U.S. Department
of Commerce
Volume 103
Number 1
January 2005
Fishery
Bulletin
U.S. Department
of Commerce
Donald 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
^nT0Fc%
•^TES 0* *"
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U.S. Department
of Commerce
Seattle, Washington
Volume 103
Number 1
January 2005
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INMFS) does not approve, recommend, or
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Fishery
Bulletin
Contents
ftB 0 1 ttJ°5
Articles
1-14 Bochenek, Eleanor A., Eric N. Powell, Allison J. Bonner,
and Sarah E. Banta
An assessment of scup (Stenotomus chrysops) and black sea
bass (Centropristas striata) discards in the directed otter trawl
fisheries in the Mid-Atlantic Bight
15-22 Cooper, Daniel W., Katherine E. Pearson, and
Donald R. Gunderson
Fecundity of shortspine thornyhead (Sebastolobus alascanus)
and longspine thornyhead (5. altivelis) (Scorpaenidae) from
the northeastern Pacific Ocean, determined by stereological
and gravimetric techniques
23-33 DeMartini, Edward E., Marti L. McCracken,
Robert B. Moffitt, and Jerry A. Wetherall
Relative pleopod length as an indicator of size at
sexual maturity in slipper (.Scyllarides squammosus) and
spiny Hawaiian (Panu/irus marginatus) lobsters
34-51 Fisher, Joseph P., and William G. Pearcy
Seasonal changes in growth of coho salmon
(Oncorhynchus kisutch) off Oregon and Washington
and concurrent changes in the spacing of scale circuli
52-62 Groeneveld, Johan C, Jimmy P. Khanyile, and
David S. Schoeman
Escapement of the Cape rock lobster (Jasus lalandu) through
the mesh and entrance of commercial traps
63-70 Grusha, Donna S., and Mark R. Patterson
Quantification of drag and lift imposed by pop-up satellite
archival tags and estimation of the metabolic cost to cownose
rays (Rhinoptera bonasus)
71-83 Harvey, Chris J.
Effects of El Nino events on energy demand and
egg production of rockfish (Scorpaenidae: Sebastes).
a bioenergetics approach
Fishery Bulletin 103(1)
84—96 Horodysky, Andrij Z., and John E. Graves
Application of pop-up satellite archival tag technology to estimate postrelease survival of
white marhn (Tetrapturus a/bidus) caught on circle and straight-shank ("J") hooks in the
western North Atlantic recreational fishery
97—107 Kerr, Lisa A., Allen H. Andrews, Kristen Munk, Kenneth H. Coale, Brian R. Frantz,
Gregor M. Cailliet, and Thomas A. Brown
Age validation of quillback (Sebastes maliger) using bomb radiocarbon
108—129 Marancik, Katrin E., Lisa M. Clough, and Jonathan A. Hare
Cross-shelf and seasonal variation in larval fish assemblages on the southeast United States
continental shelf off the coast of Georgia
130-141 O'Farrell, Michael R., and Ralph J. Larson
Year-class formation in Pacific herring (Clupea pallasi) estimated from spawning-date distributions
of |uveniles in San Francisco Bay, California
142—152 Parker, Denise M., William J. Cooke, and George H. Balazs
Diet of oceanic loggerhead sea turtles (Caretta caretta) in the central North Pacific
153—160 Roberson, Nancy E., Daniel K. Kimura, Donald R. Gunderson, and Allen M. Shimada
Indirect validation of the age-reading method for Pacific cod (Gadus macrocephalus) using otoliths
from marked and recaptured fish
161—168 Sulikowski, James A., Jeff Kneebone, Scott Elzey, Joe Jurek, Patrick D. Danley, W. Huntting Howell,
and Paul C. W. Tsang
Age and growth estimates of the thorny skate (.Amb/yra/a radiata) in the western Gulf of Maine
169—182 Tracey, Sean R., and Jeremy M. Lyle
Age validation, growth modeling, and mortality estimates for striped trumpeter (Latrts lineata)
from southeastern Australia: making the most of patchy data
183—194 Trnski, Thomas, Amanda C. Hay, and D. Stewart Fielder
Larval development of estuary perch (Macquana co/onorum) and Australian bass (M. novemaculeata)
(Perciformes: Percichthyidae), and comments on their life history
195—206 Venerus, Leonardo A., Laura Machinandiarena, Martin D. Ehrlich, and Ana M. Parma
Early life history of the Argentine sandperch Pseudoperas semifasaata (Pinguipedidae)
off northern Patagonia
207-218 Wilson, Matthew T, Annette L. Brown, and Kathryn L. Mier
Geographic variation among age-0 walleye pollock (Theragra chalcogramma).
evidence of mesoscale variation in nursery quality?
Note
219-226 Markaida, Unai, Joshua J. C. Rosenthal, and William F. Gilly
Tagging studies on the |umbo squid (Dosidicus gigas) in the Gulf of California, Mexico
227 Subscription form
Abstract — This study was undertaken
to re-assess the level of scup iSten-
otomus ehrysops) discards by weight
and to evaluate the effect of various
codend mesh sizes on the level of
scup discards in the winter-trawl
scup fishery. Scup discards were high
in directed scup tows regardless of
codend mesh — typically one to five
times the weight of landings. The
weight of scup discards in the present
study did not differ significantly from
that recorded in scup-targeted tows
in the NMFS observer database. Most
discards were required as such by the
22.86 cm TL (total length) fish-size
limit for catches. Mesh sizes sl2.7 cm,
including the current legal mesh size
(11.43 cm) did not adequately filter
out scup smaller than 22.86 cm. The
median length of scup discards was
about 19.83 cm TL. Lowering the
legal size for scup from 22.86 to 19.83
cm TL would greatly reduce discard
mortality. Scup discards were a small
fraction (0.4%) of black sea bass (Cen-
tropristis striata) landings in black-
sea-bass-targeted tows. The black sea
bass fishery is currently regulated
under the small-mesh fishery gear-
restricted area plan in which fishing
is prohibited in some areas to reduce
scup mortality. Our study found no
evidence to support the efficacy of
this management approach. The
expectations that discarding would
increase disproportionately as the trip
limit (limit [in kilograms] on catch
for a species) was reached towards
the end of the trip and that discards
would increase when the trip limit
was reduced from 4536 kg to 454 kg
at the end of the directed fishing
season were not supported. Trip limits
did not significantly affect discard
mortality.
An assessment of scup (Stenotomus ehrysops)
and black sea bass iCentropristas striata)
discards in the directed otter trawl fisheries
in the Mid-Atlantic Bight
Eleanor A. Bochenek
Eric N. Powell
Allison J. Bonner
Sarah E. Banta
Haskm Shellfish Research Laboratory
Rutgers. The State University of New Jersey
6959 Miller Ave.
Port Norns, New Jersey 08349-3167
E-mail address (for E A Bochenek), bochenek@hsrl.rutgers.edu
Manuscript submitted 6 January 2003
to the Scientific Editor's Office.
Manuscript approved for publication
7 September by the Scientific Editor.
Fish. Bull. 103:1-14(2005).
Because of regulations, market fac-
tors, and other reasons, both com-
mercial and recreational fishermen
discard some of their catch. Discards
are considered one of the principal
sources of mortality for many fish
species, including those of significant
commercial and recreational fisheries
(Howell and Langdon, 1987; Glass et
al., 1999; Suuronen et al., 1996).
The Sustainable Fisheries Act
(SFA), governing U.S. fisheries man-
agement in federal waters, states
that "conservation and management
measures shall minimize bycatch."
Much has been written about the
environmental impact of discarding
(Mooney-Seus, 1999; Alverson, 1999;
Kennelly, 1999). Discard mortality
reduces population size by limiting
the number of individuals that can
reach maturity and spawn. Because
EEZ (Exclusive Economic Zone) fish-
eries must be managed at Bmsv (bio-
mass at maximum sustainable yield)
under SFA guidelines and discards
must be included in estimates of the
TAC (total allowable catch), discard
mortality also reduces total allowable
landings. Therefore, discarding is not
just an environmental problem; it is
a problem that affects all aspects of
fisheries.
A recreational and commercial
fishery for scup (Stenotomus ehrys-
ops) occurs in the Mid- Atlantic Bight
(the portion of the U.S. Atlantic coast
extending from Cape Hatteras to
Cape Cod) and New England regions
where scup are caught south and off-
shore in the winter and north and
inshore in the summer (NEFSC1). In
1996, the legal size for commercially
caught scup was raised to 22.86 cm
total length (TL), more or less coin-
cidently with the establishment of a
legal codend mesh size of 11.43 cm
to reduce discard mortality (MAFMC,
1996). Discarding is considered to be
an important cause of mortality for
this important commercial and rec-
reational species (NEFSC2). Kennelly
(1999) reported large amounts of scup
1 NEFSC (Northeast Fisheries Science
Center). 2002. SARC 35. 35th North-
east regional stock assessment workshop
(35th SAW). Stock assessment review
committee (SARC) consensus summary
of assessments. Northeast Fisheries
Science Center Reference Document 02-
14, 259 p. Northeast Fisheries Science
Center, NMFS, NOAA, 166 Water St.,
Woods Hole, MA 02543.
2 NEFSC (Northeast Fisheries Science
Center). 2000. SARC 31. 31st north-
east regional stock assessment workshop
(31stSAW). Stock assessment review com-
mittee (SARC) consensus summary of
assessments. Northeast Fisheries Sci-
ence Center Reference Document 00-15,
409 p. Northeast Fisheries Science
Center, NMFS, NOAA, 166 Water St.,
Woods Hole, MA 02543.
Fishery Bulletin 103(1)
discards from demersal trawlers operating in certain
areas and depths in the Mid-Atlantic Bight. High num-
bers of scup discards occur in the directed scup fishery
(Powell et al., 2004). It is generally believed that one of
the keys to effective management of scup is to reduce
discard mortality (NEFSC2; NEFSC1). Fisheries manag-
ers attempt to control discard mortality using a number
of management measures, but principally through mesh
regulations and time or area closures.
Analysis of NMFS observer data by Powell et al.3
indicated that scup comprised 65% of the total catch in
scup-targeted tows, but that the discards-to-landings
ratio for scup in these tows was 1.05. Somewhat more
than half of the scup taken in scup-targeted tows were
subsequently discarded. However, this analysis was
based on relatively few observations; many of the tows
used codends with mesh sizes below the current legal
mesh size of 11.43 cm. As a consequence, applicability
of the NMFS observer data to the present-day scup
fishery is unclear. The objective of the present study
was to obtain additional observations in the directed
scup fishery to re-assess the level of discards by weight
and to evaluate the effect of simple variations in codend
mesh size on the level of scup discards.
Data analysis focused on scup. However, we also ana-
lyzed black sea bass (Centropristis striata) catches using
the same methods as those for scup. Black sea bass
were included because one management option is to
require a common codend mesh size for the two spe-
cies. The present legal mesh size for black sea bass is
10.16 cm and the minimum size of black sea bass that
can be harvested is 27.94 cm TL. Commonality would
simplify fishing methods because the two species are
often targeted on the same trip.
Methods
Description of data
This study was undertaken during the 2001 winter scup
trawl fishery in the Mid-Atlantic Bight. The legal trip
limit for scup was 4536 kg from 1 January through 24
January. After 24 January until the close of the season
in late February, the legal trip limit for scup was lowered
to 454 kg. An experimental fishing permit was obtained
from NMFS 1) to allow the vessels to fish in the GRAs
(gear-restricted areas), implemented to reduce scup
discards in the Loligo squid, (Lollgo pealei), silver hake
(Merluccius bilinearis), and black sea bass fisheries, 2)
to allow the use of codends with meshes less than the
legal 11.43-cm mesh, and 3) to allow commercial vessels
to retain an additional 1361 kg of scup per trip to help
defray study costs.
The four vessels participating in this study used the
following codends: 1) the legal-size (11.43-cm) mesh co-
dend; 2) a composite codend with 30 meshes of 10.16-cm
mesh at the very end of the bag followed by 45 meshes
of 11.43-cm mesh; and 3) codends with some meshes
212.7 cm (including codends with or without a com-
posite design). Two tows with codends of smaller mesh
size (between 6.35 and 10.16 cm) were also observed
and these tows were included in data tabulations for
completeness. The composite codend was designed as a
mechanism to reduce large catches of small scup when
abundant scup are encountered but was also designed
to retain black sea bass and scup when abundance was
low. Captains usually had two of the codends onboard
the vessel during a fishing trip and were asked to fish
the codends in an ABBA sequence (i.e., first tow with
codend A, second tow with codend B, third tow with
codend B, next tow with codend A, and so forth). These
tows typically lasted no longer than one hour. Other-
wise, the captain operated his boat using normal fishing
practices, including selecting where and when to fish.
The catch from each tow was sorted to species and
weighed. Fork lengths (FL) were obtained for a mini-
mum of fifty scup discarded followed by a minimum of
fifty scup landed. If time permitted, length-frequency
information was collected for black sea bass and dis-
carded individuals were measured. Because some regu-
lations use TL, FL was converted when necessary to TL
with the following equation: TLtcm) = 1.14FL(cm) - 0.44
(Hamer4 in MAFMC [1996]).
Catch data obtained from this study of the winter
2001 scup fishery were compared to scup-targeted tows
from the NMFS observer database for 1997 through
mid-2000 (Powell et al.3). NMFS observer program
methodology is detailed in the Northeast Fisheries
Science Center Fisheries Observer Program Manual
(NEFSC5). Mesh size reported in the NMFS observer
database included an array of small-mesh codends less
than present-day legal size, as well as the legal mesh
size of 11.43 cm.
A depth was assigned for each tow as the mean of the
depths of net deployment and retrieval. Swept area of
the tow could not be calculated directly because door
or wing spread were not recorded by us, nor were these
metrics available in NMFS observed tows. A surrogate
for true swept area was obtained as "the average of
the recorded headrope and sweep lengths" multiplied
3 Powell, E. N., E. A. Bochenek, S. E. Banta, and A. J.
Bonner. 2000. Scup bycatch in the small-mesh fisher-
ies of the Mid-Atlantic. Final Report, National Fisheries
Institute Scientific Monitoring Committee, 74 p. Haskin
Shellfish Research Laboratory, Rutgers University, 6959
Miller Ave., Port Norris, NJ 08349.
4 Hamer, P. E. 1979. Studies of the scup, Stenotomus chrys-
ops, in the Middle Atlantic Bight. N.J. Div. Fish. Game and
Shellfish, misc. rep. no. 5M, 14 p. New Jersey Department
of Environmental Protection, New Jersey Division of Fish
and Wildlife, Division of Marine Fisheries, Nacote Creek
Research Station, PO Box 418, Port Republic, NJ 08241.
5 NEFSC (Northeast Fisheries Science Center). 2001. Fish-
eries observer program manual, 217 p. Northeast Fisheries
Science Center, NMFS, NOAA, 166 Water St., Woods Hole,
MA 02583.
Bochenek et al.: Assessment of Stenotomus chrysops and Centropnstas striata discards in the Mid-Atlantic Bight
by "the recorded tow time and speed." CPUE was then
calculated by using estimated swept area as the effort
term. Scope was calculated as "tow wire out" divided by
"average water depth." For geographic location, each tow
was assigned to a 10-minute square area (10-minute
latitude and longitude) (Powell et al.3).
For some analyses, data from the present study's
winter 2001 fishery and the NMFS observer database
were assigned to categories by codend mesh size: the
legal codend with 11.43-cm mesh; a composite codend
with 10.16-cm mesh followed by 11.43-cm mesh; codends
with meshes less than 6.35 cm; codends with meshes
between 6.35 cm and 10.16 cm; and codends having
some meshes greater than or equal to 12.7 cm. Gear
type was assigned to either a millionaire or large-mesh
box net based on the net styles used in our study and
interpretations of NMFS observer-recorded net descrip-
tions by knowledgeable fishermen.
Statistical analysis
Catch was evaluated by using the ratio of scup discards
to landings, total catch of all species, total discards of
all species, total scup discards, total scup landings, and
a comparison of whether the catch of scup per tow was
above or below the median for all tows in the study. In
addition, we examined the influence of fishing decisions
on discards 1) by distinguishing tows where scup dis-
cards exceeded scup landings from tows where landings
exceeded discards and 2) by distinguishing between the
scup catch of tows taken in the first and last half of
the trip. For the latter, we also analyzed tows by their
fractional position in the trip (whether a tow occurred at
the start of a trip, V4, V2, 3Ai, or at the end of the trip).
This approach yielded results equivalent to the simpler
assignment of tows to the first and last half of the trip.
Only the results of the simpler analysis are presented.
Finally, we evaluated the impact of fishing decisions on
the length frequencies of scup caught. ANOVAs were run
by using ranked raw variables with class variables that
defined fishing practice (mesh size, gear, scope, effort),
time, and catch. The variable time was used to allocate
tows to three categories:
1 Those trips from the present study taken from 1 to
24 January 2001 with a legal trip limit of 4536 kg
of scup;
2 Those trips from the present study taken after 24
January 2001, with a legal trip limit of 454 kg of
scup; and
3 Those scup trips taken in 1997-2000 from the NMFS
observer reports.
Length frequencies were analyzed by ANOVA by using
the 25th, 50th, and 75th percentiles and the mean as
descriptive variables. In initial analyses, the interaction
terms between mesh size or time and the other indepen-
dent variables were included. Interaction terms were not
significant more frequently than expected by chance and,
accordingly, were not included in our results. Significant
differences identified by the ANOVA were further inves-
tigated by using Tukey's studentized range test and, for
covariates, by Spearman's rank correlation.
Results
Catch statistics — scup
Ten trips were taken during our study and 62 tows were
successfully completed; 39 tows targeted scup and 12
tows targeted black sea bass (Table 1). For the remaining
tows, the captain targeted Loligo squid as part of the
normal fishing process and used a much smaller codend
mesh size. These LoZ/go-targeted tows were excluded
from further analyses. However, frequent changes in
target species emphasize the need for tow rather than
trip-aggregated data in discard analyses (Powell et al.,
2004) because multiple targets within trips commonly
occur in Mid-Atlantic Bight fisheries.
The majority of tows were taken in NMFS statistical
area 622. Scup-targeted tows occurred primarily dur-
ing daylight and at depths ranging from about 73.2 to
137.2 m in our study and from 54.9 to 109.7 m in the
NMFS observer data set. A few tows from both the NMFS
observer database and our study were deleted from the
analysis because the catch was released overboard rather
than brought onboard. Bycatch estimates from these
tows were assumed to be inaccurate in comparison to
other tows. This phenomenon occurs sporadically in many
fisheries (e.g., Roel et al., 2000). In our study, six scup-
targeted tows were disregarded for this reason. All four
participating boats had at least one trip where one tow
was released overboard. Observers reported that the
net was so full of fish, primarily scup, in these tows
that it could not be brought on deck. The catch for one
black-sea-bass-targeted tow was released overboard. In
addition, tows in which no discards were recorded were
not analyzed. Generally, such tows occurred when the
observer was asleep or sea conditions were too danger-
ous to collect data from the tow. Such tows did not occur
in our study but did occur sporadically in the NMFS
observer database. Regardless of the reason, we assumed
that any tow without recorded discards represented in-
complete sampling and, consequently, we discarded that
tow from further analysis (Powell et al.3). Differences in
the tabulated number of observed tows and the number
of observed tows analyzed reflect the number of tows
excluded from the analyses for these two reasons.
Length frequency — scup
The length frequencies of landings and discards were
consistently significantly different (often PsO.0001)
(Fig. 1). The mean size of discarded scup was 17.7 cm
and ranged from 13.2 to 21.4 cm in our study. Fifty
percent of the scup discarded fell between 16.8 cm (25th
percentile) and 18.5 cm (75th percentile). In contrast,
the average size of scup landed was 24.2 cm and ranged
from 22.2 to 29.2 cm. Fifty percent of the scup landed
Fishery Bulletin 103(1)
30-i
1 Lande
Discarded
d
This study
Mean
30-
100 1
Percentile
NMFS observer data
Mean
Figure 1
Mean length-frequency fractions for scup (Stenotomus chrysops) discarded and landed in our study
and in the NMFS observer database. l = smallest size. 100 = largest size.
Table 1
Synopsis of
scup
and black-sea-bass-
-targeted tows by study, gear, and codend
mesh size, including
those tows where the catch
was released overboard.
Scup
-targeted tows
6.35-10.16 cm
11.43-cm
10.16+11.43 cm
Study
Gear
mesh
mesh
composite
>12.7cm
Totals
This study
Millionaire net
2
3
0
0
5
Large box net
0
14
19
7
40
Totals
2
17
19
7
45
<6.35-cm
6.35-10.16 cm
11.43-cm
Study
Gear
mesh
mesh
mesh
Unknown
Totals
NMFS
Millionaire net
9
5
3
0
17
Large box bet
5
4
2
7
18
Totals
14
9
5
7
35
Black-sea
bass-targeted tows
6.35-10.16 cm
11.43-cm
10.16+11.43 cm
Study
Gear
mesh
mesh
composite
Totals
This study
Millionaire net
0
0
0
0
Large box net
0
3
9
12
Totals
0
3
9
12
<6.35-cm
6.35-10.16 cm
11.43-cm
Study
Gear
mesh
mesh
mesh
L'nknown
Totals
NMFS
Millionaire net
0
0
0
0
0
Large box net
0
6
0
0
6
Totals
0
6
0
0
6
Bochenek et al.: Assessment of Stenotomus chrysops and Centropnstas striata discards in the Mid-Atlantic Bight
fell between 22.9 cm (25th percentile) and 25.0 cm (75th
percentile). For the NMFS observer data, the mean size
of scup discards was 17.2 cm and ranged from 13.6 to
20.6 cm. Fifty percent of the scup discarded fell between
16.2 cm (25th percentile) and 18.2 cm (75th percentile).
For scup landed, the mean size was 22.8 cm and ranged
from 19.4 to 28.9 cm. Fifty percent of the scup landed
fell between 21.3 cm (25th percentile) and 23.8 cm (75th
percentile).
Codend and gear
Vessels participating in this study and in the NMFS
observer program used either millionaire or box nets
(Table 1). More tows were made with the box net in both
data sets (Table 1). Most tows in our study were made
with the composite and 11.43-cm codends because com-
parison of these two codends was one focus of our study.
Most scup-targeted tows in the NMFS observer database
were made with codends <10.16 cm mesh (Table 1).
Codend mesh size did not have a significant effect
on catch length frequencies when data from our study
and the NMFS observer data were analyzed separately
or combined. We deleted codends with the smallest
meshes (meshes slO.16 cm) and re-analyzed the data
for the remaining larger codend meshes. Again, catch
length frequencies were not significantly different for
any of the codend mesh sizes. Finally, we considered
the landed and discarded scup separately. For landings,
codend mesh size had a moderately significant effect on
median length (P=0.0220) and a stronger significant
effect on mean length (P=0.0062). Codends with some
meshes 212.7 cm caught more of the landed size fraction
than the composite and slightly more than the 11.43-cm
mesh codend; however, the actual difference in mean
length between the three mesh-size groups was small,
approximately one cm (Fig. 2).
The efficiency of the codend may change with the
amount of fish caught such that selectivity declines with
high catches. Accordingly, scup catches were divided
into two groups: those above and those below the me-
dian catch for all tows. For catches above the median,
codend mesh size had a significant effect (P=0.0441)
on the 25th percentile of size for scup discarded in our
study. The 25th percentile size was largest for codends
with some meshes ^12.7 cm and smallest for the com-
posite codend. For landed scup, the 25th percentile sizes
were about 22.0 cm regardless of codend mesh size. No
significant differences existed between codend mesh
sizes for scup length frequency in tows with catches
below the median.
We examined the composition of the catch by weight.
Codend mesh size had a limited effect on the ratio
of scup discarded to landed, the total catch and to-
tal discards of all species, and total scup landed and
discarded. Scup discards were greater with codends
having some meshes 212.7 cm (P=0.0211). More scup
were landed from these tows as well (P=0.0034) and
therefore this codend style may contribute to a greater
catch rate (Table 2). Very likely, this trend in increased
I Landed, Composite
1 Landed 11.43 cm
jnik'ii > \11 tin
Figure 2
Mean scup {Stenotomus chrysops) length fractions
for those tows with landed scup with a composite
(10.16 + 11.43 cm) codend, 11.43-cm mesh codend, and
a sl2.7-cm mesh codend. l = smallest size. 100 = larg-
est size.
catch is produced by the small number of tows (n=l) in
this mesh size category rather than a real improvement
in net performance.
No significant gear effects existed for any of the
length-frequency fractions in the combined data set (our
study and NMFS observer study). The only significant
effect of scope (P= 0.0175) was on total scup discarded
in our study. This effect was not present in the NMFS
observer data set.
Discards-to-landings ratio
Of the 62 tows completed in our study, 39 targeted scup.
The NMFS observer program, from 1997-mid 2000,
included 35 scup-targeted tows (Table 3). Overall, mean
catch per tow for scup-targeted tows was 972.6 kg in
our study and 945.3 kg for NMFS observed tows. In
our study, the discards-to-landings ratio for all species
combined ranged from 1.77 with the composite codend to
2.91 with a codend with some meshes al2.7 cm. In the
NMFS observer data set, the discards-to-landings ratio
for all species combined in scup-targeted tows ranged
from 0.47 with codends having meshes of 6.35-10.16 cm
to 3.43 with codends with meshes of 11.43 cm (Table 2).
The mean discards-to-landings ratio for scup ranged
from 1.1 for the NMFS database to 2.4 for our study
(Table 3). Ratios varied from a low of 0.35 to a high of
5.72 among the various gear and mesh-size combina-
tions (Table 4).
We analyzed cases where scup discards exceeded or
were less than landings. When our data and the NMFS
observer data were combined, the 25th (P=0.0219), 50th
Fishery Bulletin 103(1)
Table 2
Mean weight (in kilograms) of scup discarded, scup landed, total discards of all species, total catch of all species
cards-to-landings ratio of all species per tow by codend mesh size for this study and the NMFS observer data.
and total dis-
Scup
Scup
Total
Total
Total discards-
Total number
Study
Codend
discarded
landed
discards
catch
to-landings ratio
of tows
This study
Composite
659.7
329.3
1078.1
1686.0
1.77
16
This study
11.43 cm
607.8
210.7
1060.2
1437.7
2.81
14
This study
al2.70 cm
1020.7
404.9
1973.4
2652.8
2.91
7
NMFS
<6.35 cm
615.5
493.4
949.1
1530.1
1.63
14
NMFS
6.35-10.16 cm
230.5
510.5
321.1
999.2
0.47
9
NMFS
11.43 cm
535.2
260.0
1015.7
1311.6
3.43
5
This study
NMFS
Table 3
Mean catch and landings per tow for scup and black sea bass-targeted tows.
Scup
Study
Tow type
Total no.
of tows
Mean catch
(kg)
Mean
landed (kg)
Mean
discarded (kg)
Ratio of scup discards
to landings
This study
NMFS
Target
Target
39
35
972.6
945.3
286.3
461.3
686.3
484.0
2.40
1.05
Black sea bass
Study
Tow type
Total no.
of tows
Mean catch
(kg)
Mean
landed (kg)
Mean
discarded (kg)
Ratio of black sea bass
discards to landings
Target
Target
10
6
365.0
171.9
278.7
170.1
86.3
1.8
0.31
0.01
(P=0.0085), and 75th (P=0.0038) percentile sizes and
the mean length (P= 0.0001) were significantly lower for
tows in which most scup were discarded (Fig. 3). When
the data sets were analyzed separately, our study found
that the 50th (P=0.0133) and 75th (P=0.0040) percentile
sizes and the mean length (P= 0.0338) were significantly
lower for tows where discards exceeded landings. Not
surprisingly, when fishermen caught larger scup, fewer
scup were discarded. In the NMFS observer data set,
no significant size effects were found for any of the
percentile fractions.
When the discards and landings were analyzed sepa-
rately, the lengths of fish discarded did not differ be-
tween tows for which discards exceeded landings and
tows for which landings exceeded discards. However, for
the landed fish, the 50th (P=0.0034) and 75th (P=0.0018)
percentile sizes and the mean length (P=0.0033) were
larger for tows where landings exceeded discards
(Fig. 4). Discards decline when larger scup are propor-
tionately more abundant in the catch.
We examined the influence of total catch (all species
combined) on the length-frequencies of scup in tows
where scup landings exceeded or did not exceed scup
discards. For those tows with total catches below the
median catch, a significant effect was noted for the
median (P=0.0039), the 75th percentile (P=0.0006),
and the mean (P=0.0288) length of scup. In those tows
where total catch weight was relatively low, the median,
mean, and 75th percentile lengths were larger in tows
where scup landings exceeded discards. No significant
effects on the length-frequency distribution of scup were
observed for total catches that were above the median.
The analysis identifies a strong trend towards the land-
ing of larger-size scup in tows yielding total catches
below the median for all tows.
Both landings and discards were affected in those
tows in which total catch fell below the median. For
landed scup, the median (P= 0.0062), the 75th percentile
(P=0.0051), and the mean (P=0.0113) length were higher
in tows with total catches below the median when scup
landings exceeded discards. For those scup that were
discarded from tows with total catches below the me-
dian, a significant size effect was observed for the 75th
percentile (P=0.0265). Discarded scup were larger in
Bochenek et al.: Assessment of Stenotomus chrysops and Centropnstas striata discards in the Mid-Atlantic Bight
Table 4
Synopsis of catch and landings data (kg) by study,
the NMFS observer database.
gear, and codend mesh size
for scup-targeted tows
in our study and those in
dear
Mesh size
Total
scup/tow
Scup
landed
Scup
discarded
Ratio of scup
discards to landings
Number
of tows
This study
Large box
10.16+11.43 cm composite
1332.3
519.3
813.0
1.57
9
11.43 cm
1572.8
431.6
1141.2
2.64
5
al2.70 cm
2609.7
624.1
1985.6
3.18
2
Millionaire
6.35-10.16 cm
32.7
16.3
16.3
1.00
1
10.16+11.43 cm composite
547.5
85.0
462.5
5.44
7
11.43 cm
399.5
88.1
311.5
3.54
9
212.70 cm
951.9
317.2
634.8
2.00
5
Unknown
636.8
94.8
542.0
5.72
1
NMFS
Large box
<6.35 cm
1076.7
196.0
880.8
4.49
5
6.35-10.16 cm
20.8
3.4
17.4
5.12
4
11.4.3 cm
176.9
131.5
45.4
0.35
2
Unknown
988.2
477.6
510.6
1.07
7
Millionaire
<6.35 cm
1126.6
658.6
468.1
0.71
9
6.35-10.16cm
1317.1
916.2
401.0
0.44
5
11.43 cm
1207.3
345.5
861.8
2.49
3
Table 5
Total discards and total catch of all fish species (in kg) and scup discarded and landed (in
by having more or less discards of scup than the median catch per tow.
kg) for only those tows characterized
Study More or less discards
Scup discarded
Scup landed
Total discards
Total catch Total number of tows
This study Less
This study More
NMFS Less
NMFS More
145.4
898.9
235.1
815.9
355.6
259.0
521.1
381.5
565.4
1451.6
426.3
1242.8
1027.5 11
1982.3 28
1058.3 20
1761.5 15
these tows, reflecting the overall larger size of the scup
catch in tows where total catch was relatively low.
Finally, for tows in which scup discards exceeded
landings, total catch of all species and total discards of
all species were also high. This trend was significant
for total catch (P=0.0273) and total discards (P=0.0038)
in our study (Table 5) and for total discards (P= 0.0017)
and total catch (P=0.0112) in the NMFS observer data
set (Table 5). Therefore, scup discards tended to increase
with respect to landings as total catch increased.
Time and effort
For our study, effort significantly affected the 25th
(P=0.0247) and 50th (P=0.0466) percentiles of the size-
frequency distribution of discards. The size frequencies
for landings were not similarly affected. In both former
cases, the 25th and 50th percentile sizes were larger when
effort was less (shorter tows). No significant effects were
observed in the NMFS observer data set. Because the
length frequency of the entire catch did not change sig-
nificantly, this is likely an effect of processing onboard
the boat.
Given trip limits, one might anticipate discards to
increase in tows made at the end of the trip. We ex-
amined the amount of scup caught either in the first
half of the tows or in the last half of the tows on each
trip. For this study, more scup were landed (P= 0.0008)
and discarded (P=0.0001) in tows that occurred during
the last half of the trip. Total catch and total discards
were unaffected. For the NMFS observer data set, more
scup were landed (P=0.0001) and discarded (P=0.0001)
Fishery Bulletin 103(1)
£ 25-
20
10
25 Mean 50 75 100
Discarded
1 25
Mean 50
Percentile
75 100
1 M
landed, less disc.
□ m.
landed, more disc.
□ N
landed, less disc.
n^
landed, more disc.
■
M. discarded, less disc.
□
M discarded, more disc
□
N, discarded, less disc.
□
N. discarded, more disc.
Figure 3
Percentiles of scup {Stenotomus chrysops) length frequency for those tows in which
discards exceeded or failed to exceed landings for landed and discarded scup. "M"
represents this study and "N" represents NMFS observer data. Landed, less disc.
= for scup landed, tows with less discarded scup than landed scup. Discarded, less
disc. = for scup discarded, tows with less discarded scup than landed scup. Landed,
more disc. = for scup landed, tows with more discards of scup than landed scup.
Discarded, more disc. = for scup discarded, tows with more discards of scup than
landed scup. l = smallest size. 100=largest size.
and the total catch of all species (P=0.0195) and total
discards of all species (P= 0.0004) were higher in tows
taken during the last half of the trip (Table 6). More
scup being landed and discarded in the last half of the
trip indicates that captains learn where to fish for scup
during the trip and CPUE rises as a consequence. No
evidence exists that discards increased with respect to
landings during the trip.
We anticipated that reduction of the trip limit from
4536 kg to 454 kg on 24 January would influence
the total weight of discards. Time did influence total
weight of scup discards (P=0.0056) in our study. More
discards per tow occurred on trips taken prior to 24
January, likely because of the larger trip limit (weight
limit per species for each trip) for the 1-24 January
period. With a larger trip limit, more scup can be
caught per tow and therefore more scup will be dis-
carded. The discards-to-landings ratio, however, was
not significantly affected — indicating that captains
controlled total scup catch in proportion to the land-
ing limit.
The present study versus the NMFS observer study
We compared trends in our data with those in the NMFS
observer data. The subset of directed scup tows in the
two data sets rarely disagreed, despite the disparity in
codend mesh sizes reported (Table 1).
