. 2A) as the primary sup-
port for this contention because of the larger data set.
The same pattern was observed at all regions, although
it was not so marked for the west coast Sardinops (Fig.
2D) because estimated Bsp (this term hereafter is used
generically) had already declined substantially between
1996 and 1998.
Despite sometimes large intervals between consecutive
surveys, there were two broad patterns in the trends for
Sardinops Bsp during the 1990s (Fig. 5). Within each
region on the south coast (Albany, Bremer Bay, and
Esperance), Bs
P DEPM
remained relatively high in the
early to mid 1990s before decreasing substantially by
1999. In contrast to the results from south coast DEPM
surveys, the west coast estimated BSP_DEPM fluctuated
widely (Table 1). This fluctuation resulted in a rela-
tively poor fit of the optimal model and correspondingly
wide CIs. Since 1996, when substantially more samples
were routinely collected during each survey on the west
coast, there has also been a decrease in Bsp consistent
with that observed on the south coast.
Inconsistency in the determination of variability es-
timates around some B^PI)EPM estimates precludes any
definitive statements about the relative precision of the
Gaughan et al.: Distribution of Sardinops sagax off southwestern Australia
629
60000 ■
Albany
50000 •
30000 ■
20000 ■
■
.
I
,
■
10000 ■
0 ■
■
1994 1996 1998 2000
80000 -
3remer Bay
60000 -
40000 -
■ \
.p
20000 -
" /
0 -
"\ £
Year
Figure 5
Sardinops sagax BSP_DEPM estimates Icircles with error bars)
and Bsp qptimai estimates (squares with accompanying 95rr
confidence interval boundaries! at four regions of southwestern
Australia. In each case the confidence intervals that extend
below the .v-axis have not been shown.
Bspoptimal estimates. Notwithstanding this, the CIs for
the optimal estimates always encompassed the DEPM
point estimates. Because the CIs were so broad in rela-
tion to the point estimates, only the point estimates for
BSP_DEPM and BSP 0PTIMAL are further compared.
The estimated Bsp .optimal indicates that for Albany
the spawning biomasses were underestimated in 1992
and 1999 and overestimated in 1997 and that the differ-
ence between estimates in each case was greater than
25% (Fig. 5, Table 4). Although the DEPM estimated
that the Albany Bsp remained steady between 1995
(17,544 t) and 1997" (18,597 t), the PPS almost halved
from 0.33 to 0.19 for these same surveys (Tables 1 and
2). For Bremer Bay the estimates for Bsp DEPM and the
Bsp-optimal were within 20% (Fig. 5, Table 4). In Esper-
ance the B
SP OPTIMAL
estimate indicates that the DEPM
underestimated Bsp by 199r in 1994, but overestimated
Bsp by 37% in 1999.
The DEPM estimates of Sardinops Bsp on the west
coast had the poorest fit against PPS. Thus, the optimal
estimates of BSP differed by >30% in four of the five
DEPM-based Bsp estimates. In particular, the 1994 and
1999 DEPM estimates were too low. and those for 1996
and 1998 were too high.
Discussion
Egg presence-absence analysis, i.e., proportion of positive
stations (PPS), was used to objectively assess changes
in the spawning area of Sardinops along the south and
lower west coasts of WA between 1991 and 1999. The
630
Fishery Bulletin 102(4)
60000 -
Espe
ranee
50000 -
40000 ■
30000 ■
.
■.
•
20000 ■
10000 ■
0 ■
■
1992 1994 1996 1998 2000
aoooo -
.
West Coas
60000 -
40000 -
■ V
■
20000 -
\
y\
■
0 -
/ \
i
1994 1996
Year
Figure 5 (continued)
collapse in distribution was evident in 1999 for three of
the four regions examined and has been attributed to a
combination of fishing mortality, several years of poor
recruitment, and two mass mortality events (Murray
and Gaughan, 2003). The spawning stock in Albany and
Bremer Bay decreased to a point where the annual total
allowable catch (TAC) in these fisheries was reduced to
zero. The concurrent decreases in Bsp _DEPM and PPS at
the south coast regions in 1999, estimated shortly after
the progression of an epidemic mass mortality (Gaughan
et al., 2000), indicates a positive relationship between
Bsp-depm and PPS. This widespread response provides
support for the concept of using the PPS-BSP DEPM rela-
tionship to objectively detect, albeit retrospectively,
particularly suspect estimates of Bsp_DEPM.
The marked decline in Bsp in 1999 to a very low
level at Albany provided sufficient contrast in the time
series of data to allow detection of an overestimation of
spawning biomass in 1997. Although the difference may
not appear to be overly large, the critical factor in this
particular case is that the Bsp of 18,597 metric tons (t)
was seen to be healthy, whereas an estimate of 13,660 t
would have clearly indicated to the Management Advi-
sory Committee a downward trend in Sar-dmops Bsp. In
turn, such a result would have supported the contention
that the stock was in decline, which was expected be-
cause of several years of poor recruitment, as evidenced
by catch-at-age data (Gaughan et al., 2002). Further-
more, in 1998, during the 6 months prior to the mass
mortality, the purse-seine fleet in Albany experienced
significant difficulties in meeting catch expectations,
which also indicated that the stock was at a low level.
Although we cannot assess precision of the revised es-
timates of Bsp, it is likely that the Bsp-OPTIMAI ^01" 1997
still overestimates the actual stock size.
The evidence for a decline in Bsl, at Bremer Bay from
1994 to 1999, as suggested by the decline in PPS, was
supported by trends in catch curves for that period,
which showed very low levels of recruitment (Gaughan
et al., 2002). The recruitment trends ensured that the
annual TACs for Bremer Bay after the mid 1990s did
not increase but instead were gradually reduced. The
Gaughan et al.: Distribution of Sardmops sagax off southwestern Australia
631
Table 4
Comparison
of estimates of spawning
biomass for Sardi
nops sagax from four regions
in southwest
era
Aust
ralia. Estimates
obtained by
using
the daily egg produc
ion method (DEPM) were re-estimated by
using
a model that
considered the proportion
of positive stations
iPPS. see text and Table 2) during each of the DEPM surveys.
In turn, a weighted
or
optimal, estimate was
derived from
the p
•evious two estimates. The difference and ratio between the optimal and the DEPM esti
mates are provided for
comparison.
Optimal estimates that fall outside the 95ri confidence intervals for the DEPM estimates
and optimal:DEPM ratios
that differ from 1 by greater than 0.25
are shown in bold type.
DEPM estimate
PPS estimate
Optimal estimate
DEPM-PPS estimate
OptimahDEPM
Albany
1991
19,300
20,190
20,209
-890
1.05
1992
16,994
25,456
21,811
-8462
1.28
1993
23,432
22,823
23,653
609
1.01
1994
31.330
26,334
29.438
4996
0.94
1995
17,544
14.484
16,347
-1197
0.93
1997
18,597
8339
13.660
10,258
0.73
1999
89
6584
3488
-6495
39.19
Bremer Bay
1992
19.280
21,346
22,689
-2066
1.18
1993
44,010
25,195
37.407
-6603
0.85
1994
28,458
24.495
29,204
3963
1.03
1999
4156
4199
4645
-43
1.12
Esperance
1993
32,252
23,542
28,220
-4032
0.88
1994
20,080
26,838
23,827
-6758
1.19
1995
31.900
28,721
30,705
3179
0.96
1999
17.396
4238
10.875
13,158
0.63
West coast
1993
41,250
48,318
43.048
-7068
1.04
1994
8714
27,350
17,049
-18,636
1.96
1996
60,228
20,968
39,845
39,260
0.66
1998
18,985
9117
13,723
9868
0.72
1999
5725
10.940
7714
-5665
1.35
very poor fit for Esperance may reflect the low sample
size or may be indicative of a certain level of decoupling
of BSP and PPS not evident in the other south coast
regions.
The 1996 estimate for the west coast was hampered
by poor estimation of adult parameters resulting from
a low number of adult samples obtained; the Bsp DEPM
estimate for that year appeared to be much too high
and, intuitively, was not used as the basis for making
management decisions at that time. The precautionary
decision to use the lower bound rather than the "best"
estimate from the 1996 west coast DEPM survey was
therefore justified. In contrast, the estimate of B^pDEP!il
of 8714 t in 1994 for the west coast Sardmops stock
appears to have been too low. The lack of an obvious
collapse in distribution off the west coast was partly
due to the marked changes in the intensity and dis-
tribution of sampling after 1996. Another contributing
factor may have been a change in the distribution of
the spawning adults because of the anomalously warm
water in the Indian Ocean in the late 1990s (Webster
et al., 1999) during the last major La Nina. The PPS
of only 0.10 in 1998, before the epidemic mortality, may
therefore have been the result of behaviorally mediated
changes in the distribution of Scuxlmops in response to
the warmer than average water temperatures (Gaughan
et al., 2000). We recognize that other factors may also
have influenced the distribution of Sardinops off the
west coast but our relatively short time series of data
precluded development of more definitive, alternative
hypotheses at this time. The potential for unusual en-
vironmental conditions to influence spawning behavior
applies equally to the south coast Sardinops; interpreta-
tion of PPS data therefore also requires consideration
of environmental conditions in each case. As our time
series of biomass estimates is extended through further
DEPM surveys, hypotheses regarding the influence of
the environment will be further developed. Prelimi-
nary hypotheses have already been presented to the
Management Advisory Committee and thus form part
of current management deliberations.
The results from this retrospective analysis will im-
mediately be used to reassess the Bsp estimates ob-
tained for Sardinops in WA during the 1990s before
632
Fishery Bulletin 102(4)
refitting them to Hall's (2000) integrated models for
the three adult assemblages on the south coast of WA.
The integrated model is tuned with BSPDEPM estimates.
Therefore, replacing BSPDEPM estimates with BSP_0PTI_
MAL estimates will result in a model that better simu-
lates the size of the Sardinops stocks off southern WA.
Although the changes may appear trivial, it is impor-
tant that re-estimating the most deviant estimates of
Bspdepm can De undertaken in a manner that satisfies
demands by stakeholders, including industry, for open-
ness and clarity in the provision of scientific advice.
As further DEPM surveys are conducted to assess the
status of the Sardinops stocks in the five to six years
following the 1998-99 mortality event, more reliable re-
lationships between PPS and Bsp DEPM will be developed.
To assist this process, the relative merits of the data
for individual DEPM surveys can also be re-examined,
particularly those data that this study has indicated to
have resulted in poor estimates of BSPDEPM. An ongoing
iterative approach that employs retrospective analyses
will be undertaken in an attempt to continuously re-
duce the variance of the PPS-BSP _DEPM relationship.
This approach will permit further refinement of Hall's
(2000) integrated model, a process already in prog-
ress (Stephenson et al.5) and will therefore contribute
to increased confidence in the scientific advice that is
provided for management of the Sardinops fisheries in
WA. Eventually, PPS alone may be sufficient to provide
an indication of spawning biomass with an acceptable
level of precision.
Besides contributing to the integrated model, the BSP
optimal point estimates obtained over nearly a decade in
each of four management regions now provide a clearer
indication of potential maximum biomass levels against
which industry members can plan their businesses. Be-
cause of the highly variable recruitment of many small
pelagic fish, purse-seine businesses that target fish such
as Sardinops should not invest at levels that require an
economic return based on maximum biomass sizes. For
the purse-seine fishing zones in southern WA the maxi-
mum spawning biomass from which purse-seine indus-
try members can expect their TAGS to be determined
are as follows: west coast 40,000 t, Albany 29,000 t,
Bremer Bay 37,000 t, and Esperance 30,000 t. Although
these values provide an upper limit to business plan-
ning, maximum biomasses should not represent invest-
ment targets. These values provide an indication of
the maximum size for the industry but, because of the
"natural and social disarray" that can result "from har-
vesting marine fish species at the crest of their produc-
tion" (Smith 2000), the industry should be structured
at a level that focuses on longer-term average biomass
and that includes industry's ability to survive during
periods of low stock size. Maximum and average Bsp
for Sardinops at each of the four management regions
Stephenson, P., N. Hall, and D. Gaughan. 2004. Unpubl.
data. Department of Fisheries. Western Australian Ma-
rine Laboratories, North Beach, Western Australia 6920,
Australia.
in southwestern Australia will be further investigated
during ongoing development of the integrated model and
as more information becomes available.
Conclusion
Even large numbers of plankton samples can result in
imprecise estimates of egg production for use in DEPM
calculations (e.g., Mangel and Smith, 1990). Relative
trends in spawning area that can be obtained from the
same survey by using egg presence-absence analysis
provide a secondary means of assessing trends in the
status of stocks. This egg presence-absence analysis
will be particularly useful for stocks already assessed
by using DEPM surveys and more so for those that do
not have large amounts of ancillary information, such
as long time-series of catch-at-age data, or meaningful
effort data.
Detection of either upwards or downwards bias in
estimates of Bsp will be considered in the integrated
model and also communicated to industry members to
increase their understanding of the stock in each region.
Although this review of biomass trends of Sardinops
during the 1990s cannot change how Sardinops were
managed during that period, an increased understand-
ing of both the stock sizes and the science behind the
biomass assessments will facilitate ongoing manage-
ment processes.
Acknowledgments
The authors sincerely thank all Department of Fish-
eries staff involved with the collection and analysis
of historical ichthyoplankton-survey data, in particu-
lar Stuart Blight, Gary Buckenara, Cameron Dawes-
Smith, Rick Fletcher, Kieren Gosden, Matt Robinson,
Rob Tregonning, Ken White, Bruce Webber, and other
personnel on PV Baudin and PV McLaughlan. We also
thank Kevern Cochrane (FAO) for a detailed review of
an earlier version of this manuscript. We are grateful
to the Fisheries Research and Development Corporation
(Canberra) that provided funding through Project 92/25
for the earlier DEPM surveys.
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Appendix 1— Derivation of model III from model II
We start with model II
"SP_DEPM ~ K, )""•-> + er
For brevity, y is used to denote PPS. We first note that
y'~=yy"'~1'- Now we obtain the Taylor series expansion of
yU-D about. v=l giving
Because y is a proportion, it satisfies 0<y<l so that
the higher powers of {y— 1) will be individually and col-
lectively small. If y is close to 0.5, a further algebraic
simplification of the second term is possible, giving the
identity
v(y-l) = -0.25 + (v-0.5)2.
vi;'"= 1 + (A-1)(v-1)-mA-1)(A-2i/2'<y-I):
+(A-l)(A-2)(A-3)/3!(.v-l)-' + ... .
Multiplying this expression through by y gives
yl = y + _y(_v-l)(A-l)
+ ytterms involving second and higher powers of t v— 1 )].
When v is in the range 0.25<v<0.75, the right-hand side
of this identity remains close to -0.25. Thus model II
may be simplified to
Bsp pps = a„(PPS) - 0.25a„( A-l ) + <?,
which is the form of model III.
634
Abstract— Understanding recoloni-
zation processes of intertidal fish
assemblages is integral for predict-
ing the consequences of significant
natural or anthropogenic impacts on
the intertidal zone. Recolonization of
experimentally defaunated intertidal
rockpools by fishes at Bass Point, New
South Wales I NSW), Australia, was
assessed quantitatively by using one
long-term and two short-term studies.
Rockpools of similar size and position
at four sites within the intertidal zone
were repeatedly defaunated of their
fish fauna after one week, one month,
and three months during two short-
term studies in spring and autumn i 5
months each), and every six months
for the long-term study (12 months).
Fish assemblages were highly resil-
ient to experimental perturbations —
recolonizing to initial fish assemblage
structure within 1-3 months. This
recolonization was primarily due to
subadults (30-40 mm TL) and adults
i >40 mm TL) moving in from adjacent
rockpools and presumably to abun-
dant species competing for access to
vacant habitat. The main recolonizers
were those species found in highest
numbers in initial samples, such as
Bathygobius cocosensis, Enneaptery-
gius rufopileus, and Girella elevata.
Defaunation did not affect the size
composition of fishes, except during
autumn and winter when juveniles
(<30 mm TL) recruited to rockpools.
It appears that Bass Point rockpool
fish assemblages are largely con-
trolled by postrecruitment density-
dependent mechanisms that indicate
that recolonization may be driven by
deterministic mechanisms.
Fish recolonization in temperate
Australian rockpools:
a quantitative experimental approach
Shane P. Griffiths
Environmental Science
and
Institute for Conservation Biology
University of Wollongong
Wollongong, New South Wales, Australia
Present address: CSIRO Marine Research
233 Middle Street
Cleveland, Queensland 4163 Australia
Email address: shanegnffiIhsacsiro.au
Ron J. West
Environmental Science
University of Wollongong
Wollongong, New South Wales, Australia
Andy R. Davis
Institute for Conservation Biology
University of Wollongong
Wollongong, New South Wales, Australia
Ken G. Russell
School of Mathematics and Applied Statistics
University of Wollongong
Wollongong, New South Wales, Australia
Manuscript submitted 28 April 2003
to thr Scientific Editor's Office.
Manuscript approved for publication
5 May 2004 by the Scientific Editor.
Fish. Bull. 102:634-647(2004).
Rocky intertidal fishes are faced with
many biotic (competition and food
availability) and abiotic (temperature
and salinity) factors that can influ-
ence their distribution and abundance
(Gibson. 1982). Despite occupying a
dynamic environment, the fish assem-
blages in intertidal rockpools have
been widely shown to remain persis-
tent through time (Grossman. 1982.
1986; Collette. 1986). These commu-
nities can also rapidly return to their
original state after major or even
catastrophic perturbations (Moring,
1996). Such resilience is less common
among assemblages of invertebrates
(Connell, 1972; Astles, 1993) because
recolonization of substrata is normally
dependent upon successful larval
settlement (Paine and Levin, 1981).
In contrast, fish can rapidly colonize
available habitat by larval recruit-
ment from the plankton (Willis and
Roberts, 1996. Beckley, 2000; Griffiths
2003a) but also by the relocation of
subadults and adults from adjacent
rockpools (Beckley, 1985a; Griffiths,
2003a). Under natural conditions rock-
pools can be defaunated by events such
as hurricanes (Moring, 1996) and, in
some regions, by seasonal freezing of
rockpool water (Thomson and Lehner,
1976; Moring, 1990). These events
can create new microhabitats or open
existing ones for fish to colonize, and
therefore have the potential to change
fish assemblage structure.
Understanding recolonization pro-
cesses of intertidal fish assemblages
is integral for predicting the conse-
quences of natural or anthropogenic
impacts on the intertidal community.
The role of disturbance and recoloni-
zation processes in structuring inter-
Griffiths et al.: Fish recolonization in temperate Australian rockpools
635
Tasman Sea
•^Shellharbniir
Bass Point
5 km
Figure 1
Map illustrating the four sampling sites at Bass Point and the location of the study loca-
tion in the Illawarra region. New South Wales, Australia.
tidal rockpool fish assemblages has received considerable
attention in many countries of the world (Bussing, 1972;
Matson et al., 1986; Yoshiyama et al., 1986; Prochazka
and Griffiths, 1992; Lardner et al., 1993; Prochazka,
1996; Faria and Almada, 1999; Silberschneider and
Booth, 2001). Such studies have identified patterns in
the rates of recovery, variation in species and size com-
position of recolonizing fish assemblages (Polivka and
Chotkowski, 1998; Beckley, 2000), and homing abilities
of many intertidal fishes (Green 1971; Yoshiyama et al.,
1992; Griffiths. 2003b).
Rockpools can be regarded as "island' habitats (Under-
wood and Skilleter, 1996) among an inhospitable rocky
landscape. Therefore, there is probably a balance be-
tween immigration (recruitment and relocation) and
emigration (mortality) of fishes after a disturbance,
sensu the equilibrium theory of island biogeography
(MacArthur and Wilson, 1967). After a period of time,
the number of species and individuals in a defaunated
rockpool can be expected to reach an asymptote when a
carrying capacity is reached. It is difficult to generalize
about recolonization rates of rockpools by fishes from
the current literature mainly owing to the diversity of
methods used, their differing effectiveness in sampling
fish, and the varying intensity of the sampling regime.
For example, most studies have used only small sample
sizes (<10 pools) and have sampled at a range of time
intervals from days (Mistry et al., 1989; Matson et al.,
1986; Polivka and Chotkowski, 1998) to years (Thomson
and Lehner, 1976; Lardner et al., 1993; Mahon and
Mahon, 1994). A second problem in measuring and
comparing fish recolonization patterns between stud-
ies is that many researchers have sampled fish using
an anesthetic (Mahon and Mahon. 1994; Pfister, 1995,
1997) or ichthyocide (Beckley, 1985a, 1985b, 2000; Wil-
lis and Roberts, 1996; Silberschneider and Booth, 2001),
which may affect subsequent catches (Yoshiyama et
al., 1986) and possibly result in fish assemblages never
reaching preperturbation conditions (see Mok and Wen,
1985; Lockett, 1998).
Nonetheless, recolonization of rockpools by fishes is
generally a rapid process, beginning within days, or
even hours, after defaunation (Collette, 1986). and com-
plete recolonization to preperturbation levels can take a
few weeks (Collette, 1986; Faria and Almada. 1999) to
several months (Mok and Wen. 1985; Willis and Rob-
erts, 1996; Polivka and Chotkowski, 1998).
The aims of this study were to quantitatively deter-
mine 1) the period required for intertidal rockpools to
recover to preperturbation levels, 2) the fish species
(permanent residents, opportunist, or transients) respon-
sible for recolonizing rockpools, 3) whether recoloniza-
tion patterns differ between the four sites at Bass Point
and between the times of year when defaunation took
place, and 4) whether fish comprise different life-history
stages before and after a disturbance (sampling) — by
examination of length-frequency distributions.
Methods
Study site and experimental design
Spatial and temporal variation in fish recolonization pat-
terns were investigated in three separate studies under-
taken along the north- and south-facing rocky platforms
at Bass Point (34°58'S, 150°93'E), New South Wales,
Australia (Fig. 1). Bass Point is a large rocky headland
that extends approximately 3 km into the Tasman Sea.
Two short-term recolonization studies (each around 5
636
Fishery Bulletin 102(4)
months in duration) were undertaken in spring-summer
and autumn-winter (hereafter referred to as spring and
autumn studies, respectively), and a long-term recolo-
nization study spanned a 12-month period. Rockpools
for each of the three studies were selected at four sites
at Bass Point, NSW, which are named Maloney's Bay
(MB), The Chair (TO, Gravel Loader (GL), and Beaky
Bay (BB) (Fig. 1). Each of the four sites are separated
by about 1 km. Rockpools were selected at each site
(50-200 m apart) according to similar physical param-
eters (i.e., volume, surface area, and substrate type)
and particularly according to their vertical elevation
on the rock platform. Because higher pools might have
less chance of fish recolonization because they are less
frequently inundated by seawater (Griffiths et al., 2003).
every effort was made to select pools located in the mid-
intertidal zone (1-1.5 m above MLLW [mean lower low
water]) and, although pools were visually similar, they
varied in volume, ranging from 762 to 2160 liters (or
0.76-2.16 m3). The bottom of the rockpools consisted of
pebbles, cobbles, and small boulders.
For the short-term studies, four rockpools were sam-
pled and fish removed at each of the four sites. In the
spring study (beginning 7 September 1999), they were
then resampled 1 week, 1 month, and 3 months af-
ter the preceding sampling date (referred to as the
"1-week," "1-month," and "3-month" samples in this
article). This study ended on 8 February 2000, after a
period of 5 months. After this date a period of at least
three months was given for pools to re-establish fish
assemblages before beginning the autumn study on 15
May 2000. Rockpools were sampled in exactly the same
manner as for the spring study, with sampling ending
on 17 September 2000. For each study, 64 samples were
taken giving a total of 128 samples for the short-term
studies. It is important to note that although every ef-
fort was made to resample pools after exactly the same
time intervals, this was not possible because of daily
time and height of tides and wave heights. For example,
for the "1 week" samples, the number of days between
samples was actually between 7 and 10 days.
To determine whether frequent sampling in the short-
term studies affected the structure of rockpool fish as-
semblages, a long-term study was undertaken by using
four different rockpools at the same four sites that were
sampled in the short-term studies. Four rockpools at
each site were considered adequate because Griffiths
(2003a) was able to detect significant differences in the
numbers of fish species and individuals in rockpools
between sites and months using four rockpools per site
in the same region that was surveyed in our study.
Rockpools were initially sampled on 22 September 1999
and then resampled twice at intervals of six months
(20 April 2000 and 11 September 2000). A total of 48
samples were taken for this study.
Data collection
Fish were collected by hand after completely emptying
each rockpool with a VMC 12V battery-powered bilge
pump of 9029 L/h capacity by using the methods of
Griffiths (2000). A thorough search of each pool was
conducted by overturning all rocks and boulders, search-
ing all crevices and shaking algal fronds until all fish
that could be seen were removed. Fishes were identified
and total lengths (TL) were measured. Fork length (FL)
was also measured for economically significant species.
Fish were categorized as being juveniles (<30 mm),
subadults (30-40 mm), or adults (>40 mm). Fish were
then released alive into rockpools or the shallow subtidal
10-30 m away from the rockpool being sampled, which
was considered to be the approximate distance that fish
may be displaced by waves and surge during significant
natural disturbances, such as storms. Each species was
categorized by its residential status in rockpool habitats
according to the definitions of Griffiths (2003c) in order
to better understand the types of fish responsible for
recolonization. These categories were "permanent resi-
dents," "opportunists," and "transients."
Statistical analyses
A repeated-measures ANOVA (RM-ANOVA) was used
(SPSS vers. 6.1; SPSS, Chicago, IL) to test for sig-
nificant differences in the numbers of species and indi-
viduals between sampling intervals (within-subjects
factor) and sites (among-subjects factor). Short- and
long-term experiments were analyzed with two sepa-
rate RM-ANOVAs. For the short-term study a third
factor of season (i.e., spring or autumn; among-sub-
jects factor) was added. All factors were considered
fixed. Assumption of sphericity of the variance-covari-
ance matrix was tested by using Mauchly's criterion
and, if violated, F tests were performed with Green-
house-Geisser-adjusted degrees of freedom. Student-
Newman-Keuls iSNK) tests were used for a posteriori
comparisons among means (numbers of species and
individuals) in RM-ANOVAs.
Nonmetric multidimensional scaling (nMDS) was
used to examine similarities in fish assemblage struc-
ture between sampling intervals and sites. Data were
fourth-root transformed, to reduce the influence of
highly abundant taxa, and a similarity matrix was
constructed by using the Bray-Curtis similarity coef-
ficient (Clarke, 1993). Stress values are given for all
ordination plots; these values describe the quality of
the representation of multidimensional relationships
of the data in a two-dimensional plane. Stress factors
of less than 0.2 (<0.2 is considered to give a good rep-
resentation of sample "relatedness" and to prevent the
prospect of drawing false inferences) were obtained for
each ordination (Clarke. 1993).
Analysis of similarities (ANOSIM) was used to test
whether fish assemblages in a priori groups differed sta-
tistically (Clarke, 1993). Abundance data for each spe-
cies were pooled for the four rockpools at each site and
time. Each ANOSIM comparison involved generating
4999 random permutations of the data to calculate the
probability that observed differences in the structure of
the fish assemblages among a priori groups could arise
Griffiths et al.: Fish recolonization in temperate Australian rockpools
637
by chance. Similarity percentages (SIMPER) were used
to determine which species were responsible for differ-
ences between selected groups. This analysis involved
calculating the average contribution of each species in
each pair of groups and comparing this contribution to
the overall dissimilarity of fish assemblages between
the groups. All multivariate analyses were carried out
with PRIMER (Plymouth routines in multivariate eco-
logical research) software (version 5.2.2, PRIMER-E
Ltd., Roborough, Plymouth, UK).
Results
Composition of rockpool fish assemblages
A total of 3658 fish representing 38 species and 19
families was caught in 176 samples from 32 rockpools at
Bass Point between 7 September 1999 and 22 September
2000 (Table 1), corresponding to densities of 0.5 and 19
species/m3 (mean 4.4 [±2.9] /m3) and 0.5 and 80 fish/m3
(mean 15.6 | ±14.6] /m3), respectively. The most numeri-
cally abundant taxa were permanent rockpool residents
representing the families Gobiidae iBathygobius cocosen-
sis), Tripterygiidae iEnneapterygius rufopileus), Clinidae
iHeteroclinus whiteleggi and H. fasciatus), Blenniidae
(Pa?-ablenrjius intermedins), and Gobiesocidae {Aspasmo-
gaster costatus), although the temporary resident Girella
elevata was the third most abundant species. The ten
most numerically abundant species represented 92% of
the catch (Table 1). Three species, G. elevata, Scorpis
lineolatus, and Myxus elongatus, represented by 504
fish were considered to be of economic significance. All
economically important fishes were caught as juveniles
in the rockpools and 89% of the fish measured less than
100 mm FL.
Numbers of species and individuals
For the short-term studies, the mean number of species
differed significantly between sampling intervals and
sites (RM-ANOVA, Table 2). With respect to the site
factor, there were significantly more species caught at
BB than at the other three sites and the latter three
sites did not differ from each other (SNK test). Only
the "1-week" samples accounted for significantly fewer
species than the initial samples (Fig. 2). However, the
mean number of species caught in the "1-month" and
"3-month" samples did not differ significantly from the
initial samples at all sites (Fig. 2).
The mean number of individuals differed significantly
between sampling intervals and sites, although there
was also a significant time x site interaction (RM-ANO-
VA, Table 2). A close investigation of the significant
interval xsite interaction, with primary interest in the
interval factor, revealed that the number of individuals
in the initial samples did not differ significantly from
samples taken after three months at the exposed sites
(MB and TC), but they did differ significantly at shel-
tered locations (GL and BB) (Fig. 2). It appeared that the
Number of species
£ 50
-5 30 _
I 10
Number of individuals
;ni1^inW
GL
Site
Figure 2
Mean i±SE) numbers of species and individuals (m~3)
caught in rockpools at Bass Point, New South Wales
between 7 September 1999 and 17 September 2000
during the short-term recolonization studies (combined
for spring and autumn) between sampling intervals
separated by 1 week, 1 month, and 3 months. Key to
sites: Maloney's Bay (MB). The Chair (TC I, Gravel Loader
(GL), Beaky Bay <BBi.
Loader and Beaky Bay sites initially supported unusu-
ally high numbers of individuals and these high numbers
may have accounted for significantly fewer individuals
caught in the subsequent samples (Fig. 2).
For the long-term study, the number of individuals
significantly differed among sampling times but did
not for number of species I RM-ANOVA, Table 3). The
significant difference in the mean number of individuals
was due to fewer individuals caught in the "12-month"
samples when fish numbers were pooled for all sites
(SNK test, Fig. 3).
Variation in abundance of major recolonizing species
The rank abundances of the numerically dominant
species were consistent for B. cocosensis and E. rufopi-
leus across all sampling intervals for all studies, even
though their relative abundances varied considerably
(Table 4). In contrast, the ranks of the least common
of the six species, namely H. whiteleggi, P. intermedius.
638
Fishery Bulletin 102(4)
Table 1
Numbers of fish for each species
caught from rockpools
at four
sites at Bass Point
NSW,
during sho
rt-term
(spring and
autumn) and long-term recolonization studies conducted between
7 September 1999
and 22
September
2000. *
= species of
commercial or recreational significance lor bothi.
Family and scientific name
Spring s
-udy
Autumn study
Long-term study
Total
Muraenidae
Gymnothorax prasinus
41
13
16
70
Gymnothorax cribroris
1
—
—
1
Plotosidae
Cnidoglanis macrocephalus
1
—
—
1
Gobiesocidae
Alabes dorsalis
—
2
2
Aspasmogaster costatus
134
41
65
240
Aspasmogaster liorhyncha
5
20
4
29
Syngnathidae
Urocampus carinirostris
1
—
—
1
Scorpaenidae
Scorpaena cardinalis
1
—
—
1
Serranidae
Acanthistius ocellatus
33
35
16
84
Epinephelus daemelii
—
2
—
2
Plesiopidae
Track inops taeniatus
1
—
—
1
Girellidae
Girella elevata*
210
93
74
377
Scorpididae
Microcanthus strigatus
1
—
—
1
Scorpis lineolatus*
94
10
16
120
Pomacentridae
Abudefduf vaigiensis
1
—
—
1
Parma microlepis
—
1
—
1
Chironemidae
Chironemus marmoratus
30
11
10
51
Mugilidae
Myxus elongatus
3
4
—
7
Labridae
Halichoeres nebulosus
—
1
—
1
Notolabrus gymnogenis
—
1
—
1
Blennidae
Parablennius intermedins
102
78
47
227
htiblcnnius melvagris
8
in
4
22
Tripterygiidae
Lepidoblennius haplodactylus
22
26
22
70
Norfolkia clarkei
7
4
3
14
Enneapterygius rufopileus
354
188
157
699
( 'linidae
Heteroclinus fascial us
59
48
38
145
Heteroclinus nasutus
1
—
—
1
Heteroclinus heptaeolus
24
—
1
25
Heteroclinus johnstoni
—
2
—
2
Heteroclinus whiteleggi
138
66
39
243
Ophiclinus gracilis
15
16
6
37
continued
Griffiths et al.: Fish recolonization in temperate Australian rockpools
639
Table 1
(continued)
Family and scientific name
Spring s
tudy
Aut
umn study
Long-term study
Total
Gobiidae
Bathygobius cocosensis
583
293
285
1161
Callogobius depressus
6
2
7
15
Callogobius mucosus
1
—
—
1
Priolepis cincta
1
—
—
1
Gobiidae sp.
1
—
—
1
Microdesmidae
Gunnellichthys monostigma
1
—
—
1
Tetraodontidae
Torquigener pleurogramma
—
1
—
1
Totals
1880
968
810
3658
Table 2
Results of repeated-measures ANOVAs for significant
differences in numbers of species and number of individ-
uals (/m:! I caught at Bass Point during two short-term
recolonization studies among sampling intervals (time)
(within-subjects factor), seasons (spring and autumn)
and sites (among-subjects factors). Both numbers of
species and individuals data were log1(1(.v+l) trans-
formed before analysis, which removed heteroscedas-
ticity in the data. Mauchly's criterion for sphericity of
variances was violated for number of species (P=0.025);
therefore the analysis was performed with Greenhouse-
Geisser-adjusted degrees of freedom. Mean squares
(MS) and significance levels are shown and significant
results are given in boldface. * = P<0.05; ** = P<0.01;
*** = P<0.001.
Source
Number of
species
df MS
Number of
fish
df MS
Among subjects
Season tSe)
Site(S)
SxSe
Residual
Within subjects
TimeiT)
TxS
TxSe
TxSxSe
Residual
1
3
3
24
2.16
6.47
2.16
6.47
51.75
Mauchlv's criterion W
14.94
46.80*
3.66
9.38
18.03**
2.93
2.54
1.89
1.41
0.569*
1 1292.24
3 2782.52**
3 63.53
24 370.27
3
9
3
9
72
825.70**
247.99
94.86
137.84
79.71
0.625
and A. costatus, varied considerably among sampling
intervals for each study. This result probably reflects
their generally low abundances, because differences in
Table 3
Results of repeated-measures ANOVAs for significant
differences in numbers of species and number of indi-
viduals (/m3l caught at Bass Point during the long-term
recolonization study among sampling intervals (within-
subjects factor) and sites (among-subjects factors). Both
numbers of species and individuals data were log10(.v+l)
transformed before analysis, which removed heterosce-
dasticity in the data. Mean squares ( MS ) and significance
levels are shown and significant results are given in bold.
** = P<0.01.
Number of
species
Source
df
MS
Number of
individuals
MS
Among subjects
Site(S) 3 86.93 176.18
Residual 12 27.49 169.67
Within subjects
TimeiT) 2 3.26 451.38**
TxS 6 4.44 111.82
Residual 24 2.84 55.45
Mauchly's criterion W 0.622 0.705
ranks can be a result of a few incidences of low indi-
vidual counts.
The mean number of the six most abundant recolo-
nizing species showed considerable variability in space
and time. For the short-term study, densities of these
species differed significantly among sites and among
time intervals or at least for higher order interactions
containing these effects (Table 5). No definitive conclu-
sions could be made regarding the effects of defaunation
on these species because short-term recolonization pat-
terns for each species were clearly variable within and
among seasons (Fig. 4). However, the mean number of
fish was generally highest in initial samples and low-
640
Fishery Bulletin 102(4)
Table 4
Ranked abundances of the
six most abundant species overall for each samp'
ing interval in
the spring, autumn, and long-term
experiments. Total numbers offish caught during each sampling
occasion from 16 rockpools
from four sites are
shown in
paren-
theses. l=initial samples;
2=samples
taken after 1 week: 3=sa
mples taken
after 1 month
4=samp
es taken
after 3 months.
Species having equally ran
ked abundances are
denoted by an "=
' sign.
Species
Spring
study
Autumr
study
Long-term study
1
2
3
4
1
2
3
4
1
2
3
Bathygobius cocosensis
1(153)
K69l
1(73)
1(59)
2(81i
1 (20)
1(58)
1(41)
1 (115i
1 (114)
1 ( 63 1
Enneapterygius rufopileus
2 1 1091
2(50)
4(33)
2(46)
1 (84)
2(12)
2(29)
3(25)
2 ( 73 i
2(43)
2(41)
Girella elevata
3(461
3(36)
3(40)
3(38)
3(341
3 ( 10 1
3 ( 16 1
5H3)
5(5)
6(3)
4( 12i
Heteroclinus whiteleggi
6(11)
=4(7)
2(51i
5(35)
6(9) =
= 4(5)
6(7l
2(371
6(4)
-4 ' 27 i
6(8)
Parablennius intermedins
4(27)
=4(7)
6(10)
6(23)
= 4(14) =
=4(5)
4(15i
4(23)
4H4i
5(14i
3(19i
Aspasmogaster costatus
5(21i
= 4(7)
5(13)
4(36)
= 4(14)
6(3)
5(8)
6(7)
3(22)
3(34)
5(9)
est in the 1-week samples at each site for the majority
of dominant species. For the long-term study only the
mean number of B. cocosensis and E. rufopileus differed
significantly among sampling times (Table 5), and this
E 30
ro 25
Number of species
35 "I Number of individuals
Figure 3
Mean (±SE) numbers of species and individuals i m'i
caught in rockpools at Bass Point, New South Wales,
between 22 September 1999 and 11 September 2000
(pooled for all four sites) during the long-term recoloniza-
t ion study. Intervals between sampling for the long-term
study were six months.
difference was due to lower numbers being caught in
the 12-month samples (Fig. 4).
Fish assemblage structure
No clear patterns emerged in the nMDS ordination plots,
with the exception of separation of the "1 week" samples
from all other samples at BB during the autumn study
(Fig. 5). ANOSIM supported these visual interpretations
of ordination plots and revealed that fish assemblages
did not differ significantly among sampling times at any
of the four sites for the spring and long-term studies
(Table 6) because abundant species E. rufopileus, B. coco-
sensis, H. fasciatus, and P. intermedius were common in
all samples (SIMPER analysis). For the autumn study,
the results of ANOSIM complemented those of RM-
ANOVA in that significant differences among sampling
intervals were detected only at BB (Table 6). At this
site the initial samples and "1-week" samples differed
significantly in their fish assemblages, which was due
to higher numbers of G. elevata and B. cocosensis in the
initial samples (SIMPER analysis).
Length-frequency distributions
Removal of fishes from rockpools did not have any
apparent effects on the length-frequency distributions
for at least two species (B. cocosensis and E. rufopi-
leus) for which there were sufficient data to construct
length-frequency histograms. Unfortunately, the less
abundant recolonizing species, namely P. intermedius,
A. costatus, and H. whiteleggi, were caught in too few
numbers to ascertain the impacts of defaunation on
their size compositions. Rockpools were mainly recolo-
nized by subadults and adults for B. cocosensis and E.
rufopileus in all three studies (Figs. 6 and 7). However,
cohorts of small juveniles (15-30 mm) were evident in
the "3-month" samples during spring and the initial
autumn studies (February to June), which could then
be clearly identified in subsequent samples (Figs. 6
and 7).
Griffiths et al.: Fish recolonization in temperate Australian rockpools
641
Bathygobius cocosensis
Enneapterygius rulopileus
Spring
^-j*— i*-! ^r1^
Long-term
Site
I
I
i
I
Girella elevata
Spring
I
Hsf^Ft fj
ftA
I
ff^M
\
5
4
3
2-
1 -
Long-term
[fitt
I
If
MB
I
"Y~
- T-
BB
[~J Initial
H 1 week
!\] 1 month
H 3 months
7J Initial
PI 6 months
ffl 12 months
Figure 4
Mean l±SEl numbers of fish (/m3) for the six most abundant species caught from rockpools at four sites
(MB=Maloney's Bay, TC=The Chair, GL = Gravel Loader, BB = Beaky Bay) during short-term (spring and autumn)
(four sampling events) and long-term (three sampling events) recolonization studies undertaken between 7
September 1999 and 22 September 2000.
Table 5
Results of repeated-measures ANOVAs for significant differences in numbers of individuals (/m3 ) representing the six most abun-
dant species caught at Bass Point during the short-term recolonization studies among sampling intervals (within-subjects factor)
and sites and seasons lamong-subjects factors). Data were log1(1(.v+l) transformed before analysis to remove heteroscedasticity in
the data. Mauchly's criterion for sphericity of variances was violated (P<0.001) for species denoted by ''; therefore analysis was
performed using Greenhouse-Geisser-adjusted degrees of freedom. Greenhouse-Geisser degrees of freedom used for within-sub-
jects factors where Mauchly's criterion for sphericity of variances was violated lP<0.001): Time (Ti= 1.55; SexT = 1.55; SxT =
4.64; SexSxT = 4.64; Residual = 34.14. Mean squares and significance levels are shown and significant results are given in bold.
Degrees of freedom are shown in parentheses. * = P<0.05; ** = P<0.01; *** = P<0.001.
Among-subjects factors
Within-subjects factors
Season {Se)
Site(S)
SexS
Residual
Time (T)
SexT
SxT
SexSxT
Residual
Species
(li
(3)
(3)
(24)
(3)
(3)
(91
(9)
(72)
Bathygobius cocosensis0
5.20
24.50***
3.62
2.18
43.99***
2.21
10.68**
3.22
1.70
Enneapterygius rufopileusG
0.66
4.38***
0.01
0.17
0.70***
0.05
0.08*
0.07*
0.04
Girella elevata
0.22
0.49
0.03
0.28
0.12**
0.07
0.05*
0.07**
0.03
Heteroclinus whiteleggi0
12.09
20.77*
1.65
4.90
18.99***
6.61*
4.31*
4.22
1.72
Parablennius intermedius
0.00
4.85*
0.20
1.20
7.88**
0.20
1.92
0.29
1.07
Aspasmogaster costatus
0.37
0.54**
0.15
0.10
0.11*
0.09
0.03
0.07*
0.03
Discussion
This study has shown that fish assemblages can quickly
return to preperturbation levels after significant distur-
bance. This resilience appears to be driven mainly by
postsettlement movements of fishes, although recruit-
ment may periodically play a significant role in popula-
tion replenishment. Not only does this provide an insight
into the ecology of rockpool fish assemblages, but this
information may also provide a basis for future sampling
protocols where the confounding effects of sampling may
be minimized.
642
Fishery Bulletin 102(4)
Parablennius intermedius
Aspasmogaster costalus
Spring -r
2_
Long-term
;JkjL
J-Jt
i
j
ft
TC
Site
Figure 4 (continued)
Heteroclinus whiteleggi
B
Maloney's Bay
o
O A
■
. ° A
■ o
o
A
Stress = 0.19
Maloney's Bay
° o
Stress = 0 in
Maloney's Bay
■'J
■ ♦
The Chair
v>
o
■'
o
A
Slits, = n l J
The Chair
A
A
■
♦ *
♦
Stress = 0 1 l
Gravel Loader
■
A o o*8
A
A
Sires,
A
= U.I6
Gravel Loader
O
■
»CAO
° 4
o o
Stress =
i 15
Gravel Loader
■
* *
o
O
■
Stress =
0.03
Beaky Bay
° ' «"'»o
Beaky Bay
Beaky Bay
♦ A*
Short-term study:
■ Initial
o 1 week
o 1 month
A 3 months
Long-term study:
■ Initial
« 6 months
A 12 months
Figure 5
Nonmetrie multidimensional scaling (MDSl plots for comparison of fish assemblages from four sites at Bass Point
in respect to initial samples and those taken after 1 week, 1 month, and 3 months during (A) spring and iBi
autumn short- term studies, and after 6 months and 12 months during (C) the long-term study. Each coordinate
represents a single mckpool sample. Stress values are shown.
Griffiths et al.: Fish recolonization in temperate Australian rockpools
643
f$ Autumn
Initial n=81
C Long-term
Initial 1=115
0 10 20 30 40 50 60 70 80
0 10 20 30 40 50 60 70 80
Total length (mm)
0 10 20 30 40 50 60 70 80
Figure 6
Length-frequency distributions (in 2-mm intervals) for Bathygobius cocosensis caught
in the initial samples and after 1 week, 1 month, and 3 months later in the short-
term study and caught in the initial sampling and 6 months and 12 months later
in the long-term study. Samples were pooled for all sites during the (Al spring and
(Bl autumn short-term recolonization studies and for all sites during (C) the long-
term recolonization study. Studies were conducted between 7 September 1999 and
22 September 2000. Samples sizes are shown.
Results of ANOSIM testing
during the spring, autumn.
Table 6
for differences in fish assemblage structure among sampling intervals at four sites at Bass Point
and long-term recolonization studies. Significant results are shown in bold.
Site
Spr
ng
Autumn
Long
term
R
P value
R P value
R
P value
Maloney's Bay
The Chair
Gravel Loader
Beaky Bay
0.002
0.185
0.083
0.025
0.474
0.057
0.165
0.383
0.029 0.393
0.014 0.422
0.027 0.389
0.726 0.000
-0.101
0.063
0.190
0.044
0.752
0.284
0.051
0.348
For rockpool fish assemblages in southeastern Aus-
tralia, a period of one week appears insufficient for
recolonization of all species if fish are removed during
sampling, whereas intervals of one to three months
appear sufficient for rockpool fish assemblages at most
Bass Point locations to recolonize to preperturbation
levels. It is possible that recolonization times may be
decreased if all fish are returned to rockpools immedi-
ately after sampling. However, this should not provide
a foundation for subsequent studies with other defauna-
tion methods, such as anesthetics or ichthyocides. The
possible residual effects of these other sampling meth-
ods, such as the mortality of mobile and sessile inver-
tebrates or the residues from chemical anesthetics and
ichthyocides are possible factors that may complicate
fish recolonization patterns (see Lockett, 1998) and
certainly require additional investigation. Nonethe-
less, in recolonization studies with chemical sampling
methods similar recolonization times as those of the
present study were found. For example, recolonization
of rockpools defaunated by ichthyocides was shown to be
complete within 1 month (Grossman, 1982; Prochazka,
1996) and 3 months (Beckley, 1985a; Willis and Rob-
erts, 1996; Polivka and Chotkowski, 1998).
Spatial variability in fish recolonization patterns
was not definitive with regard to species composition
644
Fishery Bulletin 102(4)
Spring
Autumn
/~> Long-term
Initial n=73
i — i i F1 i — I
0 10 20 30 40 50 60
Total length (mm)
Figure 7
Length-frequency distributions (in 2-mm intervals) for Enneapterygius rufopileus
caught in the initial samples and after 1 week, 1 month, and 3 months later in the
short-term study and caught in the initial sampling and 6 months and 12 months
later in the long-term study. Samples were pooled for all sites during the (A) spring
and (B) autumn short-term recolonization studies and for all sites during (C) the
long-term recolonization study. Studies were conducted between 7 September 1999
and 22 September 2000. Samples sizes are shown.
because samples were generally widely dispersed in
nMDS ordination plots. The relatively low stress values
(<0.2) indicate that high variability in fish assemblages
at the level of individual rockpools is probably respon-
sible for the patterns observed. However, some spatial
variability in fish recolonization patterns was evident
(Fig. 2) and appeared to be dependent to some extent
on exposure of sites to predominant swell. There is
evidence to suggest that wave exposure can affect the
distribution of intertidal fishes (Gibson, 1972; Ibanez et
al., 1989), although there is apparently no study that
has investigated this effect in relation to fish recoloni-
zation in rockpools. In the present study, recolonization
appeared more rapid at wave-exposed sites (MB and
TC) compared to more sheltered sites. This may have
been the result of the close distance between rockpools
at exposed sites (within meters of each other), whereas
at both sheltered sites, rockpools were significantly
farther apart. Consequently, defaunated rockpools at
exposed sites may recolonize more quickly if the major
recolonizers are derived from neighboring rockpools
as has been documented elsewhere (Beckley, 1985a;
Polivka and Chotkowski, 1998).
Fish recolonization patterns were not influenced by
the time of year that rockpools were defaunated in
either short-term or long-term studies. The numbers
of species and individuals consistently returned to pre"
perturbation levels within a few weeks, but this return
to previous levels may partially be a consequence of
the relatively small number of species that are nor-
mally found in rockpools at any given time. In such
situations a significant differences could only occur if
large-scale changes in abundances were recorded. The
lack of temporal variation in recolonization rates was
surprising because recolonization was expected to be
more rapid during summer, when the larvae of residents
and warm water transients are expected to be avail-
able for settlement (Beckley, 1985a; Willis and Roberts,
1996). Recruitment was not the major mechanism driv-
ing fish recolonization in the present study because the
majority of recolonizers were subadults and adults that
would have relocated from nearby rockpools. Although
many of the fish captured in each pool were tagged,
the vast majority offish caught in the same rockpool in
subsequent sampling events were not tagged. Griffiths
(2003b) showed that the common recolonizing species in
the present study moved between a few rockpools within
a limited home range. Therefore, postsettlement fishes
from surrounding rockpools were probably moving into
the study rockpools between each sampling event.
The movement of postsettlement fishes from adjacent
rockpools also appears to control the resilience of rock-
Griffiths et al.: Fish recolonization in temperate Australian rockpools
. 645
pool fish assemblages. Therefore, the composition of spe-
cies in newly recolonized rockpools is probably depen-
dent upon the relative abundances of species in nearby
rockpools. Species having the highest local abundances,
such as B. cocosensis and E. rufopileus, are therefore
more likely to be the primary recolonizers because va-
cant habitats have a higher probability of being located
by these species during high-tide excursions throughout
the intertidal zone (also see Polivka and Chotkowski,
1998). These species are also versatile and can exploit
a range of microhabitats and, as a result, can occupy
almost any rockpool within the intertidal zone (Griffiths
et al., 2003). This is particularly true for B. cocosensis.
In contrast, less abundant species such as H. whiteleggi
often occupy more specific, and perhaps less abundant,
microhabitats such as algal cover (see Marsh et al..
1978; Bennett and Griffiths, 1984) that may require
longer periods to locate than more abundant habitats,
such as cobble-covered substratum.
Processes regulating fish assemblages
The structure of multispecies assemblages can be
regarded as being regulated by either deterministic or
stochastic processes (see Grossman, 1982). Assemblages
regulated by deterministic processes generally occur in
environments where conditions are constant or fluctuate
consistently over time. The structure of these assem-
blages is generally predictable. This can be maintained
through a number of factors including partitioning of
resources in finite supply (Schoener, 1974; Behrents,
1987) and interspecific competition, which prevents any
single species being competitively dominant (Buss and
Jackson, 1979).
In contrast, assemblages regulated by stochastic pro-
cesses generally exist in unpredictable environments.
Here, the resources are available on a random or pe-
riodic basis, which prevents superior competitors from
dominating the assemblage (Sale, 1977, 1978). The suc-
cess of particular species can be compared to winning
a "lottery" for living space (Sale, 1977, 1978, 1982).
Consequently, stochastically regulated assemblages are
generally species rich (Sale, 1977).
Rockpool fish assemblages are often persistent for
lengthy periods, even after catastrophic natural dis-
turbances, such as hurricanes (Moring, 1996), and con-
tinual experimental eliminations (Grossman, 1982;
Collette, 1986). For example, Collette (1986) found two
species — Pholis gunnellus and Tautogolabrus adsper-
sus — to be dominant over 19 years of study in two New
England rockpools, whereas the rank of dominant spe-
cies in the rockpools of Barbados showed no evidence
of change over six years (Mahon and Mahon. 1994).
Similar stability and persistence were evident in the
present study, where B. cocosensis, E. rufopileus and
G. elevata were consistently the highest ranked species
in each collection for all three studies, regardless of
the period between sampling. This finding may indi-
cate that deterministic processes probably regulate the
Bass Point fish assemblage. If this is the case, it may
seem ironic because the intertidal zone is subjected to
a high frequency of stochastic events. It would be easy
to assume that such events could eliminate fishes from
rockpools and thus leave microhabitats for other species
to exploit. This kind of process has been documented for
some sessile intertidal invertebrate assemblages that
rely on the availability of vacant substrata for success-
ful recruitment of larvae (see examples by Raffaelli
and Hawkins. 1996). However, the locomotory capabili-
ties and morphological and physiological adaptations of
resident intertidal fishes allow them to cope with such
disturbances by being able to cope temporarily with ad-
verse conditions (Martin. 1995). As a result, the abun-
dance of resident species may be little affected under
normal disturbance regimes.
Conclusions
The results of this study have significantly increased an
understanding of the patterns of recolonization of rock-
pools by fishes and some of the processes that underpin
these patterns. Such an understanding of recoloniza-
tion processes may improve our ability to predict the
consequences of significant natural and anthropogenic
disturbances on not only the fish assemblages but also
on other intertidal community assemblages that may be
maintained by the presence offish (see Coull and Wells,
1983; Connell and Anderson, 1999).
On a more technical note, the recolonization rates
observed in the present study may provide insight for
other researchers aiming to stud}' natural temporal
variation of rockpool fish assemblages by minimizing
the possibility of confounding effects of sampling. This
may be particularly important for long-term monitoring
programs, such as for marine protected areas (MPAs).
that may require detection of changes in community
structure over time. Finding sufficient numbers of simi-
lar-size pools at a single location for monitoring can be
difficult: therefore repeated visits to the same rockpools
may often be required. For southeastern Australian
rockpools. we feel that a period of one to three months
is required before resampling the same rockpools with
the methods employed in this study. Although fish were
not returned to rockpools immediately after sampling
in the present study, we feel that this practice may
significantly increase recolonization rates. However,
the results of the present study should not provide a
foundation for studies using other defaunation methods,
such as anesthetics or ichthvocides. because other fac-
tors, such as chemical residues remaining in rockpools,
may complicate fish recolonization patterns. Further
investigation into these other factors will be necessary
in the future.
Acknowledgments
We sincerely thank Jade Butler and Alan Griffiths for
help with fieldwork. This paper is partly based upon
646
Fishery Bulletin 102(4)
research included in a Ph.D. by S. P. Griffiths funded by
an Australian Postgraduate Award. Additional funding
was granted by the Institute for Conservation Biology,
University of Wollongong, Shellharbour City Council,
The Ecology Lab. Pty. Ltd., and Ocean Beach Hotel
Fishing Club. S. P. Griffiths would like to thank CSIRO
Marine Research for support during the preparation of
this article.
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648
Abstract — We have studied the repro-
ductive biology of the goldlined sea-
bream (Rhabdosargus sarba) in the
lower Swan River Estuary in Western
Australia, focusing particularly on
elucidating the factors influencing
the duration, timing, and frequency
of spawning and on determining
potential annual fecundity. Our
results demonstrate that 1) Rhab-
dosargus sarba has indeterminate
fecundity, 2) oocyte hydration com-
mences soon after dusk (ca. 18:30 hi
and is complete by ca. 01:30-04:30 h
and 3) fish with ovaries containing
migratory nucleus oocytes, hyd rated
oocytes, or postovulatory follicles were
caught between July and November.
However, in July and August, their
prevalence was low, whereas that of
fish with ovaries containing substan-
tial numbers of atretic yolk granule
oocytes was high. Thus, spawning
activity did not start to peak until
September (early spring), when salini-
ties were rising markedly from their
winter minima. The prevalence of
spawning was positively correlated
with tidal height and was greatest
on days when the tide changed from
flood to ebb at ca. 06:00 h. i.e., just
after spawning had ceased. Because
our estimate of the average daily
prevalence of spawning by females
during the spawning season (July
to November) was 36.5%, individual
females were estimated to spawn,
on average, at intervals of about 2.7
days and thus about 45 times during
that period. Therefore, because female
R. sarba with total lengths of 180,
220, and 260 mm were estimated to
have batch fecundities of about 4500,
7700, and 12,400 eggs, respectively,
they had potential annual fecundities
of about 204,300, 346,100 and 557,500
eggs, respectively. Because spawn-
ing occurs just prior to strong ebb
tides, the eggs of/?, sarba are likely
to be transported out of the estuary
into coastal waters where salini-
ties remain at ca. 359«. Such down-
stream transport would account for
the fact that, although R. sarba exhib-
its substantial spawning activity in
the lower Swan River Estuary, few
of its early juveniles are recruited
into the nearshore shallow waters of
this estuary.
Manuscript submitted 9 June 2003
to the Scientific Editor's Office.
Manuscript approved for publication
28 April 2004 by the Scientific Editor.
Fish. Bull. 102:648-660(2004).