Bochenek et ai.: Assessment of Stenotomus chrysops and Centropnstas striata discards in the Mid-Atlantic Bight
Landed
Landed, less ihs^
D
Landed, more disc
25 Mean 50 75 100
Discarded
o 25
I Discarded, less disc.
I Discarded, more disc.
Figure 4
Percentiles of scup {Stenotomus chrysops) lengths (FL) for those tows in which
discards exceeded or failed to exceed landings for landed and discarded scup.
Codends included the composite (10.16 + 11.43 cm), 11.43 cm, and &12.7 cm
meshes. Landed, less disc. = for scup landed, tows with less discarded scup
than landed scup. Discarded, less disc. = for scup discarded, tows with less
discarded scup than landed scup. Landed, more disc. = for scup landed, tows
with more discards of scup than landed scup. Discard, more disc. = for scup
discarded, tows with more discards of scup than landed scup. l = smallest
size. 100 = largest size.
Table 6
Mean weight (in kg) of scup discarded and landed and the total of all fish
tows in the first half of the trip and the second half of the trip.
species landed and discarded per tow for
scup-targeted
Study
First half or
second half of trip
Scup discarded
Scup landed
Total discards
Total catch
Total number
of tows
This study
First
253.3
125.2
970.2
1279.7
22
This study
Second
1246.8
494.7
1501.2
2273.8
17
NMFS
First
43.2
23.2
463.0
670.3
19
NMFS
Second
1007.5
981.5
1148.3
2178.3
16
10
Fishery Bulletin 103(1)
Table 7
Mean weight (in kg) of black sea bass discarded, black sea bass landed, total discards of all species, total catch of all species, and
total discards-to-landings ratio of all species per tow by codend mesh size and gear for this study and the NMFS observer data.
Study
Gear
Codend
Black
sea bass
discarded
Black
sea bass
landed
Total
discards
Total
catch
Total
discards to
landings
Ratio of
Total number
of tows
This study
Large box
10.16+11.43 cm
composite
119.2
366.7
845.6
1306.9
1.83
7
This study
Large box
11.43 cm
5.0
25.9
1201.8
1250.3
24.78
2
This study
Millionaire
11.43 cm
18.6
168.3
368.1
683.8
1.17
1
NMFS
Large box
6.35-10.16 cm
1.8
170.1
23.7
224.2
0.12
6
Catch statistics — black sea bass
During the winter scup season, black sea bass are legally
caught with 10.16-cm mesh codends in offshore waters.
A boat captain often will target scup and black sea bass
on the same trip, but will use different mesh codends. A
total of 12 black-sea-bass-targeted tows were observed
in our study and 6 black-sea-bass-targeted tows were
documented in the NMFS observer data set (Table 1).
Length frequency — black sea bass
Black sea bass length-frequency distributions were
highly significantly different (often P=0.0001) between
those fish landed and those discarded. The mean size of
discarded black sea bass from our study was 22.9 cm and
ranged from 18.4 to 25.4 cm. Fifty percent of the black
sea bass discarded fell between 22.1 cm (25th percentile)
and 24.3 cm (75th percentile). In contrast, the mean size
of landed black sea bass was 31.1 cm and ranged from
25.4 to 40.9 cm. For black sea bass landed, fifty percent
of the fish were found between 28.6 cm (25th percentile)
and 33.3 cm (75th percentile). For the NMFS observer
data, the mean size of black sea bass discarded was 23.4
cm and ranged from 20.7 to 27.0 cm. Fifty percent of
the black sea bass discarded fell between 22.3 cm (25th
percentile) and 24.7 cm (75th percentile). The mean size
of landed black sea bass was 28.5 cm and ranged from
24.5 to 34.0 cm. For landed black sea bass, fifty percent
fell between 25.0 cm (25th percentile) and 31.5 cm (75th
percentile).
Codend and gear
Nine tows were made with the composite codend and
three tows were made with the 11.43-cm legal mesh
codend in our study. For the NMFS observer data, all
six targeted tows fell into the 6.35-10.16 cm mesh-size
group that included the legal mesh size of 10.16 cm
(Table 1).
We found no significant effects of codend mesh size
on the percentile length-frequency fractions of black
sea bass. We considered landed and discarded black sea
bass separately for those tows with total catches above
and below the median and, once again, no significant
codend mesh-size effects were observed. The total num-
ber of tows, however, was small. A significant codend
mesh-size effect (P=0.0389) was observed for black sea
bass landed. Landings were higher with the larger
mesh codends (composite 10.16+11.43 cm codend and
the 11.43-cm codend) rather than with the sl0.16-cm
mesh codend (Table 7). The small number of total tows
with the larger codend mesh sizes (10.16+11.43 cm and
the 11.43 cm) is probably responsible for this difference
in landings rather than differences in net performance.
Gear effects (net types) were not determined because
only the box net was used.
Discards-to-landings ratio
Total mean catch per tow was 365 kg and total mean
landings per tow was 279 kg for the 10 tows in our study.
For the six directed tows in the NMFS observer data,
average total catch was 172 kg and average total land-
ings were 170 kg (Table 3). In black-sea-bass-targeted
tows, the black sea bass catch comprised 34.2% of the
total catch. The discards-to-landings ratio for black sea
bass was 0.230. Relatively few black sea bass were dis-
carded. Scup comprised 0.9% of the total catch in black
sea bass targeted tows. Less than one percent (0.4%)
of the scup catch in black-sea-bass-targeted tows was
discarded.
We analyzed cases where black sea bass discards ex-
ceeded or were less than landings in tows where total
catch (all species combined) was above or below the me-
dian. For total catches above the median, a significant
size effect was noted for the median length (P=0.0040),
the 75th percentile size (P= 0.0007), and the mean length
(P= 0.0026). Larger fish were present in tows where dis-
carding was lower (Fig. 5). No significant effects on the
size distribution of black sea bass were observed in tows
with total catches below the median. We further divided
the catches above the median into discards and land-
ings. For those black sea bass that were landed from
tows with total catches above the median, a significant
size effect was observed for the 25th (P=0.0199), the
Bochenek et al.: Assessment of Stenotomus chrysops and Centropnstas striata discards in the Mid-Atlantic Bight
Landed
I Landed, less disc.
I anded, more disc
Discarded
I Discarded, less disc.
Discarded, more disc
I 25 Mean 50
Percentile
Figure 5
Percentiles of black sea bass (Centropristas striata) length frequencies for those
tows in which discards of black sea bass exceeded or failed to exceed landings for
landed or discarded black sea bass. Landed, less disc. = for black sea bass landed,
tows with less discards of black sea bass than what was landed. Discarded, less
disc. = for black sea bass discarded, tows with less discards of black sea bass
than what was landed. Landed, more disc: for black sea bass landed, tows with
more discards of black sea bass than what was landed. Discarded, more disc. =
for black sea bass discarded, tows with more discards of black sea bass than
what was landed. l = smallest size. 100 = largest size.
50th (P=0.0280), and the 75th (P=0.0090) percentile size
fractions and the mean length (P=0.0133). The size of
landed black sea bass was larger in tows where discard-
ing was low (Fig. 5).
Time and effort
Because of trip limits, discards could increase in tows
taken near the end of a trip. Therefore, we compared the
catch of black sea bass in the first and the last half of
the tows. The quantity caught and the length-frequency
percentiles were not significantly different between the
first and last half of the tows. In contrast, for scup trips,
discards and landings tended to be higher in tows made
in the last half of the trip.
Effort significantly affected the 25th (P=0.0010), 50th
(P= 0.0003), and 75th percentile (P= 0.0153) size fractions
of black sea bass for the combined data sets (NMFS
study and our study). In these cases, higher effort was
associated with more smaller fish. When the two data
sets were analyzed independently, most of the effort
effects were no longer present.
12
Fishery Bulletin 103(1)
Discussion
Scup
The type of net (gear) and the size of codend mesh had
only a minor effect on the length frequencies of scup
caught. Although variations in codend mesh size nor-
mally influence catch in other studies (Hastie, 1996;
Petrakis and Stergiou, 1997; Stergiou et al., 1997; Broad-
hurst et al., 1999), a wide range in codend mesh sizes
produced similar results for scup. Codends with some
meshes al2.7 cm appeared to catch more of the size
classes of fish chosen for landing than the composite
codend and just slightly more than the legal 11.43-cm
mesh codend; therefore the al2.7-cm mesh condend may
reduce discards. The actual difference in scup lengths
between the three codends was only about one cm. In
terms of kilograms caught, more scup were caught in
tows with the larger codend mesh. Landings increased,
but so did discards, so that the discards-to-landings ratio
remained unchanged. This finding indicates that the
small upward bias in sizes caught did not significantly
reduce total catch. In general, the smaller mesh codends
(6.35-10.16 cm) and the composite codend (10.16+11.43
cm) performed similarly to the current legal mesh design
(11.43 cm). Overall, discards of scup remained high
regardless of the type of gear (nets) and codends used.
In our study, more larger scup were caught in longer
tows. When a boat encounters a large school of scup,
the mean length of the catch tended to be smaller. In
addition, the larger-size scup tended to be caught more
often in those tows with total catches below the me-
dian. This trend is probably a biological effect, but an
effect of mesh size or gear cannot be excluded. Most
populations contain relatively few larger fish and, there-
fore, more smaller individuals. Morse6 (in Steimle et
al., 1999) noted that scup schools are size-structured.
When larger scup are less common in schools, then
schools with these larger individuals most likely would
be smaller and more effort would be required to achieve
the same catch of these individuals. The same result
would occur if larger scup tended to be on the outside
or above smaller scup in schools. Little is known about
scup behavior. However, any spatial size structure in
the population could promote a direct relationship be-
tween effort and the mean length of fish caught and an
inverse relationship between total catch (all species)
and mean length of fish caught.
As an alternative explanation for the lower catch rate
of larger individuals, clogging of the codend may occur
when catch rates are high and, as a consequence, size-
selectivity would decline. Different codend mesh sizes
do not seem to affect the number of discarded scup as
much as one might anticipate because codends clog dur-
6 Morse, W. W. 1978. Biological and fisheries data on scup,
Stenotomus chrysops (Linnaeus). NMFS, NEFSC, Sandy
Hook Lab. tech. ser. rep. no. 12, 41 p. James J. Howard
Marine Sciences Laboratory, Northeast Fisheries Science
Center, 74 Magruder Rd., Sandy Hook, NJ 07732.
ing the interception of large schools. Accordingly, lower
CPUE could produce greater size selectivity resulting in
increased mean length when catches are relatively low.
However, the trends observed in length frequency with
effort and total catch were not significantly influenced
by codend mesh size. Accordingly, the observed trend is
likely a direct consequence of fishing on size-structured
populations.
In general, more scup were landed and discarded in
the last half of a trip. This finding indicates that the
captain learns where to fish for scup by the second half
of the trip and CPUE increases as a consequence. We
had expected an increase in discards as the trip limit
was reached towards the end of the trip. However, no
effect of trip limits on the total weight of discards could
be discerned in our data set or the NMFS observer
data set.
More scup were discarded per tow in tows observed
during the first half of the 2001 season, namely 1-24
January, than in the second half of the season, 25
January-February, but the discards-to-landings ratio
did not vary for either half of the season. The fact that
the ratio did not differ indicates that more scup are
discarded per tow when fishermen are allowed a larger
trip limit (4536 kg). The higher discards of scup per tow
during the first half of the season are likely due to the
increased total catch per tow that might be anticipated
when allowable landings are higher. Accordingly, cap-
tains are able to reduce catch rate and, thus, discards
when landing limits are low.
We compared the NMFS observer database to our
observer data. Despite a substantial variation in the
distribution of codend mesh sizes between the two data
sets, the discards-to-landings ratio was not significantly
different. Concerns raised by the high discards-to-land-
ings ratio observed in the NMFS observer data were
supported by our study. The discards-to-landings ratio
for the directed scup fishery consistently exceeded 1.0.
In summary, the objective of our study was to evalu-
ate the effect of codend mesh size on the amount of scup
discards and to identify mechanisms to reduce scup
discards. Although we observed a number of trends in
discards in our study, neither the current legal mesh
nor any of the experimental codends seem to adequately
filter out scup smaller than 22.86 cm. Neither did trip
limits seem to influence the total weight of scup dis-
cards. In fact, the only consistent trends produced by
variations in effort and total catch seem most likely
due to biological effects not easily controlled for by the
captain of a fish vessel. Overall, the total weight of dis-
cards seems to be primarily a function of the regulated
size limit, abetted by the tendency for smaller fish to be
captured when encounter rates are high. The present
study found that the length of the median discards was
about 17.78 cm FL (19.83 cm TL based upon a conver-
sion factor of Hamer4 [in MAFMC, 1996]). O'Brien et
al. (1993) and NEFSC (1993) reported that 50% of both
male and female scup reach maturity at 15.49 cm FL
(17.27 cm TL). Therefore, lowering the scup minimum
size limit to 17.78 cm FL (19.83 cm TL) would greatly
Bochenek et al .: Assessment of Stenotomus chrysops and Centropnstas striata discards in the Mid-Atlantic Bight
13
reduce scup discards, yet permit the majority of scup
to attain sexual maturity. Kilograms discarded might
be reduced by more than half. Fishermen would reach
their trip limit sooner and thus stop fishing earlier.
As a result, fishing mortality rate even on larger scup
would be reduced. This single change would reduce
discards more than any change in net or codend design
tested to date and would not result in any increase in
fishing-induced mortality for scup.
the percentage in scup-targeted tows. This finding indi-
cates that there is considerable discrimination between
the two species at the level of the fishery. The black sea
bass fishery is currently regulated under the small-
mesh fishery GRA plan in which fishing is prohibited in
some areas to reduce scup mortality. This investigation
finds no evidence to support the efficacy of this manage-
ment approach. Scup discards do not appear to be an
important attribute of the black sea bass fishery.
Black sea bass
Estimates of discards of black sea bass are low in
the black-sea-bass-targeted fishery, based on the few
observed tows in our study and data from the NMFS
observer database. Regardless of which codends were
used, the same size fractions of black sea bass were
caught. The composite codend (10.16+11.43 cm mesh)
caught more black sea bass than were landed. Discards
was also higher. As with scup, mesh size and gear type
had minor effects on the size frequency, the discards-
to-landings ratio, and the kilograms of black sea bass
caught. The majority of tows where black sea bass were
caught had ratios of black sea bass discarded to landed of
less than 0.3, indicating that few discards occur in this
fishery. In contrast, most of the scup tows were charac-
terized by discards-to-landings ratios greater than one.
The differences in discards-to-landings ratios between
black sea bass and scup may be due to a combination of
biological factors controlling the average size of scup in
the larger schools and to regulatory factors that do not
match well with the size range of scup in schools.
Unlike scup, black sea bass size frequencies and total
weight caught were similar in tows taken during the
first and last half of the trip. Trip limits are in effect
for both black sea bass and scup. The difference between
the two species in the distribution of catch through the
time course of the trip may be the result of biological
effects in that the schooling of scup would tend to pro-
duce higher catches during the middle or latter part of
the trip as the captain finds schools of fish.
Powell et al.3 showed that black sea bass and scup are
caught simultaneously more frequently than expected
by chance in tows in the Atlantic mackerel (Sco?nber
sco?nbrus), Loligo squid, scup, and silver hake fisheries
and suggested that they should be regulated together.
Our analysis also showed this pattern in that the two
species were frequently caught in the same tows (39
out of 40 scup-targeted tows and seven out of 10 black-
sea-bass-targeted tows caught both scup and black sea
bass). In addition, Shepherd and Terceiro (1994), Musick
et al., (1985), and Musick and Mercer (1977) also found
that both scup and black sea bass were caught in the
same tow. Use of a common codend mesh size regulation
for both fisheries may prove useful. The failure to find
significant differences between mesh sizes suggests that
the 10.16+11.43 cm composite bag might be a reasonable
choice for both fisheries. However, scup discards were a
small fraction of black sea bass landings in black-sea-
bass-targeted tows (0.4%) — very small in comparison to
Conclusions
Because fishermen catch both scup and black sea bass
in the same tow and because the current regulations
require fishermen to use an 11.43-cm mesh codend when
targeting scup, and, a 10.16-cm mesh codend when tar-
geting black sea bass, two different codend mesh sizes
are used on the same trip. The composite codend was
designed to retain the smaller black sea bass catches
and some scup when catch rates are low but permits
more scup to escape at higher catch rates. The composite
codend (10.16+11.43 cm mesh) performed as well as the
other codends used in our study, including the 11.43-cm
legal-size codend. The composite codend with 10.16-cm
mesh followed by the 11.43-cm or 12.7-cm mesh codends
should be further evaluated on both black sea bass
and scup-directed tows. If this composite codend works
equally as well as the legal 11.43-cm mesh codend cur-
rently in place for scup (and the data presented here sug-
gest that it does), consideration should be given to using
this codend because it permits the retention of smaller
black sea bass without negatively influencing scup. This
change would eliminate the need to carry two codends
onboard and thus would reduce overall trip costs without
impacting the number of scup discards. However, neither
codend successfully addresses the need to significantly
reduce scup discarding in the scup-directed fishery.
Codends with some 12.7-cm meshes tended to reduce
discards by reducing the catchability of smaller scup,
but the trends were often not significant, possibly due
to the small sample size, but possibly also because nets
were clogged by schools of smaller-size scup. The data
indicate that further studies with 12.7-cm or greater
mesh composites may identify codend configurations
that will produce fewer discards. DeAlteris and La
Valley (1999) have documented that scup can survive
capture in a trawl net and subsequent escapement.
Therefore, optimizing codend mesh size could reduce
discard mortality.
Larger scup were caught in tows where the total catch
weight was low. Large catches tended to accompany the
interception of scup schools. These large catches can
clog the nets and thus reduce size selection even at
larger mesh sizes. Alternatively, larger scup may not
be associated with smaller scup in schools. We cannot
discriminate between the two explanations. Regard-
less of the reason, the tendency of the largest catches
to contain proportionately more smaller fish will likely
minimize the positive influence of net management in
14
Fishery Bulletin 103(1)
reducing scup discards. Rather, the tendency of the
largest catches to contain proportionately more smaller
fish suggests that fisheries managers may want to lower
the legal-size limit for scup from 22.86 cm to 17.78
cm FL. The median size of scup discards in our study
was 17.78 cm FL. Setting the size limit at 17.78 cm FL
(19.83 cm TL) would greatly reduce discards and thus
overall discard mortality. This management change
would likely have a much greater effect in reducing
scup discards than any other single management mea-
sure directed at gear modification or area closure and
would not endanger the stock (most discarded scup fail
to survive); thus, any approach significantly reducing
discards must significantly increase overall survival of
the population.
Acknowledgments
We would like to thank the National Fisheries Institute,
Scientific Monitoring Committee, for providing support
for this project. We also thank the captain and crew
for the use of the four commercial fishing vessels from
Cape May that cooperated in the project. Without their
assistance, this project would not have been possible.
We also thank NMFS-NEFSC for providing the NMFS
observer data used in our analysis.
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15
Abstract — Fecundity was estimated
for shortspine thornyhead (Sebas-
toiobus alascanus) and longspine
thornyhead (S. altivelis) from the
northeastern Pacific Ocean. Fecun-
dity was not significantly different
between shortspine thornyhead off
Alaska and the West Coast of the
United States and is described by
0.0544 xFL3978, where FL=fish fork
length (cm). Fecundity was esti-
mated for longspine thornyhead off
the West Coast of the United States
and is described by 0.8890 xFL3249.
Contrary to expectations for batch
spawners, fecundity estimates for
each species were not lower for fish
collected during the spawning season
compared to those collected prior to
the spawning season. Stereological
and gravimetric fecundity estimation
techniques for shortspine thornyhead
provided similar results. The stereo-
logical method enabled the estimation
of fecundity for samples collected ear-
lier in ovarian development; however
it could not be used for fecundity esti-
mation in larger fish.
Fecundity of shortspine thornyhead
(Sebastoiobus alascanus) and longspine
thornyhead (5. altivelis) (Scorpaenidae)
from the northeastern Pacific Ocean, determined
by stereological and gravimetric techniques*
Daniel W. Cooper
Katherine E. Pearson
Donald R. Gunderson
School of Aquatic and Fishery Sciences
University of Washington
1122 NE Boat Street
Seattle, Washington 98105
Present address (for D W Cooper, contact author): Alaska Fisheries Science Center, F/AKC2
7600 Sand Point Way NE
Seattle, Washington 98115-0700.
E-mail address (for D W Cooper) dan.cooper@noaa.gov
Manuscript submitted 15 July 2003 to
the Scientific Editor's Office.
Manuscript approved for publication
20 September 2003 by the Scientific Editor.
Fish. Bull. 103:15-22 12005).
Shortspine thornyhead {Sebastoiobus
alascanus) is distributed from the
Bering Sea to Baja California (Orr et
al., 2000). Longspine thornyhead (S.
altivelis) is distributed from the Gulf
of Alaska to Baja California (Orr et
al., 2000), and a few specimens have
recently been collected in the eastern
Bering Sea (Hoff and Britt, 2003).
Both species are commercially impor-
tant (Piner and Methot, 2001; Gaichas
and Ianelli, 2003) and inhabit deep
waters over the continental shelf and
slope. Both shortspine and longspine
thornyhead are determinate spawn-
ers (Wakefield, 1990; Pearson and
Gunderson, 2003), and spawn pelagic,
gelatinous egg masses (Pearcy, 1962;
Best, 1964; Wakefield, 1990; Wake-
field and Smith, 1990). Shortspine
thornyhead spawn between April and
July in Alaska, and between Decem-
ber and May along the West Coast of
the United States, whereas longspine
spawn between January and April
along the West Coast (Pearson and
Gunderson, 2003).
Annual fecundity is used as a mea-
sure of reproductive output in fishery
population models and life history
studies. Accurate annual fecundity
estimates require identifying oocytes
to be spawned in the current spawn-
ing season. For iteroparous spawn-
ers, developing oocytes are often
distinguished from reserve oocytes
by diameter or yolk presence (Macer,
1974). Collection date for samples is
important. If samples are collected
too early in oocyte development, some
developing oocytes will be indistin-
guishable from reserve oocytes, and
fecundity will be underestimated.
In shortspine thornyhead, oo-
cyte stages 4-8 are maturing to be
spawned in the current spawning sea-
son, whereas oocyte stages 1-3 are
reserve oocytes to be spawned in fu-
ture spawning seasons (Pearson and
Gunderson, 2003). Early vitellogenic
oocytes (stage 4) overlap in size with
late perinucleus (stage 3) reserve oo-
cytes (Pearson and Gunderson, 2003).
Late vitellogenic oocytes (stage 5) are
easily distinguished from reserve oo-
cytes. In whole oocytes, neither oo-
cyte size nor appearance can be relied
on to distinguish stage-3 and early
stage-4 oocytes; however stage-3 and
stage-4 oocytes can be visually dis-
tinguished from histological samples
(Pearson and Gunderson, 2003). Em-
erson et al. (1990) developed a stereo-
logical method to estimate fecundity
: Contribution 929 from the Joint Insti-
tute for the Study of the Atmosphere
and Ocean (JISAO), 4909 25th Ave NE,
Seattle, WA.
16
Fishery Bulletin 103(1)
from histological sections. Unlike gravimetric methods
(e.g., Hunter et al., 1992) where whole oocytes are used
to estimate fecundity, stereological methods do not rely
on oocyte diameter or other proxies for vitellogenesis. A
collection of shortspine thornyhead ovaries from Alas-
ka contained few specimens considered suitable for a
gravimetric fecundity method because too few of the
specimens contained all developing oocytes in stage 5
or beyond. However, enough samples were suitable for
the stereological method.
This study provides a fecundity estimate based on
stereological and gravimetric techniques for shortspine
thornyhead off Alaska. Benefits and limitations of the
stereological method in this case are discussed. A gravi-
metric technique is also used to estimate fecundity for
longspine thornyhead and shortspine thornyhead from
samples off the West Coast of the United States. In
addition, we examine the hypothesis that thornyheads
are batch spawners, and that fecundity consequently
declines over the course of the spawning season (Wake-
field, 1990).
Materials and methods
Ovaries were collected from a large geographic area
in Alaska, including the Gulf of Alaska, the Aleutian
Islands, and the Bering Sea. National Marine Fisheries
Service (NMFS) observers aboard commercial fishing
vessels collected ovaries from April through June 2000.
Length and somatic weight (ovaries and stomach con-
tents removed) (±5 g) were recorded at sea. Ovaries were
excised and placed in 10% formalin solution buffered
with sodium bicarbonate.
Ovaries from shortspine thornyhead and longspine
thornyhead were also collected during the 1999 NMFS
West Coast trawl survey. Samples were collected be-
tween Northern California and Washington (34°57'N lat.
121°33'W long, to 48°04' lat. 125°58'W long.). Length
and somatic weight (±2 g) were recorded at sea.
Additional West Coast longspine and shortspine
thornyhead ovaries were collected from commercial
fishing vessels by the Oregon Department of Fish and
Wildlife in Astoria. Ovaries were collected off Oregon
and Washington from February through May 2000,
during December 2000, and during January 2001. Af-
ter shipment to the NMFS Alaska Fisheries Science
Center in Seattle, length, somatic weight (±2 g), and
ovary weight (±0.001 g) were recorded. Ovaries were
excised and placed in 10% formalin buffered with so-
dium bicarbonate.
A cross section was removed from one ovarian lobe
(middle or middle posterior region) for histological pro-
cessing. When a whole cross section was too large to fit
on a microscope slide, a wedge was cut from the cross
section that included both the ovarian wall and the
center of the ovary. Samples were processed through
a dehydration series, embedded in paraffin, and sec-
tioned at 4 um. Slides were stained with hematoxylin
and eosin.
Gravimetric fecundity estimation
Histological ovary sections were examined at 100 x mag-
nification to select samples for the gravimetric method.
Oocytes were identified to one of eight developmental
stages as described by Pearson and Gunderson (2003).
To differentiate between oocytes to be spawned in the
current year and reserve oocytes for future years, only
ovaries with all maturing oocytes in stage-5 (late vitel-
logenesis) and beyond were used. By definition, yolk fills
more than 50% of the cytoplasm within stage-5 oocytes,
and the dark yolk made it easy to distinguish these
oocytes. Stage-4 oocytes would also be spawned in the
current year but overlapped significantly in size with
nonmature stage-3 oocytes, and early stage-4 oocytes
did not always have enough yolk (0-50%) to differentiate
them from stage-3 oocytes with the gravimetric method.
Specimens containing any stage-4 oocytes were omitted
as a result. Ovaries with stage-8 oocytes were also omit-
ted because the increased amount of gelatinous material
which surrounds the oocytes in Sebastolobus could not
be contained within the ovaries during subsampling.
Ovaries were weighed (±0.001 g) after they had been
stored in formalin. Subsamples were cut from the ova-
ries and weighed (±0.001 g). For smaller ovaries, an
entire cross section was taken. For larger ovaries, a
pie-piece-shaped wedge was cut from the cross section
to ensure a representative sample of outer ovarian wall.
When cut correctly, a wedge starting at the center of
the cross section would have the same weight ratio of
ovarian wall to wedge subsample as the original cross
section. Subsamples usually contained approximately
1000 oocytes (mean=1133), but this number varied ac-
cording to stage of development and the amount of ge-
latinous material in the ovary (range: 108-3711).
Gelatinous material could not be subsampled by cut-
ting at room temperature; therefore ovaries were briefly
frozen before subsampling. This procedure enabled the
gelatinous material to be cut, and also made it easier to
obtain a representative sample of the ovarian wall. Ini-
tially, parts of three ovaries were frozen, and no effects
of the freezing were detected with a light microscope.
Only samples for gravimetric fecundity estimates were
briefly frozen.
No difference in oocyte density was found among
the different regions of the ovaries (see "Results" sec-
tion); however, gravimetric subsamples were still taken
randomly along the length of the ovaries to minimize
potential bias from any location.
The oocytes in the subsamples were counted under a
stereomicroscope, and fecundity was estimated by
W
Fec = —N,
w
where Fee = estimated fecundity;
W = total ovary weight;
w = subsample weight; and
n = number of oocytes in the subsample.
Cooper et al.: Fecundity of Sebastolobus alascanus and Sebastolobus altivelis
17
Stereological fecundity estimation
The majority of oocytes within an ovary were found to
be at the same developmental stage; however develop-
ment was not completely synchronous. Some ovaries
containing stage-5 and -6 oocytes (late vitellogenesis
to migratory nucleus) also contained a few stage-4
oocytes, which although unsuitable for fecundity esti-
mation with the gravimetric method, could be used
with the stereological method described by Emerson et
al. (1990). Fecundity was estimated from ten of these
samples by using the stereological method to complete
the shortspine thornyhead collection from Alaska.
Fecundity was estimated per unit of volume and
then multiplied by the volume of both ovaries. The
formula used to estimate fecundity per unit of vol-
" PV?'
where N = the number of oocytes per unit of
volume;
k = an oocyte size correction coefficient;
/3 = an oocyte shape correction coefficient;
N„ = the average number of vitellogenic
oocytes per unit of area; and
V = the average fractional volume of vitel-
logenic oocytes per unit of area.
The method for estimating the parameter k is given in
Emerson et al. (1990) and the parameter k was estimated
for six shortspine thornyhead samples. The resulting k
values had a small range (1.0088-1.022), and a small
standard deviation (0.0066), and a mean k value of 1.017
was used for all samples as a result, ft was calculated
by using the method given in Weibel and Gomez (1962).
The ft parameter was calculated from one shortspine
thornyhead sample (53 oocytes) to be 1.565.
Exact volume of sample ovaries was impossible to
determine because portions of the ovaries had already
been removed for histological study (Pearson and
Gunderson, 2003). Volume was estimated by dividing
whole ovary weight by an average density of 1.052 g/
mL. This was the average density from six samples
(SD = 0.0297) estimated by water displacement in a
graduated cylinder.
Values for Na and V, were estimated by using a sim-
plified Weibel grid for particulate structures (Weibel
et al., 1966) instead of a Weibel multipurpose grid. A
square containing 13 rows of 13 points was created
and printed out on a clear acetate sheet. This overlay
was taped to the front of a monitor. A video camera
mounted to a stereomicroscope sent the image of the
histology section to the computer monitor. The num-
ber of vitellogenic oocytes per grid and the number of
points falling on vitellogenic oocytes were recorded and
used to estimate Na and V,, respectively. The Weibel
grid was used at 25x magnification, and 50x magnifica-
NV
V
0.5 cm
Figure 1
Partial cross section of shortspine thornyhead rockfish
{Sebastolobus alascanus) ovary showing bands of vitel-
logenic (V) and nonvitellogenic (NV) oocytes.
tion was used to help distinguish borderline vitellogenic
oocytes.
A sampling grid was placed under the ovary histologi-
cal section. The corner of the Weibel grid was aligned
with corners of the sampling grid in order to systemati-
cally sample the ovary cross section. Two histological
sections were sampled per ovary.
The number of Weibel grid counts per ovary depended
on the size of the ovary cross section. An average of
55.9 (range: 29-103) Weibel grid counts were taken per
ovary. This number was greater than the average num-
ber of Weibel grid counts used by Emerson et al. (1990),
but the extra counts were made because shortspine
thornyhead vitellogenic oocytes develop on peduncles
(Erickson and Pikitch, 1993; Pearson and Gunderson
2003) and are distributed in a band around the central
part of the ovary (Fig. 1). Because the vitellogenic oo-
cytes are not uniformly distributed, the Weibel grid was
applied systematically at more points across the entire
ovary, and the counts were averaged. Because the whole
cross section could not be systematically sampled and
averaged, cross sections of larger fish were not used for
stereological estimates.
Statistical methods
Length-fecundity relationships were estimated by using
the following equation:
Fee = alb,
18
Fishery Bulletin 103(1)
Table 1
""ecundity estimates (number of oocytes) by ovary
location and method.
Species
Stereological
method
Gravimetric method
Sample locatior
in ovary
Sample location
in ovary
Mid
Posterior
Anterior
CV
Mid
Posterior
Anterior
CV
Shortspine
122,180
87,504
111,758
0,166
131,934
110,456
111,425
0.103
Shortspine
313,131
257,378
304,348
0.103
269.453
230,992
257,427
0.078
Shortspine
184,802
199,572
203,014
0.049
Shortspine
474,432
458,877
0.024
Longspine
38,061
26,179
28,424
0.204
38,968
33,207
33,653
0.091
Longspine
36,152
23,127
19,411
0.335
Mean CV
0.147
Mean CV
0.091
where Fee = estimated fecundity;
I = fork length; and
parameters a and b were estimated by nonlinear regres-
sion with SPSS software (version 11.0, SPSS Inc., Chi-
cago, ID.
Weight-fecundity relationships were estimated by using
the following equation
Fee = mWsomatic) + bl,
where Fee = estimated fecundity;
Wtsomallc = somatic weight; and
m and 61 were estimated by using linear regression in
EXCEL (Microsoft, Redmond, WA).
Reduction in variance F tests (Quinn and Deriso,
1999) were used to compare fecundity relationships
between areas, studies, and before and during spawn-
ing season.
the gravimetric versus stereological estimates showed
that they follow a 1:1 trend line (Fig. 2). The gravimet-
ric method gave a somewhat lower coefficient of varia-
tion than the stereological method, based on multiple
samples of the same ovaries (Table 1). An F test (Quinn
and Deriso, 1999) did not show a significant difference
(P=0.84) between the gravimetric (n=16) and stereologi-
cal (??=10) methods in the length-fecundity relationships
obtained for Alaskan shortspine thornyhead, and the
data were therefore combined (Fig. 3).
Shortspine thornyhead
Shortspine thornyheads from Alaska (/!=26) and the
West Coast (n = 30) had similar fecundity at length
(Fig. 3). An F test did not indicate fecundity at length
for the two areas was significantly different (P=0.53);
therefore the data were combined to obtain the relation-
ships (Figs. 3 and 4):
Fee = 0.0544(Fork Lengthicm ))
(r2 = 0.792, 7i=56)
Results
Ovary location differences
We tested for difference in oocyte density between
middle, posterior, and anterior sections of six ovary
pairs with the stereological method (ovaries from the
migratory nucleus to late hydration phase) and did not
find a significant difference in ovary location (two-way
ANOVA, P=0.148) (Table 1).
Stereological method versus gravimetric method
The gravimetric method and the stereological method
provided similar results. For shortspine thornyhead, the
average ratio of gravimetric to stereological estimates
for ten pairs of data was 0.993 (Table 2), and a plot of
Fee = 0.223(Wtsomatic(g))- 63.079 (r2 = 0.781, n=53).
A majority of the shortspine thornyhead fecundity at
length data points obtained in this study fell below the
regression line reported by Miller (1985) (Fig. 3). The
raw data from Miller (1985) were not published; there-
fore no statistical test was possible.
The data were also separated into months preced-
ing the start of spawning and those after the start
of spawning (Pearson and Gunderson, 2003) to look
for evidence of batch spawning. Shortspine collected
between October and November were grouped as speci-
mens before the start of spawning. Shortspine collected
from April through June in Alaska and from March
through May off the West Coast were grouped as speci-
mens after the start of spawning. Fish collected after
spawning had begun (/;=41) did not show a significant
Cooper et al.: Fecundity of Sebastolobus alascanus and Sebastolobus altivelis
19
Table 2
Paired fecundity estimates (number of oocytes) by method and by section of the ovary (middle, posterior, anterior) where oocyte
samples were taken.
Specimen
Shortspine 1
Shortspine 2
Shortspine 3
Shortspine 4
Shortspine 5
Shortspine 6
Position in the ovary Gravimetric Stereological Ratio of gravimetric to stereological
Middle
Middle
Middle
Middle
Middle
Posterior
Anterior
Middle
Posterior
Anterior
150,448
195,356
427,717
414,594
131,934
110,456
111,425
269,453
230,992
257,427
184,853
187,037
307,771
561,258
122,180
87,504
111,758
313,131
257,378
304,348
O.K14
1.044
1.390
0.739
1.080
1.262
0.997
0.861
0.897
0.846
Mean ratio 0.993
w 600 i
tt)
♦
to
.E 500 •
w en
CD CD
& 0 400 '
/^
1 o
yS
3 W
g -D 300 ■
O/^ ♦
"~ ra
♦X^
ra «
Jr
y g 200 ■
♦/♦
o
**▼
£ 100 ■
S^
a>
S^
W
0 100 200 300 400 500
Gravimetric fecundity estimates
(thousands of eggs)
Figure 2
Plot of gravimetric versus stereological fecundity
estimates for ten shortspine thornyhead rockfish
[Sebastolobus alascanus) data pairs. Line = 1:1
ratio.
2500
2000 ■
£ 1500-
1000 ■
O West Coast
x Alaska gravimetric
• Alaska stereological
Combined data regression
- - • Miller (1985) regression (r>=60) 0 *J
500
20 40 60
Fork length (cm)
Figure 3
Shortspine thornyhead {Sebastolobus alascanus)
fecundity-at-length estimates by location and method,
and regression of combined data (our study) and by
regression of data from Miller's study (1985).
decrease in fecundity at length when compared to fish
collected before spawning had begun (n = ll) (F test,
P=0.71) (Fig. 5).
Longspine thornyhead
Longspine thornyhead fecundity data conformed more
closely to a linear regression on somatic weight (Fig. 6):
Fee = 183.8l(Wt8omatic(g))- 4617 (/-2 = 0.536, n=29)
than to a nonlinear regression on length (Fig. 7):
Fee = 0.889Q(Fork Length(cm))
(r2=0.442, n=29).
A majority of the predicted fecundity values at somatic
weight were higher than those derived from Wakefield's
(1990) regression line on somatic weight (Fig. 6), but
Wakefield's (1990) raw data were not published.
Wakefield (1990) estimated spawning to begin in Feb-
ruary and created separate fecundity-at-weight relation-
ships for fish collected in October-November and in
February-March). He noted a decline in fecundity as
the spawning season progressed but did not test this
fecundity difference for statistical significance. Similar
groupings (October-December, n = \l; and February-
March, n=ll) in our study did show a statistically sig-
nificant difference in fecundity as the spawning sea-
son progressed (F test, P=0.004) (Fig. 7); however, the
20
Fishery Bulletin 103(1)
2500
2000 ■
£ 1500
1000
500
Alaska and West Coast combined
Linear regression
(Alaska and West ♦
Coast combined)
0 2000 4000 6000
Somatic weight (g)
8000
Figure 4
Fecundity at somatic weight for combined Alaska
and West Coast shortspine thornyhead rockfish
iSebastolobus alascanus).
90 -
♦ West Coast (this study)
"w 80 -
Wakefield (1990) Oct- Nov (n=11)
a 70 -
co
Wakefield (1990) Feb- Mar (n=22)
o 60 -
In 50 -
CD
§f 40-
° 30-
CD
| 20-
♦
Z 10 -
♦ *i>^^ ♦
0 100 200 300 400
Somatic weight (g)
Figure 6
West Coast longspine thornyhead rockfish iSebas-
tolobus altivelis) fecundity data at somatic weight
lour study*, compared to fecundity data of Wake-
field (1990).
2500 -
♦ Oct - Nov
to
I 2000 -
to
3
Oct - Nov regression
Mar - Jun
o
§. 1 500 -
— — - Mar - Jun regression '
to
® 1000 -
o
♦ ,'
CD
E 500 -
3
z
^
0 20 40 60 80
Fork length (cm)
Figure 5
Shortspine thornyhead rockfish (Sebastolobus
alascanus) fecundity at length separated by
October-November and March-June collection
dates.
90 -
♦ Oct - Dec
"w 80 i
ID
Oct - Dec regression
ra 70 -
cn
Feb - Mar ,'
o 60 -
sz
w 50-
O. 40
o 30
® on
E
=i 10 ■
z
— — Feb - Mar regression ,'
♦ /
-L
♦ ♦/'
0 J
1
0 10 20 30 40
Fork length (cm)
Figure 7
Longspine thornyhead rockfish {Sebastolo-
bus altivelis) fecundity at length separated by
October-December and February-March collec-
tion dates.
regression lines intersected, and the February-March
group was not lower than the October-December group.
The February-March group did have lower fecundity
than the October-December group for lengths smaller
than 27 cm; however the sample size was very small. No
significant difference existed between the two groups
when the single, large fecundity observation late in the
spawning season was ignored (P=0.34).
Discussion
Emerson et al. (1990) cited the ability to distinguish
borderline vitellogenic oocytes from nonvitellogenic
oocytes as an advantage of the stereological method, and
this was a clear benefit in our study. The stereological
method allowed us to differentiate between vitellogenic
and nonvitellogenic oocytes at an earlier stage of ovary
development than was possible with the gravimetric
method. However, the use of ovaries in earlier stages of
development increases the potential magnitude of fecun-
dity overestimates due to atresia. Atresia, or the resorp-
tion of oocytes, is a potential source of error for fecundity
estimates (Hunter et al., 1992). Although atretic oocytes
can be identified with the stereological method, oocytes
that are destined for atresia will be counted, causing
fecundity to be overestimated. The amount of atresia will
determine the magnitude of this overestimate. Samples
Cooper et al.: Fecundity of Sebastolobus alascanus and Sebastolobus altivelis
21
collected at later ovarian development stages would avoid
this potential error (Tuene et al., 2002).
Because of a nonrandom distribution of vitellogenic
and nonvitellogenic oocytes in the ovary, it was neces-
sary to average Weibel grid counts over an entire ovary
cross section. Larger ovaries that did not fit on a single
slide could not be used, so that fecundity of larger fish
had to be determined with the gravimetric method. This
was a major limitation because few fish greater than 60
cm had ovaries small enough to be suitable for the ste-
reological method. This limitation, however, might not
apply to fish species with vitellogenic oocytes randomly
distributed throughout the ovary.
The number of Weibel grid counts required was larger
in our study than in Emerson et al. (1990), and the extra
counts increased the amount of time involved with com-
putation of fecundity estimates. In addition to the time
required to prepare histological sections, the time to
obtain stereological estimates took approximately twice
as long as those obtained with the gravimetric method.
Our estimates of shortspine thornyhead fecundity at
length (Fig. 3) appeared lower than the regression pub-
lished by Miller (1985), but our longspine thornyhead
fecundity estimates were higher than those published by
Wakefield (1990) (Fig. 6). Several potential explanations
exist for the differences. Temporal or geographic differ-
ences in fecundity could exist. Samples from different
decades were used in the two studies, and Wakefield
(1990) used longspine samples taken from off Point
Sur, California, whereas we used samples collected off
Oregon and Washington. However, the differences may
also be explained by methodological differences between
authors, including different criteria to include oocytes
in fecundity estimates, and differences in the ovarian
development of samples. Relatively small sample sizes
from our study and from Wakefield (1990) may add un-
certainty to these fecundity estimates. The length range
of samples could also affect comparisons for shortspine
thornyhead fecundity. The fecundity estimates from
Miller (1985) did not include any fish greater than 60
cm, whereas we used fish approaching 80 cm.
Wakefield (1990) grouped fecundity data by date,
that is to say before the start of spawning and after
the start of spawning. His data indicated a decline in
fecundity after spawning begins, which he attributed
to batch spawning. Similar temporal groupings in our
study did not necessarily show a decrease in fecundity
that was indicative of batch spawning in longspine or
shortspine thornyhead. An important caveat regarding
these comparisons is that the combination of small
sample sizes and high variability in fecundity at length
would cause only large differences in fecundity to be
detected. However, the sample sizes used for compari-
son before and during spawning season (shortspine
thornyhead n=ll, 41) (longspine thornyhead n = 17,ll)
were close to the sample sizes Wakefield (1990) used as
evidence for batch spawning (rc=ll,22). Larger sample
sizes for both species would help answer the question
of whether these are batch-spawning species. Pearson
and Gunderson (2003) did not find any hydrated oocytes
or postovulatory follicles co-occurring with vitellogenic
oocytes in histological sections of either species used in
our study. They concluded that batch spawning does not
occur from off Northern California to Alaska for short-
spine thornyhead, and from off Northern California to
Washington for longspine thornyhead, and the results
of the present study support this conclusion.
Ovaries are often opportunistically collected dur-
ing commercial fishing seasons or scheduled fisheries
surveys and may not provide oocyte samples from the
optimum time of year for estimating fecundity with
gravimetric techniques. Nevertheless, the stereological
technique enabled us to make fecundity estimates for a
greater number of the available samples. The technique
could be used in similar instances where the logistics
of sampling require collections to be made earlier than
the optimal date for gravimetric estimates.
Acknowledgments
Dave Douglas of the Oregon Department of Fish and
Wildlife collected many samples, as did numerous NMFS
RACE and REFM division scientists and the following
NMFS observers: C. Colway, A. Hayward, W. Mitchell,
E. White, N. Spang, K. Redslob, M. Waters, and D. Tran.
We thank Frank Morado, Lisa Appesland, and Dan
Nichol of the NMFS Alaska Fisheries Science Center
(AFSC) for use of equipment and equipment instruc-
tion. We also thank Marcus Duke of the UW SAFS for
creating a Weibel grid. Jim Ianelli and Rebecca Reuter
of the NMFS Alaska Fisheries Science Center provided
quantitative assistance. Cathy Schwartz of the UW
SAFS assisted with the figures and tables. We thank
two anonymous reviewers for providing useful comments.
This research was supported by the Joint Institute for
the Study of the Atmosphere and Ocean (JISAO) under
NOAA cooperative agreement no. NA17RJ1232.
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Pearson, K. E„ and D. R. Gunderson.
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2001. Stock assessment and fishery evaluation report
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of the United States 2001. In Status of the Pacific
coast groundfish fishery through 2001 and acceptable
biological catches for 2002. Pacific Fishery Manage-
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23
Abstract — Body size at gonadal matu-
rity is described for females of the slip-
per lobster (Scyllarides squammosus)
(Scyllaridae) and the endemic Hawaiian
spiny lobster (Panulirus marginatus)
(Palinuridae) based on microscopic ex-
amination of histological preparations of
ovaries. These data are used to validate
several morphological metrics (relative
exopodite length, ovigerous condition)
of functional sexual maturity. Relative
exopodite length ("pleopod length"! pro-
duced consistent estimates of size at
maturity when evaluated with a newly
derived statistical application for esti-
mating size at the morphometric matu-
ration point IMMP) for the population,
identified as the midpoint of a sigmoid
function spanning the estimated bound-
aries of overlap between the largest
immature and smallest adult animals.
Estimates of the MMP were related to
matched (same-year) characterizations
of sexual maturity based on ovigerous
condition — a more conventional measure
of functional maturity previously used to
characterize maturity for the two lobster
species. Both measures of functional
maturity were similar for the respective
species and were within 5% and 2% of
one another for slipper and spiny lob-
ster, respectively. The precision observed
for two shipboard collection series of
pleopod-length data indicated that the
method is reliable and not dependent on
specialized expertise. Precision of matu-
rity estimates for S. squammosus with
the pleopod-length metric was similar
to that for P. marginatus with any of
the other measures (including conven-
tional evidence of ovigerous condition)
and greatly exceeded the precision of
estimates for S. squammosus based
on ovigerous condition alone. The two
measures of functional maturity aver-
aged within 8f» of the estimated size at
gonadal maturity for the respective spe-
cies. Appendage-to-body size proportions,
such as the pleopod length metric, hold
great promise, particularly for species
of slipper lobsters like S. squammosus
for which there exist no other reliable
conventional morphological measures of
sexual maturity. Morphometric propor-
tions also should be included among the
factors evaluated when assessing size at
sexual maturity in spiny lobster stocks;
previously, these proportions have been
obtained routinely only for brachyuran
crabs within the Crustacea.
Manuscript submitted 2 September
2003 to the Scientific Editor's Office.
Manuscript approved for publication
26 August 2004 by the Scientific Editor.
Fish. Bull. 103:23-33 (20051.
Relative pleopod length as an indicator of
size at sexual maturity in slipper
(Scyllarides squammosus) and
spiny Hawaiian (Panulirus marginatus) lobsters
Edward E. DeMartini
Marti L. McCracken
Robert B. Moffitt
Jerry A. Wetherall
Pacific Islands Fisheries Science Center
National Marine Fisheries Service, NOAA
2570 Dole Street
Honolulu, Hawaii 96822-2396
E mail address (for E. E. DeMartini) edward demartinianooa gov
Estimates of body size and age at
sexual maturity provide key informa-
tion for stock assessments and hence
for managing sustainable fisheries.
Characterizations of size at matu-
rity are relatively straightforward in
lobsters and most other crustaceans.
One presently accepted standard is
to regress percentage mature against
classes of some body size metric and to
fit a logistic model to predict the size
class in which 50% of the population
is mature. A necessary prerequisite is
accurate data on the maturation state
of individuals. In spiny lobsters of the
family Palinuridae, female matura-
tion is usually deduced from "berried"
(ovigerous) condition (Groeneveld and
Melville-Smith, 1994), the presence
of external morphological indicators
such as changes in the number of pleo-
pod setae (Gregory and Labisky, 1981;
Montgomery, 1992), relative lengths
of abdominal and thoracic segments
(Jayakody, 1989), or proportional
lengths of segments of walking or egg-
bearing appendages at the pubertal
molt (George and Morgan, 1979; Grey,
1979; Juinio, 1987; Plaut, 1993; Evans
et al., 1995; Hogarth and Barratt,
1996; Minagawa and Higuchi, 1997).
A major complication arises, however,
when the percentage mature within
size classes cannot be accurately
described. Such is the case for Scyl-
larides squammosus, a species of slip-
per lobster (family Scyllaridae) that
prior to closure of the fishery in 2000
had become an increasingly important
target of the Northwestern Hawaiian
Island (NWHI) commercial trap fish-
ery. In S. squammosus, unberried but
mature females are indistinguishable,
based on gross external morphology,
from immature females. In this spe-
cies, the additional variance intro-
duced by combining falsely classified
"immature" with truly immature
females inflates requisite sample sizes
enough (given the sampling effort fea-
sible on annual research surveys) to
prevent characterization of possible
changes in size at maturity with data
pooled from less than several surveys.
Combining unberried adults with true
immature individuals also introduces
an overestimation bias (DeMartini et
al., 2003).
To date only one study has provided
a description of the use of a morpho-
logical measure of maturity in a slip-
per lobster (Hossain, 1978). Morphol-
ogy-based maturity measures have
been described for numerous spiny
lobsters of the genus Panulirus, but
such measures for the endemic Ha-
waiian spiny lobster (Panulirus mar-
ginatus) have not been fully described
(Prescott, 1984).
Our objectives are to describe the
development and use of an external
body metric for accurately and pre-
cisely characterizing body size at mor-
phological (functional) sexual maturi-
ty in female Scyllarides squammosus.
We likewise use this external metric
24
Fishery Bulletin 103(1)
to estimate size at maturity of females of the Hawai-
ian spiny lobster, for which functional maturity can be
accurately described by using a combination of other,
more apparent external features. We also estimate body
size at gonadal maturity by microscopic examination of
histological preparations of ovaries of each species and
use these results to validate the functional maturity
characterizations. We contrast the benefits of the dif-
ferent approaches for estimating functional maturity in
these two lobsters and discuss the potential importance
of applying efficient measures of maturation for manag-
ing the NWHI lobster fishery.
Materials and methods
Specimen collection
A research vessel was used to set and retrieve lobster
traps. All specimens of spiny lobster used in this study
were taken from Necker Bank surrounding Necker Island
(23°34'N, 164°42'W), NWHI. All the slipper lobsters used
were taken from Maro Bank, located about 600 km to
the northwest of Necker at 25°25'N, 170°35'W. Lobsters
were caught from bank terraces at median depths of 15
fm (slipper lobsters, Maro) and 17 fm (spiny lobsters,
Necker) with molded plastic (Fathoms Plus", San Diego,
CA) traps baited with 1 kg of mackerel (Scomber japoni-
cus) and left for a standard (overnight) soak.
Shipboard processing
All specimens were processed alive within minutes
of trap retrieval. Tail width (TW), as defined for slip-
per lobster by DeMartini and Williams (2001) and for
Hawaiian spiny lobster by DeMartini et al. (2003), was
measured with 0.1 mm accuracy. Berried females were
scored by egg-development stage with a gross visual
proxy (brooded eggs noted as either orange or brown
in color to the unaided eye). Female spiny lobsters
were scored by the presence or absence and by condi-
tion ("smooth"=unused, "rough"=partly used) of sper-
matophoric (sperm) mass (Matthews, 1951; Berry and
Heydorn, 1970) on the sternum. Female S. squammosus
in almost all cases lack a sperm mass and the presence-
absence of this feature provides no useful information.
In 1998-2000, ovaries were dissected from a maximum
of two living specimens for each 1-mm TW class of the
two species and fixed in 10% (sea water buffered) for-
malin for subsequent histological analyses. Egg-bear-
ing "tails" (abdominal segments) were flash-frozen at
-20 C.
During 1997-99, pleopods of each species were mea-
sured aboard ship to evaluate measurement accuracy
under field conditions. Maxima of 10 live individuals
per 1-mm TW class of each species were measured as
described below. Two independent measurements of
each specimen were made by each of two measurers
(one inexperienced and one experienced). In 2000-01,
pleopods for a larger series of morphometries were simi-
larly measured aboard ship to evaluate production-
scale numbers (500-1000 specimens per species on each
cruise) based on a single measurement per specimen
taken by one measurer.
Laboratory measurements
Beginning with specimens collected in 2000, the lengths
of exopodites on first pleopods were measured for a
representative sample of berried and unberried tails of
each species, after the tails were thawed overnight in a
refrigerator at 3 C. Preliminary observations indicated
that the first pleopod was disproportionately large in
berried females; measurements of the first pleopod of
all (berried and unberried) females moreover were the
most precise, i.e. the measurements were more likely to
be obtained again — probably because the first pleopod
was the easiest to measure. The straightline distance
between base and tip of exopodite on the first pleopod
(exopodite length=EL) was measured with dial calipers
to 0.01 mm. An analogous measurement of exopodite
width (EW) was taken perpendicular to the EL axis at
the structure's widest point. The left exopodite in ven-
tral aspect (Fig. 1) was routinely measured because the
ventral aspect was easier to measure for live animals
aboard ship. Measurements of the right exopodite (of
the same specimen) in dorsal aspect were taken for a
range of body sizes to evaluate the possible influence of
aspect (dorsal vs. ventral) or body side (left vs. right) on
the measurement that was taken. Replicate measure-
ments (independent, with calipers reset to zero between
measurements) were used to assess inter-measurer and
inherent measurement error. Formalized ovaries were
weighed (blotted damp-dry) to the nearest 0.01 g after
fixation for at least a month.
Histological validation
Fixed ovary specimens of each species were dehydrated,
imbedded, and sectioned by using standard techniques,
and were stained with hematoxylin and counter-stained
with eosin to differentiate protein and yolk materials
within oocytes. Histological slides were viewed under a
compound microscope at 150x magnification. For each
specimen, the diameters (average of major and minor
axis) were measured for 10 oocytes (randomly chosen)
within the largest size class of oocytes present. The
median diameter was used to characterize oocyte size
for that specimen; the median diameter based on 10
measurements yielded CVs (100% x standard error/mean)
<10% (DeMartini et al., 2003). Developmental staging
followed Minagawa (1997) and Minagawa and Sano
(1997): females were scored as mature 1) if unberried
in developing or ripe ovarian stages II and III, respec-
tively; 2) if berried in ripe and redeveloping stages
IV and V, respectively; or 3) if recently spent (stage
VI) with heavily setose pleopods (P. marginatus only).
Inactive females in stage I were scored as immature. A
gonad index, calculated as GI = (OWx 105/TW3), where
OW = ovary weight in g, was used to complement his-
DeMartini et al.: Validated morphological metric for lobster size at maturity
25
Female, Scyllandes squammosus, 56.0 mm TW
29.8 mm exopodite length
5mm
exopodite
B
5mm
Female, Panulirus marginalus, 51 .2 mm TAW
36.1 mm exopodite length
endopodite
egg-bearing
setae
exopodite
endopodite
egg-bearing
setae
Figure 1
Schematic diagram of the left first exopodite (ventral aspect! of (A) slipper lobster (Scyllarides squammosus) and (B) the
Hawaiian spiny lobster I Panulirus marginatus), showing axis of measurement. TW = tail width.
tological scores in assessing gonadal maturity
(Minagawa and Sano, 1997). Gonadal maturity
was used as a means of validating, as well as ref-
erencing, estimates of size at functional maturity
(Ennis, 1984).
Statistical analyses
Data for EL and EW (as response variables) and
TW (regressor) for the same specimen were first
plotted for all specimens of each species. Prelimi-
nary evaluations of these data (both raw and log-
transformed) with least-squares linear regression
(REG procedure; SAS vers. 8, SAS Institute, Inc.,
Cary, NC) indicated allometric relationships for
which double-log functions provided approximate
fits. Identification of join points by iteration based
on minimizing the total residual sums of squares
of pairs of joined regression equations (Somerton,
1980), however, resulted in linear spline fits that,
although significant, had obviously nonrandom
residuals. Simple linear fits with log-log plots, how-
ever, were useful for selecting the most appropriate
metric: the regressions of EW on TW, qualitatively
similar to those for EL regressed on TW, had con-
sistently lower r2 values, likely because pleopod
width was more difficult to measure than pleopod
length. The EL metric was therefore chosen for all
further analyses.
Because lobsters, like most biological populations, are
composed of individuals that differ in the size at which
first maturity occurs, we fitted a curve to the EL-TW re-
lation that included a sigmoid segment bridging the re-
gion between the estimated sizes of the smallest adults
(0O) and the largest immature individuals (0j) (Fig. 2).
The curve was fitted by using iterative reweighted least
CO
Q.
>.
"O
o
n
o
"5
E
o
"ro
o
<D
N
if)
^^— adult curve
•— juvenile curve
(
s'
s
s
s
y
s
% e,
Body size
Figure 2
Conceptual model of the relationships between size of an allo-
metric body part and body size in a population of organisms
in which large immature individuals overlap in body size with
small adults. Size overlap of immature individuals and adults
is indicated by the distance between 60 and 6V
squares (S-Plus 6 for Windows, Insightful Corporation,
Seattle, WA; Ratkowsky, 1983) with appropriate weights
to standardize the variance (Appendix). The morphomet-
ric maturation point, hereafter referred to as the MMP,
was estimated at the inflection ([0Q+0J/2) of the sigmoid
segment of the curve. This inflexion point represents
the body size at which we expect 50% of the lobsters to
become sexually mature (median size at attainment of
26
Fishery Bulletin 103(1)
maturity). Confidence bounds on the MMP were estimat-
ed by using the studentized bootstrap method (Davison
and Hinkley, 1997) with 1000 iterations.
In order to characterize median body size at gonadal
maturity, the percentage mature per 5-mm TW class,
deduced from viewing histological preparations of ova-
ries, was fitted to the conventional (2-parameter) logis-
tic model,
Px = 100/{l + exp[-a(7W-6)]},
where Px = percent mature at TW = x;
a and b are unknown constants; and
TW = tail width in mm.
To similarly estimate median size at maturity based
on gross external characteristics, the percentage ma-
ture per 5-mm TW class was fitted to a 3-parameter
logistic model for Scyllarides squammosus and to the
conventional 2-parameter logistic for Panulirus mar-
ginatus. For S. squammosus, percentage maturity per
5-mm TW class was estimated by fitting the 3-param-
eter logistic equation,
Pv=100a/{l + exp[(46/o)(c-7TV)]},
where a = the asymptotic proportion berried;
b = the slope of the logistic function at the inflec-
tion point; and
c = TWSQ is the tail width at the inflection point
(size at 50% of asymptote).
This function has been fully described for estimating per-
centage maturity based on incidence of ovigerous females
in iS. squammosus; the extra parameter is needed to fit
an asymptote to the sigmoidal function at a value less
than 100% (DeMartini et al., 2002). Parameters of the
various models were estimated by using the maximum-
likelihood nonlinear curve fitting procedure SAS NLIN;
all nonlinear regressions were weighted by the square
root of sample sizes.
The body size at which 50% of the population was es-
timated as mature (hereafter referred to as TW50) was
compared for 1) TW50 based on the relative incidence of
berried individuals within the female population (both
species), adjusted for the co-presence of a sperm mass
(P. marginatus only), 2) TW50 estimated from histologi-
cal evidence (both species), and 3) the MMP of the allo-
metric EL-to-TW relation (both species). Estimates were
compared graphically among methods for each species.
Analyses of pleopod-based maturity followed a series
of evaluations of pleopod characteristics used to identify
a standardized metric. Measurement aspect (dorsal,
ventral) and side (right, left) were compared within
individuals by using paired £-tests. A randomized com-
plete block (RCB) ANOVA (SAS PROC ANOVA), with
specimen as the blocking factor, was used to evaluate
the effects of measurer and measurement venue (at
sea versus ashore) on the mean measurement bias and
precision (CVs) of pleopod measurements.
Results
Pleopod characteristics
Measurement error, and effect of side of lobster and
aspect (ventral versus dorsal) on measurements Inher-
ent measurement error averaged 0.23 mm and 0.16 mm
(1.0% and 0.4%) for slipper and Hawaiian spiny lobster,
respectively, based on two independent measurements
by the same measurer. Exopodites of left-side pleopods
averaged 3% and 2% shorter than exopodites of right-
side pleopods for the two respective species (paired Mest;
both P<0.001; Table 1). Exopodites of first left pleopods
were 4% and 2% longer in ventral aspect for slipper and
spiny lobster, respectively, (RCB ANOVA; both P<0.001;
Table 1).
Measurement venue A matched (same-specimen) series
of measurements made aboard ship versus in the labo-
ratory (all by the same measurer) indicated a system-
atic difference in left pleopod length ( ship > lab; RCB
ANOVA; both P=0.001) for slipper lobster and spiny
lobster (Table 1). For each species, however, the mean
difference between venues was trivial (0.2-0.4 mm or
0.6-1.4%). Differences between ship and laboratory were
detectable despite the consistently lower precision pro-
vided by shipboard measurements (shipboard CVs were
47% and 39% larger for slipper and spiny lobster, respec-
tively; RCB ANOVA: both P<0.001; Table 1). Absolute
differences between shipboard and lab CVs were small
for the respective species (0.2% and 0.7%; Table 1).
Measurer effects An extensive series of shipboard inter-
measurer comparisons between pleopod length mea-
surements taken by one experienced (A) and a second
inexperienced (B) measurer indicated trivial systematic
differences between measurers (0.2%; RCB ANOVA;
P=0.25). Precision also was unaffected by measurer
(P=0.31; Table 1).
Standardized metric It follows from the above that the
best measure available for use was the length (in ven-
tral aspect) of the left first exopodite. This metric was
used in all quantitative comparisons among maturity
assessment methods and is recommended for future
applications with these species.
Estimated sizes at functional maturity
Slipper lobster Pleopod-to-TW relations for S. squammo-
sus did not differ meaningfully between 2000 and 2001
(ANCOVA; accept HQ: slopes equal, P=0.11; intercepts
only 0.5% different) and both years' data were pooled for
further analyses. The estimated MMP (95% CI) for the
TW at which 50% of the female S. squami7iosus exhibit a
disproportionately long first left exopodite was 47.6 mm
(45.1-49.4 mm; Fig. 3). Estimated median body size at
functional maturity based on presence or absence of ber-
ried eggs, using the same series of 2000-01 specimens,
was 55.5 (52.7-58.3) mm TW (Fig. 4).
DeMartini et al.: Validated morphological metric for lobster size at maturity
27
Table 1
Results of tests of potential effects of various criterion variables on the accuracy (bias of delta-barsl and precision (CVs of deltas)
for measured lengths of first pleopod exopodites for slipper lobster (Scyllarides squammosus) and Hawaiian spiny lobster (Panu-
lirus marginatus) caught from Necker Bank, Hawaii. Delta-bar = mean paired-difference; samples sizes are n paired observa-
tions.
Variable
Slipper lobster
Body side (left vs. right)
Measurement aspect (ventral vs. dorsal)
Measurement venue (shipboard vs. lab)
Measurement venue (shipboard vs. lab)
Measurer (A vs. B)
Measurer (A vs. B)
Spiny lobster
Body side (left vs. right)
Measurement aspect (ventral vs. dorsal)
Measurement venue (shipboard vs. lab)
Measurement venue (shipboard vs. lab)
Measurer (A vs. B)
Measurer (A vs. B)
Criterion
Test statistic
Delta-bar
accuracy
paired ?=-4.0
0.9 mm
accuracy
RCB Anova
Pi, 62=202.7
0.9 mm
accuracy
RCB Anova
Fl 62=23.6
0.4 mm
precision
RCB Anova
*Y 62=21-6
0.7%
accuracy
RCB Anova
^1.62 = 213
0.3 mm
precision
RCB Anova
Fi, 62=1-54
0.2%
accuracy
paired t=-5.7
0.7 mm
accuracy
RCB Anova
Fi. 32=31-7
0.7 mm
accuracy
RCB Anova
F187=11.62
0.2 mm
precision
RCB Anova
Fi, 87=11-74
0.4%
accuracy
RCB Anova
Fi. 87=1.37
<0.1 mm
precision
RCB Anova
F!, 87=l-04
<0.2 %
0.001
1)1)01
0.001
0.001
0.001
0.22
0.001
0.001
0.001
0.001
0.25
0.31
74
63
63
63
63
63
135
33
88
Spiny lobster Year effects on pleopod-to-TW relations
for P. marginatus were likewise insignificant ( ANCOVA;
accept H0: slopes equal, P>0.67; intercepts only 0.2% dif-
ferent) and data for both years were pooled for further
analyses. The MMP for the TW at which 50% of the P.
marginatus females exhibit a disproportionately long
pleopod was 36.4 mm (34.1-38.0 mm; Fig. 5). Figure 6
illustrates the corresponding estimate of median size
at functional maturity, 35.4 (33.7-37.1) mm TW, based
on the combined criteria of sperm mass and berried egg
presence, for P. marginatus.
Estimated sizes at physiological maturity
Gonadal maturity determined from microscopic staging
of histological ovary preparations indicated matura-
tion stages ranging from oogonial to fully vitellogenic
(Table 2; Minagawa and Sano, 1997) for the females of
each species. For both species, gonad indices (GIs) and
median oocyte diameters generally increased over the
cycle of development even though berried specimens
exhibited lower GIs and oocyte sizes than unberried
adults of the respective species (Table 2). The ovaries
of mature females contained a preponderance of fully
yolked oocytes whose average minimum diameter (fol-
lowing dehydration and staining) was 0.24 mm and
0.30 mm for S. squammosus and P. marginatus, respec-
tively. The maximum observed diameter of fully yolked
oocytes was 0.60 mm (in S. squammosus) and 0.58 mm
{P. marginatus).
The proportions of observed immature individuals
ranged from 32% to 38% of total female specimens
(depending on species) and were sufficient to construct
logistic curves relating percentage gonadal maturity to
body size for each species. Estimated median TWs at
gonadal maturity were 51.1 (48.6-53.5) mm and 40.5
(37.9-43.1) mm TW for S. squammosus (Fig. 4) and P.
marginatus (Fig. 6), respectively.
28
Fishery Bulletin 103(1)
50
Seyllarides squammosus •
E
E
Ol
c
0>
"O
o
Q.
O
CD
CL
e
CD
_l
40
30
20
/ oo„°
• 1 1 59 > ([e(l+e,]/2)
0
2
0
o 29 < ([e(1+e,]/2)
0 30 40 50 60 70 80 90
Tall width (mm)
Figure 3
Scatterplots of the relation between exopodite length and
tail
width for slipper lobster (Seyllarides squammosus). The
moi
phometric maturation point (MMP; indicated by the verti-
cal
line) represents the allometric threshold coincident with
sexual maturity ([0Q+0J1/2). The outlier indicated by an arrow
was
not used in estimating the MMP.
Table 2
Stages of ovarian development in 197 slipper lobster {Seyllarides squammosus
ginatus) caught from Necker Bank, Hawaii. There were no stage-VI S. squam
) and 122 Hawaiian spiny lobster (Panulirus mar-
710SUS.