Factors influencing the timing and frequency of
spawning and fecundity of the goldlined seabream
(Rhabdosargus sarba) (Sparidae)
in the lower reaches of an estuary
S. Alexander Hesp
Ian C. Potter
Centre for Fish and Fisheries Research
School of Biological Sciences and Biotechnology
Murdoch University
South Street
Murdoch, Western Australia 6150, Australia
E-mail address (for I C Potter, contact author): i.pottera'murdoch edu.au
Sonja R. M. Schubert
Ernst-Moritz Arndt Universitaet, Hansestadt Greifswald
F.-L.-Jahn StraBe 15a
17487 Greifswald, Germany
The goldlined seabream {Rhabdosar-
gus sarba) is an important recreational
and commercial fish species in numer-
ous regions throughout the Indo-west
Pacific (van der Elst, 1988; El-Agamy,
1989; Kuiter, 1993). Although this
species is a protandrous hermaphro-
dite in certain regions, e.g., the waters
of Hong Kong and South Africa (Yeung
and Chan, 1987; Garratt, 1993). it is a
rudimentary hermaphrodite in a range
of environments in Western Australia
(Hesp and Potter, 2003). Rudimentary
hermaphrodites are those species in
which the juveniles possess gonads
consisting of both immature testicular
and ovarian tissues that, in adults,
develop permanently into either func-
tional testes with rudimentary ovar-
ian tissue or functional ovaries with
rudimentary testicular tissue (Buxton
and Garratt, 1990). In Western Aus-
tralia, R. sarba attains similar maxi-
mum lengths, i.e., 346-370 mm, in
temperate marine coastal waters and
the lower reaches of the Swan River
Estuary on the lower west coast of
Australia and in a large subtropical
embayment ca. 800 km farther north
(Hesp et al., 2004). However, the max-
imum age recorded for this species in
the estuary. 7 years, was far less than
that for the other two environments:
temperate marine coastal waters (11
years) and a large subtropical embay-
ment (13 years) (Hesp et al., 2004).
Although R. sarba is typically re-
garded as a marine species that fre-
quently uses estuaries as a nursery
area (e.g., Wallace, 1975; Potter and
Hyndes, 1999; Smith and Suthers,
2000), it spawns in the lower Swan
River Estuary as well as in coastal
waters outside this estuary (Hesp and
Potter, 2003). However, this sparid
attains maturity later in the estuary
than in those nearby coastal marine
waters. If this indication that the on-
set of spawning for R. sarba in the
Swan River Estuary is related to the
attainment of higher salinities in the
spring, it would parallel the situation
recorded for the spotted seatrout (Cy-
noscion nebulosus) in the estuaries of
the Gulf of Mexico where this species
completes its entire life cycle ( Brown-
Peterson et al., 2002).
Despite the importance and wide-
spread occurrence of R. sarba. and
the great value of fecundity data for
stock assessments (Hunter et al.,
1992: Nichol and Acuna, 2001), on-
ly one attempt has apparently been
made to estimate the annual fecun-
dity of wild populations of this sparid
(El-Agamy, 1989). Although El-Aga-
my (1989) recognized that R. sarba
is a "fractional" spawner and has a
Hesp et al.: Timing and frequency of spawning and fecundity of Rhabdosargus sarba
649
protracted spawning season, he recorded the fecundity
of this species as the number of larger eggs (diameter
>180 fjm) estimated to be present in the ovaries of
mature females just prior to the commencement of the
spawning period. Thus, the very strong possibility that
some eggs with diameters <180 /jm would have been
destined to have become fully mature and released at
some stage during the protracted spawning season, i.e.,
the species has indeterminate fecundity, was not taken
into account.
In species with indeterminate fecundity, the distri-
bution of oocyte diameters essentially forms a contin-
uum, reflecting the continuous maturation of oocytes
throughout the spawning season and thus the progres-
sion through to maturity of some of the small and pre-
vitellogenic oocytes that were present at the beginning
of the spawning period. Consequently, counts of the
standing stock of larger oocytes found just prior to the
onset of spawning will result in an underestimate of the
potential annual fecundity of such species (Hunter et al.,
1985. 1992; Lisovenko and Andrianov, 1991). Estimation
of the annual fecundity of species with indeterminate
fecundity thus requires a combination of data on batch
fecundity and spawning frequency (Hunter et al.. 19851.
Batch fecundity, i.e., the number of oocytes released
during a single spawning event, can be estimated by
counting the number of hydrated oocytes present in
ovaries immediately prior to that spawning (Hunter
et al., 1985). The frequency with which a fish spawns
during the spawning period can be determined from the
frequency of mature female fish possessing ovaries with
either hydrated oocytes or postovulatory follicles (POFs)
of a known age (Hunter and Macewicz, 1985).
The spawning of many marine species of teleosts and
invertebrates is correlated with lunar periodicity and the
associated tidal cycles (e.g., Schwassmann, 1971; Taylor.
1984; Greeley et al., 1986; Hoque et al., 1999), with the
spawning of such fish species typically peaking around
the full or new moon (or both) (e.g., Johannes. 1978;
Taylor and DiMichele. 1980; Greeley et al., 1986). Many
fish and invertebrates with pelagic eggs spawn on high
or ebb tides that enable eggs and the subsequent larval
stages to be transported away from spawning areas,
in which planktivorous predators are concentrated. This
process thus reduces the likelihood of those early life
cycle stages being subjected to predation (Taylor, 1984;
Johnson et al., 1990; Morgan, 1990). The fact that there
is very little recruitment of the early 0+ individuals of
R. sarba into the lower Swan River Estuary, where ex-
tensive spawning occurs, indicates that tides transport
the eggs of this species from spawning areas in the
estuary into coastal marine waters (Hesp and Potter,
2003; Hesp et al., 2004).
This investigation, which involved a detailed study of
the females of R. sarba in the lower Swan River Estuary,
had the following aims: 1) to test the hypothesis that
R. sarba has indeterminate fecundity; 2) to establish
the period during the day when the oocytes of R. sarba
become hydrated and when ovulation and spawning
occur; 3) to establish whether R. sarba spawns mainly
when salinities are high and thus approach those of the
marine waters in which this species typically breeds
and whether spawning is correlated with the strength
and type (ebb vs flood) of tide in the lower reaches of
the Swan River Estuary; 4) to estimate the average
frequency of spawning for R. sarba during the spawning
period; 5) and to determine the relationship between
batch fecundity and fish length, and to use this rela-
tionship, in combination with the average spawning
frequency, to calculate the potential annual fecundity
of R. sarba of different sizes.
Materials and methods
Tide, lunar phase, and salinity
The maximum daily tidal heights at the mouth of the
Swan River Estuary were calculated by using the tidal
prediction data of the Coastal Data Centre at the Depart-
ment of Planning and Infrastructure, Government of
Western Australia (http://www.coastaldata. transport.
wa.gov.au). The maximum tidal range at the mouth of
the Swan River Estuary is small, i.e., <0.8 m, and tides
can be diurnal or semidiurnal, depending on the time
of year (Spencer, 1956). Salinity was measured on each
sampling occasion by using a Yellow Springs Instru-
ments salinity meter (YSI model number 30, Yellow
Springs Instrument Co., Inc., Yellow Springs. OH).
Sampling
During 2001 and 2002, female Rhabdosargus sarba
were collected by seine netting in nearshore shallow
waters at distances of ca. 2.5 to 5 km from the mouth
of the Swan River Estuary, and by rod and line fishing
in water depths of 10-12 m at a distance of ca. 150 m
from the shore (for details of sampling region and seine
net, see Hesp and Potter, 2003). Sampling was under-
taken at least once weekly between July and November,
the period when R. sarba reach maturity in the lower
Swan River Estuary (Hesp and Potter, 2003). It was
restricted to the hours between dusk (ca. 18:00 h) and
dawn (ca 06:00 h) because extensive seine netting and
angling during the day in our earlier study failed to yield
any R. sarba. The failure to capture R. sarba by these
methods during daylight reflected the offshore movement
of this species from the shallows prior to dawn and a
far stronger targeting of bait by the large numbers of
the banded toadfish {Torquigener pleurogramma) that
feed in the offshore waters of the lower estuary during
the day. Because the lower reaches of the Swan River
Estuary act as a shipping harbor, alternative sampling
methods, such as gill netting and spearing, could not
be used to catch R. sarba during the day. The data for
2000 and 2001 were augmented by those derived from
fish collected from the same location by using the same
methods in 1998 and 1999 (Hesp and Potter, 2003). In
total, the results of the present study are based on an
examination of over 2000 R. sarba, of which 510 were
650
Fishery Bulletin 102(4)
Table 1
Characteristics of each macroscopic stage in the development of the ovaries of Rhabdosargus sarba, and its corresponding histo-
logical characteristics. Adapted from Laevastu (19651. Terminology for oocyte stages follows Wallace and Selman (1989).
Stage
Macroscopic characteristics
Histological characteristics
I Virgin
Ovary is very small and strand-like.
II Immature
and resting
Small and transparent. Yellowish-orange in
color. Oocytes not visible through ovarian
wall.
Ill Developing Slightly larger than stage II. Reddish color.
Oocytes visible through ovarian wall.
Rhabdosargus sarba is a rudimentary hermaphrodite, sensu
Hesp and Potter (2003). Thus, the gonads of small juveniles
contain only connective tissue. Larger juveniles possess
gonads (ovotestes) in which each ovarian lobe consists of
an immature ovarian and testicular zone, separated by
connective tissue. The ovotestes develop later into gonads
containing almost entirely ovarian tissue (functional ovaries)
or, in the case of males, gonads containing almost entirely
testicular tissue (functional testes).
Ovigerous lamellae highly organized. Chromatin nucleolar
and perinucleolar oocytes dominate the complement of
oocytes. Oogonia sometimes present. Chromatin nucleolar
oocytes present in all subsequent ovarian stages.
Chromatin nucleolar, perinucleolar and cortical alveolar
oocytes present.
Cortical alveolar and yolk granule oocytes abundant.
IV Maturing Larger than stage III. Reddish-orange in
color. Yolk granule oocytes visible through
ovarian wall.
V Mature Larger than stage IV occupying half to two Yolk granule oocytes predominant.
thirds of body cavity. Extensive capillaries
visible in ovarian wall.
VI Spawning Hydrated oocytes visible through ovarian Migratory nucleus oocytes, hydrated oocytes, or postovula-
wall. Note that fish with ovaries in "spawn- tory follicles present,
ing condition" can only be detected macro-
scopically when caught during the hydration
period.
VII Spent
Smaller than V and VI and flaccid. Some yolk Some remnant yolk granule oocytes present, all or almost al
granule oocytes visible through ovarian wall. of which are typically undergoing atresia.
VIII Spent and Small and dark red.
recovering
Extensive scar tissue present. Ovarian lamellae becoming
reorganized. No yolk granule oocytes present.
females with stage-V (mature) or stage-VI (spawning)
ovaries (see Table 1 for definitions of these stages).
During the above sampling, R. sarba was collected
for up to 2 hours at intervals commencing at 18:30,
21:30, 00:30, and 03:30 h on 1-2 September 2001 and
for up to 2 hours at intervals commencing at 18:30 and
22:30 h on 13 September 2001. One of the ovarian lobes
of up to five fish caught during each of these above
time intervals was cut into several pieces, preserved in
10'' neutrally buffered formalin solution and used for
determining the distributions of oocyte diameters at
the above different times. The other lobe was used for
histology to determine the oocyte stages present in that
lobe, and thus, by extrapolation, also the stages of the
oocytes in the lobe that had been preserved in formalin.
The resultant comparisons were used, in conjunction
with data from other times, to elucidate the pattern of
oocyte development during hydration and the duration
of hydration and timing of ovulation.
Gonadal staging and histology of ovaries
The sex, total length (to the nearest 1 mm), and total
weight and gonad weight (to the nearest 0.01 g) of each
fish were recorded. From its macroscopic appearance,
each gonad was assigned to one of the following stages in
maturation, based on the scheme of Laevastu (1965), i.e.,
I = virgin, II = immature and resting, III = developing,
IV = maturing, V = mature, VI = spawning, VII = spent,
VIII = spent and recovering. The corresponding histolog-
ical characteristics of each macroscopic stage are shown
in Table 1. When hydrated oocytes could be seen through
the ovarian wall of a fish, a note was made as to whether
they were distributed throughout the ovary or were in
Hesp et al.: Timing and frequency of spawning and fecundity of Rhabdosargus sarba
651
the ovarian duct and thus whether or not ovulation had
commenced at the time of capture of that fish.
For all histological studies of the gonads, part of the
mid region of one of the ovarian lobes was placed in
Bouin's fixative for ca. 48 hours, dehydrated in a series
of ethanols, embedded in paraffin wax, cut into 6-um
sections, and stained with Mallory's trichrome. The ova-
ries were fixed within 1-3 hours of capture of the fish.
To test the hypothesis that R. sarba has indetermi-
nate fecundity, the diameters of 100 oocytes in histo-
logical sections of stage-VI ovaries of two fish caught
during the spawning period were measured to the near-
est 10 /jm by using an eyepiece graticule in a compound
microscope and the stage of each of those oocytes was
recorded. Measurements were restricted to oocytes in
which a nucleus was visible in their center to ensure
that the oocytes had been sectioned through their center
and that the diameters were thus measured accurately.
This approach could not be used to measure the oocyte
diameters of hydrated oocytes in histological sections
because the nucleus of these oocytes undergoes germi-
nal vesicle breakdown.
Histological sections of numerous ovaries were used
to determine the timing of the formation and degen-
eration of postovulatory follicles (POFs). An age was
assigned to the POFs found in ovaries of fish caught
at different times of the day, based on the timing of
ovulation and the degree to which those POFs had
degenerated (Hunter and Goldberg, 1980; Hunter and
Macewicz, 1985). Histological sections were also used
to determine the relative abundance of the different
stages of atresia in ovaries at different times during
the spawning period.
The jars containing the ovarian lobes that had been
preserved in formalin at the different time intervals on
1. 2, and 13 September 2001 (see earlier) were shaken
until the oocytes of each ovary had become evenly sus-
pended in the solution. The resultant solution from
each ovary was then passed through a 125-/jm sieve
to remove the smallest oocytes, and we were able thus
to focus our study more specifically on the vitellogenic
oocytes. Comparisons of the appearance of the larger
oocytes under a dissecting microscope with those of the
different oocyte stages in histological sections of the
other ovarian lobe of the same fish were used to allocate
the oocytes observed under the dissecting microscope
to a specific stage in oocyte development. Each oocyte
in a representative subsample of 100 oocytes from each
formalin-preserved ovarian lobe was measured under a
dissecting microscope with an eyepiece graticule. This
approach enabled the diameters of hydrated oocytes to
be measured accurately, which was not possible with
histological sections (see earlier).
Categorization of stages in atresia, fecundity estimates,
and spawning frequency
On the basis of their histological characteristics, atretic
oocytes were allocated to either the a or /3 stages, by
using the criteria of Hunter and Macewicz (1985). Mature
ovaries were categorized according to the proportions
of their a and /3 atretic oocytes (Hunter and Macewicz,
1985). Thus, atretic state 0 = ovaries with yolked oocytes
but no a atretic oocytes; atretic state 1 = ovaries in which
less than 509c of the yolked oocytes are in the a stage
of atresia; atretic state 2 = ovaries in which less than
509c of the yolked oocytes are a atretic and atretic state
3 = ovaries which contain no yolked oocytes but do pos-
sess |3 atretic oocytes. During the present study, atretic
state 1 ovaries were further divided into three categories
on the basis of the percentage of a atretic yolk granule
oocytes in histological sections, namely early (<10%), mid
(10-359? I and late (36-50%) atretic state 1, an approach
similar to that adopted by Farley and Davis (1998).
The batch fecundities of 31 R. sarba were estimated
from the number of hydrated oocytes in one of the ovar-
ian lobes of fish that had been preserved in 109c neu-
trally buffered formalin. These fish were chosen because
histological examination of their other ovarian lobe dem-
onstrated that the ovaries were in atretic state 0 or early
state 1, i.e., less than 10% of their yolk granule oocytes
were atretic and newly formed POFs were not present
(Hunter et al., 1992; Nichol and Acuna, 2001). The for-
malin-preserved ovarian lobe was dried with blotting pa-
per and ca. 180-200 mg of tissue was removed from each
of its anterior, middle, and posterior regions and weighed
to the nearest 1 mg. These pieces of tissue were placed on
separate slides, covered with 309c glycerol and examined
under a dissecting microscope. The oocytes were then
teased apart and the number of hydrated oocytes record-
ed. The number of hydrated oocytes in each of the three
pieces of ovarian tissue of known weight were then used,
in conjunction with the weight of both ovarian lobes, to
estimate the total number of hydrated oocytes (=batch
fecundity) that would have been present in the pair of
ovarian lobes of each fish. The prevalence of spawning on
any given night is expressed as the percentage of female
fish with hydrated eggs (ovarian stage VD among all fe-
male fish with stage-V I mature) and stage-VI (spawning)
ovaries. These estimates were based on an examination
of samples collected between 22:00 and 01:30 h, when it
was possible to determine which female fish were going
to spawn in the ensuing few hours (see Hunter et al.,
1985, for further details of this method).
Results
Although mean monthly salinities in the lower Swan
River Estuary in late spring to early winter were close
to that of full strength sea water (359cc), they fell pre-
cipitously to a minimum of 23%c (minimum individual
value=14'?c) in August, and then rose sharply in early
to mid-spring (Fig. 1).
Staging of the ovaries and confirmation of
indeterminate fecundity
The characteristics of each macroscopic stage of the
ovaries of R. sarba and the corresponding histologi-
652
Fishery Bulletin 102(4)
40
35
30
25
20
15 L
80
60 S
40
20
J 0
Month
Figure 1
Mean monthly salinities I±1SE) at the bottom of the water column
in the lower Swan River Estuary throughout the year and the preva-
lences of atresia in mature ovaries of Rhabdosargus sarba between
July and November, which are shown as histograms, together with
the number of fish examined. Closed rectangles on the horizontal
axis refer to summer and winter months, and the open rectangles
to autumn and spring months.
cal characteristics are presented in Table 1. Because
stages V and VI could be distinguished macroscopi-
cally only during the period of oocyte hydration, the
macroscopic data for these two stages had to be com-
bined for other times. The diameters of the oocytes in
histological sections of an ovarian lobe from each of two
mature female R. sarba caught during the spawning
season — oocyte diameters that were typical of those
from mature R. sarba during this period — formed an
essentially continuous distribution (Fig. 2). This distri-
bution reflected the presence of oocytes at all stages in
development from chromatin nucleolar oocytes to yolk
granule oocytes and demonstrated that R. sarba has
indeterminate fecundity sensu Hunter et al. (1985).
Thus, the potential annual fecundity is not fixed prior
to the commencement of the spawning period and conse-
quently the potential annual fecundity of R. sarba has to
be estimated by using a combination of batch fecundity
and spawning frequency.
Period of hydration and spawning
The diameters of oocytes in ovaries of fish collected at
intervals on 1-2 September 2001 and 13 September
2001 and which had been retained on the 125-^im sieve,
produced a modal class that, for each time interval,
fell between 420 and 600 fim (Fig. 3). At ca. 18:30 h on
1 September 2001, the oocyte diameters formed a single
mode, and the vast majority of oocytes were less than
720 ;im and produced a modal class at 420-539 um
(Fig. 3). However, by ca. 21:30 h on the same evening.
the maximum diameter of the oocytes had increased
markedly and the distribution of the oocyte diameters
was beginning to become bimodal. with modal classes at
480-539 and 780-839 ^m. By 00:30 h on 2 September,
the oocyte diameter distributions had become markedly
bimodal, and the modal diameter class of the largest
oocytes at this time, and also at 03:30 h, lay between
840 and 959 ^(m (Fig. 3). The oocyte diameter frequen-
cies on 13 September were essentially the same as those
at similar times on 1 September; the distributions were
unimodal at 18:30 h and bimodal at 22:30 h (Fig. 3).
The oocyte diameters of each fish within a given time
slot on 1, 2, and 13 September exhibited essentially the
same distribution.
Histological sections showed that, at 18:30 h on
1 September 2001, most of the mature ovaries contained
migratory nucleus stage oocytes, i.e., oocytes in which
the nucleus was migrating towards the edge of the cy-
toplasm and a conspicuous lipid droplet was present in
the cytoplasm (Fig. 4A). However, it was difficult at this
time to distinguish migratory nucleus oocytes from yolk
granule oocytes under a dissecting microscope (Fig. 4B).
By 21:30 h, the yolk and lipid of the larger oocytes had
begun to coalesce and the nucleus could sometimes be
seen near the edge of the cytoplasm (Fig. 4Cl. Their
relatively larger size, translucent appearance, and one's
ability to detect their lipid droplet enabled these hydrat-
ing oocytes to be far more readily distinguished from
yolk granule oocytes under a dissecting microscope
than was the case earlier in the evening (cf. Fig. 4, B
and D). By 00:30 h. the largest oocytes had increased
Hesp et al.: Timing and frequency of spawning and fecundity of Rhabdosargus sarba
653
further in size and all of their lipid and yolk material
had coalesced (Fig. 4E). Under the dissecting micro-
scope, these hydrated oocytes were of similar appear-
ance to the corresponding oocytes at 21:30 h (Fig. 4F).
Although mature fish with ovaries containing the above
stages in oocyte hydration were frequently found in
nearshore shallow waters, the numbers of such fish in
these waters declined markedly after about 00:30 h
and none of the few fish caught there after this time
contained recently formed POFs. However, fish with
ovaries containing newly formed POFs were caught in
offshore deeper waters.
Histological examination demonstrated that, when
hydrated oocytes were present in the ovarian duct,
the ovary contained recently formed POFs, which are
formed by the thecal and granulosa layers of the oocytes
that surround the zona radiata externa (Fig. 5A). Newly
formed POFs (0-6 h old) possess a conspicuous lumen
and their granulosa cells contain prominent darkly
stained nuclei (Fig. 5B). These newly formed postovula-
tory follicles were first observed in the ovaries of females
caught at ca. 01:30 h and were present in the ovaries of
several fish caught in the ensuing four hours. In con-
trast, no newly formed POFs were found in the ovaries
of R . sarba at dusk, i.e., ca. 18:30 h. At this time, the
POFs comprised one of two morphological forms. The
first and least degenerate form was less well organized
than newly formed POFs and its nuclei were becoming
pycnotic (Fig. 5C); the second form was smaller and
highly degenerate and its nuclei had become far less
visible or undetectable (Fig. 5D). The least degenerate
of the two forms of POFs in ovaries of fish caught at ca.
22:00 and 01:00 h (Fig. 5, D and E) represents stages in
degeneracy that are intermediate between those of the
two different forms described above for the ovaries of
fish caught at 18:30 h. These POFs were thus compact
and, although some of their nuclei were still detectable,
they were markedly pycnotic.
Chromatin nucleolar oocytes
Perinucleolar oocytes
D Cortical alveolar oocytes
Yolk granule oocytes
30
20
10
■ Chromatin nucleolar oocytes
E3 Perinucleolar oocytes
fJJ Cortical alveolar oocytes
B Yolk granule oocytes
0 100 200 300 400 500
Oocyte diameter (urn)
Figure 2
Percent frequency distributions for the oocyte diameters
of different oocyte stages in histological sections of stage-
VI ovaries of two female Rhabdosargus sarba.
Influence of salinity and tides on spawning
Both a and /5 atretic oocytes were frequently observed
in the ovaries of R. sarba. The chorion (zona radiata)
of the early a atretic vitellogenic oocyte was distorted,
fragmented, and had moved inwards (Fig 6A). By the /3
atretic stage, the yolk and lipid had been resorbed and
a large proportion of the oocyte volume was occupied by
vacuoles (Fig. 6B).
Sixty-two percent and 72% of the stage-V and stage-
VI ovaries sectioned in July and August, respectively,
were at mid or late atretic state 1, i.e., 11-50% of their
yolk granule oocytes were a atretic (Fig. 1). However,
the prevalence of these mid-late state-1 ovaries declined
precipitously to 28% in September, as salinities rose
markedly, and remained at a similar level until the end
of spawning in late November.
Histological sections showed that, in July and August,
only 39r/c of the 57 pairs of ovarian lobes of R. sarba
that were macroscopically assigned as stage V and
stage VI contained migratory nucleus oocytes, hydrated
oocytes, or POFs, i.e., were at stage VI. However, in the
following two months, 76% of the 88 pairs of ovarian
lobes of R. sarba, that were macroscopically assigned
as stage V or stage VI, were shown by histology to be
at stage VI.
During September, when spawning activity was great-
est, the prevalence of spawning (PS) was positively
correlated (P<0.05) with maximum daily tidal height
(T). PS = 91.72T + 20.73 (/-2 = 0.46, number of sampling
occasions=10) (Fig. 7A).
Data for the same days as those used to provide the
points shown in Fig. 7A demonstrated that the preva-
lence of spawning (PS) is inversely correlated with the
difference in hours between the time when spawning is
believed to cease (ca. 06:00 h, see later) and the time
of high tide. PS = -8.26(T) + 78.22 (r2=0.49, number of
sampling occasions=10) (Fig. 7B). Thus, the prevalence
of these "spawning" females was greatest on those days
when the time that the tide was about to change from
flood to ebb coincided with the time when R. sarba is
considered to cease spawning.
654
Fishery Bulletin 102(4)
1 and 2 September
1 and 2 September
30 r
20
10
0
30
20
10
g- 30
lL
20
10
0
30
20
10
0 L
18:30 h
n = 5
Ql
i i i — i — i — i — i — t — i — i — i
21:30h
n = 5
tn=
00:30 h
rt = 5
hJ
i i — i — 1_
_j — i — i — i
03:30 h
n = 2
r
*<P^<&<&4PoPjP<&<&
■<? $><W
13 September
13 September
18:30 h
n = 5
Hliliri
_i i i — i — i — i — i — i
22:30 h
n=5
M
0=
\? it nr t»° or A1' <tr qP^^Tr
'.c?^
Oocyte diameter (jim)
Figure 3
Frequency distributions for the oocyte diameters in mature ovaries of
Rhabdosargus sarba caught on 1-2 and 13 September 2001. The ovaries had
been preserved in formalin and their oocytes had been passed through a
125-^m sieve. The time of commencement of each 2-hour sampling interval
is shown, n = number offish used for oocyte diameter measurements.
Batch fecundity, spawning frequency,
and potential annual fecundity
The relationship between batch fecundity iBF) and
total length iTL) shown in Figure 8, and between batch
fecundity and somatic weight (W) are described by the
following equations:
InBF = 5.00251nrL-17.557
(P<0.001; r2=0.52, n = 30),
BF = 1997e00105W
(P<0.001; r2=0.55, n=30).
The batch fecundities of R. sarba. predicted by the above
equations for fish with lengths of 180, 220. and 260 mm,
were ca. 4500, 7700. and 12,400, eggs, respectively, and
for fish with somatic weights of 100, 150, and 200 g were
ca. 5700, 9600, and 16,300 eggs, respectively. The average
daily prevalence of spawning during the spawning period
was 36.5^. Thus, during this period, individual females
spawned, on average, once every 2.7 days and therefore
about 45 times during the spawning season. The poten-
tial annual fecundities of female R. sarba with lengths
of 180, 220. and 260 mm were thus estimated to be ca.
204,300, 346,100, and 557,500 eggs, respectively.
Hesp et al.: Timing and frequency of spawning and fecundity of Rhabdosargus sarba
655
Figure 4
Histological sections of ovaries of individual Rhabdosargus sarba caught on
1 and 2September 2001 at ca. 18:30 h (A), 21:30 h (Cl and 00:30 h (E) and
photographs of the oocytes from the other lobe of the ovary of the same three
fish (B, D ,Fi. c = coalescing yolk and lipid; ho=hydrating oocyte; l = lipid
droplet; mn=migratory nucleus oocyte; n = nucleus; yg=yolk granule oocyte.
Scale bars = 200 fim in A, C, and D and 250 jim in B, D, and F.
Discussion
Oocyte hydration, ovulation, and spawning periods
Because histological studies showed that the ovaries of
numerous fish caught on different occasions between
18:30 and 20:30 h did not contain recently formed POFs,
we deduced that these fish had not spawned in the
previous few hours. However, at this time, the ovaries
of many fish, that were designated macroscopically as
at stage V and stage VI, often contained numerous
migratory nucleus-stage oocytes and, towards the end
of this period, often a few oocytes in the early stages of
hydration. Although the frequency distributions of the
oocyte diameters offish examined on both 1 and 13 Sep-
tember were still unimodal at 18:30 to 20:30 h, they had
become bimodal by 21:30 to 23:30 h (Fig. 3), reflecting
the fact that, by this time, numerous oocytes had become
markedly enlarged through hydration. The above data
demonstrate that hydration typically commences soon
after dusk. Furthermore, because a number of J?, sarba
caught between 01:30 and 04:30 h, and particularly
towards the end of this time interval, contained ovaries
undergoing ovulation and had newly formed POFs, the
period between the onset of hydration and commence-
ment of ovulation typically lasts about 7-10 hours, which
is very similar to the duration estimated for species
such as the black sea anchovy [Engraulis encrasicholus)
(Lisovenko and Andrianov, 1991) and ballyhoo (Hemir-
amphus brasiliensis) (McBride et al., 2003). Although we
656
Fishery Bulletin 102(4)
Figure 5
Histological sections through ovaries of Rhabdosargus sarba showing
lAl the outer layers of a yolk granule oocyte, and postovulatory follicles in
the ovaries offish collected at (B) ca. 02:00, (C and D) ca. 18:30, (E) ca.
22:00 and ca. (F) 01:00 h. g=granulosa layer; lu = lumen; t = thecal layer;
yg=yolk granule; yv=yolk vesicle; zre = zona radiata externa. Scale bars =
25 ftm in A, and 50 pra in B-F.
caught several R. sarba with new POFs in their ovaries
and hydrated oocytes in their oviducts, we were able to
catch only one individual of this species in which the
ovaries possessed new POFs and no hydrated oocytes.
The latter fish, which had clearly just completed spawn-
ing, was caught between 05:00 and 06:00 h.
Several species are known typically to complete
spawning in the 10-14 hours after the time when their
oocytes commence hydration, e.g., the northern anchovy
(Engraulis mordax) (Hunter and Macewicz, 1985), the
spotted seatrout (Cynoscion nebulosus) (Brown-Peterson
et al., 1988) and the horse mackerel (Trachurus trachu-
rus) (Karlou-Riga and Economidis, 1997). Furthermore,
spawning is typically completed 2-5 hours after the
commencement of ovulation, e.g., the spotted seatrout
(Cynoscion nebulosus) (Brown-Peterson et al., 1988),
the Black Sea anchovy [Engraulis encrasicholus) (Lisov-
enko and Andrianov, 1991) and the weakfish {Cynoscion
regalis) (Taylor and Villoso, 1994). These consistent
data, when considered in conjunction with the similar
duration of hydration of R. sarba, and the capture of a
very recently spawned fish between 05:00 and 06:00 h.
provide very strong circumstantial evidence that, in
the lower Swan River Estuary, R. sarba spawns mainly
between 02:00 and 06:00 h.
The newest POFs in the ovaries of R. sarba caught
at dusk, i.e., at 18:30 h, had degenerated to an extent
similar to those of ca. 12-h-old POFs in the ovaries of
other species, e.g. the skipjack tuna (Katsuwonus pela-
mis) (Hunter et al., 1986) and the whitemouth croaker
Hesp et al.: Timing and frequency of spawning and fecundity of Rhabdosargus sarba
657
^m^
Figure 6
Histological sections of ovaries of Rhabdosargus sarba showing an oocyte at
the (A) a and (B) /3 stages of atresia. c = chorion; t= thecal layer; v= vacuole.
Scale bars = 100 pm in A and 50 j.tm in B.
iMicropogonias furnieri) (Macchi et al., 2003). This
finding provides further evidence that R. sarba spawns
close to dawn. Certainly, the state of degeneration of the
newest POFs in mature ovaries of R. sarba at dusk pro-
vides very strong circumstantial evidence that spawn-
ing could not have occurred during at least most of the
previous daylight hours.
Our results demonstrate that the prevalence of fish
with ovaries at mid to late atretic state 1 declined
precipitously as salinities increased from their winter
minima in July and August and that this decrease
was accompanied by an increase in the prevalence of
migratory nucleus oocytes, hydrated oocytes or POFs.
The implication that the oocytes of R. sarba are often
inhibited from undergoing final oocyte maturation when
salinities are low parallels the conclusions drawn for
the influence of salinity on the gonadal development of
Cynoscion nebulosus in estuaries entering the Gulf of
Mexico (Brown-Peterson et al., 2002). The resorption of
yolk granule oocytes by the ovaries of R. sarba in July
and August would help conserve energy at a time when,
if those oocytes progressed through to final maturation
and were released, they would be exposed to salinities
that are known to be lower than those required for op-
timal development (Mihelkakis and Kitajima, 1994).
Frequency of spawning
Because ovulation lasts for ca. 2-5 hours, the POFs that
were present in ovulating ovaries and that showed no
detectable signs of degeneration were presumably <3
hours old. It then follows that, when POFs at intermedi-
ate and advanced stages of degeneration were present
in those same ovaries, those POFs were presumably ca.
24 and ca. 48 hours old, respectively. Thus, the pres-
ence of these three very distinct forms of POFs in the
same ovary of a fish implies that individual R. sarba are
capable of spawning on at least three successive days
during that part of the month when spawning activity
is greatest.
The estimated average frequency of spawning by R.
sarba, i.e., once every 2.7 days, is essentially the same
as that recorded for several other species, including e.g.,
spotted seatrout (Cynoscion nebulosus) (Brown-Peter-
son et al., 1988. 2002), red drum iSciaenops ocellatus)
(Wilson and Nieland, 1994), and common snook (Centro-
pomus undecimalis) (Taylor et al., 1998). The resultant
conclusion that R. sarba spawns about 45 times during
a spawning period is comparable to that estimated for
black sea anchovy (Engraulis encrasicholus) (Lisovenko
and Andrionov, 1991) and cobia (Rachycentron canadum)
(Brown-Peterson et al., 2001). However, spawning fre-
quency does vary markedly among species.
Relationship between spawning time and tidal cycle
Although seine netting between 00:30 and 05:30 h on a
number of days yielded no female R. sarba with newly
formed POFs, rod-and-line angling in deeper water
between 01:30 and 04:30 h yielded several females in
which the ovaries contained both newly formed POFs
and concentrations of hydrated oocytes in their oviducts,
and also running ripe males. This finding provides
strong circumstantial evidence that, just prior to ovula-
tion, R. sarba moves from nearshore shallows to offshore
deeper waters.
Because R. sarba typically spawns just prior to the
commencement of a relatively strong ebb tide, the fer-
tilized eggs would likely be transported downstream
and out of the estuary. The conclusion that eggs are
swept out of the estuary is supported by the fact that
only 15 larvae of R. sarba were caught during extensive
sampling of the lower Swan River Estuary and that
virtually all of these larvae were caught at its mouth
(Gaughan et al., 1990). A downstream movement of
eggs would be further facilitated by R. sarba spawn-
ing in deeper waters, where the current is greatest.
Emigration of eggs from the estuary would enhance
the chances of survival of the eggs of this essentially
marine species by ensuring that they would develop in
658
Fishery Bulletin 102(4)
60
40
I °
0 0.1 0 2 0 3 0 4 0 5 0 6 0 7
Predicted maximum change in daily tidal level (m)
B
Number of hours between high tide and
estimated time of spawning completion (06:00 h)
Figure 7
Relationship between prevalence of spawning and
(A) the predicted maximum change in daily tidal level
and (Bi the difference between the time of high tide
and the time at which spawning in Rhabdosargus sarba
is estimated to be completed in the lower Swan River
Estuary I 06:00 h). Each point represents the data for
a separate sampling occasion.
11.5
11.0
m
>, 105
§ 100
o
CD
~ 9.5
o
1 9.0
9
■ : \^^ • *
c
^^-""»
8.5
• •
•
8.0
•
7.5
S.2 5.3 54 55 5.6
In total length (mm)
Figure 8
Relationship between batch fecundity ( = number of
hydrated oocytes) and total length Imml for Rhabdosar-
gus sarba.
Spratelloicles robustus was particularly numerous in
some of our seine-net catches, a movement of the eggs
ofi?. sarba out of the estuary would also enhance their
chances of avoiding predation by that species.
A downstream transport of eggs would account for
the relatively few young 0+ juveniles that are recruited
into the nearshore shallow waters of the estuary ( Hesp
et al., 2004). Indeed, substantial recruitment into these
nearshore waters, presumably as a result of immigra-
tion from coastal marine waters, does not occur until
R. sarba is about one year old and about 140 mm in
length (Hesp et al.. 2004). Because R. sarba settles at a
length of ca. 12 mm (Hesp et al., 2004) and ca. 30 days
of age (Neira1), this immigration back into the estuary
does not occur until 11 months after settlement. In
contrast to the situation in the Swan River Estuary, R.
sarba elsewhere typically spawns in marine waters and
their larvae often enter estuaries on flood tides (e.g..
Miskiewicz, 1986; Neira and Potter, 1992).
a marine environment in which salinity remained con-
stantly at ca. 35'</, rather than in one in which sudden
rainfall could result in sudden marked declines in salin-
ity. However, the possession of spawning cycles linked
to lunar and tidal periodicities can reduce the likeli-
hood of predation (Taylor, 1984). For example, Johannes
(1978) pointed out that, because the spawning of many
reef-dwelling fishes is synchronized with the lunar cycle
and occurs on high or ebbing tides, their eggs would be
transported away from reefs, where the concentration
of predators is high, and consequently the likelihood
of predation during the early stages of life would be
reduced. Because planktivorous fishes are abundant in
estuaries (Johnson et al., 1990; Morgan, 1990), includ-
ing the Swan River Estuary where the planktivorous
Potential annual fecundity
The estimates of potential annual fecundity derived for
R. sarba during the present study, which ranged from
109,000 to 2,417,000 eggs for fishes of 188 and 266 mm
total length, respectively, greatly exceed those of El-
Agamy (1989), which ranged from 23,000 to 99,000 eggs
for fishes of 170 and 260 mm total length, respectively.
However, because El-Agamy ( 1989 ) based his estimates
on the number of large oocytes present in the ovaries of
individual R. sarba, he did not take into account the fact
1 Neira. F. J. 2004. Personal commun. Australian Maritime
College. Faculty of Fisheries and Marine Environment.
PO Box 21, Beaconsfield. Tasmania 7270. Australia.
Hesp et al.: Timing and frequency of spawning and fecundity of Rhabdosargus sarba
659
that this species has indeterminate fecundity. Thus, the
values recorded for the annual fecundity of R. sarba in
the Arabian Gulf almost certainly represent a marked
underestimate of the true annual fecundity of this spe-
cies in that region.
Acknowledgments
Our gratitude is expressed to colleagues and friends
for help with sampling — to G. Thomson for preparing
the histological sections, to F. J. Neira for information
on the larval phase of R. sarba, and to D. Fairclough
and two anonymous reviewers for invaluable comments
on the manuscript. Financial support was provided by
Murdoch University.
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661
Abstract — Novel data on the spatial
and temporal distribution of fishing
effort and population abundance are
presented for the market squid fishery
lLoligo opaleseens) in the Southern
California Bight, 1992-2000. Fishing
effort was measured by the detection
of boat lights by the Defense Meteo-
rological Satellite Program (DMSPi
Operational Linescan System (OLS).
Visual confirmation of fishing vessels
by nocturnal aerial surveys indicated
that lights detected by satellites are
reliable indicators of fishing effort.
Overall, fishing activity was con-
centrated off the following Channel
Islands: Santa Rosa, Santa Cruz,
Anacapa, and Santa Catalina. Fishing
activity occurred at depths of 100 m or
less. Landings, effort, and squid abun-
dance (measured as landings per unit
of effort. LPUE) markedly declined
during the 1997-98 El Nino; land-
ings and LPUE increased afterwards.
Within a fishing season, the location
of fishing activity shifted from the
northern shores of Santa Rosa and
Santa Cruz Islands in October, the
typical starting date for squid fishing
in the Bight, to the southern shores
by March, the typical end of the squid
season. Light detection by satellites
offers a source of fine-scale spatial
and temporal data on fishing effort for
the market squid fishery off Califor-
nia, and these data can be integrated
with environmental data and fishing
logbook data in the development of a
management plan.
Fishery dynamics of the California
market squid (Loligo opaleseens),
as measured by satellite remote sensing
Michael R Maxwell
University of California
c/o Southwest Fisheries Science Center
8604 La Jolla Shores Drive
La Jolla, California 92037
Present address: Department of Biology
University of San Diego
5998 Alcala Park
San Diego, California 92110
E-mail address. maxwellm@sandiegoedu
Annette Henry
California Department of Fish and Game
8604 La Jolla Shores Drive
La Jolla, California 92037
Christopher D. Elvidge
NOAA National Geophysical Data Center
325 Broadway
Boulder, Colorado 80305
Jeffrey Safran
Vinita R. Hobson
Ingrid Nelson
Benjamin T. Tuttle
Cooperative Institute for Research in
Environmental Sciences
University of Colorado
Boulder, Colorado 80303
John B. Dietz
Cooperative Institute for Research on
Atmosphere
Colorado State University
Fort Collins, Colorado 80523
John R. Hunter
Southwest Fisheries Science Center
NOAA National Marine Fisheries Service
8604 La Jolla Shores Drive
La Jolla, California 92037
Manuscript submitted 24 February 2003
to the Scientific Editor's Office.
Manuscript approved for publication
17 June 2004 by the Scientific Editor.
Fish. Bull. 102:661-670 (2004).
The market squid I Loligo opalesce?is)
(also known as the opalescent inshore
squid, FAO [Roper et al„ 1984]) is cur-
rently the largest revenue fishery for
California (Vojkovich, 1998; CDFG,
2000). The fishery's importance rose
steadily in the 1980s and 1990s, in
response to increased demand in Asia
coupled with declines in other fisheries
off the U.S. West Coast. Market squid
is a short-lived species (Jackson, 1994;
Butler et al., 1999) whose abundance
appears to be readily impacted by
environmental variability. For exam-
ple, squid landings plummeted during
the 1997-98 El Nino but reached a
record high in the following year
(CDFG, 2000). Considered an inte-
gral component of California's pelagic
fishery, the market squid was included
in the Coastal Pelagic Species Fishery
Management Plan as approved by the
Pacific Fisheries Management Council
in 1998. In this plan, federal authority
is invoked to monitor the fishery to
ensure the provisions of the Magnu-
son-Stevens Fishery Conservation and
Management Act of 1996. If a resource
is estimated as overfished, the Coun-
cil is to consider implementing active
management measures.
The lack of records of fishing effort,
such as vessel logbooks or observer
data, hampered initial attempts to
formulate a management plan for the
market squid. The nature of the fish-
ery, however, suggested an alternative
measure of fishing effort: the detec-
tion of boat lights by satellites. The
market squid is typically harvested on
shallow nearshore spawning grounds
in the Southern California Bight and
Monterey Bay (Vojkovich, 1998). At
night, specialized lightboats shine
high intensity (c. 30,000 watt) lights
on the water, which attract and con-
gregate the squid near the surface.
Seiner boats then capture the con-
centrated squid with purse-seine nets
(Vojkovich, 1998). The lights of the
fishing boats are detected and record-
ed by the U.S. Air Force Defense Me-
teorological Satellite Program (DMSP)
Operational Linescan System (OLS).
DMSP-OLS satellites continuously
orbit the planet, acquiring data on
662
Fishery Bulletin 102(4)
meteorology and, incidentally, nighttime light sources
(Croft, 1978; Elvidge et al., 1997, 2001b). Nighttime
light detection by satellites has proven useful for vari-
ous environmental questions, such as identifying the
extent of forest fires (Elvidge et al., 2001a) and the
effects of urban lighting on sea turtle nest selection
and hatchling survivorship (Salmon et al., 2000). Com-
pilation of light data for the global light-fishing squid
fleet has contributed to examinations of the fishery's
ecosystem impacts (Rodhouse et al., 2001). For local
squid fisheries, the locations of boat lights over space
and time are particularly valuable in cases where na-
tional boundaries pose constraints on the collection of
effort data (e.g., Illex argentinus in the southwestern
Atlantic, Waluda et al., 2002).
In this study, we used boat lights to quantify the spa-
tial and temporal patterns of market squid fishing ac-
tivity in the Southern California Bight over the period
1992-2000. The bight has come to represent the great
majority of squid landings off California (Vojkovich,
1998; Butler et al., 1999; CDFG, 2000). An important
component of our study is ground-truthing work that
validates the feasibility of using light data as a measure
of fishing effort. This estimate for fishing effort enables
us to present novel landings-per-unit-of-effort (LPUE)
data for the market squid. A companion paper analyzes
the light detection properties of the DMSP-OLS satellites
over the Southern California Bight (Elvidge et al.1).
Materials and methods
Light detection by satellites
The DMSP is a polar orbiting satellite system that
acquires daytime and nighttime data during each orbit.
The OLS is an oscillating scan radiometer designed for
cloud imaging. A full technical description of image
acquisition by the DMSP-OLS system, and the subse-
quent processing of images, appears in a companion
paper (Elvidge et al.1). Briefly, the DMSP-OLS acquired
nighttime data for over 2200 satellite orbits over the
Southern California Bight (i.e., 117° to 122° W, 32°30'
to 34°30'N) between 26 April 1992 and 4 April 2001.
Four different satellites were employed during this time.
Three overlapped in operation dates, producing mul-
tiple images for some dates. On all dates, images were
acquired between 18:30 and 22:00 Pacific Standard Time
(PST), with 20:21 PST being the average time. The satel-
lite images were processed into geo-referenced images of
boat lights and clouds. This process involved superimpos-
ing a field of grid cells onto the satellite image, which
quantified the satellite's "field of view," the extent of
detected clouds, and the area available for light detec-
tion. Image pixels of lights were taken directly from the
1 Elvidge, C. D., J. Safran, M. R. Maxwell, K. E. Baugh, A.
Henry, and J. R. Hunter. Unpubl. data. Satellite based
indices of lightboat fishing effort.
satellite image. Pixels were identified as lights by their
visible band digital number. The images were subjected
to quality-control procedures to correct for atmospheric
noise and to eliminate images overly contaminated by
solar glare, sunlight, heavy lunar illumination, or those
containing missing data. Fixed sources of lights, such as
city lights along the southern California coast, the city of
Avalon (Santa Catalina Island), off-shore oil platforms,
and naval installations, were masked from the light
detection algorithm.
Data deliveries were irregular during 1992, result-
ing in gaps in the early part of the time series. For
1992-98, only data collected during the dark half of
the lunar cycle were available. To control for lunar il-
lumination throughout the time series, we restricted
analysis of fishery data to images for which lunar il-
lumination was less than 0.02 lux (lumens per square
meter). Images for analysis were evaluated against ad-
ditional criteria. For a given image, we calculated the
number of total grid cells that were not used for light
detection because of glare, missing data, or the mask-
ing of known nonboat lights. If the resulting number of
grid cells left available for light detection was at least
50% of the original number of cells, we retained the
image for analysis. Cloud coverage can obscure light
sources1; therefore we used only images from nights
when clouds covered less than 25% of the grid cells
available for light detection. For nights with multiple
acceptable images, we averaged the percent cloud cover-
age and the number of detected light pixels.
Ground-truthing: aerial observations of boat activity
To determine the relationship between detected light
pixels and the number of squid fishing vessels on the
water, 35 aerial surveys were conducted from 10 June
1999 to 18 May 2000. Each survey took place in a Cessna
337 Skymaster flown at an average altitude of 1160 m
above sea level. The path of each survey covered the
main areas of squid fishing activity within the South-
ern California Bight (Fig. 1): from San Diego, over the
Channel Islands, to Point Conception, and back down the
coastline to San Diego. Each survey took approximately
four hours to complete, occurring between 18:00 h and
midnight PST. These times encompassed the time that
the DMSP-OLS satellites were over the bight. The 35
surveys produced 26 nights of usable data. Survey data
were discarded if satellite images were unavailable, if
flights were aborted because of weather, or if heavy fog
obscured boat visibility. We note that, for this ground-
truthing work, we did not restrict our analysis to nights
with lunar illumination of less than 0.02 lux. Rather,
we used all of the acceptable 26 nights, and quantified
lunar illumination as a proportion of the moon's phase,
where 0.00 denoted a new moon and 1.00 denoted a full
moon.
All vessels on the water were identified by using Fuji-
non 10x50 gyroscopic binoculars, and the GPS positions
of all vessels were recorded. Vessel type was identified
as either a nonsquid vessel or as a squid fishing vessel.
Maxwell et al.: Fishery dynamics of Lo/igo opalescens
663
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Figure 1
Fishing activity for the market squid in the Southern California Bight, from 26 April 1992 to 28 May 2000.
(At Composite satellite image of squid fishing vessel lights (black marks). Permanent sources of lights (e.g.,
city lights, offshore oil platforms, naval installations) are removed. CalCOFI stations 83.42 ("A"; 34.18°N,
119.51°W) and 83.51 ("B"; 33.88°N, 120.13°W) are indicated. (B) Squid landings as reported by California
Dept. Fish and Game fishing blocks. Gray: blocks that account for 6.8 million kg (2%) or more of the land-
ings from blocks 651-896. Black: blocks that account for 20.5 million kg (6%) or more. Latitudinal blocks
1032-1035 are indicated. Santa Cruz Island is marked "999" to aid correspondence with A.
664
Fishery Bulletin 102(4)
Squid fishing vessels could not always be distinguished
as light boats or seiners and therefore were recorded as
"squid fishing vessels."
The numbers of squid fishing vessels showed large
skew in their frequency distribution. These data were
transformed by x' = log10(x+l). Similarly, proportion
lunar phase was transformed by x' = arcsin(V.r), and
detected light pixels were transformed by x' = log]0(.v+l)
to correct for skew (Zar, 1984). These transformations
produced normally distributed data acceptable for re-
gression analysis. With these transformed variables,
multiple stepwise regression (forward selection) was
performed with the software S-Plus 2000 (MathSoft
Inc., Cambridge, MA) to examine the effects of squid
fishing vessels and the proportion lunar phase on de-
tected light pixels. Squid fishing vessels and proportion
lunar phase showed very little correlation (r=-0.09).
Fishery characteristics, 1992-2000
For quantitative analysis of the fishery data, we aggre-
gated the nightly satellite data (i.e., light pixels detected
on the water) into calendar quarters, as suggested by
the within-year distribution of squid landings in the
bight (Butler et al., 1999). To standardize conditions of
light detection, we excluded all data after 28 May 2000,
because this was the starting date of mandatory shield-
ing of the high intensity lights of the lightboats. This
regulation was enforced by California's Department of
Fish and Game to reduce light pollution by the light-
boats. The shields did not totally obscure the lightboats
from detection by the satellites (authors' pers. obs.) but
made the emitted light less bright, and, hence, less
detectable by the satellites. Thus, our data for fishing
effort spanned calendar quarters from Jul-Sep 1992 to
Jan-Mar 2000. We included a quarter for analysis if it
contained 10 or more nights of acceptable images. By
these criteria, we described effort for 24 of the 31 cal-
endar quarters. The mean number of nights per quarter
was 26 (range=10-72 nights).
The quantity (kg) and location of landed market squid
were recorded by California Department of Fish and
Game (CDFG) throughout the 1992-2000 study pe-
riod and were made available to the authors. During
this study period, squid fishing in the bight occurred
exclusively at night (Vojkovich, 1998). The squid were
landed at port within several hours after being caught;
therefore the landings for a given day corresponded to
the previous night's effort. Squid fishermen reported
the locations of their hauls by CDFG fishing blocks. We
defined catch taken from the Southern California Bight
as that from blocks 651-896 and 1032-1035 (Fig. 1).
Blocks 651-896 are typically 10' latitude x 10' longitude
and can be used to locate regions of high catch. Blocks
1032-1035 are large latitudinal bands, generally 30'
wide, that encompass blocks 651-896. We used blocks
1032-1035 in calculating the total catch in the bight,
but not in depicting the location of the catch.
To construct the abundance index of landings per
unit of effort (LPUE). we first estimated the number of
squid fishing vessels for each night of satellite data, us-
ing the regression results of the ground-truthing work
(see "Results" section). We then summed the nightly
estimated number of vessels for each calendar quarter.
For those nights for which we had estimated numbers of
vessels, we also summed the landed catch within each
calendar quarter. To arrive at LPUE for the quarter,
we divided the summed landings by the corresponding
summed effort.
Environmental data
We used the multivariate ENSO index (MEI) to indicate
overall environmental conditions over the course of the
1992-2000 study period. The MEI is a multivariate
index that incorporates sea level pressure, surface zonal
and meridional wind components, sea surface tempera-
ture, surface air temperature, and cloudiness (Wolter
and Timlin, 1998). The MEI index is calculated for the
tropical Pacific (i.e., between 10°N and 10°S, from Asia
to the Americas), and its monthly values appear on
the website http://www.cdc.noaa.gov/~kew/MEI/table.
html.2
Analysis of the location of fishing effort over the
course of the traditional squid fishing season in the
bight led to an investigation of oceanographic data for
waters surrounding Santa Cruz Island in March. Spe-
cifically, we examined sea temperature from two sourc-
es. First, we obtained sea surface temperature for all
satellite nights in March 1993-2000 from the Physical
Oceanography Distributed Active Archive Center (PO.
DAAC) at California Institute of Technology (Pasadena,
CA). These data were reported for 18x18 km grids,
which were approximately the size of the 10'xlO' fish-
ing blocks. We selected the grid that covered block 686
to represent the northern shore of the island, and that
which covered block 708 to represent the southern shore
(Fig. IB). For each year in the 1993-2000 period, we
calculated mean March temperature for both blocks.
The second source of sea temperature was the da-
tabase maintained by the California Cooperative Oce-
anic Fisheries Investigations (CalCOFI). Since 1950.
the CalCOFI program has conducted quarterly survey
cruises along transects perpendicular to the southern
California coast. This system of transects incorporates
66 geographically fixed stations. At each station, a
conductivity-temperature-depth (CTD) instrument is
deployed. Details on survey methods appear on the web-
site http://www-mlrg.ucsd.edu/calcofi. html. :1 along with
the publicly accessible database. For April 1993-2000,
we obtained temperatures at sea surface and at 75 me-
ters depth at two stations (Fig. 1A): 83.42 (northeast
of Santa Cruz Island: 34.18°N, 119.51°W) and 83.51
(southwest of Santa Cruz Island; 33.88DN, 120.13 W).
- NOAA-CIRES Climate Diagnostics Center website. I Ac-
cessed 3 November 200.3.1
3 California Cooperative Oceanic Fisheries Investigations
website. [Accessed 3 November 200.3.1
Maxwell et al.: Fishery dynamics of Loligo opalescens
665
One measurement was made at each station
at sea surface and at 75 meters depth during
April (n = 8 for both depths).
Results
Ground-truthing: aerial observations
of boat activity
Nonsquid vessels used weak lights (i.e., much
less than 30,000 watts), which did not show
in the satellite images. On average, 23 squid
fishing vessels were observed each night by
the aerial surveys (range = 0-64 vessels, n=26
nights). The 20:00-midnight observation
period was the peak time for attraction of
squid by the light boats. Although the squid
vessels did change location during this time,
they typically left their lights running to
continue searching for squid. The number of
squid vessels explained much of the varia-
tion in detected light pixels; proportion lunar
phase failed to enter the analysis as a signifi-
cant variable (Table 1). Detected light pixels increased
with the number of squid vessels (Fig. 2).
The regression analysis yields the following simpli-
fied equation:
log10(p, +l) = 1.25xlog10(x, +1), (1)
where xt = observed number of squid vessels; and
pt = detected light pixels for night t.
We used inverse prediction to estimate the number
of squid vessels for each satellite night (Et\ in the
1992-2000 period (Zar, 1984). The estimated number
of squid vessels was found by the equation
3.0-
♦ ♦
♦
^.
♦ *
+
♦ ,'
«> 2.0-
♦ ♦ *- ' ' ♦
"cB
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ra 10-
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0.0 1.0 2.0
Log10 (observed squid vessels + 1 )
Figure 2
Plot of log10-transformed number of squid vessels and detected light
pixels. Regression line taken from the statistics in Table 1.
Table 1
Multiple stepwise (forward selection) regression of de-
tected light pixels on squid fishing vessels (transformed:
x'=log10(x+l) and proportion lunar phase (transformed:
.r'=arcsin( Vr). r2=0.64; ANOVA: Fl 24 = 42.66, P<0.0001.
Variable
Coefficient ±SE
Squid fishing vessels
INTERCEPT
Proportion lunar phase
1.25 ±0.19
0.07 ±0.24
not entered
<0.0001
>0.75
not entered
4=io"«-(ft+imB-i=1J»/ft+i-i-
(2)
The ground sample distance of the satellite data is
2.7 km, which means that multiple squid vessels may
potentially fit into one pixel of detected light. This could
result in an underestimation of effort. The severity of
this problem can be assessed by examining the coeffi-
cient of the simple linear regression of log-transformed
variables represented by Equation 1. One of four sce-
narios is possible: 1) boats are not aggregated (coef-
ficient^), 2) boats are aggregated regardless of the
number of boats on the water (coefficients), 3) boats
are aggregated only when many boats are on the water
(coefficient<l), or 4) boats are aggregated only when few
boats are on the water (coefficient>l). The coefficient
in Equation 1 is 1.25, which fails to significantly differ
from 1.00 (f-test for regression coefficient: t = 1.305,
j30 = 1, df = 24, P > 0.2, two-tailed; power < 0.5, retrospec-
tively calculated; Zar, 1984). This result suggests that
very little clumping of the boats occurred (scenario 1),
or that the degree of clumping was independent of the
number of boats on the water (scenario 2). Although the
statistical power of this ^-test is not high (power<0.5),
we conclude that the data provide more support for sce-
narios 1 and 2 over scenarios 3 and 4. Either scenario,
1 or 2, allows for a comparison of the relative values of
estimated effort and LPUE within a time series.