Ovarian stage
Characteristics of ovaries and oocytes
Gonad index
mean ±SD
(range)
n
Most advanced
oocyte substage
(median diameter)
Slipper lobster
oogonia and previtellogenic oocytes conspicuous;
0.43+0.25
60
preyolk platelet
I (inactive)
ovary white
(0.02-1.08)
(0.18 mm)
II— III
(developing and ripe)
unberried; developing moderately to fully
vitellogenic oocytes; ovary pale orange to orange
1.63 ±1.45
(0.25-5.47)
75
prematuration
or maturation (0.28 mm)
IV-V
(ripe and redeveloping)
berried; developed fully yolked oocytes;
ovary dark orange
1.12 ±0.66
(0.15-3.30)
62
maturation
(0.26 mm)
Spiny lobster
I (inactive)
oogonia and previtellogenic oocytes; ovary white
0.85 ±0.67
(0.16-2.59)
30
preyolk platelet
(0.12)
II— III
(developing and ripe)
unberried; developing moderately to fully
vitellogenic oocytes; ovary pale orange to orange
14.03 ±4.46
(3.32-22.69)
42
prematuration
or maturation
(0.49)
IV-V
(ripe and redeveloping)
berried; developed fully yolked oocytes;
ovary dark orange
5.84 ±4.31
(0.56-17.06)
47
maturation (0.30)
VI (spent)
residual unspawned mature oocytes;
ovulation traces
14.85 ±6.38
(7.5-18.9)
3
yolk platelet but
atretic (0.48)
DeMartini et al.: Validated morphological metric for lobster size at maturity
29
Discussion
Properties of the EL-TW model
In order to determine morphometric maturity, we first
attempted to use a method developed by Watters and
Hobday (1998). With this method splines were used to
model the relationship between the morphometric char-
acter and body size; then the morphometric size at which
the second derivative of the fitted curve is maximal is
computed. At first this technique is alluring in that it
makes no allometric or other assumption as to the shape
of the relationship between the morphometric character
and body size. It instead assumes that maturation cor-
responds to the maximum of the second derivative. This
assumption is likely invalid even if we assume that the
relationship between the morphometric character and
body size changes abruptly at maturation for each indi-
vidual (as at the pubertal molt in crustaceans) because
individuals in the population mature at different sizes.
When we applied the Watters and Hobday method, the
resulting body size estimate appeared to character-
ize the minimum, not the median, size at attainment
of sexual maturity in the population and was clearly
inappropriate for our needs. Our method generated
fitted splines that were comfortingly similar in shape
to the parametric logistic (sigmoidal function) models
that we used to estimate maturation with berried and
histological criteria.
The magnitude of the difference between the sizes at
maturity estimated by our and the Watters and Hobday
(1998) model should vary in proportion to the magni-
tude of the difference between the minimum (0O) and
median ([0o+0j]/2) body sizes at maturity and therefore
be case-dependent. In our slipper lobster case, the 80
and 0l estimates differed by about 6.6 mm; hence, the
two model estimates differed by about 6.6/2 = 3.3 mm
or approximately 7% of the [{6^+6-^)12} median. Because
other cases certainly include those in which immature
and adult sizes overlap even more greatly, we suggest
that our more general and accurate model be adopted.
Functional versus physiological measures of maturity
Morphological features can provide adequate if imperfect
measures of functional sexual maturity, as can physi-
ological evidence for gonadal maturity (Ennis, 1984).
Morphological features such as ovigerous condition can
underestimate the incidence of mature individuals, but
the degree to which they do so depends on numerous fac-
tors including species and population. Physiological met-
rics in some cases can provide more accurate estimators
of both body size and age at maturity because they reveal
the reproductive readiness of individuals at the time
of collection. Individual body size and age at maturity
can be decoupled from functional maturity metrics in
Crustacea, however. For example, some crustaceans like
majid crabs exhibit determinate growth following a ter-
minal, pubertal molt (Hartnoll, 1982). For such species,
size at attainment of sexual maturity is synonymous
100
50
Tail width (TW, mm)
Figure 4
Scatterplots and fitted curves of the relations between
body size (tail width, TW) and percent sexual maturity
based on functional maturity gauged by presence-absence
of berried condition (dotted curve), overlaid on gonadal
maturation gauged by microscopic examination of ovaries
(dark-line curve); the pleopod length-based morphometric
maturation point (MMP) estimate of size at functional
maturity is indicated by the large circle with cross-hairs
(©), for slipper lobster iScyllarides squammosus). A
3-parameter logistic equation was necessary to fit the
dotted curve; a 2-parameter logistic was sufficient to
fit the dark-line curve (see text).
with the median body size of adults. These two attributes
are not synonymous for lobsters with indeterminate
growth. It is further obvious that the pleopods and other
allometric body parts of Crustacea like lobsters reflect
an array of gonadal maturities ranging from developing
immature to fully mature, which can be problematic
because some or many females might abort and resorb
developing gonadal eggs after the pubertal molt (Aiken
and Waddy, 1980) or may not become inseminated (Hey-
dorn, 1969). By attributing maturity to specimens that
either have not matured physiologically or that will not
reproduce although capable of doing so, appendage-to-
body proportions can underestimate the age at maturity
in Crustacea. The degree of underestimation should
be proportional to the incidence of gonadal resorption
during the intermolt period following the pubertal molt,
30
Fishery Bulletin 103(1)
Panulirus marginatus
10 20 30 40 50 60 70 80 90
Tail width (mm)
Figure 5
Scatterplots of the relation between pleopod length and tail
width for the Hawaiian spiny lobster (Panulirus marginatus).
The morphometric maturation point (MMP: indicated by a
vertical line) represents the allometric threshold coincident
with sexual maturity ([Oo+fJ 12).
as well as the duration of the intermolt. These specific
topics deserve future study.
The above caveats notwithstanding, it is helpful to
compare estimates of body sizes at sexual maturity
based on various morphological and physiological evi-
dence and to ascertain the degree of agreement among
the estimates (Fernandez-Vergaz et al., 2000). The es-
timate of MMP (47.6 mm) indicated by the pleopod
length-to-TW relation for S. squammosus, for example,
was about 16% smaller than the median size at matu-
rity (55.5 [±1.35 SE] mm) estimated by using simple
presence-absence of berried eggs for the same series of
specimens. The latter estimate, however, is imprecise
and an overestimate. The long-term mean TW at 50%
maturity based on berried condition for the period from
1986 to 2001, indistinguishable among component years,
was 50.0 ±0.83 mm, more precise than the single-year
estimate although still biased high (DeMartini et al.,
2002). If this 50.0 value is used for reference, the pleo-
pod length-based estimate of the MMP falls within <5%
of the long-term mean. For P. marginatus, the analogous
MMP = 36.4 mm value was within 3% of the estimated
median size at maturity (35.4 mm) based on the com-
bined criteria of berried eggs and sperm mass presence.
All the various estimates of functional maturity for the
two species were within 2.0-12.6% (mean=7.9%) of the
best respective estimate of gonadal maturity. These
close similarities, despite the inherent biases of the two
methods, indicate that maturity metrics such as relative
pleopod length can provide highly satisfactory proxies
of true functional maturity that are closely related to
gonadal maturity in certain cases.
Pleopod length as a maturity metric
In some Crustacea (once again, not lobsters, as far as
is known), allometries are not fixed at the pubertal
molt; and, in a minority of these, allometric growth
is seasonally cyclic and allometries disappear when
mature instars molt during nonreproductive periods
(Hartnoll, 1974. 1982). And body proportions may not be
strong predictors of sexual maturity for clawed lobsters
(Comeau and Savoie, 2002). In many, if not most, deca-
pods such as spiny lobsters (e.g., George and Morgan,
1979; Groeneveld and Melville-Smith, 1994), however,
relative appendage-to-body sizes, as well as obvious
morphological criteria such as the presence of berried
eggs and a sperm mass, indicate functional sexual matu-
rity. Body part allometries in some cases can be better
predictors of maturity than more obvious characters
like berried eggs. An incomplete measure such as per-
centage berried, exemplified by the slipper lobster (S.
squammosus) in the present study, can falsely fail to
detect reproductively inactive adult females. Appendage-
to-body size proportions thus have one major advantage
over other morphometries in that they permit reproduc-
tively inactive adult females to be correctly classified
as mature. This advantage is relatively unimportant
in other species like P. marginatus for which additional
gross morphological indicators such as the presence-
absence of a sperm mass complement the information
provided by berried condition. Even so, proportional
appendage lengths can be used in such cases as another
fairly inexpensive and independent measure that could
contribute to a multivariate assessment of maturity.
DeMartim et al.: Validated morphological metric for lobster size at maturity
31
100
Panulirus marginatus
curve: histological criteria
Px= 100/(1 +exp-(-9.415+0.233TW))
l2= 0.907
curve: berried +
sperm mass criteria
Px = 1 00 / (1 + exp-(-1 8.836+0.532 TW))
^=0.895
50 60
Tail width (TW, mm)
80
Figure 6
Scatterplots and fitted curves for the relations between
body size (tail width, TW) and percent sexual maturity
based on functional maturity gauged by presence-absence
of sperm mass and berried condition (dotted curve),
overlaid on gonadal maturation gauged by microscopic
examination of ovaries (dark-line curve); the pleopod
length-based morphometric maturation point (MMP)
estimate of size at functional maturity is indicated
by the large circle with cross-hairs (©), for Hawaiian
spiny lobster (Panulirus marginatus). Two-parameter
logistic equations were sufficient to fit both the dotted
and dark-line curves.
truly immature from mature, but reproductively inac-
tive, females generates an inflated "immature" class,
and the estimates of median size at sexual maturity
thus obtained with logistic equation fits are biased high.
Variances of median-size estimates based on sample
sizes available on single research surveys are often so
large that 3-parameter logistic applications (necessary
to scale maturity to 100%) fail to converge, and reliable
individual-year estimates are impossible (DeMartini
et al., 2002). Unfortunately, the temporal dynamics
of targeting species by fishermen in the NWHI trap
fishery and the rapid phenotypic responses in fecundity
and maturation size to harvesting, fluctuating natural
productivity, and changing population densities that
have been observed in P. marginatus (DeMartini et al.,
2003), require that size at maturity be re-estimated at
short (one-to-several-year) intervals for this species at
least and possibly for S. squammosus as well.
The accurate and precise estimates of median body
size at sexual maturity made possible by using the
pleopod length metric enable such yearly re-evaluations
for S. squammosus and provide a second reliable and
independent estimator for P. marginatus. Our success-
ful applications for a scyllarid as well as a palinurid,
together with prior observations for numerous other
spiny lobster species, indicate that easily measured
appendage length-to-body size relations are generally
suitable for assessing functional sexual maturity in
lobsters and other decapods. We recommend that these
relations be explored for other commercially exploited
crustacean stocks and wherever possible routinely ap-
plied to provide cost-effective and timely information
on size at maturity for stock assessments. Managers
responsible for the assessment of lobster and other crus-
tacean stocks will then have a more complete toolbox
of methods generally available for assessing the size
at maturity and harvestability of stocks, particularly
for species like S. squammosus in which conventional
morphological measures are inadequate.
Acknowledgments
We thank D. Yamaguchi for assistance with Figure 1
and G. DiNardo and J. Polovina for constructive criti-
cisms of the manuscript.
unconstrained by a conspicuous but perhaps inaccurate
feature like berried condition.
Literature cited
Management implications
Estimates of body size at sexual maturity can provide
key information to various stock assessment models, but
only if the estimates are accurate and sufficiently pre-
cise. For the slipper lobster (S. squammosus), DeMartini
et al. (2002) have shown that estimates made by using
percent berried as the lone maturity criterion, the only
morphological metric previously available, are both
inaccurate and imprecise. The inability to distinguish
Aiken, D. E., and S. L. Waddy.
1980. Reproductive biology. /« The biology and manage-
ment of lobsters, vol. I, physiology and behavior (J. S.
Cobb and B. F. Phillips, eds.), p. 215-276. Academic
Press, New York, NY.
Berry, P. F., and A. E. F. Heydorn.
1970. A comparison of the spermatophoric masses and
mechanisms of fertilization in Southern African spiny
lobsters (Palinuridae). S. Afr. Assoc. Mar. Biol. Res.,
Oceanogr. Res. Inst. Invest. Rep. 25, 18 p.
32
Fishery Bulletin 103(1)
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DeMartini et al.: Validated morphological metric for lobster size at maturity
33
Appendix
Method for estimation of maturation
with pleopod metrics
To model the allometry we used the power function
Y=(5X'1' and assumed multiplicative error. The logarithmic
transformation of this function leads to a linear regres-
sion model. Specifically, we defined ln(Y) = f1(X)+e1
where fi(X)=a1+l\\n{X) and a, =ln((3j), as the allometric
relationship for juvenile lobsters and ln(Y) = f2(X)+e2,
where f2(X)=a2+fi2\n(X) and a2 =ln(d2), as the allometric
relationship for adult lobsters. The errors, el and e2, were
assumed to be independent and normally distributed
with mean 0 and variance <jj2 and o22, respectively.
We assumed that maturation occurred over a range
of tail widths. Dividing the domain of x into four
intervals, we defined the probability that a lobster
with observed tail width x was mature (m) as
P(m\x)--
x-en
exp
' J0o+el-2x'
0,-x
exp
el-eQ
e0<x<
x<e0
x<ex
x>(
(i)
When y=0, Pim\x) increases linearly from 0 to 1 over
the interval [80, 6l ]. For y>0, the curves are sigmoidal,
symmetrical, and the rate that the probability changes
with respect to tail width is bell shaped (the sigmoidal
curve first accelerates, then decelerates). The point of
inflection, {6^+0^12, is the tail width at which 50% of
the lobsters are expected to be mature. For both species,
we assumed that yaO.
Defining the allometry model and the probability
of maturity as above, we expressed the model relat-
ing pleopod length to tail width as ln( Y)=/1(X)(1-
P(m\x))+f2iX)Pim\x)+e, where f are independent normal
variates with mean 0 and covariance Vm.
Assuming (.t,,y() i=l, ... ,n independent paired obser-
vations and cP- = o^=o22, V!H=Io2+M, where / is the (n x
n) identity matrix, M is the diagonal matrix MU=A2 (xt)
P(m,l.v,) (1-P(m,l.v,)), and AU,)^*,)-/^*,). Hence, we
have a weighted least squares problem with weights
(o'+Mj
if xl s 00 or xl a 6X
ife0<xi<e1.
(2)
To fit the model, we defined a3=c<2-c<1 and P3=P2~Pi
and expressed the model as ln( Y)=f3(X)P(m\x)+f1(X)+e,
where f3(X)=a3+ /33 ln(X). To ensure that the curve in
the transition range was monotonically increasing (if
P3>0), 80 was bounded such that 0oaexp(-cc3//33), and
if /33<0, 61 was bounded such that 0jsexp(-a3//33). The
curve was fitted by using iteratively reweighted least
squares. The weights were recomputed at each iteration.
While fitting the lobster data to the specified model,
we observed that one or more of the parameters in-
volved in defining the sigmoidal curve departed from
linear behavior. Under these circumstances, the con-
fidence interval derived by assuming the asymptotic
properties of maximum likelihood estimates may be
invalid (Ratkowsky, 1983). Therefore, we computed ap-
proximate 95% confidence intervals for the point of
inflection using the bootstrap method. Specifically, we
used case resampling with 1000 bootstrap replications.
Confidence intervals were derived by using the studen-
tized bootstrap confidence limits (Davison and Hinkley,
1997).
J4
Abstract — In this study we present
new information on seasonal variation
in absolute growth rate in length of
coho salmon (Oncorhynchus kisutch ) in
the ocean off Oregon and Washington,
and relate these changes in growth
rate to concurrent changes in the
spacing of scale circuli. Average spac-
ing of scale circuli and average rate of
circulus formation were significantly
and positively correlated with average
growth rate among groups of juvenile
and maturing coho salmon and thus
could provide estimates of growth
between age groups and seasons.
Regression analyses indicated that
the spacing of circuli was proportional
to the scale growth rate raised to the
0.4-0.6 power. Seasonal changes in
the spacing of scale circuli reflected
seasonal changes in apparent growth
rates offish. Spacing of circuli at the
scale margin was greatest during the
spring and early summer, decreased
during the summer, and was lowest in
winter or early spring. Changes over
time in length offish caught during
research cruises indicated that the
average growth rate of juvenile coho
salmon between June and Septem-
ber was about 1.3 mm/d and then
decreased during the fall and winter
to about 0.6 mm/d. Average growth
rate of maturing fish was about 2
mm/d between May and June, then
decreased to about 1 mm/d between
June and September. Average appar-
ent growth rates of groups of matur-
ing coded-wire-tagged coho salmon
caught in the ocean hook-and-line
fisheries also decreased between June
and September. Our results indicate
that seasonal change in the spacing
of scale circuli is a useful indicator
of seasonal change in growth rate of
coho salmon in the ocean.
Seasonal changes in growth of coho salmon
(Oncorhynchus kisutch) off Oregon and
Washington and concurrent changes
in the spacing of scale circuli
Joseph P. Fisher
William G. Pearcy
College of Oceanic and Atmospheric Sciences
Oregon State University
104 Ocean Admin. Building
Corvallis, Oregon 97331-5503
E-mail address (for J. P. Fisher) |fisheng>coasoregonstateedu
Manuscript submitted 20 September
2003 to the Scientific Editor.
Manuscript approved for publication
8 September 2004 by the Scientific Editor
Fish. Bull. 34-51(2005).
Large interannual and decadal varia-
tions occur in the abundance and pro-
ductivity of North Pacific salmonids.
These fluctuations, which affect har-
vestable biomass, are influenced by
survival rates, ages at maturity, and
somatic growth (Beamish and Bouil-
lon, 1993; Mantua et al., 1997; Hare
et al. 1999; Pyper et al., 1999; Hobday
and Boehlert, 2001).
The growth of smolts after ocean
entry — growth that is critical to
production — is also thought to be
an important determinant of their
survival. As for juvenile and larval
fishes in general, size-selective mor-
tality may occur (Miller et al., 1988;
Bailey and Houde, 1989; Litvak and
Leggett, 1992; Sogard, 1997) with
the result that faster growing sal-
monids experience less mortality
from predators than slower growing
salmonids (Parker, 1971; Bax, 1983;
Fisher and Pearcy, 1988; Holtby et
al., 1990; Jaenicke et al., 1994; Wil-
lette, 1996, 2001). This size-selective
mortality may explain much of the
interannual variability in survival
of juvenile salmonids and the sub-
sequent abundance of different year
classes. However, other investigators
have not found a strong relationship
between growth of juvenile salmon
and mortality (Fisher and Pearcy,
1988; Mathews and Ishida, 1989;
Blackbourn, 1990).
Intercirculus spacing of scales has
been used to estimate early ocean
growth rate of juvenile salmon and
has been linked to differential sur-
vival rates. For example, Healey
(1982) used the spacing of the first
five circuli to demonstrate intensive
size-selective mortality in juvenile
chum salmon (Oncorhynchus keta) as
they migrated offshore. Holtby et al.
(1990) correlated early ocean growth,
based on intercirculus spacing, with
marine survival of age 1+ coho (O.
kisutch) smolts. The spacing of early
ocean circuli from the scales of ma-
turing Atlantic salmon (Salmo salar)
has been used to estimate juvenile
growth rates, which are correlated
with survival and age at maturity,
and to identify stocks (Friedland et
al., 1993; Friedland and Haas, 1996;
Friedland and Reddin, 2000; Fried-
land et al., 2000).
Correlation between circulus spac-
ing and growth rate was reported
by Fisher and Pearcy (1990) for age
0.0 coho smolts reared for 60 days in
salt water tanks. In addition, posi-
tive correlations between the spacing
of scale circuli and fish growth rate
have been observed for rainbow trout
(O. mykiss) (Bhatia, 1932), and sock-
eye salmon (O. nerka) (Fukuwaka and
Kaeriyama, 1997), and between the
spacing of circuli and feeding ration
and growth for sockeye salmon (Bil-
ton and Robins, 1971; Bilton, 1975).
Bigelow and White (1996) were able
to manipulate the spacing of scale
circuli of cutthroat trout (O. clarkii)
Fisher and Pearcy: Seasonal changes in growth of Oncorhynchus kisutch off Oregon and Washington
35
Table 1
Main sources of coho salmon data used in this study.
Source Numbers of fish
Scale samples
CWT maturing fish caught in the Oregon ocean sport and troll fisheries 1982-92 (see Table 2) 687
687
Maturing coho salmon caught in the ocean during research cruises
1981-85 1391
352
1998-2002 714
236
Juvenile fish caught in the ocean during research cruises
1981-85
1798
1998-2002 3684
1052
CWT maturing coho salmon caught in the sport and troll ocean fisheries (all catch areas) 149,718
—
and released between northern Oregon and northern Washington'
1 FL data in the Pacific States Marine Fisheries Commission, Regional Mark Information System online CWT data
base http
//ww
w.rmis.org/.
[Accessed 1 April 2003.]
in the hatchery by varying the feeding levels: the group
that was fed the most also grew the most and had the
most widely spaced scale circuli. Positive correlations
between circulus spacing and growth also have been ob-
served for nonsalmonid fishes including Tilapia (Doyle
et al., 1987; Matricia et. al., 1989; Talbot and Doyle,
1992), and walleye (Stizostedion vitreum) (Glenn and
Mathias, 1985).
Circulus spacing is potentially useful for comparing
ocean growth rates of salmon in the ocean. Spacing of
the first few ocean scale circuli may indicate relative
growth rates of juvenile fish immediately after ocean
entry. However, in order for spacing of scale circuli to be
a practical indicator of fish growth rate, the relationship
between the two must be consistent and significant.
The relationship between circulus spacing and fish or
scale growth rate is determined by the relative rates
of growth and circulus formation. If circuli (like tree
rings) are formed at a constant rate, then there would
be a directly proportional relationship between spacing
and growth rate (e.g., a doubling of growth rate would
result in a doubling of spacing). Conversely, if the rates
at which circuli are formed are directly proportional
to growth rates (e.g., a doubling of growth rate would
result in a doubling of circulus formation rate), then the
spacing of circuli would be constant. Our earlier study
of growth rate, circulus formation, and circulus spacing
among 82 individually marked juvenile coho salmon
growing for a period of 63 days in saltwater tanks indi-
cated that neither of these two extremes is the case, but
that both circulus formation rate and circulus spacing
are positively correlated with fish growth rate (Fisher
and Pearcy, 1990).
Our main objectives in this study are to further as-
sess the reliability of circulus spacing as an indicator
of growth rate in FL of coho salmon in the ocean, to
investigate how growth of coho salmon changes season-
ally, and to compare any seasonal changes in growth
rate with seasonal changes in the spacing of scale cir-
culi. If circulus spacing is a reliable indicator of growth
rate, then seasonal changes in growth rate should be
tracked by changes in the spacing of circuli laid down
at the scale margin. We investigated relationships be-
tween scale growth rate, fish growth rate, circulus spac-
ing, and circulus formation rate for coded-wire-tagged
(CWT) adult coho salmon collected in the ocean fisher-
ies in years when ocean growth varied widely, including
year classes affected by the 1982-83 El Nino, and for
juvenile and maturing coho salmon caught in the ocean
off Oregon and Washington in research cruises 1981-85
and 1998-2002.
Materials and methods
Scale and FL data
Fish fork length (FL) and scale data from a variety
of sources were used in this study (Table 1). During
research cruises on the Oregon and Washington coastal
shelf we collected juvenile and maturing coho salmon
in the upper 20-40 m of the water column with purse
seines from 1981-85 (Pearcy and Fisher, 1988, 1990)
and with a rope trawl from 1998-2002 (Emmett and
Brodeur, 2000). Scales samples were removed from the
fish from an area equivalent to area "A" described in
Scarnnechia (1979). When scales were not available from
area "A," we took scales from between areas "A" and "B"
in Scarnnechia (1979). (See also Clutter and Whitesel,
1956). We also examined scales from the same area
from 687 maturing CWT Columbia River and northern
coastal Oregon coho salmon caught in the Oregon ocean
fisheries between 1982 and 1992.
Changes over time in FLs of maturing coho salmon
caught in research nets and of CWT hatchery coho
salmon originating between northern Oregon and north-
ern Washington and caught in the ocean fisheries be-
36
Fishery Bulletin 103(1)
1982-1983
1983-1984
Figure 1
Scales from the 1982-83 and 1983-84 (smolt year through adult year) year
classes of coho salmon (Oncorhynchus kisutch) showing the axis of measurement,
the scale focus (F), ocean entry (OE), the annulus (A) at the end of the annual
ring and the scale margin (Ml.
tween 1975 and 2002 were used to estimate growth
rates of maturing fish (Table 1).
Scale measurements
We measured the distances (mm) along the anterior-pos-
terior scale axis from the focus (F) to the last circulus
of the freshwater zone (ocean entry, OE), to the outside
edge of the winter annual ring (the "winter annulus,"
A) when present, and to the margin (M), and also deter-
mined the total numbers and average spacing of circuli
in the ocean growth zone (Fig. 1). For certain scale
samples we also determined the spacing of every circulus
in the ocean growth zone of the scales or of the last few
circuli at the scale margin.
Measurements of scales from juvenile fish caught
during research cruises 1981-85 were taken from im-
ages projected by a microfiche reader at a magnifica-
tion of about 88x and measurements of scales from all
other fish were acquired with image analysis software
(Optimas, vers. 5.1, Optimas, Inc., Seattle, WA, and
Image-Pro Discovery, vers. 4.5, Media Cybernetics, Sil-
ver Spring, MD) by using a CCD camera coupled to a
Leica compound microscope. All measurements were
calibrated from images of a stage micrometer.
Circulus spacing and formation rate versus growth rate
We used correlation and regression analyses to relate
average circulus spacing and formation rate to average
scale and fish growth rate among year classes of juvenile
coho salmon during their first four or five months in the
ocean and among groups of maturing CWT coho salmon
during their entire ocean life (Table 2). We described
the relationships between the scale characteristics and
growth rate as power functions by using natural log
(In) transformed variables in linear regressions. Geo-
metric mean (GM) regression (Ricker, 1973, 1992; Sokal
and Rohlf, 1995) was used to relate the In-transformed
variables because they were subject to both natural
variability and measurement error and because our pur-
pose in the present study was to describe the functional
relationships between the variables and not to predict
one from the other.
For each fish, rates of scale growth, fish growth,
and circulus formation in the ocean were estimated
as (SR-SR0E)/Ad, (FL-FL0E)IAd, and CIRC/Ad, re-
spectively, where SR = scale radius at capture, SR0E=
scale radius at ocean entry (F to OE in Fig. 1), FL =
fork length at capture, FL()A=estimated fork length at
ocean entry, C/.RC=the total number of circuli in the
ocean growth zone of the scale, and Ad = estimated days
between ocean entry and capture. Average spacing of
circuli was calculated as (SRLAST-SR0E)/CIRC, where
SRj ,lsr=the scale radius to the last circulus before the
scale margin.
For juvenile fish, FL0E was estimated by using the
Fraser-Lee back-calculation method (Ricker, 1992) and
the intercept from the FL-SR regression for ocean-
caught juvenile fish (34.16 mm. Fig. 2). However, be-
Fisher and Pearcy: Seasonal changes in growth of Oncorhynchus kisutch off Oregon and Washington
37
cause of allometry in the FL-SR relationships of juvenile
and maturing fish (Fig. 2), which a ln-ln transformation
of the data failed adequately to correct, the Fraser-Lee
method was not used to estimate FLOE of the maturing
fish caught in the ocean. Instead, FLOE of maturing
fish was estimated by direct substitution of (SROE) into
the GM regression relationship between FL and SR for
juvenile coho salmon caught in the ocean 1981-85 and
1998-2001 (gray regression line. Fig. 2).
For juvenile fish caught in August or September, Ad
was estimated as the capture date minus 25 May, a date
near the peak of coho salmon smolt migration in the
Columbia River estuary (Dawley et al., 1985a). Because
we used a single date of ocean entry for all fish, errors
in estimated growth rates of some individual juvenile
coho salmon probably were quite large; the timing of
ocean entry of fish can vary by as much as two months.
However, for the correlation and regression analyses we
used growth rates averaged by year class, which were
probably quite accurate, if the average date of ocean
entry of the fish in the samples is assumed to be similar
across years. In the Columbia River, the major source
of juvenile coho salmon on the Oregon and Washington
coasts, ocean entry was concentrated between late April
and early June and the timing of ocean entry varied
little between years (Dawley et al., 1985a).
Dates of ocean entry of the maturing CWT Sandy
and Cowlitz hatchery coho salmon (Table 2) were esti-
mated from the hatchery release dates and the rates of
downstream migrations of these fish observed during
extensive sampling of migrating smolts at rkm 75 in the
upper Columbia River estuary (Dawley et al., 1985b). To
estimate dates of ocean entry of the Fall Creek hatch-
ery fish, for which data on downstream migration were
lacking, we assumed that smolts migrated to the ocean
from the different release sites at the same average rate
of downstream migration as that of Cowlitz Hatchery
fish released in late April (5.7 km/d).
Potential errors in estimated growth rates of matur-
ing CWT coho salmon caused by inaccurately estimat-
ing size of fish at ocean entry, or date of ocean entry,
were proportionally very small when compared to the
total amount or duration of ocean growth. At a typical
SR0E of around 0.7 mm, the 95% prediction limits for
FL from the SR-FL regression of juvenile fish (Fig. 2)
are about ±31mm. An error in size at OE of 15-30 mm
would only be 2-10% of the estimated total growth in
FL in the ocean of the maturing fish (320 mm-610 mm).
Similarly, an error in estimated date of ocean entry of
30 days would equal only about 6-10% of the total time
that the fish was in the ocean (336-535 d). Errors for
the group-averaged data used in our correlation and
regression analyses were probably much lower.
Seasonal changes in spacing of circuli
To investigate whether circulus spacing and growth
rate were correlated seasonally, we first described the
patterns of seasonally changing circulus spacing of
juvenile and maturing coho salmon in the ocean and
Table 2
Nine year classes of juvenile coho salmon caught in
research nets in August or September and 17 groups of
CWT maturing coho salmon caught in the Oregon ocean
fisheries used in the correlation and regression analyses
of scale characteristics and growth rate. CWT maturing
fish were from three hatcheries (Fall Creek "F" on the
northern Oregon coast and Sandy "S" and Cowlitz "C" in
the lower Columbia River basin) and were released from
hatcheries during three periods.
Capture year
Hatcheries
Numbers offish
CWT maturing fish released late April
or early May (days 119-127)
1982 F, S
1983 F, S, C
1984 S, C
1985 S, C
1986 S
1987 S
1989 S
1990 S
CWT maturing fish released in March (days 74-76
1984 F 31
1985 F 21
CWT maturing fish released in late May or early
Juneldays 151-157)
1991 S 30
1992 S 77
11, 15
34, 17, 51
52,35
12,26
67
94
57
18
Juvenile fish
1981
1982
1983
1984
1998
1999
2000
2001
2002
99
95
81
88
13
60
75
67
123
then compared these patterns of changing circulus
spacing to changing fish growth rates. Because the
widths of the pre-annulus and postannulus scale zones
and the numbers of circuli in each zone varied greatly
among individual fish and among groups of fish, we
described circulus spacing in each of 25 equally spaced
intervals between OE and the annulus and in each of
25 equally spaced intervals between the annulus and
the scale margin, rather than on a circulus by circulus
basis. Specifically, the pre-annulus and postannulus
ocean zones of scales were each divided into 25 equal
intervals, and the radial distance from OE to the upper
bounds of each of the intervals was determined. Next,
the numbers of ocean circuli between OE and the upper
bounds of each of the 50 intervals were interpolated.
For example, if a boundary fell 25% of the distance
38
Fishery Bulletin 103(1)
— 400
200
between the 38th and 39th ocean circulus, the
circulus number 38.25 was assigned to that
boundary. We calculated the circulus spac-
ing in each interval as 4mm/Acirc, where
4mm = the width in mm of the interval, and
4circ = the difference between the interpo-
lated circulus numbers at the upper and
lower bounds of the interval. The circulus
spacing in each of the 50 intervals was aver-
aged across all the scales from the fish in a
group. This produced a profile of the average
spacing of circuli at 50 different positions
in relation to OE (lower bound of interval
1), the annulus (upper bound of interval
25) and the scale margin (upper bound of
interval 50). Finally, the group-average cir-
culus spacing in each of the 50 intervals was
plotted against the group-average radial dis-
tance from OE to the upper bounds of each
of the 50 intervals. For juvenile fish caught
in trawls in September 1999-2002, circu-
lus spacing was described at 25 intervals
in relation to OE (lower bound of interval
1) and the scale margin (upper bound of
interval 25).
Seasonal changes in the spacing of circuli
at the growing edge of the scale may reflect
similar seasonal changes in the growth rate
of the juvenile and maturing coho salmon.
To investigate this possible correlation, we
measured the spacing of the last two circu-
lus pairs at the scale margin of juvenile fish
caught in early and late summer in 1982
and 1999 through 2002 and of maturing fish
caught in research nets 1981-83 and 2000-2002 and in
the ocean fisheries 1982-92 (Table 1). Mean spacing of
the last two circulus pairs was summarized by cruise
for the fish caught in research nets, and by 10-day catch
intervals for the fish caught in the ocean fisheries. The
seasonal trends in spacing at the scale margin were
then compared with the seasonal trend in apparent
growth rates of fish.
Seasonal changes in fish growth rate
Seasonal trends in growth rates of juvenile and matur-
ing coho salmon caught in research cruises 1981-83 and
1998-2002 were estimated from the changes between
cruises in average FL. We also estimated average growth
rates (pooled across years) of juvenile and adult coho
salmon during different seasons by fitting regressions
to the FL versus catch date data.
Changing stock composition of the juvenile (Teel et
al., 2003) or maturing coho salmon caught in research
nets over the course of the summer could potentially
have a strong effect, independent of growth, on the size
distributions of fish caught at different times. Therefore,
changes over time in average FLs of mixed stocks of
fish, such as in our research collections, may not ac-
curately indicate actual fish growth rates.
1000
800
600 -
0 -
o Adults, May-Sept. 1981-1983
° Adults, June and Sept, 2001 , 2002
• Adults, June 2000 and Table 2
• Juveniles, 1981-1985, 1998-2001
FL (mm) = 1 50-94 SR* 34.1 6,
n=2834. r2 = 0.94
Scale radius (mm)
Figure 2
Fork length (FL) versus scale radius (SR) for juvenile and matur-
ing coho salmon I O. kisutch) caught in research trawls and GM
regressions of FL versus SR fitted to juvenile and adult fish sepa-
rately. Note the allometry in the FL-SR relationship of juvenile
and adult fish.
Because of the potential for error when inferring
seasonal changes in growth rate from changes over
time in average FLs of mixed stocks of fish, we also
examined temporal changes in FL of maturing CWT
coho salmon of known origin caught in the ocean hook-
and-line fisheries (sport and troll fisheries). Using data
available from the Pacific States Marine Fisheries Com-
mission1 we investigated changes over the summer in
FLs of maturing CWT coho salmon originating from
six areas (north Oregon coast, lower Columbia River
basin-Oregon, lower Columbia River basin-Washington,
Willapa Bay basin, Grays Harbor basin, and the north-
west Washington coast). Because the date that a smolt
is released from a hatchery (e.g., March vs. June) could
affect its size the following year, we also grouped the
fish by release periods of 25-46 days duration. Da-
ta were available on FLs of maturing CWT fish from
1975-2002. For each group in each year we calculated
the average FL of CWT fish at 10-day intervals in the
hook-and-line fisheries (sport and troll fisheries) pooled
for all catch areas between California and Alaska. Data
were discarded when there were fewer than 5 fish mea-
1 Regional Mark Information System CWT database (http://
www.rmis.org). [Accessed on: 1 April 2003.1
Fisher and Pearcy: Seasonal changes in growth of Oncorhynchus kisutch off Oregon and Washington
39
Table 3
Summary statistics of
lus formation, and avc
and during the entire
average estimated fish growth rate, average estimated scale growth rate, average
rage circulus spacing between ocean entry and late summer for nine year classes
ocean growth period for the 17 groups of CWT maturing coho salmon (see Table 2)
estimated rate of circu-
of juvenile coho salmon
Statistic
Average fish
growth rate
(mm/d)
Average scale
growth rate
(mm/dl
Average circulus
formation rate
(circuli/d)
Average circulus
spacing
(mm)
Juvenile fish, n=9
Grand average
1.33
0.0087
0.188
0.0460
Minimum
1.18
0.0080
0.175
0.0428
Maximum
1.52
0.0101
0.202
0.0494
SD
0.10
0.0007
0.008
0.0023
CV
7.6%
8.3%
4.1%
4.9%
Maturing fish, n = 17
Grand average
1.11
0.0060
0.131
0.0463
Minumum
0.94
0.0048
0.110
0.0426
Maximum
1.23
0.0066
0.144
0.0511
SD
0.07
0.0005
0.009
0.0020
CV
6.7%
8.1%
6.8%
4.4%
sured in any 10-day catch period. The average FLs
were averaged across all years of data, yielding grand-
average FLs for each 10-day catch period. The grand
average FL for each 10-day catch interval comprised
1-27 years of data, but those periods with fewer than 5
years of data were discarded. In all, FLs from 149,718
fish were used in the analysis. Grand average FLs and
the apparent growth rates in FL between each 10-day
catch period were plotted against date and compared
with the seasonal changes in circulus spacing at the
scale margin of the fish in our scale sample.
Results
Growth and scale statistics for juvenile and maturing fish
Average growth rates and circulus formation rates were
greater for juvenile fish during their first ocean summer
than for maturing fish during their entire ocean life
probably because maturing fish experience slow growth
in the winter (Table 3). During their first summer in
the ocean, juvenile fish grew an average of 1.33 mm/d
and formed circuli at the rate of 0.188/d (one every 5.3
days): whereas, during their entire ocean life maturing
fish grew an average of 1.11 mm/d and formed circuli
at the rate of 0.131/d (one every 7.6 days). The highest
average growth rate (1.52 mm/d) among the eight year
classes of juvenile coho salmon was about 28% higher
than the lowest average growth rate (1.18 mm/d). The
percentage range in growth rate of maturing fish was
similar (31%). Average spacing of circuli was similar for
both juvenile and maturing coho salmon (0.0460 mm vs.
0.0463 mm), probably because scales from the maturing
fish contained both more narrowly spaced circuli formed
during the winter and more widely spaced circuli formed
during the second ocean summer (see below). The varia-
tion among groups in average circulus spacing (CV=4.9%
and 4.4%) was lower than the variation in fish or scale
growth rates (CV=6.7% to 8.3%), although estimation
error may have increased the coefficients of variation
of the growth rates.
Correlations between scale characteristics
and growth rate
Circulus spacing was strongly correlated (r=0.89 and
0.82, respectively) with scale and fish growth rates
among the nine year classes of juvenile coho salmon
(Table 4). Circulus spacing was also significantly cor-
related with scale and fish growth rates among the
17 groups of maturing fish, but the correlations were
weaker (r=0.57 and 0.55, respectively) than those for
the juvenile fish. Conversely, correlations between the
rate of circulus formation and the scale and fish growth
rates were slightly higher for the maturing fish (r=0.85
and 0.75, respectively) than for the juvenile fish (r=0.76
and 0.81, respectively). These results suggest that when
growth is averaged over several seasons, during which
growth rate varies greatly and may even cease for vary-
ing periods of time, differences in growth among year
classes or groups may be reflected more clearly by dif-
ferences in the numbers of circuli laid down on the scale
than by differences in the average spacing of circuli.
Although the average spacing of circuli and the aver-
age rate at which circuli form were both correlated with
scale and fish growth rates, they were not correlated
with each other (Table 4). This finding indicates that
40
Fishery Bulletin 103(1)
circulus spacing and circulus formation rate are inde-
pendent indicators of growth rate — both tending to in-
crease with increasing growth rate but not necessarily
together in the same fish or in the same group or year
class. At least when averaged over periods of months or
more than a year, differences in average growth rate
may be expressed by differences in average spacing of
circuli, differences in average rate of circulus formation,
or differences in both.
Regressions of circulus spacing and formation rate
on growth rate
We expressed average spacing of circuli and rates of
circulus formation as power functions of the scale growth
rates, equivalent to linear regressions of ln-ln trans-
formed data. These regressions are shown in Figures
3 and 4 for year classes of juvenile fish and groups
of maturing fish, respectively. Because scale growth
rate and fish growth rate were very strongly corre-
lated (Table 4), we show only the regressions with scale
growth rate.
Change in average spacing of circuli and in average
rate at which circuli form was proportionally smaller
than the change in average scale growth rate. Aver-
age spacing of circuli was proportional to the average
scale growth rate raised to the 0.6 power (juvenile fish,
Fig. 3A) or the 0.5 power (maturing fish, Fig. 4A). If
these relationships hold over a wider range of scale
growth rate and circulus spacing, then a doubling of
scale growth rate would be associated with only a 1.5-
fold (20-6) or 1.4-fold (205) increase in circulus spac-
ing. Similarly, average rate of circulus formation was
proportional to the average scale growth rate raised to
the 0.5 power (juvenile fish, Fig. 3B) or the 0.8 power
(maturing fish, Fig. 4B).
Seasonal changes in circulus spacing and fish growth rate
Seasonal changes in average circulus spacing were con-
sistent among the different year classes and release
times of CWT coho salmon (Fig. 5, A-E). During the
first year in the ocean, average spacing of scale circuli
increased rapidly after OE (usually in May) to aver-
age peak values of about 0.050 mm-0.055 mm, then
gradually decreased to average minimum values of
about 0.031 mm-0.040 mm in the annual ring. By late
September 1999-2002, spacing at the margin of scales
from juvenile fish had decreased from peak values (Fig.
5E), indicating that the gradual decrease in spacing of
circuli which forms the annual ring begins as early as
the late summer of the first ocean year. For some year
classes (e.g., 82-83, 85-86, 90-91, 91-92) the annual
ring was a distinct narrow zone of very closely spaced
circuli (Fig. 5, A and C), whereas in other years the
annual ring was broad and subtle, with more widely
spaced circuli (e.g., 83-84, 86-87, and 84-85 for the
March released fish; Fig. 5, A and B).
After the annulus (black dots, Fig. 5), the spacing
of circuli increased sharply to peak values of about
Table 4
Correlations (r) between average circulus spacing (mmi,
average estimated scale growth rate (mm/d), average
estimated fish growth rate (mm/dl, and average esti-
mated circulus formation rate (circuli/d) between ocean
entry and late summer for nine year classes of juvenile
coho salmon and during the entire ocean growth period
for 17 groups of CWT maturing coho salmon (see Table
2). All correlations were significant (P<0.05), except were
noted ("n.s").
Comparison
Circulus spacing
vs. scale growth rate
Circulus spacing
vs. fish growth rate
Circulus spacing
vs. circulus formation rate
Scale growth rate
vs. fish growth rate
Scale growth rate
vs. circulus formation rate
Fish growth rate
vs. circulus formation rate
Juvenile
Maturing
fish
fish
r
r
0.89
0.57
0.82
0.55
0.38, n.s.
0.05, n.s
0.97
0.91
0.76
0.85
0.81
0.75
0.055 mm-0.060 mm and remained high for a vari-
able distance. Compared to the peak spacing, spacing
of circuli at the scale margin was relatively high for
maturing fish caught in late June or July 1982, 1984,
1985, 1986, 1987, 1991, and 2000, whereas, spacing at
the scale margin was quite low compared to the peak
spacing for fish caught in July 1983, 1989, 1990, and
1992 (Fig. 5, A, C, and D). Spacing at the scale margin
was very low among unmarked maturing fish caught in
late September 2001 (Fig. 5D).
Compared to the large interseasonal variation in
spacing of circuli in the pre- and postannulus zones,
from about 0.03 mm in the annual ring to about 0.06
mm for the most widely spaced circuli, interannual
variation the peak and minimum spacing of circuli was
quite small. The peak spacing of circuli was similar
among year classes, even when total growth differed
greatly (e.g., the 82-83 vs. the 81-82 and 83-84 year
classes, Fig 5A). The unusually small postannulus scale
growth of fish caught during a strong El Nino in July
1983 (Fig. 5A) was characterized by a much narrower
region of widely spaced circuli and more closely spaced
circuli at the scale margin than in other years.
In general, pre-annulus scale growth was greatest for
the fish released in March (Fig. 5B), was slightly less
for the fish released in late April or early May (Fig. 5A),
and was smallest for the fish released in late May or
early June (Fig. 5C). These data indicate that date of
release may strongly affect the amount of growth at-
Fisher and Pearcy: Seasonal changes in growth of Oncorhynchus kisutch off Oregon and Washington 41
Spacing = 0.839 ■ScaleCrouvthRate0 613 . n - 9. r= 0.88. I2 = 0.78
a)
E 020
0)
S> 017
CircRate= 2 03V ScaleGrowthRale0502 .n = 9, r=0.74, ^ = 0.55
0.007 0 008 0 009 0.010 0 011
Scale growth rate (mm/d)
Figure 3
Estimated average scale growth rate versus (A) average spac-
ing of ocean circuli and (B) estimated average rate of circulus
formation for nine year classes (see Table 2) of juvenile coho
salmon (O. kisutch) caught in the ocean in research nets in
August (1981) or September (1982-84 and 1998-2002; black
symbols, ±2 SE). Regressions are GM linear regressions of
In-transformed variables (presented in their power function
form).
tained by juvenile coho salmon during their first sum-
mer, fall, and winter in the ocean.
Do the seasonal changes in circulus spacing in the
ocean growth zones of scales coincide with similar sea-
sonal changes in growth rates of juvenile and maturing
coho salmon? In Figure 6 we plotted the average lengths
of juvenile and maturing coho salmon from all research
cruises 1981-2002 and the average apparent growth
rates of coho salmon during different seasons (dashed
lines). Apparent average growth rate of juvenile coho
salmon between June and September was 1.30 mm/d,
about twice the apparent growth rate of 0.64 mm/d
between September and the following May. Apparent
growth rates of maturing fish between late May and
late June was very rapid (2.11 mm/d), about twice as
great as the apparent growth rate of maturing fish later
between June and September (1.01 mm/d).
In a general sense, this pattern of changing apparent
growth rate over time in the ocean corresponds well to
the pattern of changing circulus spacing seen in Fig-
ure 5, A-E. The rapid growth of juvenile coho salmon
between June and September occurs during a period
when the spacing of circuli generally is high (Fig. 5E).
When maturing fish were caught in the ocean fisheries
in late June and in July and August a zone of widely
spaced circuli already was present on the scales (Fig. 5,
42
Fishery Bulletin 103(1)
E
E. 0050
Spacing =0 61 7'ScaleGrowthRate
□
A
o
o
Cowlilz.rel days 123-124
Fall Creek, rel. days 121-122
Fall Creek, rel days 74-76
Sandy, rel days 119-127
Sandy, rel days 151-157
0 0040 0 0045 0 0050 0 0055 0 0060 0 0065 0 0070 0.0075 0 0060
CircRate = 6 61 b' ScaleGrowthRate
n=17. /-=087, i2 = 0.75
B
0.0040 0.0045 0.0050 0.0055 0.0060 0.0065 0 0070 0.0075 0 0080
Scale growth rate (mm/d)
Figure 4
Estimated average scale growth rate versus (A) average spac-
ing of ocean circuli and (B) estimated average rate of circu-
lus formation for 17 groups (see Table 2) of maturing coho
salmon (O. kisutch) caught in the Oregon ocean fisheries
(±2 SE). Regressions are GM linear regressions of In-transformed
variables (presented in their power function form). Data for
Sandy Hatchery fish caught in 1983 and 1984 are labeled as
examples of year when average growth rates were extremely
different.
A-C), indicating that these widely spaced circuli were
produced earlier during the period of apparently rapid
growth in the spring and early summer (Fig. 6). Circu-
lus spacing at the scale margin was already declining
in July among maturing fish in some years (Fig. 5A),
and was clearly lower among maturing fish caught in
August or September (Fig. 5, B and D) indicating that
these more narrowly spaced circuli were produced some-
time during the apparently slower growth of maturing
fish between late June and September (Fig. 6). Finally,
the low spacing of circuli in the annual ring occurs
sometime between late September of the first year and
mid-May of the second year, which was also the period
of lowest apparent growth rate (Fig. 6).
The pattern of changing circulus spacing at the scale
margin is most clearly seen when average spacing of the
outer two circulus pairs is plotted against the average
Julian day of capture (Fig. 7, A and B). Among juvenile
fish caught in research nets, the average spacing of the
circuli at the scale margin was narrower in September
than in June (Fig. 7A, see also Fig. 5E). We lack suf-
ficient FL data from mid and late summer to deter-
mine whether or not a decrease in the average growth
rate of juvenile fish was associated with the observed
Fisher and Pearcy: Seasonal changes in growth of Oncorhynchus kisutch off Oregon and Washington
43
Late April-Early May release — July recovery
0 060 -
0.055 -
0.050
0.045 H
0.040
0.035
0.030
0.5
2.0
0 060
0.055
0.050
0.045
0.040 -
0.035 -
0 030
84-85. n = 27
85-86, n = 54
0.0
0.5
— I —
1.0
2.0
2.5
0060
0.055
0.050
0.045
0.040
0.035
0.030
1 1 1 1 1
00 05 1.0 1.5 20 25
Mean scale radius (mm, OE = 0)
Figure 5
Profiles of changing average circulus spacing (±2 SE) versus
average scale radius at 50 intervals along the axis of mea-
surement (see "Methods and Materials" section) for matur-
ing coho salmon (O. kisutch) caught in the ocean fisheries
and (A) released as smolts from hatcheries in late April
or early May and caught in July, (B) released in March,
(C) released in late May or early June and caught late
June to late July, (D) unmarked maturing fish caught in
research nets in June 2000 and September 2001, and (E)
juvenile fish caught September 1999-2002. For clarity,
error bars for the average scale radius at each interval
are not shown.
decrease in spacing of circuli at the scale margin in
September.
Among maturing fish, average spacing of the last two
circulus pairs at the scale margin decreased greatly
between the spring through early summer period and
early fall (Fig. 7B). The decrease in circulus spacing at
the scale margin during the summer occurred for both
maturing fish of mixed stocks caught in research nets
(gray and white symbols) and for CWT fish of known
stocks caught in the ocean sport and troll fisheries
(black symbols). The decrease also was very consis-
tent among year classes; 11 of the 12 year-class groups
(grouped by release period and pooled across hatcher-
ies) of Table 2 showed significant negative correlations
between spacing at the margin and date of capture
(P<0.05, r=-0.40 to -0.59). In September the aver-
age circulus spacing at the scale margin was about as
low as the average circulus spacing in the annual ring
(about 0.035 mm).
The decrease in spacing of circuli at the scale margin
over the summer mirrors a similar decrease over the
summer in apparent growth rates in FL of maturing
fish caught in research nets (Fig. 7C). The apparent
growth rates of maturing coho salmon were usually
44
Fishery Bulletin 103(1)
March release
0 065 -
0.060 -
0.055 -
0.050 -
0.045 -
0.040
0 035
■ 83-84, n = 24. 7/9 • 8/8 recovery
• 84-85. n = 15. 7/29 - 9/2 recovery
00
0.5
3.0
Late May-June release, June 19— July 19 recovery
F
fc
0.060 -
0.055 -
CO
0.050 -
in
in
0 045 -
-j
0.040 -
C )
~>
0.035 -
c
0.030 -
Surface trawl research: maturing fish
0 060 -
0.055
0.050 -
0.045
0.040
0.035
0 030
— 99-00. n= 78, 6/19-6/25 recovery
Y\ 00-01 , n = 50. 9/21 - 9/29 recovery
05 1.0 1 5 20
Mean scale growth (mm)
— i —
25
Surface trawl research: juvenile fish
E
b
0 060
en
c
0.055
ra
0.050
W)
0.045
0.040
o
0.035
c
0030
1999
„
= 60,9/21-
0/1 recovery
2000
n
= 75,9'19
9/24 recovery
2001
n
= 67. 9/21
9;27 recovery
2002
n
= 122,9/26
■ 9/30 recovery
0.2 0.4 0.6 08
Mean scale radius (mm, OE = 0)
Figure 5 (continued)
—\ —
1.0
higher between the May and June research cruises
(2-3 mm FL/d) than between cruises later in the sum-
mer (0.5-1.5 mm FL/d)(Fig. 7C, see also Fig. 6). The
concurrent decreases in spacing of circuli at the scale
margin and in apparent growth rate of coho salmon in
the ocean is consistent with the hypothesis that sea-
sonal changes in scale circulus spacing reflect seasonal
changes in fish growth rate.
Additional evidence for decreasing growth rate of
maturing coho salmon over the course of the summer
comes from FLs of CWT fish in the hook-and-line fish-
eries (sport and troll fisheries). Generally, apparent
growth rates in FL of maturing coho salmon originat-
ing from northern coastal Oregon streams and from
both the Oregon and Washington sides of the Columbia
river basin were highest from late May to mid-June and
Fisher and Pearcy: Seasonal changes in growth of Oncorhynchus kisutch off Oregon and Washington
45
700
600
500
400
300
200
0
1981
□
1982
A
1983
V
1984
O
1985
o
1998
□
1999
A
2000
V
2001
o
2002
From Ishida etal. 1998
1 30 mm/d
5/30 7/19 9/7
1 1 1
10/27 12/16 2/04
Date
-r
T"
3/25 5/15 7/03
— I 1 —
8/22 10/11
Figure 6
Average lengths (±2 SE) of juvenile and maturing coho salmon (O. kisutch)
caught during research cruises off Oregon and Washington in different
months and years (gray and white symbols. The dashed lines are linear
regressions and indicate apparent growth rates in FL between the differ-
ent catch periods. The late April 2000 sample of maturing coho salmon
was from a single trawl off the mouth of the Columbia River (Robert L
Emmett, NMFS/NWFSC/HMSC, 2030 S Marine Science Drive, Newport,
OR 97365. personal commun.). The small open circles are average lengths
(±2 SE) of coho salmon from Ishida et al. (1998) (their Appendix Table 6)
plotted against the 15th day of the months in which they were sampled.
decreased greatly by mid-August (Fig. 8, A and B). For
three periods, 20 May-29 June, 29 June-8 August, and
8 August-27 September, median apparent growth rates
were 1.43 mm/d (ra=19), 0.64 mm/d (re=24), and 0.24
mm/d (n=27), respectively.
Growth rates of fish from coastal Washington rivers
also decreased over the summer, but the decrease was
not as great as for the Oregon and Columbia River fish,
and the apparent growth rates of the Washington fish
were higher at comparable times during the summer
(Fig. 9, A and B). The apparent growth rates of Gray
Harbor basin fish were over 2 mm/d from late June
to mid- July and remained comparatively high (about
1.0 mm/d) into late October (Fig. 9B). Washington fish
generally were not caught in the fisheries until mid-
or late June, about a month after the first catches of
the Oregon and Columbia River fish. For three peri-
ods 19 June-29 July, 29 July-7 September, and 7 Sep-
tember-27 October, median apparent growth rates of
the coastal Washington fish were 1.23 mm/d (n=13),
0.92 mm/d (n = \Q), and 1.06 mm/d (n=9), respectively.
The growth data for CWT fish from the sport and
troll fisheries, especially those for the coastal Oregon
and Columbia River stocks, were consistent with the
growth data from the mixed stock catches of coho
salmon in research nets off Oregon and Washington in
that both data sets indicated a substantial decrease in
growth rate (FL) of maturing coho salmon between the
May-June period and the August-September period.
The decreases over the summer in circulus spacing at
the scale margin (Fig. 7B) and in apparent growth rates
of maturing CWT coho salmon of known origin (Fig. 8B)
is further evidence that scale circulus spacing and fish
growth rate are correlated seasonally.
Discussion
Our data indicate that the seasonal cycle of chang-
ing ocean circulus spacing on scales of juvenile and
adult coho salmon mirrors a similar seasonal cycle in
the growth rate of these fish. We lack direct data for
coho salmon collected between late September of the
first calendar year of ocean residence and mid-May
of the second calendar year, but growth rate during
part of the fall and winter may be as low as 0.5mm/d
46
Fishery Bulletin 103(1)
- 1 r-
Apr 30 May 20 Jun 9 Jun 29 Jul 19 Aug 8 Aug 28 Sep 17 Oct 7 Oct 27
0065
0 060
0.045
& 0.040 -
ro 0.035 -
0.030
B
Maturing fish
Apr 30 May 20 Jun 9 Jun 29 Jul! 9 Aug 8 Aug 28 Sep 17 Oct 7 Oct 27
□
A
Maturing fish
$ 2
o
Research purse seines
and
surface trawls
O
1981 mixed stocks
D
1982 mixed stocks
A
1983 mixed stocks
V
1984 mixed stocks
0
1985 mixed stocks
o
1998 mixed stocks
□
1999 mixed stocks
A
2000 mixed stocks
V
2001 mixed stocks
O
2002 mixed stocks
Oreg
on ocean fisheries:
■
Cowlitz (all years of Table 2)
•
Sandy (all years of Table 2)
A
Fall Creek (all years of Table 2)
Apr 30 May 20 Jun 9 Jun 29 Jul 19 Aug 8 Aug 28 Sep 17 Oct 7 Oct 27
Date
Figure 7
Average spacing of the last two intercircular spaces at the scale margin versus
average catch date for (Al juvenile coho salmon (O. kisutch) caught during research
cruises and (B) maturing coho salmon caught during research cruises (gray and
white symbols) and in the ocean fisheries (black symbols, averaged by 10-day
periods, all years combined). Also shown for comparison with the temporal changes
in circulus spacing are (C) the apparent growth rates of maturing coho salmon
between research cruises (based on changes in mean FL; see Fig. 6) plotted against
the mid-point of each growth period.
based on data in Ishida et al. (1998). Therefore, the
roughly twofold range in spacing of circuli in the ocean
growth zone of scales from maturing fish that we found
probably represents about a fourfold range in fish growth
rate in the ocean (from about 0.5 mm/d in the winter to
2.1mm/d in the spring and early summer). Thus, changes
in the spacing of scale circuli are relatively small when
compared to the corresponding changes in fish growth
Fisher and Pearcy: Seasonal changes in growth of Oncorhynchus kisutch off Oregon and Washington
47
LOCR Oregon 4/24 - 5/20 release
LOCR Oregon 5/21 • 6/14 release
LOCR Wash. 4/24 - 5/20 release
LOCR Wash. 5/21 -6/14 release
NOOR 3/01 - 3/31 release
NOOR 4/10- 5/10 release
Ape 30 May 20 Jun 9 Jun 29 Jul 19 Aug 8 Aug 28 Sep 17 Oct 7 Oct 27 Nov 16
B
T3
E
E
1 * v
* S . 2 9 ' ■ '
r * -
- ♦ ' ♦ to
T n a □
□
O ■ D
Apr 30 May 20 Jun 9 Jun 29 Jul 19 Aug 8 Aug 28 Sep 17 Oct 7 Oct 27 Nov 16
Date
Figure 8
(A) Grand-mean FLs (±2 SE) by 10-day intervals over the years
1975-2002 of CWT lower Columbia River (LOCR) Oregon and
Washington stocks and northern coastal Oregon stocks (NOOR)
of maturing coho salmon (O. kisutch). Only intervals with five
or more years of data are shown. (B) The corresponding aver-
age apparent growth rates between each 10-day interval. Note
the apparent decrease in growth rate between early and late
summer.
rate. However, the large seasonal changes in growth rate
of coho salmon in the ocean are readily detectable from
the changes in circulus spacing on the scale.
In June 2001, 2002, and 2003 average spacing of the
last two circulus pairs at the scale margin was positive-
ly correlated (P<0.01) with plasma IGF-I (insulin-like
growth factor-I) concentrations from juvenile fish caught
in the ocean in research nets (n=119, 163, and 206 and
r=0.52, 0.52, and 0.59 in 2001, 2002, and 2003, respec-
tively) (Beckman2 and Fisher, unpubl. data). Because
plasma IGF-I levels have been shown to be positively
2 Beckman, B. 2004. Unpubl. data. Integrative Fish Biol-
ogy Program, Northwest Fisheries Science Center, National
Marine Fisheries Service, 2725 Montlake Boulevard East,
Seattle, Washington 98112.
48
Fishery Bulletin 103(1)
correlated with instantaneous growth rates (in length)
of juvenile coho salmon (Beckman et al., 2004), the
finding that plasma IGF-I is also correlated with the
spacing of circuli at the scale margin of juvenile coho
salmon is further evidence that circulus spacing and
growth rate are positively related for coho salmon.
Our data suggest that growth rate in FL of matur-
ing coho salmon is usually highest between early or
mid-April and late June. This is a period of increasing
photoperiod and often rising sea-surface temperature
(SST) at 50°N in the northeastern Pacific Ocean, but is
well before the maximum SST in late August (Fig. 10).
Both increased day length and temperature stimulate
growth in salmonids (Brett, 1979; Bjornsson, 1997). The
750 -i
A I
700 -
xf]
p" 650 -
s
^^^
length
o
o
$r
Fork
o
w
—9- NWC 3/21 • 4/20 Release
500 ■
— O- NWC 4/21 - 5/25 Release
—A— GRAY 4/20 - 5/30 Release
450 -
—A— WILP 4/05 • 5/20 Release
Apr 30 May 20 Jun 9 Jun 29 Jul 19 Aug 8 Aug28Sep17 Oct 7 Oct 27 Nov 16
B
3 ■
(mm/d)
ro
A
A
A A
3
2
1 '-
CD
C
0)
a
a.
a. o -
<
• A A
o 6 a
A 8 . » • A A
8 ' ° •
0 A * A m
O
Apr30 May20 Jun 9 Jun 29 Jul 19 Aug 8 Aug 28 Sep17 Oct 7 Oct27 Nov 16
Date
Figure 9
(A) Grand-mean FLs by 10-day intervals over the years
1975-2002 of CWT coastal Washington stocks of matur-
ing coho salmon (O. kisuteh) from the Willapa Bay basin
(WILP), Grays Harbor basin (GRAY), and coast north of
Grays Harbor (NWC). (B) The corresponding average appar-
ent growth rates between each 10-day interval.
decreases in apparent growth rate in length of maturing
coho salmon after the summer solstice could be associ-
ated with a number of factors. One possibility is that
there is a shift during the summer away from skeletal
growth to growth in weight (with a resultant increase
in condition) or to gonadal development. Data in Ishida
et al. (1998) for coho salmon caught in research nets
in the North Pacific tend to support this proposition
(their Appendix Table 6). Their data indicate that the
rate of growth in FL of maturing coho salmon decreased
from 1.45 mm/d between April and May to 0.49 mm/d
between July and August. (See also Fig. 6, present
study). Over the same time period the condition index
(weight (g)x(107/FL[mm]3)) of the fish they sampled
increased from 113.3 to 143.8, an increase of 27%.
Thus, skeletal growth slowed over the summer, but
the condition of the fish increased.
In contrast to growth rates of Columbia River co-
ho salmon, which decreased greatly between early
and late summer, and were quite low (s0.5 mm/d)
by August and September, the growth rates of fish
from the Grays Harbor basin, although also declin-
ing during the summer, remained high well into
September and early October (-0.7-1.4 mm/d), al-
lowing the Grays Harbor fish to attain a significantly
larger final average FL. Several factors may result in
the differing growth patterns of maturing fish from
these two groups. Many of the fish from the Columbia
River are early spawners, and peak spawning occurs
from late October to early November, whereas the
Grays Harbor fish are mainly late spawners, and
peak spawning occurs from mid-November to late-
December (Weitkamp et al., 1995). Because of their
later spawning the Grays Harbor fish may shift from
somatic to gonadal growth later in the summer or
fall than do the earlier spawners from the Columbia
River. Maturing coho salmon from the Grays Harbor
drainage also have a much more northerly distribu-
tion than do maturing fish from the Columbia River
(Weitkamp and Neely, 2002) and, therefore, the two
groups encounter very different ocean conditions (e.g.,
temperature, salinity, prey fields, prey distributions,
and potential competitors for food) while feeding in
coastal waters. The different environmental condi-
tions experienced by the Columbia River and Grays
Harbor fish may also contribute to their differing
temporal growth patterns.
Because of the poor conditions for growth of fish
associated with the 1983 El Nino, adult coho salmon
in 1983 were exceptionally small off Oregon and
were in poor condition (Pearcy et al., 1985; Johnson,
1988). Our scale analysis indicates that the small
size of fish in 1983 was largely due to a failure of
growth of maturing fish after formation of the winter
annulus. Although the average scale radius between
OE and the winter annulus was slightly smaller for
the 1982-83 year class than for other year classes,
the average scale radius between the winter annu-
lus and the scale margin, representing the growth
of maturing fish in spring and early summer, was
Fisher and Pearcy: Seasonal changes in growth of Oncorhynchus kisutch off Oregon and Washington 49
16 -
14 -
~ 12 -
O
H
co
W 10-
8 -
Jr\
Day length (h)
CO (D "T CM O
4 SST ( °C )
™^~ Day length (hours)
Yearly
and ol
Point,
Canad
tions s
gc.ca/c
the pe
Jan Mar May Jul Sep Nov
Month (15th)
Figure 10
cycle of day length (sunrise to sunset; black line) at 50°N
sea surface temperature (SST) (°C; ±2 SE) at Amphitrite
Vancouver Island, B.C. SST data from Fisheries and Oceans,
a, Pacific Region, Science Branch, British Columbia lightsta-
alinity and temperature data, URL: http://www-sci.pac. dfo-mpo.
sap/data/lighthouse/amphitr.day. SST is the daily average for
riod 22 August 1934-31 July 1999.
exceptionally low for this year class (Fig. 5A). Circulus
spacing revealed two notable trends. First, in 1983
the maximum spacing of circuli following the winter
annulus was only very slightly lower than in other
years, which indicates that spring growth in FL of
maturing fish in 1983 was not unusually low. Perhaps
maturing coho salmon continued to grow in length in
spring 1983, when photoperiod was increasing rapidly,
despite low food availability. Bjornsson (1997) found
that changes in photoperiod may possibly control the
level of pituitary growth hormone (GH), which strongly
stimulates skeletal growth in salmonids and that in-
creased levels of GH can induce growth in length even
during starvation. Second, the spacing of circuli at the
scale margin for fish caught in July 1983 was unusu-
ally low. similar to the spacing at the scale margin
from fish caught in August of most years. This find-
ing indicates very slow growth rates for maturing fish
by July 1983. Length data1 for maturing CWT coho
salmon from the Oregon side of the Columbia River
basin caught in the ocean sport and troll fisheries
indicated that between June and September 1983
the average length of fish changed very little, which
would indicate that somatic growth ceased during the
summer.
Our results confirm the utility of circulus spacing
as an indicator of growth rate in FL of coho salmon
in the ocean. Correlations between average circulus
spacing and estimated average growth rates of groups
of fish were significant and positive (Table 4), even
when growth was measured over long intervals of time
(four to five months for juveniles, and over a year for
maturing coho salmon), and even when the estimates
of growth rate were subject to error In addition, our
data indicate large seasonal changes in growth rate in
FL of coho salmon in the coastal ocean off Oregon and
Washington, a result also suggested by data in Ishida
et al. (1998) for coho salmon in the North Pacific (see
Fig. 6), and these seasonal changes in growth rate ap-
pear to be tracked by seasonal changes in spacing of
scale circuli.
Acknowledgments
We thank all personnel from the Estuarine and Ocean
Ecology Division of the National Marine Fisheries Ser-
vice and from Oregon State University who participated
either in the research cruises or in processing samples
from those cruises. We also thank Lisa Borgerson of the
Oregon Department of Fish and Wildlife for supplying
scales from coho salmon caught in the ocean fisheries,
and the captains and crews of the FV Sea Eagle, FV
Ocean Harvester, FV Frosti and the RV Ricker for their
expert assistance during the cruises. Ric Brodeur and
Edmundo Casillas provided helpful comments on an
earlier version of this paper. This study was funded by
the Bonneville Power Administration through a grant to
the National Marine Fisheries Service and from NMFS
to Oregon State University.
50
Fishery Bulletin 103(1)
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52
Abstract — Metal-framed traps cov-
ered with polyethylene mesh used
in the fishery for the South African
Cape rock lobster (Jasus lalandii)
incidentally capture large numbers
of undersize (<75 mm CD specimens.
Air-exposure, handling, and release
procedures affect captured rock lob-
sters and reduce the productivity of
the stock, which is heavily fished.
Optimally, traps should retain legal-
size rock lobsters and allow sublegal
animals to escape before traps are
hauled. Escapement, based on lobster
morphometric measurements, through
meshes of 62 mm, 75 mm, and 100
mm was investigated theoretically
under controlled conditions in an
aquarium, and during field trials.
SELECT models were used to model
escapement, wherever appropriate.
Size-selectivity curves based on the
logistic model fitted the aquarium and
field data better than asymmetrical
Richards curves. The lobster length
at 50% retention (L50) on the escape-
ment curve for 100-mm mesh in the
aquarium (75.5 mm CL) approximated
the minimum legal size (75 mm CL);
however estimates of Z/50 increased to
77.4 mm in field trials where trap-
entrances were sealed, and to 82.2
mm where trap-entrances were open.