Fishery characteristics, 1992-2000
A composite satellite image of all squid fishing activity
in the Southern California Bight during the 1992-2000
study period revealed major concentrations of effort off
the Channel Islands, especially Santa Rosa, Santa Cruz,
Anacapa, and Santa Catalina (Fig. 1A). Squid fishing
occurs close to the island shores and is bounded by the
100-m contour. During the study period, 379.2 billion
kg of squid were landed in the bight: 341.2 billion from
blocks 651-896 (Fig. IB), and the remainder from the
large blocks 1032-1035. The main areas of fishing activ-
ity, as indicated by satellite, are consistent with the
blocks of high catch (Fig. IB). We note that blocks 682
666
Fishery Bulletin 102(4)
and 720, although areas of high catch, do not appear on
the satellite composite because the mainland shore was
excluded from light detection. Further, much activity
was evident around Santa Barbara Island (block 765).
Although this block represented 4.0 million kg (18th
out of the 127 blocks), it did not rank highly enough for
inclusion in Fig. IB.
Analysis of temporal trends in the fishery showed
peaks in landed catch for the bight in the fall and
winter quarters (Oct-Dec and Jan-Mar, respectively;
Fig. 3A). There was a near absence of catch during
c >
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az
1992 1993 1994 1995 1996 1997 1998 1999 2000
Quarter
Figure 3
Time series of market squid fishery data in Southern California
Bight, by calendar quarter (Jul-Sep 1992 to Jan-Mar 2000).
The Jan-Mar quarters are marked by dashed vertical lines.
(A) Landings are in kg (blocks 651-896, 1032-1035). (B) Mean
±SE nightly fishing effort, in estimated number of squid vessels.
(C) Landings per unit of effort (LPUEl: summed landings (kg)
on satellite nights were divided by summed effort (estimated
number of squid vessels) on the corresponding nights.
most of 1997-98 (Fig. 3A), which corresponded to the
strong El Nino event during this period (Fig. 4). Effort
data revealed surges in the Oct-Dec quarters before
the 1997-98 El Nino (Fig. 3B). The Oct-Dec quarter
of 1998 signalled a resumption of fishing effort follow-
ing El Nino, but effort levels for 1999 and early 2000
were lower than pre-El Nino levels. Interestingly, squid
abundance, as measured by landings per unit of effort
(LPUE), showed a rapid increase from the El Nino lows,
and squid abundance for 1999-2000 reached the high-
est values of the time series (Fig. 3C).
Analysis of boat locations along the Channel
Islands revealed a shift over the course of the
fishing season. Compiling the satellite data to
yield composite images in multiyear sets, we
found that fishing activity in October consis-
tently included the north shore of Santa Cruz
Island (Fig. 5, A,C,E). In contrast, fishing ac-
tivity in March showed considerable reduction
along the north side of Santa Cruz Is., but activ-
ity continued along the island's southern shore
(Fig. 5, B,D,F). Composite images for December
and January were also examined for all of the
multiyear sets. December marked a transitional
stage from the activity in October to reduction
of fishing in March along the northern shores.
In all multiyear sets, the December lights along
northern Santa Cruz Island were more scat-
tered and less dense than those in October.
January images were very similar to those for
March. Although data from March 1993-95 in-
dicated little fishing activity, a composite image
for January 1993-95 was very similar to that
for March 1999-2000: light banks occurred off
southern Santa Cruz, southeastern Santa Rosa,
and around Anacapa, but were virtually absent
from northern Santa Cruz and Santa Rosa.
Water temperatures around Santa Cruz Is-
land did not consistently differ between north-
ern and southern waters. March sea surface
temperatures, measured by satellite, were very
similar for the island's northern and south-
ern shores (Table 2). April sea surface tem-
peratures, measured at CalCOFI stations, were
slightly warmer to the northeast of the island
(Table 2). Temperatures at 75 meters, however,
were nearly identical for the two CalCOFI sta-
tions (Table 2).
Discussion
The satellite images and landings data corrobo-
rated spatial and temporal patterns of fishing
activity for the market squid. For the period
1992-2000, both data sets indicated intense
harvesting along the Channel Islands of Santa
Rosa, Santa Cruz, Anacapa, and Santa Cata-
lina. The satellite images captured additional
information, such as fishing activity being
Maxwell et al.: Fishery dynamics of Loligo opalescens
667
Table 2
Water temperature ( C I for the northern and southern waters around Santa Cruz Island, March and April, 1993-
-2000.
Northern waters Southern waters
Depth (m) Location Mean Min Max Location Mean Min
Max
March sea surface temperature, as measured by satellite (PO.DAAC datai'
0 Block 686 14.5 12.8 15.7 Block 708 14.7 13.2
15.9
April temperature, measured at CalCOFI stations2
0 Station 83.42 13.6 11.6 16.7 Station 83.51 12.8 11.2
14.5
75 Station 83.42 9.9 9.3 11.2 Station 83.51 10.3 9.3
11.2
1 Measurements made on multiple nights per month of March (range of measured nights per month of March: 6-26 1. "Mean" is the overall average
of the mean March temperatures; "Min" is the minimum of the mean values, "Max is the maximum, of the mean values.
2 One measurement made at each station at each depth per month of April (n = 8 for both depths).
clearly delimited by the 100-m contour. The landings
data, reported by fishing blocks, were much cruder in
geographic scale and failed to catch this subtlety.
The ground-truthing work conducted by aerial sur-
veys indicated that detected light pixels are useful in
estimating the number of squid vessels in operation.
This result is consistent with examination of the fish-
ery for the squid Illex argentinus in the southwestern
Atlantic, where vessels use powerful lamps to attract
the squid to lures (Waluda et al., 2002). In the latter
fishery, analysis of images acquired by the DMSP-OLS
satellites revealed a good fit between the recorded num-
ber of vessels in operation on a given night and the
number of light pixels detected (Waluda et al., 2002).
In the present study, the fishery data showed a
strong response to the 1997-98 El Nino event, which
was one of the strongest events on record (Wolter and
Timlin, 1998). Fishing effort and landings tended to
peak in the Oct-Dec and Jan-Mar quarters before
the 1997-98 El Nino. Both data series dramatically
dropped during the 1997-98 El Nino and showed recov-
ery afterwards. Squid abundance, measured as LPUE,
also showed a pronounced drop and rapid increase in
response to the El Nino. It is interesting to note that
another index of market squid abundance, the occur-
rence of squid beaks in the scat of sea lions, showed
similar responses to earlier El Nino events (Lowry and
Carretta, 1999). Squid beak occurrence dropped steeply
during the strong 1983-84 El Nino, and increased
afterwards. Beak occurrence also dipped and rose in
response to a milder El Nino in 1992-93. Significantly,
Lowry and Carretta (1999) examined southern Chan-
nel Islands: Santa Barbara, San Clemente, and San
Nicolas. Our present study reflects squid abundance
primarily around northern Channel Islands (e.g., Santa
Rosa, Santa Cruz, Anacapa). Taken together, these
studies may indicate that El Nino exerts a bight-wide
influence on squid abundance.
We suggest that a strong El Nino event changes the
reproductive conditions for the market squid in the
-2.0-1 1 1 1 1 1 1 1 h
1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
Figure 4
Multivariate ENSO index iMEI) for the tropical Pacific
(between 10CN and 10°Si, by month. Data were obtained
from http://www.cdc.noaa.gov/~kew/MEI/table.html.
Southern California Bight. With regard to spawning,
the spawning population becomes less abundant on the
traditional shallow-water spawning grounds. Research
on a congener, the South African chokka squid (Loligo
vulgaris reynaudii), points to possible environmental
influences on spawning for loliginid squid (Roberts and
Sauer, 1994). Off South Africa, a strong El Nino can
lead to reduced upwelling and increased turbidity. In
normal years, upwelling, presumably detected by the
squid as an influx of cold water, may trigger spawning
behavior (Roberts and Sauer. 1994). In El Nino years
off South Africa, reduced upwelling and increased tur-
bidity on the inshore spawning grounds are thought to
force the spawners into deeper water, beyond the reach
of the fishery (Roberts and Sauer, 1994). In a recent
study, catch for the chokka squid increased with strong
easterly winds, which caused upwelling, and decreased
with increased turbidity (Schon et al., 2002). In the
California Current System, upwelling decreases during
strong El Nino events (Schwing et al., 2000). Upwelling
668
Fishery Bulletin 102(4)
October 1992,
1993. 1994
V
-O*^-
Los
Angeles
A
^
March 1993, 1994, 1995
120VJ n9*w
October 1995, 1996, 1997
March 1996,
1997, 1998
'"^.
Los
34'" Nh
. - ~
Angeles
D
• *C>^_
120°W 119°W
October 1998, 1999, 2000
120°W 119°W
March 1999, 2000
119°W
Figure 5
Location of fishing activity, as indicated by black areas, for the early ( October i and
late (March l parts of the traditional squid fishing season in the Southern California
Bight. 1992-2000. For each month, a multiyear composite image is shown. (A) October
1992, 1993. 1994. (Bi March 1993. 1994, 1995. (Cl October 1995, 1996, 1997. (Dl
March 1996, 1997, 1998. (E) October 1998, 1999. (F) March 1999, 2000.
in the Southern California Bight was reduced during
the 1997-98 El Nino (Hay ward, 2000). It is not known
how market squid adults respond to changes in water
temperature or turbidity, or whether spawning fish shift
to other habitats during El Nino events.
A strong El Nino event can also alter feeding and
developmental conditions for squid. During the 1997-98
El Nino, macrozooplankton abundance substantially
decreased in the Southern California Bight and off
Baja California (Lynn et al., 1998; Hayward, 2000; La-
vaniegos et al., 2002). Food availability affects growth
rates of loligind squid (Jackson and Moltschaniwskyj,
2001). Recently, Jackson and Domeier (2003) indicated
lower growth rates for the market squid in the Southern
California Bight during the 1997-98 El Nino.
In the present study, fishing effort following the
1997-98 El Nino was generally below pre-El Nino lev-
els. The subsequent high levels of catch in late 1999
and early 2000 may indicate that squid were in great
abundance, thereby requiring less overall catch effort
to meet market demand. A strong La Nina succeeded
the 1997-98 El Nino (Lynn and Bograd. 2002; Schwing
et al., 2002), with strong upwelling and high macrozoo-
plankton abundance in the Southern California Bight
by spring 1999 (Schwing et al., 2000; Hayward, 2000).
Indeed, the high LPUE in the present study in late 1999
and early 2000 points to increased squid abundance in
response to a more productive environment. Alterna-
tively, one could argue that increased fishing efficiency.
not increased squid abundance, resulted in high LPUE.
One manifestation of higher fishing efficiency could be
a contracted fishing range, where especially productive
pockets are identified and targeted. An overall com-
parison of fishing location in October and March before
and after El Nino did not support this explanation: the
total spatial extent of fishing activity was not greatly
Maxwell et al.: Fishery dynamics of Loligo opalescens
. 669
reduced in post-El Nino October or March. A noticeable
concentration of fishing effort off the southern shore
of Santa Cruz Island was evident in the post-El Nino
period, however. The landings data may indicate that
this southern shore, represented by blocks 708 and
709, was indeed productive. In the pre-El Nino period
(1992-96), blocks 708 and 709 represented 3% of the
landings in the bight. In the post-El Nino period (1999
to early 2000), these two blocks came to represent 12%
of the landings.
The spatial distribution of fishing activity appears to
shift over the course of the squid fishing season. In the
Southern California Bight, October and March mark
the traditional beginning and end of the squid fishing
season, respectively (Butler et al., 1999). In the present
study, fishing activity along the Santa Rosa and Santa
Cruz Islands moved largely to the southern shores by
March, leaving the northern shores relatively unfished.
This spatial shift may reflect change in local squid
habitat or changes in the fishermen's behavior. As a
rough indicator of habitat quality, water temperature
did not consistently differ between the northern and
southern waters around Santa Cruz Island in March
and April, both at sea surface and at 75 meters depth.
Wind conditions, on the other hand, change consider-
ably from October to March. The northern shores of
Santa Rosa and Santa Cruz lie on the rim of the San-
ta Barbara Channel. Wind speed and wind stress are
relatively low through the channel in the fall and early
winter but increase significantly in March to remain
high throughout the spring and summer (Winant and
Dorman, 1997; Harms and Winant, 1998; Dorman and
Winant, 2000). It remains unresolved whether the high
winds in the Channel in March and April create ocean-
floor turbulence and turbidity that discourage squid
spawning (cf, Roberts and Sauer, 1994), or whether
fishermen simply eschew the rocky Channel in favor of
the southern shores of the islands.
Although satellite remote sensing can generate a
"neutral party" record of fishing effort, we note three
caveats associated with satellite data. First, large sta-
tionary sources of light, such as coastal cities, must be
excluded when quantifying fishing vessel activity. The
exclusion of urban light sources can result in under-
estimating effort, because boats that work near large
light sources can be excluded from analysis. We were
concerned that an underestimation of effort along the
mainland coast would explain this study's post-El Nino
increase in LPUE. Landings data, however, may indi-
cate that effort in coastal blocks actually declined after
the 1997-98 El Nino. Coastal blocks accounted for 19%
of the landings in the pre-El Nino years (1992-96),
dropping to 11% of landings in the post-El Nino years
(1999 to early 2000).
Second, the spatial resolution of the satellite imag-
es may be large enough to allow multiple boats to fit
into one "pixel" of detected light. Thus, effort may be
underestimated. Analysis of the ground-truthing fly-
overs, however, did not indicate a strong interaction
between boat aggregation and nightly fleet size. Boats
may have indeed aggregated over the course of our
study, but our analysis indicates that such aggregation
was independent of nightly fleet size. In this case, the
absolute values of estimated effort and LPUE would be
underestimated across all dates. The relative values of
effort and LPUE, however, will be only slightly affected
within a time series; therefore we place confidence in
our examinations of the temporal patterns of the ef-
fort-based data. A third caveat is specific to the present
study. The ground-truthing work occurred during a pe-
riod of relatively low fishing effort (1999-2000). Future
fly-overs during periods of greater effort will be useful
in corroborating our observed relationship between fly-
over and satellite data.
The present study demonstrates that light detection
by satellite remote sensing is useful for examining tem-
poral and spatial patterns of fishing effort and popula-
tion abundance, as measured by LPUE. Light detection
by satellite has certain drawbacks, but these are not
insurmountable. Importantly, geo-referenced satellite
images provide an independent source of fishing effort,
which can be feasibly integrated with environmental
data through GIS analysis. With regard to market squid
off California, satellite data can help provide fine-scale
data on fishing location for this fishery's ongoing man-
agement efforts4'5 (see also Mangel et al., 2002). Al-
though mandatory shielding of the boat lights went into
effect in May 2000, these lights are still detectable by
the satellites (authors' pers. obs.). Recently, effort log-
books have become mandatory for squid fishermen off
California. This requirement points to a unique oppor-
tunity to collect and corroborate fishery-dependent and
independent measures of fishing effort.
Acknowledgments
We owe much gratitude to personnel of California's
Department of Fish and Game for their assistance in
the ground-truthing work. In particular, we thank the
pilots Jeff Veal and Tom Evans, and the following aerial
observers: D. Bergen, T. Bishop, S. Carner, D. Hanan,
C. Kong, J. Kraus, A. Lohse, S. MacWilliams, D. Ono,
M. Songer, J. Wagner, and E. Wilson. We also thank
Paul Crone for collaboration on this project, Chris Reiss
for extracting CalCOFI water temperature data. Rich
Cosgrove for assistance with mapping, Kevin Hill for
information about the Pacific Fisheries Management
Council, and George Watters and anonymous review-
ers for constructive comments. This project was funded
by the California Department of Fish and Game and
U.S. Department of Commerce (NOAA NESDIS Ocean
Remote Sensing Program).
4 California Department of Fish and Game. 2003. Draft:
Market squid fishery management plan. [Available from:
Calif. Dept. Fish Game, 4949 Viewridge Avenue, San Diego,
CA 92123.]
5 Maxwell, M. R., L. D. Jacobson, and R. Conser. Manuscript in
review. Eggs-per-recruit model for management of the Cali-
fornia market squid (Loligo opalescens) fishery.
670
Fishery Bulletin 102(4)
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671
Abstract-In May 2001, the National
Marine Fisheries Service (NMFS)
opened two areas in the northwest-
ern Atlantic Ocean that had been
previously closed to the U.S. sea
scallop I Placopecten magellanicus)
dredge fishery. Upon reopening these
areas, termed the "Hudson Canyon
Controlled Access Area" and the "Vir-
ginia Beach Controlled Access Area."
NMFS observers found that marine
turtles were being caught inciden-
tally in scallop dredges. This study
uses the generalized linear model and
the generalized additive model fitting
techniques to identify environmen-
tal factors and gear characteristics
that influence bycatch rates, and to
predict total bycatch in these two
areas during May-December 2001 and
2002 by incorporating environmental
factors into the models. Significant
factors affecting sea turtle bycatch
were season, time-of-day, sea sur-
face temperature, and depth zone. In
estimating total bycatch, rates were
stratified according to a combination
of all these factors except time-of-
day which was not available in fish-
ing logbooks. Highest bycatch rates
occurred during the summer season,
in temperatures greater than 19°C,
and in water depths from 49 to 57 m.
Total estimated bycatch of sea turtles
during May-December in 2001 and
2002 in both areas combined was 169
animals ( CV= 55.3 ), of which 164 ( 97% )
animals were caught in the Hudson
Canyon area. From these findings, it
may be possible to predict hot spots
for sea turtle bycatch in future years
in the controlled access areas.
Magnitude and distribution of sea turtle bycatch
in the sea scallop (Placopecten magellanicus)
dredge fishery in two areas of the
northwestern Atlantic Ocean, 2001-2002
Kimberly T. Murray
Northeast Fisheries Science Center
National Marine Fisheries Service
166 Water Street
Woods Hole, Massachusetts 02543
E-mail address. Kimberly Murray<S'noaa gov
Manuscript submitted 1 December 2003
to the Scientific Editor's Office.
Manuscript approved for publication
27 May 2004 by the Scientific Editor.
Fish. Bull. 102:671-681 12004).
Five species of sea turtles in the
northwestern Atlantic Ocean are
protected under the U.S. Endangered
Species Act of 1973. The loggerhead
turtle (Caretta caretta) is listed as a
threatened species, and the leather-
back (Dermochelys coriacea), hawks-
bill (Eretmochelys imbricata), Kemp's
ridley iLepidochelys kempii), and
certain populations of the green sea
turtle (Chelonia mydas) are listed as
endangered. Populations of each of
these species have declined principally
as a result of human activities (NRC,
1990).
The incidental capture, or bycatch,
of sea turtles in commercial fisheries
is a major source of mortality (NRC,
1990; Turtle Expert Working Group,
2000). These turtles are captured in-
cidentally in pelagic longlines (Lewi-
son et al., 2004), trawls (Epperly,
2003), gill nets (Julian and Beeson.
1998), pound nets, weirs, pots, and
traps (NMFS and USFWS, 1991; Al-
len, 2000). Such threats occur at vari-
ous life stages of a population and at
different intensities, and consequent-
ly have implications for management
policy (Heppell et al., 2003).
The U.S. National Marine Fisher-
ies Service (NMFS) has implemented
management measures in both the
Atlantic and the Pacific in the form
of gear modifications or time and area
closures to reduce sea turtle bycatch.
For example, since the early 1990s,
turtle excluder devices (TEDs) have
been required in all inshore and off-
shore shrimp trawl nets in southeast-
ern U.S. waters (Epperly, 2003) to re-
duce sea turtle mortality (Henwood
and Stuntz, 1987). Bycatches of sea
turtles in the U.S. pelagic longline
fisheries for swordfish and tuna (Wit-
zell, 1999) led to a year-round clo-
sure of a 2.6 million nmi2 area in the
northwestern Atlantic Ocean to these
fisheries beginning in 2002.
In recent years, documented inter-
actions have occurred between sea
turtles and sea scallop dredges, a pre-
viously unidentified threat in recovery
planning efforts (NMFS, 1991). Dur-
ing 2001 and 2002, fisheries observers
aboard commercial sea scallop vessels
documented the bycatch of sea turtles
in two small regions of the Mid-Atlan-
tic Bight (MAB). These areas, termed
the "Hudson Canyon Controlled Ac-
cess Area" (approximately 3150 km2i
and the "Virginia Beach Controlled
Access Area" (approximately 900 km2)
were closed to scallop fishing in April
1998 but reopened in May 2001 on a
conditional basis (Fig. 1). This study
uses the generalized linear and gen-
eralized additive models to identify
environmental factors and gear char-
acteristics affecting the bycatch rate
of sea turtles in these two areas and
to predict total bycatch by sea scallop
dredge vessels in these two areas in
2001 and 2002.
Methods
The fishery
In 2001 and 2002. 137 and 93 com-
mercial vessels, respectively, partici-
pated in the Controlled Area Access
Program sea scallop fishery. Although
672
Fishery Bulletin 102(4)
40"0'0"N
74=0'0"W
1
A
' Hudson Canyon
Controlled Access Area
Virginia Beach
Controlled Access Area
Mid-Atlantic Controlled Access Areas
for the sea scallop fishery 2001 and 2002
50 Fathom Isobath
100 Fathom Isobath
Figure 1
Mid-Atlantic controlled access areas for the sea scallop fishery 2001
and 2002.
the U.S. commercial scallop fishery operates year-round,
the area access program in 2001 began on 1 May, and
in 2002 on 1 March, and ended on 28 February follow-
ing the respective fishing year (1 March-28 February).
Vessels in the controlled access areas fished around
the clock for approximately 5-12 days, accomplishing
between 40 and 160 hauls per trip. Dredges in the con-
trolled areas were generally fished at depths between
45 and 75 m. The average haul duration was about 1
hour. Most vessels fished two dredges simultaneously
(one from each side of the vessel), which were generally
either 3.9 or 4.5 m (13 or 15 ft) wide.
Vessels in the Mid-Atlantic typically fish with a New
Bedford style scallop dredge equipped for soft-bottom
substrates. In this configuration, tickler chains strung
from the sweep chain run horizontally between the
dredge frame and the ring bag and are designed to
raise scallops off the bottom and into the bag. Turtles
become entrapped in the ring bag or on the dredge
frame. For dredging on hard bottom, such as in New
England, vertical up and down chains hang over the
tickler chains, preventing boulders from entering the
ring bag (Smolowitz, 1998). New Bedford style scallop
dredges have also been used in U.S. fisheries in the
Pacific (PSMFC1).
1 Pacific States Marine Fisheries Commission (PSMFC I.
2003. Description of fishing gears used on the Pacific
Coast, http://pcouncil.org/habitat/geardesc.pdf. [Accessed
6 April 2004.]
Murray: Magnitude and distribution of sea turtle bycatch in the sea scallop dredge fishery
673
Data sources
Observer data Observers were placed on randomly
selected vessels fishing in the controlled areas to record
the bycatch of turtles and other protected species. From
May to December in 2001 and 2002, observers sampled
11% of the commercial fishing effort in the Hudson
Canyon region, and in October 2001, 16% of the effort in
Virginia Beach. No trips were observed in the Virginia
Beach region during 2002 because of low commercial
fishing effort in the area. Observers were on- and off-
watch on an irregular schedule throughout a 24-hour
period, observing on average 65% of the hauls on a trip.
When a dredge was hauled on board, observers recorded
the haul location, time, depth, tow speed, tow duration,
number of dredges observed, and the presence or absence
of turtle bycatch. In 2001, observers identified 20% of the
turtles that came aboard as loggerhead sea turtles but
were unable to identify the remaining 80%. As a result
of improved observer training (NMFS 200.3), observers
identified 88% of the turtles as loggerhead sea turtles
in 2002, but they were unable to identify the remain-
ing 12%. Given that observers document the loggerhead
species most commonly in the Mid-Atlantic area, and
that all sea turtles positively identified were loggerhead
sea turtles, bycatch estimates in this analysis are con-
sidered to be those of loggerhead sea turtles. Although
some turtles may have been released alive or injured,
this analysis does not differentiate between live, dead,
and injured animals.
Fishing effort data Under the 1982 Atlantic Sea Scallop
Fishery Management Plan, all vessels targeting scallops
must complete a vessel trip report ( VTR) log (as of 1994)
indicating area fished, kept and discarded catch, and
fishing effort. These data were used to estimate the total
fishing effort of the fleet. In calculating fishing effort,
one unit of effort equals a single dredge haul because
vessels may fish one or two dredges simultaneously on
each haul. Because a preliminary analysis showed that
tow duration or dredge length does not significantly
affect the probability of turtle capture, dredge haul effort
was not standardized for these two variables. All VTR
trips from May to December in the controlled areas were
used in the analysis. Because completion of vessel trip
reports is mandatory and trips to the controlled areas
were closely monitored, it was assumed that the VTR
data represented 100% of total fishing effort.
Sea surface temperature Sea surface temperature at
each position reported in the observer and VTR data-
bases was extracted from NOAA AVHRR (advanced
very high resolution radiometer) coastwatch satellite
images. A Visual Basic (Microsoft Corp., Redmond, WA)
routine was used to extract temperatures from 7-day
composite images (3 days forward and backward from
the haul date), by using a 3x3 cell window at 1-km
resolution. Therefore, a 9-km2 area of coverage around
each coordinate position was used to extract sea surface
temperature. Within the 3x3 cell search radius, the pixel
representing the warmest temperature was used to avoid
temperatures affected by cloud coverage.
Data analysis
Missing temperature data Sea surface temperature
values could not be obtained for 33% of the VTR data
and 10% of the observer data because of either missing
coordinate positions on the VTR logs or bad satellite
images. For these fishing events, sea surface tempera-
ture was predicted by using a linear regression based
on year, month, and area. For the observer data, area
was defined as either Hudson Canyon or Virginia Beach
access areas (r2=0.88). For the VTR data, the vessel's
home state served as a proxy for area fished because
most of the missing temperature values were due to
missing coordinate positions (r2=0.86).
Modeling approach Generalized linear model (GLM)
and generalized additive model (GAM) fitting techniques
were used to understand and predict bycatch rates of sea
turtles in relation to environmental variables, fishing
practices, and gear characteristics in the commercial
sea scallop fishery. Unlike classic linear regression
models, GLMs and GAMs allow for nonlinearity and
nonconstant variance structures in the data (Guisan
et al., 2002). GAMs differ from GLMs in that smooth
functions replace the linear predictors in GLMs (Hastie
and Tibshirani, 1990). Smooth functions, or "smoothers,"
summarize the trend of a response measurement as a
function of multiple predictors (Hastie and Tibshirani,
1990) and therefore some form of parametric relation-
ship between the response and explanatory variables
is not assumed (Guisan et al. 2002). Both frameworks
have been used to model abundance or probability events
as a function of environmental variables (Frost et al.,
1999; Denis et al., 2002; Guisan et al., 2002; Hamazaki,
2002).
A modeling approach to estimate bycatch of sea tur-
tles in the sea scallop dredge fishery was preferred over
the ratio method (Cochran, 1977) that has been used
to estimate bycatch of marine mammals and turtles
in other fisheries (Epperly et al., 1995; Rossman and
Merrick, 1999). With the ratio method, the observed
number of sea turtles divided by the observed effort is
used to calculate a bycatch rate, and this rate is then
multiplied by total commercial fishing effort to derive
a bycatch estimate. Bycatch data in the sea scallop
dredge fishery violate the underlying assumptions of the
ratio method (Cochran, 1977), largely because sea turtle
bycatch is binomially distributed with a nonconstant
variance. An analyis of binary response data derived
from a statistical model allows bycatch rates to be pre-
dicted by using factors that account for variability in
bycatch. Moreover, stratifying bycatch rates according
to these factors will reduce variability in total bycatch
estimates. For the sea turtle data analyzed in the pres-
ent study, the GLM approach provided a more accurate
and less biased mortality estimate than that derived
using the ratio method.
674
Fishery Bulletin 102(4)
GAM smoothers Before a GLM was constructed, a
GAM helped group continuous variables into catego-
ries. Fitting the GLM model with categorized variables
was necessary to extrapolate bycatch rates in order to
derive a total estimate of the bycatch of sea turtles in
scallop dredges in the controlled access areas. All of the
variables tested in the GLM model were first fitted to
a GAM, in which the parameters of the continuous pre-
diction variables were estimated by a smoothing spline.
Variable values were grouped according to whether they
had a positive or negative influence on the bycatch rate
(i.e., the group explained more or less of the bycatch
rate).
Development of a GLM bycatch model Because bycatch
events were counts ranging from zero or one, a logistic
regression was used to model the probability of sea
turtle bycatch (GLM function, SPLUS 6.1, Seattle, WA).
Each dredge haul is a data point and the response was
whether turtle bycatch was zero or one. Probability of
sea turtle bycatch (p) was calculated as
p = ey 1 1 + ey
y = P0+P1x1+P2x2+...+ pixi,
where pt is a parameter coefficient;
xl is a predictor variable; and
y is a sea turtle bycatch event.
Dredge hauls are assumed to be independent because
turtles were never simultaneously caught in both dredges
operating from a vessel during a single haul.
A forward stepwise selection method was used to de-
termine the best fitting model. Model parameters were
estimated by maximizing the log-likelihood function.
The null model was the first model in the stepwise
process and was specified with a single intercept term
as
H0: logiturtle bycatch) = 1.
At each step, a new variable was added to the null model
(Appendix 1) and tested against the former model formu-
lation (ANOVA function, chi-square test) to determine
the better fitting model. A preliminary assessment of a
broad suite of gear characteristics and environmental
factors indicated that 10 variables could significantly
affect bycatch rates. The main effects of each variable
were tested in the stepwise selection process as well
as the interaction between season and temperature.
Because the order of the predictor variables affects their
significance, main effects were entered in various orders.
If a P-value was less than 0.05, then the additional vari-
able was considered to explain more of the variability in
bycatch than a model without that variable. Each new
model was also compared against the former model by
using the Akaike information criterion (AIC), which is
defined as
A/C = -21og(L(0ly)) + 2.K',
where log(L(6H y )) = the numerical value of the log-likeli-
hood at its maximum point; and
K = the number of estimable parameters
(Burnham and Anderson, 20021.
The AIC is a measure of the level of parsimony, defined
as a model that fits the data well and includes as few
parameters as necessary (Palka and Rossman, 2001). If
the AIC value decreases, the new combination of vari-
ables in the model fit the data better.
To investigate whether the bycatch data are over-
dispersed, that is. where the sampling variance exceeds
the theoretical variance, the GLM model was refitted
by using a quasi-likelihood function. When data are
over-dispersed, the estimated over-dispersion parameter
is generally between 1 and 4 (Burnham and Ander-
son, 2002). The over-dispersion parameter fitted to the
global model was 0.61, indicating these data were not
over-dispersed and error assumptions of the binomial
model were appropriate for analyzing these data.
Alias patterns in the final model were examined to
assess correlation among the explanatory variables.
The fit of the final model was assessed by plotting the
observed turtle bycatch against the predicted turtle
bycatch. The r2 value indicated how well predictions
from the linear model fit the actual data.
Bycatch rate estimates The spatial and temporal strati-
fication of bycatch rates in each of the controlled access
areas was determined by the explanatory variables in
the best-fitting GLM. Parameter estimates from the
model were used to predict the bycatch rate for each
stratum.
The coefficient of variation (CV) for each bycatch
rate was estimated by bootstrap resampling (Efron and
Tibshirani, 199.3). The resampling unit was a scallop
dredge haul. Replicate bycatch rates were generated
with the best-fitting GLM model, by sampling with
replacement 1000 times from the original data set.
The CV was defined as the standard deviation of the
bootstrap replicate bycatch rates in a stratum divided
by the bycatch rate for that stratum estimated from the
original data. Variances and CVs of combined estimates
were based on means weighted by their respective vari-
ances (Wade and Angliss, 1997).
Total bycatch The total estimated turtle bycatch in
each stratum was calculated as the product of predicted
bycatch per dredge haul (i.e., the predicted bycatch
rate) for that stratum and the total number of dredge
hauls accomplished by the commercial fishery in that
stratum:
^ Predicted bycatch
V Dredge hauls t
where ; = stratum
■ [Total dredge hauls),.
Murray: Magnitude and distribution of sea turtle bycatch in the sea scallop dredge fishery
675
Table 1
Analysis of deviance for significant factors a
to contruct a model to predict total bycatch
ffectir
AIC =
igsea turtle bycatch. Significant factors
Akaike information criterion.
were used to stratify bycatch rates and
Model
df
Deviance
Residual df
Residual deviance
Pfchil
AIC
null model only
18,071
405.29
407.2989
n ui 'I + year
1
-2.33
18,070
402.96
0.12626
406.9611
null + season
2
19.81
18,069
385.48
0.00004
391.4807
null + season + temp
1
9.34
18,068
376.13
0.00223
384.1319
null + season + temp + depth
2
17.23
18,066
358.89
0.00018
370.8983
null + season + temp + depth + time of day
1
7.86
18,065
351.03
0.00503
365.0318
null + depth + time of day + season (temp)
1
1.64
18,064
349.39
0.20011
365.3903
null + season + temp + depth + time of day
+ state
4
3.77
18,061
347.25
0.43746
369.2579
null + season + temp + depth + time of day
+ dredge frame width
2
3.27
18.063
347.76
0.19487
365.7611
null + season + temp + depth + time of day
+ number of up and down chains
1
0.54
18,064
350.48
0.45955
366.4849
null + season + temp + depth + time of day
+ number of tickler chains
1
3.18
18,064
347.84
0.07436
363.8480
Annual bycatch was the sum of the stratified bycatch
estimates. The finite population correction factor (Co-
chran, 1977) was applied to bycatch estimates in stratas
where the observer coverage was greater than 10%.
Number of dredge hauls in the VTR database without
coordinate positions (32%) were prorated between the
stratified areas according to the percentage of dredge
hauls with known coordinates from the same year,
state, and stratified areas.
Results
Observed bycatch
Nine and 16 turtle bycatch were observed in 2001 and
2002, respectively, in the Hudson Canyon controlled
access area. Of the 25 turtles taken in the Hudson
Canyon area across both years, 21 (84%) were taken
during summer months. Two turtle bycatch were
observed in the Virginia Beach access area during fall
2001 — the only time when there was observer coverage
in this area across both years.
GAM smoothers
Plots of the smoothed functions in the GAM revealed
whether the continuous variable in the model explained
any error in the bycatch rate estimates. For example,
a plot of the smooth function for depth as a covariate
revealed that bycatch rates may be higher between 49
m (27 fm) and 57 m (31 fm) and lower around this zone
(Fig. 2). Likewise, a plot of the smooth function for tem-
perature as a covariate revealed that bycatch rates may
be higher above 19°C. These plots helped bin the continu-
ous variables into categories (Appendix 1) which could
then be tested in the GLM. All continuous variables in
the GAM were categorized in a similar manner.
GLM bycatch model
Significant factors affecting sea turtle bycatch were
season, sea surface temperature, depth zone, and time-
of-day (Table 1). These variables were significant despite
the order in which they were tested in the model. The
model with the lowest AIC value was considered the
"best" model, although time-of-day could not be included
in the final model to predict bycatch rates. This level of
information is not recorded in commercial fisheries log-
books; therefore bycatch rates based on time-of-day could
not be extrapolated to total bycatch. Width of the scallop
dredge frame, number of tickler chains, and number of
up and down chains were not significant variables.
Model fit
The number of predicted sea turtle bycatch closely
matched the observed bycatch in both years in all
bycatch strata (Table 2). Strata were defined according
to variables identified in the GLM as having a significant
effect on bycatch rates. The relationship between actual
and observed takes was strong (r2=0.93), indicating that
the predictions from the model fitted the data well.
Bycatch rate estimates
Bycatch rates were stratified by season, temperature inter-
val, and depth zone (Table 3). Because year was not a
676
Fishery Bulletin 102(4)
10 -
y'
0 -
§• -10-
-20
20 25 30 35 40 45
Depth (fm)
10 -
'*■*
0
'"'''-•-•--•.-._f^^^
s (temperature)
o o
^/
-30 _
0 5 10 15 20 25 30
Temperature (C)
Figure 2
Partial fits for the general additive model (GAM) of sea turtle bycatch with
depth and temperature as covariates, showing the relationship estimated
by a smoothing spline. Depths between 27 fm (49 ml and 31 fm (57 m). and
temperatures above 19°C, have a positive influence on the bycatch rate.
95^ confidence bands are also shown. All continuous variables in the GAM
were categorized in a similar manner. The "s" on the y-axis represents a
smoothed function for each variable and explains the effect of each variable
on sea turtle bycatch per haul.
significant factor in the final model, predicted bycatch
rates were the same for 2001 and 2002. Highest sea turtle
bycatch rates occurred during the summer season (Aug-
Sep), in temperatures warmer than 19C, in water depths
from 49 to 57 m. Lowest bycatch rates occurred during the
fall (Oct-Dec) and spring (May-June), in temperatures
cooler than 19 C, and in water depths less than 49 m.
Total bycatch
The total estimated bycatch of sea turtles in the Mid-
Atlantic controlled access areas in 2001 and 2002 com-
bined was 169 animals (CV=55.3) (Table 4). Of this total,
164 animals (97'* ) were caught in the Hudson Canyon
area: 69 (42', i in 2001 and 95 (58%) in 2002. Total esti-
Murray: Magnitude and distribution of sea turtle bycatch in the sea scallop dredge fishery
. 677
Table 2
Observec
versus
predicted number of turtle byeatch, by stratum. 2001 and 2002. Obs.=
observed; Pred.
=predicted.
Spr
ng
Summer
]
Fall
Number of
Number of
Number of
Number of
Number of
Number of
obs.
pred.
obs.
pred.
obs.
pred.
Water depth
Temp.
turtle bycatch
turtle bycatch
turtle bycatch
turtle bycatch
turtle bycatch
turtle bycatch
Shallow
High
0
0
0
0
0
0
Low
0
0
0
0
0
0
Mid-depth
High
2
1
17
16
1
2
Low
0
0
0
0
1
0
Deep
High
1
1
4
5
1
0
Low
0
0
0
0
0
0
Table 3
Stratification of turtle bycatch
rates with associated CVs.
N.C.E.=no commercial effort.
Water depth
Temperature
Spring (May- June l
Summer (Aug-Sepi
Fall(Oct-Dec)
Shallow (<49 ml
High(>19°C)
0.0000027(82.5)
0.0000052(62.1)
0.0000030(87.71
Low(<19°C)
0.0000002(99.5)
N.C.E.
0.0000002(106.6)
Mid-depth (49-57
ml High(>19°C)
0.0032018(64.9)
0.0061179(25.4)
0.0035838(57.2)
Low(<19°C)
0.0002117(95.4)
N.C.E.
0.0002371(98.3)
Deep(>57m)
High(>19°C)
0.0007578(73.8)
0.0014512(41.9)
0.0008485(80.5)
Low(<19°C)
0.0000500(92.91
N.C.E.
0.0000560(103.8)
Table 4
Total bycatch estimates by
year and
season
with
weighted CVs (%)
N.C.E.
=no commercial effort.
Spring
Summer
Fall
Total
Hudson Canyon
2001
10(89.2)
50(61.5)
9(105.8)
69
2002
13(89.2)
78(61.5)
4(105.8)
95
Virginia Beach
2001
N.C.E.
N.C.E.
5(105.8)
5
2002
0
0
N.C.E.
0
Totals
23
128
18
169(55.31
mated bycatch of turtles in the Virginia Beach area was
five animals in 2001 and zero animals in 2002.
Across both areas, the highest bycatches occurred in
summer (128 turtles; 76%), followed by spring (23 tur-
tles; U7( ) and fall (18 turtles; 10%) (Table 5). One hun-
dred thirty-two (78%) (CV=49.6) sea turtles were caught
in the mid-depth zone from 49 to 57 m, whereas 37 (22%)
(CV=59.6) sea turtles were caught in waters deeper
than 57 m. One-hundred fifty-eight (93%) (CV=51.2) sea
turtles were caught in waters warmer than 19°C, and 11
(7%) (CV=74.9) in waters cooler than 19°C.
Discussion
Use of bycatch models
Generalized linear and generalized additive models
help to identify environmental variables or fishing
practices that influence the probability of sea turtle
bycatch. In estimating total mortality, bycatch rates can
then be stratified according to these factors, reducing
unexplained variability in the total estimate. More-
over, understanding factors that lead to a high or low
678
Fishery Bulletin 102(4)
Table 5
Total bycatch estimates by season, depth.
and temperat
jre strata in
Hudson Canyon and Virginia Beach controlled access areas
in 2001 and 2002 with 95<7r confidence intervals. Spring=May-Jun;
Summer=Jul
-Sep; Fall=
=Oct-Dec. N.E.C
= no commercial
effort; N.O.=no observer
coverage.
Water depth
Temperature
2001
2002
Total
Spring
Summer
Fall
Spring
Summer
Fall
Shallow l<49 ml
High(>19°C)
0
0
0
0
0
0
0
Low«19°Ci
0
N.O.
0
0
N.C.E.
0
0
Mid-Depth (49-57 mi
High(>19°C)
6(0-13)
37(21-59)
2(0-5)
8(0-211
65(34-961
5(0-9)
123
Low(<19°C)
2(0-8)
N.C.E.
4(0-191
1(0-2)
N.C.E.
2i0-10i
9
Deep (>57 ml
High(>19°C)
2(0-51
13(4-25i
2(0-51
4i0-lll
13(4-24)
1 (0-1)
35
Low«19°C)
0(0-11
N.C.E.
1 (0-6)
0(0-1)
N.C.E.
1(0-2)
2
Total
10
50
9
13
78
9
169
probability of bycatch can motivate bycatch mitigation
research. Finally, the ability to predict bycatch on the
basis of explanatory variables allows one to examine the
relative effectiveness of different management measures
designed to reduce bycatch (Kobayashi and Polovina2).
Ultimately this framework can improve the assessment
of threats to turtles and broaden conservation options.
Magnitude of bycatch
During May-December in 2001 and 2002, an estimated
169 animals were captured incidentally by commercial
sea scallop dredge vessels in two areas of the Mid- Atlan-
tic Bight. Throughout the entire Mid-Atlantic Bight, the
magnitude of bycatch was probably larger, particularly
because the factors associated with the high bycatch
rates were not specific to the controlled access areas. Of
the 11 observed turtles measured for size, 9 (82%) were
between 70-80 cm straight carapace length (the large
juvenile stage). Stage class models indicate that the long-
term survivability of loggerhead sea turtles is sensitive
to mortality at this life stage (Crouse et al., 1987).
Factors influencing bycatch
The incidental capture of turtles occurs where there
is overlap between fishing effort and turtle habitat.
The elevated probability of turtle bycatch occurring
in warm waters, during summer, at depths between
50 and 60 m is consistent with the habitat regime of
loggerhead sea turtles in the Mid-Atlantic (Shoop and
Kenney, 1992; Epperly et al., 1995; Coles and Musick,
2000). During the oceanic phase of their life cycle, sea
turtles occupy habitats at specific temperatures or with
bathymetric features that concentrate prey and other
areas of enhanced productivity (Polovina et al.. 2000).
In Mid-Atlantic waters, high aggregations of loggerhead
sea turtes have been observed in the summer, in waters
22-49 m deep, at temperatures from 20° to 24°C (Shoop
and Kenney, 1992). In the Hudson Canyon and Virginia
Beach controlled access creas, the bycatch of sea turtles
was associated with habitat conditions rather than gear
characteristics. From these findings, it may be possible
to predict future hotspots for sea turtle bycatch in the
controlled access areas where fishing effort and sea
turtles overlap in time and space. These hotspots may
be centered over the portion of the Hudson Canyon
where depths are between 50 and 60 m. after waters
warm to 19 C.
Because of the low amount of observer data in the
Virginia Beach area, predicted bycatch rates for this
area were based largely on conditions within the Hud-
son Canyon area. Sea scallop fishing effort occurs year-
round both north and south of the Hudson Canyon,
and high concentrations of loggerhead sea turtles (de-
termined from migratory patterns) exist in spring and
fall from North Carolina to northern Maryland ( Shoop
and Kenney, 1992). It is probable that the distribution
of turtles and scallop fishing effort co-occur in other
regions of the Mid-Atlantic, particularly south of the
Hudson Canyon. The scallop dredge fishery in the Mid-
Atlantic is a complex, dynamic system; there may be
other factors influencing the bycatch of sea turtles in
the fishery south of the Hudson Canyon that were not
observed. However, without additional data on turtle
interactions in these areas, it is unwise to extrapolate
bycatch estimates beyond the scope of the data in this
analysis.
2 Kobayashi. D. R., and J. J. Polovina. 2000. Time/area
closure analysis for turtle take reductions. Appendix C,
Environmental Impact Statement, FMP for Pelagic Fisher-
ies of the Western Pacific, 44 p. NMFS Honolulu, Hawaii,
96822.
Conservation management options
Time and area closures Models of turtle migrations can
be used to predict interactions with fisheries in time
and space to maximize the efficiency of time and area
Murray: Magnitude and distribution of sea turtle bycatch in the sea scallop dredge fishery
679
closures (Morreale, 1996). The results of this analy-
sis indicate that bycatch rates are affected by season,
depth, and sea surface temperature. Within certain
months and depth zones, therefore, the time when sea
surface temperature reaches a threshold level may be
the time to trigger an area closure. For example, this
type of management approach has been taken in the
southeastern United States to regulate turtle bycatch
in the large-mesh gill-net fishery.3 The timing of sea-
sonally adjusted area closures is based upon analyzing
sea surface temperatures in relation to the presence
or absence of sea turtles throughout the area (Epperly
et al., 1995; Epperly and Braun-McNeill4). In addition,
temperature thresholds currently trigger area closures
in the southern California driftnet fishery during El
Nino conditions to prevent the incidental capture of log-
gerhead sea turtles.5
Results from the present study can be used to help
evaluate potential bycatch reduction under different
management scenarios, given certain assumptions. For
example, had the portion of the Hudson Canyon con-
trolled access area between depths of 49 and 57 m been
closed after surface waters reached 19°C in the summer
(the stratum with highest bycatch), the closure would
have reduced bycatch by 39%. For this estimate, it is
assumed that surface temperatures remain above 19°C
throughout the summer and drop below 19°C thereafter.
Further, this bycatch reduction scenario also assumes
that fishing effort shifts proportionately to the fall and
spring season within the same depth zone and that
bycatch rates remain the same as those that are cal-
culated. Alternatively, fishing effort could shift within
a season to shallow and deep depth zones if scallop
catch-per-unit-of-effort were not affected. Under this
assumption, bycatch would be reduced by 60'"< under
the same time and area closure. However, unless there
are concurrent reductions in fishing effort, bycatch
reductions achieved by these measures could well be
offset by increases in bycatch in other depth strata
and seasons.
Gear or fishing modifications Management actions to
modify gear or fishing practices can be evaluated in a
similar manner. For instance, this analysis indicates
that bycatch rates are influenced by the time-of-day
when dredges are in the water. Time-of-day was not used
to stratify bycatch rates or to extrapolate total bycatch
estimates because of limitations in the fishing effort
data ( VTR records). If time-of-day had been incorporated
into the bycatch model, the model would have predicted
higher bycatch rates when dredges were set between 4
am and 4 pm (day tows). If the stratum with the highest
bycatch rate (summer, high surface temperatures, and
depths between 49 and 57 m), had been further strati-
fied by time-of-day, the model would have predicted a
bycatch rate of 0.008 sea turtles/dredge hauls during the
day, and 0.002 turtles/dredge hauls during the night. If
all the commercial vessels had been fishing during the
day in this stratum (;? = 6352 dredges in 2001), the esti-
mated bycatch would have been 51 turtles. If the vessels
had been fishing during the night, the total estimated
bycatch would have been 13 turtles. According to these
rates and effort, restricting vessels to night-time tows
between the hours of 4 pm and 4 am has the potential to
reduce bycatch by 75% in this particular stratum.
Although specific gear characteristics did not show
a strong relationship to sea turtle bycatch in this
analysis, further work should be conducted to evaluate
whether specific gear characteristics could be modified
to decrease bycatch. For example, the near significance
with the model incorporating number of tickler chains
(P=0.07) warrants further testing of this gear charac-
teristic. Tickler chains cover the mouth of the dredge in
a grid-like configuration with the vertical up and down
chains. The number of chains on the bag and distance
between the chains may help to prevent sea turtles from
entering the dredge bag. This dredge configuration is
currently being tested for sea turtle bycatch reduction
in the Hudson Canyon area (DuPaul and Smolowitz6).
Further research should also examine the behavior
of sea turtles in relation to dredge gear for a more
complete understanding of how and when turtles are
entrapped.
Sea turtles and scallop dredge interactions cannot be
viewed in isolation from other gear types and conserva-
tion measures. Some fisheries that co-occur with sea
turtles may have an equal, if not greater, impact on
turtles than do scallop dredges (e.g., the shrimp trawl
fishery in the Gulf of Mexico (Henwood and Stuntz,
1987]). Changes in sea turtle abundance, or shifts in
fishing effort, may increase the likelihood of encounters
in both net and dredge fisheries. If environmental condi-
tions associated with high bycatch rates in the Hudson
Canyon and Virginia Beach areas are consistent across
years, it may be possible to anticipate and deter future
interactions from occurring.
Acknowledgments
I would like to thank Debra Palka and Marjorie Ross-
man for help with analytical and statistical approaches
to bycatch estimation. Andy Solow and Andy Beet at the
Marine Policy Center, Woods Hole Oceanographic Insti-
tute, also provided guidance in the statistical analysis.
David Mountain provided invaluable help in acquiring
3 Final Rule. FR 67: 71895-71900. 3 December 2002.
4 Epperly, S. P. and J. Braun-McNeill. 2002. Unpubl. data.
The use of AVHRR Imagery and the management of sea turtle
interactions in the Mid-Atlantic Bight. NMFS Southeast
Fisheries Science Center, Miami, Florida, 33149.
5 Final Rule, FR 68: 69962-69967, 16 December 2003.
6 DuPaul. W. P., and R. Smolowitz. 2003. Unpubl. data.
Industry trials of a modified sea scallop dredge to minimize
the catch of sea turtles. Virginia Institute of Marine Sci-
ence, Gloucester Point, Virginia, 23062, and Coonamessett
Farm, East Falmouth, Massachusetts, 02536.
680
Fishery Bulletin 102(4)
sea surface temperature for
data. Frederic Serchuk, Richa
Marjorie Rossman, and Pau
Fisheries Science Center all
of the manuscript. Jeffrey S
mous reviewers provided val
peer review. Finally, I wish to
collected data on interactions
sea scallop dredge fishery.
the Observer and VTR
rd Merrick, Debra Palka,
Rago at the Northeast
provided initial reviews
eminoff and two anony-
uable comments during
thank the observers who
between turtles and the
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Appendix 1
Categorical variables
examined in an analysis of factors affecting sea turtle bycatch in the sea scallop dredge fishery. Frequency
of observed dredges ir
each category is also shown.
Number of
Number of
Number of
Number of
observed
observed
observed
observed
dredges in
dredges in
dredges in
dredges in
Hudson
Virginia
Hudson
Virginia
Variable
Category
Canyon 2001
Beach 2001
Canyon 2002
Beach 2002
Year
2001 or 2002
9493
520
8059
0
Season
Spring = May and June
3919
0
1987
0
Summer = July, August, September
2719
0
3764
0
Fall = October, November, December
2855
520
2308
0
State in which
Connecticut
199
0
595
0
scallops were landed
Massachusetts
4925
0
5628
0
New Jersey
2849
0
740
0
Rhode Island
112
0
474
0
Virginia
1408
520
622
0
Frame width'
Small = 3.0-3.9 m ( 10-13 ft)
560
0
443
0
category
Medium = >3.9 m and <4.5 m (15 ft)
3987
122
3013
0
Large = <4.5 m-4.8 m ( 15-16 ft )
4946
398
4603
0
Number of up and
Code 1 = 0 chains
4256
520
2171
0
down chains used-
Code 2 = 1-4 chains
4089
0
5378
0
Code 3 = >4 chains
1148
0
510
0
Number of tickler
Code 1 = <2 chains
6890
520
4469
0
chains used3
Code 2 = >2 chains
2603
0
3590
0
Time-of-day
Day = 4 am-4 pm
5514
346
4854
0
Night = 4 pm-4 am
3979
174
3205
0
Sea surface
Hi = >19'C
3910
518
4883
0
temperature
Low = <19°C
5583
2
3176
0
Depth
Shallow = 40-<49 m (22-27 fmi
1089
42
782
0
Mid-Depth = 49-57 m (27-31 fin)
3371
280
3642
0
Deep = >57-88 m (31-48 fm)
5033
198
3635
0
; Width of the dredge fra
me.
2 Vertical chains attache
i to the sweep on the bottom of the dredge that
prevent rocks from entering the chain
bag. Number of up
and down chains
were influenced by bottom type.
3 Horizontal chains attac
hed to the sweep on the bottom of the dredge that help stir up contents of the sea bottom. Number of ti<
kler chains were
influenced by bottom t\
pe.
682
Abstract — Numerous studies have
applied skeletochronology to sea turtle
species. Because many of the studies
have lacked validation, the applica-
tion of this technique to sea turtle
age estimation has been called into
question. To address this concern, we
obtained humeri from 13 known-age
Kemp's ridley (Lepidochelys kempii)
and two loggerhead (Caretta caretta)
sea turtles for the purposes of examin-
ing the growth marks and comparing
growth mark counts to actual age. We
found evidence for annual deposition
of growth marks in both these spe-
cies. Corroborative results were found
in Kemp's ridley sea turtles from a
comparison of death date and amount
of bone growth following the comple-
tion of the last growth mark (n=76).
Formation of the lines of arrested
growth in Kemp's ridley sea turtles
consistently occurred in the spring for
animals that strand dead along the
mid- and south U.S. Atlantic coast.
For both Kemp's ridley and loggerhead
sea turtles, we also found a propor-
tional allometry between bone growth
• humerus dimensions) and somatic
growth (straight carapace length i,
indicating that size-at-age and growth
rates can be estimated from dimen-
sions of early growth marks. These
results validate skeletochronology as
a method for estimating age in Kemp's
ridley and loggerhead sea turtles from
the southeast United States.
Validation and interpretation of annual
skeletal marks in loggerhead (Caretta caretta)
and Kemp's ridley (Lepidochelys kempii) sea turtles
Melissa L. Snover
Duke University Marine Laboratory
135 Duke Marine Lab Road
Beaufort, North Carolina 28516
Present addresss: Pacific Fisheries Environmental Laboratory
1352 Lighthouse Ave.
Pacific Grove, California 93950
E-mail address: melissa snover g noaa gov
Aleta A. Hohn
Center for Coastal Fisheries and Habitat Research
National Marine Fisheries Service, NOAA
101 Pivers Island Road
Beaufort, North Carolina 28516
Manuscript submitted 1 5 August 200,3
to the Scientific Editor's Office.
Manuscript approved for publication
ii June 2004 by the Scientific Editor
Fish. Bull. 102:682-692 (2004 I.
The basic tenet of skeletochronology is
that bone growth is cyclic and has an
annual periodicity in which bone for-
mation ceases or slows before new, rel-
atively rapid bone formation resumes
(Simmons, 1992; Castanet et al„ 1993;
Klevezal, 1996). This interruption of
bone formation is evidenced within
the primary periosteal compacta by
histological features, which take two
forms in decalcified and stained thin-
sections. The most common form is a
thin line that appears darker than the
surrounding tissue, termed the "line
of arrested growth" (LAG) (Castanet
et al., 1977). The second, less-common
form is a broader and less distinct line
that also stains darker, referred to as
an annulus (Castanet et al., 1977).
Alternating with LAGs or annuli are
broad zones that stain homogeneously
light, and represent areas of active
bone formation. Together, a broad
zone followed by either a LAG or an
annulus represents a skeletal growth
mark (GM) (Castanet et al., 1993). To
apply skeletochronology to a species,
the annual periodicity of the GM must
be validated.
Validation studies are necessary
not only to confirm the annual nature1
of the GM but also to identify and in-
terpret anomalous LAGs. Anomalous
LAGs that are a common problem in
skeletochronology studies of reptiles
and amphibians include double (Chin-
samy et al., 1995; El Mouden et al.,
1997; Guarino et al., 1998), splitting
(Guarino et al., 1995; 1998; Coles et
al., 2001), and supplemental (Guarino
et al, 1995; Lima et al., 2000; Tren-
ham et al., 2000) lines. In addition to
anomalous LAGs, there are two other
difficulties typical in skeletochronol-
ogy studies; compression of LAGs at
the periphery of the bone and resorp-
tion of the innermost LAGs. In older
animals the GMs are compressed at
the outer periphery of the bone as a
result of decreased growth. Francil-
lon-Vieillot et al. (1990) term this
phenomenon "rapprochement" and it
is a problem when the LAGs become
too close together to be differentiated
— usually in the small phalangeal
bones used in amphibian studies lEg-
gert and Guyetant. 1999; Lima et al.,
2000; Leclair et al.. 2000).
In addition to anomalous and com-
pressed LAGs, the loss of early GMs
through endosteal resorption is an-
other problem with skeletochronol-
ogy. Although this does not present a
problem with most amphibian species
(Kusano et al., 1995; Castanet et al.,
1996; Sagor et al., 1998), the prob-
lem is extreme in skeletochronology
studies of loggerhead (Caretta caretta;
Klinger and Musick. 1995; Zug et al.,
1995; Parham and Zug, 1997), green
Snover and Hohn: Validation and interpretation of skeletal marks in Caretta caretta and Lepidochelys kempu
683
Table 1
Species and history of known
-age sea turtles analyzed in this study.
Sample
Species
History during captivity
Age (yr)
LK-1
Lepidochelys kempu
Captive for first year, then released
5.0
LK-2
L. kempii
Captive for first year, then released
6.5
LK-3
L. kempii
Captive for first year, then released
4.5
LK-4
L. kempii
Tagged and released after hatching
1.27
LK-5
L. kempii
Tagged and released after hatching
1.70
LK-6
L. kempii
Tagged and released after hatching
1.72
LK-7
L. kempii
Tagged and released after hatching
2.37
LK-8
L. kempii
Tagged and released after hatching
2.37
LK-9
L. kempii
Tagged and released after hatching
3.25
LK-10
L. kempii
Tagged and released after hatching
2.0
LK-11
L. kempii
Tagged and released after hatching
2.75
LK-12
L. kempii
Tagged and released after hatching
3.0
LK-13
L. kempii
Tagged and released after hatching
4.25
CC-1
Caretta caretta
Captive during entire life
29.4
CC-2
C. caretta
Captive for first two years, then released
8.0
(Chelonia mydas; Zug and Glor, 1998; Zug et al., 2002)
and Kemp's ridley (Lepidochelys kempii; Zug et al.,
1997) sea turtles. In each of these studies, the authors
used various protocols to estimate the number of lay-
ers lost. Any protocol estimating the number of layers
lost to resorption relies on the concept that the spatial
pattern of the LAGs is representative of the growth of
the animal. To confirm this assumption, researchers
must establish a correlation between bone dimensions
and body size (Hutton, 1986; Klinger and Musick, 1992;
Leclair and Laurin, 1996).
Two of the studies that have applied skeletochronology
to sea turtles have demonstrated annual GMs in both
juvenile (Klinger and Musick, 1992) and adult (Coles et
al., 2001) loggerhead sea turtles. Numerous additional
studies have applied skeletochronology to sea turtles.
To date, the technique has been applied to loggerhead
(Zug et al., 1986; Zug et al, 1995; Bjorndal et al., 2003),
green (Bjorndal et al., 1998; Zug and Glor, 1998; Zug
et al., 2002), Kemp's ridleys (Zug et al., 1997), and
leatherback [Dermochelys coriacea) (Zug and Parham,
1996) sea turtles. What is needed for the appropriate
application of skeletochronology to sea turtle species
is additional validation of annual GMs and a guide to
their interpretation. Furthermore, because resorption is
a problem in sea turtle bones, the validation of a pro-
portional allometry between bone and somatic growth
is necessary to enable back-calculation.
In this study, we address each of these issues for
Kemp's ridley and loggerhead sea turtles by examining
humeri from known-age animals. We analyzed each
humerus without prior knowledge of the animal's age
and we present the results of our analyses, including
reinterpretations of bones for which we were incorrect
in our age assessments. The purpose of this study was
to use known-age samples both to validate the likeli-
hood that GMs are annual and as a learning tool for the
best guide to interpreting GM in wild animals.
Materials and methods
We obtained samples from two known-age loggerhead
and 13 known-age Kemp's ridley sea turtles (Table 1).
In addition, we collected samples from 240 wild logger-
head and 262 wild Kemp's ridley sea turtles. With the
exception of one loggerhead, CC-1, all of the sea turtles
died in the wild and samples were retrieved from the
carcasses. Sample CC-1 died in captivity.
Sample preparation
Zug et al. (1986) analyzed skeletal elements of the cra-
nium and right forelimb of loggerhead sea turtles and
determined that the humerus was most suited to skeleto-
chronology studies. Therefore, we also used the humerus.
Specimens arrived as either dried bones or whole flippers.
For flippers, we dissected out the humerus, which v/as
then flensed, boiled, and air-dried for at least two weeks.
We cross-sectioned each humerus at a site just distal to
the deltopectoral crest. At this site, the ratio of cortical
to cancellous bone is highest (Zug et al., 1986), and the
region immediately distal to the insertion scar of the
deltopectoral muscle on the ventral side of the bone maxi-
mizes that ratio (see Zug et al., 1986 for diagrams of the
loggerhead sea turtle humerus). This site also provided
a landmark that allowed us to section at equivalent sites
on every humerus.
We removed 2-3 mm thick sections at that site us-
ing a Buehler® isomet low speed saw. This section was
684
Fishery Bulletin 102(4)
fixed in 109c formalin then decalcified by using a com-
mercial decalcifying agent (RDO, Apex Engineering
Products Corporation, Calvert City, Kentucky). Time
to decalcification varied with the size of the bone and
the strength of the solution, usually between 12 and 36
hours. Following decalcification, 25-f.im thick cross-sec-
tions were made by using a freezing-stage microtome.
Sections were stained in Erlich's hematoxylin diluted
1:1 with distilled water (Klevezal, 1996) and mounted
on slides in 100% glycerin.
Known-age sea turtles
We received the humeri from each of two captive, known-
age loggerhead sea turtles after they died (Table 1). The
first specimen, CC-1, was held in an outdoor tank during
the summer months and inside a greenhouse during the
winter months (this turtle was the same captive female
noted in Swartz, 1997). The second, CC-2, was raised in
captivity for two years then released from Panama City,
Florida, into the Gulf of Mexico.
For the Kemp's ridley sea turtles, we received humeri
from 13 dead known-age animals (Table 1). The head-
start Kemp's ridleys were raised in captivity for one
year, then released as part of a binational program oper-
ated jointly by state and federal U.S. agencies and the
Instituto Nacional de la Pesca (INP) of Mexico (Klima
and McVey, 1995). The coded-wire-tagged (CWT) Kemp's
ridley sea turtles were tagged and released as hatch-
lings. This tagging program is operated jointly by the
U.S. National Marine Fisheries Service (NMFS) Galves-
ton Laboratory and the INP of Mexico as a means of
gaining a better understanding of the early life history
of the Kemp's ridley sea turtle (Caillouet et al., 1997).
Using the methods described previously, we prepared
stained thin-sections from the humeri. Without prior
knowledge of the animal's history, the number of visible
LAGs was quantified for each bone and a minimum age
estimated. Our age estimates were then compared to
the age information available for each animal.
Indirect validation of annual growth marks
Peabody (1961) and Castanet et al. (1993) suggested that
the correlation between the width of the last zone formed
and the date of death provided an indirect means of vali-
dating that deposition of the LAG occurs annually and at
the same time of year for an individual population. We
applied this method to 76 wild Kemp's ridley sea turtles
for which humeri displayed between one and five LAGs.
Each of these animals had stranded dead along the
Atlantic coast between Maryland and North Carolina.
Thin-sections were prepared of the humeri as described
above. We quantified the width of the last zone formed
by measuring the outside diameter of the whole section
(D0) and the diameter of the last competed LAG (DL),
between the lateral edges of the bone on an axis paral-
lel to the dorsal edge. The amount of bone growth after
the last LAG (D0-DL) was plotted against the Julian
stranding date, with the assumption that stranding
date approximated date of death. Least-squares linear
regressions were fitted to the data.
Validation of the relationship between
LAG diameter and body size
In order to relate GM diameters to somatic growth rates,
there must be a constant proportionality between bone
growth and somatic growth (Chaloupka and Musick,
1997). To address this proportionality, we took eight
morphometric measurements of 240 wild loggerhead and
262 wild Kemp's ridley humeri, using digital calipers
or a tape measure when dimensions were beyond the
range of the calipers. Measurements of maximum length,
longitudinal length, proximal width, distal width, delto-
pectoral crest width, lateral diameter at sectioning site,
ventral to dorsal thickness at sectioning site, and mass
were recorded. We compared these measurements with
the carapace length, measured as standard straight-line
length (SCL) from the nuchal notch to the posterior end
of the posterior marginal, using a least-squares linear
regression. For mass, the data were natural-log trans-
formed to form a linear regression.
Results
Known-age Kemp's ridley sea turtles
Three Kemp's ridley sea turtles captive for one year
and then released were recovered 4.5 to 6.5 years after
hatching (Table 1). Sample LK-1 had minimal resorp-
tion and four complete GMs, each comprising one zone
followed by a LAG. An additional zone was seen at the
periphery and the LAG that would complete this last
GM was not yet visible at the outer edge of the humerus
cross-section. From GM counts and death date, we esti-
mated the age of this animal accurately at five years
(Fig. 1). Sample LK-2 retained five completed and one
incomplete GM; however, we observed a large area of
resorption in the interior region of the cross-section
that potentially obscured additional GMs. We aged this
animal at a minimum of 5.5 years, the actual age being
6.5 years. Sample LK-3 displayed four completed GMs
and one incomplete mark. Without prior knowledge of
this animal's age, we estimated the age accurately at
4.5 years based on layer count and time of death.
Ten of the Kemp's ridley sea turtle samples were
tagged and released after hatching, and no time was
spent in captivity (Table 1). Results from these ten re-
covered animals allowed us the opportunity to study
and interpret the early GM patterns in noncaptive ani-
mals. The first year mark for Kemp's ridley sea turtles
appeared to be a poorly defined annulus, as evidenced
by LK-4 (Fig. 2A). In turtles greater than two years
old, similar first year marks also appeared more or less
distinctly (Figs. 2B and 3). Additional marks, which can
only be interpreted as supplemental lines given the age
of the animal, appeared between GM one and the outer
edge of the bone in LK-6 (Fig. 2B) and LK-10. Specimens
Snover and Hohn: Validation and interpretation of skeletal marks in Caretta caretta and Lepidochelys kempu
685
LK-7 and LK-8 were difficult to inter-
pret and in our initial assessment we
underestimated age by one year. In
both of these samples, the LAG rep-
resenting the end of the second GM
was very close to the outer edge of the
bone cross-section and was difficult
to differentiate from the edge. Hence
these samples were not counted in the
initial assessment. Because both of
these animals died in the fall, there
would have been a full growing sea-
son, and hence a growth zone, follow-
ing the completion of the second GM.
Both of these animals were recovered
dead in Cape Cod, Massachusetts,
during the fall of 1999 when record
numbers of cold-stunned sea turtles
stranded in that region.
Humerus cross-sections from LK-9
through LK-13 (Fig. 3) showed poorly
defined annuli at the end of the first
GM — annuli similar to the poorly
defined annulus in LK-4 (Fig.2A).
Subsequent GMs in these humerus
cross-sections contained well-defined
LAGs. Without prior knowledge of
these animals' history we accurately
aged each of them from GM counts
and stranding date. Specimens LK-9
through LK-13 demonstrated clearly
that well-defined LAGs were depos-
ited at the end of year two and in
subsequent years, providing evidence
that any lines between the year-one
annulus and the year-two LAGs were
supplemental.
Known-age loggerhead sea turtles
The first known-age loggerhead sea
turtle, CC-1, was 29.4 years old.
Eleven LAGs were discernible around
the circumference of the bone cross-
section (Fig. 4A), although the LAGs
become too compressed on the lateral
edges of the bone to be differentiated;
hence counts were made on the ven-
tral and dorsal edges.! Fig. 4). Trac-
ing the LAGs from the lateral to the
ventral edge of the bone, we observed
that these LAGs at some point became
bifurcating and splitting LAGs and we
interpreted each branch as a separate
LAG. An additional nine LAGs can
still be seen within the resorption zone
in most areas of the bone (Fig. 4B). On
the dorsal side of the cross-section, at
least four less-distinct LAGs or annuli
could still be observed; these had been
LAG-4 CAG"-3-
E
GM-'
Figure 1
Image of a humerus cross-section from a headstart Kemp's ridley {Lepido-
chelys kempii, LK-1) sea turtle. GM-1 refers to growth mark one; LAG-2,
LAG-3, and LAG-4 refer to the lines of arrested growth ending growth marks
two, three, and four. Curved dashed lines highlight GM-1 and the LAG.
Black bar represents 1 mm in length. This specimen was 5.0 years old.
Annulus ending
GM-1
B
/?
Supplementa
lines
Annulus ending
GM-1
Figure 2
Images of humeri cross-sections of two coded-wire-tagged Kemp's ridley
sea turtles (L. kempii). GM-1 refers to growth mark one. Black bar repre-
sents 1 mm for both images. (A) Specimen LK-4 was 1.27 years old. (B)
Specimen LK-6 was 1.72 years old.
686
Fishery Bulletin 102(4)
Annulus ending
GM-1
3 "t 4
LAG-2 ' \
LAG-3LAG-4
Figure 3
Image of humerus cross-section from a coded-wire-tagged Kemp's ridleys (L.
kempii). Black bar represent 1 mm in length. GM-1 refers to growth mark
one; LAG-2, LAG-3, and LAG-4 refer to the lines of arrested growth ending
growth marks two, three, and four. Curved black lines highlight LAGs or
annuli. This specimen, LK-13, was 4.75 years old.
resorbed in all other parts of the bone (Fig. 4C). There
had been a great deal of remodeling within the bone and
much of the inner portion of the bone had been resorbed.
Summing all of these GMs, we gave a minimum age esti-
mate of 24 years without prior knowledge of the history
of the animal. The outermost 20 GMs contained well-
defined LAGs that were spaced close together, whereas
the four interior-most visible GMs contained LAGs or
annuli that were spaced farther apart (Fig. 4). The
number of layers completely resorbed was five.
A second known-age loggerhead sea turtle, CC-2, was
eight years old. We assigned a minimum age estimate
of five years. Just outside of the resorption area was
a series of three LAGs that were very close together
(Fig. 5). In our initial analysis, we assumed that three
LAGs so close together could not each be deposited an-
nually and we interpreted the triple LAGs as a single
LAG with an anomalous appearance. We re-evaluated
this assumption after learning its history. The animal
was in captivity for two years and then released at
42.7 cm SCL in October 1994. Counting back from the
outside of the bone, the outermost of the triplet LAGs
would represent spring 1996. Given this evidence, our
best interpretation of this bone section was that the
innermost of the triplets of LAGs indicated release and
was therefore not an annual mark. The next LAG was
likely deposited the following spring (1995) and was
likely an annual mark. The third of the closely spaced
LAGs likely represented spring 1996, indicating that
the animal did not grow significantly in its first year
in the wild (Fig. 5). Following the three closely spaced
LAGs. there were four additional indistinct LAGs or
annuli that represented the remaining years at large.
The outermost of these was very close to the edge of the
bone, indicating that the animal did not grow much, if
at all, during the last summer of its life.
Indirect validation of annual growth marks
For Kemp's ridley sea turtles, there was a significant
increase in the amount of bone deposited after the last
LAG from 20 June to 30 November (Fig. 6). The LAGs
near the outer edges of the bones were fully visible in
strandings that occurred after 20 June. Earlier detec-
tion of the outer LAGs was unlikely because a certain
amount of bone formation must occur following the LAG
before it can be discerned from the edge. There was not
a significant relationship between bone growth and date
from 1 December to 19 June. The slope of this regression
was very close to zero (6 = -0.003). indicating no trend,
either increasing or decreasing, in the amount of bone
deposited during this time (Fig. 6).
Validation of the relationship between LAG diameter
and body size
The regressions of the eight morphometric measure-
ments of loggerhead and Kemp's ridley sea turtle humeri
against SCL revealed high correlations between bone
dimension and body size (Table 2). Most importantly for
purposes of back-calculation, the lateral diameter at the
sectioning site of the humerus i distal to the insertion
scar of the deltopectoral muscle) and the body length of
the animal was highly correlated.
Snover and Hohn: Validation and interpretation of skeletal marks in Caretta caretta and Lepidochetys kempii
687
Discussion
Validation of the annual nature of growth marks
Our results supported annual deposition of GMs in log-
gerhead and Kemp's ridley sea turtles. The headstarted
and older CWT Kemp's ridley sea turtles in particular
highlighted the likelihood of annual marks. These ani-
mals displayed sharp and regularly spaced LAGs that
were consistent with the actual ages of the animals.
The results from the CWT Kemp's ridley sea turtles also
emphasized the difficulties in interpreting early GMs.
From these animals we concluded that in general Kemp's
ridley sea turtles deposit a poorly defined annulus in
their first year and well-defined LAGs starting with the
end of the second year and in following years.
For loggerhead sea turtles, only CC-2 spent any time
in the wild. The number of GMs deposited after the
animal was released (determined from the appearance
of the anomalous triplet of LAGs) was consistent with
the number of years for which the animal was at large,
considering that the first mark was deposited at release.
This indicated that not less than one GM was deposited
per year, and that additional or supplemental LAGs
or annuli indistinguishable from annual lines may be
deposited under extreme conditions, such as at the time
of release into the wild. Fortunately, in this case, these
extreme conditions were not frequent enough to have a
serious impact on age estimates. For the life-time cap-
tive animal, CC-1, our estimated minimum age was
five years shorter than the actual age of 29.4 years and
clearly demonstrated that not more than one GM was
deposited each year. Because of the relatively large size
of the sea turtle humerus, in comparison to phalanges
of amphibians, rapprochement did not appear to be a
problem in our attempts to discern LAGs. This bone
was similar in appearance to adult wild loggerhead and
Kemp's ridleys sea turtles with rapprochement of the
peripheral LAGs and resorption of most of the interior
GMs. Although accurate age estimates cannot be made
of these bones through skeletochronology, if rapproche-
ment correlates to the timing of sexual maturity, counts
of the compressed GMs can provide valuable informa-
tion on postreproductive longevity and adult survival.
This information can be combined with average age at
reproductive maturation for piecing together the life
history of sea turtles. Although our sample size for
loggerhead sea turtles was very small (two), the size
complements a tetracycline-injection study that previ-
ously validated annual GMs for juvenile loggerhead
sea turtles from Chesapeake Bay (Klinger and Musick,
1992). In addition, an adult loggerhead sea turtle from
that same study stranded dead 8.25 years after in-
jection and provided evidence of annual deposition of
growth marks in adults (Coles et al., 2001).
The indirect validation results for Kemp's ridley sea
turtles highlighted the cyclic nature of bone growth;
bone deposition increases from late spring through early
summer to fall and no bone deposition occurs from De-
cember to spring. From this information we inferred
10
11
B
-9-
-10-
11
=14/15=
16
12
13
17
19,
20
c
-24-
"./-23-
.-22-
J2.Y
J20-
Figure 4
Images of different portions of the humerus cross-sec-
tions of CC-1 (Caretta caretta). Black bar represents 1
mm in length for all views. (A and Bl The outer edge
of the bone is at the top of the photo. (C) The outer
edge of the bone is towards the bottom of the photo. For
all views, lines of arrested growth (LAGs) are labeled
with numbers; low numbers represent the most recently
deposited LAGs (near the outer edge of the bone) and
higher numbers represent the earlier LAGs.
that LAGs form annually in the spring for Kemp's rid-
ley sea turtles that strand along the mid- to southeast
U.S. Atlantic coast and that these LAGs are visible at
the edges of the bones by late spring to early summer.
688
Fishery Bulletin 102(4)
triple LAG
^> .
>-'.c •* a C o
y' ? f ^ 5 > Q
J3 -j - ^ *
a *•» '• ■•" h" ■ ■ '
\ '
■-■>
'¥>
o "
Figure 5
Image of a section of the humerus cross-section of
CC-2 (C. caretta). Outer edge of bone is towards the
bottom of the photo. Solid lines (upper left I highlight a
series of triple lines of arrested growth (LAGs); curved
dashed lines highlight the three diffuse LAGs. Black
bar represents 1 mm in length.
Most studied species of reptiles and amphibians deposit
GMs within their bones (Castanet et al., 1993; Smirina,
1994). For some of these species, the annual nature of the
GM has been validated (e.g.. Tucker, 1997; de Buffrenil
and Castanet, 2000; Trenham et al., 2000). For others,
it is consistent with their ecology that the marks must
represent annual events (Castanet et al., 1993). Growth
marks observed in loggerhead (Zug et al., 1986; Zug et
al., 1995; Coles et al., 2001), Kemp's ridley (Zug et al.,
1997), and green (Zug and Glor, 1998; Zug et al., 2002)
sea turtles are similar in structure to those observed in
other species of reptiles and amphibians. Drawing on
previous studies of reptiles and amphibians, validation
studies on sea turtles, and the evidence presented in this
article, we assert that GM in bones of sea turtles are
likely deposited primarily with an annual periodicity.
Given these results, on the surface it seems contradic-
tory that in two validation studies annual GMs could
not be confirmed. For serpentine species, Collins and
Rodda (1994) injected brown snakes with a fluorescent
marker and kept them in captivity for one year under
two different feeding regimes. Five or six GMs vary-
ing in distinctness were identified beyond the fluores-
cent marks in bone cross-sections. Statistical analyses
showed that these marks may relate to shedding events.
It is unclear if the GM pattern prior to captivity was
similar to what was seen after the fluorescent mark.
The forced feeding component of that study may have
induced higher growth rates than would be found in
nature, causing the shedding events to appear as his-
tological marks in the bone.
In a sea turtle study, Bjorndal et al. (1998) did not
find GMs in the humeri of green sea turtle bones. They
suggested that the tropical marine habitat of the study
5 -i
LU 3 -
150
250
350
Julian date
450
550
Figure 6
Julian date of stranding plotted against the amount of
bone deposited peripherally to the last LAG in Kemp's
ridley sea turtles (L. kempii: n = 76). D0 represents
the outside diameter of the humerus, DL represents
the diameter of the last LAG. Julian dates on x-axis
equate to 20 June through 19 June; therefore num-
bers that are greater than 365 represent the Julian
date plus 365. Solid lines represent linear regressions
that were run separately for 6 months. 20 June to 31
November I filled squares) and 1 December to 19 June
(open squares). The regression for the first six months
was significant (P<0.006i and the regression for the
second six months was not significant lP= 0.27 1.
population (approximately 21°07'N) allowed for con-
tinual activity and growth and inhibited GM forma-
tion. However, GMs have been clearly demonstrated
in green sea turtles from the coastal waters of Florida
(approximately 29°N) (Zug and Glor, 1998) and Hawaii
(approximately 22°N) (Zug et al., 2002). Other studies
of reptiles and amphibians in tropical and warm tem-
porate climates have reported distinct GMs in species
that remain active year-round (i.e., do not hibernate
or estivate) (Patnaik and Behera, 1981; Estaban et al.,
1996; Guarino et al.. 1998).
Interpretation of anomalous LAGs
Although our sample sizes were small, especially for log-
gerhead sea turtles, several characteristics were noted
in the analyses of the samples that would affect how
anomalous LAGs are interpreted. Three interpretations
of double and bifurcating LAGs are provided. The first
interpretation is that if double LAGs appear frequently
in individual bones and throughout the sample, they
likely indicate an ecology that has two growth cycles
per year (Castanet et al., 1993). In this case the two
LAGs are distinct from each other over the entire bone
cross-section. This pattern was observed in the newt
Triturus marmoratus living at a high altitude where
the animals had both winter and summer dormancy
periods (Castanet and Smirina. 1990; Caetano et al.,
1985; Caetano and Castanet, 1993). The second inter-
pretation of double LAGs is that they result from a brief
Snover and Hohn: Validation and interpretation of skeletal marks in Caretta caretta and Lepidoche/ys kempn
689
Table 2
Regressions equations and statistics from correlations between dimensions of the humerus and notch-to-tip straight carapace
length (SCL, cm) in loggerhead and Kemp's ridley sea turtles. All F statistics are significant at P<0.005.
Humeral measurement
Model equation
SE slope
Loggerhead sea turtles In =243)
Maximal length (ML, mm)
Longitudinal length ILL, mm)
Proximal width (PW. mm)
Deltopectoral crest width (DCW, mm)
Site of sectioning width ISW, mm)
Site of sectioning thickness ( ST, mm)
Distal width (DW, mm)
Mass(M, g)
Kemp's ridley sea turtles (rc=262)
Maximal length (ML, mm)
Longitudinal length (LL, mm)
Proximal width iPW, mm)
Deltopectoral crest width (DCW, mm)
Site of sectioning width ( S W, mm )
Site of sectioning thickness (ST. mm)
Distal width ( DW, mm)
Mass (M, g)
SCL = 0.44xA/L + 5.97
SCL = 0.47xLL + 4.85
SCL = 1.06xPW + 7.31
SCL= 1.69xDCW + 6.04
SCL = 2.38xSW + 5.48
SCL = 4.13xST + 11.62
SCL = 1.28xZW+5.43
ln(SCL) = 0.30xln(M) + 2.94
SCL = 0.43xML + 4.69
SCL = 0.47xLL + 3.11
SCL = 1.12xPW+4.39
SCL = 1.69xDCW + 3.35
SCL = 2.48xSW + 2.74
SCL = 4.16xST+ 4.79
SCL= 1.36xDW+ 0.227
LNiSCL) = 0.30xLN(M) + 2.89
0.0064
4814
0.95
0.0064
5381
0.96
0.015
4857
0.95
0.026
4069
0.94
0.037
4110
0.94
0.080
2682
0.92
0.021
3684
0.94
0.0022
18905
0.99
0.0040
10970
0.98
0.0039
14772
0.98
0.010
12390
0.98
0.017
10200
0.98
0.033
5715
0.96
0.072
3306
0.93
0.013
11435
0.98
0.0023
16305
0.98
interruption of hibernation (Hemelaar and van Gelder,
1980). In this instance little bone deposition would
occur and the layers would not be distinct from each
other over the entire bone, thus giving the appearance
of a bifurcating LAG (Hemelaar and van Gelder, 1980).
The third interpretation of double or bifurcating LAGs
is that they result from extreme decreased growth over
the active period, which places annual LAGs very close
to each other and in some cases they appear to merge
(de Buffrenil and Castanet, 2000).
With the first two interpretations, a double or bifur-
cating LAG would be counted as one for the purposes of
age estimation, whereas the third interpretation would
necessitate counting each LAG or bifurcating branch
separately. Coles et al. (2001) interpreted a bifurcat-
ing LAG as one LAG in an adult loggerhead sea turtle
that was recovered 8.25 years after it had been injected
with oxytetracycline. In cross-sections of the humerus,
Coles et al. (2001) reported seven LAGs following the
tetracycline mark, six plus the bifurcating LAG. The
animal was marked on 20 June 1989 and recovered
dead on 22 September 1997. It is reasonable to assume
that, as with Kemp's ridley sea turtles from the same
region, the LAGs form in the spring, and Coles et al.
(2001) showed that the oxytetracycline mark overlaid
one of the LAGs — likely the LAG deposited in spring
of 1989. Therefore, there should have been eight LAGs
deposited after the tetracycline mark, not seven, each
representing the spring of years 1990 through 1997.
In this case, then, the bifurcating mark in this bone
should be counted as two LAGs.
Similarly, for splitting LAGs, where numerous thin-
ner LAGs branch out from what appears to be one thick
LAG, Francillon-Vieillot et al. (1990) examined different
bones from the same animal and determined whether
each thin LAG comprising splitting LAGs should be
counted as one LAG. In our analysis of the adult log-
gerhead sea turtle, CC-1, we observed several bifurcat-
ing and splitting LAGs. each of which eventually split
into two or more thinner LAGs. We counted each of the
thin LAGs as one. Because the LAG count was close to
the actual age of the animal, this interpretation ap-
pears to have been appropriate for compressed LAGs
in adult humeri.
The question remains as to whether this is the ap-
propriate interpretation for double or bifurcating LAGs
in juveniles. Wild loggerhead growth rates have been
monitored in an ongoing mark-recapture study in Pam-
lico and Core Sounds in North Carolina (Epperly et al.,
1995). Epperly et al. (1995) currently have 65 growth
rates for 49 juvenile loggerhead sea turtles between 45.1
and 81.0 cm SCL at initial capture that were at-large
for one year (±0.1 year). The mean annual growth rate
for all of the animals is 2.09 cm/yr. However, of the
65 growth records, 11 of them displayed an annual in-
crease of 0.3 cm or less in SCL (Braun-McNeill1). Hence
it is not uncommon for juvenile loggerhead sea turtles to
Braun-McNeill, J. 2004. Personal commun. Center for
Coastal Fisheries and Habitat Research, National Marine
Fisheries Service, NOAA, 101 Pivers Island Rd., Beaufort,
NC 28516
690
Fishery Bulletin 102(4)
grow little or not at all over the course of a year. Using
the equation for width at sectioning site from Table 2,
we found that the increase in bone diameter for these 11
animals was =0.13 mm or less, which places the LAGs
very close together. Because it not uncommon for sea
turtle to exhibit little or no growth over a year, LAGs
spaced closely together very likely represent distinct
years as also determined by de Buffrenil and Castanet
(2000). Although the sample sizes are still small for a
definitive answer, our results indicate that counting
the LAGs individually is the correct interpretation of
double or bifurcating LAGs in juvenile as well as adult
loggerhead sea turtles.
Similarly, our results indicate the same interpretation
for double or bifurcating LAGs in juvenile Kemp's ridley
sea turtles. The CWT Kemp's ridley sea turtles, samples
LK-7 and LK-8, displayed LAGs near the outer edge
of the bone and a small amount of bone was deposited
after the LAGs. These animals were each 2.25 years
old and had one-year marks visible in the humeri but
no LAGs or annuli other than those at the periphery.
Other CWT samples clearly indicated that LAGs are
deposited at the end of the second GM. The indirect
validation results demonstrated that LAGs were visible
in bone tissue by late spring or early summer. It seemed
that the LAGs at the outer edge of the LK-7 and LK-8
bones were the LAGs ending the second GM and that
very little growth occurred over the subsequent growing
season. Both of these animals were recovered as dead
strandings resulting from a major cold stun event in
Cape Cod, Massachusetts, in 1999; hence their growth
rates may have been anomalous in their last year of
life. Had these animals survived the cold stun event,
they would have deposited a year-three LAG very close
to year two, giving the appearance of a double or bi-
furcating LAG.
Another anomaly in skeletochronology, supplemen-
tal lines, may form as a result of temporary stressful
environmental events such as droughts. In support of
this, Rogers and Harvey (1994) noted a supplemental
line in 11 of 43 specimens of the toad Bufo cognatus,
and in 10 of these animals the supplemental line was
within a growth zone that corresponded to a drought
year. Most skeletochronology studies that have noted
the presence of supplemental lines have indicated that
supplemental lines are easily identified as such because
they are less distinct and do not appear around the
entire circumference of the bone. In general, the same
has been observed in sea turtles. Supplemental lines
do appear but are generally easily differentiated from
LAGs by appearance. An exception to this was the
presence of supplemental marks in one- to two-year-old
Kemp's ridley sea turtles. These marks were similar
in appearance to the first year annuli. We were able
to identify these marks as supplemental only by the
observation of known-age animals. In addition, there
appeared to be a supplemental line in CC-2 that rep-
resented when the animal was released; hence, highly
stressful events may cause the deposition of nonannual
lines, but these events are likely to be relatively rare
in wild turtles and not likely to interfere significantly
with age estimations.
Resorption of early growth marks
The loss of the early GMs due to endosteal resorption
and remodeling of the interior region of the bone is a lim-
iting factor in the application of skeletochronology to sea
turtles. From our findings, it was possible to accurately
age juvenile Kemp's ridley sea turtles up to at least 5
years from GM counts and this may be true for other
sea turtle species (e.g., Bjorndal et al., 2003), with the
possible exception of the leatherback sea turtle (Zug and
Parham, 1996). Because sea turtles have distinct life-
cycle stages, we suggest that in order to age a population
of sea turtles, one must acquire an ontogenetic series of
samples spanning all sizes and stages. Average duration
can be determined for each ontogenetic stage and the
approximate age of older animals with extreme resorp-
tion can be estimated. Because GM patterns appear to
mimic somatic growth rates, once growth through each
life-cycle stage is understood, backcalculation techniques
can be used to estimate the number of layers resorbed.
Conclusions
For many species, skeletochronology is not a perfect
method for age estimation. As GMs are histological
expressions of variation in rates of osteogenesis (Casta-
net et al., 1993). external factors and individual varia-
tion will affect the appearance of the marks (Castanet
et al., 1993, Esteban et al., 1996, Wave and Gregory.
1998). Endosteal resorption also serves to confound this
technique and is the primary difficulty in the application
of the technique to sea turtles. However, the evidence
presented in the present study gives strong support
to the concept that GMs are deposited on an annual
basis in sea turtles and that the spatial pattern of the
GMs correspond to the growth rates of the animal. The
GMs therefore provide invaluable information on age
and growth that cannot otherwise be easily obtained,
and age determination by skeletocronology is valid and
appropriate for the study of sea turtles.
Acknowledgments
We thank L. Crowder, S. Heppell, A. Read, and D.
Rittschof for their valuable comments on earlier ver-
sions of this manuscript. A. Gorgone. B. Brown and J.
Weaver provided assistance with the preparation of the
humeri. Most of the humeri were received through the
Sea Turtle Stranding and Salvage Network, a coopera-
tive endeavor between the National Marine Fisheries
Service, other federal and state agencies, many academic
and private entities, and innumerable volunteers. We
especially thank R. Boettcher and W. Teas. In addition,
humeri were received from F. Swartz at the Univer-
sity of North Carolina-Chapel Hill Institute of Marine
Snover and Hohn: Validation and interpretation of skeletal marks in Caretta caretta and Lepidochelys kempu
691
Science, B. Higgins at the National Marine Fisheries
Service-Galveston Lab, the Virginia Marine Science
Museum Stranding Program, the Maryland Department
of Natural Resources, and the Massachusetts Audu-
bon Society in Wellfleet. Funding was provided by the
National Marine Fisheries Service. All work was done
under and complied with the provisions of the Sea Turtle
Research Permit TE-676379-2 issued by the U.S. Fish
and Wildlife Service.
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693
Abstract— Blue tCallinectes sapidus)
(Portunidae), lady (Ovalipes ocella-
tus) (Portunidae I, and Atlantic rock
(Cancer irroratus) (Cancridae) crabs
inhabit estuaries on the northeast
United States coast for parts or all
of their life cycles. Their distribu-
tions overlap or cross during cer-
tain seasons. During a 1991-94
monthly otter trawl survey in the
Hudson-Raritan Estuary between
New York and New Jersey, blue and
lady crabs were collected in warmer
months and Atlantic rock crabs in
colder months. Sex ratios, male:
female, of mature crabs were 1:2.0
for blue crabs, 1:3.1 for lady crabs,
and 21.4:1 for Atlantic rock crabs.
Crabs, 1286 in total, were sub-
sampled for dietary analysis, and
the dominant prey taxa for all crabs,
by volume of foregut contents, were
mollusks and crustaceans. The pro-
portion of amphipods and shrimp in
diets decreased as crab size increased.
Trophic niche breadth was widest for
blue crabs, narrower for lady crabs,
and narrowest for Atlantic rock crabs.
Trophic overlap was lowest between
lady crabs and Atlantic rock crabs,
mainly because of frequent consump-
tion of the dwarf surfclam (Mulinia
lateralis) by the former and the blue
mussel (Mytilus edulis) by the latter.
The result of cluster analysis showed
that size class and location of capture
of predators in the estuary were more
influential on diet than the species
or sex of the predators.
The Hudson-Raritan Estuary as a crossroads
for distribution of blue (Callinectes sapidus),
lady (Ovalipes ocellatus),
and Atlantic rock {Cancer irroratus) crabs
Linda L. Stehlik
Robert A. Pikanowski
Donald G. McMillan
James J, Howard Marine Sciences Laboratory
Northeast Fisheries Science Center
National Marine Fisheries Service, NOAA
74 Magruder Road
Highlands, New Jersey 07732
E-mail address (for L L Stehlik): Linda Stehlika' noaa.gov
Manuscript submitted 27 November
2000 to the Scientific Editor's Office.
Manuscript approved for publication
4 May 2004 by the Scientific Editor.
Fish. Bull. 102:693-710 (20041.
The blue crab (Callinectes sapidus)
(Portunidae), the lady crab {Ovali-
pes ocellatus) (Portunidae), and the
Atlantic rock crab (Cancer irroratus)
(Cancridae) are the largest and most
common brachyuran crabs inhabiting
both estuaries and inner continen-
tal shelves of the northeast coast of
North America. The centers of abun-
dance of these three species over-
lap in estuarine and coastal waters
from New York to Virginia, although
their ranges along the northwest
Atlantic coast are broad. The blue
crab is nearly always an estuarine
resident, except during its larval
stages, and ranges from the waters
off Nova Scotia to Argentina (Wil-
liams, 1984). The northernmost estu-
aries where the species is abundant
enough for commercial harvest are
in New Jersey and New York (Briggs,
1998; Stehlik et al., 1998). The lady
crab is distributed from the waters
off Prince Edward Island to those
off Georgia but it is most numerous
from Georges Bank to Cape Hatteras
(Williams, 1984). The Atlantic rock
crab (referred to as "rock crab" in
this article) is distributed in waters
from off Labrador to Florida but is
most common in estuaries from Nova
Scotia to Virginia (Williams, 1984;
Stehlik et al., 1991). Seasonal migra-
tions are common for all three spe-
cies. Although Jonah crabs (Cancer
borealis) are present on the continen-
tal shelf, they are not included in the
present study because they are rare
within the Hudson-Raritan Estuary
where our study was conducted.
Physiological tolerances and habi-
tat preferences of these crabs have
been extensively studied. In eastern
United States estuaries the blue crab
occurs in shallow to deep, sandy to
muddy estuaries and tributaries
along marsh edges, and in seagrass
(Van Engel, 1958; Milliken and Wil-
liams, 1984; Hines et al., 1987; Wil-
son et al., 1990; van Montfrans et
al., 1991; Rountree and Able, 1992).
In the colder portions of its range,
it becomes less active at about 15°C
(Leffler, 1972), and buries itself, with-
out eating, when the temperature is
<5°C (Auster and DeGoursey, 1994).
It survives at 34°C (Leffler, 1972) and
at salinities from 0 to 50 ppt (Guerin
and Stickle, 1992). The lady crab is
most common on sand substrates
(Williams, 1984). It is present on the
inner continental shelf from off Cape
Cod to off the Carolinas throughout
the year (Stehlik et al., 1991). Its tem-
perature tolerance is unknown, but it
does not survive in <21 ppt (Birchard
et al., 1982). The rock crab's optimum
temperature range for activity is 14-
22°C (Jeffries, 1966); thus the species
avoids high summer temperatures.
It is found on many substrates, such
as sand, mud, bare rock, cobble, and
algal beds.
694
Fishery Bulletin 102(4)
The diet of the blue crab is generally mollusks, crabs,
and fish, depending on crab size (Virnstein, 1977;
Laughlin, 1982; Ryer, 1987; Hines et al„ 1990). The
diet of the lady crab is mainly bivalves such as My a
arenaria and Spisula solidissima, and some crustaceans
(McDermott, 1983; Ropes, 1989; Stehlik, 1993). The
rock crab consumes mollusks, small crustaceans, crabs,
urchins, and fish (Scarratt and Lowe, 1972; Drummond-
Davis et al., 1982; Hudon and Lamarche, 1989; Ojeda
and Dearborn, 1991; Stehlik, 1993). In some of the
aforementioned studies these crabs have been consid-
ered opportunistic and as such may be competitors for
the same prey taxa. However, differences in maximum
body size, chela structure, and the presence or absence
of swimming appendages among blue, lady, and rock
crabs indicate that they may have differences in diet
(Warner and Jones, 1976; Williams. 1984).
Within the Hudson-Raritan Estuary, blue, lady, and
rock crabs are all abundant, providing an opportunity
to study partitioning of habitat and food resources by
these species. The objectives of our study were to de-
termine the temporal and spatial overlap of blue, lady,
and rock crabs in this estuary and to differentiate the
composition of their diets by the species, sex, and size
of predators, and by location of collection.
This study has potential practical applications. Re-
source managers could use the results to consider when
and where crabs depend upon certain locations to com-
plete their life cycles, if dredging, filling, or sanctuaries
were proposed. Dietary analysis of these crabs could
indicate if they are a cause of mortality for young stages
of commercially important species. For instance, the
northern quahog (Mercenaria mercenaria) and the soft-
shell clam <M. arenaria i recently have supported and
presently support commercial and recreational harvests
in the Hudson-Raritan Estuary (MacKenzie. 1990; 1997)
and when young these clams are consumed by crabs.
The blue crab supports lucrative fisheries in the estuary
(Stehlik et al., 1998) and predation by various species of
crabs upon blue crab juveniles may affect recruitment.
Materials and methods
Study area
The Hudson-Raritan Estuary, bordered by New Jersey on
the south and Staten Island and Brooklyn, New York, on
the north (Fig.l), has a surface area of about 280 km2.
The Hudson, Raritan, and Navesink-Shrewsbury rivers
flow into the estuary from the north, west, and south,
respectively. The study area is bounded on the west by
the 74°15' longitude line; on the east by a line between
the northeast corner of Sandy Hook, NJ, and the tip of
Rockaway Point, NY; and on all sides by the-3 m con-
tour. The area was divided into nine strata according
to physiographic features (Wilk et al.1). Sandy-bottom
strata included Sandy Hook Bay (stratum 1), Raritan
Bay south of Raritan Channel (stratum 2), and Lower
Bay north of Raritan Channel (stratum 3). Eastern
strata of more irregular depths were Romer Shoals
(stratum 4), East Bank between Ambrose Channel and
Rockaway, NY (stratum 5), and Gravesend Bay at the
mouth of the Hudson River (stratum 6). Three strata
were channels; Ambrose (stratum 7), Chapel Hill (stra-
tum 8), and Raritan (stratum 9). Raritan Channel is
maintained at a depth of 13.7 m, and the average depth
of adjacent nonchannel stations is 7.1 m. Gravesend Bay-
is more than 13 m deep in its center.
The bottom of the Hudson-Raritan Estuary consists
mostly of soft sediments (Jones et al., 1979; Coch, 1986:
Wilber2). The substrates in semi-sheltered southern
strata 1 and 2 are predominantly fine sand, silt, and
clay; those of stratum 3 are mainly medium sand, with
a mixture of sand, silt, and clay near channels; those
of ocean-exposed strata 4, 5, 6, and 7 are gravel, sand,
silt, broken shell, and have beds of blue mussels (Myti-
lus edulis). The bottom of Ambrose Channel is silt and
clay near its head and fine sand toward the ocean.
The sediments of the other two channels, and their
immediate borders, are sand, silt, and clay. Based on
physiographic form, temperature ranges, and sediments,
strata 1, 2, 3, 8, and 9 were considered inner or river-
ward strata, whereas 4, 5, 6, and 7 were considered
outer or oceanic-influenced strata.
Collections and analyses
Crabs were collected during monthly otter trawl sur-
veys of the Hudson-Raritan Estuary from June 1991 to
December 1994 (Wilk et al.1). Sampling was done from
the 18-m research vessel Gloria Michelle by towing
a 9.1-m otter trawl with a chain sewn to the bottom
opening, and a 76-mm mesh net with a 51-mm codend
liner. Wooden trawl doors were deployed to spread open
the net. The net was towed once per station for 10 min
at 5.6 km/h to cover a distance of approximately 1 km.
All tows were made between 8 am and 2 pm. During
1991. fixed stations were towed (number of stations in
1991: 10 in June, 8 in July; 11 in August; 18 in Sep-
tember; 22 in October; 23 in November; 34 in Decem-
ber). Beginning in 1992, a stratified random sampling
design was used, in which the nine strata were divided
into 190 blocks of approximately 0.5 minutes latitude
by 0.5 minutes longitude. Each month, 40 blocks were
randomly sampled without replication, and the number
of blocks in each stratum was proportional to the area
of the stratum. Because of conflicting schedules, the
vessel was not available in May or September 1992 or
1994. Temperature and salinity of water 1 m above the
bottom were measured after each tow. During 1991
1 Wilk. S. J.. E. M. MacHaffie. D. G. McMillan, A. L. Pacheco, R.
A. Pikanowski, and L. L. Stehlik. 1996. Fish, megainver-
tebrates, and associated hydrographic observations collected
in the Hudson-Raritan Estuary, January 1992-December
1993, 95 p. Northeast Fish. Sci. Cent." Ref. Doc. 96-14,
NMFS. Woods Hole, MA.
- Wilber, P. 2000. Unpubl. data. Coastal Services Center.
National Ocean Survey. NOAA, 2234 Hobson Avenue, Charles-
ton, SC, 29405.
Stehlik et al.: Distribution patterns of various crab species in the Hudson-Raritan Estuary
695
73° 59'
74°|15'W
New York
74°|00'
73°] 59'
74°|15'W
Figure 1
Hudson-Raritan Estuary, from New York to New Jersey, with 3-m contour, drawn boundaries,
and the nine strata of the Hudson-Raritan Estuary trawl survey. The inset shows the location
of the estuary on the United States coast off New York and New Jersey.
and 1992 temperature and salinity were determined by
using a Niskin bottle, a thermometer, and an induction
salinometer. Beginning in January 1993 a Hydrolab"
Surveyor III multiprobe was used.
Fish and large invertebrates were counted, weighed,
and measured (±1.0 cm), and sexes of the crabs were re-
corded. Catch per unit of effort or number per tow was
used to estimate relative abundance. Crabs were mea-
sured by carapace width (CW) between the tips of the
anterolateral teeth. Specimens were saved for dietary
analysis from June 1991 through June 1992. These
specimens were measured (±1.0 mm) and molt stages
were classified as intermolt (hard-shelled), premolt (new
skin separates easily from inside the carapace), soft-
shelled, or postmolt (early and late papershell).
For some analyses, we separated crabs into two size
classes based on maturity because preferred habitats,
tolerances, or reproductive needs may be different for
different life stages. Most researchers use a carapace
width at which 250% or >80% of the individuals are
mature (produce viable eggs or sperm) as a separation
boundary. Maturity in males is determined by dissec-
tion or by allometric changes in growth of appendages
(Hartnoll, 1978; Block and Rebach, 1998; de Lestang
et al., 2003). Most female blue crabs in our study area
and in Virginia had completed their pubertal molt and
thus could reproduce by 12 cm CW (Van Engel, 1958;
Fisher, 1999; Stehlik, unpubl. data). In Virginia, 80%
of male blue crabs are mature by 11.9 cm (Van Engel,
1990). In lady crabs from the New York coast, nearly all
males are mature at >6 cm, and females at about 5 cm
(Briggs and Grahn3). In the middle-Atlantic portion of
their range, male rock crabs mature at 5 cm (Haefner,
1976) and some females <5 cm bear eggs (Reilly and
Saila, 1978). We chose the following CW boundaries
for >80% maturity: blue crabs, >12 cm both sexes; lady
crabs, 25 cm both sexes; and rock crabs, males ^5 cm
and females ^4 cm.
Data on blue, lady, and rock crabs from NEFSC
(Northeast Fisheries Science Center, NOAA) fall bot-
tom trawl surveys on the northeast United States con-
tinental shelf, 1992-94, were used to expand the geo-
graphical viewpoint of our study. The presence of each
species in each tow was plotted to show distributions in
a representative year. 1992. The plots were made with
Surfer® (version 6, Golden Software Inc., Golden, CO).
Methods on the trawl surveys are described elsewhere
(Azarovitz, 1981).
3 Briggs, P. T.. and C. M. Grahn. 1996. Aspects of the fish-
ery biology of the lady crab tOvalipes ocellatus) in New York
waters, 8 p. An in-house paper. New York State Department
of Environmental Conservation, 205 North Belle Mead Road,
Suite 1, East Setauket, NY, 11733.
696
Fishery Bulletin 102(4)
Foregut contents were analyzed as in Stehlik (1993).
The foregut of each crab was removed and preserved in
7095 ethanol. After opening the foregut, we estimated
fullness of the gut (from 0c/c to 100%) visually, and prey
items were identified to the lowest possible taxon. The
proportion of the total volume of the foregut contents con-
tributed by each prey taxon was estimated visually — a
less labor-intensive modification of the methods of Wil-
liams (1981), Hyslop (1980), and Steimle et al. (1994).
The volume of each prey taxon was multiplied by the
percentage of gut fullness. Combining all foreguts, the
volumes of prey taxa were listed in descending order.
The top 12 prey categories on the list (with the excep-
tion of "unidentified" and nonexclusive categories such as
Mollusca) were selected for use in most of the subsequent
analyses. Foreguts that did not contain prey in any of the
12 categories were dropped from numerical analyses.
The dietary data were grouped in turn by predator
species, sex, size class, and collection stratum, and the
mean percentage volumes of each of the 12 mutually
exclusive prey categories were calculated. For graphic
representation of ontogenetic differences in diet, blue
and rock crabs were grouped for convenience into 20-
mm CW classes, and lady crabs were grouped in 10-mm
CW classes because of their smaller size range. For
numerical analyses, two maturity classes were used.
We used Mann-Whitney tests to compare diets between
sexes within predator species and between maturity
stages within predator species. The test statistic was a
chi square approximation.
Group average cluster analysis was used to graph the
separation of diets by species, sexes, maturity stages,
and strata by using the 12 prey categories as dependent
variables. A Bray-Curtis similarity matrix was gener-
ated for each of the groupings, cluster analysis was
performed by using Systat® (version 10. SPSS Inc., Chi-
cago, IL), and dendrograms were generated by using the
Bray-Curtis values as distance measures (Romesburg.
1984; Marshall and Elliott, 1997). A percent similarity
level was chosen a posteriori that generated a reason-
able number of classes.
Analysis of similarity (ANOSIM) was used to test
for statistical significance of dietary differences among
predator species and for sexes within species. Analysis
of dissimilarity (SIMPER) was used to determine which
prey taxa contributed most to the differences between
species pairs (Clarke and Warwick, 1994).
Spatial, temporal, and trophic niche breadth and over-
lap indices were calculated from the number per tow
(1992-94) and diets (June 1991-June 1992) of each
crab species and sex. Temporal niche and overlap were
calculated by month for combined years. Female rock
crabs were dropped from consideration of trophic niche
overlap due to low sample size.
Niche breadth (Colwell and Futuyama, 1971; Mar-
shall and Elliot, 1997) is a measure of exploitation
within a particular resource (for example, substrates
or prey taxa within an estuary by a species). Niche
breadth values are relative and can be compared only
within one study. The highest value corresponds to the
broadest niche, or to habitat or a diet generalist rather
than to a specialist. Niche breadth (S) was calculated
by the formula of Colwell and Futuyama (1971), and
modified for measuring trophic niche breadth according
to Hines et al. (1990):
B = 1 / £( pk r from./ = 1 to n .
where phl = Nkj I Yk ipki is the proportion of crabs of
species k associated with resource state
j)\
j = resource states (months, strata, diet cat-
egories);
n = number of resource states;
Nkj = catch per tow of species k at resource state
j; and
Yk = catch per tow of species k over all resource
states.
When trophic niche breadth was calculated,
Nh = total volume of diet category j consumed by preda-
tor k ;
Yk = total volume of all diet categories consumed by
predator k.
Niche overlap is a measure of the joint use of a resource
by two species (Colwell and Futuyama, 1971). Niche
overlap (CAl) between species h and i was calculated
by the following formula (Colwell and Futuyama, 1971;
Hines et al., 1990):
C/,,=l-0.5(Xlp,,,-;V)fi-onV = lto».
where ph/ and p„ are calculated in the same manner as
Pk, above.
This index ranges from 0 (no overlap) to 1 (complete over-
lap) and is independent of sample size and differential
resource availability (Eggleston et al.. 1998).
Results
Temperature and salinity
Bottom water temperature in the study area followed
a temperate seasonal cycle. The range during 1992-94
was from 0 to 26.6 C. Using the monthly mean tempera-
ture below or above 10°C, and migration cycles of the
crabs, we grouped the months into two seasons: winter
(November through April) and summer (May through
October). The mean temperature in the winter months
1992-94 was 5.5°C, and that for summer was 18.9°C.
Temperature nearest the estuary mouth was usually a
few degrees lower in summer months and higher in the
winter months each year, compared with the average
throughout the estuary.
Bottom salinity in the study area ranged from 15.0 to
33.5 ppt. The majority of stations had salinities between
Stehlik et al.: Distribution patterns of various crab species in the Hudson-Rantan Estuary
697
Table 1
Species, sex, number collected (n), and sex ratio (SR, ma
e:female) of a
1 crab
; collecte
d du
ring the
Hudson-Ra
■itan Estuary
trawl survey, June 1991-
December 1994.
Mat
urity boundaries are expla
ned in
the text
For the subsample examined for stom-
ach contents (June 1991-
-June 1992), number
i/i ), number
of non-empty
stomachs, and the mean an
i range of carapace width
(CW, mm) are presented.
Crab species,
SR(m:f)
SR(m:f)
stomach
Subsample CW
sex
collected
immature
mature
opened
empty
Mean
(Range)
Blue, male
2803
1:1.13
1:1.97
167
120
112
(35-185)
Blue, female
4816
272
208
129
(21-169)
Lady, male
14,903
1:1.30
1:2.12
173
124
60
(34-88)
Lady, female
29.681
255
228
55
(30-89)
Atlantic rock, male
15,503
4.65:1
21.43:1
400
281
92
(28-130)
Atlantic rock, female
822
19
14
51
(29-80)
Total
68,528
1286
975
25 and 30 ppt. Salinity decreased with distance from
the bay mouth and in any one month, the difference
in salinity between stations at the estuary mouth and
those at the westernmost part of the study area was
approximately 5-10 ppt.
Catch by species, size, and sex
From June 1991 through December 1994, more than
68,000 blue, lady, and rock crabs were caught in 1200
otter trawl tows (Table 1). Other mega-invertebrates
in the tows included the northern moonsnail (Euspira
heros), the horseshoe crab (Limulus polyphenols), the
American lobster (Homarus americanus), the portly
spider crab (Libinia emarginata), the flatclaw hermit
crab tPagurus pollicaris), mud crabs (Xanthidae), and
the sea star (Asterias sp. )
Catch per tow of crabs by size class increased as
they became large enough to be retained by the mesh
of the net (Fig. 2). Abundances of female blue and lady
crabs in the study area were greater than those of the
males. In rock crabs, males predominated (Table 1). Im-
mature blue and lady crabs had sex ratios fairly close
to 1:1 (male:female). Sex ratio in mature blue crabs,
however, was 1:1.97, and in mature lady crabs, 1:2.12.
In all sizes of rock crabs, sex ratio strongly favored
males, particularly in mature crabs, in which the ratio
was 21.43:1.
Temporal and spatial variation in catch
The maximum relative abundance of blue and lady
crabs occurred during the warm months each year,
whereas rock crabs were abundant only in the cold
months (Fig. 3). Blue crabs were scarce in the otter
trawls from January through May or June. We believe
that many of them do remain in the study area, but are
relatively inactive and are not accessible to otter trawls,
as discussed below. Lady crabs migrated into the estu-
ary in April and May and left in October and November.
15
10
5
0
a"
^ 20
o
c
a>
cr
a>
r 10-
Blue crabs
r*r¥P
ml
I
-^r
I
Lady crabs
Male
I Female
IL
15-
Rock crabs
10-
n n I"
r
5-
i
0-
■■'Hi-
II,
4 8 12 16 20
Carapace width (cmL
Figure 2
Carapace width (cm) frequencies for male and
female blue, lady, and rock crabs collected
during the Hudson-Raritan Estuary trawl
survey, June 1991-December 1994, by percent
frequency of the total catch of each species.
698
Fishery Bulletin 102(4)
Rock crabs migrated into the estuary in November and
gradually left during April, May, and June.
Hundreds of soft and postmolt male rock crabs were
caught each winter in the study area (Fig. 4). The high-
est numbers of molting rock crabs were collected each
December and January, and almost all of these crabs
had completed molting by February. Very few molting
or postmolt blue or lady crabs were caught.
The relative abundances of the three species varied
by stratum (Fig. 5, A-C; Fig. 6). Blue crabs of both
sexes were caught mainly in strata near river mouths
(strata 1. 2, and 6), in the Chapel Hill and Raritan
channels (strata 8 and 9) in summer, but mainly in
stratum 6 and in the channels in winter. Lady crabs
were widely distributed and were caught throughout
the study area, including the outer strata close to the
ocean. Male rock crabs were most frequently collected
in and near the channels and in strata 1 and 6, whereas
female rock crabs were sparsely scattered throughout
the study area.
6 8 10 12 2 4 6 8 10 12
1991 1992
4 6 8
1993
10 1;
4 6 8 10 12
1994
6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 1:
1991 1992 1993 1994
10 12 2 4 6 8 10 12
1991 1992
6 8 10 1 j
1993
4 6 8 10 12
1994
O
Figure 3
Catch per unit of effort (number/towl of blue, lady, and rock crabs by month,
graphed with mean bottom temperatures. June 1991-December 1994.
Stehlik et al.: Distribution patterns of various crab species in the Hudson-Rantan Estuary
699
Foregut fullness
The total number of blue, lady, and rock crab foreguts
examined was 1286. Foregut fullness varied by month
in blue and rock crabs. The average fullness of blue
crabs was 1% by volume from January through April,
and 34% for the rest of the year. Ovigerous blue crabs
(/? =27) averaged 40% full. Lady crabs' average full-
ness was 41% during the months when they were pres-
ent. The average fullness of rock crabs was 30% in all
months when they were present; a minimum occurred in
January when fullness was 7%. Of 419 rock crabs exam-
ined, intermolt crabs (rc=293) were 33% full, premolt
crabs (n = 9) were empty, soft crabs (n=22) were empty,
and postmolt crabs 1/2 = 95) were 20% full. Some rock
crabs in the late postmolt stage were full even though
their chelae were not completely calcined.
Diet composition
The number of crabs containing food was 975, and they
consumed 44 identifiable taxa (Table 2). Most of the
mollusks preyed upon were <15 mm in shell length.