Therfore, rock lobsters that cannot
escape through the mesh of sealed
field traps do so through the trap
entrance of open traps. By contrast,
the wider selection range and lower
L25 of field, compared to aquarium,
trials ^SR = 8.2 mm vs. 2.6 mm;
L.,5=73.4 mm vs. 74.1 mm), indicate
that small lobsters that should be
able to escape from 100-mm mesh
traps do not always do so. Escape-
ment from 62-mm mesh traps with
open entrance funnels increased by
40-60% over sealed traps. The find-
ings of this study with a known size
distribution, are related to those of a
recent indirect (comparative) study for
the same species, and implications for
trap surveys, commercial catch rates,
and ghost fishing are discussed.
Escapement of the Cape rock lobster
(Jasus lalandii) through the mesh
and entrance of commercial traps
Johan C. Groeneveld
Marine and Coastal Management
5lh floor Foretrust Building
Martin Hamerschlacht Street, Foreshore
Cape Town, South Africa
E-mail address. Jgroenev<a>deat.gov.za
Jimmy P. Khanyile
National Research Foundation
P.O. Box 2600
Pretoria 0001, South Africa
David S. Schoeman
Department of Zoology
University of Port Elizabeth
Port Elizabeth 6031, South Africa
Manuscript submitted 20 March 2003
to the Scientific Editor.
Manuscript approved for publication
1 July 2003 by the Scientific Editor.
Fish Bull. 103:52-62 (2005).
The traps used in lobster and crab
fisheries are a versatile fishing gear
that can be modified to target specific
species and size ranges through choice
of design and bait (Miller, 1990). Selec-
tion by traps of only the desired size
classes reduces sorting time and may
increase the catch rates of legal-size
animals (Fogarty and Borden, 1980;
Everson et al., 1992; Rosa-Pacheco
and Ramirez-Rodriguez, 1996). Cap-
ture, sorting and release procedures
have furthermore been implicated in
accidental and stress-induced mor-
talities (Brown and Caputi, 1983;
1985; Hunt et al., 1986), as well as
in sublethal injuries, such as limb
loss (legs or antennae), which may
retard somatic growth (Davis, 1981;
Brown and Caputi, 1985). Air expo-
sure, even over short periods, can
induce behavioral changes such as
reduced responsiveness to threatening
stimuli (Vermeer, 1987) and lead to
higher predation risk among released
animals (Brown and Caputi, 1983).
Furthermore, displacement from
home reefs disrupts feeding behav-
ior and can affect growth increments
(Brown and Caputi, 1985). Manag-
ers of many crustacean trap fisher-
ies have responded to these problems
by introducing escape vents of vari-
ous sizes and shapes (Krouse, 1989;
Miller, 1990; Everson et al., 1992;
Arana and Ziller, 1994; Rosa-Pacheco
and Ramirez-Rodriguez, 1996; Treble
et al., 1998; Schoeman et al., 2002a),
because they successfully allow under-
size specimens to escape (Arana and
Ziller, 1994; Treble et al. 1998).
In fisheries management, size selec-
tivity curves are important for esti-
mates of incidental mortality, recruit-
ment in yield-per-recruit analysis,
and age- and length-based popula-
tion models (Millar and Fryer, 1999).
Notably, size selectivity can be used
to evaluate the minimum legal size
(MLS) and the effects of changing
escape vent or mesh size regulations
on the future productivity of the re-
source (Treble et al., 1998).
Most selectivity studies on which
mesh- or escape vent size are based
are comparative (indirect), imply-
ing that the size distribution of the
population is unknown and that
variants of the same gear type are
fished simultaneously (Millar and
Fryer, 1999). Results from indirect
studies can, however, be influenced
by trap soak times, trap saturation
effects (Miller, 1990), seasonal size
and sex-specific patterns in catchabil-
ity (Pollock and Beyers, 1979), and by
differences in morphometric ratios of
subpopulations (Fogarty and Borden,
Groeneveld et al.: Escapement of Jasus lalandn from traps
53
1980; Maynard et al., 1987). These disadvantages are
offset by the convenience with which indirect studies
measure selectivity under operational conditions. Far
fewer direct studies, in which the size distribution of
the fished population is known (Millar and Fryer, 1999),
have been published, and those that have been pub-
lished have included several laboratory studies where
the escape of crustaceans from traps was monitored
(Krouse and Thomas, 1975; Krouse, 1978; Everson et
al., 1992). Direct studies do not recreate true commer-
cial conditions, but rather provide a contact-selectivity
curve (or retention curve) that quantifies the difference
in length distribution between the catch and the popula-
tion offish coming in contact with the gear (Millar and
Fryer, 1999). This information is useful as a benchmark
against which operational, seasonal, and spatial selec-
tivity patterns can be measured.
Commercial fishing for the South African Cape rock
lobster (Jasus lalandii) originated in the late nine-
teenth century and reached its pinnacle in the 1950s,
when nearly 11,000 tons were landed annually (Pol-
lock, 1986). However, since then catches have declined
markedly, especially during the 1990s, when annual
catch restrictions based on the assumption of decreased
population strength, reduced the yield to 2000-3000
tons per year (Pollock et al., 2000). In response to
these operational changes, several recent modifications
have been made to the regulations governing gear used
in the fishery (Schoeman et al., 2002b). The changes
most pertinent to this study took place in 1984, when
mesh size was increased from 62 to 100 mm (stretched)
to reduce the relative catch of undersize J. lalandii
(Schoeman et al., 2002b), and during the early 1990s,
when the minimum size limit was reduced from its
historic level of 89 mm carapace length (CL) to 75 mm
CL (Cockcroft and Payne, 1999; Pollock et al., 2000).
Despite these two measures, the proportion of the com-
mercial catch <75 mm CL that has to be released re-
mains around 35-40% (MCM1). At present, the biomass
of the J. lalandii resource that is larger than the mini-
mum legal size is estimated at about 6% of its pristine
value, whereas the spawning biomass (of mature female
rock lobsters) is estimated to be 21% (Johnston, 1998).
Consequently, it is clear that the resource is heavily
depleted and that there is little scope for wasted produc-
tion through unnecessary damage to undersize lobsters
(Schoeman et al., 2002a).
Most studies on trap selectivity of J. lalandii (New-
man and Pollock, 1969; Crous, 1976; Pollock and Bey-
ers, 1979) predate the changes to mesh and minimum
legal size described above and did not provide selectiv-
ity curves. In the only recent study, Schoeman et al.
(2002a) used the SELECT (Share Each LEngth class's
Catch Total) method (Millar, 1992, Milllar and Walsh,
1992) to investigate the selectivity properties of vari-
1 MCM (Marine and Coastal Management). 2002. Unpubl.
data. MCM, Martin Hamershclacht St., Cape Town, South
Africa.
ous modifications to commercial and research traps in
comparison with the standard 100-mm stretched mesh
trap design. This study was indirect, in that it simu-
lated commercial fishing and compared catch rates in
other traps to those made with a small-mesh (62 mm,
stretched) trap, which acted as a control.
Several processes are involved in the selectivity of
traps: namely the attraction of rock lobsters by bait;
their ability to enter traps through trap openings of
various sizes, shapes, and localities within the trap;
their behavior in and around traps; their escapement
through the trap opening and their escapement through
mesh openings or escape vents (Miller, 1990). The pres-
ent study focuses on escapement of captured J. lalandii
through the mesh of stretched mesh traps and through
trap entrances. The aims are to investigate the relation-
ships between CL and other morphometric measures for
male rock lobsters in order to use these relationships
to estimate theoretical escapement curves for any given
mesh size; to compare these curves to observed escape-
ment rates through selected meshes in the aquarium;
and to extend these comparisons to field conditions. The
overall aim is to determine the optimum mesh charac-
teristics that maximize efficiency in targeting legal-size
male J. lalandii.
Material and methods
Mesh size of lobster traps
Mesh size is defined as the measurement from inside
of knot to inside of knot when the net is stretched in
the direction of the long diagonal of the meshes, i.e.,
lengthwise of the net. Netting is made of polyethylene.
Commercial rock lobster traps (Fig. 1) are covered with
100-mm stretched mesh (or 50-mm bars, also measured
from the insides of knots), which are stretched in such
a manner over the metal frame that the openings are
square.
Morphometric variables measured
Following manual trials that involved fitting lobster car-
apaces of different sizes through an adjustable square
hole, three carapace dimensions were identified as likely
to play a role in regulating escapement. These were the
following: 1) carapace width (CW), measured laterally,
across the widest point of the carapace; 2) carapace
depth (CD), measured dorsoventrally, extending from
the highest point of the dorsal carapace surface to
the lowest point on the ventral surface of the thoracic
plate; and 3) carapace base (CB), measured ventrally,
between the distal edges of the second segment of the
last walking legs, with the legs folded flush against
the carapace.
Each of these dimensions was measured (±1 mm) for
each of 169 male rock lobsters caught in research traps
deployed off the Cape Peninsula between 1999 and
2002. Corresponding data regarding carapace length
54
Fishery Bulletin 103(1)
Figure 1
(A) Standard metal-framed traps (0.8 m x 0.5 mxl.35 m high) covered with
stretched polyethylene mesh used in the commercial fishery for J. lalandii
and during field experiments (note the 100-mm mesh size covering on the com-
mercial traps, and the 62-mm mesh size on the codend and entrance funnel).
(B) Metal-framed escapement cages covered with 62-mm (shown), 75-mm, and
100-mm mesh used in the aquarium experiments (frames were 0.6 mx0.6 m,
with a depth of 0.25 m).
(CL), measured mid-dorsally from the posterior edge
of the carapace to the anterior tip of the rostral spine,
were also collected. This was done because CL is the
dimension most frequently mentioned in legislation
pertaining to this species (Schoeman et al., 2002b) and
has therefore been the focus of most size-based studies
(Newman and Pollock, 1969; Pollock and Beyers, 1979;
Schoeman et al., 2002a). Relationships between the CL
and each of CW, CD, and CB were explored by using
simple least-squares regression analyses.
Theoretical calculations of escapement
In order to investigate morphological characteristics that
physically limit escapement through meshes of various
dimensions as a function of CL, digital photographs were
taken of the posterior cross section of 46 male carapaces
(tail removed) covering a range of sizes between 40 mm
CL and 106 mm CL. Using standard graphics software,
we superimposed a square on each image to represent
a square of polyethylene mesh, similar to that used in
a South African rock lobster trap.
This simulated mesh was orientated so that its base
was parallel with the carapace base of the lobster under
consideration. It was then proportioned so that each of
its sides was equal in length to the corresponding CB.
Once this procedure had been completed, the simu-
lated mesh square was rotated and resized so that we
could determine the dimensions of the smallest square
through which each lobster could pass. This measure
was designated the "critical mesh size" for that image.
Critical mesh size was related to CL by using simple
linear regression analysis. In this way, the theoretically
appropriate mesh aperture required to target all lobster
larger than a given size could be predicted from the
minimum CL of the target group (for convenience, this
CL will be designated the "critical CL").
Aquarium trials
Having addressed the matter of whether or not lobsters
theoretically should be able to escape a mesh of given
dimensions, the next question to be posed is whether or
not they can do so under ideal (laboratory) conditions?
For these purposes, three stretched mesh sizes were
considered: 1) 62 mm, which coincides with the mesh
size used in the commercial fishery prior to 1984 and
also with the mesh currently used on traps deployed
in the Fishery Independent Monitoring Survey (FIMS)
(Schoeman et al., 2002a); 2) 100 mm, which corresponds
with the mesh currently used on commercial traps for
J. lalandii; and 3) 75 mm, which was used to provide
Groeneveld et al.: Escapement of Jasus lalandu from traps
55
information on selectivity for meshes of intermediate
aperture dimensions.
Each of these experimental meshes was used to con-
struct an escapement cage by stretching the mesh over
a mild-steel frame in order to present square escape
apertures of varying dimensions, as determined by
the size of the mesh used (Fig. 1). These cages were
deployed in an aquarium tank measuring 1.8 mxl.8
m and having a depth of 1.5 m. Fresh sea water was
continuously supplied to this tank by a through-flow
system that regulating water temperature between 12°
and \&°C, well within the natural temperature range of
J. lalandii (Heydorn, 1969).
For each mesh size, male rock lobsters of various
carapace lengths (373 lobsters measuring 34-91 mm CL
for 62-mm mesh; 351 lobsters measuring 34-75 mm CL
for 75-mm mesh; and 142 lobsters measuring 70-91 mm
CL for 100-mm mesh) were collected live from the sea
and transported to the experimental aquarium tank.
Care was taken to ensure that approximately equal
numbers of lobsters were available for each 2-mm size-
class within the respective size ranges, although fewer
lobsters tended to be available in size classes towards
the ends of the frequency distributions.
Once at the aquarium, lobsters were placed inside
the experimental cages in groups of up to 20 and left
for 30 minutes. Individuals that did not escape during
this period were gently pushed towards the mesh open-
ings, encouraging escapement, where this was possible.
Subsequently, the CL frequency distributions were de-
termined both for those lobsters that escaped the mesh
as well as those that were retained. Several replicate
escapement experiments were conducted for each mesh
size, but because the experimental cages were too small
to hold large numbers of lobsters, replicate selection
curves could not be computed. Instead, all data were
pooled for each mesh size for further analyses.
Field trials
The final question to be posed is whether or not lobsters
do escape from traps when afforded the opportunity to
do so under field conditions? To address this problem,
field trials were undertaken off the Western Cape Pen-
insula during monthly sampling sessions conducted by
the research vessel Sardinops in July 2000 and from
December 2001 to March 2002— a total of five distinct
sampling surveys.
Four categories of standard rock lobster traps (Fig.
1) were employed: 1) 62-mm stretched mesh, with en-
trance funnels open; 2) 62-mm stretched mesh, with en-
trance funnels blocked by a fine-mesh insert; 3) 100-mm
stretched mesh, with entrance funnels open; and 4) 100-
mm stretched mesh, with entrance funnels blocked.
Duplicate bottom long-lines consisting of 10 traps
each were prepared, of which six were normal commer-
cial traps, and the remaining four were experimental
traps, and these 10 traps were spread in haphazard
order along the line, excluding the end traps. Into each
trap was placed a sample of approximately 40 male rock
lobsters, each of which had been measured (CL) and
marked by cutting a notch in its uropod. In this way,
it was possible to distinguish between lobsters that had
been placed in the trap and those that had entered the
trap of their own accord.
Experimental traps were deployed without bait, in
order to limit their ability to attract lobsters and also
to remove one of the prime incentives that captive lob-
sters might have to remain in a trap, even when it
could escape. These trap lines were soaked overnight
and on their retrieval, each remaining lobster was re-
measured (CL) and inspected to identify specimens that
had entered the traps voluntarily. Eight replicates were
completed for each of the four categories of traps.
Construction of selectivity curves
The contact-selection curves (sensu Millar and Fryer,
1999) for the meshes used in the laboratory and field
trials were modeled by using the SELECT method
(Millar and Walsh, 1992) as applied to covered codend
experiments (Millar and Fryer, 1999). We felt that this
approach was warranted because we collected data with
respect to lobsters in both a "codend" (those retained
in the traps) and a "cover" (those that escaped, but for
which data were available by inference).
The logistic and Richards formulations of the general
selectivity curve were fitted by using Excel (Microsoft,
Redmond, WA) routines (Tokai2). These two selectivity
functions were chosen because of their relative simplic-
ity, their broad use over a range of different fisheries,
and the availability of estimation routines for their
parameters (Millar and Fryer, 1999).
The Richards curve has the equation
r(l)
( exp(a+b,
(l + exp(a +
bl)_
bl)
where r(l) is the probability that an individual of length
I attempting to pass through a mesh of given size will
be retained by it (Millar and Fryer, 1999); and a, b, and
5 are constants. The logistic curve is the special case of
this formulation, where 5=1.
According to these models, the lobster length at 50%
retention (L50) and the selection range {SR=L75-L25)
are defined as follows:
In
0.5"
1 - 0.5'
simplifying to L50 = - — when 5 = 1, and
b
: Tokai, T. 2002. Personal commun. Department of Marine
Science and Technology, Tokyo University of Fisheries, Konan
Minatoku, Tokyo 108, Japan.
56
Fishery Bulletin 103(1)
In
SR =
0.75°
1-0.755
In
0.25')
1-0.2515
simplifying to SR = — - — , when <5 = 1.
All calculations were made on the basis of 2-mm-CL
size classes covering the entire size range for each fre-
quency distribution. The 2-mm-CL size classes were
used to ensure consistency across models, and also
to balance data resolution against the number of size
classes expected to have either zero catch or zero escape-
ment (Millar and Fryer, 1999). Wherever necessary,
hypothesis tests were conducted in accordance with the
recommendations of Millar and Walsh (1992) and Millar
and Fryer (1999).
Results
Morphometric relationships
Least-squares regression analysis indicated highly sig-
nificant linear relationships between CL and each of
the other morphometric variables measured (Fig. 2). In
each case, at least 97% of the variability in the predic-
tor variable was explained by CL, indicating a high
degree of correlation among predictors. Nevertheless, for
any given CL, CB was consistently the largest variable
measured, whereas CD was the smallest. Furthermore,
CB increased more rapidly in response to increasing CL
than either CW or CD (ANCOVA: F=115.165; df=2, 167;
P<0.001). We therefore concluded that CB would likely
be the morphometric variable that limits escapement
through stretched square meshes.
100-1
o CW (mm) = 0-74 x CL (mm) - 4 45 rmn
go-
r2=0.98; n=169; P< 0.001
• CD (mm) = 0.61 x CL (mm)- 16.74 mm
's? 80-
E
tn 70-
o
? 60 ■
CO
Q 50-
O
3 40-
o
r2= 0.97; n= 169; P< 0.001 m^
• CB (mm) = 0 80 x CL (mm) - 2.25 nrm ■ ■^■"o *
r*= 0.98; n = 169; P< 0.001 miM^^ \^S^^
JV>' Jfty^T^ _»Sw/»
30
40 50 60 70 80 90 100 110
CL (mm)
Figure 2
Individual linear relationships between carapace length (CL) and
each of carapace width (CW), carapace depth (CD), and carapace
base (CB) for J. lalandii.
Theoretical calculation of escapement
The mesh size that appeared (on the basis of visual inspec-
tion) to limit escapement was expressed as a function of
CL with a simple, linear, least-squares regression model
(Fig. 3). This relationship was highly significant and
explained 99% of the variability in critical mesh size.
Using inverse prediction methods (Zar, 1999), we
calculated the critical CL (mean ±95% confidence inter-
val) from the regression model illustrated in Figure 3
for any mesh size. For 62-mm mesh, the critical CL is
estimated at 43.8 (±4.12) mm; for the 75-mm mesh the
estimate is 52.3 (±4.15) mm; whereas for the 100-mm
mesh it is 68.7 (±4.12) mm. Given the implicit assump-
tion that lobsters smaller than the critical CL can es-
cape, but that larger lobsters are retained, the mean
critical CL can be used as an estimate of L50.
Aquarium trials
No lobsters larger than 48 mm CL escaped the 62-mm
mesh traps in the aquarium and none smaller than
44 mm CL were retained. This finding resulted in an
extremely steep selection curve with a narrow SR (Fig.
4; Table 1). For the 75-mm mesh, no lobsters larger than
61 mm CL escaped and no lobsters smaller than 54 mm
CL were retained. This finding resulted in a slightly
more gentle selection curve, but with a reasonably tight
SR (Fig. 4, Table 1). Similarly, for the 100-mm mesh, no
lobsters larger than 79 mm CL escaped and no lobsters
smaller than 74 mm CL were retained. This finding
resulted in a selection curve that closely resembled that
for the 75-mm mesh, except that the curve shifted a few
size categories to the right (Fig. 4; Table 1).
For all meshes, the symmetrical logistic model was se-
lected in preference to the asymmetrical Richards model
(Table 1), and in all cases the selected model fitted
the data reasonably well (Fig. 4). It should,
however, be noted that all hypothesis tests
were conducted by using the deviance residu-
als and their degrees of freedom for all size
classes sampled. This was necessary because
the very tight selection curves (especially for
the 62-mm mesh) resulted in relatively small
numbers of size classes in which retention
probability was neither zero nor one.
The above results indicate that L50-esti-
mates for each mesh size are substantially
larger than the corresponding estimates of
critical CL from the theoretical escapement
model. In fact, assuming that the asymptotic
standard errors provided in Table 1 could be
converted to 95% confidence intervals by a
multiplication factor of two, only the confi-
dence intervals for these statistics from the
62 mm mesh would overlap. By contrast, con-
fidence intervals for the critical CL are well
below those for the L50 for both the 75 mm
mesh and the 100-mm mesh. This impression
is confirmed by inspecting the probabilities of
Groeneveld et al.: Escapement of Jasus lalandu from traps
57
Table 1
Statistics from SELECT
analysis for the aquarium escapement trials. Values
in parentheses are
asymptotic standard errors
sensu Millar
(1993). The
^e standard errors are provided
only for the best model fits for each of the various categories of data.
Note that all
hypothesis
tests were cond
ucted by using deviance residual
3 for the full model and their degrees of freedom (see
text for explanation).
62-mm
mesh
75
mm
mesh
100-mm
mesh
Logistic
Richards
Logistic
Richards
Logistic
Richards
a
-76.479
(23.159)
-351.538
-58.217
(10.079)
-400.075
-64.101
(11.655)
-41.224
b (/mm)
1.649
(0.500)
7.463
0.991
(0.173)
6.589
0.849
(0.155)
0.615
o
6.567
13.173
0.010
L50 (mm)
46.389
(0.309)
46.493
58.717
(0.302)
59.333
75.459
(0.376)
75.144
SR (mm)
1.333
(0.404)
0.989
2.216
(0.386)
2.200
2.587
(0.471)
2.567
Selection factor
0.75
0.78
0.76
H0: data have binomial d
stribution (i.e..
data are not overdispersed)
Deviance
0.802
0.209
1.984
1.092
8.675
6.435
df
27
26
19
18
12
11
P-value
1
1
0.999
0.728
0.730
0.843
ff0:6=l
Deviance
0.593
0.892
2.240
df
1
1
1
P-value
0.441
0.345
0.134
retention, r(l), by each mesh size of a lobster at its cor-
responding mean critical CL. For the 62-mm mesh this
probability is 0.014 (0.926 at the upper 95% confidence
limit for the critical CL); for the 75-mm mesh it is 0.002
(0.096 at the upper 95% confidence limit for the critical
CL); and for the 100-mm mesh it is 0.003 (0.099 at the
upper 95% confidence limit for the critical CL).
Field trials
Escapement from traps with 62-mm mesh was highly
variable both for the traps with entrance funnels left
open, as well as for those with entrance funnels that
were sealed, but was surprisingly high for the latter
(Fig. 5). Furthermore, it is clear that the relationship
between proportion of lobsters retained and CL was
not logistic, as it was for the larger mesh sizes (Figs.
5 and 6). Instead, simple, least squares regression
analysis indicated linear relationships between these
variables both for traps with open entrance funnels as
well as for those with entrance funnels closed (Fig. 5).
There was no difference between the slopes (r=1.138;
df=10; P=0.282; common slope = 0.795/mm), although
their intercepts did differ significantly (r=14.079; df =
11;P«0.001).
170 -
g 150 -
Mesh size (mm) = 1 .53 x CL (mm) - 5.07 mn •
r 2 = 0.99; n = 46; P=< 0.001 ^^
8 130-
*f^^
01
• fcAt
M 110 -
_ 90 -
to
o
■■£ 70 -
O i
>_^*
40 SO 60 70 80 90 100 110
CL(mm)
Figure 3
The relationship between carapace length of J. lalandil
and mesh size below which escape should theoretically
not be possible.
No lobsters smaller than 62 mm CL were retained
in the 100-mm mesh traps with open entrances, and
no upper size limit was reached beyond which escape-
ment was completely eliminated. By contrast, when the
entrance funnels to the traps were sealed, no lobsters
smaller than 64 mm CL were retained and no lobsters
58
Fishery Bulletin 103(1)
1.0 1
o 8
0.6
0.4
0.2-
0.0
30
90 100
T^
I.O-i
<u
c
CO
0.8-
0)
OB-
r
g
(14
o
n
112-
LL
00-
30 40 50 60 70 80
1.0-1
30 40 50 60
0.4
0.0
B
n
-0.4-1
34.5 38.5 42.5 46.5 50.5 54.5 58.5 62.5 66.5
1.0 i
00
D
~n
Ji
-0 5-1 —
34 5 38 5 42 546 550 554 558 562 .566.570.574.5
625 66.5 70.5 74 5 78 5 82.5 86 5 90 5
CL (mm)
Figure 4
Fitted selectivity curves from the selected models (identified in Table 1) and their deviance
residuals for a range of stretched square meshes under aquarium conditions. A and B are
for 62-mm mesh, C and D are for 75-mm mesh and E and F are for 100-mm mesh.
52 57 62 67 72
CL-class mid-point (mm)
Figure 5
Relationship between proportion of rock lobsters retained
by 62-mm mesh trap and carapace length (aggregated
into 5-mm size classes). Filled circles represent data
from traps with entrance funnels sealed [Proportion
retained = 0.58/mmxCL (mm) + 48.35; r2 = 0.79; n=l\
P= 0.008), whereas open circles represent data from traps
with entrance funnels open {Proportion retained = 1.0l/
mmxCL (mm)-38.94; r2 = 0.62; n = l\ P=0.036).
larger than 84 mm CL escaped. This resulted in contact
selectivity curves for which estimates of both L50 and
SR decreased when captive lobsters were denied the op-
portunity to escape through the entrance funnels (Fig.
6; Table 2). This finding indicates that considerable
numbers of lobsters of all sizes can escape commercial
traps by the entrance funnels.
Irrespective of whether the entrance funnels of the
traps was sealed, the symmetrical logistic model was se-
lected in preference to the asymmetrical Richards model
(Table 2), and the selected model fitted the data reason-
ably well (Fig. 6; Table 2), although not as well as the
models fitted to the aquarium data (Fig. 4; Table 1).
In comparison with the selectivity curves from the
aquarium trials with 100-mm mesh, the corresponding
curves from field trials indicated that greater numbers
of larger lobsters are retained in practice than under
laboratory conditions (Figs. 4 and 6). This finding in-
dicates that some lobsters are retained in commercial
traps, even though they can escape, which goes some
way to explaining the more "scattered" fit of the logistic
model compared to the field data.
Groeneveld et al.: Escapement of Jasus lalandii from traps
59
1.0
08
. • 3.0 1
A V^ 2.0
B
0.6
0.4
/ • 1.0-
% 00'
/ -1.0
""■' '| "I" I
0-2
/' -2.0-
a> 00
•rf.-*^
§ 30 40 50 60 70 80 90 100 53.5 63.5 73.5 83.5 93.5
c
o
o
§■ 1.0 1
0.8
C «*<- ao,
*/ 20
D
0.6
0.4
/ 1"°
/• 0.0
•7 -i.o
■ III 1 1 1 !■■
■ i| I |"| |
0.2
y* -2 0
30 40 50 60 70 80 90 100 53.5 63.5 73.5 83.5 93.5
CL (mm)
Figure 6
Fitted selectivity curves from the selected models (identified in Table 2) and their deviance
residuals for escapement of -7. lalandii from commercial rock lobster traps covered with 100-mm
stretched square meshes under field conditions. A and B are for traps with open entrance
funnels; C and D are for traps with sealed entrance funnels.
Discussion
This study focuses on escapement of Cape rock lobster
(J. lalandii) through mesh openings, and on escape-
ment through the trap entrance of commercial traps.
Three questions were initially posed, namely: through
what mesh size, in theory, can a lobster of given CL
escape; are lobsters physically able to escape through
this theoretical mesh size, or are there other factors such
as orientation and mobility of lobster appendages that
prevent escapement; and what proportion of sublegal
and legal size lobsters escape through the mesh and
trap entrance of commercial traps? In brief, the results
showed a weak leak between theoretical values and the
ability of the lobsters to escape.
Carapace base (CB) was isolated as the dimension
most likely to limit escapement through stretched
square meshes. This dimension superceded carapace
width and depth, which have been more widely assumed
to be the limiting factors to escapement of lobsters
(Treble et al., 1998), mainly because our measurement
included the width of the last pair of walking legs,
folded flush against the carapace. Experimenting with
lobster carapaces and an adjustable square hole showed
that the joints of these appendages protrude ventrolater-
al^ from the carapace, and the orientation and limited
mobility of these appendages would prevent the lobster
from escaping. Nevertheless, our theoretical escapement
model included all three measurements in the underly-
ing computer simulations to determine the appropriate
mesh aperture required to target all lobsters larger
than a given size.
The theoretical escapement model produced surpris-
ingly small values of "critical CL" for all three mesh
sizes in comparison with the corresponding selectivity
curves from the aquarium experiment. This result im-
plies that many rock lobsters that should theoretically
not have been able to escape, did so in the aquarium
trials. We therefore concluded that the theoretical model
was weak and that the mechanics of escapement ap-
pear to be more complex than can be shown by simple
measurements of the carapace dimensions and may rely
also on the orientation of lobsters during escapement
(Stasko, 1975).
Selectivity curves developed from aquarium data in-
dicated that an 85-mm-CL lobster should not have been
able to escape a 100-mm mesh trap. However, field data
indicated that escapement from 100-mm mesh traps
with sealed trap openings exceeded 10%. Thus, rock
lobsters that should not have been able to escape, ac-
cording to aquarium experiments, did escape under
field conditions. This result was expected, because the
mesh of traps used in the commercial fishery (and field
experiments) is often unevenly stretched across the met-
al trap-frame, and therefore some openings lose their
square dimensions. This unevenness in the stretch of
the mesh was clearly illustrated by a random sample of
40 knot-to-knot aperture measurements from four 100-
mm mesh commercial traps, which had diagonal dimen-
sions significantly larger than the 70.71 mm predicted
60
Fishery Bulletin 103(1)
by Pythagoras's theorem (r=4.470; df =39; P«0.001).
In addition, repairs to torn meshes often leave openings
that are somewhat larger than 100 mm and that are not
square (Groeneveld, personal, observ. ). The wider SR of
the selectivity curve for field data compared to the tight
SR of the aquarium curves supports this "unevenly
stretched mesh" hypothesis.
Paradoxically, a 70-mm-CL lobster, which has a 1%
chance of being retained by a 100 mm mesh in the
laboratory has an 11% probability of being retained by
a trap with the same mesh in the field (even when its
entrances are sealed). Thus, some rock lobsters that
should, and could have escaped through the 100 mm
mesh of the field traps did not. Schoeman et al. (2002a)
suggested that small rock lobsters that can escape do
not always do so because they use the trap as a refuge
against predators. Alternatively, overnight soak times
(as used in the field trials) may be too short for all
the small rock lobsters to escape. The probability of
Table 2
Statistics from SELECT analysis for the field escapement
trials. Values in parentheses are asymptotic standard
errors sensu Millar (1993). These standard errors are
provided only for the best model fits for each of the vari-
ous categories of data. Note that all hypothesis tests were
conducted by using deviance residuals for the full model
and their degrees of freedom (see text for explanation).
100-mm mesh
100-mm mesh
Trap-entrance
open
Trap-entrance
sealed
Logistic
Richards
Logistic
Richards
a
-17.856
(2.460)
-14.299
-20.801
(2.437)
-51.967
b (/mm)
0.217
(0.031)
0.181
0.2686
(0.031)
0.626
6
0.641
4.238
L50 (mm)
82.274
(0.379)
82.222
77.444
(0.379)
78.458
Si? (mm)
10.124
(0.498)
10.809
8.181
(0.498)
7.997
Selection factor
0.82
0.77
H0: data have binomial distribution
(i.e., data are not overdispersed)
Deviance
21.593
21.257
18.698
15.807
df
19
18
17
16
P-value
0.305
0.267
0.346
0.467
ff0:S=l
Deviance
0.336
2.891
df
1
1
P-value
0.562
0.090
escape is much reduced during hauling because captive
specimens are then pressed into a tight mass within the
fine-mesh (62-mm) codend of the trap.
No escapement from sealed 62-mm mesh traps was
expected during field trials, based on the aquarium
L50 of 46.4 (±0.3) mm and the size range of lobsters
used in the field (60 mm-95 mm CL). Nevertheless,
small losses (0-18%, depending on lobster size; see
Fig. 5) did occur. Only two explanations are possi-
ble, namely: 1) that lobsters still managed to escaped
through the mesh of the sealed 62-mm traps, despite
precautions taken to ensure that the meshes of these
traps were undamaged and that trap openings were
properly sealed; and 2) that some individuals sus-
tained injuries during exposure and handling, and
subsequently were cannibalized by the healthy rock
lobsters in the traps. This second conclusion is sup-
ported by the presence of shell fragments observed
in traps after their retrieval. Because these regres-
sions had the same positive slopes, it seems likely
that smaller rock lobsters would be more susceptible
to injury and cannibalism than larger animals, and
their susceptibility holds irrespective of whether the
trap entrance is sealed or not.
Escapement from 62-mm mesh traps with open en-
trance funnels increased by 40-60% compared to es-
capement from traps with sealed traps (Fig. 5). This
finding has significant implications for the FIMS, which
relies on catches made by 62-mm mesh traps and is con-
ducted annually as a measure of the relative abundance
of the J. lalandii resource. During a survey, it is as-
sumed that all the Cape rock lobsters that are captured
are retained and that trap-selection is uniform across
all the size classes of these lobsters (Johnston, 1998).
It appears that neither of these two assumptions can
be met: significant escapement does occur through the
trap entrance and there is a greater retention of larger
specimens than smaller specimens .
When the trap entrance was left open in the 100-
mm mesh field trials, L50 increased to 82.3 mm (from
77.4 mm in sealed traps), thus indicating that captive
Cape rock lobsters can and do use the trap entrance of
commercial traps to escape. The open traps also have
a wider SR of 10.1 mm (compared to 8.2 mm in sealed
traps), and therefore animals with a CL of >87 mm
(L75=87.3 mm), which are very unlikely to be able to
get through the mesh apertures, will still be able to use
the trap entrance to exit. The presence of this escape
vent implies that there is little danger of ghost-fishing
when using this trap type and that Cape rock lobsters
of all sizes should be able to vacate the trap once the
bait has been consumed. From a commercial viewpoint,
however, the problem of leaving traps in the water for
too long is that legal-size specimens, which cannot fit
through the mesh, will escape through the entrance,
thus decreasing catch rates considerably.