The crabs consumed were mud crabs (Xanthidae) and
juvenile stages of other Anomura and Brachyura. When
foreguts were only partially full, well-digested remains
of prey frequently could be identified by pieces of shell
or opercula, mandibles (for shrimp), or chela tips and
carapace fragments (for crabs) (Elner et al., 1985). Rec-
ognizable prey taxa were grouped into 12 mutually
exclusive categories (Table 3), which contributed 80.1%
of the volume of all prey. The prey category "CRABS"
represented pooled fragments of all crabs except Pagu-
120
100
80
60-
40
20
0
V
Papershell
■ Soft
= Premolt
Hard
8 9 10 11 12 1
3 4 5 6
1991
1992
Figure 4
Number of rock crabs at each molt stage by month.
1991-92.
Figure 5
Catch per unit of effort of (Al blue, (B) lady, and (Cl rock crabs, sexes combined
January 1992-December 1994, mapped by the midpoint of each tow.
ridae and Xanthidae. Crabs containing prey in one or
more of the 12 categories numbered 713.
Differences in diet by predator species, sex, and size
Although the three predator species shared most prey
taxa, there were differences in the proportions of the
taxa consumed (Fig. 7). Mann-Whitney tests comparing
diets of sexes within each species showed only two sig-
nificant differences out of 36 comparisons. After cluster
analysis upon the 12 prey types by species, sex, and
size class (immature and mature), the resulting den-
drogram showed that diets were most similar between
size classes within a species (Fig. 8).
Female rock crabs were not included
because of their small sample size.
When the diets of the three species
were compared by analysis of simi-
larity (ANOSIM) they were found
to be different (P=0.067>, but the
data were extremely variable and
not normally distributed. No signifi-
cant differences were found between
sexes within species and we there-
fore pooled sexes within species.
Pairwise comparisons of the spe-
cies were performed by analysis of
dissimilarity (SIMPER). Four taxa
contributed significantly to the dif-
ference in diets of the first pair: the
bivalves M. edulis and M. lateralis
were more important in the diets
of lady crabs, and Xanthidae and
CRABS, were more important in
the diets of blue crabs. The diets
of blue crabs and rock crabs were
significantly different in four taxa:
CRABS and M. lateralis were more
important for blue crabs, and M.
edulis and Xanthidae for rock crabs.
700
Fishery Bulletin 102(4)
Rock crab
Hudson-Rantan Estuary
New York
"
qp °
© ° ,0 rf>
None
o 1-9
o 10-49
O 50-99
O 100-249
O 2 250
Figure 5 (continued)
The diets of lady crabs and rock crabs were significantly
different in two taxa: M. lateralis for lady crabs and M.
edulis for rock crabs.
Within the crab size ranges sampled adequately by
our gear, we found some ontogenetic differences in di-
ets (Fig. 9). Notably, amphipods and shrimp were con-
sumed by smaller sizes of all three predators. Certain
mollusks, such as N. trivittatus and the Atlantic jack-
knife clam (Ensis directus), increased in occurrence in
foreguts with increasing crab size. Smaller lady crabs
primarily fed upon M. lateralis, but larger ones broad-
ened their diets to include other mollusks such as slip-
persnails (Crepidula spp.) and M. edulis. Blue and rock
crabs exhibited two peaks in consumption of M. edulis:
the foreguts of small crabs contained recently settled
mussels, whereas those of large crabs contained shell
fragments and meat of larger mussels. Xanthidae and
Paguridae, small in body size, were eaten mostly by
intermediate-size predators.
Mann-Whitney tests showed that amphipods were
the only prey significantly different (P<0.01) between
maturity classes for all three crab species.
Spatial variability in diets
Cluster analysis of the diets by species and stratum
defined six groups at 50% similarity (Fig. 10). Group A
consisted of lady and rock crabs caught at oceanward
Stehlik et al.: Distribution patterns of various crab species in the Hudson-Raritan Estuary
701
Blue crab, winter
E3 Males
■ Females
1
12
4 5 6 7 8 9
Blue crab, summer
fll
12 3 4 5
J
6 7 8 9
Lady crab, summer
12 3 4 5 6
l DO
80
60
40
20
0
Rock crab, winter
n
q_q_
gj
6-
4
2
0
Rock crab, summer
^R-n I
2mlA
m
3 4
Strata of Hudson-Raritan estuary
Figure 6
Catch per unit of effort for male and female crabs by seasons and strata,
January 1992-December 1994. Note differences in scale among j axes.
100
Blue
Lady
Rock
m
FISH
□
XAN
HI
PAG
Hi
CRAB
^
SHR
■
AMPH
mi
MUL
i
MYT
m
ENS
□
CREP
g§
NASS
■
POLY
Figure 7
Percent volume of prey (of the 12 chosen categories) of
blue, lady, and rock crabs from the Hudson-Raritan
Estuary, including all strata and size classes, June
1991-June 1992. n=713. Codes for prey taxa are from
Table 3.
Rock_M_Imm
Rock_M_Mat
Blue_M_Imm
Blue_F_Mat
Blue_M_Mat
Blue_F_Imm
Lady_M_Mat
Lady_F_Mat
Lady_M_Imm
Lady_F_Imm
i 1 1 1 1 1 1 1 1
100 90 80 70 60 50 40 30 20
Percent similarity in diet
Figure 8
Cluster analysis dendrogram of similarities of the
diets of species, sexes (M=male. F=female), and matu-
rity stages (Imm=immature, Mat = mature) of blue,
lady, and rock crabs, including all seasons and strata,
June 1991-June 1992. Female rock crabs were not
included because of the small sample size.
702
Fishery Bulletin 102(4)
Table 2
Percent frequency of occurrence (ci
FRE) and percent
volume (%VOL
) of prey of blue, lady.
and rock crabs collected du
"ing the
trawl survey, June 1991-June 1992. Dashes mean that the dietary
item was not found in any stomachs of that crab
species.
"Unid." means unidentified: "other'
means uncommon
identified taxa
not listed below.
Blue crab
Lady crat
Rock crab
r£FRE
<7rVOL
7rFRE
^VOL
%FRE
rrVOL
Number of nonempty foreguts
328
352
295
Plant material
1.5
<0.1
2.8
0.3
4.4
0.1
Hydrozoa
0.6
<0.1
1.4
<0.1
1.4
0.1
Mollusca. unid.
6.7
0.9
3.4
0.9
12.3
14.2
Bivalvia, unid., other
12.2
1.4
11.1
1.6
7.8
4.6
Anadara transversa
—
—
0.3
0.1
—
—
Ensis directus
2.4
0.8
9.9
4.8
8.2
6.2
Lyonsia hyalina
—
—
0.3
<0.1
—
—
Mercenaria mercenaria
0.3
<0.1
0.3
<0.1
—
—
Mulinia lateralis
9.3
13.6
43.5
33.1
6.8
1.4
Mya arenaria
—
—
0.3
0.4
—
—
Mytilus edulis
19.6
14.3
13.9
9.8
28.7
27.3
Nucula proximo
3.4
0.4
5.1
0.6
0.7
0.1
Petricola pholadiformis
1.2
0.1
2.3
0.8
—
—
Pitar morrhuanus
—
—
0.3
<0.1
—
—
Spisula solidissima
—
—
1.7
0.5
—
—
Tellina agilis
4.6
1.5
9.4
2.1
1.4
0.2
Gastropoda, unid., other
6.4
0.7
4.0
0.2
1.0
0.1
Crepidula fornieata, eonvexa
8.6
2.5
5.4
2.8
0.3
<0.1
Crepidula plana
0.6
<0.1
0.3
<0.1
—
—
Nassarius obsoletus
1.5
1.2
0.3
0.2
0.3
<0.1
Nassarius trivittatus
20.8
6.8
15.6
4.6
0.3
<0.1
Naticidae
—
—
0.6
<0.1
—
—
Rictaxis punctostriatus
—
—
0.9
0.1
0.3
<0.1
Cephalopoda
0.3
0.8
0.6
0.3
—
—
Polychaeta, unid., other
2.4
0.2
4.3
0.3
2.7
0.9
Glyceridae
—
—
0.9
0.3
—
—
Hydroides dianthus
—
—
0.3
<0.1
—
—
Nephtyidae
—
—
0.9
0.3
—
—
Nereidae
1.5
0.3
1.7
0.1
0.7
0.3
Pherusa afftnis
—
—
—
—
0.3
0.1
Pectinaria gouldii
2.4
0.8
15.9
2.4
0.7
<0.1
Polynoidae
—
—
0.3
<0.1
1.4
0.1
Insecta
0.3
<0.1
—
—
—
—
Crustacea, unid., other
4.9
0.6
3.4
0.3
5.8
1.4
Amphipoda, unid., other
2.8
0.6
7.7
1.4
1.4
0.2
Ampelisca sp.
1.5
0.6
6.8
1.3
0.7
0.4
Corophium sp.
0.6
0.2
1.7
0.7
—
—
Gammarus sp.
—
—
3.1
3.3
—
—
Mysidacea
—
—
0.3
<0.1
—
—
Caridean shrimp, unid.. other
0.6
<0.1
2.0
0.1
0.7
<0.1
Crangon septemspinosa
2.8
0.6
6.0
2.3
3.1
2.0
Crabs unid., other'
17.7
7.4
8.8
2.7
11.3
4.2
Callinectes sapid us
0.3
<0.1
0.6
0.1
1.4
1.8
Cancer irroratus
1.5
1.0
2.3
0.5
2.0
1.4
Libinia sp.
0.9
0.6
0.9
0.6
1.0
0.5
continued
Stehlik et al.: Distribution patterns of various crab species in the Hudson-Rantan Estuary
. 703
Table 2 (continued)
Blue ci
ab
Lady crab
Rock crab
^FRE
%VOL
<*FRE
WOL
<7tFRE
-2VOL
Crabs unid., other1 (cont.l
0.6
<0.1
2.0
0.1
0.7
<0.1
Ovalipes ocellatus
3.4
3.6
0.6
0.2
1.0
1.0
Pagurus longicarpus
2.1
1.5
1.7
0.6
—
—
Pagurus sp.
8.0
4.3
5.4
2.3
1.7
0.1
Xanthidae
21.1
20.8
15.9
10.6
21.2
18.4
Fish remains and scales
2.1
0.9
3.4
0.7
6.4
3.7
Inorganic debris, sand, mud
0.9
<0.1
0.9
0.2
0.7
0.1
Shell hash
2.4
1.5
—
—
—
—
Human-made objects
4.0
<0.1
4.8
<0.1
1.7
<0.1
Unid. organic matter
—
9.2
—
5.3
—
9.0
Mytilus byssus
1.8
<0.1
2.0
<0.1
3.1
0.2
Table 3
Twelve mutually exclusive prey categories that contributed 80^ of the prey volume of all crabs examined. Codes are used in
Figures 7 and 9. "Other" means uncommon identified taxa.
CODE
Category
Identifiable species
NASS
mud snails
CREP
slipper shells
ENS
razor clam
MYT
blue mussel
MUL
dwarf surfclam
POLY
Polychaeta
AMPH
Amphipoda
SHR
shrimp
CRAB
crabs
PAG
hermit crabs
XAN
mud crabs
FISH
fish, fish scales
Nassarius trivittatus, N. obsoletus
Crepidula fornicata, C. convexa, C. plana
Ensis directus
Mytilus edulis
Mulinia lateralis
all
all
Crangon septemspinosa, unid., other
Libinia sp.. Cancer irroratus. Ovalipes ocellatus, Callinectes sapidus, crab unid.
and others excluding Paguridae or Xanthidae
Pagurus acadianus, P. longicarpus, unid., other
Xanthidae: Dyspanopeus sayi, unid., other
all
outer strata (4, 5, and 7) that consumed large quanti-
ties of M. edulis. Clumps of recently settled and larger
mussels were frequently collected in trawl nets in these
strata. Group B contained crabs from Gravesend Bay,
(stratum 6 ) that ate primarily M. edulis and M. lateralis.
Group C contained crabs caught in the siltier southern
strata and nearby channel (strata 1, 2, and 9) that con-
sumed mainly M. lateralis, M. edulis, and CRABS. Group
D consisted of rock crabs collected at inner strata (2,
3, and 8) that fed primarily upon E. directus and Xan-
thidae. Ensis directus was most common in diets in the
northern sandier strata (strata 3, 5, 6, and 7). Groups
E and F consisted of lady and rock crabs that consumed
mainly M. lateralis. Four species-stratum combinations
did not cluster with any groups.
Temporal, spatial, and trophic niche breadth and overlap
Niche breadth and overlap were calculated for both sexes
of the three crab species (Table 4). Lady crabs of both
sexes had the narrowest temporal niches (3.896 and
4.592), reflecting their presence in the estuary strictly
in warm months. The temporal niche breadth of female
blue crabs (8.187) was greatest, reflecting their year-long
presence in the study area, even in the cold months when
many males remain in rivers. The temporal overlaps of
704
Fishery Bulletin 102(4)
Blue 10°
crab
Lady
crab
Rock
crab
Percent volume
40-59 60-79 80-99 100-119 120-139 140-159 160-185
100
tfiQfiS
tssss
FISH
□
XAN
m
PAG
ggg
CRAB
^
SHR
■
AMPH
on
MUL
□
MYT
ESS
ENS
□
CREP
B
NASS
■
POLY
IffiS
FISH
□
XAN
m
PAG
\g%
CRAB
m
SHR
■
AMPH
m
MUL
□
MYT
ss
ENS
□
CREP
HI
NASS
■
POLY
100
£3
FISH
□
XAN
m
PAG
gg
CRAB
m
SHR
■
AMPH
he
MUL
□
MYT
us
ENS
□
CREP
n
NASS
■
POLY
40-59
60-79
80-99
100-119
120-139
Carapace width classes (mm)
Figure 9
Percent volume of prey I of the 12 categories I by 10- or 20-mm size classes
of blue, lady, and rock crabs, all seasons and strata. Codes for prey taxa
are from Table 3.
male and female lady crabs with male rock crabs were
the lowest in the matrix (0.149 and 0.186).
The spatial niche breadths of lady crabs were larg-
est (7.320 and 7.324) (a result of their nonaggrega-
tive distribution throughout the study area), whereas
the other two species tended to aggregate in certain
locations, particularly in or near channels. Female
rock crabs also had a broad spatial niche, although
they were caught much less frequently than the other
groups. Spatial overlap was highest within species,
particularly between male and female lady crabs
(0.908).
Stehlik et al.: Distribution patterns of various crab species in the Hudson-Raritan Estuary
705
Predator/
stratum
Lady
Lady
Rock
Rock
Rock
Rock
Blue
Lady
Blue
Lady
Blue
Lady
Blue
Blue
Rock
Blue
Rock
Rock
Rock
Lady
Lady
Rock
Lady
Lady
I 1 1 1 1 1 1 1 1 1
100 90 80 70 60 50 40 30 20 10
Percent similarity in diet
Figure 10
Cluster analysis dendrogram of the diets of blue,
lady, and rock crabs from the nine strata of the
Hudson-Raritan Estuary. The vertical line at 50%
similarity defines groups A-F.
42.00
40 00 -
38.00
36.00 -
Trophic niche breadth was greatest in male and fe-
male blue crabs (5.234 and 6.563) and male lady crabs
(6.166) (Table 4). It was narrowest for female rock crabs,
but sample size was low. Overlap was highest within
species: blue crab males and females (0.819), and lady
crab males and females (0.861). Overlap was lowest
between lady and rock crabs, sexes combined (0.427 i.
Discussion
Temporal and spatial overlap within the estuary
The scatter plots (Fig. 5) and spatial niche overlap
indices indicate substantial likelihood of co-occurrence
and encounter among blue, lady, and rock crabs in the
Hudson-Raritan Estuary. However, the species were not
all active in the study area at the same time. Seasonal
migration and winter torpor are two mechanisms that,
at times, prevent interspecies encounters. Rock crabs had
low temporal overlaps with blue and lady crabs because
when rock crabs migrate in from the coastal ocean, lady
crabs migrate out and blue crabs become less active and
sometimes bury themselves. Although otter trawling does
not adequately sample buried blue crabs, commercial crab
dredgers catch large numbers of overwintering blue crabs
from December through March in and near the Raritan
and Chapel Hill channels (Stehlik et al., 1998).
Temporal overlap between blue crabs and lady crabs
was fairly high because of their co-occurrence in the
■fr
it
Z^r^*-^"
A
Qa""
'\ O
-76.00
-74.00
-72.00
-70.00
-68.00
-66.00
Figure 11
Presence of blue, lady, and rock crabs at stations from the
fall 1992 bottom trawl survey, (Northeast Fisheries Science
Center, Woods Hole, MAl. Each point represents presence at
a station. Occurrence inside the estuaries! boxed symbols)
was derived from the literature cited in this article.
warm months. It was expected that intra-estuarine spa-
tial separation might minimize contact between these
species because they are reported to prefer different
substrates. The blue crab is known to occupy a variety
of substrate types, including sand, mud, and submerged
vegetation (Milliken and Williams, 1984; Wilson et al.
1990), whereas the lady crab is primarily collected on
sand (Williams and Wigley, 1977). The lady crab bur-
ies itself in sand more readily than in mud (Barshaw
and Able, 1990) and it is able to forage more efficiently
in sand than in sand-gravel or sand-shell substrates
(Sponaugle and Lawton, 1990). However, as shown in
Figures 5 and 6, lady crabs were not confined to sandy
strata but were most abundant on the fine-grained sedi-
ment strata 1, 2, and 9.
The pattern of seasonal estuarine use by blue and
lady crabs is not unique to the Hudson-Raritan Estuary.
Other estuaries in which the two Portunidae are abun-
dant in summer months but uncommon in winter are
Barnegat Bay, NJ (Milstein et al., 1977; pers. observ. ),
Delaware Bay (Winget et al., 1974), and Chesapeake
Bay (Haefner and Van Engel, 1975).
Rock crabs undergo seasonal migrations from coastal
waters into and out of estuaries, but the timing differs
by latitude. In Canada, the Gulf of Maine, and northern
Massachusetts, rock crabs are much more abundant in
immediate coastal waters, estuaries, and in the inter-
tidal zone in warmer months (Krouse, 1972; Scarratt
and Lowe, 1972). Rock crabs are more numerous in
Narragansett Bay, Rhode Island, in warmer months
(Jeffries, 1966; Clancy4). Juveniles are present inside
Clancy, M. 2002. Personal commun. Boston University,
College of General Studies, Division of Natural Science,
Boston, MA, 02115.
706
Fishery Bulletin 102(4)
Table 4
Niche breadth and overlap for temporal, spat
al, and ti
-ophic dimensions among blue,
lady, and rock crabs.
For temporal and
spatial niches, all crabs (of all sizes) collected
in 1992-
94 are included. For trophic analyses, only the crabs
containing
one or
more of the 12 prey categories were included. Female rock crabs were
size.
not included in trophic overlap
because of the small sample
Number
Mean
Niche
of crabs
CW, mm
breadth
Overlap
matrices
Temporal niche
{n =12 months, 1992-94)
BCF
LCM
LCF
RCM
RCF
Blue crab male (BCM)
2191
125
6.104
BCM
0.854
0.604
0.618
0.297
0.463
Blue crab female (BCF)
3483
129
8.187
BCF
0.649
0.576
0.376
0.564
Lady crab male (LCM)
11883
62
4.592
LCM
0.894
0.186
0.417
Lady crab female (LCF)
25312
61
3.896
LCF
0.149
0.339
Rock crab male (RCM)
14530
85
6.764
RCM
0.479
Rock crab female (RCF)
778
51
5.782
Spatial niche
(ra=9 strata, 1992-94)
BCF
LCM
LCF
RCM
RCF
Blue crab male
2191
125
3.927
BCM
0.757
0.720
0.703
0.675
0.474
Blue crab female
3483
129
5.343
BCF
0.679
0.685
0.746
0.641
Lady crab male
11883
62
7.324
LCM
0.908
0.677
0.616
Lady crab female
25312
61
7.320
LCF
0.678
0.638
Rock crab male
14530
85
5.447
RCM
0.763
Rock crab female
778
51
7.191
Trophic niche
in=12 prey categories, 1991-92)
BCF
LCM
LCF
RCM
Blue crab male
84
111.0
5.234
BCM
0.819
0.570
0.580
0.576
Blue crab female
139
127.9
6.563
BCF
0.629
0.651
0.609
Lady crab male
98
59.4
6.166
LCM
0.861
0.437
Lady crab female
200
54.9
4.655
LCF
0.417
Rock crab male
181
88.8
4.139
Rock crab female
11
53.7
2.620
Trophic niche, sexes combined
Ui = 12 prey categories, 1991-92)
LC
RC
Blue crab (BO
223
121.6
6.250
BC
0.628
0.623
Lady crab ( LC )
298
56.4
5.140
LC
0.427
Rock crab ( RC )
192
86.8
4.008
that bay all year (Reilly and Saila, 1978). In contrast,
in Delaware Bay and Chesapeake Bay they occur in
coastal waters and estuaries mainly in colder months
(Winget et al., 1974; Haefner and Van Engel, 1975;
Haefner, 1976). Our data showed that rock crabs in
the Hudson-Raritan Estuary conform to the pattern of
migration typical of the latter southern bays.
A crossroads or overlap in distribution of the three
crab species is more evident when a broader area on the
continental shelf from Cape Cod to Cape Hatteras is con-
sidered. Crab presence was plotted by using data from
the fall 1992 continental shelf trawl survey <Fig. 11).
Fall surveys are done in September and October when
waters are still warm. In the coastal waters off Rari-
tan, Delaware, and Chesapeake Bays, blue and lady
crabs were collected, whereas rock crabs were collected
mainly on the central shelf. Estuarine presence in warm
months, compiled from citations in the present study, is
marked by symbols.
Sex ratios
In the Hudson-Raritan Estuary, sex ratios of blue, lady,
and rock crabs were different from 1:1. In mature blue
crabs, the sex ratio favored females because the study
area is in the deeper oceanward portion of the estuarine
system, where females release their eggs and overwinter.
Many males spend their entire lives in water of relatively
low salinity (Van Engel, 1958), such as is found in the
nearby Hudson, Raritan, and Navesink-Shrewsbury
rivers. In the Navesink River, the sex ratio of male to
female blue crabs ;>12 cm over a two-year period was
2.6:1 (Meise and Stehlik, 2003).
In the Hudson-Raritan Estuary, female lady crabs
a5 cm outnumbered males 2:1. Many of these females
were ovigerous and therefore estuarine use may be
related to reproduction. We were unable to locate pub-
lished reports of lady crabs or other Ovalipes spp. mat-
ing locations, single-sex migrations, or locations of lar-
Stehlik et al.: Distribution patterns of various crab species in the Hudson-Raritan Estuary
707
val release, any of which might be a reason for the use
of the estuaries by female lady crabs.
The rock crabs that enter the estuary were predomi-
nantly males, and many females may never enter the
estuary. Males use the estuary to molt, and possibly to
avoid predators offshore. In comparison, on the north-
west Atlantic continental shelf, the sex ratio in winter
dredge collections was 1:2.2 males:females (Stehlik et
al., 1991).
Feeding periodicity
Food consumption in crabs is affected by daily and
seasonal cycles, temperature changes, reproductive
rhythms, and molt (Warner, 1977; Stevens et al, 1982;
Ryer, 1987; Mantelatto, 2001). In our study area, blue
crabs ate little when inactive during the winter months,
as reported above. Choy (1986) reported less feeding
during egg-brooding in Portunidae, but in our study we
found that fullness was about 40% in both egg-bearing
and non-egg-bearing females in summer. A lack of feed-
ing before and during molt, until calcification has suf-
ficiently progressed, is typical of crabs (Warner, 1977).
Empty stomachs in premolt and soft rock crabs in our
study supported this observation.
Diet composition
We found that in the Hudson-Raritan Estuary, the most
important prey items of blue crabs by volume were
Xanthidae, then the mollusks M. edulis and M. late-
ralis, whereas only 2% of the prey volume was from
cannibalism. In contrast, small blue crabs are of major
importance in the diets of large blue crabs in Florida
(Laughlin, 1982) and Maryland (Hines et al., 1990).
and cannibalism is the source of more than 75% of the
mortality of juveniles near estuarine shores (Hines and
Ruiz, 1995). The major targets of cannibalism, early
instars or molting juveniles, may be more abundant in
rivers adjacent to our study area (Meise and Stehlik.
2003).
The diets of rock crabs in estuarine and coastal
Canada and Maine usually contained a larger num-
ber of prey categories than did the diets in the pres-
ent study (Scarratt and Lowe, 1972; Drummond-Davis
et al.. 1982; Hudon and Lamarche, 1989; Ojeda and
Dearborn, 1991). These northern studies were done on
rock, boulders, cobble, sand, and algal beds, where the
diversity of habitats within a study area may offer a
larger assortment of potential prey than the soft-bottom
habitat of our estuary.
In the Hudson-Raritan Estuary, juveniles of commer-
cially or recreationally harvested species were rarely
consumed by the three species of crabs. Among mol-
lusks, M. arenaria and M. mercenaria were scarce in
crab stomachs, perhaps because other taxa such as M.
lateralis, N. trivittatus, and Xanthidae provided abun-
dant prey. The other commercially important species
eaten by crabs was the blue crab juvenile, but infre-
quently as mentioned above.
Differences in diet among species, sexes,
and size classes of predators
Our data did not support our hypotheses, based on exist-
ing studies, that blue, lady, and rock crabs would have
different diets as a consequence of their species-specific
body and chela structures. Blue and lady crabs (unlike
rock crabs) swim, allowing them a greater foraging
area than rock crabs. Chela structure affects the type
and size of prey that can be crushed (Vermeij, 1978;
Seed and Hughes, 1995; Behrens Yamada and Bould-
ing, 1998). In Portunidae. the long chelae (in relation
to their CW) have short muscle fibers better suited to
quick grabbing than to prolonged crushing (Warner
and Jones, 1976; Seed and Hughes, 1997). The chelae
of Cancridae are monomorphic (same characteristics
left and right sides), have relatively short, stout teeth,
and close relatively slowly because of their muscle fibers
(Warner and Jones, 1976). Chela crushing force (New-
tons), measured with a force transducer, is positively
correlated with chela height and thickness (Govind
and Blundon, 1985; Block and Rebach, 1998). Although
the chela structures of blue and rock crabs are quite
different, the chelae of mature rock crabs (9-13.5 cm
CW) generate crushing forces comparable to those of
cutter and crusher chelae of mature male blue crabs
(12-16 cm) (Govind and Blundon, 1985).
Chela crushing force in mature blue and rock crabs is
likely to be more than sufficient for successful foraging
upon all but the largest prey (Block and Rebach, 1998)
and may not be a major determinant of diet. In fact,
crabs often prey upon small or young bivalves rather
than on large sizes, perhaps because the latter require
more handling time and may damage chelae (Juanes.
1992; Seed and Hughes, 19951. Because Portunidae
swim and have more versatile chelae, they may be ex-
pected to have broader trophic niches than Cancridae.
In our study, blue crabs had the broadest trophic niche,
lady crabs had an intermediate trophic niche, and rock
crabs had the narrowest trophic niche.
We found no significant differences in diet by sex
within species. Sexual dimorphism within a crab spe-
cies accelerates after puberty (Hartnoll. 1978), but our
study included many immature crabs. Some experiment-
ers using force transducers found no significant differ-
ence in crushing force between the sexes of blue crabs
of a broad size range (Blundon and Kennedy, 1982;
Seed and Hughes, 1997), but in blue crabs >135 mm,
males produced significantly more force than females
(Eggleston, 1990). Sexual dimorphism is found in chela
length, but not chela height, in lady crabs (significantly-
different slopes of CL/CW by regression; Stehlik, un-
publ. data).
Carapace width and the proportion of chela height to
carapace width are positively correlated with crushing
force, which makes it possible for larger crabs to con-
sume larger, harder-shelled mollusks or crustaceans
(Hartnoll, 1978; Block and Rebach, 1998). The larg-
est lady crabs do not grow to the carapace widths or
chela lengths of mature blue crabs; therefore the force
708
Fishery Bulletin 102(4)
of their chelae cannot match those of blue crabs. As
they grow, Cancridae and Portunidae undergo shifts in
diet, and may be divided into ontogenetically distinct
trophic units (Laughlin, 1982; Stevens et al., 1982:
Stoner and Buchanan, 1990; Rosas et al.. 1994). In
our study, larger crabs dropped amphipods and shrimp
from their diets, but otherwise only minor changes
occurred in prey identity and relative volumes of prey
taxa among size classes (Fig. 9). An interesting ontoge-
netic shift was in the size of prey eaten: small crabs ate
small individuals of prey taxa, such as M. edulis, and
Xanthidae, and large crabs ate large individuals of the
same taxa. Thus in our study the influence of physical
structure upon diet was greater as body size increased
within a species than among species.
Spatial variability and overlap in diets
The three predators were scattered throughout the
cluster diagram of diet among strata of the estuary
(Fig. 10), yet crabs from inner and outer groups of strata
usually clustered separately. We concluded that loca-
tion influenced diet more than did predator identity.
The inner, outer, and channel strata differ in depth,
sediment type, currents, and mean temperature, and
therefore in benthic and epibenthic prey assemblages.
Our results support the concept that these species are
mainly opportunistic in diet, as was suggested for blue
crabs (Laughlin, 19821, and rock crabs (Hudon and
Lamarche, 1989). The Hudson-Raritan and other nearby
coastal and estuarine areas from Long Island Sound to
Chesapeake Bay are crossroads where blue, lady, and
rock crabs share space and resources.
Acknowledgments
We thank those who helped design and carry out the
Hudson-Raritan Estuary trawl surveys, especially Stuart
Wilk, Anthony Pacheco, and Eileen MacHaffie. We also
thank Fred Farwell, Sherman Kingsley, and the NOAA
Corps captains and crew. Suellen Fromm was instru-
mental in obtaining data from NEFSC trawl surveys.
We thank the scientists who shared their opinions and
unpublished data. We are indebted to colleagues Mary
Fabrizio, Clyde MacKenzie, John Manderson, Carol
Meise, Frank Steimle, Allan Stoner, and anonymous
reviewers who helped improve the manuscript. This
paper is dedicated to the memory of Tony Pacheco.
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711
Abstract — As nearshore fish popu-
lations decline, many commercial
fishermen have shifted fishing effort
to deeper continental slope habitats
to target fishes for which biological
information is limited. One such fish-
ery that developed in the northeastern
Pacific Ocean in the early 1980s was
for the blackgill rockfish (Sebastes
melanostomits), a deep-dwelling
(300-800 mi species that congre-
gates over rocky pinnacles, mainly
from southern California to southern
Oregon. Growth zone-derived age esti-
mates from otolith thin sections were
compared to ages obtained from the
radioactive disequilibria of 210Pb, in
relation to its parent, 226Ra, in otolith
cores of blackgill rockfish. Age esti-
mates were validated up to 41 years,
and a strong pattern of agreement
supported a longevity exceeding 90
years. Age and length data fitted
to the von Bertalanffy growth func-
tion indicated that blackgill rockfish
are slow-growing (A' = 0.040 females.
0.068 males I and that females grow
slower than males, but reach a greater
length. Age at 509c maturity, derived
from previously published length-at-
maturity estimates, was 17 years for
males and 21 years for females. The
results of this study agree with gen-
eral life history traits already recog-
nized for many Sebastes species, such
as long life, slow growth, and late
age at maturation. These traits may
undermine the sustainability of black-
gill rockfish populations when heavy
fishing pressure, such as that which
occurred in the 1980s, is applied.
Radiometric validation of age, growth,
and longevity for the blackgill rockfish
(Sebastes melanostomus)
Melissa M Stevens
Allen H. Andrews
Gregor M. Cailliet
Kenneth H. Coale
Moss Landing Marine Laboratories
8272 Moss Landing Road
Moss Landing, California 95039
E-mail address ((or A. H Andrews, contact author): andrewsiS'mlml calstate.edu
Craig C Lundstrom
Department of Geology
University of Illinois— Urbana Champaign
255 Natural History Bldg.
1301 W.Green Street
Urbana, llmois 61801
Manuscript submitted 9 June 2003
to the Scientific Editor's Office.
Manuscript approved for publication
18 June 2004 by the Scientific Editor.
Fish. Bull. 102:711-722 (20041.
The blackgill rockfish (Sebastes mela-
nostomus) is a deep-water rockfish
that is found mainly along the conti-
nental slope between 300 and 800 m
depth off central and southern Cali-
fornia (Moser and Ahlstrom. 1978;
Cross, 1987; Williams and Ralston,
2002). Although not as heavily tar-
geted in relation to other commercially
important rockfish species, a directed
commercial fishery for blackgill rock-
fish has existed since the mid-1970s,
beginning off southern California
(Point Conception area) and spreading
northward ( Monterey area) as stocks
of other heavily fished rockfishes
declined (Butler et al., 1999). Using
acoustic sonar and set nets, the com-
mercial fleet was able to catch large
aggregations of previously unexploited
blackgill rockfish. Landings peaked in
1983 with 1346 metric tons (t) caught
coast-wide, but declined over the next
decade, presumably because of the dis-
appearance of the large concentrations
that could be located with acoustical
gear (Butler et al., 1999). In 2001,
141 t were reportedly landed along
the entire west coast (PacFIN1) — less
than half of the allowable catch (343 t;
NOAA, 2001) for blackgill rockfish
that year.
The first stock assessment of black-
gill rockfish was made by Butler et
al. (1999). One objective of this as-
sessment was to determine age and
growth characteristics, which were
then applied to estimate age-at-ma-
turity, natural mortality, and stock
biomass. Using conventional aging
methods (i.e., otolith increments),
we estimated that blackgill rockfish
live at least 87 years and reach full
(100%) maturity from 13 to 26 years
for females, and from 13 to 24 years
for males. Although such estimates
are useful and should be considered
whenever available, validation of the
age-estimation procedure is needed to
be certain of accurate age estimates
(Beamish and McFarlane, 1983;
Campana, 2001). Inaccurate age de-
terminations in some cases have led
to overharvesting of stocks such as
Pacific ocean perch (Sebastes alutus)
1 PacFIN (Pacific Fisheries Information
Network). 2002. Commercial fisher-
ies landing data. http://www.PacFIN.
org. [Accessed 9 August 2002].
712
Fishery Bulletin 102(4)
and orange roughy (Hoplostethus atlanticus; Beamish,
1979; Archibald et al., 1983; Mace et al., 1990). These
historical examples of fishery collapses necessitate that
age validation be achieved before age and growth infor-
mation is applied to management.
In the last decade, radiometric age validation has
been applied successfully to over 20 species of rock-
fishes and other marine teleosts (Burton et al., 1999;
Kastelle et al., 2000; Andrews et al., 20021. The most
common technique uses the disequilibria between two
radioisotopes, radium-226 (226Ral and lead-210 (210Pb),
present in the otolith (Bennett et al., 1982; Smith et al.,
1991). Radium-226 is a naturally occurring radioisotope
and calcium analogue that is incorporated from the
surrounding seawater into the aragonitic crystalline
matrix of fish otoliths. Radium-226 decays through a
series of short-lived radioisotopes to 210Pb. Because
the half-lives of these isotopes are known, the ratio of
activity between them (210Pb:226Ra) gives a measure of
elapsed time since the initial incorporation of 226Ra into
the otolith (Campana et al., 1990). Radium-226 decays
very slowly (a 1600 year half-life) in relation to 21"Pb
(a 22 year half-life), allowing the activity ratio of these
radioisotopes to build into secular equilibrium (1:1 ra-
tio; Smith et al., 1991). Based on this relationship (also
referred to as ingrowth), the 210Pb: 226Ra activity ratio
is suitable for age determination in fishes up to 5 half-
lives of 210Pb, or approximately 120 years of age (An-
drews et al., 1999b; Campana. 2001). This approach is
therefore ideally suited to the blackgill rockfish, whose
longevity has been estimated at almost 90 years (Butler
et al., 1999).
The objectives of this study were 1) to estimate age
from otolith growth zone counts, 2) to describe growth,
and 3) to validate the annual periodicity of growth
zones used to estimate longevity for the blackgill rock-
fish with the radiometric aging technique. An ancillary
objective was to create a reliable predictive relationship
between average otolith weight and estimated age for
use as a timesaving tool in the management of this
species. Growth zones quantified in sectioned otoliths
were used to estimate age, and growth was described
by using the von Bertalanffy growth function. Final age
estimates were directly compared to radiometric ages to
evaluate agreement between the two methods and ulti-
mately were used to validate age estimation procedures,
age-at-maturity, and longevity for this species.
Materials and methods
Approximately 1210 blackgill rockfish sagittal otoliths
were available for this study. Otoliths were collected
by National Marine Fisheries Service (NMFS) person-
nel from commercial vessels in 1985 at ports along the
California coastline (Long Beach to Fort Bragg), and
during NMFS research surveys from 1998 to 2000 from
central California to the Oregon-Washington border.
Thirty-two juvenile blackgill rockfish, collected from
spot prawn traps along the central California coast, were
provided by Robert Lea of the California Department of
Fish and Game (CDFG). Fish total length iTL; cm or
mm), catch area (port or geographic location), and otolith
weights (right and left. 1985 samples only) were pro-
vided. Otoliths were first considered for age estimation
i sectioning!, and the remainder were reserved for radio-
metric analysis. Otolith weights (left and right, male
and female) were measured to the nearest milligram
and compared with £-tests to determine if significant
differences in mass existed between sides or sexes.
Estimation of age and growth
Based on previous aging studies and the need to con-
serve samples for radiometric analysis, approximately
310 otoliths (25% of the collection) were assumed to be
sufficient for age estimation. The left otolith from 5 to
30 fish, depending upon the number available in each
50-mm size class (ranging from 100 mm to 600 mm),
was randomly chosen by using a basic resampling tool.
Otoliths were thin-sectioned and mounted onto glass
slides. Approximately 50 otoliths were damaged in the
sectioning process, leaving 260 otoliths available for
age estimation.
Sections were viewed by three readers under magnifi-
cation (25 and 40x) with transmitted or reflected light.
Each reader obtained age estimates by inspecting all
available growth axes, choosing the most discernible
axis, and reading it three times consecutively. A growth
zone (here termed an "annulus") was defined as one pair
of translucent (winter-forming) and opaque (summer-
forming) bands. A final age, based on each reader's most
confident estimate, was chosen. Precision between and
within readers was compared by using average percent
error (APE; Beamish and Fournier, 1981 1, index of pre-
cision (D) and coefficient of variation (CV; Chang, 1982).
Percent agreement among readers was also calculated.
Reader 1 (author) determined the final age estimate for
each section as described in Mahoney (2002). Ages that
could not be confidently resolved (through re-examina-
tion or discussion) were removed from analysis.
Length and age estimates for males, females, and sex-
es combined were fitted to the von Bertalanffy growth
function (VBGF). A small portion of juvenile samples
(/j =16) were included in each function. Because there
was strong agreement between facility aging techniques
(MLML and NMFS, La Jolla. Butler et al. 1999), ad-
ditional aged samples were added to strengthen the
VBGF and age prediction models (ra=119). Estimates of
age at first, 50%, and 100^ maturity were calculated
by inserting existing size at maturity data (Echeverria.
HIST ) into the VBGF and solving for age (t).
Age prediction, age group determination,
and core extraction
Campana et al. 1 1990 ) was the first to circumvent the
assumption of constant 226Ra uptake throughout the
life of the fish by eliminating younger growth layers
from adult otoliths, leaving just the oldest layers of
Stevens et al.: Radiometric validation of age, growth, and longevity of Sebastes melanostomus
713
otolith growth (i.e., the core, representing the first few
years of life). Radium-226 is present at such low activity
levels, however, that many otolith cores from fish of a
similar age and same sex must be pooled to acquire the
mass of material needed for detection (-0.5 to 1 gram;
Andrews et al., 1999a, 1999b). Because we possessed
a limited number of blackgill rockfish otoliths (-1200),
an age prediction model was created to conserve otolith
material for radiometric analysis. It was appropriate to
assume from the results of Francis (2003) that within-
sample heterogeneity with respect to otolith age and
mass growth rate was negligible in the core material.
To determine age groups for radiometric analyses,
final ages for fish whose otoliths were sectioned, along
with their corresponding average otolith weight (left
and right, «=2), were used to predict age for the re-
maining fish in the collection. Several parameters were
regressed to determine a predictive relationship be-
tween average otolith weight (henceforth termed "oto-
lith weight") and estimated age (i.e., section age). The
following regressions were compared to estimated age
by using Kruskal-Wallis (nonnormal) ANOVA: 1) oto-
lith weight (to the nearest 0.001 g), 2) otolith weight
and fish length (to the nearest 1 mm), and 3) otolith
weight plus otolith length (to the nearest 0.001 mm)
multiplied by otolith weight (as an interaction term). A
power function was also investigated but did not result
in a better fit than that provided by a simple linear
regression (either log-transformed or normal). A paired
sample (-test and student's (-test for slopes were used
to determine if a significant difference existed between
male and female otolith weight, and between male and
female otolith weight-to-age regressions, respectfully.
The final regression equations were applied to the aver-
age otolith weight for all individual remaining fish to
obtain a predicted age. Age groups were created if there
was sufficient otolith material from fish of the same sex
and of a similar predicted age.
The predicted age range for each group was kept as
narrow as possible while permitting enough material for
analysis; approximately 25 to 50 otoliths were needed at
a target core weight of 0.02 g. Fish that had both oto-
liths intact (not sectioned or broken) were preferred to
reduce the number of fish for each radiometric sample.
To better insure sample conformity, 90% confidence
intervals with respect to fish length and otolith weight
were used to eliminate from each group dissimilar fish
that may have varied significantly from predicted age.
In addition to this discriminating technique, groups
were further confined by capture year and location.
Only samples caught in the same year and similar geo-
graphic location (based on the majority of port locations
within 300 miles) were included in the same group.
Core size was determined by viewing several whole
juvenile blackgill rockfish otoliths with estimated ages
between 1 and 7 years. The first annulus was deter-
mined to be approximately 2 mm wide, and a 3-year-old
otolith was measured at 3 mm wide, 4 mm long, and 1
mm thick, and having a weight of 0.02 g. These dimen-
sions were chosen as the target core size because a core
of this size could be easily extracted, yet was young
enough to minimize the possible error associated with
variable 226Ra uptake in the first few years of growth.
Otoliths from adult fish were ground down to the tar-
get core size with a lapping wheel and 80- to 120-grit
silicon-carbide paper. Otoliths from selected juveniles,
if older than age 3 (core size), were also ground to the
target core size.
Radiometric analysis
The radiometric analysis was conducted as described in
Andrews et al. (1999a, 1999b). Because previous studies
have revealed extremely low levels of 210Pb and 226Ra in
otolith samples, trace metal precautions were employed
throughout sample cleaning and processing (Bennett et
al., 1982; Campana et al., 1990; Andrews et al. ,1999a).
Acids were double distilled (GFS Chemicals", Powell,
OH) and all dilutions were made using Millipore- filtered
Milli-Q water (18 MQ/cm). Samples were thoroughly
cleaned, dried, and weighed to the nearest 0.0001 g
prior to dissolution. Whole juvenile otoliths groups were
analyzed first to determine if exogenous 210Pb was a
significant factor, and to determine baseline levels of
226Ra activity.
Because of the low-level detection problems associ-
ated with (beta) /3-decay of 2lnPb, the activity 210Pb
was quantified through the autodeposition and (alpha)
a-spectrometric determination of its daughter proxy,
polonium-210 (210Po, half-life=138 days; Flynn, 1968). In
preparation for 210Po analysis, samples were dissolved
in acid and spiked with a calibrated yield tracer, 208Po,
estimated to be 5 times the activity of 210Po in the oto-
lith sample. Polonium isotopes from the sample were
autodeposited onto a purified silver planchet (A.F Mur-
phy Die and Machine Co., North Quincy, MA) held in
a rotating Teflon™ holder over a 4-hour period (Flynn,
1968). The activity of 208Po and 210Po on the planchets
was measured with ion-implant detectors in a Tennelec
(Oak Ridge, TN) TC256 or-spectrometer interfaced with
a multichannel analyzer and an eight channel digital
multiplexer. Counts were recorded with Nucleus'-' soft-
ware (Nucleus Personal Computer Analyzer II, The Nu-
cleus Inc., Oak Ridge, TN) on an IBM computer. Counts
measured over periods that ranged from 28 to 50 days
accumulated from 160 to 919 total counts. Lead-210 ac-
tivity, along with uncertainty, was calculated in a series
of equations that corrected for background and reagent
counts, as well as error associated with count statistics
and procedure (pipetting error, yield-tracer uncertainty,
etc; Andrews et al., 1999a). The remaining sample was
dried and conserved for 226Ra analysis.
Determination of 226Ra employed an elemental sepa-
ration procedure followed by isotope-dilution thermal
ionization mass spectrometry (TIMS) as described in
Andrews et al. (1999a, 1999b). The sample was spiked
with a known amount of 22sRa yield tracer estimated
to produce a 226Ra:228Ra atom ratio close to one. The
samples were dissolved in strong acid and dried re-
peatedly (~90-100°C) until the sample color was bright
714
Fishery Bulletin 102(4)
white, indicating that most organic material had
been removed. A three-step elemental separation
procedure was used to remove calcium and bari-
um, elements that interfere with the detection of
radium in the TIMS process. This involved pass-
ing the samples through three cation exchange
columns, two containing a slurry of BioRad AGE
50W-X8 resin (first and second column), and one
containing EiChroM Sr® resin (third column).
The samples were introduced to a highly acidic
medium within the columns, which separated the
elements according to elution characteristics (An-
drews et al., 1999b).
Radiometric age for each group was determined
by inserting the measured 210Pb and 22BRa activi-
ties into the secular equilibrium model (Smith et
al., 1991) and correcting for the elapsed time be-
tween capture and autodeposition. Because these
activities were measured from the same sample,
the calculation was independent of sample mass
(Andrews et al., 1999a, 1999b). Propagated uncer-
tainty associated with the final 210Pb activity was
based on count statistics, and procedural error
and uncertainty for the final 226Ra activity was
based on procedural error and an instrumental
TIMS analysis routine (Wang et al., 1975; An-
drews et al.. 1999b). The combined errors were
used to calculate high and low radiometric ages.
Accuracy of age estimates
Measured 210Pb:226Ra activity ratios for each age
group, along with their total sample age (predicted
age + time since capture), were plotted with the
expected 210Pb:226Ra growth curve. Each age group
range was widened by multiplying the minimum
and maximum age in the range by the age estimate
CV, which was determined from the variability in
age estimates among three readers. Agreement
between the measured ratio with respect to esti-
mated age and the expected ratio (ingrowth curve)
provided an indication of the age estimate accuracy.
Radiometric age was compared to the average pre-
dicted age for each group by using two tests: 1) a
paired sample £-test to determine if a significant
difference existed between the two age estimates
for the groups and 2) predicted age was plotted
against radiometric age and the correlation was
compared to a hypothetical agreement line (slope of
1) by using r-tests for slope and elevation.
Results
- __ — -
mZ&toSEL
\
1 mm
jjK,
yjmiffZ- iTm
pp>*^^
i
:
Figure 1
Three images of a blackgill rockfish (Sebastes melariostomus)
otolith section viewed with transmitted light at 25x magni-
fication (top), 40x (center), and 80x magnification (bottom).
This section was aged most consistently as 90 years under a
microscope, but because of finer digital resolution and contrast,
the section pictured can be aged as high as 102 years.
Estimation of age and growth
Growth zones observed within otolith sections of most
blackgill rockfish were difficult to interpret. Distinction
of the first annulus was often ambiguous, and the band-
ing pattern during the first several years (1 to -10) of
growth was, in some sections, wide and inconsistent.
After approximately 8 to 12 growth zones, the zone width
transitioned to a narrower zone, which became extremely
compressed after 20-40 growth zones. In some sections,
these older zones were beyond optical resolution, whereas
in others they were remarkably clear (Fig. 1).
Stevens et al.: Radiometric validation of age, growth, and longevity of Sebastes melanostomus
715
Table 1
Comparison
of von Bertalanffy growth function
pai
ameters for this studv and Butler et al.
(1999
; in parentheses), for com-
bined sexes,
females.
and males. All lengths are
total
lengths (mm). Note that the sample
size for females and males does
not sum
to 332 because the same juvenile samp
es
Ul-.
= 16) were used for each sex, and onlv
once
for combined sexes. N.R.=
not reported
Combined sexes
Females
Males
L_ (mm)
509(524')
548(554')
448(467')
95% CI
491-528 (N.R.)
520-576 (N.R.i
434-462 (N.R.)
k
0.045(0.040)
0.040(0.040)
0.068(0.060)
95% CI
0.038-0.052
0.033-0.047
0.058-0.078
*o
-4.86 (-5.02)
-4.49 (-4.66)
-2.37l-2.98)
95% CI
-6.60 to -3.12
-6.30 to -2.67
-3.55 to -1.19
/!
332(335)
181 (98)
167(78)
r2
0.81(0.79)
0.87(0.90)
0.87(0.92)
1 Total ler
gths
from some samples in Butler et al., 1999
were estimated from fork length < FL in mmi by using an
equation from Echeverria and
Lenarz
1984).
The most consistent axis in the otolith section for
which confident interpretations could be made was
along either the sulcus ridge, or along the dorsoventral
margin. Final age estimates were resolved for 197 fish,
or approximately 76% of the 260 successfully sectioned
otoliths. Agreement among readers was relatively low:
approximately 24% of age estimates were within ±1
year, 61% were within ±5 years, and 87% were within
±10 years. The mean difference in age estimates be-
tween readers was 2.9 ±4.0 years. Among the three
readers, APE was 10.7%, D was 8.4%, and CV was
14.6%. Average percent error, D, and CV estimates were
comparable within readers; reader 1 APE was 5.2%, D
was 4.1%, and CV was 7.0%. The two oldest fish to be
aged were a 90-year-old male (450 mm TL) collected in
1999 and an 87-year-old female (546 mm TL) collected
in 1985. Both individuals were caught south of Point
Conception, California.
The VBGF fitted to age and length data resulted in
distinct growth curves for male and female blackgill
rockfish (Fig. 2). This difference is also represented
by non-overlapping confidence intervals with respect
to the primary VBGF parameters (LM, k; Table 1). The
growth coefficient, k, ranged from 0.040 (±0.007, fe-
male) to 0.068 (±0.010, male), and asymptotic length
was 448 ±14 mm for males to 548 ±28 mm for females.
The asymptotic length for females was 32 mm less than
the largest female fish sampled (580 mm TL), and for
males, was 74 mm less than the largest male sampled
(522 mm TL). The fit for all three functions was satis-
factory (r2=0.81, 0.87; Table 1, Fig. 2). Estimated ages
at first, 50%, and 100% maturity, derived from insert-
ing published estimates of length-at-maturity (Echever-
ria, 1987) into the growth model for each sex, were 15,
21, and 22 years for females and 13, 17, and 28 years
for males (Table 2).
Table 2
Age at maturity estimates, in years, for ma
blackgill rockfish (95'i confidence intervals
theses). Maturity estimates were derived
published estimates of length at maturity
Bertalanffy growth function.
e and female
are in paren-
by inserting
into the von
First
50%
100%
maturity
maturity
maturity
Females
15(12-22)
21(16-31)
22(17-33)
Length at
maturity' ( mm )
300
350
360
Males
13(11-15)
17(14-20)
27(22-35)
Length at
maturity' (mm)
290
330
390
' Echeverria 11987).
Age prediction, age group determination,
and core extraction
A paired sample r-test indicated that there was a sig-
nificant difference between male and female average
otolith weight (f=4.54, P<0.001), and a student's r-test
for slopes indicated a significant difference between male
and female average otolith weight-to-age regressions
(rm, = 1.967, ?=2.87, P<0.05). Therefore, male and female
age estimates and regressions were treated separately.
There was no statistical difference between regres-
sions involving fish length and average otolith weight
(Kruskal-Wallis one-way ANOVA on ranks, #=4.834,
P=0.089). A simple linear regression, with average oto-
lith weight as the independent variable and estimated
716
Fishery Bulletin 102(4)
age as the dependent variable, was sufficient to pre-
dict age. Log normalizing the regressions to stabilize
the variance in older age estimates was unsuccessful
(Cochran's test: «=0.05, 36 df, C=0.4748, P=0.486). The
final regressions are given in Figure 3.
Fourteen age groups based on the predicted ages of
unsectioned otoliths were chosen. These groups consist-
700
600
500
400
■2> 300
200
100
o males
X females
female
Female age = 548(1 - e-°<*°('*««»)t ^=181 (/=0.87)
Male age = 448(1 - e"0068!'*237!), n=167 (/=0.87)
10 20 30 40 50 60
Otolith section age (yr)
70
80
90
100
Figure 2
Blackgill rockfish (Sebastes melanostomus) von Bertalanffy growth functions
plotted for males and females. Observed and expected values, as well as the
parameters of the equations, are given. Note that the same juvenile samples
(/; = 16) were included in both male and female equations.
100 -
males:
90 -
y=108.24x-2.65
r2=0.83, n=151 "
80 -
, females
females: ♦ J^-
y=93.803x + 0.175 ' males . ^^
70 -
f 60"
I 50 -
m
CO
a 4°-
<
30 -
20 -
r2=0.85, n=165 ' ♦
* ■ l^' ^
■ 0 9 m, _^^° •»
" ■ • • ^^^r?
■ males
10 -
• females
0 'T "' 1 1 1 1 1 1 1 1 1
0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 0.800 0.900
Average otolith weight (g)
Figure 3
Predictive relationship between average otolith weight and estimated age for blackgill
rockfish (Sebastes melanostomus). These regression equations were used to predict
the age of fish whose otoliths were reserved for radiometric analysis.
ed of four juvenile groups, and five male and five female
adult groups I Table 3). Fish lengths ranged from 82 mm
to 580 mm TL, and predicted age ranged from 1 to 69
years. The number of otolith cores per age group ranged
from 11 to 59, representing 7 to 32 fish per group. Total
sample weight for each age group ranged from 0.4649 g
to 1.6424 g. Whole otolith weight ranged from 0.041
to 0.842 g, and average individ-
ual core weight for the adult age
groups ranged from 0.025 g to
0.028 g. The process of extracting
the core inadvertently destroyed
some otoliths in the grinding pro-
cess, leading to smaller samples
for some groups.
Radiometric analysis
Radiometric analysis of all age
groups (n = 14) resulted in the
successful determination of 210Pb
activity for all samples, and lim-
ited success for 226Ra (Table 4).
Activities of 210Pb increased, as
expected, fivefold from juvenile to
adult age groups, and ranged from
near 0.01 dpm/g for the juvenile
samples to over 0.05 dpm/g for the
oldest age groups. Error associ-
ated with these measurements
ranged from 3.7 to 9.2 % (Is). The
detection of 226Ra activity was
met with some technical difficul-
ties. Because of poor radium
recovery, radium measure-
ments were unreliable in
three samples and radium
was lost in four samples.
Therefore, an average of the
reliable 226Ra measurements
was used because of the rel-
ative consistency of levels
measured in these samples
(0.0643 ±0.0035 dpm/g,
n=l). The use of a single
estimate for 226Ra activ-
ity was acceptable prior to
refinement of the technique
(Andrews et al., 1999b). Cal-
culated 210Pb:226Ra ratios
increased as expected from
0.172 to 0.845 and 0.912 for
the oldest groups (Table 4).
Age estimate accuracy
Radiometric ages were in
agreement with predicted
ages, as evidenced by concor-
dance of 210Pb:226Ra activity
Stevens et al.: Radiometric validation of age, growth, and longevity of Sebastes melanostomus
717
Table 3
Summary data for 14 pooled otolith age groups of blackgill rockfish. The age range and sample weight of each age group was
based on the age prediction model and otolith availability. Groups were confined by year of capture, and for the 1985 samples, by
port location. Mean total length (±1 standard deviation) of individuals per group is provided, along with the number offish and
otoliths, total sample weight, and average core weight.
Sample
number
Age group
(yr)
Sex
Capture
year
Mean
length
±cjiTL mm)
Number of
fish,' number
of otoliths
Sample
weight
(g)
Avg.
core weight
(g)
BG1
1-3
Juvenile
1998
154+26
7, ll2
0.4649
0.042
BG2
4
Juvenile
1998
200 ±8
10, 82
1.1687
0.065
BG3
4-5
Juvenile
1999
217 ±9
15, 192
1.6630
0.088
BG4
1-7
Juvenile
2000
119 ±37
25, 362
0.7854
0.022
BG5
29-31
Female
1985
400 ±20
25,46
1.2510
0.027
BG6
26-28
Male
1985
379 ±19
22.35
0.8866
0.025
BG7
11-17
Female
1998
276 ±20
22,33
0.9018
0.027
BG8
39-41
Female
1985
458 ±22
31,53
1.3332
0.025
BG9
48-54
Male
1985
459 ±21
25,48
1.2491
0.026
BG10
60-69
Female
1985
525 ±30
19,30
0.8254
0.028
BG11
19-23
Male
1998
329 ±16
21,39
1.0313
0.026
BG12
56-59
Female
1985
502 ±28
13.25
0.6989
0.028
BG13
39-41
Male
1985
428 ±24
31,59
1.6424
0.028
BG14
42-47
Male
1998
423 ±26
32,54
1.4267
0.026
1 Both otoliths
were not available
for every fish chosen.
- Whole j
jveni
e otoliths.
Table 4
Summary of radiometric results for pooled otolith age groups. Samples are listed in order of increasing age-group range. Activi-
ties are expressed as disintegrations per minute, per gram (dpm/g). Radium-226 activity was averaged among samples with low-
analytical error (<10%; n=l) and was determined to be 0.0643 (±0.0035) dpm/g. This value was then applied to all samples to
gain an estimate of 226Ra activity and radiometric age. Agreement between radiometric age and predicted age was qualified by
the degree of overlap between the two age ranges. Radiometric age incorporates the time between capture and analysis.
Sample
210Pb activity
210pb.226Ea
Radiometric
Radiometric
Predicted age
Average
Age range
number
(dpm/g) ±%s1
activity ratio
age (yr)
age range (yr)
group range2
age3 (yr)
agreement^
BG1
0.0154 ±8.6
0.234
7.1
5.4-8.7
0-3
2
Exceeds
BG2
0.0124 ±6.7
0.193
5.5
4.3-6.5
4-5
4
Overlaps
BG3
0.0118 ±5.5
0.184
5.5
4.5-6.4
4-6
4.5
Overlaps
BG4
0.0111 ±9.2
0,172
6.0
5.3-6.7
0-8
3.5
Encompasses
BG7
0.0300 ±5.6
0.467
18.0
15.2-21.4
9-19
14
Overlaps
BG11
0.0276 ±5.8
0.430
15.7
13.2-18.7
16-26
21
Overlaps
BG6
0.0440 ±4.7
0.684
22.3
16.2-30.3
22-32
27
Overlaps
BG5
0.0439 ±4.4
0.683
22.1
16.2-30.3
25-35
30
Overlaps
BG13
0.0481 ±3.8
0.749
29.3
21.8-40.4
33-47
40
Overlaps
BG8
0.0494 ±4.0
0.769
32.1
23.7-45.1
33-47
40
Overlaps
BG14
0.0499 ±3.8
0.777
45.8
37.3-59.1
36-54
45
Overlaps
BG9
0.0560 ±3.7
0.871
50.7
35.8-85.1
41-62
51
Encompasses
BG12
0.0586 ±4.7
0.912
62.9
40.7-undef.
48-67
57
Encompasses
BG10
0.0543 ±4.4
0.845
44.8
31.6-71.6
51-79
65
Overlaps
' Error calculation based on the standard deviation of 210Pb activity (Wanget al., 1975).
2 Predicted age range was extended by 14.6% of coefficient of variation (CV) associated with growth-zone-derived age estimates.
3 The average predicted age of each radiometric age group.
4 Definition of terms: Exceeds = radiometric age range is greater than predicted age range; Overlaps = radiometric age range partially agrees with
predicted age range; Encompasses = radiometric age range was in agreement with predicted age range.
718
Fishery Bulletin 102(4)
in otolith cores with expected ingrowth curves through
time (Fig. 4). Of the 14 pooled otolith groups, three had
radiometric age ranges that fully encompassed the pre-
dicted age range, ten resulted in overlapping age ranges,
and one exceeded predicted age (Table 4). In addition,
radiometric ages were in close agreement with predicted
ages in a direct comparison (r2=0.88; Fig. 5). Further
Ntests indicated no significant difference in slope (£=1.92,
P=0.092) or elevation U=0.163, P=2.201) between the
regression and a hypothetical agreement line (slope of
1), confirming the close agreement of radiometric age
and predicted age.
Discussion
Estimation of age and growth
The growth pattern present in otoliths of blackgill rock-
fish was often difficult to interpret. Complications inher-
ent to the growth pattern were the following: obscure
growth zones up to age 10-15 (the ages when the otolith
begins to thicken laterally), rapid transition to slower
growth, conflicting or ambiguous growth patterns, and
poor resolution of extremely compressed zones in old-age
fish. Irregular patterns may have led to enumeration of
false growth zones (checks), and the compression of the
outer layers may have concealed growth zones present in
older fish. This finding has been consistent among previ-
ous studies of rockfishes I Chilton and Beamish, 1982).
1.2
1 1
1.0
0.9
0.8
0.7
06
0.5
04
0.3
0.2
0.1
0.0
4^
^
=2
i
Expected Ingrowth Curve
a Juvenile age groups
• Female age groups
■ Male age groups
20
40 60
Sample age (yr)
Figure 4
Measured 210Pb:226Ra ratio plotted against total sample age (mean
predicted age plus time since capture! of blackgill rockfish iSebastes
melanostomus), with respect to the expected 210Pb:226Ra activity
ratio. Horizontal error bars represent the predicted age range (based
on age prediction model extended by 14.6% CV). Vertical error
bars represent high and low activity ratios based on the analytical
uncertainty associated with 2lnPb and 226Ra measurements.
Because of the difficulty involved in interpreting growth
patterns, aging of blackgill rockfish otoliths involved a
high degree of individual subjectivity, as evidenced by
the relatively low precision (D=8.4%) and high varia-
tion (CV=15%) between readers. However, there were
some remarkably clear otoliths and for these we were
highly confident of age estimates (Fig. 1). Overall, 87%
of between-reader age estimates were within 10 years,
emphasizing that although the method of interpretation
of growth can be imprecise, it provides a reasonable
indication of the growth characteristics and longevity
of this species.
The von Bertalanffy growth parameters for male
and female blackgill rockfish appear to indicate that
blackgill rockfish possess distinct patterns of growth
(Table 1). Female blackgill rockfish exhibited a slower
growth rate than males up to approximately 25-30
years of age (Fig. 2). At this point, the male growth
rate slows and approaches an asymptotic length of 448
mm, but females continue to grow in length, reaching
an asymptotic length of 548 mm. This trend of slower
growing, but ultimately larger females has been ob-
served in other slope-dwelling Sebastes species, such
as the darkblotched (S. crameri; Rogers et al., 20001,
and splitnose (S. diploproa; Wilson and Boehlert. 1990)
rockfishes. For both sexes, the growth coefficient is low
(k = 0. 040-0. 068) when compared to shallower-dwell-
ing (50-200 m) rockfishes, such as the greenstriped
(S. elongates, 0.10-0.12; Love et al., 1990) and widow
(S. entomelas, 0.20-0.25; Williams et al., 2000) rock-
fishes, but very similar to other deep-dwell-
ing, long-lived species, such as the short-
spine thornyhead (Sebastolobus alaseanus,
£ = 0.020; Cailliet et al., 2001), yelloweye (S.
ruberrimus, £ = 0.046; Andrews et al., 2002),
and bank (S. rufus, £ = 0.041; Cailliet et al.,
2001) rockfishes.
Previous maturity estimates for blackgill
rockfish (7-9 yr males, 6-10 yr females;
Echeverria 1987). based on whole otolith
counts, were much lower than estimates ob-
tained from section ages in the present study
(Table 2). Maturity estimates from our study
support those derived by Butler et al. (1999).
largely because the aging protocol was the
same between facilities. Although our growth
model included some age estimates (37%)
from Butler et al. (1999), our results further
confirm age at maturity (Table 2). Compared
to other species of the genus, blackgill rock-
fish have a late maturity that resides at the
upper end of the range for rockfishes (Cail-
liet et al., 2001; Love et al., 2002).
Extraordinarily old ages in average-size
fish exhibited by the blackgill rockfish
should not be dismissed as an anomaly. In
this study the oldest blackgill rockfish was
a 90-year-old male (aged as high as 102
years) that was 450 mm TL. This fish was
160 mm less than the maximum reported
100
Stevens et al.: Radiometric validation of age, growth, and longevity of Sebastes melanostomus
719
0
length (Love et al., 2002). Accord-
ing to an experienced rockfish age
and growth researcher, "some of
the oldest specimens [rockfish] are
rarely the largest (lengthwise),
and most, if not all, are males."
(Munk2) The reasons for this age-
length pattern are beyond the
scope of this study, but the impli-
cations for stock dynamics and
management are that it is worthy
of further consideration.
Age prediction, age-group
determination,
and core extraction
The use of otolith weight as a proxy
for age has benefits over conven-
tional otolith aging methods by
reducing cost, increasing sample
size, and allowing greater objectiv-
ity (Boehlert, 1985; Pawson, 1990;
Fletcher, 1991; Pilling et al., 2003).
In this study, predicting ages from
otolith weight increased the number
of unsectioned otoliths that could
be used in the radiometric analysis,
but the prediction model also ampli-
fied the uncertainty associated
with estimates of age. especially
in older fish. The variance around
the regression line increased with
otolith weight, and log normalizing the data did not
eliminate this problem. Older predicted ages, there-
fore, were more uncertain than younger ages (Fig. 3).
Although limited to a specific otolith weight range, the
prediction model presented here may provide managers
with a more efficient and less costly way to investigate
the age structure of blackgill rockfish stocks.
In an ideal study, otoliths from the entire estimated
age range for blackgill rockfish would be available in
the sample set. Otoliths from fish with predicted ages
greater than 70 years, however, were not present in our
study in sufficient numbers to allow age determination
by radiometric methods. This was so, even though more
than half of the 1200 otolith pairs obtained for ourstudy
were sampled directly from commercial fishing vessels
in 1985 along the coast of central and southern Cali-
fornia, where the bulk of the fishery occurred. Because
fishermen often target adult aggregations, the absence
of these older individuals may be an indication that the
population had already experienced depletion of older
age classes at the time of sample collection, particularly
if natural mortality is thought to be low for most rock-
1:1 line
Regression
y=0.823x + 2.534
r =0.89
20
40 60
Predicted age (yr)
80
100
Figure 5
Direct comparison of mean predicted age and radiometric age for 14 pooled
otolith age groups for blackgill rockfish (Sebastes melanostomus). A regres-
sion of the data points and 1:1 line of agreement are included for comparison.
Horizontal error bars represent the error associated with age estimation
(average predicted age multiplied by 14.6% CV), plus the standard error of
the regression (Is) used to predict age for radiometric samples. Vertical error
bars represent high and low radiometric age estimates based on the analytical
uncertainty associated with 210Pb and 22fiRa measurements.
fishes (Bloeser3). However, it is possible that the largest,
oldest fish are naturally rare, even at the start of an
intensive commercial fishery. Knowledge of blackgill
rockfish pre-exploitation stock structure and population
dynamics would help to elucidate which (depletion of
older age classes or a natural situation of low numbers
of older fish) is the more likely scenario.
Radiometric analysis
In previous studies the analytical uncertainty of 226Ra
was the limiting factor in radiometric age determina-
tion (Andrews et al., 1999a). Typically, TIMS determi-
nation of 226Ra reduces error to less than 1-3% of the
determined value, but technical difficulties (improperly
mixed nitric acid) led to poor recovery and loss of radium
in seven samples. The remaining seven samples were
deemed reliable because of relatively high radium recov-
ery, longer run times, and low analytical uncertainty
as determined by the TIMS analysis routine. The 226Ra
activity determined for these samples was consistent
2 Munk. K. 2002. Personal commun. Alaska Department
of Fish and Game, P.O. 25526, Juneau, AK 99802.
3 Bloeser, J. A. 1999. Diminishing returns: the status of
West Coast rockfish, 94 p. Pacific Marine Conservation
Council, P.O. Box 59, Astoria, OR 97103.
720
Fishery Bulletin 102(4)
enough that we could assume that 226Ra activities were
similar among all samples and that use of an average
was valid (0.0643 [±0.0035] dpm/g). This approach is
acceptable because 226Ra activities measured in pre-
vious radiometric studies on Pacific rockfishes were
relatively constant. For example, the activity of cored
yelloweye rockfish (S. ruberrimus) otoliths had a mean
226Ra activity of 0.0312 (±0.0026) dpm/g (n=18; Andrews
et al., 2002), and the rougheye rockfish (S. aleutianus),
another deepwater species (to 730 m; Love et al., 2002),
had a similar otolith core 226Ra activity averaging 0.065
(±0.003) dpm/g (Kastelle et al., 2000).
Accuracy and uncertainty of ages estimates
Radiometric activities measured in blackgill rockfish
otoliths generally agreed with expected activity ratios
for 210Pb and 226Ra (Fig. 4), confirming the validity of
growth-zone-derived age estimates. In addition, a direct
comparison between radiometric age and predicted age
resulted in a strong agreement (r2=0.89; Fig. 5), which
was further supported by slope and elevation tests that
revealed no significant difference from a 1:1 agreement
line.
The most critical sources of error involved in age
estimation, prediction, and radiometric age determina-
tion were the following: 1) age estimate uncertainty, 2)
regression error associated with predicted ages, and 3)
analytical uncertainty associated with the radiometric
aging technique (TIMS and a-spectrometry). Conven-
tional aging techniques are inherently subjective (Boe-
hlert, 1985; Campana, 2001) and thus create uncertain-
ty associated with an estimated age. This uncertainty
is transferred to the prediction model, where the natu-
ral variability associated with individual otolith weight
must also be considered. For most samples, however, the
error bars either overlapped or were in contact with the
agreement line (Figs. 4 and 5), further confirming the
concordance of radiometric age with predicted age.
Implications for management
When considering the longevity of rockfishes for which
a maximum age has been reported (Munk, 2001; Cail-
liet et al., 2001), a longevity exceeding 90 years places
the blackgill rockfish within the top 2Q(7c of long-lived
rockfishes. There is a trend for rockfishes that may
indicate that longevity increases as maximum depth of
occurrence increases, and physiological adaptations to
the environmental conditions of deep-sea living could
provide an explanation (Cailliet et al., 2001). The con-
firmed longevity and the maximum depth of occurrence
(~800 m) for the blackgill rockfish provide further sup-
port for this concept.
Longevity in the rockfishes has been central to its
evolutionary success in relation to other marine teleosts.
The suite of life history characters implicit with a long
lifespan (slow adult growth, late age-at-maturity, low
adult natural mortality) represent a "slow and steady"
adaptive strategy, whereby the energy allocated towards
individual growth is prolonged, eventually contributing
to greater fecundity (due to larger size at maturity)
over the lifespan of the individual. This reproductive
strategy serves to propagate genetic material across
several generations, as well as to diffuse the effect of
mortality associated with each reproductive event (Lea-
man, 1991). In this sense, longevity may act to buffer
the species against short-term (El Nino) and long-term
environmental change (Pacific Decadal Oscillations),
and the stochasticity inherent in the Pacific Ocean
system (Moser et al., 2000).
In the absence of fishing pressure, the genetic con-
tribution of a slow-growing, longer-lived species may
be more conserved in the collective species' gene pool
i Munk2 1. In the presence of fishing pressure, however,
this "slow and steady" adaptation may be detrimental
(Musick, 1999). Although modeling fish populations for
the purpose of management typically involves some or
all of these parameters, the focus is often on deter-
mining sustainable biomass and this approach largely
ignores the unknown effects of changes in age struc-
ture due to removal of the oldest individuals from the
population (Craig, 1985), as well as a loss of genetic
diversity that could prevent full recovery of severely
depleted populations (Hauser et al, 2002). Given the
current depressed condition of many heavily fished rock-
fish stocks, species-specific life history characteristics,
such as longevity, growth rate, and age-at-maturity
estimates, should be given thorough consideration in
the development of an effective management strategy.
Management regulations that account for these charac-
teristics, such as a limited fishing season, or designa-
tion of harvest refugia (Yoklavich, 1998), would provide
a stronger basis for conservation and sustainability of
the resource.
Acknowledgments
We wish to thank John Butler, Don Pearson, and Cindy
Taylor of the Southwest Fisheries Science Center, Mark
Wilkins, Jerry Hoff, Waldo Wakefield, and Bob Lauth
of the Alaska Fisheries Science Center, and Bob Lea
of CDFG for donating specimens for this study. Mary
Yoklavich (NMFS). Di Tracey and Larry Paul (NIWA,
New Zealand), Kristen Munk (ADFG), Don Pearson
(NMFS), Tom Laidig (NMFS), and Steve Campana
(DFO, Canada) provided valuable insight into black-
gill rockfish growth patterns. Patrick McDonald of the
Oregon Department of Fish and Wildlife aged otolith
sections. Pete Holden at the University of California,
Santa Cruz, measured radium in the refined samples
using TIMS. The comments and suggestions of three
anonymous reviewers were greatly appreciated. This
work was supported by the National Sea Grant College
Program of the U.S. Department of Commerce's National
Oceanic and Atmospheric Administration under NOAA
Grant number NA06RG0142, project number R/F-182.
through the California Sea Grant College Program; and
in part by the California State Resources Agency.
Stevens et al.: Radiometric validation of age, growth, and longevity of Sebastes melanostomus
721
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723
Abstract— Larval and juvenile devel-
opment of finescale menhaden (Bre-
voortia gunteri) is described for the
first time by using wild-caught indi-
viduals from Nueces Bay, Texas, and
is compared with larval and juvenile
development of co-occurring gulf
menhaden (B. patronus). Meristics.
morphometries, and pigmentation pat-
terns were examined as development
proceeded. An illustrated series of
finescale menhaden is presented to
show changes that occurred during
development. For finescale menhaden,
transformation to the juvenile stage
was completed by 17-19 mm standard
length (SL). By contrast, transfor-
mation to the juvenile stage for gulf
menhaden was not complete until 2.3-
25 mm SL. Characteristics useful for
separating larval and juvenile fines-
cale menhaden from gulf menhaden
included 1) the presence or absence of
pigment at the base of the insertion of
the pelvic fins; 2) the standard length
at which medial predorsal pigment
occurs; 3) differences in the number
of dorsal fin ray elements; and, 4) the
number of vertebrae.
Descriptions of larval, prejuvenile, and
juvenile finescale menhaden
(Brevoortia gunteri) (family Clupeidae),
and comparisons to gulf menhaden (B. patronus)
James M. Tolan
Texas Parks and Wildlife Department
6300 Ocean Dr., NRC 2501
Corpus Christ!, Texas 78412
E-mail address: James Tolan @tpwd. state. tx. us
David A. Newstead
Center for Coastal Studies
Texas A&M University-Corpus Christi
6300 Ocean Dr., NRC 3216
Corpus Christi, Texas 78412
Manuscript submitted 9 September 2003
to the Scientific Editor's Office.
Manuscript approved for publication
14 June 2004 by the Scientific Editor.
Fish. Bull. 102:723-732 (20041.
Finescale menhaden {Brevoortia gun-
teri Hildebrand), one of three recog-
nized species of menhaden (Reintjes,
1969; Hettler. 1984) found in the Gulf
of Mexico, occurs in the northern and
western Gulf of Mexico, from Chande-
leur Bay, Louisiana, to Campeche Bay,
west of Punto Morros (McEachran
and Fechhelm, 1998). Despite their
common occurrence in coastal and
estuarine waters along the Texas and
Mexico coasts (Simmons, 1957; Helher,
1962; Hoese, 1965; Whitehead, 1985;
Castillo-Rivera and Kobelkowsky,
2000), their early development has
not been described. Early develop-
ment of gulf menhaden (B. patronus
Goode), on the other hand, has been
well described (Suttkus, 1956; Hettler,
1984; Ahrenholz, 1991).
In coastal waters of the western
Gulf of Mexico, finescale menhaden
are spatially and temporally sym-
patric with gulf menhaden (Castillo-
Rivera et al., 1996). Gulf menhaden
are found throughout the northern
gulf from Florida Bay to Campeche
Bay. Yellowfin menhaden \B. smithi
Hildebrand) are found in the eastern
gulf from the Mississippi River Delta
to Cape Lookout, North Carolina,
and co-occur with finescale menha-
den only in its extreme western range
(Dahlberg, 1970; Hoese and Moore,
1977 ). A large amount of hybrid intro-
gression occurs between gulf and yel-
lowfin menhaden, although finescale
hybrids (either finescalexgulf menha-
den or finescalexyellowfin menhaden)
have not been reported (Ahrenholz,
1991).
Both finescale and gulf menhaden
are estuarine-dependent species in-
habiting shallow nursery areas for
their early development (Gunter,
1945; Shaw et al., 1985; Castillo-Ri-
vera and Kobelkowsky, 2000). Gulf
menhaden are intermittent or multi-
ple spawners (Christmas and Waller,
1975; Lewis and Roithmayr, 1981),
and adults move offshore in late sum-
mer and early fall. Spawning off the
coast of Texas is protracted, and the
spawning season begins at the end of
August and continues through April
(Shaw et al.. 1985). Estuarine immi-
gration of gulf menhaden ranging in
size from 10 to 32 mm TL has been
observed from late October through
April (Copeland, 1965: Gallaway and
Strawn, 1974; Allshouse, 1983). In
Nueces Bay, the greatest densities of
gulf menhaden larvae are seen from
late February to early May, and the
peak immigration of 19-26 mm TL
individuals occurs from late April and
early May (Newstead, 2003). Fines-
cale menhaden spawn in estuarine or
nearshore areas (Gunter, 1945; Sim-
mons, 1957) and their spawning sea-
son has been reported from November
to March (Ahrenholz, 1991). Hellier
(1962) reported 25-mm-TL specimens
taken from the Upper Laguna Madre
724
Fishery Bulletin 102(4)
on the lower Texas coast during February, and Gunter
(1945), Simmons (1957), and Hoese (1965) have reported
postlarval finescale menhaden from the middle and low-
er Texas coasts from January to May. Gulf menhaden
have received considerable attention in fishery science
because of their large population sizes and resulting
ecological and economic importance in the northern
Gulf of Mexico (Nelson and Ahrenholz, 1981; Smith,
19911, whereas finescale menhaden are less numerous
and not directly sought by any recognized fishery (Ahr-
enholz, 1991). Our study describes for the first time the
development of postflexion (late larval), prejuvenile, and
juvenile finescale menhaden.
Materials and methods
squares regression techniques (SigmaPlot, version 5.0,
SPSS Inc., Chicago, IL) in order to graphically illustrate
any development differences between the two species.
Increasing ratios (BD/SL, CP/SL, and EYE/SL) were
described with an exponential rise-to-maximum equation:
y = a(l
-bx
),
whereas, the decreasing ratio of PAL/SL measurements
were described with a exponential decay equation:
y = ae
-bx
In both equations, y = body proportion ratio; .r = SL:
a = intercept; and b = SL specific exponential rate of
change.
A total of 170 wild-caught finescale menhaden larvae
and juveniles were used to describe early development.
All specimens came from ichthyoplankton collections
in Nueces Bay, Texas (27.87°N, 97.5TW), during May
and June 2003. Individuals were collected in the tidal
channels of Nueces Delta with a side-mounted push net
(60-cm ring net, 0.505-mm mesh). For comparison, 357
wild-caught gulf menhaden larvae and juveniles col-
lected during May and June of 1999, 2000, and 2002
from two nearby stations outside the delta (less than 1.5
km away), in addition to the tidal channel collections of
2003. were also studied. All individuals were initially
fixed in either 10% formalin or 95% ethanol and trans-
ferred to fresh 95% ethanol after 48 hours.
Pigment patterns were recorded and specimens of fin-
escale menhaden were illustrated. Gulf menhaden were
not illustrated because the figures in Hettler (1984) are
adequate.
Morphometries
Body measurements were made to the nearest 0.1 mm
with an ocular micrometer fitted to a dissecting micro-
scope. All individuals collected were postflexion, preju-
venile, or juvenile stage as defined in Leis and Rennis
(1983), and standard length (SL) was measured as the
distance from the tip of the snout along the midline to
a vertical line through the posterior edge of the hypural
plate. All lengths are SL unless otherwise noted. Defini-
tions and other terms are as follows:
BD = body depth; vertical depth at the pectoral sym-
physis.
CP = caudal peduncle; horizontal distance from the
posterior edge of the dorsal fin base to the pos-
terior edge of the hypural plate.
EYE = eye diameter; horizontal distance between the
anterior and posterior edges of the fleshy orbit.
PAL = preanal length; distance from the tip of the
snout to the origin of the anal fin. measured
along the midline.
Ratios of these four body proportion measurements in
relation to SL were fitted by means of nonlinear least
Meristics
Each specimen was examined to determine whether
scale formation had been initiated, and a total count
of ventral scutes for specimens in which they were suf-
ficiently developed was obtained. A total of 37 finescale
and 48 gulf menhaden from the 2003 collections were
cleared and stained according to Potthoff ( 1984) and
used for fin-ray and vertebrae counts. Because of the dif-
ficulty in accurately counting myomeres in transforming
clupeids (Hettler, 1984; Ditty et al., 1994), we chose to
count total vertebrae and use the number of postdorsal
and preanal vertebrae instead of postdorsal and preanal
myomeres as a potential diagnostic character. Fin-ray
counts included dorsal, anal, and caudal fins (both prin-
cipal and procurrent rays).
Results
Morphological development
Finescale menhaden larvae were first collected at 9.7 mm
and ranged to 22.5 mm as transforming juveniles (Fig.
1). Transformation from the larval to the juvenile form
began around 14 mm and was completed by around 20
mm (Fig 2). Ratios of body depth, caudal peduncle, and
eye diameter all increased in relation to standard length
as larvae grew, whereas snout-to-anal length decreased
i Table 1). The decrease in snout-to-anal length reflected
the transformation from the elongate fusiform shape of
the larvae to the laterally compressed deep-bodied shape
of the juvenile. Scales began to form at around 15 mm on
the caudal peduncle region and progressed forward along
the ventral and lateral surfaces towards the dorsal sur-
face. None of the individuals examined had the enlarged
and fringed median scales preceding the dorsal fin,
which are an adult characteristic of the genus Brevoor-
tia. Ventral scutes also began forming around 15 mm,
and the full complement of 27-31 scutes (McEachran
and Fechhelm, 1998) was found by 19 mm.
Gulf menhaden ranged from 11.7 mm as larvae to
40.4 mm juveniles. For gulf menhaden, body depth.
Tolan and Newstead: Larval and |uvenile development of Brevoortia gunten
725
Table 1
Proportional measurements in
development.
relation to standard length
(SL) used to describe
finescale
menhaden {Brevoortia
gunteri) larval
Length class
(mm, SL)
Number of
specimens
Body depth:
SL
Preanal length:
SL
Caudal peduncle:
SL
Ey
3 diameter:
SL
<11.0
1
0.100
0.804
0.256
0.054
11.1-12.0
2
0.108
0.798
0.259
0.059
12.1-13.0
5
0.119
0.778
0.251
0.059
13.1-14.0
15
0.139
0.764
0.263
0.064
14.1-15.0
28
0.136
0.756
0.269
0.062
15.1-16.0
25
0.168
0.735
0.281
0.074
16.1-17.0
23
0.208
0.711
0.302
0.082
17.1-18.0
17
0.220
0.705
0.311
0.085
18.1-19.0
3
0.239
0.700
0.327
0.080
19.1-20.0
2
0.219
0.700
0.304
0.078
>20.1
1
0.318
0.690
0.304
0.093
caudal peduncle, and eye diameter ratios all similarly
increased in relation to standard length as larvae grew,
whereas snout-to-anal length decreased (Table 2). Scale
initiation in gulf menhaden was not seen until 19 mm,
and ventral scutes did not begin forming until around
18 mm. The full complement of scutes (28-32 scutes;
McEachran and Fechhelm, 1998) was seen by around
25 mm. No enlarged median dorsal scales were noted
from the gulf menhaden individuals examined.
With little overlap in the 15-20 mm size range (see
Fig. 1) and a limited number of juvenile-size finescale
menhaden (SL>20 mm), it was not possible to effectively
separate finescale and gulf menhaden morphometrically
on the basis of BD:SL, PAL:SL, CP:SL, and EYE:SL
ratios (Fig 3). By 25 mm, proportional body measure-
ments had become nearly constant for gulf menhaden
whereas body measurements were still changing for
finescale menhaden even though they appeared to be
fully transformed. For a fish of given size, finescale
menhaden typically had a greater body depth, a shorter
preanal length, and a greater caudal peduncle length
than gulf menhaden.
Meristic features
No recently hatched or preflexion finescale menhaden
were examined and all postflexion individuals followed
the fin development sequence identified for other clupe-
ids (Houde et al., 1974: Hettler, 1984; Ditty et al., 1994).
The caudal and dorsal fins are first to develop, followed
by the pelvic fins, whereas the pectoral fins are the
last to fully develop even though the pectorals are the
first fins to form as nonrayed buds. Only vertebrae and
dorsal-fin ray counts were useful in separating finescale
and gulf menhaden, because most other meristics over-
lapped (Table 3). Finescale menhaden had fewer total
vertebrae ( = 43 vs. 46) and fewer dorsal-fin rays (median
125
100
75
B. gunteri
n=170
50
25
§ o
O
J"
^^
25
50
S. patronus
n=357
75
100
—
i
i i i
5 15 25 35 45
Body length (mm)
Figure 1
Length-frequency histograms for Brevoortia gunteri
and B. patronus derived from ichthyoplankton col-
lections in Nueces Bay, Texas, during May and June
(1999-2003).
value = 18 vs. 21) than gulf menhaden. Postdorsal and
preanal vertebrae also showed a high degree of overlap
between the two species (Table 3). The forward move-
ment of the anal fin in relation to the dorsal fin was
most evident in fully transformed gulf menhaden, and
the number of postdorsal-preanal vertebrae decreased
from 4 to -3. The relative placement of the anal fin also
726
Fishery Bulletin 102(4)
i'liiiiiiin'illftiiiiumi
13.7 mm
5.0 mm
Figure 2
Developmental stages of Brevoortia gunteri. iAi Postflexion larva, 13.7 mm. (B) Postflexion
larva, 15.0 mm. (C) Transforming larva, 17.2 mm. (D) Transforming larva, 19.0 mm. (Ei
Transformed juvenile, 23.9 mm.
Table 2
Proportional
measurements relative
to standard length
(SL
) used to describe
gulf menhaden {Brevoortia
patronus) larval
development.
Length class
Number of
Body depth:
Preanal length:
Caudal peduncle:
E
ve diameter:
(mm, SL)
specimens
SL
SL
SL
SL
<14.0
1
0.086
0.829
0.229
0.061
14.1-15.0
1
0.119
0.786
0.238
0.061
15.1-16.0
3
0.136
0.764
0.261
0.063
16.1-17.0
4
0.136
0.764
0.261
0.063
17.1-18.0
5
0.144
0.749
0.257
0.065
18.1-19.0
13
0.169
0.733
0.265
0.067
19.1-20.0
26
0.183
0.725
0.274
0.074
20.1-21.0
22
0.176
0.735
0.271
0.068
21.1-22.0
17
0.236
0.719
0.282
0.084
22.1-24.0
9
0.286
0.709
0.298
0.095
24.1-26.0
2
0.337
0.730
0.313
0.103
26.1-29.0
11
0.352
0.730
0.299
0.098
29.1-32.0
4
0.356
0.740
0.308
0.100
>32.1
3
0.380
0.736
0.294
0.097
Tolan and Newstead: Larval and |uvenile development of Brevoortia gunten
727
gSSgSSgHJfMISHp
Figure 2 (continued)
Table 3
Meristies in finescale menhaden, Brevoortia gunteri, (37 specimens) and in gulf menhaden. B. patronus, (48 specimens). Median
values are given in parentheses.
B. gunteri
B. patronus
Number in
full
complement
Meristic
B. gunteri
B. patronus
Caudal-fin rays
Principal (dorsal)
10
10
10-11
(ventral l
9
9
9-10
Procurrent (dorsal)
7-9(8)
8-9(8)
8-9
(ventral l
7-8(7)
5'-8(7)
7-8
Dorsal-fin rays
17-20 ( 18 )
16'-23(21)
17-20
21-23
Anal-fin rays
18-24(22)
20-23(21)
20-25
18-22
Vertebrae
43-44(43)
40'-46(46)
42-44
45-46
Postdorsal and preanal
vertebrae
0-3(2)
-32-4(l)
2-43
1 B. patronus larva SL = 11.7 mm.
2 B. patronus fully transformed individual SL = 40.4 mm.
3 Postdorsal and preanal myomere counts in larvae 10-15 mm SL (Ditty et al., 1994)
728
Fishery Bulletin 102(4)
A
0.4 -
° s^<r^^~°°~
(Q 0.3 -
Q.
0
"D
O 02 -
m
/ 0(8, y/
A^A A ®5Ccb0
0 1 -
a* *aA /
a o y
0 0 — i 1 1 ■ 1 1 1 ■ 1 1 1 1 r
10 15 20 25 30 35 40
090 i
B
0.85 -
a B gunteri
d o e. patronus
_J
W
§ 080 -
D)
c
QJ
ra
ra 0 75 -
CL
0 70 -
a a\
A \aa A
^#V «o j^ ^e O O _
aA^\^ ° ° ^ % o o o °
a^a|1o°£ 0<<?0 o
A
0 65 -
i i 1 1 1 1 1
10 15 20 25 30 35 40
Body length (mmj
Figure 3
Morphometric comparisons (shown as a percentage of standard length
[SL1 1 for wild-caught Brcvoortia gunteri and B. patronus. (A) BD/SL.
1B1 PAL/SL. (C) CP/SL. (Dl EYE/SL. Best fit nonlinear regression
lines were fitted by least squares estimation.
changed in finescale menhaden, although the number
of postdorsal-preanal vertebrae only decreased from
three to zero.
Pigmentation
Early pigmentation patterns in finescale menhaden (Fig.
2) were similar, but not identical, to the pigmentation
described for gulf menhaden (Suttkus, 1956; Hettler,
1984). Both dorsal and ventral notochord tip pigment,
which are diagnostic for the genus Brevoortia (Fig. 2),
were found in all individuals examined. In specimens
<14 mm, pigmentation was sparse and found primarily
along the ventral margin of the caudal peduncle, the
base of the anal fin, at the end of the gut near the vent.
and ventrally as two lines beginning at the pectoral fin
bases below the foregut. Along the dorsal margin of the
hindgut, 3-6 fine melanophores were usually present.
At the base of the pelvic fins, 1-2 small, paired stellate
melanophores were present. Additionally, all individuals
had a medial melanophore along the isthmus (ventral
midline anterior to the cleithrum) and most had an
internal melanophore at the nape. Other pigment pres-
ent in the smallest finescale larvae included a series of
paired melanophores anterior to the dorsal fin base (seen
in 26^ of the larvae examined). This predorsal mid-line
pigment series increased both in size and number as the
larvae grew. The head was unpigmented.
By 16 mm, pigment increased along the dorsal sur-
face of the hindgut, the base of the dorsal fin, and the
Tolan and Newstead: Larval and |uvenile development of Brevoortia gunten
729
gunteri
patronus
D
gunten
patronus
20 25 30
Body length (mm)
Figure 3 (continued)
base of the anal fin (Fig. 2). The predorsal midline
melanophores series was more prominent (51% of the
individuals displayed this pigment pattern). Additional
pigmentation included paired lateral melanophores near
the dorsal region of the brain cavity, internal pigment
above the notochord from the posterior margin of the
base of the dorsal fin to the caudal fin, and internal
pigment over the gas bladder. A large melanophore was
also present above the base of the pectoral fin.
By 18 mm, the dorsal surface of the head became
highly pigmented with up to 25 small melanophores.
The snout, lower jaw, and pelvic fins were also pigment-
ed by this size. The dorsal and ventral surfaces of the
caudal peduncle, as well as the medial predorsal region
became more densely pigmented. Outstanding features
at this size included 2-9 ventrolateral melanophores in
a series along the digestive tract level with the pectoral
fins, and isthmus pigment was separated into two spots
in many individuals. By 20 mm, the head region was
heavily pigmented and the mid-line predorsal pigment
progressed fully to the head. Ventrolaterally, 10-30 me-
lanophores forming a triangular pattern covered much
of the digestive tract. New pigmentation features at this
size included 1-3 small melanophores at the base of the
eye and an internal series below the notochord from the
base of the dorsal fin to the caudal fin. Pigmentation
at the pelvic fin insertion was lost in some specimens,
although it was still visible internally in all but one of
the cleared and stained specimens. Isthmus pigmenta-
tion was also lost at this size.
Living juveniles (>20 mm) are silvery in color over
most of the body. The head, back, and dorsal and cau-
dal fins are all pigmented. In preservation, two dark,
slash-like pigments spots were present on the posterior
lateral body above and below the urostyle. In nearly
all other aspects, juvenile finescale menhaden closely
730
Fishery Bulletin 102(4)
resembled adults by this size. No humeral spots were
noted in the two individuals examined.
Discussion
Finescale menhaden larvae resemble the larvae of other
clupeids (Houde and Fore, 1973; Jones et al., 1978;
McGowan and Berry, 1983; Hettler, 1984: Ditty et al.,
1994) in having elongate, slender bodies, light pigmen-
tation, and a small head lacking spines. They have a
long, straight gut, often with striations along the hind-
gut, posteriorly placed dorsal and anal fins, and the
vent is always posterior to the dorsal fin base (Jones
et al., 1978). Hettler (1984) discussed the separation of
individual species of Brevoortia, and Ditty et al. (1994)
presented a synopsis of characters to separate clupeid
larvae (<15 mm) based on meristic, morphometries,
and pigmentation. Finescale menhaden have 43-44
vertebrae, whereas gulf menhaden have 44-46. Yel-
lowfin menhaden are reported to have 45-47 vertebrae
(Houde and Swanson, 1975). The number of vertebrae,
which should approximate the number of myomeres
in larvae much smaller than those collected in this
study, in conjunction with pigment differences have been
shown to be useful in separating clupeid species com-
plexes (Ditty et al., 1994). In the western gulf, counts of
43-44 vertebrae (=myomeres) would separate finescale
menhaden from other clupeid larvae such as Sardinella
aurita (45-47 vertebrae; Ditty et al., 1994), Etrumeus
teres (48-50 vertebrae; Fahay, 1983), and Opisthonema
oglinum (45-46 vertebrae; Richards et al., 1974). Spe-
cies from the western gulf with similar vertebral counts
(Harengula jaguana, 39-42; Houde et al., 1974; and
Jenkinsia lamprotaenia, 39-42; Powles, 1977) can be
distinguished from finescale menhaden by their larger
PAL:SL ratio (>85% at 15 mm for Harengula vs. <85l7c
for finescale menhaden. Table 1) and fewer anal rays
(13-14 for Jenkinsia vs. 18-24 for finescale menhaden,
Table 3). Although vertebral counts were used suc-
cessfully in distinguishing finescale menhaden from
gulf menhaden, the time necessary to clear and stain
larvae makes this method impractical for distinguishing
between large numbers of menhaden.
In larval and prejuvenile stages, finescale and gulf
menhaden are morphologically very similar. Propor-
tional body measurements overlapped too greatly to
reliably distinguish the two species. Only the presence
of medial predorsal pigment prior to transformation,
stellate melanophores at the pelvic fin base, and the
size at transformation were useful characters in distin-
guishing the two species. Hettler (1984) noted that gulf
menhaden lack paired melanophores in the predorsal
region until initiation of transformation. Pigment at the
pelvic fin base appears to be a diagnostic character for
the small-scale menhadens because Houde and Swan-
son (1975) also reported a similar feature in yellowfin
menhaden as small as 12.3 mm. Although the presence
of this pigment at the pelvic fin base is proposed to
be diagnostic for the small-scale menhadens (present
study), Hettler's (1984) illustration of a 16.5-mm gulf
menhaden shows this pigment. Pigmentation descrip-
tions for developing gulf menhaden have not specifi-
cally addressed melanophores at the pelvic fin insertion
(Hettler, 1984). Finescale menhaden transform at a
smaller size (17-19 mm) than any of the other Gulf of
Mexico menhadens. Gulf menhaden did not complete
transformation until around 25 mm, which is in agree-
ment with the reported lengths of 25-28 mm for both
laboratory reared and wild-caught individuals ( Suttkus.
1956; Hettler. 1984). Yellowfin menhaden reach trans-
formation at an intermediate size (20-23 mm; Houde
and Swanson, 1975).
Even as adults, finescale menhaden very closely re-
semble gulf menhaden (Hoese and Moore. 1977) and few
reliable characters effectively separate them. Only the
absence of striations on the margin of the operculum, a
single humeral spot (with no hint of trailing spots along
the lateral margins I, and more scale rows (60-77 in fi-
nescale vs. 36-50 in gulf menhaden; Hoese and Moore,
1977; McEachran and Fechhelm, 1998) distinguish fin-
escale from gulf menhaden. All other meristics overlap
greatly; i.e., counts of dorsal-fin rays, anal-fin rays,
pectoral-fin rays, pelvic-fin rays, gill-raker counts, and
ventral scutes. Although externally similar, significant
differences in internal structure between finescale and
gulf menhaden have been documented. Finescale men-
haden have fewer branchiospinules and shorter inter-
mediate gill rakers than gulf menhaden and, as such,
filter mainly zooplankton from the water column; gulf
menhaden, in contrast, feed primarily on phvtoplankton
and detritus (Castillo-Rivera et al., 1996).
Based on length-frequency differences seen between
the two species (Fig. 1), the reported spawning season
for finescale menhaden along the middle Texas coast
could be extended to late May. We still do not know of
characters that would distinguish finescale menhaden
eggs, and yolksac. preflexion, and flexion larvae from
other species in the genus Brevoortia. In order to fully
describe the development of finescale menhaden, labo-
ratory spawning and rearing experiments are needed
to fully describe these early-life stages. Houde (1973)
presented relatively simple rearing techniques that al-
low descriptions of the developmental stages of larval
fish (from egg through transformation of larvae to the
juvenile stage). These methods have been used success-
fully for Atlantic, gulf, and yellowfin menhaden, and
presumably, finescale menhaden could be reared with
these same techniques if their eggs could be obtained.
The rearing of finescale menhaden would also allow the
effectiveness of the proposed pigment characters used
to separate finescale menhaden from gulf menhaden to
be tested.
Acknowledgments
This work was performed with funding from the Coastal
Bend Bays & Estuaries Program under contract 0203.
The Texas Parks and Wildlife Department, Coastal
Tolan and Newstead: Larval and |uvenile development of Brevoortia gunteri
731
Studies Program, Resource Protection Division provided
additional interagency cooperation in the form of equip-
ment and field logistical support. This manuscript was
improved by comments from two anonymous reviewers.
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733
Abstract-The stomach contents of the
minimal armhook squid iBerryteuthis
anonychus) were examined for 338
specimens captured in the northeast
Pacific during May 1999. The speci-
mens were collected at seven stations
between 145-165°W and 39-49°N and
ranged in mantle length from 10.3
to 102.2 mm. Their diet comprised
seven major prey groups (copepods,
chaetognaths, amphipods. euphausi-
ids, ostracods, unidentified fish, and
unidentified gelatinous prey) and was
dominated by copepods and chaeto-
gnaths. Copepod prey comprised four
genera, and 86% by number of the
copepods were from the genus Neo-
calanus. Neocalanus cristatus was the
most abundant prey taxa, composing
50% by mass and 35% by number of
the total diet. Parasagitta elegans
(Chaetognatha) occurred in more
stomachs (47%) than any other prey
taxon. Amphipods occurred in 19% of
the stomachs but composed only 5% by
number and 3% by mass of the total
prey consumed. The four remaining
prey groups (euphausiids, ostracods.
unidentified fish, and unidentified
gelatinous prey) together composed
<29c by mass and <1% by number of
the diet. There was no major change
in the diet through the size range
of squid examined and no evidence
of cannibalism or predation on other
cephalopod species.
Diet of the minimal armhook squid
(Berryteuthis anonychus)
(Cephalopoda: Gonatidae)
in the northeast Pacific during spring
Kazuhisa Uchikawa
National Research Institute ot Far Seas Fisheries
5-7-1 Shimizu-Ondo
Shizuoka, 424-8633, Japan
E-mail address stomyctS affrc go ip
John R. Bower
Northern Biosphere Field Science Center, Hakodate Branch
Hokkaido University
3-1-1 Minato-cho, Hakodate
Hokkaido 041-8611, Japan
Yasuko Sato
Department of Agriculture, Forestry and Fisheries, Nngata Prefecture
Agriculture Affairs Division
Shlnko-cho
Nngata 950-8570, Japan
Yasunori Sakurai
Graduate School of Fisheries Sciences
Hokkaido University
3-1-1 Minato-cho, Hakodate
Hokkaido 041-8611, Japan
Manuscript submitted 2 September 2003
to the Scientific Editor's Office.
Manuscript approved for publication
29 June 2004 by the Scientific Editor.
Fish. Bull. 102:733-739 12004).
The squid family Gonatidae plays
an important role in the ecosystems
of the North Pacific. In the Sea of
Okhotsk, the annual production of
gonatid squids is more than half that
offish production (Lapko, 1996), and
in the western and central Bering
Sea, gonatid production is thought to
exceed that of the dominant fish fami-
lies (Radchenko, 1992). In the sub-
arctic North Pacific, the gonatids are
an important link in the pelagic food
web iBrodeur et al., 1999). To better
understand the food web in the North
Pacific and the processes influencing
the production of gonatid squids in
this region, information is needed on
the feeding behavior of these squids.
The minimal armhook squid iBerry-
teuthis anonychus) (also known as the
"smallfin gonate squid" [Roper et al.,
1984]) is a small gonatid (maximum
mantle length = 150 mm) distributed
mainly in the northeast Pacific (Rop-
er et al.. 1984: Bower et al., 2002). It
is a major prey for fishes, squids, sea-
birds, and marine mammals (Ogi et
al., 1980; Pearcy et al., 1988; Pearcy,
1991; Kuramochi et al., 1993; Pearcy
et al., 1993; Ohizumi et al., 2003) but
is not targeted by any fishery. Despite
the importance of B. anonychus in the
food web of the subarctic North Pa-
cific, the only published reports on
its feeding behavior are two abstracts
in the Russian literature (Lapshina,
1988; Didenko, 1990). In this arti-
cle, we provide further information
on the feeding behavior of B. anony-
chus by describing the diet of a wide
size range of squid collected from the
northeast Pacific during late spring.
Methods
Berryteuthis anonychus was collected
during a United States National
734
Fishery Bulletin 102(4)
65°N
60°N
55°N
50°N
45 N
40° N
35°N
180 W
"I T
170°W 160:W 150'W 140 W 130"W 120 W
Figure 1
Sampling stations in the northeast Pacific where Berryteuthis
anonychus were collected during May 1999. Numbers indicate
station numbers.
Marine Fisheries Service (NMFS) survey of salmon in
the northeast Pacific (Carlson et al., 1999; Bower et al.,
2002). Samples were collected during 6-17 May 1999
at seven stations between 145-165°W and 39-49°N
(Fig. 1). At each station, a midwater trawl modified to
fish at the surface was towed for 1 hour. The trawl was
198 m long and had hexagonal mesh in its wings and
body, and a 1.2-cm mesh liner was used in the codend.
Trawling speeds were 7-9 km/h, and the average net
dimensions while fishing were 16 m vertical spread and
45 m horizontal spread.
Squid samples were frozen on board to -20°C and
preserved in 50% isopropyl alcohol in the laboratory.
The mantle length (ML) of each squid was measured
to the nearest 0.1 mm, and each squid was weighed to
the nearest 0.01 g. The stomach contents of 338 squid
(167 males, 144 females, 27 undetermined) ranging in
ML from 10.3 to 102.2 mm (Fig. 2) were examined un-
der a stereomicroscope. A total of 359 squid were col-
lected during the survey (Bower et al., 2002), but 21 of
these specimens were either damaged or lost, and thus
excluded from our analyses. Most prey items were frag-
mented; therefore prey identification was usually based
on diagnostic body parts as described in Brodsky (1950),
Miller (1988), Baker et al. (1990), and Vinogradov et al.
(1996). and by comparison with zooplankton specimens
collected in the same area. The prey items were counted
and weighed to the nearest 0.01 mg. These wet mass
measurements presumably underestimated the initial wet
masses because mass loss occurs in invertebrate samples
preserved in isopropyl alcohol (e.g., Howmiller, 1972),
and it was assumed all prey taxa were equally affected
by the preservation. The numbers of individuals of each
6CH
50-
40-
Z 30-
20-
10-|
0
n = 338
10 20 30 40 50 60 70 80 90 100
Mantle length (mm)
Figure 2
Length-frequency distribution for Berryteuthis
anonychus.
prey taxon were estimated from the numbers of prey
parts, such as copepod mandibles, amphipod heads and
chaetognath seizing hooks. Because of the difficulty in
distinguishing the copepods Neocalanus plumchrus and
N. flemingeri, they were grouped as a single taxon, N.
plumchrus+flemingeri. Some calanoid copepods that could
not be identified to genus level were identified as either
a "specialized form" or a "generalized form"; characters
of the specialized form included appendages that were
greatly enlarged or strongly developed with chelae, spines
on the posterior corners of the terminal thoracic segment,
Uchikawa et al.: Diet of Berryteuthis anonychus in the northeast Pacific during spring
735
Table 1
Numbers of Berryteuthis anonychus
stomachs with iden-
tifiable
prey remains.
without identifiable remains, and
without
remains from
the northeast Pacific. Station num-
bers refer to those shown in Figure 1
With
Without
Station
identifiable
identifiable
Without
no.
remains
remains
remains
Total
1
25
0
0
25
2
29
19
45
93
3
33
0
2
35
4
12
1
2
15
5
51
9
6
66
6
44
18
16
78
7
26
0
0
26
Total
220
47
71
338
and an asymmetrically swollen genital segment. The gen-
eralized form included calanoid copepods of the Calanus
type that did not share any of these characters.
A stomach-contents index (SCI, %) was calculated
as SCI=(wet mass of total stomach contents/wet body
mass)xl00. For each prey taxon, the percentages by
number (N) and wet mass (WM) of the total prey, and
the percentage frequency of occurrence (F) were de-
termined. An index of relative importance (IRI) was
calculated for each prey taxon as IRf = Ft x lNt+ WMt)
(Pinkas et al., 1971), where i denotes the taxon. The IRI
for each major group of prey taxa was then standard-
ized to '/dRI (Cortes. 1997):
n
%IRI, = 100 x IRI, I £ IRIt ,
where /; is the total number of groups collected.
Copepod mandible size is directly related to the cara-
pace length of several calanoid copepods in the North
Atlantic (Karlson and Bamstedt, 1994); therefore man-
dible width was used as an indicator of relative prey
size to compare copepod prey size with squid mantle
size. A total of 87 mandibles were measured from the
stomachs of 10 squid measuring 29-102 mm ML.
Results
Of the 338 stomachs examined, 267 (79%) contained
prey, and 220 (65% ) contained identifiable prey (Table 1).
Individual SCI values ranged from 0% to 8.0% (station
mean = 1.0%). SCI values varied significantly among
sampling times (Kruskal-Wallis test, P<0.001), and the
two highest SCI values occurred in the afternoon and
just after sunset (Fig. 3).
The diet of B. anonychus comprised seven major
prey groups and was dominated by copepods (A?=70%,
3.0-1 T
t h>
2.5-
{ 1
2.0-
o 15"
CO
1.0-
263
-15
0.5"
66
_87 78
1 1 1 1 1 1 1 1 1
6 8 10 12 14 16 18 20 22 24
Time of day (h)
T
Sunrise Sunset
Figure 3
Mean stomach contents index (SCI) of Berrvteuthis
anonychus collected in the northeast Pacific during
May 1999 at different times of day. SE = standard
error of the mean. Numbers indicate squid sample
size for each sampling.
WM=85%, F=74%, %IRI=87%) and chaetognaths
(N=24%, WM=11%, F=48%, <7dRI=129c) (Table 2). The
five other prey groups (amphipods, euphausiids, ostra-
cods, unidentified fish, and unidentified gelatinous prey)
each had a 9cIRI value <1%.
Copepod prey comprised four genera, and 86% by
number of the copepods were from the genus Neocala-
nus. Neocalanus cristatus was the most abundant prey
taxa. composing 50% by mass and 35% by number of
the total diet. The three Neocalanus taxa (Neocalanus
spp., N. plumchrus+flemingeri, and N. cristatus) com-
posed 85% by mass and 68% by number of the diet.
Neocalanus cristatus was identified based on the pres-
ence of the head crest, which develops at the C5 copepo-
dite stage (Brodsky, 1950). Thus, this taxon comprises
only the C5 and C6 stages, and possible members of
the Neocalanus spp. taxon include N. plumchrus, N.
flemingeri, and earlier stages (C1-C4) of N. cristatus.
Squid >60 mm ML fed mainly on Neocalanus crista-
tus (2V=39%, WM=53%, F=50%) and Neocalanus spp.
(iV=29%, WM= 31%. F=40%), whereas those <60 mm
ML fed mainly on Neocalanus spp. (AT=43%, WM=53%,
P=29%) and Neocalanus plumchrus+flemingeri (N=8%,
WM=10%, F=14%), and consumed few C5-C6 Neocala-
nus cristatus (N=4%, WM=4%, F=6%). The mandible
size of copepod prey showed a clear positive relationship
with ML (Fig. 4), indicating that the squid fed on larger
copepods as the squid grew. Taxa from other copepod
genera (i.e., Candacia, Metridia, and Pleuromamma)
composed 0.5% of the total prey number and 0.1% of
the total wet mass (Table 2).
Parasagitta elegans, the only identified chaetognath,
occurred in more stomachs (47%) than any other prey
taxon and in 58% of the stomachs from squid >60 mm
736
Fishery Bulletin 102(4)
Table 2
Prey items identified from stomach contents of Berry teu
this anonychus collected in the northeast Pacific during May 1999. %IRI:
standardized index of relative importance. %IRI values in parentheses are
those for <60
mm
ML and
>60 mm ML squid. Fre-
quency of occurrence was calculated from the number
of stomachs containing food. "-
means prey taxon was not present in
stomachs.
Number
Wet mass
Frequency of
%IRI
Taxon
(%)
(%)
occurrence
(%)
(<60 mm ML, >60 mm ML)
Copepoda
70.2
85.3
74.2
86.5(80.9,84.81
Candacia columbine
0.2
0.1
1.9
Candaeia sp.
<0.1
<0.1
0.4
Metridia paeifica
0.2
<0.1
2.2
Neoealanus cristatus
35.0
50.4
23.2
Neocalanus plumchrus+flemingeri
3.1
1.8
12.4
Neoealanus spp.
30.0
32.3
33.3
Pleuromamma spp.
0.1
<0.1
1.9
Calanoida (generalized form)
0.5
0.3
4.9
Calanoida (specialized form)
0.1
0.1
0.4
Unidentified Calanoida
0.9
0.3
14.2
Unidentified Copepoda
0.1
0.1
2.6
Chaetognatha
23.9
10.8
47.6
12.4(18.1, 13.9)
Parasagitta elegens
23.8
10.7
47.2
Unidentified Chaetognatha
0.1
0.1
1.1
Amphipoda
4.6
2.5
19.1
1.0(1.0. 1.3)
Hyperia medusarum
0.8
0.9
2.2
Themisto paeifica
2.5
0.9
7.5
Unidentified Hyperiidae
0.4
0.5
0.7
Unidentified Physocephalata
<0.1
<0.1
0.4
Unidentified Hyperiidea
0.7
0.2
7.5
Unidentified Amphipoda
0.1
<0.1
1.9
Euphausiacea
0.5
0.9
4.5
<0.1 (<0.1,0.1)
Euphausia paeifica
<0.1
0.4
0.5
Thysanoessa sp.
<0.1
<0.1
0.4
Unidentified Euphausiacea
0.5
0.5
3.7
Ostracoda
<0.1
<0.1
1.1
<0.1 (<0.1,— )
Unidentified fish
<0.1
0.8
0.4
<0.1 (— , <0.1)
Unidentified gelatinous prey
<0.1
<0.1
0.4
<0.1 (<0.1,— )
Unidentified Crustacea
0.1
<0.1
1.1
Unidentified material
0.6
0.1
18.7
Neocalanus plumchrus and N. flemingeri
were grouped as a si
ogle taxon tN. plumchrus+flemingeri) because of d i f ri c l
Ity in distinguishing these
species in partly digested materials.
Neocalanus cristatus comprises stages C5
and C6 only.
Neocalanus spp. = N. cristatus (stages Cl-
C4 ). N. plumchrus, and N. flemingeri.
Calanoida (specialized form! = unidentified individuals with markedly enlarged appendages. strongU
deve
loped chel
ae, a spine on the posterior
corner of the terminal thoracic segment, or asymmetrically swollen genital segments.
Calanoida (generalized form) = unidentifi
?d Calanus-type individuals that share none
of the characters of the special
zed form.
ML. P. elegans was the third most abundant prey taxon,
composing 24% by number and 11% by mass of the total
diet (Table 2).
Amphipods (mainly Themisto paeifica and Hyperia
medusarum) were consumed by 199r of the squid but
composed only 5% by number and 3% by wet mass of
the total prey consumed. The four other prey groups
combined composed <2re by mass and <1% by number
of the diet. There were no major changes in %IR1 val-
ues through the size range of squid examined (Table 1)
and no evidence of cannibalism or predation on other
cephalopod species.
Uchikawa et al.: Diet of Berryteuthis anonychus in the northeast Pacific during spring
737
0, KM > i — i~i — ■ i ■ — r-1 — i ■ i — ■ i ■ — r-1 — i
20 30 4(1 50 60 70 80 90 100 110
Mantle length (mm)
Figure 4
Relationship between mandible width of
copepod prey and mantle length of Ber-
ryteuthis anonychus.
Discussion
The diet of Berryteuthis anonychus collected in the north-
east Pacific during May was dominated by calanoid
copepods and chaetognaths. During early July in this
area, B. anonychus larger than those examined in the
present study (ML: 75-127 mm vs. 10-102 mm) fed on
a wider variety of prey, including primarily calanoid
copepods, hyperiid amphipods, pteropods, and euphau-
siids (Lapshina, 1988). Possible causes for this change
in diet include seasonal change in prey availability and
an ontogenetic change in the squid's ability to capture
prey.