The aquarium result (L50=75.1 mm) is considered
the most accurate direct measurement of the selectiv-
ity of 100-mm square mesh for J. lalandii, because
care was taken to ensure that the mesh was stretched
Groeneveld et al.: Escapement of Jasus lalandu from traps
61
evenly with square openings across the metal trap-
frame and because we made sure that all lobsters
that could escape, did, resulting in a tight SR of 2.6
mm. This L50 is remarkably close to the present MLS
of 75 mm CL for the commercial fishery, especially
considering that 100-mm mesh was first used when
the MLS was 89 mm CL, and that the commercial
mesh size remained at 100 mm despite the 14 mm CL
reduction in MLS during the early 1990s (Schoeman
et al., 2002b). The L50 obtained from the field trials
with sealed trap openings (77.4 mm) was also close to
the present MLS.
In a recent indirect study (i.e., where the size com-
position of a population was unknown) Schoeman et al.
(2002a) found L-0 to be 79.2 mm (SJR=11.1 mm) under
commercial operational conditions. The increase in L50
(above the 75.1 mm and 77.4 mm found in the direct
aquarium and field studies, respectively) is the result of
the trap entrances of commercial traps remaining open,
so that rock lobsters that are too large to fit through
the mesh can still escape through the entrance. In the
present direct study, this factor increased the L50 from
77.5 mm (sealed entrance) to 82.2 mm (open entrance)
for 100-mm mesh. Thus, one conclusion of the indirect
study, namely that the South African fishery for J.
lalandii is unusual in that standard commercial traps
are covered with mesh having an aperture considerably
wider (L50=79.2 mm CL) than that required to retain
Cape rock lobsters of the current MLS (Schoeman et
al., 2002a), must now be seen in a different light. The
selectivity of the 100-mm stretched mesh itself now
appears not to be wider than that which is currently
required (based on the direct results). Rather, the indi-
rectly determined L50 appears to have been inflated by
the numbers of larger lobsters that were able to escape
through the trap entrance.
Direct studies of the escapement of crustaceans from
pots (Krouse and Thomas, 1975; Krouse, 1978; Everson
et al., 1992) have often been criticized because these
studies themselves may affect the behavior of the ani-
mals and do not include the dynamics of the processes
of entry and escapement (Xu and Millar, 1993; Treble
et al., 1998). We recognize these weaknesses, but felt
that direct studies remain useful because they can be
used to set a theoretical benchmark against which the
results of indirect studies can be tested, especially if
the trap selectivity of the latter depends on area and
season. Various insights were gained from the pres-
ent study, particularly because it closely followed an
indirect study of trap selectivity for J. lalandii (Schoe-
man et al., 2002a). In conclusion, this study of escape-
ment of J. lalandii through square meshes showed 1)
that 100-mm mesh size is, theoretically, near optimal
for the fishery; 2) that many Cape rock lobsters that
are able to escape through the mesh do not do so; 3)
that the rock lobsters that are shown theoretically to
be unable to escape through the mesh of commercial
traps, often can do so; and 4) that specimens too large
to escape through the mesh can escape through the
trap entrance.
Acknowledgments
This study would not have been possible without the
funding and infrastructure provided by Marine and
Coastal Management (Department of Environmental
Affairs and Tourism, South Africa). In particular, we
would like to thank our colleagues, Steven McCue, Neil
van den Heever, and Danie van Zyl for technical sup-
port. We are also grateful to the skipper and crew of the
research vessel Sardinops, which was used to conduct
the field trials. J.P.K. received financial assistance from
the Fridtjof Nansen and NORAD, and would like to
thank his supervisors, Anders Ferno and Geir Blom, at
the University of Bergen in Norway, for their assistance
with an earlier draft of this manuscript. D.S.S. thanks
the University of Port Elizabeth for support in terms
of finance and infrastructure. Finally, the constructive
comments of three anonymous referees are acknowl-
edged; these aided substantially in clarifying certain
parts of the original manuscript.
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63
Abstract — The recent development
of the pop-up satellite archival tag
(PSAT) has allowed the collection of
information on a tagged animal, such
as geolocation, pressure (depth), and
ambient water temperature. The suc-
cess of early studies, where PSATs
were used on pelagic fishes, has
spurred increasing interest in the
use of these tags on a large variety
of species and age groups. However,
some species and age groups may not
be suitable candidates for carrying a
PSAT because of the relatively large
size of the tag and the consequent
energy cost to the study animal. We
examined potential energetic costs
to carrying a tag for the cownose ray
iRhinoptera bonasus). Two forces act
on an animal tagged with a PSAT: lift
from the PSATs buoyancy and drag as
the tag is moved through the water
column. In a freshwater flume, a
spring scale measured the total force
exerted by a PSAT at flume velocities
from 0.00 to 0.60 m/s. By measuring
the angle of deflection of the PSAT at
each velocity, we separated total force
into its constituent forces — lift and
drag. The power required to carry a
PSAT horizontally through the water
was then calculated from the drag
force and velocity. Using published
metabolic rates, we calculated the
power for a ray of a given size to
swim at a specified velocity (i.e., its
swimming power). For each velocity,
the power required to carry a PSAT
was compared to the swimming power
expressed as a percentage, </rTAX (Tag
Altered eXertion). A %TAX greater
than 5% was felt to be energetically
significant. Our analysis indicated
that a ray larger than 14.8 kg can
carry a PSAT without exceeding this
criterion. This method of estimat-
ing swimming power can be applied
to other species and would allow a
researcher to decide the suitability
of a given study animal for tagging
with a PSAT.
Quantification of drag and lift imposed
by pop-up satellite archival tags and
estimation of the metabolic cost
to cownose rays (Rhinoptera bonasus)*
Donna S. Grusha
Mark R. Patterson
Virginia Institute of Marine Science
College of William and Mary
P.O. Box 1346
Gloucester Point, Virginia 23062-1346
E-mail address (for D. S Grusha): dsg@vimsedu
Manuscript submitted 21 May 2003
to the Scientific Editor's Office.
Manuscript approved for publication
13 July 2004 by the Scientific Editor.
Fish. Bull. 103:63-70 (2005).
The pop-up satellite archival tag
(PSAT) was developed in the late 1990s
primarily for the tracking of large
pelagic fish (Arnold and Dewar, 2001;
Gunn and Block, 2001). This electronic
tag is attached to a large fish, collects
data on the environment of the fish
for a preprogrammed period, and then
detaches from the fish by corrosion of
a release pin. A float on the tag car-
ries the tag to the surface of the water
where the PSAT begins transmitting
the archived environmental data. The
pop-up location is determined by the
Argos satellites that in turn transmit
the data to a relay station. The earli-
est uses of these tags have been on
large pelagic fishes such as Atlantic
bluefin tuna (Thunnus thynnus) (Block
et al., 1998; Lutcavage et al., 1999)
and blue marlin (Makaira nigricans)
(Graves et al., 2002). In the early tuna
studies, PSATs were used to investi-
gate geographic range and possible
stock structure. Graves et al. (2002)
used the tags to assess postrelease
survival of blue marlin from the rec-
reational fishery. Over their short his-
tory, the PSATs have been improved
to collect even more data than the
original models and currently record
light levels, temperature, and pres-
sure readings. The light levels are
used to estimate geolocation and the
pressure readings are converted to
depth measurements. Combined with
the temperature readings, the depth
measurements can provide detailed
information about the study animal's
swimming behavior. Experiences with
the first-generation tags led to the
development of various fail-safe fea-
tures (Arnold and Dewar, 2001). Both
premature detachment (made evident
by the tag floating at the surface) or
lack of vertical movement (i.e., con-
stant depth, which indicates probable
death of the animal) initiate early
transmission of archived data. Should
the tag be carried to an extreme depth
where water pressure might physically
crush the tag, release mechanisms,
both software-based and mechanical,
have been developed to free the tag
from the animal.
PSATs were developed to supple-
ment the tracking data that could
be acquired through acoustic tag-
ging and archival tagging. Acoustic
tagging is most useful for studying
fine-scale movement and habitat use
and for collecting physiological data
(Arnold and Dewar, 2001; Gunn and
Block, 2001). However, its use is lim-
ited by the need for labor-intensive,
real-time tracking from a research
vessel or the availability of fixed lis-
tening stations. Dagorn et al. (2001)
described clear interactions between
some of the yellowfin tuna (Thunnus
albacares) being tracked and the re-
search vessel — a violation of the as-
sumption that the tracking operation
does not alter the behavior of the fish.
Archival tags also collect both envi-
ronmental and physiological data but
Contribution 2629 from the Virginia
Institute of Marine Science, College of
William and Mary, Gloucester Point.
VA 23062.
64
Fishery Bulletin 103(1)
over much longer time scales (sometimes years) and
across ocean-basin geographic scales (Arnold and Dew-
ar, 2001; Gunn and Block, 2001). These tags can provide
information on both seasonal behavior and migration
routes. Although data collection is fishery-independent,
data retrieval is dependent on the recapture of the fish
by fishermen and on the recognition and return of the
archival tag. PSATs are a merger of archival and satel-
lite telemetry technology. Because PSATs are attached
externally, only environmental data can be collected.
The tags can be programmed to gather data for a prede-
termined duration and then to disengage and transmit
data at a determined time. The major advantage of
this tag is that both data acquisition and retrieval are
fishery-independent and the researcher knows when to
expect to receive data. However, data retrieval is lim-
ited by data compression required to compensate for low
data transfer rates to the Argos satellites, finite battery
life, and relatively high transmission errors (Arnold and
Dewar, 2001; Gunn and Block, 2001). PSATs provide
accurate endpoint locations based on Doppler shifts of
successive transmissions during a single satellite pass.
However, geolocation throughout the tagging duration
is based on light levels that estimate dawn and dusk.
By determining time of local noon and day length, lon-
gitude and latitude can be calculated. According to Hill
and Braun (2001), even with optimal geolocation analy-
sis, the expected variability in longitude is a constant
0.32° but the expected variability in latitude will never
be less than 0.7°. The relationship between day length
and latitude is strongest at high latitudes and at the
time of the solstices but weakens near the equator and
becomes nearly indeterminate at the equinoxes (Sibert
et al., 2003).
An implicit assumption in using these tags is that
while the fish tows the tag, the tag does not affect the
study animal's behavior or survival. This is a reason-
able assumption for large pelagic fishes and is sup-
ported by theoretical estimates of the energetic cost of
towing a PSAT (Kerstetter, 2002); however, the actual
energy cost to a given fish has not previously been
quantified. The success of early studies on pelagic fishes
has spurred increasing interest in using these tags on a
large variety of species and age groups. As studies are
undertaken with PSATs, a logical extension is to pose
the question: "At what point does the energy cost of car-
rying a PSAT negatively affect a study animal?" Blay-
lock (1990) addressed a similar question regarding the
impact of sonic transmitters on the swimming behavior
of cownose rays (Rhinoptera bonasus). In his study, he
videotaped cownose rays for ten-minute intervals before
and after attachment of a mock transmitter. Energy
expenditure was estimated by counting wingbeats per
second before and after attachment of the transmitter.
He concluded that in the short term a transmitter-to-
ray mass ratio of less than 0.03 had no statistically
significant effect on ray swimming behavior.
In this study, the impact of a PSAT on a study ani-
mal is evaluated in terms of the forces that the PSAT
exerts on the animal, specifically lift (i.e., buoyancy)
and drag. Lift and drag are both vector quantities; lift
acts in the vertical direction and drag, as measured
in this study, acts in the horizontal direction. These
vector components are additive to give the total force
acting on the attachment site of a PSAT. At a recent
tagging workshop associated with the Pelagic Fisheries
Research Program,1 the problem of premature release
of some PSATs from the research animal was cited
as a common difficulty. Premature release may be at-
tributed to a number of potential failures of either the
tag itself or the attachment device. Possible sources
for this problem cited at this workshop include detach-
ment of the anchor from the study animal, failure of
the tether between the PSAT and the anchor, failure of
the release pin on the PSAT, and failure of the release
software itself. The magnitude of the total force acting
on the attachment site chronically may provide some
insight into whether anchor failure is a possible source
for this problem.
Drag as an isolated force is the product of four defin-
ing factors:
FD = VzpS IflCn,
(1)
where FD = force due to drag (in newtons, N);
p = density (kg/m3) of the fluid through which
the object is moving;
S = projected surface area (m2) of the object;
U = relative velocity (m/s) between the object
and the fluid; and
CD = drag coefficient (dimensionless) which is
largely dependent upon the shape of the
object.
Furthermore, the power required to pull the tag through
the water can also be related to drag mathematically:
FDU
V2pS U3CD,
(2)
where P = power (in watts, W).
Of particular note in these relationships, drag is pro-
portional to velocity squared and power is related to ve-
locity cubed provided that all other factors are constant.
For example, as velocity is doubled, drag increases by
a factor of four, whereas power increases by a factor of
eight. The characteristic of the tag that most affects
drag in this relationship is its projected surface area
which, in turn, is defined by its size and shape. The
projected surface area of the PSAT changes as the tag
is pulled through the water at different velocities and
in turn changes the drag coefficient at each velocity.
On the other hand, lift is determined by the buoyancy
of the tag. The dry weight of the tag is not a factor
in either of these relationships under steady flow con-
1 Pelagic Fisheries Research Program. 2002. PFRP PI Meet-
ing, December 4-6, 2002. University of Hawaii at Manoa,
1000 Pope Rd., MSB 312, Honolulu, HI 96822. http://www.
soest.hawaii.edu/PFRP/meetings.html. (Accessed 16 June
2004.]
Grusha and Patterson: Quantification of the drag and lift of pop-up satellite archival tags
65
Wildlife Computers
ditions. The weight of the tag is
only important during accelera-
tions and decelerations. During
acceleration, the mass of the tag
positively affects the magnitude
of two separate forces that add to
the hydrodynamic drag, and like-
wise during deceleration, these
extra forces develop on the at-
tachment point that could cause
tag loss.
The motivation for this study
is to determine the feasibil-
ity of tagging cownose rays {R.
bonasus) with PSATs to study
their fall migration. By quanti-
fying the forces that act upon an
animal when a PSAT is attached,
and using published metabolic
rates, we can estimate the en-
ergetic cost for the ray to carry
a PSAT. Moreover, this type of
analysis can be used to determine
the minimum size of ray suitable
for tagging. Considering the wide
variety of user-determined modifications that
can be implemented in applying these tags,
this experiment is intentionally designed to
isolate the PSAT from other variables. In
this way, these results can be applied to a
broad range of applications so that each user
can decide the manner in which a specific
modification of the tag is likely to affect the
forces of lift and drag.
Methods
Drag was measured on two brands of PSAT.
One tag was manufactured by Wildlife Com-
puters, Inc. (Model PAT, 16150 NE 85th St
#226, Redmond, WA 98052) and the other was
a mock tag made by Microwave Telemetry, Inc.
(Model PTT-100, 10280 Old Columbia Road,
Suite 260, Columbia, MD 21046) weighted to
simulate a functional tag. The two tags are
very similar in size and shape (Fig. 1). The
Wildlife Computer PAT has a body length of
180 mm (not including the antenna) and a
dry weight of 75 g and the Microwave Telem-
etry PTT is 175 mm long and weighs 68 g.
Measurements were obtained in a 22,700-
liter freshwater recirculating flume 24 meters in length
located at the Virginia Institute of Marine Science. A
30-g spring scale was used to measure force and was
suspended above the flume. A 1.25-cm low-friction Delrin
rod was suspended approximately 55 cm below the water
surface by a metal bracket and placed directly below the
spring scale. A 90-cm length of 0.46-mm diameter (20-lb
test) monofilament line connected the tag to the spring
Length- 180 mm
Weight- 75 g
Length -175 mm
Weight - 68 g
Figure 1
The shape and dimensions of two brands of pop-up satellite archival tag.
Diagra
tion of
Figure 2
m of experimental design, showing how 0, the angle of deflec-
the tag, was measured.
scale by loops tied at either end. One loop was threaded
through the release pin in order to lasso the tag. The
other loop was then attached to the clip on the spring
scale and the tag was passed under the Delrin rod so that
it floated to the other side (Fig. 2). The depth of the Delrin
rod and the length of the monofilament were selected
so that the tag was completely immersed in the water
throughout the experiment and so that it floated within
66
Fishery Bulletin 103(1)
Table 1
Spring scale measurements, angle of deflection, summary of forces exerted and power required for two brands of PSAT over
flume velocities from 0.00 m/s to 0.60 m/s. The spring scale measurements include the range over a 5-minute period. The angle of
deflection was measured from the horizontal. Total force, lift, and drag (in newtons, N) were calculated from Equations 3, 4, and
5, respectively. Power lin watts, W) was calculated as the product of flume velocity and drag.
Flume velocity
PSAT (m/s)
Spring scale
measurement
(g)
0
1 )
Total force
(N)
Lift
(Ni
Drag
(N)
Power
(W)
Wildlife Computers
0.00
6.50 ±0.25
90.0
0.064
0.064
0.000
0.000
0.15
7.50+0.25
76.5
0.074
0.072
0.017
0.003
0.30
10.50 ±0.25
42.0
0.103
0.069
0.076
0.023
0.45
15.0 ±0.5
40.0
0.147
0.094
0.113
0.051
0.60
19.0 ±1.0
31.5
0.186
0.097
0.159
0.095
Microwave Telemetry
0.00
11.75 ±0.25
90.0
0.115
0.115
0.000
0.000
0.15
12.25 ±0.25
75.5
0.120
0.116
0.030
0.004
0.30
13.50 ±0.25
61.5
0.132
0.116
0.063
0.019
0.45
16.0 ±0.5
42.5
0.157
0.106
0.116
0.052
0.60
21.5 ±1.0
41.5
0.211
0.140
0.159
0.095
the central portion of the flume. Prior to the experiment,
the monofilament line was attached to the spring scale
and the spring scale was then set at zero so that the
weight of the monofilament line was excluded from the
subsequent measurements. The flume temperature was
measured at 20°C. Measurements were taken on each
tag at flume velocities of 0.0, 0.15, 0.30, 0.45, and 0.60
m/s, the maximum velocity of the flume. At each flume
velocity, the flume flow was allowed to equilibrate for 10
minutes. Then spring scale measurements were observed
over a period of five minutes and the mid-point measure-
ment and its range were recorded. The raw measurement
was then converted to total force, FT (N):
FT = (rawmeasurement(g))(lkg/1000g)(9.8m/s2). (3)
In addition, a digital photo was taken of each tag
at each velocity from the side of the flume in order to
measure the angle of deflection (6) as measured upward
from horizontal. Accordingly, the total force {FT) could
then be separated into its component forces, lift (FL)
and drag (FD):
FL = sin 6 FT,
FD = cos 0 FT.
(4)
(5)
Results
The spring scale measurement for the Wildlife Comput-
ers PAT increased from 6.50 g at 0.00 m/s to 19.0 g at
0.60 m/s and the Microwave Telemetry PTT increased
from 11.75 g to 21.5 g over the same flume velocity
increase (Table 1). Because of increasing turbulence
in the flume at the two higher flume velocities, the
range of the spring scale measurements also increased.
The total force exerted by the Wildlife Computers PAT
increased from 0.064 N to 0.186 N as the flume velocity
was increased (Table 1). Similarly, the drag and calcu-
lated power required to pull the tag through the water
column at the highest velocity was 0.159 N and 0.095 W,
respectively. The lift of this PSAT also increased, but not
continuously, from 0.064 N to 0.097 N. The forces exerted
by the Microwave Telemetry PTT were very similar but
had higher lift values. The total force increased from
0.115 N to 0.211 N, the drag increased to 0.159 N and
the power required to pull this PSAT was 0.095 W at the
highest velocity. The lift increased from 0.115 N to 0.140
N but again not in a continuous manner. Force-velocity
curves for both PSATs were very similar (Fig. 3). Lift
was relatively constant for each tag, although at differ-
ent magnitudes. Total force and drag both increased over
the range of flume velocities and roughly paralleled each
other between 0.30 m/s and 0.60 m/s.
Discussion
Considered alone, the power required to pull a given
PSAT at a particular velocity has little relevance, but
when considered in the context of an animal's usual
energy expenditure to swim at that velocity, it can be
expressed as %TAX (Tag Altered eXertion), defined as
the increase in energy required by the animal to pull the
PSAT at the specified velocity, normalized by the routine
or active metabolic rate (see below). In his biotelemetry
studies, Blaylock (1992) measured mean routine swim-
ming speeds between 0.20 m/s and 0.29 m/s in cownose
rays. Maximum swimming speeds for cownose rays have
Grusha and Patterson: Quantification of the drag and lift of pop-up satellite archival tags
67
not been measured; however, with visual
observation. Smith (1980) reported witness-
ing several undisturbed schools of cownose
rays swimming near the surface at -4-5
knots (2.06-2.57 m/s). Using data reported
in first sightings during spring migration
of cownose rays along the South Atlantic
Bight, Smith estimated migration speeds as
high as 12.5 nautical miles per day. Assum-
ing the rays migrated continuously, that
rate would require a swimming speed of
0.27 m/s; if they were actively migrating
50% of the time, they would have to swim
at 0.54 m/s.
Published metabolic rates can be used to
estimate the energy required for an animal
to swim at various speeds. When informa-
tion is not available on a study species,
a suitable proxy species can be used. In
the example of the cownose ray, no data
are currently available regarding meta-
bolic rates; however, DuPreez et al. (1988)
published metabolic rates for the bull ray
(Myliobatis [=Myliobatus] aquila) over a
range of temperatures. Myliobatis aquila is
a good proxy species for R. bonasus because
the two species are morphologically similar,
similar in size, and both inhabit temperate
to subtropical coastal waters. Because the
flume measurements were obtained at 20°C
and this is also a typical mid-range tem-
perature for either species, the equations
for metabolic rates at this temperature will
be used (Eq. 6, a-c). Metabolic rates are
expressed as a set of three equations that yield the
standard metabolic rate (SMR), the routine metabolic
rate (RMR), and the active metabolic rate (AMR).
Wildlife Computers PAT
-■•-■- Total Force
■--*-■ -Lift
— •— Drag
90_ ._.J?£r.
31 5
, . jm
40.0", - --"■"" .-.
42.0° - — ' ^^^-""^
_.-■•■ ______ -"^ A
Microwave Telemetry PTT
Velocity (m/s)
Figure 3
Comparison of force-velocity curves of two brands of PSAT. Total
force (in newtons, N) and its component forces, lift and drag, are
plotted against flume velocity (m/s). The angle of deflection of the
PSAT as measured upward from horizontal is indicated above each
set of points
SMR log10 R = 2.86 - 0.32 x
log10 (M x 1000),
where SP,MR = swimming power (W) for RMR or AMR.
Making the appropriate substitutions into Equation 7
yields SPRMR = 0.76 W and SPAMR = 1.99 W. Drag can
then be expressed as %TAX:
(6a)
%TAX = (P I SP/MP) x 100.
(8)
RMR log10r? = 2.79 -0.27 x log10(M x 1000), (6b)
AMR log10r? = 2.74- 0.22 x log10(Mx 1000), (6c)
where M = mass (kg) of the ray (DuPreez et al.'s 1988
equations have been modified so as to
express M in MKS units); and
R = metabolic rate (mg 09/(kg x h)).
Using the size of an average female cownose ray of 15.5
kg (Smith, 1980) and solving for R, the SMR, RMR and
AMR are estimated as 33.0, 45.6, and 65.8 mg 02/(kg x
h) respectively. These rates can then be used to estimate
swimming power at routine and active swimming speeds:
SP-,MR=(?MR-SMR)x
(lW/kg)/(256mg0.2/(kgxh))xM,
(7)
For swimming speeds of 0.15 m/s and 0.30 m/s, SPRMR is
used, and for swimming speeds of 0.45 m/s and 0.60 m/s,
SPAMR is used (Table 2).
Although lift has not been considered in the above
analysis, it is an important component of the total force
affecting a study animal. As a chronically applied force
acting against the anchor site where the PSAT attaches,
this total force may contribute to premature release of
the PSAT from the study animal. Moreover, for ani-
mals where diving behavior is important for survival
(e.g., diving for prey or diving to escape predators) lift
becomes an additional tax on the animal's energy re-
souces. Using total force as an approximation of the
force to be overcome by the animal when diving, we can
estimate the total power required to dive as Total force
as %TAX (Table 2).
We propose that an increase in energy requirement,
%TAX, of <5% will not negatively impact a study ani-
68
Fishery Bulletin 103(1)
Table 2
Metabolic cost to a 15.5 kg cownose ray carrying a PSAT at various velocities expressed as 9c TAX. Drag and total force are the
forces created by the PSAT to be overcome by the swimming ray. Power and total power are the rates of energy expenditure
required to overcome these forces. Drag as 9CTAX and Total force as %TAX are the increases in energy expenditures, normalized
by the routine or active metabolic rate (speed dependent — see text), required to carry the PSAT at a given velocity. Drag, power,
and Drag as 9cTAX apply to a ray swimming in the horizontal plane. Total force, total power, and Total force as %TAX account
for the buoyancy of the PSAT and apply when the ray is diving.
PSAT
Flume velocity Drag
(m/s) <N>
Power
(W)
Drag as
OTAX
Total force
(N)
Total power
(W)
Total force as
%TAX
Wildlife Computers
0.00
0.000
0.000
0.00
0.064
0.000
0.00
0.15
0.017
0.003
0.34
0.074
0.011
1.44
0.30
0.076
0.023
3.01
0.103
0.031
4.05
0.45
0.113
0.051
2.55
0.147
0.066
3.33
0.60
0.159
0.095
4.80
0.186
0.112
5.63
Microwave Telemetry
0.00
0.000
0.000
0.00
0.115
0.000
0.00
0.15
0.030
0.004
0.59
0.120
0.018
2.36
0.30
0.063
0.019
2.46
0.132
0.040
5.20
0.45
0.116
0.052
2.62
0.157
0.071
3.55
0.60
0.159
0.095
4.77
0.211
0.126
6.37
mal that has adequate food resources in nature; higher
loads are felt to be energetically significant. In this ex-
ample using a 15.5-kg cownose ray, the Drag as %TAX
is within acceptable parameters; however, at 0.60 m/s
the Total force as %TAX begins to exceed these guide-
lines. At this point, a researcher would have to consider
whether diving behavior at this speed would be a sig-
nificant factor in the animal's survival.
Another application of this information would be to
determine the minimum reasonable size for a study ani-
mal of a particular species. Blaylock (1990) attempted to
address this issue for cownose rays by considering the
transmitter-to-ray mass ratio using dry weights. The
advantage of using metabolic rates is that it identifies
subtler but significant increases in energy requirement
to carry a PSAT. In his study, Blaylock examined two
age groups, a 0+ age group that had an average weight
of 1.8 kg and a 1+ age group that ranged in size be-
tween 4.3 kg and 7.8 kg. He concluded that the 0+ age
group was negatively impacted by the sonic tag but that
the 1+ age group was not effected. A PSAT is physically
smaller than the sonic tags used in his experiment; in
addition, it is attached to the animal at the nose-end
of the tag so that it is carried with the long axis of the
tag parallel to the long axis of the animal (Blaylock's
sonic tags were attached so that the long axis of the
tag was carried perpendicular to the long axis of the
animal). Both these factors — smaller physical size and
nose-end orientation in space — decrease the projected
surface area of the tag. As an example, consider the
metabolic cost of carrying a Wildlife Computers PAT
to each of these sizes (1.8, 4.3, and 7.8 kg) of cownose
ray (Table 3). For the 1.8-kg ray, only the exertion of
carrying the PSAT at 0.15 m/s horizontally was associ-
ated with a %TAX of <5%; higher swimming speeds or
downward diving markedly increased the %TAX. It is
obvious why short-term effects of carrying a sonic tag
were evident. For the 4.3-kg ray, all swimming speeds
greater than 0.15 m/s, whether horizontal or diving,
required increased energy expenditures of >5%. For the
7.8-kg ray, %TAX was acceptable at 0.15 m/s, marginal
to slightly elevated for mid-range speeds, and was clear-
ly excessive at high speed. According to this analysis,
rays of these size classes would not be good candidates
for carrying a PSAT. As determined in this study, the
smallest cownose ray that ought to be considered for
PSAT tracking would be 14.8 kg. Drag as %TAX is s5%
for all speeds and only slightly >57c for Total force as
%TAX at 0.60 m/s. Because prolonged high speed div-
ing behavior is not likely a factor in this ray's ability
to survive, the minor elevation of %TAX for diving at
0.60 m/s can be disregarded.
When applying this type of analysis to other species
that predominantly swim at speeds greater than 0.60
m/s, several caveats make unwise the extrapolation of
these data to higher velocities. Referring back to the
equations describing drag and power. Equation 1 and
Equation 2, respectively, drag is proportional to veloc-
ity squared and power is proportional to velocity cubed
provided that all other factors are constant. However,
in examining Figure 3, as velocity increases from 0.00
m/s to 0.60 m/s, all other factors are not constant. Spe-
cifically, the angle of deflection, 9, decreases from 90°
at 0.00 m/s to as low as 31.5° at 0.60 m/s. First, the
projected surface area, S, over which water flows de-
creases as velocity increases. Second, the orientation
(effective shape) of the object also effectively changes
as velocity increases. Hence the drag co-efficient, CD
Grusha and Patterson: Quantification of the drag and lift of pop-up satellite archival tags
69
Table 3
Metabolic costs to various sizes of cownose ray to
increase in energy expenditure, normalized by thi
ray to carry the PSAT while swimming in the hor
applies when the ray is diving.
carry a Wildlife Computers
routine or active metabolic
zontal plane. Total force as
PSAT expressed as %TAX. Drag as %TAX is the
rate (speed dependent — see text), required by the
%TAX accounts for the buoyancy of the PSAT and
Weight
of ray
(kg)
Drag as
%TAX
Total force as %TAX
Swimming velocity (m/s)
Swimming velocity (m/s)
0.15
0.30
0.45
0.60
0.15
0.30
0.45
0.60
1.8
2.39
21.32
18.53
34.84
10.25
28.69
24.19
40.86
4.3
1.05
9.32
8.06
15.16
4.48
12.58
10.53
17.78
7.8
14.8
0.62
0.35
5.50
3.15
4.70
2.66
8.84
5.00
2.65
1.51
7.41
4.24
6.41
3.48
10.37
5.87
also changes. At some velocity greater than 0.60 m/s,
9 will approach 0°, and at that point S and CD would
remain constant for higher velocities. After that veloc-
ity is reached, then for higher velocities, drag would
increase proportionately to the square of velocity and
power would increase proportionately to the cube of ve-
locity. In other words, between 0.00 m/s and 0.60 m/s,
the changes in S and CD mask the parabolic relation-
ship of drag with velocity. Because the velocity at which
S and CD become constant is not known, extrapolations
far beyond the maximum velocity for which drag was
measured would be risky.
The effect of the changing values of S and CD is evi-
dent in this data set. For example in Table 1, as velocity
doubles from 0.30 m/s to 0.60 m/s, drag increases by
only 2.09 and 2.52 for the Wildlife Computers PAT and
the Microwave Telemetry PTT-100, respectively, rather
than by a factor of four. Similarly, power increases by
4.13 and 5.00 for the two PSATs and not by a factor of
eight. For both these tags, d decreases with increasing
velocity resulting in a smaller value for S and a differ-
ent value for CD.
By examining the forces exerted by a PSAT at various
velocities, insights regarding the impact of these forces
on a study animal can be gained. The combined forces
of lift and drag act chronically on the anchor site of the
PSAT. Although this study does not specifically address
attachment methods, the forces of lift and drag exerted
by a PSAT are not negligible and cannot be ignored
when evaluating an attachment technique. A PSAT
also imposes an energetic cost to the study animal. If
that energy cost compromises the animal's behavior or
survival, the information gained from the tag is not rep-
resentative of an untagged animal. By estimating the
energetic cost to an intended study animal, a researcher
can make a more informed decision regarding the suit-
ability of the animal for this type of tagging. Although
direct extrapolation to higher swimming speeds is not
possible with our data, the principles outlined in this
study can be applied to faster swimming species such
as tunas and billfishes that are frequently tagged.
Acknowledgments
We would like to thank T. Nelson, S. Wilson, W. Reisner
and R. Gammisch for their assistance in running and
setting up the flume, T. Mathes for his enthusiastic sup-
port, and R. Brill, D. Kersetter, and J. Hoenig for helpful
discussions. Financial support was provided by NOAA
Office of Sea Grant.
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Abstract — Fish bioenergetics models
estimate relationships between energy
budgets and environmental and physi-
ological variables. This study presents
a generic rockfish (Sebastes) bioen-
ergetics model and estimates energy
consumption by northern California
blue rockfish (S. mystinus) under
average (baseline I and El Nino con-
ditions. Compared to males, female
S. mystinus required more energy
because they were larger and had
greater reproductive costs. When El
Nino conditions I warmer tempera-
tures; lower growth, condition, and
fecundity) were experienced every 3-7
years, energy consumption decreased
on an individual and a per-recruit
basis in relation to baseline conditions,
but the decrease was minor (<4% at
the individual scale, <7% at the per-
recruit scale) compared to decreases
in female egg production (12-19% at
the individual scale. 15-23% at the
per-recruit scale). When mortality in
per-recruit models was increased by
adding fishing, energy consumption
in El Nino models grew more similar
to that seen in the baseline model.
However, egg production decreased
significantly — an effect exacerbated
by the frequency of El Nino events.
Sensitivity analyses showed that
energy consumption estimates were
most sensitive to respiration param-
eters, energy density, and female
fecundity, and that estimated con-
sumption increased as parameter
uncertainty increased. This model
provides a means of understand-
ing rockfish trophic ecology in the
context of community structure and
environmental change by synthe-
sizing metabolic, demographic, and
environmental information. Future
research should focus on acquiring
such information so that models like
the bioenergetics model can be used to
estimate the effect of climate change,
community shifts, and different har-
vesting strategies on rockfish energy
demands.
Effects of El Nino events on energy demand
and egg production of rockfish
(Scorpaenidae: Sebastes):
a bioenergetics approach
Chris J. Harvey
Northwest Fisheries Science Center
National Marine Fisheries Service
2725 Montlake Blvd. E
Seattle, Washington 98112
E-mail address Chris. Harveyignoaa gov
Manuscript submitted 20 October 2003
to the Scientific Editor's Office.
Manuscript approved for publication
2 August 2004 by the Scientific Editor.
Fish. Bull. 103:71-83 (2005).