The zooplankton composition in the upper 150 m of
the subarctic North Pacific is highly seasonal. Neocala-
nus copepods, the major prey of B. anonychus, dominate
the epipelagic zooplankton community during spring
and early summer (Mackas and Tsuda. 1999). They
then descend from the upper layer to spend the late
summer, autumn, and early winter at 400-2000 m, well
below the depth range of B. anonychus (0-200 m; Nesis,
1997). As a result of this ontogenetic descent, the upper
ocean zooplankton biomass decreases greatly, and the
community is then dominated by a different group of
species. This group includes euphausiids (Mackas and
Tsuda, 1999), which are consumed by more B. anony-
chus in July (28%; Lapshina, 1988) than in May (5%;
present study). Other prey that show a large increase
in frequency of occurrence between May and July are
amphipods (19% in May, 52% in July) and pteropods
(0% in May, 40% in July).
Oceanic squids such as B. anonychus generally feed
on small crustaceans as juveniles and then shift their
diet to larger fish and other cephalopods as they grow
(Rodhouse and Nigmatullin, 1996). We observed no such
ontogenetic shift within the size range examined, but
copepod prey size was found to increase with growth.
These data are consistent with those for other squids
in that prey size increases during development (Nixon,
1987; Hanlon and Messenger, 1996). Most gonatids
undergo ontogenetic vertical descent (Roper and Young,
1975; Nesis, 1997), and a clear shift in the diet can ac-
company this habitat shift (e.g., as seen in Berryteuthis
magister; Nesis, 1997). Nesis (1997), however, suggested
that B. anonychus does not undergo ontogenetic descent;
therefore no such habitat-change-related shift in diet
would be expected to occur in this species.
Highest feeding intensities were recorded in the after-
noon and just after sunset, which would indicate that
B. anonychus feeds both day and night. Such a feed-
ing scenario is supported by the high overlap in depth
distributions of B. anonychus (day: 50-200 m, night:
0-150 m; Nesis, 1997) and its main prey, Neocalanus
cristatus; during spring, N. cristatus occurs mainly at
50-150 m, and like the other Neocalanus species, shows
no evidence of diel vertical migration (Mackas et al.,
1993). Therefore B. anonychus and N. cristatus occupy
nearly the same depth range both day and night.
The chaetognath Parasagitta elegans was the third
most abundant prey taxon and was consumed by more
squid than any other taxon. Parasagitta elegans forms
an important fraction of the springtime macrozooplank-
ton community in the North Pacific (Brodeur and Ter-
azaki, 1999) and inhabits mainly the epipelagic layer
(0-200 m) (Kotori, 1976; Terazaki and Miller, 1986);
therefore predation on P. elegans could also occur both
day and night. Another gonatid squid. Gonatus mado-
kai, has also been found to prey on Parasagitta sp.
(Kubodera and Okutani, 1977).
There was no evidence of cannibalism, which com-
monly occurs in many gonatids, particularly Berryteu-
this magister and Gonatopsis borealis (Lapko, 1996;
Nesis, 1997). Cannibalism in squids appears to occur
less frequently when prey are abundant (Shchetinnikov,
1992; Santos and Haimovici, 1997), as is the case in
the North Pacific during spring. In addition, at nearly
every station sampled, squid of a small size range were
collected (Bower et al., 2002); therefore it seems that op-
portunities for intercohort cannibalism were limited.
The large stock size of B. anonychus in the North
Pacific (Nesis, 1997) and its importance in the diet of
higher predators may indicate that the food chain from
copepods through squids and these higher predators is
an important trophic pathway in the pelagic food web of
the Subarctic Pacific during spring. The large seasonal-
ity in zooplankton composition in the upper 150 m may
indicate that these trophic pathways will show similar
seasonal variations.
Acknowledgments
We thank the late H. Richard Carlson for providing
us with squids collected during the May 1999 NMFS
salmon survey aboard the FV Great Pacific. We also
thank Chingis Nigmatullin and the late Kir Nesis for
translating two Russian abstracts into English, H. Sugi-
738
Fishery Bulletin 102(4)
saki and M. Terazaki for helping identify prey, K. Ichige
for helping in the laboratory, and the three anonymous
reviewers of the manuscript.
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740
Abstract— The relative abundance
of Bristol Bay red king crab (Para-
lithodes camtschaticus) is estimated
each year for stock assessment by
using catch-per-swept-area data col-
lected on the Alaska Fisheries Sci-
ence Center's annual eastern Bering
Sea bottom trawl survey. To estimate
survey trawl capture efficiency for red
king crab, an experiment was con-
ducted with an auxiliary net (fitted
with its own heavy chain-link foot-
rope I that was attached beneath the
trawl to capture crabs escaping under
the survey trawl footrope. Capture
probability was then estimated by
fitting a model to the proportion of
crabs captured and crab size data.
For males, mean capture probability
was 727 at 95 mm (carapace length),
the size at which full vulnerability to
the survey trawl is assigned in the
current management model: 84. 1^ at
135 mm, the legal size for the fish-
ery; and 939c at 184 mm, the maxi-
mum size observed in this study. For
females, mean capture probability was
707c at 90 mm, the size at which full
vulnerability to the survey trawl is
assigned in the current manage-
ment model, and 777 at 162 mm,
the maximum size observed in this
study. The precision of our estimates
for each sex decreased for juveniles
under 60 mm and for the largest
crab because of small sample sizes.
In situ data collected from trawl-
mounted video cameras were used to
determine the importance of various
factors associated with the capture of
individual crabs. Capture probabil-
ity was significantly higher when a
crab was standing when struck by the
footrope, rather than crouching, and
higher when a crab was hit along its
body axis, rather than from the side.
Capture probability also increased as
a function of increasing crab size but
decreased with increasing footrope
distance from the bottom and when
artificial light was provided for the
video camera.
Capture probability of a survey trawl for
red king crab (Paralithodes camtschaticus)
Kenneth L. Weinberg
Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
7600 Sand Point Way N.E
Seattle, Washington 98115
E-mail address ken Weinberg gnoaa gov
Robert S. Otto
Kodiak Fisheries Research Center
National Marine Fisheries Service, NOAA
301 Research Court
Kodiak, Alaska 99615
David A. Somerton
Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
7600 Sand Point Way N.E.
Seattle, Washington 98115
Manuscript submitted 5 September 2003
to the Scientific Editor's Office.
Manuscript approved for publication
28 April 2004 by the Scientific Editor.
Fish. Bull. 102:740-749(2004)
Regulations limit the annual har-
vest of Bristol Bay red king crab
(RKC; Paralithodes camtschaticus) to
males >135 mm in carapace length1
(6.5 inches carapace width), and the
size of the harvest is dependent upon
the estimated biomasses of mature
males and females. For stock assess-
ments of RKC, area-swept abundance
estimates are determined from the
data from annual eastern Bering Sea
(EBS) bottom trawl surveys conducted
by the National Marine Fisheries Ser-
vice, Alaska Fisheries Science Center
(AFSC), and these estimates are used
as input into a length-based assess-
ment model (Zheng et al., 1995) to
compute the total allowable catch for
each annual fishing season.
It is assumed with the current as-
sessment model that all male RKC
>95 mm and all female RKC >90 mm
within the path of the survey trawl
(wingtip to wingtip) are captured.
This assumption seems reasonable
because the survey trawl uses a small
diameter footrope designed to stay
close to the bottom and red king crab
are quite large. However, video pho-
tography taken following the 2000
EBS survey revealed that a consider-
able number of large (>90 rami RKC
pass under the footrope of the survey
trawl.
To assess the potential impact of
escaping crab on the calculation of
crab biomass, we conducted an ex-
periment to estimate the size-related
capture efficiency of the standard
survey bottom trawl for Bristol Bay
RKC. In this experiment, crab pass-
ing beneath the survey trawl were
subsequently captured with an aux-
iliary net that was attached under-
neath and behind the footrope of
the survey trawl (Engas and Godo,
1989; Walsh, 1992). Experimental
nets like the one used for this study
have been used previously in trawl
efficiency studies for flatfish (Munro
and Somerton, 2002), as well as for
snow iChionoecetes opilio) and Tan-
ner (C. bairdi) crabs (Somerton and
Otto, 1999). Trawl catch data alone,
however, tell little about the details
involved with escapement. Therefore,
we deployed a video camera on the
trawl to observe crab behavior and
analyzed a combination of trawl-per-
1 All references to measured crab lengths
are carapace length.
Weinberg et al.: Capture probablity of a survey trawl for Parahthodes camtschaticus
741
trawl codend
auxiliary codend
trawl footrope
wrapped wire
chain hangings
twine hangings
fishing line
auxiliary footrope
Figure 1
The 83/112 Eastern bottom trawl with auxiliary net used in the 2002
red king crab capture efficiency experiment (figure adapted from Munro
and Somerton, 2002, with permission from Elsevierl.
formance and crab-behavioral variables to help us un-
derstand the escapement process.
Materials and methods
Description of trawl gear
The 83/112 Eastern bottom trawl has been used by the
AFSC in annual surveys to assess EBS crab and shelf
groundfish stocks since 1982 (Armistead and Nichol,
1993). For the present experiment, an auxiliary net with
an independent footrope constructed of heavy chain-link
and a separate codend were attached to the bottom of
the survey trawl to capture epibenthic animals passing
beneath the trawl footrope (Fig. 1). Briefly, the 83/112
Eastern is a low-rise trawl that has a 25.3-m long hea-
drope strung with 48 floats giving it approximately 102
kg of lift and a 34.1 m long, 5.2-cm diameter footrope
constructed of 1.6-cm stranded wire rope protected with
a single wrap of polypropylene line and split rubber hose.
The net is constructed with nylon twine: 10.1-cm stretch
mesh throughout the wing and throat sections; 8.9-cm
stretch mesh in the intermediate section; a double layer
of 8.9-cm stretch mesh in the codend; and a 3.1-cm
stretch mesh liner in the codend. It is fished with a pair
of 1.8x2.7-m steel V-doors weighing approximately 816
kg apiece.
The auxiliary net attaches to the wingtips and to the
bottom of the survey trawl so that the bottom panel of
the trawl serves as the top panel of the auxiliary net
up to the beginning of the intermediate section. At this
point, the two nets part and the auxiliary net then has
a top panel of 8.9-cm stretch mesh and a double layer
742
Fishery Bulletin 102(4)
61 "N-
60 N-
59 N-
58 N-
57°N-
56N-
55N-
54N-
166 W
164 = W
162 W
160 W
158 W
Figure 2
The annual eastern Bering Sea survey station grid showing the
number of successful tows per station block made during the 2002
red king crab capture efficiency study. Each block represents a
400-nmi2 area.
codend with a 3.1-cm stretch mesh liner. The 38.2 m long
auxiliary footrope constructed of heavy 16-mm-long link
trawl chain was designed to drag through soft bottom
and presumably captures all escaping crabs. Munro and
Somerton (2002) provided detailed construction plans of
this experimental gear in their appendices.
Experimental design
Operations were conducted from 21 to 29 July 2002,
aboard the FV Arcturus, one of two commercial stern
trawlers chartered by the AFSC since 1993 to carry
out annual Bering Sea groundfish surveys. Trawling
took place in Bristol Bay (Fig. 2) at depths from 41 to
77 m and followed standardized survey protocols that
included towing during daylight hours at a 1.5 m/sec (3
knots) vessel speed and using locked winches and stan-
dardized lengths of trawl warp (scope) at each towing
depth. Acoustic net mensuration equipment was used
to measure wing spread for each tow. Bottom contact
sensors were used on the centers of both the trawl and
auxiliary footropes to measure the distance (in centime-
ters) between the footropes and the bottom (Somerton
and Weinberg. 2001). A silicon-intensified tube (SIT)
camera, which uses ambient light, was attached to the
center of the trawl to view RKC interaction with the
footrope. On some of our trial tows, however, a 30-W
quartz halogen light was also used to increase contrast
between ambient light and the sea floor.
Two departures from standardized survey protocol
were necessary for this experiment. First. 27.5-m long
bridles were used instead of the survey standard 55-
m long bridles to help offset the loss of wing spread
caused by the added drag of the auxiliary net (Munro
and Somerton, 2002). Second, tow length was shortened
from the survey standard of 30 min to 20 min to mini-
mize the decrease of path width over time due to in-
creased drag from large catches in the auxiliary net.
Weinberg et al.: Capture probablity of a survey trawl for Paralithodes camtschaticus
743
Towing sites were selected according to catch rates
and carapace lengths obtained from the recently com-
pleted 2002 EBS survey (Stevens2). Tows were made in
pairs, one in a northerly direction, the other in a south-
erly direction and were offset to the east or west by a
minimum of 0.1 nmi; the initial direction was chosen
randomly in order to mitigate any bias that the current
flow might have on footrope contact with the bottom
(Weinberg, 2003). Increased effort was given to sites
producing favorable numbers and crab lengths by add-
ing additional towing pairs. For each tow the total catch
of all species from each net was first weighed before all
RKC were removed from the catch, weighed, coded by
sex, and measured to the nearest millimeter.
Data analysis
Trawl geometry Trawl geometry for standard survey
nets and experimental nets was measured to confirm
that the two gear types fished similarly. Average wing
spreads and footrope heights off-bottom for experimental
tows were compared to those from 33 standard survey
gear tows taken at the same or nearby sampling loca-
tions. Because the depth of sampling varied, wing spread
and footrope height were linearly regressed on scope,
a factor variable indicating gear type (i.e., survey or
experimental), and their interaction. Two-tailed r-tests
were used to test for the difference in the slopes and the
intercepts between gear types. Significance of the inter-
action term indicated that slopes differed between gear
types. For nonsignificant interaction, significance of the
intercepts indicated that wing spread or footrope height
differed between gear types by a constant amount.
Capture probability Capture probability for the experi-
mental gear was estimated from catch data of the trawl
and the auxiliary net as a function of carapace length
(L) for both male and female crab. Based on the assump-
tion that the auxiliary net allows no escapement, the
probability of capture at the footrope was modeled as a
logistic function (Munro and Somerton, 2002) by using
SPLUS software (version 6.1, Insightful Corporation,
Seattle, WA). Two models were considered: the first,
a two-parameter model which reaches an asymptotic
maximum of 1 (unity):
PlLh
l+e-<a+pLr
(1)
and the second, a three-parameter model which reaches
an asymptotic maximum less than 1:
PiD-
1 + e
-la+/3L)
(2)
2 Stevens, B. G., R. A. Macintosh, J. A. Haaga, C. E. Armistead,
and R. S. Otto. 2002. Report to industry on the 2002
eastern Bering Sea crab survey. AFSC Proc. Rep. 2002-5,
59 p. Alaska Fish. Sci. Cent., Natl. Mar. Fish. Serv., NOAA,
Kodiak Fishery Research Center, 301 Research Court, Kodiak
AK 99615.
Because crab capture at the footrope is a binomial pro-
cess (i.e., crabs are either captured or they escape), the
models were fitted to the capture and length data by
using maximum likelihood (Millar, 1992; Munro and
Somerton, 2001) and the data were pooled across tows.
For each sex, both models were fitted to the data, and the
best of the competing models was selected according to
the lowest obtained value of the Akaike information cri-
terion (AIC; Burnham and Anderson, 1998), defined as
AIC = -2(log likelihood ) + 2( number of parameters).
After choosing a model for each sex, we examined whether
the capture probability curves differed between sexes by
fitting a model to the data for both sexes combined, and
then comparing the value of AIC for this model to the
sum of the AIC values for the models fitted to each sex,
again using the minimum AIC value to objectively select
the better of the two models.
Bootstrapped confidence intervals were constructed for
the mean capture probability for each 1-mm length cat-
egory, between the smallest and the largest individuals
(Efron and Tibshirani, 1993) by resampling the catch-
at-size data from individual hauls 1000 times. Empirical
95% confidence intervals were then determined as the
range between the 25th highest and the 25th lowest of
the bootstrap capture probability estimates.
Video data analyses
To understand the factors associated with crab escape-
ment under the footrope, a video camera was mounted
on the trawl to observe RKC interaction with the center
of the trawl footrope. These in situ video observations
included tows made in 2000 on the standard trawl and in
2002 on the experimental trawl. Artificial light was pro-
vided for all of the 2000 tows, and for some of the 2002
trial tows made before the capture efficiency experiment
began. All the 2002 experimental tows were made under
natural light conditions. RKC encounters observed on
the videotapes were counted from the time the footrope
settled to the bottom until the time the footrope was
lifted off-bottom at the end of the tow. The probability of
capture was predicted as a function of several explana-
tory variables. Variables observed and codes (in paren-
theses) for each individual included the following:
1 the capture event — the crab escaped beneath the
footrope (0) or was captured (1);
2 use of artificial light — the tow was made with (0)
or without artificial light (1);
3 estimated mean footrope height above the sea floor
over the course of the entire tow was based on the
bottom contact sensor and was expressed in centi-
meters (0-5);
4 body height — the crab was observed to be crouching
with its legs either tucked beneath the carapace or
stretched out so that the carapace was very close
to the bottom (0) or standing upright on its dactyls
(1);
744
Fishery Bulletin 102(4)
Table 1
Regression coefficients of wing spread (widthl and footrope distance from the bottom (footropel as a function of scope and gear
type based on tows from the capture efficiency experiment and tows using standard survey gear. Also provided are the results of
two-tailed Mests testing for the difference in intercept between gear types.
Slope
Intercept
Experimental gear (n = 43)
Standard gear (n = 33l
P intercept
Width (ml
Footrope (cm)
0.0038
0.0087
15.3206
-1.2582
16.0713
-0.4241
<0.0000
0.0023
5 body orientation at the point of contact with the
footrope — footrope contact occurred along the body
axis (1) or from the side (2);
6 crab size — small (0), medium (1), or large (2), where
size is expressed as an approximation based on
visual comparison of carapace length to the dimen-
sions of trawl parts, such as mesh or chain links.
Corresponding length intervals were approximately
<90 mm, 90-135 mm, and >135 mm.
As a general rule, crabs could be seen in the videos 1-2
seconds prior to contact with the footrope. Assignment
of codes was typically straightforward. However, in some
instances, several reviews of the encounter were neces-
sary in order to determine a crab's position or orientation
in relation to the footrope.
The probability of capture was estimated by using
stepwise generalized linear modeling (GLM; Venables
and Ripley, 1994) to fit a logistic model describing the
probability of capture as a function of crab size, where
body height, body orientation, average footrope distance
from the bottom during the tow, the use of artificial
light, and all possible first order interactions were con-
sidered as additional potential terms. The model fitting
procedure (with data from crabs for which all variables
were observed) entailed a stepwise backward model se-
lection process. The process began with fitting the model
to all interaction terms less one, and then calculating
and comparing the resulting AIC values. The interaction
producing the largest decrease in AIC was subsequently
eliminated. Next, the procedure was repeated with the
remaining terms until no interaction term could be
eliminated without increasing the AIC. Then, the above
process was repeated for the main effects. For the main
effects having an interaction term, both the main effects
and the interaction term were eliminated together as a
unit. The final model chosen contained those terms that
produced the minimum AIC value.
Results
Effect of the auxiliary net on trawl geometry
Regressions of wing spread and footrope height on
scope, gear type, and their interaction were compared
to determine how closely the two gear types fished. The
interaction term was not significant for wing spread
(P=0.08) nor for footrope height (P=0.82), indicating that
the slopes did not differ between gear types. However.
tests of the intercepts were significant for both wing
spread and footrope height and indicated that trawl
geometry differed between survey and experimental
trawls (Table 1). Predicted standard survey wing spreads
for the minimum (137 m), median (229 m), and maxi-
mum (320 m) scopes used were 16.6, 16.9. and 17.3 m
— approximately 0.8 m more than the experimental
gear at the same scopes. Predicted footrope distances
off the bottom were 0.8, 1.6, and 2.4 cm, at the above
three scope values — approximately 0.8 cm greater than
the experimental gear. Although we detected statistical
differences in the trawl geometry between the two gear
types, the actual difference in physical measurements
was small and presumably had only a nominal effect on
the results of the capture efficiency experiment.
Our assumption that the auxiliary net caught all
escaping crabs was reinforced by two observations: 1)
the data from the bottom contact sensor on the chain
footrope indicated consistent contact with the sea floor;
and 2) the auxiliary net consistently had large catches
of benthic organisms other than crab, such as starfish
and shells, and produced enough drag on the system to
reduce wing spread. The effectiveness of the auxiliary
footrope at capturing escaping crab is in part due to
its weight and small diameter that enable it to sweep
beneath the crabs and in part due to the suspension of
benthic organisms initiated by the turbulence created
by the passing of the first footrope.
Length-based capture probability
Capture probability was estimated from length mea-
surements (n=3233) collected from 43 successful
experimental tows (21 north, 22 south) made within
11 standard EBS survey station blocks (Fig. 2). Male
samples (n = 1667) ranged in size from 23 to 184 mm
(Fig. 3). Female samples (/? = 1566) ranged in size from
51 to 162 mm.
The two-parameter model (model 1) of capture prob-
ability was selected over the three-parameter model
(model 2) because it had a lower AIC value for both
male and female RKC (Table 2). For the comparison of
Weinberg et al.: Capture probabhty of a survey trawl for Paralithodes camtschaticus
745
100 i
Males
80 ■
P Captures
1
n
n
60 ■
■ Escapes
'
n
40-
20 -
1 1
, 1
1
1
_nJl
1
ll
1
1
1
l
1
1
1
■ L n n.
20
30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180
0)
0)
LL
150
n
125
Females
□ Captures
100 ■
75-
■ Escapes
n
50-
1
25 -
— ill
1
1,
1
1
J
1 1 . ~.
20
30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180
Carapace length (5 mm bins)
Figure 3
Size frequency of red king crabs taken in the survey trawl (captures! and the
auxiliary
let (escapes) during the 2002 capture efficiency study. Crab have
been binned into 5-mm carapace length intervals.
Table 2
Estimated parameter and Akaike's
and the 3-parameter logistic models
strapping 1000 replicates are provi
Eastern survey bottom trawl.
information criterion (AIC) values for the maximum
for males, females, and for sexes combined. Parameter
ied for the final model used to estimate red king crab
likelihood fit of the 2-parameter
variance estimates based on boot-
:apture probability for the 83/112
Sex
Model
a
P
7
AIC
Var a
Var/3
Covariance a/3
Male
1/(1 +e-(a + W)
-0.7366
0.0178
—
1725.3
0.113
1.28xl0-5
-1.14xl0-3
//(l +e-(a + ft')
-0.8826
0.0209
0.9622
1727.1
—
—
—
Female
l/(l + e-(a + »)
0.3540
0.0054
—
1875.7
0.279
2.58xl0-5
-2.63xl0-3
y/(l +e-lo + b])
0.3540
0.0054
0.9999
1877.7
—
—
—
Combined sexes
1/(1 +e-(« + W)
-0.4569
0.0143
—
3612.7
—
—
—
selectivity curves for males and females with model 1,
we found the summed AIC for separate curves to be
lower than the AIC for sexes combined. Consequently,
separate selectivity curves were estimated for males
and females (Table 2).
The fitted model predicted male capture probabil-
ity to be 41.9% at 23 mm (size of the smallest male
observed); 72.2% at 95 mm (size at which full vulner-
ability to the survey trawl is assigned in the current
management model); 80.2% at 120 mm (size assigned
746
Fishery Bulletin 102(4)
in the current management model for male maturity);
84.1% at 135 mm (legal size for males); and 92.7% at
184 mm (size of the largest male crab encountered in
1.0-
o
Males
o
0.8-
° ■■c^o
0.6-
o
0.4-
0.2-
O
50 100 150
Carapace length (mm)
Figure 4
A 2-parameter logistic model (solid line) and 959S confi-
dence bounds idashed lines) estimating male red king crab
capture probability for the 83/112 Eastern survey bottom
trawl. Symbols are scaled to the sample length frequency
summed over all tows and binned into 5-mm carapace length
intervals. Symbols range in size from the smallest circle
representing a single individual to the largest circle repre-
senting 138 males.
1 0n
0.8-
o
o. 0.6
0
0.4
0.2
o
-~9
Females
0^
o
■ 06
o
o
0
0
50 100 150
Carapace length (mm)
Figure 5
A 2-parameter logistic model isolid line) and 959! confi-
dence bounds idashed linesl estimating female red king crab
capture probability for the 83/112 Eastern survey bottom
trawl. Symbols are scaled to the sample length frequency
summed over all tows and binned into 5-mm carapace length
intervals. Symbols range in size from the smallest circle
representing two individuals to the largest circle represent-
ing 206 females.
our experiment [Fig. 4]). The fitted model predicted
female capture probability to be 65.27c at 51 mm (size
of the smallest female observed); 69.8% at 90 mm (size
at which both full vulnerability to the survey trawl
and 50% female maturity are assigned in the cur-
rent management model); 74.7% at 135 mm (same
size at which males enter the fishery); and 77.4%
at 162 mm (size of the largest female crab encoun-
tered in our experiment [Fig. 5]). Estimated capture
probability for both male and female crab was equal
at 88 mm (69.9%). Model variability, as indicated
by the 95% confidence bounds, was greatest at the
extremes of our size ranges because of low sample
frequency. This was especially true for small crabs,
and the uncertainty was so large that extrapolation
of the capture probability functions to either males
or females below <60 mm is not recommended.
Factors influencing escapement
Modeling the effect of various factors on capture
probability was based on observations of RKC
(ra=248) from videotapes collected during 28 EBS
tows. Approximately two-thirds of the counted crabs
were captured. The influence of artificial lighting,
body height, footrope distance from the bottom,
crab size, body orientation, and the interaction of
body height and body orientation were significant
(Table 3). Capture probability decreased when lights
were used and when the distance between the foot-
rope and the bottom increased. Capture probability
increased when crabs were standing up on their
legs, with increased body size, and when the footrope
contact was made along the body axis rather than
from the side of the crab.
Capture probability, based on direct observation,
was predicted by the fitted logistic models to illus-
trate how the various explanatory variables affect
the capture outcome. We present two examples. In
the first case, capture probability in natural light
Table 3
Model coefficients for predicting red king crab cap-
ture probability from counts obtained with a trawl-
mounted video camera.
Standard
Value
error
Intercept
-2.014
0.676
Light variable
-0.959
0.526
Body height variable
3.789
0.624
Body orientation variable
0.207
0.613
Crab size variable
1.506
0.315
Footrope height variable
-0.286
0.197
Body height and orientation
-1.436
0.785
interaction
Weinberg et al.: Capture probablity of a survey trawl for Paralnhodes camtschat/cus
747
conditions and when crab are oriented sideways
to the oncoming footrope, was predicted as a func-
tion of footrope distance off the bottom for each
size class, and for both standing and crouching
crab (Fig. 6). For all size groups, capture prob-
ability decreased with increasing footrope height
from the bottom. The importance of whether a
crab was standing or crouching diminishes with
decreasing crab size because the footrope is more
likely to pass completely over smaller crab. In
contrast, the importance of standing was higher
for large crab because they were more likely to be
undercut by the footrope and captured, whereas
crouching crab were more susceptible to hav-
ing their legs first pinned down by the footrope,
which exerted a downward pressure on their
carapace and allowed the footrope to pass over
the crab. Capture probability of medium-size in-
dividuals, which included a large proportion of
egg-bearing females, was more dependent upon
the body height of the crab. Footrope contact be-
low the carapace typically resulted in capture;
however contact above the legs often forced the
crab's carapace down, causing the crab to roll
forward and pass beneath the footrope.
In the second case, capture probability was
predicted for natural light conditions when the
footrope is 1 cm off-bottom, as a function of crab
size, by body orientation to the footrope, and
for standing and crouching individuals (Fig. 7).
Under these conditions, capture probability was
greater for crab contacted along their body ax-
is than for crab hit from the side. In addition,
capture probability increased with crab size for
both standing and crouching crab, regardless
of whether the footrope first contacted the crab
along their body axis or from the side. When the
footrope was 1 cm off bottom, the difference in
the body-orientation effect on capture probability
for standing crab was greater for smaller crab
than for medium and larger individuals, but rela-
tively equal for crouching crab of all sizes.
1 0-
Standing
08-
^~~~ . _^^
06-
Medium ~~~ — -- ________^^
04-
*■"-— _
0.2-
^r— _____^^
5 00-
O
Q-
i i i i i
12 3 4 5
CD
3
CO
O
Crouching
0.8-
Large""" — ______^
0.6-
^^— -^__^
0.4-
___^ ^
Medium""^" — .
02-
~~~~- — _
0.0-
Small
■ i i i i
12 3 4 5
Footrope height (cm)
Figure 6
Estimated red king crab capture probability (based on direct
observations! by size class as a function of footrope height above
the bottom for standing and crouching individuals. For this
model, it was assumed that no artificial light was used for the
camera and that crab were oriented sideways to the footrope
upon initial contact.
Discussion
Our observations confirmed that adult Bristol Bay red
king crab can escape beneath the footrope of the AFSC's
83/112 Eastern survey bottom trawl under normal
towing conditions. Capture probability increased with
size but did not reach 100% for the largest crab caught.
For the current management model used for RKC stock
assessments, 100% capture probability is assumed for
adult crabs and should be revised. A recruitment ogive
is used in the calculation of the total spawning bio-
mass for defining overfishing under the Magnuson-
Stevens Fishery Conservation and Management Act
(Stevens2). Revised computations of vulnerability will be
required for this purpose as well. Survey trawl selectiv-
ity, although similar between the two sexes at prerecruit
sizes, was generally 15% higher for legal-size males
than for equal-size females. This between-sex difference
in capture probability may be explained by behavioral
differences (for instance, egg-bearing females stand dif-
ferently from large males). Unfortunately, crab, when
viewed from above, mask their gender; thus sex was
excluded from our modeling exercise of video data.
Survey catch statistics for RKC are routinely included
in the management modeling procedure to estimate the
abundance of legal-size males (>135 mm), male prere-
cruits (95-134 mm), the effective spawning biomass of
males (>120 mm), and the spawning biomass of females
(>90 mm, as determined from size at 50% maturity). We
estimated capture probability for legal-size males (up
to 184 mm) to range from 84% to 93%, for prerecruit
males from 73% to 84%, and for the mature portion
of the male spawning population (up to 184 mm) from
748
Fishery Bulletin 102(4)
80% to 93% Our estimated capture probability for the
survey trawl on the female portion of the spawning
RKC population ranged from 70% to 77% for crab up
to 162 mm. A review of the AFSC database for EBS
crab surveys showed that the largest male and female
crabs taken were 200 mm and 172 mm. Corresponding
capture probabilities estimated by the model for these
size crabs were 94% and 78%, respectively.
Two main factors affect the overall capture efficiency
of epibenthic species by a bottom trawl: 1) horizontal
herding, defined as movement into the path of the trawl
between the wingtips in response to stimuli produced by
the doors or bridles; and 2) escapement, defined as the
avoidance of capture once the crab is within the path of
the trawl. We believe herding is negligible because our
observations of crab movement, which were consistent
with those reported by Rose (1999), indicated that RKCs
are slow-moving animals that can travel only slight dis-
tances before being overtaken by a trawl approaching
1.0-
Standing ______
0.8-
^ ^^^^
0.6-
j^^^^^
04-
0.2-
Capture probability
o o
■ i i
small medium large
Crouching
0.8-
0.6-
/^^
0.4-
^^^^
0.2-
^ ad"**
0.0-
I" 1 1
small medium large
Crab size
Figure 7
Estimated red king crab capture probability (based on direct
observations) by body orientation at the time of footrope contact
as a function of crab size for standing and crouching individuals.
For this model, it was assumed that, no artificial light was used
for the camera and that the footrope was 1 cm off bottom.
at 1.5 m/sec. Our video observations of the trawl bridle
revealed that RKCs consistently passed over the top of
the bare cable, with one exception — where a few crabs
were seen sliding along the bridle, legs entangled, to the
wingtip before being cast outside the path of the trawl.
Escapement is likely restricted to footrope escapement
because mesh escapement is impeded by the spiny sur-
face and long legs of the crab and could only occur for
the smallest individuals, which we encountered in low
numbers and which could not be predicted reliably by
our model.
We recognize from the analysis of our in situ data
that capture probability is influenced not only by trawl
performance but also by crab behavior. For instance,
crabs standing upright, such as moving or migrating
individuals, are more susceptible to capture than those
with their bodies resting on the substrate. Crab density
could also affect capture probability as seen for some
species offish (Godo et al., 1999). The crabs we observed
with our video cameras were fairly dispersed and
the maximum number of crabs seen in any single
video frame was two (twice observed). Crabs in
relatively low abundance are likely to react di-
rectly to the gear, but in areas of high abun-
dance, crabs may react to each other in response
to the stimuli from the approaching gear, causing
them to crouch or conversely move away from
perceived danger. Both of these responses would
result in a different capture probability.
Our estimates of capture probability apply
to the conditions in which the EBS survey is
conducted; that is, relatively disperse offshore
populations encountered during daylight hours on
sandy bottom during the summer months. There
are other behavioral factors or environmental
conditions that we did not consider in the present
study but which could affect the efficiency of the
survey trawl. These include, but are not limited
to, the following: trawling where the substrate is
substantially different; crabs that are either ag-
gregated into pods or are buried (Dew3); and tem-
peratures or tidal currents that would affect the
migratory or feeding behavior, and therefore the
body height of crab (Dew, 1990). Our estimates
of capture probability are also based on the as-
sumption that the auxiliary net is 100% efficient
at capturing crab escaping beneath the footrope
of the survey trawl. We have no direct evidence to
believe otherwise. However, if crabs also escaped
the auxiliary net, then our estimates of capture
probability would be too large.
In conclusion, we wish to clarify to users of
our findings that, although these experimen-
tally determined selectivity models indicate an
upward correction in spawning biomass of red
king crab may be in order, we find no reason
3 Dew. C. B. 2003. Personal commun. Alaska
Fisheries Science Center, 7600 Sand Point Wav NE,
Seattle, WA 98115.
Weinberg et al.: Capture probablity of a survey trawl for Para/ithodes camtschaticus
749
to claim that the stock is in any better condition than
the condition that was determined by the most recent
assessment. The foremost utility of the AFSC annual
EBS surveys is to monitor distribution and abundance
trends through time. The survey accomplishes this by
maintaining strict protocols and consistency in trawling
methods, in computation of area-swept abundance, and
in nonenvironmentally affected trawl efficiency. The
survey times series is designed to detect changes in
abundance, signaling advances in the population's re-
building processes, regardless of whether crab are 100%
or 80% vulnerable to the survey trawl. We advocate that
careful consideration be given to the other factors that
drive the management model, along with the results of
our capture efficiency experiment, to ensure that the
stock rebuilding process remains uninterrupted.
Acknowledgments
We are thankful to Captain Glenn Sullivan and the crew
of the FV Arcturus for their professional attitudes and
relentless attention to detail; to scientists Chris John-
ston, Frank Shaw, and Kerim Aydin for their assistance
at sea following the 2002 survey; to Craig Rose and Scott
McEntire for technical support; to Dave King and Jim
Smart for preparation of the experimental trawl gear;
and to Gary Walters, Braxton Dew, Doug Pengilly, Jie
Zheng, and our anonymous reviewers for their helpful
comments during the manuscript review process.
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Burnham, K. P.. and D. R. Anderson.
1998. Model selection and inference: a practical infor-
mation-theoretic approach, .353 p. Springer-Verlag,
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Dew, C, B.
1990. Behavioral ecology of podding red king crab,
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Efron, B., and R. Tibshirani.
1993. An introduction to the bootstrap, 436 p. Chapman
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Engas, A., and O. R. Godo.
1989. Escape offish under the fishing line of a Norwegian
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God0, O. R.. S. J. Walsh, and A. Engas.
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750
Evidence of shark predation and scavenging on
fishes equipped with pop-up satellite archival tags
David W. Kerstetter
School of Marine Science
Virginia Institute of Marine Science
College of William and Mary
Gloucester Point, Virginia 23062
E-mail address: bailey@vims.edu
Jeffery J. Polovina
Pacific Islands Fisheries Science Center
National Marine Fisheries Service
Honolulu, Hawaii 96822
John E. Graves
School of Marine Science
Virginia Institute of Marine Science
College of William and Mary
Gloucester Point, Virginia 23062
Over the past few years, pop-up sat-
ellite archival tags (PSATs) have
been used to investigate the behav-
ior, movements, thermal biology,
and postrelease mortality of a wide
range of large, highly migratory spe-
cies including bluefin tuna (Block et
al., 2001), swordfish (Sedberry and
Loefer, 2001), blue marlin (Graves et
al., 2002), striped marlin (Domeier
and Dewar, 2003), and white sharks
(Boustany et al., 2002). PSAT tag
technology has improved rapidly,
and current tag models are capable
of collecting, processing, and stor-
ing large amounts of information on
light level, temperature, and pressure
(depth) for a predetermined length of
time before the release of these tags
from animals. After release, the tags
float to the surface, and transmit the
stored data to passing satellites of the
Argos system.
A problem noted by several au-
thors using early PSAT models was
the occasional occurrence of tags
that did not transmit data. Clearly,
a tag attached to a moribund fish
that would sink to a depth exceeding
the pressure limit of the tag casing
would be destroyed. To prevent the
loss of tags due to mortality events,
tag manufacturers and researchers
have developed mechanisms that re-
lease tags from dead or dying fish
before the structural integrity of the
tag is compromised at depth. These
mechanisms include both mechani-
cal devices that sever the monofila-
ment tether that attaches the tag to
the fish upon reaching a given depth
and internal software subroutines
that activate the normal electronic
release mechanism if the tag either
reaches a certain depth or maintains
a constant depth for a predetermined
length of time.
Despite the addition of these re-
lease mechanisms to PSATs, some
tags still fail to transmit data. Such
failure could result from any of the
following events or conditions: me-
chanical failure of a critical tag com-
ponent; destruction by fishing crews
unaware of or not participating in
the present research; excessive epi-
faunal growth that makes the tag
negatively buoyant or prevents the
tag from floating with the antenna
in a vertical position; or fouling of
the tag on the fish, fishing gear, or
flotsam. Another cause of failure is
that the tags could be lost as a re-
sult of ingestion. For example, a free-
swimming white marlin (Tetrapturus
albidus) was observed mouthing and
almost swallowing a free-floating
PSAT off the Dominican Republic in
May 2002 (Graves, personal observ.).
Alternately, the tag could be ingested
incidentally with part of the tagged
fish, as described by Jolley and Irby
(1979) who reported that an acoustic
tag on a sailfish (Istiophorus platyp-
terus) was eaten along with the fish
by an undetermined species of shark.
In this note, we present data from
PSATs deployed on two white marlin
in the western North Atlantic Ocean
and on an opah (Lampris guttatus)
in the central Pacific; the data from
these tags indicate that the tags were
consumed by sharks.
Materials and methods
White marlin 1 (WM1)
At approximately 10:00 am local time
on 1 September 2002, a white marlin
was observed on pelagic longline
gear set during the night near the
southeastern edge of Georges Bank.
The fish, which had been caught
on a slightly offset, straight-shank
J-style hook (size 9/0), was manu-
ally guided with the leader along-
side the vessel. A PTT-100 HR model
PSAT (Microwave Telemetry, Inc.,
Columbia, MD) was attached to the
dorsal musculature approximately 5
cm below the base of the dorsal fin
with a large nylon anchor according
to the procedure and tether design
described in Kerstetter et al. (20031.
The tag was activated shortly after
the white marlin was first identified,
although approximately one hour is
required following activation for this
tag model to begin collecting data.
The tag was programmed to record
point measurements of temperature,
light, and pressure (depth I in four-
minute time intervals and to detach
from the animal after 10 days. After
release from the fish, the positively
buoyant tag was expected to float to
the surface and transmit stored and
real-time data. For both white marlin
Manuscript submitted 27 April 2003
to the Scientific Editor's Office.
Manuscript approved for publication
7 June 2004 by the Scientific Editor.
Fish. Bull. 102:750-756120041.
NOTE Kerstetter et al.: Shark predation and scavenging on fishes equipped with satellite archival tags
751
Table 1
Comparison of depths
and temperatures recorded by three
pop-up sa
tellite archiva
tags (PSATs) before and
after the tags
were
ingested by
an organism.
Befo
•e ingestion
Afte
r ingestion
Depth
Depth
Temp.
Temp
Depth
Depth
Temp
Temp
range
mean
range
mean
range
mean
range
mean
Animal
(m)
(SD)
CO
(SD)
;;
(m)
(SD)
CO
(SD)
n
WM1
145.2
145.2
(±0.00)
11.6-11
11.7
(±0.07l
179
0-564.9
130.0
(±237.50)
12.1-26.5
24.1
(±0.84)
2755
WM2
0-26.9
5.9
(±4.44)
19.8-27.8
24.7
(±0.91)
207
0-699.3
131.0
(±162.61)
18.9-29.5
27.3
(±1.20)
1683
Opah
32-456
221.81
(±92.20)
8-25.6
16.68
(±4.21)
360
0-524
170.56
(±133.83)
26.2-30.6
28.64
(±0.67)
168
tags, minimum straight-line distances were calculated
between the point of release and the first clearly trans-
mitted location of the tag following its release (pop-off)
(Argos location codes 0-3).
At the time of tagging, the longline hook used to cap-
ture the fish was not visible in the mouth of the white
marlin. The leader was therefore cut as close as possible
to the fish before the fish was released, following the
standard operating procedure for the domestic pelagic
longline fleet. The fish was maintained alongside the
vessel for less than three minutes for the application of
the PSAT and a conventional streamer tag. Although the
white marlin was initially active at the side of the vessel,
some light bleeding from the gills was noted. After re-
lease, the fish swam away slowly under its own power.
the dorsal musculature with a Wildlife Computers tita-
nium anchor. The tag was programmed to record the
temperature and depth occupied by the fish in binned
histograms, and the minimum and maximum tempera-
tures and depths for 12-hour time periods. However,
these 12-hour bins encompassed both day and night
periods. The tag was programmed to be released six
months after deployment. In the event of a premature
release, the tag was programmed to begin transmitting
stored data if it remained at the surface for longer than
three days. The opah was lively and quickly dived after
it was released.
Results
White marlin 2 (WM2)
At 9:05 am on 2 August 2003, a white marlin was
observed on pelagic longline gear with the same configu-
ration in the same approximate area of Georges Bank as
WM1. The fish was caught by a circle hook (size 16/0) in
the right corner of the mouth, and although the stomach
was everted, the fish appeared to be in excellent physi-
cal condition. A PTT-100 HR tag had been activated at
6:30 am that morning, and was therefore collecting data
at the time of tagging. After the fish was brought to the
side of the vessel, both the PSAT and a conventional
streamer tag were attached to this fish in less than three
minutes by using the same protocol as that described for
WM1, and the fish swam strongly away from the vessel
after release without any evident bleeding.
Opah
At 5:52 pm local time on 21 November 2002, a female
opah was observed on pelagic longline gear set during
the day east of the Island of Hawaii. The fish was brought
to the side of the fishing vessel and a Wildlife Computers
(Redmond. WA) PAT2 model tag was attached through
WM1
Release of the PSAT was expected to occur on 10 Sep-
tember 2002 and the tag was expected to begin transmit-
ting data on that date, but the first transmission was
not received until almost two days later. At the time of
first transmission, the PSAT was 81.3 km (43.9 nmi)
west-southwest of the tagging location. A total of 81.5%
of the archived light level, temperature, and pressure
(depth) data was recovered.
The light level, temperature, and pressure (depth)
readings over time are presented in Fig. 1 (A-C) and
summarized in Table 1. The first light level measure-
ments indicated that the fish was already in relatively
dark waters within one hour following its release. Light
levels continued to drop to almost zero during the next
ten hours and remained at that level for the next nine
days (Fig. 1A). During the next seven-day surface trans-
mission period, the tag recorded real-time day and night
differences in light levels, which indicated that the light
sensor was functioning properly.
Sea surface temperatures in the area where the gear
was set and hauled back, varied from 25.2° to 26.7°C
(D. Kerstetter. unpubl. data) and the first temperature
752
Fishery Bulletin 102(4)
Q.
CD
D
A
WM1
flu
1
200 •
i
i"f
f
400 •
'A
i
1 !l
i:
600 •
i
9/1/02 9/4/02 9/7/02 9/10/02 9/13/02 9/16/02 9/19/02
B
9/1/02 9/4/02 9/7/02 9/10/02 9/13/02 9/16/02 9/19/02
c
1.0'
™
""
"T r
np
08.
06-
04.
02.
1
~
9/1/02 9/4/02 9/7/02 9/10/02 9/13/02 9/16/02 9/19/02
WM2
8/3/03 8/6'03 8/9/03 8/12/03 8/15/03 8/18/03 8/21/03 8/24/03
E
32
28-
24-
20-
8/3/03 8/6/03 8/9/03 8/12/03 8/15/03 8/18/03 8/21/03 8/24/03
8/3/03 8/6/03 8/9/03 8 12/03 8/15/03 8/18/03 8/21/03 8 24,03
Figure 1
Graphs of data on and depth (A and Di. temperature (B and E), and light index iC and Fl for tags WM1
and WM2. Lighter lines and points are prior to programmed release date, whereas darker lines and points
are "real-time" surface condition measurements transmitted by the tag in addition to the archived data.
recording by the PSAT (one hour after activation) was
11°C (Fig. IB). The temperature remained fairly con-
stant at 11°C for a period of approximately ten hours
after which there was a rapid rise to 25°C. The temper-
ature of the PSAT remained between 22.5° and 26. 5C
for the next nine days (until the programmed release
date), with the exception of one brief decrease to 20 C
on 8 September. When the tag began transmitting on
12 September, the real-time surface temperature was
23.6°C.
The pressure data (Fig. IC) indicated that the tag was
at a depth of approximately 145 m at one hour following
release. The PSAT remained at this depth for a little
more than ten hours after which the data suggested
that there was a rapid rise to the surface. For the next
nine days, the tag reported considerable vertical move-
ment between the surface and depths to 565 m. The
tag was at the surface when it began transmitting both
archived and real-time data on 12 September.
WM2
The tag reported data as expected on 13 August 2003
and transmitted 57.3rr of the archived data. At the time
of first transmission, the PSAT was 600.1 km (324.0
nmi) east-southeast of the tagging location. Summary
depth and temperature data recorded by the PSAT are
included in Table 1.
From the depth and temperature data, it appears
that the fish survived for approximately 24 hours af-
ter release, at which point the light readings dropped
to zero (see Fig, ID) and remained at that level for
NOTE Kerstetter et al.: Shark predation and scavenging on fishes equipped with satellite archival tags
753
the next eight days. The depth record following
this change in light level was marked by several
discrete diving events, and depths (see Fig. IF)
ranged between the surface and over 699 m.
Recorded temperatures for this period varied
between 18.9° and 29.5°C, although sea surface
temperatures in the area where gear was set and
hauled back varied from 20.9° to 26.0°C (Ker-
stetter, unpubl. data). On 12 August, the light
level returned to its maximum value and the tag
remained at the surface for approximately one
day until its scheduled release date (13 August)
when it began transmitting data.
Opah
The PAT2 satellite tag was expected to pop-up
6 months after deployment, but the first trans-
mission was received after only 34 days from a
location about 330 km (178 nmi) northwest of the
deployment site. All the archived binned light
level, temperature, and pressure (depth) data
from this period were recovered (see Table 1).
This tag model collected eight temperature and
depth samples during each 12-hour period, result-
ing in 16 values per day or 528 total values for
the deployment period. The two 12-hour blocks
were removed from all analyses to more accu-
rately represent the differences in data between
specimens: 1) the 12-hour block after tagging in
order to allow for the recovery of the animal, and
2) the 12-hour block during which the predation
event putatively occurred in order to clarify the
potentially distant depth and temperature char-
acteristics of the ingesting animal.
The measured sea surface temperature during
the tagging of the opah was 25.9°C. The ranges
of dive depths, temperature, and light based on
minimum and maximum values over the 12-hour
day and night periods showed two distinct pat-
terns (Fig. 2). During the first period (23 days),
the dive depths ranged from about 32 to 456
m (Fig. 2A). Water temperatures encountered
by the tag during this period ranged from 8.0°
to 25.6°C (Fig. 2B) and the light index values
ranged from about 50 to 150 (Fig. 2C). During
the second period (11 days), the dive depths ranged from
0 to 524 m, temperature ranged from 26.2° to 30.6°C
(higher than the 24.2-24.8°C SST recorded by the tag
after it was released from the fish), and the light index
recorded persistently low values.
Discussion
WM1
Our interpretation of these data is that the PSAT
on WM1 was ingested by an animal scavenging the
marlin carcass. The first PSAT readings for WM1,
Dive minimums and maximums
0
100
E
200
Q
300
400
500
'
11/24/02 11/30/02 12/6/02 12/12/02 12/18/02 12/24/02
Dive minimums and maximums
28
'.•■' Ii'' I'-'-'l'l
O
24-
o
Q.
E
|2
20 -
16 -
12 -
R
O i ' i ' 1 ' l ' I ' i
11/24/02 11/30/02 12/6/02 12/12/02 12/18/02 12/24/02
Light minimums and maximums from location data
250
200-
en
0
=J
CO
>
150
100
_i
50- ' I I
0
, | ..,11...
I I I ' 1 ' I
11/24/02 11/30/02 12/6/02 12/12/02 12/18/02 12/24/02
Date
Figure 2
G
raphs of depth (A), temperature (B), and light index (C) for
the opah PAT tag from deployment until transmission.
recorded about one hour after its release, indicated
that the marlin was already dead or moribund by
that time and was descending to the ocean floor. For
the next ten hours, the tag and carcass remained at
a constant depth of 145 m (the depth of the nearest
sounding at the site of release, according to NOAA
depth chart 13003 [1998], was approximately 160 m)
and at a temperature of 11°C. The light level steadily
decreased at approximately 4:30 pm, corresponding to
changes in ambient light from the setting of the sun.
At approximately 9:00 pm local time, there was a dra-
matic change in conditions when temperature rapidly
rose to near 26°C and depths began to vary between
the surface and 600 m.
754
Fishery Bulletin 102(4)
We cannot attribute these chang-
es to a resuscitation of the fish for
three reasons. 1) The measured light
levels indicated that the tag was in
complete darkness for a period often
days, even though it was at the sur-
face during daylight hours. A mal-
functioning light sensor cannot ex-
plain this observation because the tag
recorded day and night differences
in light levels at the surface during
the seven-day transmission period af-
ter it was released from the fish. 2)
After a rapid increase, the tempera-
ture remained relatively constant,
between 23° and 26°C, even when
the tag was at depths in excess of
300 m. Although dive behavior may
be affected by location-specific con-
ditions, previous PSAT observations
of more than 20 other white marlin
indicated that temperature ranges of
individual dive events rarely exceed
8°C when, it is assumed, animals
make foraging dives to depth (Horo-
dysky et al., in press). 3) The PSAT
recorded several dives in excess of 400 m, and previous
observations of white marlin have revealed no dives in
excess of 220 m (Horodysky et al., in press). Finally,
the PSAT was scheduled to be released from WM1 after
ten days on 10 September. Although archiving of light,
temperature, and pressure data ceased on that date, the
tag did not begin transmitting until 12 September.
WM2
The shallow dive patterns reported by this fish may
indicate that it survived for approximately 24 hours
following its release. Between 12:45 and 3:07 pm (local
time), the light level fell abruptly from the maximum
light level value to zero. At 3:08 pm, the temperature
was 19.8°C at 166 m depth; by 4:37 pm, the tempera-
ture was above 24°C and remained above this value for
the remainder of the deployment period. At 5:58 pm on
12 September, the light levels returned to maximum
strength from zero — an indication that the tag had
likely been egested. For the 19 hours remaining of the
programmed deployment period prior to pop-off, the
depth, light, and temperature data all indicated that
the tag was floating at the surface.
Opah
Based on recovered data, our conjecture is that the tag
was attached to the live opah for the first 23 days. Then,
sometime during the 12-hour period from 2:00 pm 13
December to 2:00 am 14 December the tag was ingested.
From our data, we cannot discern whether 1) the tag
was detached prematurely from the opah and was float-
ing on the surface when it was ingested, 2) an animal
D
CD
■o
Temperature
Depth
Figure 3
Delayed temperature changes recorded by tag WM1 following deep dive
events on the morning of 2 September 2002. Arrows indicate the lowest
temperatures recorded in association with a movement of the animal to
depth; note that these temperatures were often recorded while the animal
was at or near the surface and therefore represent a delay between depth
and temperature.
attacked the opah and ingested the tag incidentally,
or 3) an animal ingested the tag alone. However, it is
unlikely that the opah died, sank to the ocean floor, and
was scavenged because the ocean floor in the area where
the opah was tagged is below 2000 m. We have observed
from other tags on opahs what we believe are mortalities;
these occur shortly after tagging and show that the tag
reaches depths in excess of 1000 m before detaching when
the emergency pressure release in the tag is triggered. We
did not observe depths below 600 m at any time during
this record, and therefore the pressure-induced detach-
ment mechanism on the tag was not triggered.
The ingestion hypothesis for the failure of these three
tags to transmit data is supported by several lines of
evidence. First, the light level readings were consistent
with a tag residing in the complete darkness of an
alimentary canal. Second, although temperature varia-
tions occurred during the deployment period, the delay
in temperature changes during dives to depths indicates
that the tags were not directly exposed to ambient wa-
ter (see Fig. 3 for an example from WM1, as well as the
comparisons in Table 1) and further may indicate that
the scavenger was either endothermic or of large enough
size to mitigate heat loss at depth.
There are several organisms that could have eaten
these PSATs, whether by scavenging a carcass or at-
tacking a moving fish. Clearly, each of these organisms
was sufficiently large to ingest the tag without seri-
ously damaging it. It is unlikely that a cetacean was
responsible for any of these events because internal
temperatures for odontocete whales (including killer
whales, Orcinus orca) range between approximately 36°
and 38°C (Whittow et al., 1974)— well above the range
of temperatures recorded by the PSATs.
NOTE Kerstetter et al.: Shark predation and scavenging on fishes equipped with satellite archival tags
755
The only other natural predators of large pelagic
fishes are various species of sharks. Several species of
lamnid sharks maintain elevated body temperatures,
including the shortfin mako {Isurus oxyrinchus) and the
white shark (Carcharodon carchariasl, both of which are
found in the area of Georges Bank (Cramer, 2000) and
the Central Pacific (Compagno, 1984). Several shortfin
makos were caught by the same longline vessel during
the week following each white marlin PSAT deployment
(WM1: n=4, 95-189 cm FL; WM2: n=3, 94-199 cm FL)
(Kerstetter, unpubl. data). The opah tag record closely
resembles the relatively constant temperature noted for
lamnid sharks, despite the independence of stomach
temperature with ambient water for these endothermic
sharks as reported by Carey et al. (1981). It is also
interesting to note that although precipitous tempera-
ture fluctuations were generally absent, a rapid drop in
temperature from 24° to 20°C was observed with tag
WM1 on 8 September at 32.3 m depth— a fluctuation
that could have resulted from another feeding event
that brought cool food matter into the stomach. Simi-
lar reductions in stomach temperatures due to feeding
have been noted for white sharks (McCosker, 1987). The
range of temperatures recorded by each of the two white
marlin tags appears rather broad for an endothermic
shark, however, and although the temperature at depth
was not measured, the delay in stomach temperature
closely resembles the pattern of blue shark internal
temperatures {Prionace glauca) measured in the Mid-
Atlantic (Carey and Scharold, 1990).
The diving behavior recorded by the three tags also
corroborates ingestion of the tags by sharks. Carey et al.
(1982) reported that a tagged white shark off Long Is-
land, New York, made frequent dives to the bottom dur-
ing a 3.5-day acoustic tracking period. White sharks are
known to dive to depth while scavenging whale carcasses
(Dudley et al., 2000; Carey et al., 1982). A juvenile white
shark also tracked by Klimley et al. (2002) spent far
more extended times at depth than either white marlin
tag. Although the programming of the tag on the opah
precludes such fine-scale analyses of diving behavior, the
available data are not inconsistent with the mako tracks
in the study of Klimley et al. (2002). However, the short
duration dives with frequent returns to the surface seen
with the two white marlin tags most closely resemble
those of blue sharks (Carey and Scharold, 1990) and
were notably missing from the tracks of three shortfin
makos observed by Klimley et al. (2002).
If sharks were indeed the scavenging animals, it
is likely that the tags were regurgitated, rather than
egested through the alimentary canal, whereupon the
PSAT floated to the surface and was able to transmit
the archived data. The narrow diameter of the spiral
valve in the elasmobranch gastrointestinal tract would
likely be too narrow to allow the undamaged passage
of an object the size of a PSAT, even for a large shark.
Although the available literature describing regurgita-
tion abilities of pelagic sharks is rather limited, Hazin
et al. (1994) reported that 35% of blue sharks brought
aboard for scientific study had everted and protruding
stomachs. Economakis and Lobel (1998) also stated
their belief that regurgitation of ingested ultrasonic
tags was the primary cause of lost tracks for grey reef
sharks iCarcharhinus amblyrhynchos) on Johnston Atoll
in the central Pacific Ocean.
Conclusions
The temperatures and dive depths recorded by the opah
tag and both white marlin tags after apparent ingestion
share similarities, yet also contain sufficient information
to indicate the different identities of the ingesting organ-
isms. The dive depths in all cases ranged from the surface
to over 500 m, whereas the temperatures remained rela-
tively constant at several degrees above the background
SST, even during deep dive events. Temperature ranges
alone strongly indicate sharks rather than odontocete
whales were the ingesting organisms. However, limited
literature on the internal stomach temperatures of the
various pelagic sharks forces us to rely on telemetered
diving behavior data for further species identification,
which we used in the present study to suggest that blue
sharks ingested the two white marlin tags (on account
of the broad range of recorded temperatures) and that
an endothermic shark ingested the opah tag.
It is not possible to account for all of the factors that
may result in the failure of satellite tags to transmit
data, but the results from these three PSATs indicated
that biological activities such as predation and scaveng-
ing may play an important role. We believe that the
most consistent explanation for the data transmitted
by these three tags is that they were ingested by large
sharks. One cannot calculate the probability that a
tag could be engulfed whole without physical damage
to the tag, survive for several days in the caustic en-
vironment of a digestive system, and be regurgitated
with sufficient battery power to transmit data to the
Argos satellites, but we suspect that the probability is
not very great. We expect that a far greater number of
tags may have had similar fates, that is to say, they
were damaged by predation or scavenging and digestion
processes or were regurgitated later in the transmis-
sion cycle, when the PSAT batteries had insufficient
remaining power for successful data transmission. The
failure of satellite tag to transmit data is frequently
considered to be the result of internal tag malfunction
or user error. However, these three data sets clearly
indicate that the failure of PSATs to function may also
be due to predation or scavenging events.
Acknowledgments
The authors would like to thank the Captain of the FV
Sea Pearl and Captain Greg O'Neill of the FV Carol Ann,
Don Hawn (University of Hawaii), who deployed the tag
on the opah, Evan Howell (PIFSC) for analyses of the
opah data, Andrij Horodysky (VIMS), who provided a
critical review of the manuscript. Melinda Braun (Wild-
756
Fishery Bulletin 102(4)
life Computers), who suggested the predation hypothesis
to explain the opah data, and Lissa Werbos (Microwave
Telemetry. Inc.), who independently suggested the scav-
enging hypothesis for the WM1 data. This research was
supported in part by the National Marine Fisheries
Service, the NOAA Ocean Exploration Program, and
the University of Hawaii Pelagic Fisheries Research
Program (PFRP).
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757
Survival rates for rays discarded by the
bottom trawl squid fishery off the Falkland Islands
Vladimir V. Laptikhovsky
Falkland Islands Government Fisheries Department
P.O. Box 598
Stanley, FIQQ 1ZZ
Falkland Islands
E-mail address: vlaptikhovskyigfisheries.gov fk
Waters off the Falkland Islands are
subject to a specialized multispecies
ray fishery and were first fished by
a Korean fleet in 1989. More than
twenty different rajid species have
been recorded from catches around
the islands, and five species accounted
for 87.04% of the total catch during
1993-2002. Catches peaked in 1993
at 8523 metric tons, and specific fish-
ing licenses — R (second season) and F
(first season) — were first introduced
in 1994 and in 1995, respectively
(Agnew et al. 2000; Falkland Islands
Government, 2002; Wakeford et al.,
in press).
In addition to the licensed ray fish-
ery, rays are taken as bycatch in the
bottom trawl fishery that targets the
squid Loligo gahi and, to a lesser ex-
tent, by the trawl fishery that targets
finfish. A 10% bycatch of nontarget
species is allowed in both these fish-
eries. In 2000-2002, the reported
ray bycatch of trawlers not licensed
to catch rays represented between
20.2% and 31.9% of the total ray
catch. However, under-reporting of
elasmobranch bycatch is a common
practice for trawl fisheries where
sharks and rays are discarded (Ste-
vens et al., 2000), and the reported
chondrichthyan catch is only about
half of the estimated actual global
catch (Bonfil, 1994). The actual ray
bycatch in Falkland waters may be
much higher than reported because
only large rays are processed (and
therefore, reported) onboard trawl-
ers. This situation makes ray fishery
management in the Falkland Islands,
which is already difficult because of
the nature of the multispecies tar-
get, even more complicated. However,
good management is of primary im-
portance because sharks and rays
appear to be particularly vulnerable
to over-exploitation because of their
late attainment of sexual maturity,
long life span, both low fecundity and
natural mortality, and close relation-
ship between recruitment and paren-
tal stock (Stevens et al., 20001. In
the Falkland trawl fisheries (which
includes most trawlers licensed to
catch rays), rays smaller than ap-
proximately 30 cm disk width are
discarded after spending between 5
min and 4 hours in the fish bin and
passing through the factory sorting
line together with other catch. Some
rays that have been caught, stored,
and then discarded still show signs
of life. In contrast to other marine
organisms whose survival after be-
ing discarded has been investigated,
ray survival has been studied only
in Australian waters (Stobutzki et
al.. 2002). The aim of this study was
to investigate the survival rates of
discarded rays onboard trawlers in
the Falkland waters.
Materials and methods
The research was conducted onboard
the Falkland Islands registered
trawler Sil (length of 78.5 m, gross
tons (GRT) of 2156 t, net tons (NT)
of 647 t). The vessel used a bottom
trawl with a vertical opening of 5 m,
horizontal opening of 30 m, and a
codend mesh size of 110 mm. Trawl-
ing speed varied between 3.8 and and
4.2 kn. Fishing occurred at a depth
of 80-190 m during the day and the
early part of the night. The surface
temperature was 8.7-9.2°C; the near
bottom temperature was 6.8-7.6°C.
Up to four hauls occurred daily. Each
catch was released from the codend
into the fish bin, which had a continu-
ous supply of sea water, and the catch
immediately began to be sorted on a
conveyor belt. Squids and commercial
fish were separated from the noncom-
mercial discarded bycatch and were
frozen. Of a total of 4306.2 kg of rays
caught during the observed period,
67.0% were discarded and only the
large rays were processed. The time
taken to sort the catch was between
1 and 3 hours.
A total of 66 rays that had been
discarded by fishermen were sampled
randomly from the conveyor belt and
put into a 40-liter (44x35x26 cm)
or a 60-liter (31x76x26 cm) fish box
that contained running seawater.
For each animal, the species and sex
was identified and total length (TL)
and disk width (DW) were measured
within 1 cm. Their "stamina index"
was assigned according to four major
categories:
A alive, flapping wings.
I immobile, but alive, reacting to
irritation, spiracles beginning
to work actively after being
placed in seawater.
D dead; immobile, but spiracles begin
to move slowly and irregularly
after being placed in seawater.
DD dead; paralyzed, body stiffened
and wings curved but may
resume breathing after being
placed in seawater.
Each ray (including those evident-
ly dead) was kept in these boxes ei-
ther until its death was evident (no
breathing) or it fully recovered and
began to try to swim actively. In
some rays the rate of spiracle con-
tractions was episodically recorded.
Manuscript submitted 5 June 2003
to the Scientific Editor's Office.
Manuscript approved for publication
30 June 2004 by the Scientific Editor.
Fish. Bull. 102:757-759 (2004).
758
Fishery Bulletin 102(4)
Table 1
Species composition and
survival of sampled
rays. DW= disk width.
Species
n
TL, cm
DW. cm
T
ime spent in fish bin (min.)
Survival rate (%)
Bathyraja albomaculata
14
36-61
26-44
20-110 (mean 45)
71.4
B. brachiurops
11
15-67
9-49
31-145 (mean 72)
54.6
B. griseocauda
3
62-83
47-60
30-75 (mean 60)
0.0
B. macloviana
2
36-42
24-29
70-135
0.0
B. magellanica
5
30-44
20-30
50-125 (mean 90)
60.0
Bathyraja sp.
16
24-104
21-74
5-120 (mean 52 )
75.0
Psammobatis sp.
15
29-47
18-33
30-200 (mean 98)
60.0
Table 2
Ray survival (S% ), mean recovery time (RT, min.), and occurrence of the four
of time (T, min.) spent in the fish bin. T=time (minutes). A=alive; I=immobile;
'stamina index" categories after different
D=presumed dead; DD = dead.
periods
T n S
RT
Occurrence of categories c'< l
A
I D
DD
5-30 16 87.5
31-60 20 75.0
65-120 24 41.7
125-200 6 16.7
38.2
55.5
102.2
20'
18.75
10.0
0
0
25 18.75
30.0 40.0
20.8 50.0
16.7 83.3
37.5
20.0
29.2
0
' Only one individual (Psammobathis sp. 1.
Results
The sampled rays belonged to eight species (Table 1). Of
the 66 sampled rays, a total of 21 were dead at sampling,
four recovered breathing but then died, and 39 survived.
Two rays recorded as category DD in the "stamina
index" were released before full recovery after being held
for 4 to 9 hours in running water. Even though these
individuals were still breathing, both were considered
dead because they still had stiffened bodies and curved
wings. If they had been in such a state for a long time
in their natural habitat, they almost certainly would
have been consumed by scavengers or caught again by
another trawler. The overall survival rate was 59.1%,
female survival rate was 66.7%, and male survival rate
was 56.4%.
All five rays assigned to the "stamina index" category
A were sampled between 5 and 30 min (mean 20 min)
after the catch was poured into the fish bin. All five
individuals began immediately to breathe normally and
recovered within 5 to 20 minutes.
Of a total of 18 rays assigned to the "stamina index"
category I, which were sampled between 15 and 145 min
(mean 55.7 min) after haul, 88.9% (n=16) survived. The
breathing of these specimens at the time of sampling
was usually slow, although occasionally normal. Spira-
cle contraction rates gradually increased from an initial
rate of 5-15 bit/min to 25-28 bit/min for B.brachiurops
specimens and to 35-38 bit/min for individuals of B.
albomaculata and Bathyraja sp. Upon attaining normal
breathing, they remained immobile, but fully recovered
between 15 minutes and 3 hours.
The survival rate of 28 rays that were assigned to
the "stamina index" category D was 39.3% («=11). Of
the remaining individuals, two rays died after 15 and
45 minutes after being placed in running seawater and
15 rays were dead at the time of sampling. The skates
were sampled between 30 and 200 min (mean 84.2 min)
after the haul. Those that survived took 5-80 minutes
to recover normal breathing and between 15 and 315
minutes to attain full recovery.
A total of 15 rays were assigned the "stamina index"
category DD. However seven of them (46.7%) survived.
These individuals were sampled between 20 and 115
minutes (mean 63.9 min.) after the haul and fully re-
covered within 40 to 150 minutes.
Survival rate varied substantially among the eight
species sampled (Table 1). In general, ray survival dras-
tically decreased and recovery time increased with the
time spent in the fish bin (Table 2). The critical dura-
tion in the fish bin appeared to be between one and two
hours; only one Psammobathis sp. survived more than
two hours in the fish bin and exhibited a surprisingly
fast recovery.
NOTE Laptikhovsky: Survival rates for rays by the bottom trawl squid fishery
759
Discussion
Acknowledgments
The survival of discarded rays during trawling opera-
tions in the Falkland waters is quite important. Although
65.2% of the individuals were initially assigned as dead,
the actual mortality was 40. 99c, although it took some
rays up to six hours to recover. Survival of shallow-water
shelf species such as Psammobatis sp., in particular, but
also B. brachiurops and B. magellaniea, was somewhat
higher than relatively deep-water species such as B.
albomaculata, B. griseocauda, and Bathyraja sp., which
inhabit the shelf edge and upper part of the slope. This
survival rate was most likely related to the greater
resilience to environmental changes for shallow-water
species, whose habitat is more changeable both season-
ally and spatially. Male survival was lower, which is in
accordance with data for rays and skates obtained in
northern Australian waters (Stobutzky et al., 2002).
Recent data from a tropical prawn fishery off northern
Australia showed that on average 449c of individuals of
a number of ray and shark species survived a trawl-
ing event (Stobutzky et al., 2002). The Falkland ray
survival rate was higher. This difference may be due
either to the higher metabolic rates of tropical ray spe-
cies (and therefore a higher vulnerability to asphyxia),
or to an overestimation of their mortality, which was
assessed immediately after individuals where landed on
deck (unlike the recovery time allowed in the present
study). The latter factor is more probable because in the
present study 41.9% of rays initially recorded as dead
(D and DD) eventually recovered.
Despite the demonstrated ability of skates to survive
after being caught and stored in fish bins, their contin-
ued survival is not guaranteed once they are discarded.
They may fall prey to the hundreds of albatrosses and
other scavenging birds that are associated with trawl-
ers (author's pers. obs.). The consumption of differ-
ent discarded fish species and squids from trawlers in
Falkland waters by seabirds, primarily by black-browed
albatrosses, has been studied (Thompson, 1992), but it
is not known whether rays are also taken by sea birds
and to what extent. Despite the great abundance of
seabirds around vessels in the Southwest Atlantic, it
is likely that they consume a minor part of discards as
found in Australia (Hill and Wassenberg, 2000). Most
of the discarded fish probably fall to the sea floor and
attract and are consumed by bottom scavengers and
bottom dwellers (Laptikhovsky and Fetisov, 1999; Lap-
tikhovsky and Arkhipkin, 2003). Consequently, even
after recovering and successfully avoiding the seabirds,
the discarded skates may be consumed or mortally in-
jured by these bottom scavengers during the recovery
time, which appears to be about 0.5-1.5 hours.
I would like to thank the crew of FV Sil for their valu-
able help during sampling procedures and their hospital-
ity onboard; the Director of Fisheries, John Barton, for
supporting this work; A. I. Arkhipkin and an anonimous
reviewer for valuable comments; and Helen Otley (FIFD)
for language editing.
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Acknowledgment of reviewers
The editorial staff of Fishery Bulletin would like to acknowledge the scientists
who reviewed articles published in 2003-2004. Their contributions have helped
ensure the publication of quality science.
Dr. G.R. Abbe
Dr. Pere Abello
Mr. Douglas H. Adams
Dr. Vera N. Agostini
Dr. Juergen Alheit
Dr. Robert J. Allman
Mr. Michael D. Arendt
Dr. Alexander I. Arkhipkin
Dr. David A. Armstrong
Dr. Colin Attwood
Ms. Larisa Avens
Mr. M. Scott Baker Jr.
Dr. Donald M. Baltz
Dr. A. Banner
Dr. Jay Barlow
Dr. Steve Berkeley
Dr. Eric R Bjorkstedt
Dr. James A. Bohnsack
Ms. Genevieve Briand
Dr. Richard W. Brill
Dr. Alejandro M. Brockmann
Dr. Fiona M. Brook
Dr. Elizabeth Brooks
Dr. Nancy Brown-Peterson
Dr. Jay Burnett
Mr. Michael Burton
Dr. Morgan S. Busby
Dr. Michael Canino
Dr. John K. Carlson
Dr. Milani Y. Chaloupka
Dr. David M. Checkley Jr.
Dr. Susan J. Chivers
Dr. Phillip J. Clapham
Dr. William Coles
Mr. L. Alan Collins
Dr. Craig Dahlgren
Dr. Marilyn E. Dahlheim
Dr. Louis B. Daniel III
Dr. Jana L.D. Davis
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Dr. Edward E. DeMartini
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Ms. Moira Galbraith
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Dr. Chris Habicht
Dr. Lewis J. Haldorson
Dr. J. Mark Hanson
Dr. E. Brian Hartwick
Dr. James T. Harvey
Dr. Jonathan Heifetz
Dr. Kevin T. Hill
Dr. Simeon Hill
Dr. David B. Holts
Dr. J. Jeffrey Isely
Dr. George D. Jackson
Ms. Nadine Johnston
Dr. Lindsay Joll
Dr. Michel J. Kaiser
Mr. Craig R. Kastelle
Dr. Izhar A. Khan
Dr. J. King
Dr. A. Peter Klimley
Dr. Suzanne Kohin
Dr. Thomas E. Laidig
Dr. Richard W. Langton
Ms. Amy Lapolla
Dr. Robert N. Lea
Dr. Christopher M. Legault
Dr. Steven T. Lindley
Dr. Romuald Lipcius
Dr. Kwang Ming Liu
Dr. Kai Lorenzen
Dr. Milton S. Love
Mr. Mark S. Lowry
Dr. Mark Luckenbach
Dr. R. Bruce MacFarlane
Dr. William K. Macy
Dr. Richard McBride
Dr. Susanne McDermott
Ms. Kitty Mecklenburg
Dr. David A. Milton
Dr. T.J. Minello
Mr. Karl W. Mueller
Dr. Ashley Mullen
Dr. Keith D. Mullin
Dr. Michael D. Murphy
Dr. Kate Myers
Dr. Wallace J. Nichols
Dr. Peter F. Olesiuk
Dr. Ernst Peebles
Dr. Karl M. Polivka
Dr. Kenneth H. Pollock
Dr. Allyn B. Powell
Dr. Hans-Joachim Raetz
Dr. Stephen Ralston
Mrs. Tone Rasmussen
Dr. Sherrylynn Rowe
Dr. Peter Rubec
Mr. D.E. Ruzzante
Dr. Yvonne Sadovy
Dr. Bernard Sainte-Marie
Dr. Kurt M. Schaefer
Dr. George R. Sedberry
Dr. Jeffrey Seminoff
Mr. Lawrence Settle
Dr. James B. Shaklee
Dr. Alan Sinclair
Dr. Oscar Sosa-Nishizaki
Dr. Gretchen Steiger
Dr. David L. Stein
Dr. Allan W. Stoner
Dr. D.P Swain
Dr. Yonat Swimmer
Dr. Yuji Tanaka
Dr. Sven Thatje
Dr. A.M. Tokranov
Dr. M.J. Tremblay
Dr. Marc Trudel
Dr. Fred M. Utter
Dr. Peter Van Tamelen
Dr. Michael Vecchione
Dr. Claire M. Waluda
Mr. William Watson
Dr. George Watters
Dr. Elizabeth L. Wenner
Mr. A.J. Winship
Dr. Sabine Petra Wintner
Dr. Bernd Wursig
Dr. Orio Yamamura
Dr. Richard E. Young
761
Fishery Bulletin Index
Volume 102(1-4), 2004
List ot titles
102(1)
142 Growth, mortality, and hatchdate distributions of
larval and juvenile spotted seatrout (Cynoscion
jiebulosus) in Florida Bay, Everglades National
Park, by Allyn B. Powell, Robin T. Chesire, Elisabeth
H. Laban, James Colvocoresses, Patrick O'Donnell,
and Marie Davidian
1 The effects of size-selective fisheries on the stock
dynamics of and sperm limitation in sex-changing
fish, by Suzanne H. Alonzo and Marc Mangel
14 An environmentally based growth model that uses
finite difference calculus with maximum likeli-
hood method: its application to the brackish water
bivalve Corbicula japonica in Lake Abashiri, Japan,
by Katsuhisa Baba, Toshifumi Kawajiri, Yasuhuro
Kuwahara, and Shigeru Nakao
25 Juvenile salmonid distribution, growth, condition,
origin, and environmental and species associations
in the Northern California Current, by Rick D.
Brodeur, Joseph P. Fisher, David J. Teel, Robert L.
Emmett, Edmundo Casillas, and Todd W. Miller
47 Spatial and temporal variation in the diet of the
California sea lion (Zalophus californianus) in the
Gulf of California, Mexico, by Francisco J. Garcia-
Rodriguez and David Auarioles-Gamboa.
63 Recruitment and spawning-stock biomass distribu-
tion of bay anchovy {Anchoa mitchilli ) in Chesapeake
Bay. by Sukgeun Jung and Edward D. Houde
78 Coupling ecology and economy: modeling optimal
release scenarios for summer flounder (Paralichthys
dentatus) stock enhancement, by Todd G. Kellison
and David B. Eggleston
94 Sex-specific growth and mortality, spawning season,
and female maturation of the stripey bass (Lutjanus
carponotatus) on the Great Barrrier Reef, by Jacob
T. Krtizer
156 Age determination and growth of the night shark
(Carcharhinus signatus) off the northeastern Brazil-
ian coast, by Francisco M. Santana and Rosangela
Lessa
168 Distribution and biology of prowfish (Zaprora sile-
nus) in the northeast Pacific, by Keith R. Smith,
David A. Somerton, Mei-Sun Yang, and Daniel G.
Nichol
179 Fish lost at sea: the effect of soak time on pelagic
longline catches, by Peter Ward, Ransom A. Myers,
and Wade Blanchard
196 Effects of density-dependence and sea surface tem-
perature on interannual variation in length-at-age of
chub mackerel (Scomber japonicus ) in the Kuroshio-
Oyashio area during 1970-1997, by Chikako Wata-
nabe and Akihiko Yatsu
207 Latitudinal and seasonal egg-size variation of
the anchoveta (Engraulis ringens) off the Chilean
coast, by Llanos-Rivera, Alejandra, and Leonard R.
Castro
213 Molecular methods for the genetic identification
of salmonid prey from Pacific harbor seal iPhoca
vitulina richardsi) scat, by Maureen Purcell, Greg
Mackey. Eric LaHood, Harriet Huber, and Linda
Park
221 Diel vertical migration of the bigeye thresher shark
(Alopias superciliosus), a species possessing orbital
retia mirabilia, by Kevin C. Weng and Barbara A.
Block
108 Examination of the foraging habits of Pacific harbor
seal (Phoca vitulina richardsi) to describe their use
of the Umpqua River, Oregon, and their predation on
salmonids, by Anthony J. Orr, Adria S. Banks, Steve
Mellman, Harriet R. Huber, Robert L. DeLong, and
Robin F. Brown
118 Larval development of the sidestriped shrimp (Pan-
dalopsis dispar Rathbun) (Crustacea, Decapoda,
Pandalidae) reared in the laboratory, by Wongyu
Park, R. Ian Perry, and Sung Yun Hong
127 Sources of age determination errors for sablefish
(Anoplopoma fimbria) by Donald E. Pearson and
Franklin R. Shaw
102(2)
233 Annual estimates of the unobserved incidental kill
of pantropical spotted dolphin (Stenella attenuata
attenuata) calves in the tuna purse-seine fishery of
the eastern tropical Pacific, by Frederick Archer, Tim
Gerrodette, Susan Chivers, and Alan Jackson
245 A remarkable new species of Psednos (Teleostei:
Liparidae ) from the western North Atlantic Ocean,
by Natalia V. Chernova and David L. Stein
251 Age and growth of sailfish (Istiophorus platypterus)
in waters off eastern Taiwan, by Wei-Chuan Chiang,
Chi-Lu Sun, Su-Zan Yeh, and Wei-Cheng Su
762
Fishery Bulletin 102(4)
264 A habitat-use model to determine essential fish
habitat for juvenile brown shrimp {Farfantepenaeus
aztecus) in Galveston Bay, Texas, by Randall D.
Clark, John D. Christensen, Mark E. Monaco, Philip
A. Caldwell, Geoffrey A. Matthews, and Thomas J.
Minello
102(3)
407 Testicular development in migrant and spawning
bluefin tuna (Thunnus thynnus (L.>) from the east-
ern Atlantic and Mediterranean, by Francisco J.
Abascal. Cesar Megina, and Antonio Medina
278 Translocation as a strategy to rehabilitate the queen
conch {Strombus gigas) population in the Florida
Keys, by Gabriel A. Delgado, Claudine T Bartels,
Robert A. Glazer, Nancy J. Brown-Peterson, and
Kevin J. McCarthy
289 Genetic differentiation among Atlantic cod (Gadus
morhua) from Browns Bank, Georges Bank, and
Nantucket Shoals, by Christopher Lage, Kristen
Kuhn, and Irv Kornfield
298 Conserving oyster reef habitat by switching from
dredging and tonging to diver harvesting, by Hunter
S. Lenihan and Charles H. Peterson
306 Fecundity, egg deposition, and mortality of market
squid iLolilgo opalescens), by Beverly J. Macewicz,
John R. Hunter, Nancy C. H. Lo, and Erin L. LaCasella
418 Maturity, ovarian cycle, fecundity, and age-specific
parturition of black rockfish (Sebastes melanops), by
Stephen J. Bobko and Steven A. Berkeley
430 Maori octopus ( Octopus maorum ) bycatch and south-
ern rock lobster (Jasus edwardsii) mortality in the
South Australian lobster fishery, by Daniel J. Brock
and Timothy M. Ward
441 Small-boat surveys for coastal dolphins: line-tran-
sect surveys of Hector's dolphins (Cephalorhymhus
hectori), by Stephen Dawson, Elisabeth Slooten,
Sam DuFresne, Paul Wade, and Deanna Clement
452 Description and growth of larval and pelagic juvenile
pygmy rockfish (Sebastes wilsoni) (family Sebasti-
dae), by Thomas E. Laidig, Keith M. Sakuma, and
Jason A. Stannard
328 The dusky rockfishes (Teleostei: Scorpaeniformes I
of the North Pacific Ocean: resurrection of Sebastes
variabilis (Pallas, 1814) and a redescription of
Sebastes ciliatus iTilesius, 1813), by James Wilder
Orr and James E. Blackburn
349 Recruitment as a evolving random process of aggre-
gation and mortality, by Joseph E. Powers
366 Diet shifts of juvenile red snapper (Lutjanus
campechanus) with changes in habitat and fish size,
by Stephen T Szedlmayer and Jason D. Lee
464 Estimating the emigration rate of fish stocks from
marine sanctuaries using tag-recovery data, by
Richard McGarvey
473 Reproductive dynamics of female spotted seatrout
(Cynoscion nebulosus) in South Carolina, by William
A. Roumillat and Myra C. Brouwer
488 Estimating Dungeness crab (Cancer magistvr^
abundance: crab pots and dive transects compared,
by S. James Taggart, Charles E. O'Clair, Thomas C.
Shirley, and Jennifer Mondragon
376 Individual growth rates and movement of juvenile
white shrimp (Litopenaeus setiferus) in a tidal marsh
nursery, by Stacey Webb and Ronald T. Kneib
389 Does the California market squid (Loligo opalescens)
spawn naturally during the day or at night? A note
on the successful use of ROVs to obtain basic fisher-
ies biology data, by John Forsythe, Nuutti Kangas,
and Roger T. Hanlon
393 Incidental capture of loggerhead (Caretta caretta)
and leatherback (Dermochelys coriacea) sea turtles
by the pelagic longline fishery off southern Brazil,
by Jorge E. Kotas, Silvio dos Santos, Venancio G.
de Azevedo, Berenice M. G. Gallo. and Paulo C. R.
Barata
400 Diet changes of Pacific cod {Gadus macrocephalus)
in Pavlof Bay associated with climate changes in the
Gulf of Alaska between 1980 and 1995, by Mei-Sun
Yang
498 A method to improve size estimates of walleye pol-
lock (Theragra chalcogramma) and Atka mackerel
(Pleurogrammus monopterygius) consumed by pin-
nipeds: digestion correction factors applied to bones
and otoliths recovered in scats, by Dominic J. Tollit.
Susan G. Heaslip, Tonya K. Zeppelin, Ruth Joy,
Katherine A. Call, and Andrew W. Trites
509 Sizes of walleye pollock (Theragra chalcogramma)
and Atka mackerel (Pleurogrammus monopter-
ygius) consumed by the western stock of Steller sea
lions (Eumetopias jubatus) in Alaska from 1999
to 2000, by Tonya K Zeppelin, Dominic J. Tollit,
Katherine A Call, Trevor J. Orchard, and Carolyn
J. Gudmundson
522 Sizes of walleye pollock (Theragra chalcogramma)
consumed by the eastern stock of Steller sea lions
{Eumetopias jubatus) in Southeast Alaska from 1994
to 1999, by Dominic J. Tollit, Susan G. Heaslip, and
Andrew Trites
List of titles
763
533 Multidirectional movements of sportfish species
between an estuarine no-take zone and surrounding
waters of the Indian River Lagoon, Florida, by Derek
M. Tremain, Christopher W. Harnden, and Douglas
H. Adams
545 Distribution, age, and growth of young-of-the year
greater amberj ack (Seriola dumerili ) associated with
pelagic Sargassum, by R. J. David Wells and Jay R.
Rooker
555 Identification of formalin-preserved eggs of red
sea bream iPagrus major) (Pisces: Sparidae) using
monoclonal antibodies, by Shingo Hiroishi, Yas-
utaka Yuki, Eriko Yuruzume, Yosuke Onishi, Tomoji
Ikeda, Hironobu Komaki, and Muneo Okiyama
102(4)
563 Distribution and abundance of humpback whales
(Megaptera novaeangliae) and other marine mam-
mals off the northern Washington coast, by John
Calambokidis, Gretchen H. Steiger, David K. Ellifrit,
Barry L. Troutman, and C. Edward Bowlby
581 Reproductive biology of male franciscanas (Ponto-
poria blainvillei) (Mammalia: Cetacea) from Rio
Grande do Sul, southern Brazil, by Daniel Danile-
wicz, Juan A. Claver, Alejo L. Perez Carrera, Edu-
ardo R. Secchi, and Nelson F. Fontoura
593 Red snapper (Lutjanus campechanus) demographic
structure in the northern Gulf of Mexico based on
spatial patterns in growth rates and morphomet-
ries, by Andrew J. Fischer, M. Scott Baker Jr., and
Charles A. Wilson
604 Elemental signatures in otoliths of larval walleye
pollock (Theragra chalcogramma) from the north-
east Pacific Ocean, by Jennifer L. FitzGerald. Simon
R. Thorrold. Kevin M. Bailey, Annette L. Brown, and
Kenneth P. Severin
617 A sudden collapse in distribution of Pacific sar-
dine (Sardinops saga.x} off southwestern Australia
enables an objective re-assessment of biomass
estimates, by Daniel J. Gaughan, Timothy I. Leary,
Ronald W. Mitchell, and Ian W. Wright
634 Fish recolonization in temperate Australian rock-
pools: a quantitative experimental approach, by
Shane P. Griffiths, Ron J. West, Andy R. Davis, and
Ken G. Russell
661 Fishery dynamics of the California market squid
(Loligo opalescens), as measured by satellite remote
sensing, by Michael R. Maxwell, Annette Henry,
Christopher D. Elvidge. Jeffrey Safran, Vinita R.
Hobson. Ingrid Nelson, Benjamin T. Tuttle, John B.
Dietz. and John R. Hunter
671 Magnitude and distribution of sea turtle bycatch in
the sea scallop (Placopecten magellanicus) dredge
fishery in two areas of the northwestern Atlantic
Ocean, 2001-2002, by Kimberly T. Murray
682 Validation and interpretation of annual skeletal
marks in loggerhead (Caretta caretta) and Kemps
ridley (Lepidochelys kempii) sea turtles, by Melissa
L. Snover and Aleta A. Hohn.
693 The Hudson-Raritan Estuary as a crossroads for dis-
tribution of blue iCallinectes sapidus), lady (Ovali-
pes ocellatus), and Atlantic rock (Cancer irroratus)
crabs, by Linda L. Stehlik. Robert A. Pikanowski,
and Donald G. McMillan
711 Radiometric validation of age, growth, and longevity
for the blackgill rockfish (Sebastes melanostomus),
by Melissa M. Stevens, Allen H. Andrews, Gregor
M. Cailliet. Kenneth H. Coale. and Craig C.
Lundstrom
723 Descriptions of larval, prejuvenile, and juvenile
finescale menhaden (Brevoortia gunteri) (family
Clupeidae), and comparisons to gulf menhaden
(B. patronus), by James M. Tolan and David A.
Newstead
740 Capture probability of a survey trawl for red king
crab (Paralithodes camtschaticus), by Kenneth L.
Weinberg, Robert S. Otto, and David A. Somerton
733 Diet of the minimal armhook squid {Berryteuthis
anonychus) (Cephalopoda: Gonatidae) in the north-
east Pacific during spring, by Kazuhisa Uchikawa,
John R. Bower, Yasuko Sato, and Yasunori Sakurai
750 Evidence of shark predation and scavenging of fishes
equipped with pop-up satellite archival tags, by
David W. Kerstetter, Jeffery J. Polovina, and John
E. Graves
757 Survival rates of rays discarded by the bottom trawl
squid fishery off the Falkland slands, by Vladimir V.
Laptikhovsky
648 Factors influencing the timing and frequency of
spawning and fecundity of the goldlined seabream
iRhabdosargus sarba) (Sparidae) in the lower
reaches of an estuary, by S. Alexander Hesp, Ian C.
Potter, and Sonja R. M. Schubert
764
Fishery Bulletin 102(4)
Fishery Bulletin Index
Volume 102(1-4), 2004
List ot authors
Abascal, Francisco J. 407
Adams, Douglas H. 533
Alonzo, Suzanne H. 1
Andrews, Allen H. 711
Archer, Frederick 233
Auarioles-Gamboa, David 47
Azevedo, Venancio G. de 393
Baba, Katsuhisa 14
Bailey, Kevin M. 604
Baker Jr., M. Scott 593
Banks, Adria S. 108
Barata, Paulo C. R. 393
Bartels, Claudine T. 278
Berkeley, Steven A. 418
Blackburn, James E. 328
Blanchard, Wade 179
Block, Barbara A. 221
Bobko, Stephen J. 418
Bower, John R. 733
Bowlby, C. Edward 563
Brock, Daniel J. 430
Brodeur, Rick D. 25
Brouwer, Myra C. 473
Brown, Annette L. 604
Brown, Robin F. 108
Brown-Peterson, Nancy J. 278
Cailliet, Gregor M. 711
Caldwell, Philip A. 264
Call, Katherine A. 498, 509
Calambokidis, John 563
Casillas, Edmundo 25
Castro, Leonard R. 207
Chernova, Natalia V. 245
Cheshire, Robin T. 142
Chiang, Wei-Chuan 251
Chivers, Susan 233
Christensen, John D. 264
Clark, Randall D. 264
Claver, Juan A. 581
Clement, Deanna 441
Coale, Kenneth H. 711
Colvocoresses, James 142
Danilewicz, Daniel 581
Davidian, Marie 142
Davis, Andy R. 634
Dawson, Stephen 441
Delgado, Gabriel A. 278
DeLong, Robert L. 108
Dietz, JohnB. 661
DuFresne, Sam 441
Eggleston, David B. 78
Ellifnt, David K 563
Elvidge, Christopher D. 661
Emmett, Robert L. 25
Fischer, Andrew J. 593
Fisher, Joseph P. 25
FitzGerald, Jennifer L. 604
Fontoura, Nelson F 581
Forsythe, John 389
Gallo, Berenice M. G. 393
Garcia-Rodriguez, Francisco J. 47
Gaughan, Daniel J. 617
Gerrodette, Tim 233
Glazer, Robert A. 278
Graves, John E. 750
Griffiths, Shane P. 634
Gudmundson, Carolyn J. 509
Hanlon, Roger T, 389
Harnden, Christopher W. 533
Heaslip, Susan G. 498, 522
Henry, Annette 661
Hesp, S. Alexander 648
Hiroishi, Shingo 555
Hobson, Vinita R. 661
Hohn,AletaA. 682
Hong, Sung Yun 118
Houde, Edward D. 63
Huber, Harriet R. 108,213
Hunter, John R. 306, 661
Ikeda, Tomoji 555
Jackson, Alan 233
Joy, Ruth 498
Jung, Sukgeun 63
Kangas, Nuutti 389
Kawajiri, Toshifumi 14
Kellison, Todd G. 78
Kerstetter, David W. 750
Kneib, Ronald T 376
Komaki, Hironobu 555
Kornfield, Irv 289
Kotas, Jorge E. 393
Kritzer, Jacob P. 94
Kuhn, Kristen 289
Kuwahara, Yasuhiro 14
Laban, Elisabeth H. 142
LaCasella, Erin L. 306
Lage, Christopher 289
LaHood, Eric 213
Laidig, Thomas E. 452
Laptikhovsky, Vladimir V. 757
Leary, Timothy I. 617
Lee, Jason D. 366
Lenihan, Hunter S. 298
Lessa, Rosangela 156
Llanos-Rivera, Alejandra 207
Lo, Nancy C. H. 306
Lundstrom, Craig C. 711
Macewicz, Beverly J. 306
Mackey, Greg 213
Mangel, Marc 1
Matthews, Geoffrey A. 264
Maxwell, Michael R. 661
McCarthy, Kevin J. 278
McGarvey, Richard 464
McMillan, Donald G. 693
Medina, Antonio 407
Megina, Cesar 407
Mellman, Steve 108
Miller, Todd W. 25
Minello, Thomas J. 264
Mitchell, Ronald W. 617
Monaco, Mark E. 264
Mondragon, Jennifer 488
Murray, Kimberly T 671
Myers, Ransom A. 179
Nakao, Shigeru 14
Nelson, Ingrid 661
Newstead, David A. 723
Nichol, Daniel G. 168
O'Clair, Charles E. 488
O'Donnell, Patrick 142
Okiyama, Muneo 555
Onishi, Yosuke 555
Orchard, Trevor J. 509
Orr, Anthony J. 108
Orr, James W. 328
Otto, Robert S. 740
Park, Linda 213
Park, Wongyu R. 118
Pearson, Donald E. 127
Perez Carrera, Alejo L. 581
Perry, R. Ian 118
Peterson, Charles H. 298
Pikanowski, Robert A. 693
Polovina, Jeffery J. 750
List of authors
765
Potter, Ian C. 648
Powell, Allyn B. 142
Powers, Joseph E. 349
Purcell, Maureen 213
Rooker, Jay R. 545
Roumillat, William A. 473
Russell, Ken G. 634
Safran, Jeffrey 661
Sakuma, Keith M. 452
Sakurai, Yasunori 733
Santana, Francisco M. 156
Santos, Silvio dos 393
Sato,Yasuko 733
Secchi, Eduardo R. 581
Severin, Kenneth P. 604
Shaw, Franklin R. 127
Shirley, Thomas C. 488
Schubert, Sonja R. M. 648
Slooten, Elisabeth 441
Smith, Keith R. 168
Snover, Melissa L. 682
Somerton, David A. 168, 740
Stannard, Jason A. 452
Stehlik, Linda L. 693
Steiger, Gretchen H. 563
Stein, David L. 245
Stevens, Melissa M. 711
Su, Wei-Cheng 251
Sun, Chi-Lu 251
Szedlmayer, Stephen T. 366
Taggart, S. James 488
Teel, David J. 25
Tolan, James M. 723
Tollit, Dominic J. 498, 509, 522
Thorrold, Simon R. 604
Tremain, Derek M. 533
Trites, Andrew W 498, 522
Troutman, Barry L. 563
Tuttle, Benjamin T. 661
Uchikawa, Kazuhisa 733
Wade, Paul 441
Ward, Peter 179
Ward. Timothy M. 430
Watanabe, Chikako 196
Webb, Stacey 376
Wells, R. J. David 545
Weng, Kevin C. 221
Weinberg, Kenneth L. 740
West, Ron J. 634
Wilson, Charles A. 593
Wright, Ian W. 617
Yang, Mei-Sun 168, 400
Yatsu, Akihiko 196
Yeh, Su-Zan 251
Yuki, Yasutaka 555
Yuruzume, Eriko 555
Zeppelin, Tonya K. 498, 509
766
Fishery Bulletin 102(4)
Fishery Bulletin Index
Volume 102(1-4), 2004
List ot subjects
Abundance
Crab, Dungeness 488
dolphin. Hector's 441
estimates (pelagic longline) 179
harbor seal. Pacific 108
whales 563
Age
and growth
amberjack, greater 533
rockfish, blackgill 711
sailfish 251
shark, night 156
determination
problems with 127
sablefish 127
validation 711
Aggregation 349
Alabama 366
Alaska 488, 498, 509, 522
Aleutian Islands 168
Alopias superciliosus - see shark,
bigeye thresher
Alternative fishing practices 298
Amberjack, greater 545
Anchoa mitchilli - see anchovy, bay
Anchoveta 207
Anchovy, bay 63
Anoplopoma fimbria - see sablefish
Antibodies, monoclonal 555
Assemblages 634
Atlantic 245,407,671
Australia 430, 464, 634, 581, 617.
634
Bass, stripey 94
Batch fecundity 473
Bering Sea 509
Berryteuthis anonychus - see squid,
minimal armhook
Biomass
distribution 63
estimation (sardine) 617
spawning stock 63
Bones 498
Bottom trawl 168, 757, 740
Brazil 156,393,581
Brevoortia
gunteri - see menhaden, finescale
patronus -see menhaden, gulf
Browns Bank 289
Bycatch
in longline fishery 393
in lobster fishery 430
in sea scallop fishery 671
in squid fishery 757
in tuna purse-seine fishery 233
of dolphins 233
of octopus 430
of sea turtles 393,671
California 25, 306, 389, 453
Callineetes sapidus - see crab, blue
Cancer
irroratus - see crab, Atlantic rock
magister - see crab, Dungeness
Capture
incidental (sea turtles) 393
probability 740
-recapture 563
Carcharhinus signatus - see shark,
night
Caretta caretta - see sea turtles,
loggerhead
Catch rate 430
Catchability 740
Cephalorhynchus hectori - see
dolphin. Hector's
Cetaceans 661
Chesapeake Bay 63
Chile 207
Climate change 400
Clupeidae 723
Cod
Atlantic 289
Pacific 400
Conch, queen 278
Controlled access areas 563
Corbicula japonica 14
CPUE 489
Crab
Atlantic rock 693
blue 693
Dungeness 489
lady 693
red king 740
Crassostrea virgin ica -see oyster,
American
Crustacea 118,489
Cynoscion nebulosus - see seatrout,
spotted
Daytime spawning 389
Demographic structure 593
Density (population) 179
Dermochelys coriacea - see sea turtle,
leatherback
Descriptions (taxonomic)
Brevoortia
gunteri 723
patronus 723
Psednos 245
Sebastes
ciliatus 328
variabilis 328
wilsoni 452
Diet
cod. Pacific 400
prey volume 366
prowfish 168
sea lion
California 47
Steller 498, 509, 522
seal, harbor 108
snapper, red 366
squid 733
Digestion correction factor 498
Dissolved oxygen 63
Distribution
amberjack, greater 533
crab 693
hatchdate ( seatrout ) 142
prowfish 168
salmon, juvenile 25
whale 563
Diurnal cycle 389
Dive transects 489
Dissolved oxygen (DO) 63
Dolphin
Hector's 441
Spotted, pantropical 233
Dorsal-fin spine 251
Egg
deposition 306
identification (seabream) 555
-size variation 207
Elasmobranch 156, 221, 757, 750
Emigration rate 464
Engraulis ringens - see anchoveta
Escapement 740
Estuaries 376,533,648
Eumetopias jubatus -see sea lion.
Steller
Everglades 142
Falkland Islands 757
Farfantepenaeus aztecus - see shrimp,
brown
Fecundity 473, 648
batch 648
relative 473
rockfish, black 418
seabream 648
squid, market 306
List of sublets
767
Finite difference calculus 14
Fish size (red snapper) 366
Fisheries
interaction 509
management 581
size-selective 1
tuna 233
Fishery dynamics (squid) 661
Fishery reserve 533
Florida
Bay 142
eastern coast 533
Keys 278
Flounder, summer 78
Footrope 740
Formalin 555
Foraging (harbor seal) 108
Franciscana 581
Gadus
macroeephalus - see cod, Pacific
morhua - see cod, Atlantic
Galveston Bay 264
Generalized linear model 563
Generalized additive model 563
Genetic
differentiation (among cod) 289
identification 108, 213
Georges Bank 289
GIS 264
Glacier Bay 489
GLOBEC 25
Goldlined seabream 648
Gonadosomatic index 94
Great Barrier Reef 94
Growth
amberjack, greater 545
curve 156
prowfish 168
rockfish452, 711
seatrout, spotted 142
sex-specific 94
shark, night 156
shrimp, white 376
snapper, red 593
Gulf of Alaska 168,400,509
Gulf of California 47
Gulf of Mexico 593
Habitat
conservation 298
use of 264
Hand harvesting 298
Harvesting techniques 298
Hatching date
seatrout, spotted 545
snapper, red 366
histology 407
Hudson-Raritan Estuary 693
Humerus 682
Hypergeometric likelihood 464
Identification (fish eggs) 555
Incidental kill 233
Indeterminate 648
Indian River Lagoon 533
Intertidal 634
Istiophorus platypterus - see sailfish
Japan 14, 196
Jasus edwardsii - see lobster,
southern rock
Juvenile studies 25, 142, 264
menhaden 723
mortality 233
pollock 604
rockfish 453
shrimp 264, 376
snapper 366
Kuroshio-Oyashio 179
Lake 14
Larval
description 723
development 118, 723
rockfish 453
Lead210 711
Length
at age, chub mackerel 179
frequency, shark 156
Life history
model 1
seatrout. spotted 142
Line-transect survey 441, 563
Liparidae 245
Litopenaeus setiferus -see shrimp,
white
Lobster, southern rock 430
Loligo opalescens - see squid, market
Longevity ( rockfish ) 711
Longline fishery 179,393
Lutjanus
campechanus - see snapper, red
carponotatus - see bass, stripey
Mackerel
Atka 498, 509
chub 179, 196
Mammals 47,108, 213, 581, 563
Marginal increment analysis 156
Mark-recapture 78, 376
Marlin, white 750
Marine sanctuaries 464
Maturity
bass, stripey 94
rockfish, black 418
Maximum likelihood method 14
Mediterranean 407
Megaptera novaeangliae -see whale,
humpback
Menhaden
finescale 723
gulf 723
Mexico 47, 593
Microwire tags 376
Mid-water trawl survey 63
Migration
diel 221
from marine reserves 533
shark 221
vertical 221
Models
growth 14
habitat use 264
life history 1
optimal release 78
recruitment 349
Mortality 349
amberjack, greater 545
dolphin, pantropical spotted 233
lobster 430
longline fishery 179
seatrout, spotted 142
squid, market 306
Movement
shrimp 376
sportfish 533
MtDNA
rockfish 453
salmonids 213
Multidimensional scaling 36
Nantucket Shoals 289
National marine sanctuary 563
New South Wales 634
New species 245
New Zealand 441
North Carolina (flounder) 78
Northern California Current 25
Nursery habitat 366, 376
Octopus, maori 430
Octopus maorum - see octopus, maori
Oncorhynchus
kisutch - see salmon, coho 108
Opah 750
Orbital retia mirabilia 221
Orcinus orca - see whale, killer
Oregon 108,418
Otoliths
amberjack, greater 545
elemental signature in 604
in fecal samples 47, 108, 498, 522
rockfish 453
Ovalipes ocellatus - see crab, lady
Ovarian cycle 418
Oxytetracycline 127
Oyster, American 298
768
Fishery Bulletin 102(4)
Pacific Ocean 168, 233, 328, 733, 604,
733
Pagrus major - see sea bream, red
Pandalopsis clispar - see shrimp,
sidestriped
Paralichthys dentatus -see flounder,
summer
Paralithodes eamtschaticus -see crab,
red king
Parturition (rockfish) 418
PavlofBay 400
Penaeidae 376
Phoca vitulina richardsi - see seal,
harbor
Photo-identification (marine
mammals) 563
Pinnipeds 498, 509, 522
Phocoenoides dalli - see porpoise,
Dall's
Placopecten magellanicus - see sea
scallop
Pleurogrammus monopterygius - see
mackerel, Atka
Poikilotherm 682
Pollock, walleye 498, 509, 522, 604
Pontoporia blainvillei -see
franciscana
Pop-up satellite archival tags 221, 750
Population
dynamics 661
structure 604
Porgy, red 1
Porpoise, Dall's 563
Postovulatory follicle 473
Prey-size selectivity 509, 522
Protogynous 1
Prowfish 168
Psednos rossi - see snailfish
Purse-seine fishery 233
Radiometric age 711
Radium226 711
Rays 757
Recolonization (fish in rockpools) 634
Recovery 278
Recruitment
anchovy, bay 63
processes of 349
Reef habitat 298
Remote sensing 661
Remotely operated vehicle 389
Reproduction
bass, stripey 94
behavior 389
franciscana 581
prowfish 168
rockfish, black 418
seatrout, spotted 473
squid 389
tuna, bluefin 407
Residence time 376
Restoration
conch 278,
oyster 298
Rhabdosargus sarba — see seabream,
goldlined
Rio Grande do Sul 581
Rockfish
black 418
blackgill 711
dusky 328
pygmy 452
rockpools 634
ROV (remotely operated vehicle) 389
Sablefish 127
Sailfish 251
Salmon
coho 25
decline in Onchorynchus spp. 108
juvenile 25
predation on 108
prey of 213
Salmonids 25, 213
juvenile 25
Sampling bias 488
Sardine, Pacific 581, 617
Sardinops sagax - see sardine.
Pacific
Sargassum 545
Satellite
archival tags 750
remote sensing 661
Scale-free networks 349
Scat 47, 108, 213, 498, 522
Scomber japonicus - see mackerel,
chub
Scorpaenidae 711
SCUBA 366
Sea bream
goldined 648
red 555
Sea lion
California 47
Steller 498, 509, 522
Sea scallop 671
Sea surface temperature 179
Seal, harbor 108, 213
Seatrout, spotted 142, 473
Sebastes
ciliatus - see rockfish, dusky
melanops -see rockfish, black
melanostomus - see rockfish,
blackgill
variabilis - see rockfish, dusky
uilsoni - see rockfish, pygmy
Sea turtle
Kemp's ridley 682
leatherback 393
loggerhead 393,682
Seriola dumerili - see amberjack,
greater
Sex
change 1
ratio 693
Sexual maturity 418
Sharks
thresher, bigeye 221
night 156
predation 750
Shrimp
brown 264
sidestriped 118
white 376
Size-selective fisheries 1
Skeletochronology (sea turtles) 682
Snailfish 245
Snapper
red 366, 593
Spanish flag 93
Soak time (gear) 179
South Carolina 473
Sparidae 555,648
Spawning
anchovy, bay 63
bass, stripey 94
diel 389
frequency 473
seabream 648
season 418, 648
squid 306
stock biomass 63
tuna, bluefin 407
Species
protogynous 1
Squid 73
fishery 757
market 306,389,661
minimal armhook 733
SteneUa attenuata attenuata -see
dolphin, spotted, pantropical
Stock enhancement 78
Strombus gigas - see conch, queen
Surveys
dolphin 441,489
with fish traps 127
Survival rates 179, 757
Tagging 464, 750, 604
marine reserves 464, 533
natural 604
shark 221, 750
Taiwan 251
Temperate estuaries 693
Temperature
Effect on fish size I mackerel) 196
List of subjects
769
Testicular development 407
Tetrapturus albidus - see marlin,
white
Theragra chalcogramma - see pollock,
walleye
Thunnus thynnus - see tuna, bluefin
Translocation (for rehabilitation) 278
Traps 430
Trawl efficiency 740
Trophic niche breadth 693
Tuna, bluefin 407
Turtle - see sea turtle
Umpqua River 108, 213
Underwater video 740
Vertebral sections 156
Washington 563
Western North Atlantic 245
Whale
humpback 563
killer 563
Young-of-the-year (amberjack) 545
Zalophus californianus - see sea lion,
California
Zaprora silenus -see prowfish
770
Fishery Bulletin 102(4)
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Fishery Bulletin
Guidelines for contributors
Content of papers
Articles
Articles are reports of 10 to 30 pages (double
spaced) that describe original research in one or
a combination of the following fields of marine
science: taxonomy, biology, genetics, mathematics
(including modeling), statistics, engineering, eco-
nomics, and ecology.
Notes
Notes are reports of 5 to 10 pages without an
abstract that describe methods and results not
supported by a large body of data. Although all
contributions are subject to peer review, responsi-
bility for the contents of articles and notes rests
upon the authors and not upon the editor or the
publisher. It is therefore important that authors
consider the contents of their manuscripts care-
fully. Submission of an article is un-derstood to
imply that the article is original and is not being
considered for publication elsewhere. Manuscripts
must be written in English. Authors whose native
language is not English are strongly advised to
have their manuscripts checked for fluency by
English-speaking colleagues prior to submission.
Preparation of papers
Text
Title page should include authors' full names and
mailing addresses (street address required) and
the senior author's telephone, fax number, e-mail
address, as well as a list of key words to describe the
contents of the manuscript. Abstract must be less
than one typed page (double spaced) and must not
contain any citations. It should state the main scope
of the research but emphasize the author's con-
clusions and relevant findings. Because abstracts
are circulated by abstracting agencies, it is impor-
tant that they represent the research clearly and
concisely. General text must be typed in double-
spaced format. A brief introduction should state the
broad significance of the paper; the remainder of
the paper should be divided into the following sec-
tions: Materials and methods, Results, Discussion
(or Conclusions), and Acknowledgments. Headings
within each section must be short, reflect a logical
sequence, and follow the rules of multiple subdi-
vision (i.e. there can be no subdivision without at
least two subheadings). The entire text should be
intelligible to interdisciplinary readers; therefore,
all acronyms and abbreviations should be written
out and all lesser-known technical terms should be
defined the first time they are mentioned. The
scientific names of species must be written out the
first time they are mentioned; subsequent mention
of scientific names may be abbreviated. Follow Sci-
entific style and format: CBE manual for authors,
editors, and publishers (6th ed.) for editorial style
and the most current issue of the American Fish-
eries Society's common and scientific names of
fishes from the United States and Canada for
fish nomenclature. Dates should be written as fol-
lows: 11 November 1991. Measurements should be
expressed in metric units, e.g. metric tons (t). The
numeral one ( 1 ) should be typed as a one, not as a
lower-case el (1).
Footnotes
Use footnotes to add editorial comments regarding
claims made in the text and to document unpub-
lished works or works with local circulation. Foot-
notes should be numbered with Arabic numerals
and inserted in 10-point font at the bottom of the
first page on which they are cited. Footnotes should
be formatted in the same manner as citations.
If a manuscript is unpublished, in the process
of review, or if the information provided in the
footnote has been conveyed verbally, please state
this information as ''unpubl. data," "manuscript
in review," and "personal commun.," respectively.
Authors are advised wherever possible to avoid ref-
erences to nonstandard literature (unpublished lit-
erature that is difficult to obtain, such as internal
reports, processed reports, administrative reports,
ICES council minutes, IWC minutes or working
papers, any "research" or "working" documents,
laboratory reports, contract reports, and manu-
scripts in review). If these references are used,
please indicate whether they are available from
NTIS (National Technical Information Sendee) or
from some other public depository. Footnote format:
author (last name, followed by first-name initials);
year; title of report or manuscript; type of report
and its administrative or serial number; name and
address of agency or institution where the report is
filed.
Literature cited
The literature cited section comprises works that
have been published and those accepted for pub-
lication (works in press) in peer-reviewed jour-
nals and books. Follow the name and year system
for citation format. In the text, write "Smith and
Jones ( 1977 ) reported" but if the citation takes
the form of parenthetical matter, write "(Smith
and Jones, 1977)." In the literature cited section,
list citations alphabetically by last name of senior
author: For example, Alston, 1952; Mannly, 1988;
Smith, 1932; Smith, 1947; Stalinsky and Jones,
1985. Abbreviations of journals should conform
to the abbreviations given in the Serial sources
for the BIOSIS previews database. Authors are
responsible for the accuracy and completeness of
all illations. Literature citation format: author
(last name, followed by first-name initials); year;
title of report or article; abbreviated title of the
journal in which the article was published, volume
number, page numbers. For books, please provide
publisher, city, and state.
Tables
Tables should not be excessive in size and must be
cited in numerical order in the text. Headings in
tables should be short but ample enough to allow
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symbols must be explained in the table legend.
Other incidental comments may be footnoted (use
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asterisks only to indicate probability in statistical
data. Place table legends on the same page as the
table data. We accept tables saved in most spread-
sheet software programs (e.g. Microsoft Excel).
Please note the following:
• Use a comma in numbers of five digits or more
(e.g. 13,000 but 3000).
• Use zeros before all decimal points for values
less than one (e.g. 0.31).
Figures
Figures include line illustrations, computer-gener-
ated line graphs, and photographs (or slides). They
must be cited in numerical order in the text. Line
illustrations are best submitted as original draw-
ings. Computer-generated line graphs should be
printed on laser-quality paper. Photographs should
be submitted on glossy paper with good contrast.
All figures are to be labeled with senior author's
name and the number of the figure (e.g. Smith,
Fig. 4). Use Helvetica or Arial font to label ana-
tomical parts (line drawings) or variables (graphs)
within figures; use Times Roman bold font to label
the different, sections of a figure (e.g. A, B, C).
Figure legends should explain all symbols and
abbreviations seen within the figure and should be
typed in double-spaced format on a separate page
at the end of the manuscript. We advise authors to
peruse a recent issue of Fishery Bulletin for stan-
dard formats. Please note the following:
•Capitalize the first letter of the first word of
axis labels.
• Do not. use overly large font sizes to label axes
or parts within figures.
• Do not use boldface fonts within figures.
• Do not create outline rules around graphs.
• Do not use horizontal lines through graphs.
• Do not use large font sizes to label degrees of
longitude and latitude on maps.
• Indicate direction of degrees longitude and
latitude on maps (e.g. 170 El
• Avoid placing labels on a vertical plane
(except on y axis).
•Avoid odd (nonstandard) patterns to mark
sections of bar graphs and pie charts.
Copyright law
Fishery Bulletin . a U.S. government publication, is
not subject to copyright law. If an author wishes to
reproduce any part of Fishery Bulletin in his or her
work, he or she is obliged, however, to acknowledge
the source of the extracted literature.
Submission of papers
Send four printed copies (one original plus three
copies ) — clipped, not stapled — to the Scientific Edi-
tor, at the address shown below. Send photocopies
of figures with initial submission of manuscript.
Original figures will be requested later when the
manuscript has been accepted for publication.
Do not send your manuscript on diskette until
requested to do so.
Dr. Norman Bartoo
National Marine Fisheries Service, NOAA
8604 La Jolla Shores Drive
La Jolla, CA 92037
Once the manuscript has been accepted for publi-
cation, you will be asked to submit a software copy
of your manuscript. The software copy should be
submitted in WordPerfect or Word format (in
Word, save as Rich Text Format). Please note that
we do not accept ASCII text files. Color figures
must be CMYK files.
Reprints
Copies of published articles and notes are avail-
able free of charge to the senior author (50 copies)
and to his or her laboratory (50 copies). Additional
copies may be purchased in lots of 100 when the
author receives page proofs.
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