Over 90 species of rockfish (Sebastes
spp.) are found in kelp beds, rocky
reefs, pelagic habitats, and continental
shelf and slope zones of the temperate
and subarctic North Pacific; these spe-
cies feed on a range of organisms, from
zooplankton to fish (Love et al., 20021.
Although they are a key component of
groundfish fisheries on the U.S. Pacific
Coast, many rockfish have declined
considerably in recent decades, owing
to overfishing and climate-induced
downturns in production (Parker et
al., 2000). Conservation efforts, rang-
ing from coast-wide fishery closures to
establishment of marine reserves, have
been enacted in order to rehabilitate
rockfish stocks. The efficacy of such
actions depends in part on the dynam-
ics of the communities in which rock-
fish exist. Key among these dynamics
are trophic interactions, as influenced
by abiotic factors and rockfish popula-
tion structure.
Although rockfish are widely dis-
tributed and important to the ecolo-
gy, fisheries, and conservation efforts
of the Pacific Coast, little is known
about their trophic dynamics. For ex-
ample, of the 65 rockfish species that
live along the North American West
Coast, quantitative diet data are
available for only 15 species (Murie.
1995). Better information on the food
habits and energetics of both juvenile
and adult rockfish would facilitate
a greater understanding of the role
they play in their communities, and
how their role is affected by external
forces. This is particularly true given
observations that environmental vari-
ation can have strong effects on rock-
fish growth and condition (Lenarz et
al., 1995; Woodbury, 1999).
Fish bioenergetics models relate
the energy consumption, growth, and
energy allocation patterns of fishes
to environmental and physiological
variables such as temperature, food
quality, body size, and reproductive
status (Kitchell et al., 1977). These
models, founded in thermodynamic
laws of mass and energy balance,
can successfully predict patterns of
energy demands by fish (Madenjian
et al., 2000). At the scale of the indi-
vidual fish, bioenergetics models can
estimate effects of a fish on its com-
munity (in terms of the amount of
prey it consumes) and effects of the
environment on the fish, such as how
changes in temperature or food avail-
ability influence energy consumption
and growth (Rice et al., 1983). When
coupled to population models, bio-
energetics models can predict prey-
predator supply-demand relationships
(Negus, 1995) and determine how
different fishery management poli-
cies will affect prey resources in the
community from which the targeted
fish is extracted (Kitchell et al., 1997;
Essington et al., 2002; Schindler et
al., 2002). Thus, these models may
facilitate a more community- or eco-
system-level approach to rockfish
management.
In this study, I develop a generic
Sebastes bioenergetics model. My first
objective is to detail the parameters
and the sensitivity analysis of the
model, thereby offering a synthesis
of what is known about Sebastes en-
ergetic physiology and identifying pa-
rameters for which greater informa-
tion is desirable. The second goal is
to present a simple application of the
model: an estimation of the effects of
72
Fishery Bulletin 103(1)
El Nino related environmental changes on the energy
demands of blue rockfish (S. mystinus) under unfished
and fished conditions. Two relevant characteristics of
El Nino events in U.S. West Coast waters are elevated
temperatures and reductions in growth rates and re-
productive condition of Sebastes (Lenarz et al., 1995;
VenTresca et al., 1995; Woodbury, 1999). The bioener-
getics approach can incorporate these changes and can
therefore help to characterize the role of rockfish as
consumers in a dynamic environment.
Methods
Model structure
I followed the basic structure of bioenergetics models
established for other fishes (e.g., Kitchell et al., 1977;
Hewett and Johnson, 1992), in which energy intake
(consumption) equals all energy outputs (respiration,
wastes, growth, and reproduction). The basic model
equation is
C = (i? + A + S) + (F + U) + (AB + G)
(1)
where C = consumption, R = respiration, A = active
metabolism, S = specific dynamic action (digestive costs),
F = egestion, U = excretion, AB = somatic growth, and G
= gonad production. The respiration and active metabo-
lism portions of Equation 1 take the form
R = RA x WRB x f(T) x ACT,
(2)
where RA and RB are constants that describe the allo-
metric respiration function, W is wet biomass, f(T) is a
temperature dependence function, and ACT is an activ-
ity multiplier (Kitchell et al., 1977). The function f(T)
(Kitchell et al., 1977) is a hump-shaped function that
requires estimates of optimal (RTO) and maximum
(RTM) temperatures for respiration, and a Q10 (RQ).
The terms S, U, and F all scale to total consumption
(Kitchell et al., 1977). One can thus think of them as a
general energy loss term
Loss = (S + U) x (C -F) + F.
(3)
Model parameters
Although parameters are derived from studies of many
rockfish species, I developed the present model to describe
energetic dynamics of S. mystinus, for which a consider-
able literature exists regarding diet and responses to
climate variability (e.g., Hallacher and Roberts, 1985;
Bodkin et al., 1987; Hobson and Chess, 1988; Lenarz et
al., 1995; VenTresca et al., 1995).
Respiration parameter estimates came from studies
of other Sebastes species or related scorpaenid fishes
(Table 1). For RTM, I used published estimates for S.
thompsoni and S. schlegeli (Ouchi, 1977; Tsuchida and
Setoguma, 1997), and assumed that RTO would be 5°C
Table 1
Parameter
model.
values for the generic Sebastes bioenergetics
Parameter
Description
Value
RA
Intercept of the allometric
respiration function
0.0143
RB
Slope for allometric
respiration function
-0.2485
RQ
Slope for temperature
dependence of respiration (<?10>
2
ACT
Multiplier for active
metabolism
1
RTO
Optimum temperature
for respiration
23°C
RTM
Maximum temperature
for respiration
28°C
SDA
Specific dynamic action
coefficient
0.163
FA
Egestion coefficient
0.104
UA
Excretion coefficient
0.068
ED
Energy density
(somatic tissue) of wet mass
6,120 J/g
GED
Energy density
(female gonadal tissue)
of wet mass
8,627 J/g
GA
Coefficient of the female
length-fecundity relationship
1.559
GB
Exponent of the female
length-fecundity relationship
3.179
GSI„lax
Maximum male
gonadosomatic index
0.008
cooler. The resulting RTO was similar to upper tem-
peratures at which juvenile S. diploproa experienced zero
growth while feeding (Boehlert, 1981). RQ was based on
low-temperature Q10 values in several scorpaenid respi-
ration studies (Boehlert et al. 1991; Yang et al., 1992;
Kita et al, 1996; Vetter and Lynn, 1997). RA, the oxygen
consumption rate for a 1-g fish at RTO, was derived from
data for nongestating S. schlegeli (Boehlert et al., 1991).
RB, which describes the allometric scaling of respiration,
was also derived from data for nongestating S. schlegeli
spanning a range of roughly 0.7 to 1.9 kg body mass
(Boehlert et al., 1991). Respiration terms were converted
to energy units by an oxycalorific correction (13.56 J/mg
09), and then to biomass by assuming that rockfish en-
ergy density (ED) = 6,120 J/g wet mass (Perez, 1994).
The ACT multiplier was assumed to equal 1. This
assumption is best justified in cases where routine res-
piration rates were used to determine parameters for
the model. Boehlert et al. (1991) stated that S. schlegeli
in their analysis were generally inactive, which implies
that rates derived from their data represent resting
Harvey: Effects of El Nino events on consumption and egg production of Sebastes spp.
73
metabolism. I chose to keep ACT at 1, however, because
I could find no data describing a reasonable activity
multiplier. Thus. Sebastes model outputs may underes-
timate energy consumption under conditions in which
individuals are especially active.
I obtained growth (AB in Eq. 1) terms using von
Bertalanffy length-at-age curves and data for length-
to-mass conversions for S. mystinus as summarized
by Love et al. (2002). Because female S. mystinus are
larger at age than males, growth was modeled with
sex-specific von Bertalanffy curves with the difference
equation method of Gulland (1983). Digestion and waste
terms S, F, and U were derived from previous teleost
models (Hewett and Johnson, 1992).
I estimated gonad production (G) with gonadosomatic
indexes (GSI) and size-fecundity relationships (females
only), assuming that female and male S. mystinus ma-
ture gradually over the range of lengths observed by
Wyllie-Echeverria (1987), and reproduce once annually.
For males, I assumed that gonads have the same ED as
somatic tissue; for females, I assumed that gonadal en-
ergy density (GED) = 8,627 J/g, which was the average
of gonadal energy density at the onset of embryogenesis
for S. flavidus and S. jordani (MacFarlane and Norton,
1999). Estimated maximum female GSI was based on
a fecundity-length relationship:
fecundity = GA x TLGB,
(4)
where GA and GB were taken from a generic rockfish
length-fecundity relationship (Love et al., 2002) and TL
is total length in cm. Fecundity was converted to bio-
mass units by assuming that each egg weighed 0.0003 g,
which I derived from Love et al. (1990) by dividing the
mean maximum female gonad weight by the estimated
fecundity of modal mature females for several species.
For mature males, I assumed a constant maximum GSI
based on data for other species (Love et al., 1990). Post-
spawning GSI was assumed to be 10% of the maximum
for each sex, as with other rockfish (Love et al., 1990).
The G terms were the difference between the maximum
and minimum GSIs for each sex, expressed as mass
(and, in females, adjusted by multiplying by GED/ED).
Rockfish are viviparous, and developing larvae may
receive energy from both yolk and maternal sources
(Love et al., 2002). During gestation in a laboratory,
female S. schlegeli consumed 35% to 117% more oxygen
than nongestating fish of similar size (Boehlert et al.,
1991). To account for the possibility that blue rockfish
may also be matrotrophically viviparous, I increased
female respiration by 50% during the gestation period
(assumed to be 45 days per year based on gestation
times of other species [Boehlert et al., 1991]).
Model application: effects of El Nino
on blue rockfish energy consumption
To examine the effects of El Nino on S. mystinus energy
consumption, I created two model conditions: a baseline
model and an El Nino model that estimated S. mystinus
Table 2
Changes in the S. mystinus bioenergetics model that were
implemented in El N
ino scenarios in relation to the base-
line model.
Variable
Change
Temperature
Increased 1.5°C in El Nino years7
Growth
(length increment)
Decreased 17.5% in El Nino years'
Female condition
Decreased 10% in El Nino years;
factor
decreased 5% the year following
an El Nino2
Male condition
Decreased 7.5% in El Nino years;
factor
decreased 5% the year following
an El Nino-
Fecundity
Decreased 67% in El Nino years2
1 Source: Lenarz et al..
1995.
- Source: VenTresca et al.. 1995.
energy demands, in megajoules (MJ), required for neces-
sary growth, reproduction, and related metabolic costs.
I used MJ rather than prey biomass as the currency
because quantitative, seasonal diet data for S. mystinus
in northern California were available for average years
(Hobson and Chess 1988) but not for El Nino years. During
the 1982-83 El Nino, Lea et al. (1999) found that central
Californian S. mystinus consumed large numbers of the
pelagic crab Pleuroneodes planipes, which is typically
found south of Point Conception during average years.
During the same time period, S. fnystinus ate few tuni-
cates or scyphozoans (Lea et al., 1999), which were the
predominate prey of S. mystinus in average years (Hobson
and Chess, 1988). These findings suggest a major shift in
S. mystinus prey composition during El Nino events.
The baseline model simulates energy consumption of
northern California S. mystinus from age 0 to age 30,
based on quarterly growth estimates from sex-specific
von Bertalanffy curves (Love et al., 2002) and seasonal
temperature data from Hobson and Chess (1988). Mature
females released larvae in the fourth quarter of each
year, and mature males released gametes in the third
quarter (Wyllie-Echeverria, 1987). Energy consumption
for both sexes from ages 0 to 30 was expressed at two
scales: for the 30-year life span of an individual; and on
a per-recruit basis (under the assumption that there was
no fishing mortality and that the natural mortality rate
[M] was 0.2, applied in quarterly time steps).
The El Nino model was similar to the baseline model,
except an El Nino occurred every three to seven years.
During these years there were changes in temperature,
growth, condition, and fecundity (Table 2). Temperature
increases in El Nino years were similar to temperature
anomalies in northern California waters during major
El Nino events from 1957 to 1993 (Lenarz et al., 1995).
Changes in growth (in terms of length increment), con-
74
Fishery Bulletin 103(1)
dition (the ratio of actual to expected weight, based on
length-weight relationships), and fecundity were based
on empirical measures of S. mystinus during El Nino
years (Lenarz et al., 1995; VenTresca et al., 1995). As
in the baseline model, 1 expressed energy consumption
by both sexes at individual and per-recruit scales.
Finally, I ran simulations at the per-recruit scale in
which the total mortality rate (Z) was increased by add-
ing a fishing-induced mortality rate (F) in increments of
0.05 to M; fishing mortality was imposed on fish greater
than 20 cm, the size at which S. mystinus enters fisher-
ies in California waters (Laidig et al., 2003). The range
of Z examined was 0.2 (natural mortality only) to 1.0
(a heavily overfished condition). These simulations were
run under baseline conditions and El Nino conditions
to determine if there was any interaction between El
Nino effects and Z.
Sensitivity analysis
To measure sensitivity of the Sebastes bioenergetics
model to different parameters, I used a Monte Carlo
error analysis method (Bartell et al., 1986). In this
method, parameters are drawn randomly from normal
distributions with means equal to parameter estimates
(Table 1) and with a coefficient of variation (CV) of either
2%, 10%, or 20%. Cases where randomly drawn RTO
was greater than RTM were discarded. Female and
male models were run 1000 times for each of the three
CVs. Individual simulations ran to age 30 at 0.25-year
increments; seasonal temperatures were those used in
the baseline model. Parameter influence on 30-year
cumulative consumption estimates was judged accord-
ing to the parameters' relative partial sums of squares
(RPSS), which quantify the influence of a parameter
after all other parameters have been accounted for.
RPSS for all parameters were calculated with SYSTAT
(version 10.2, SYSTAT Software Inc., Richmond, CA).
Additionally, means and standard deviations of con-
sumption estimates from RPSS analyses were calculated
to capture the range of energy consumption possible over
the lifetime of female and male S. mystinus.
Results
Northern California S. mystinus baseline energy demands
Baseline energetic demands of northern California S.
mystinus were a function of size, sex, and the scale of
calculation (i.e., individual versus per recruit). As size
increased, more energy was allocated to respiration,
elimination of wastes, and reproduction, and steadily
less energy was allocated to growth (Fig. 1). At the
individual scale, females consumed more than males at
all ages. The sexes diverged markedly as fish matured
(beginning at age 3 for females, age 4 for males), and
continued to diverge as fish approached asymptotic
sizes (Fig. 2A). The disparity was related to sex-based
differences in growth rate, maximum size, GSI, and
the increased respiration of gestating females. Cumu-
lative consumption through age 30 was 285.0 MJ for
individual females, and 174.6 MJ for individual males.
Assuming a prey energy density of 1500 J/g (given S.
mystinus diets [Hobson and Chess, 1988] and prey-
density measurements of the same or related prey spe-
cies [Paine and Vadas, 1969; Thayer et al., 1973; Foy
and Norcross, 1999]), this energy density equates to
a long-term average energy consumption rate of 2.7%
body mass per day for females and 2.8% body mass per
day for males.
Females also had greater requirements than males
at the per-recruit scale, although mortality gradually
lessened the contribution of older age classes (Fig. 2B),
nullifying some of the disparity between the sexes at
the individual scale. Cumulative female and male per-
recruit energy consumption was 20.7 MJ and 14.8 MJ,
respectively. Per-recruit energy consumption, the prod-
uct of age-specific consumption rate and relative fish
abundance, peaked at ages 4-6, indicating that those
age groups have the greatest potential to affect their
prey species.
Effects of El Nino on S. mystinus energetics
El Nino events changed S. mystinus energy consumption
compared to that in the baseline model, but the direction
and magnitude of change were dependent on sex, age,
scale of calculation (individual vs. per recruit), and the
number and frequency of El Nino events experienced by
a given cohort. To demonstrate this change, I modeled
growth of two cohorts that experienced El Nino regimes
of moderate or high intensity. The first cohort ("cohort
A") experienced five El Nino events by age 30, whereas
the second cohort ("cohort B") experienced eight El Nino
events (Figs. 3 and 4).
At the scale of individual fish, cohorts A and B experi-
enced lower energy consumption in El Nino events, par-
ticularly among females. During El Nino years, which
first occurred at age 3 for cohort A and at age 1 for co-
hort B, consumption by females was always lower than
the baseline value (Fig. 3A). In immature females, the
disparity was 7-10% lower than the baseline value and
was 12-13% lower for mature females. These reductions
in consumption were a function of lower growth rates,
poor condition factor, and reduced fecundity during El
Nino years. In contrast, consumption by males during
El Nino years was 4-9% lower than the baseline value
among immature individuals, but was roughly equal to
the baseline value for mature individuals (Fig. 3B), in
part because males did not experience drastic changes
in reproductive condition during El Nino years. Both
sexes experienced years when energy consumption was
greater than the baseline value, particularly two years
after an El Nino event when the somatic condition fac-
tor returned to normal and greater-than-average growth
for that age occurred. By age 30, sizes of fish in both
El Nino models were close to the asymptotic maxima
and were therefore similar to baseline sizes (Table 3).
Cumulative 30-year energy consumption values were
Harvey: bffects of El Nino events on consumption and egg production of Sebastes spp
75
12 -
£ 0
10
15
20
25
30
Figure 1
Estimated allocation of energy consumption by northern California S.
mystinus from ages 0 to 30 under baseline model conditions. Consumption
(C) is allocated as respiration (R), waste, and digestive costs (F+U+SDA),
growth (4B), and reproduction (G). (A) Females. (B) Males.
also similar in all models and in both sexes, despite the
declines experienced by females.
Repeated exposure to El Nino also affected reproduc-
tion by S. mystinus. Both sexes experienced delays in
maturation as a result of slowed growth rates during
El Nino events, and the delay was related to the num-
ber of El Nino years experienced at young ages. In the
baseline model, 50% maturity was reached at age 6
for both sexes. In cohort A, 50% maturity was reached
at age 6 by females, but at age 7 by males. Under the
more arduous conditions of cohort B, both sexes reached
50% maturity at age 7. The effect of delayed maturation
in terms of energy consumption should be greatest in
females because of their greater investments in repro-
duction, although this was not especially noticeable
at the scale of cumulative consumption per individual
(Table 3). A further effect of El Nino events occurred
in female egg production. The dramatic reduction in
fecundity during El Nino years over the course of an
individual female's life caused cumulative egg produc-
tion in cohort A to be only 87.9%> of the baseline level,
and cohort B female egg production was only 81.3% of
the baseline level (Fig. 3C).
More pronounced El Nino effects occurred at the per-
recruit scale. El Nino conditions reduced per-recruit en-
ergy consumption in both sexes in contrast to baseline
conditions (Fig. 4, A and B). Incorporating mortality
lowered the contribution of older age groups, where
individual consumption was highest (Fig. 3, A and B),
thereby magnifying the El Nino effects on young fish.
The negative effects on young age classes were exac-
erbated in females by slowed maturation and reduced
7b
Fishery Bulletin 103(1)
0 5 10 15 20
Age (y)
Figure 2
Estimated energy consumption by S. mystinus under baseline model con-
ditions. (A) Females and males at the per-individual scale. (B) Females
and males at the per-recruit scale, assuming a mortality rate (Z) of 0.2
(i.e., no fishing mortality).
Table 3
Final weights and cumulative energy consumptions for
female and male S. mystinus from bioenergetics models
run under baseline and El Nino conditions. All values are
taken from the end of the 30th year. Cohort-A and cohort-B
individuals experienced five and eight El Nino events,
respectively (see Figs. 3 and 4).
Final weight (g)
Total
consumption (MJ)
Model
Females
Males Females Males
Baseline
Cohort A
Cohort B
1,134.3
1,129.4
1,126.8
617.2
616.5
616.1
285.0
278.1
273.6
174.6
173.3
172.1
fecundity (due to slower growth), resulting in lower
per-recruit consumption to meet reproductive costs.
Thirty-year cumulative per-recruit energy consumption
was 20.0 MJ for cohort-A females (3.2% lower than
the baseline value), and 19.4 MJ for cohort-B females
(6.3% less than the baseline value). Cumulative per-re-
cruit consumption by cohort-A males was 14.5 MJ (1.9%
lower than baseline), whereas cohort-B males consumed
14.2 MJ (4.4%. less than the baseline level). The reduc-
tion of cumulative egg production was also more drastic
at the per-recruit scale: cohort-A females produced 15%
fewer eggs than the baseline level, whereas cohort-B fe-
males produced 23% fewer eggs at the per-recruit scale
(Fig. 4C). These reductions in egg production were re-
lated to smaller size, lower fecundity in El Nino years,
delayed maturation, and accumulative mortality, all of
which allowed fewer females to reach maturity.
Harvey: Effects of El Nino events on consumption and egg production of Sebastes spp.
77
m 12 "
O
o
O
180
120
60 "
D
10
15
20
10
15
20
10
15
20
10
15
Age (y)
20
25
25
25
30
30
30
B
B
B
B
B
B
B
B
A
A
r
A
— i
A
1
r
A
1
30
Figure 3
Estimated energy consumption and egg production by S. mystinus at
the per-individual scale, under baseline conditions and for two cohorts
(A and B) in which El Nino events occurred every three to seven years.
(A) Female energy consumption. (B) Male energy consumption. (C) Egg
production. (D) Timing of El Nino events for cohorts A and B.
Effects of El Nino on fished cohorts
Adding fishing mortality to the total mortality rate
applied in the per-recruit simulations caused changes in
the total energy consumption and egg production of S.
mystinus experiencing repeated El Nino events, in con-
strast to the baseline state. Under both El Nino regimes,
per-recruit consumption by both sexes increased slowly
as Z increased until it was nearly identical to the base-
line level for cohort A (Fig. 5A) or exceeded the baseline
for cohort B (Fig. 5B). The reason for this is that the
slower growth experienced during El Nino years meant
that fish reached 200 mm (the size of recruitment into
the fishery) later and therefore were not as rapidly sub-
jected to fishing mortality as baseline fish. This extra
period of feeding prior to reaching 200 mm was sufficient
to equal or exceed the per-recruit energy consumption
level in the baseline model.
In contrast, increased Z caused strong declines in
egg production, and that effect was exacerbated by the
frequency of El Nino years, as demonstrated by the
steeper decline in cohort B (Fig. 5B). Delayed matura-
tion caused by El Nino meant that many females were
removed by fishing before they were able to reproduce;
78
Fishery Bulletin 103(1)
Baseline
--■ — Cohort A
—a— Cohort B
10 15
D
B
B
B
B
B
B
B
B
A
A
A
A
A
10
15
Age (y)
20
25
30
Figure 4
Estimated energy consumption and egg production by S. mystinus at
the per-recruit scale, under baseline conditions and for two cohorts (A
and B) in which El Nino events occurred every three to seven years.
(Al Female enrgy consumption. (B) Male energy consumption. (C) Egg
production. (Dl Timing of El Nino events for cohorts A and B.
furthermore, those that escaped fishing had lower fe-
cundities because of their smaller size and reduced
egg production because of the number of El Nino years
experienced.
Sensitivity analysis
Based on the RPSS analysis, sensitivity of rockfish
bioenergetics models to parameter variation was a func-
tion of sex, size, and the CV of the parameter set. When
CV = 2%, the model was most sensitive to respiration
parameters in Equation 2 (particularly RB, RQ, and
RTO) and to ED, although the rank order varied slightly
by sex (Fig. 6, A and B). The sum of the RPSScv=2fJ
for all parameters was >0.99 for both the male and
female models. This result implies that energy consump-
tion responded linearly to parameter variation because
summed RPSS values scale from 0 to 1, with 1 implying
a linear response to parameter perturbation (Bartell et
al., 1986). When CV increased to 10%, the rank order
of parameter sensitivity changed slightly, although res-
piration parameters and ED remained most important
Harvey: Effects of El Nino events on consumption and egg production of Sebastes spp.
79
1.0 -
0.9 -
A
0.8 -
0.7 -
Male consumption
Female consumption
3
>
0.6 -
— o — Egg production
a)
o
0.5 -
1 1 1 1
0.2
0.4
0.6
0.8
1.0
o
c
o
1.0 -
^__^^
Q
O
a.
0.9 -
0.8 -
0.7 -
0.6 -
0.5 -
1 1 1 ^"
0.2
0.4 0.6 0.!
Total mortaility rate (Z)
1.0
Figure 5
Effects of mortality (Z, increased due to fishingl on S. mystinus responses
to El Nino events, in relation to a baseline model with identical Z. (A)
Cohort A, which experienced 5 El Nino years (see Figs. 3 and 4). (B)
Cohort B, which experienced 8 El Nino years.
(Fig. 6, C and D). RPSScv=10(-r values declined to 0.84
and 0.94 for females and males, respectively, indicating a
greater degree of nonlinearity in response to parameter
variation. Finally, when CV increased to 20%, there
were major changes in parameter rank order and RPSS,
especially for females (Fig. 6E). All female parameters
essentially had equal weight, and RPSScv=2(r; dropped
dramatically to 0.14, indicating a nonlinear response to
parameter variation. Males experienced slight changes
in parameter rank order at CV = 20% (Fig. 6F) and
increasingly nonlinear behavior related to parameter
variation (RPSScv=20r; = 0.81). Because the major differ-
ence in the models for the two sexes is the reproductive
terms (i.e., Eq. 4 for females vs. the simple GSI calcula-
tion for males), the GA or GB terms (or both) appear
to be the cause of poor female model performance at
high parameter uncertainty. Also, because GA and GB
should only affect female energy budgets as the females
mature, model sensitivity to those parameters is likely
size dependent.
Energy consumption estimates generated in RPSS
analyses were consistently greater than estimates gen-
erated by the baseline deterministic model, which used
the parameter values from Table 1. Mean consump-
tion estimates and standard deviations increased as
the parameter CV increased (Table 4). This effect was
more pronounced in females than in males, especially
when parameter CV=20%. At that level of parameter
uncertainty, male and especially female consumption
estimates had very large standard deviations.
80
Fishery Bulletin 103(1)
in
C/3
D-
0.30 - A
0.25
0.20
0.15
0.10 H
0.05
0.00
n n,
0.30 -| Q
0.25-
0.20 -
0.15 -
0.10 -
0.05 - 1
0 00 -±K-
nnnnnnnn
fi
0.30
0.25
0.20 H
0.15
0.10 -
0.05 -
0.00
E
<m0k05<<<<mQQ
ccoceOhi-Q^dooujiu
< dc ce co cd
0.30 n
0.25
0.20
0.15 -
0.10
0.05 -
0.00
B
~r — ^r — ^
n n
0.30 -i J)
0.25
0.20
0.15
0.10
0 05
0.00
nnnnn
0.30 -, y
0.25 ■
0.20 -
0.15
IIlOl-hDll.
< tr oc co
CD
Parameter
Figure 6
Relative partial sums of squares (RPSS) at three levels of uncertainty for param-
eters of the Sebastes bioenergetics model. Parameters are listed in Table 1. (A, C, E)
Females. (B, D, F) Males. Parameter coefficients of variation (CV) were 2% (A, B),
10% (C, D), or 20% (E, F).
Discussion
According to the generic rockfish bioenergetics model,
repeated exposure to El Nino conditions lowered the
growth, maturation rate, and reproductive level of S.
mystinus. This happened at both the individual and
per-recruit scales; the latter may be most relevant when
placing a cohort of fish into a community context because
younger age groups have the greatest potential energy
demand when mortality is accounted for. In El Nino
years, increased temperatures caused respiration rates
of both sexes to increase in contrast to respiration rate
in the baseline model, whereas lower growth rates and
poor fecundity reduced energy demands. In the long
term, these rates equated to a net decrease in energy
consumption, which was more pronounced in females
than in males because of the higher growth rate and
reproductive investment for females. Ironically, adding
mortality through fishing pressure lessened the effect
of El Nino on S. mystinus consumption in contrast to
baseline conditions, but that was because rockfish in the
El Nino models took longer to reach sizes vulnerable to
Harvey: Effects of El Nino events on consumption and egg production of Sebastes spp.
81
Table 4
Energy consumption estimates for S. mystinus by a deter-
ministic baseline model (parameters given in Table 11
and simulations run for relative partial sums of squares
(RPSS) analysis. Estimates from the RPSS analysis were
determined at three levels of parameter uncertainty, with
parameter coefficients of variation (CV) equal to 2, 10, or
20%.
Estimated energy consumption
(MJ:mean ±SD)
Model
Females
Males
Baseline
CV = 2%
CV = 10%
CV = 20%
285.0
286.0 ±16.1
314.3 ±102.8
515.1 ±1131.4
174.6
175.3 ±10.1
183.9 ±57.6
209.0 ±131.7
fishing. However, the El Nino models may have overesti-
mated per-recruit consumption because I did not add in
direct El Nino related mortality; natural mortality may
actually increase during El Nino years, as suggested by
anecdotal mass mortality events affecting S. mystinus
during the 1982-83 El Nino (Bodkin et al., 1987).
More dramatic than the effect of El Nino on energy
consumption was the effect on egg production. Indi-
vidual and per-recruit lifetime fecundity dropped (by
roughly 12-19% and 15-23%, respectively) in the El
Nino models — an effect that was even more drastic as
fishing pressure increased. These declines were dispro-
portionate in comparison to changes in long-term energy
consumption, which declined by <4% at the individual
scale and <7% at the per-recruit scale under even an
arduous El Nino regime; and compared to changes in
the size of age-30 individuals, which were essentially
equal in the baseline and El Nino models. In other
words, under a long-term climate regime with El Nino
events, total energy demand of females is similar to a
baseline regime, and lifetime gross conversion efficiency
(growth/consumption) increases, but the conversion ef-
ficiency of consumption into reproduction is constrained
considerably. That constraint is due largely to delayed
maturity, poorer overall fecundity (particularly in El
Nino years), and, at the per-recruit scale, the culling
effect of natural and fishing mortality.
Of course, the implications from the models for S.
mystinus must be viewed as hypotheses based on a ge-
neric Sebastes model. Although the ability of the bioen-
ergetics approach to synthesize demographic, physiologi-
cal, and environmental data makes it a powerful tool
for characterizing dynamic linkages between fish, prey
communities, and climate, use of this approach for stud-
ies of Sebastes will require additional empirical data.
A rich body of information exists for some parameters,
such as growth rate, fecundity, and depth distribution
(Love et al., 1990; Love et al., 2002). However, many
relevant data are lacking, notably diet data. Because
of seasonal changes in temperature and reproductive
state, rockfish energetics are also seasonal. Seasonal
diet changes have been observed in several (largely in-
shore) species (Love and Ebeling, 1978; Hallacher and
Roberts, 1985; Hobson and Chess, 1988; Murie, 1995).
Diets may also change with fish size (Love and Ebel-
ing, 1978; Murie, 1995). Data that capture the trophic
ontogeny of different species would allow a better depic-
tion of how energy consumptive patterns of a population
change with demographics, particularly given the dis-
proportionate demands of younger age classes (Fig. 4).
When possible, diet data should be based on weight or
volume so that estimates of energy requirements can be
readily converted into masses of prey consumed.
Properly incorporating environmental variability will
require information not just on temperature variability,
but on how rockfish growth, reproduction, and diet vary
under different climate regimes. As discussed previ-
ously, El Nino and Pacific Decadal Oscillation events
have been shown to affect growth, fecundity, and re-
cruitment success of some well-studied species of rock-
fish. Little information is available on how these factors
are affected by La Nina events, however. Furthermore,
climate variability may lead to markedly different prey
communities (Brodeur and Pearcy, 1992; Lea et al.,
1999), resulting in diet shifts about which we currently
have little information for most rockfish. Because S.
mystinus maintained relatively high energy demand
during El Nino years, despite slower growth rates and
lower fecundity, the prey quality and quantity during
such events is clearly important.
Ultimately, these models can be expanded to the pop-
ulation level to place rockfish in the context of their
communities. This approach can elucidate how factors
such as fishing, environmental variability, and recruit-
ment variability influence the role of rockfish as preda-
tors on specific prey taxa, as has been done in bioener-
getics models for other predators (Kitchell et al., 1997;
Essington et al., 2002; Schindler et al., 2002). Because
energy budgets are influenced by fish size and reproduc-
tive state, expanding to the population level will require
size- or age-structured population models, such as those
used in many rockfish stock assessments (e.g., Pacific
Fishery Management Council, 2000). Most Sebastes
stock assessments to date are for species that live in
shelf or slope habitats, whereas the species whose food
habits and basic energetic information are best known
are inshore species. Therefore, a key part of producing
useful bioenergetics analysis at the population level will
be to prioritize populations or species assemblages for
which bioenergetics models might be most useful, and to
identify which type of information (population structure
or basic biology and ecology) is lacking.
Finally, the generic model parameters in this study re-
quired information from several species. Interspecies pa-
rameter borrowing has been criticized (Ney, 1993), and
the results from such models deserve careful appraisal.
The sensitivity analysis demonstrates the importance
of this issue: with increasing parameter uncertainty.
82
Fishery Bulletin 103(1)
the model not only became less reliable (i.e., RPSS de-
creased, especially for females), but also projected higher
energy consumption rates. However, the sensitivity anal-
ysis points specifically to the parameters (respiration,
energy density, female fecundity) that are most influ-
ential and deserve attention in laboratory studies. Ad-
ditional work is required to better characterize ACT, the
activity multiplier, particularly for Sebastes species that
are more pelagically oriented. In many bioenergetics
models, consumption is a parameter, such that growth,
not consumption, can be the model output. Although
studies of energy consumption by juvenile black rock-
fish (S. melanops) have been undertaken (Boehlert and
Yoklavich, 1983), more effort is needed in this area.
Conclusion
Although there are limitations to realizing the potential
of bioenergetics models in the study of rockfish ecology,
those limitations do not overshadow the value of using
available information to produce general heuristic models
to examine important questions. Such questions include
how climate variability affects rockfish consumption pat-
terns, reproduction, and predation rates on different prey
taxa; how size-selective fishing may influence rockfish
consumption patterns; and how rockfish energy demands
compare with available prey resources in regions where
population rebuilding efforts are proposed or under way.
When ultimately coupled with population models, the
bioenergetics approach offers a means to clarify the role
that rockfish play in their communities.
Acknowledgments
Suggestions from Phil Levin, Nick Tolimieri, Daniel
Schindler, Rich Zabel, Jim Kitchell, Steve Bartell, Kevin
Piner, Tina Wyllie-Echeverria, and two anonymous
reviewers greatly improved this manuscript.
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84
Abstract — Short-duration (5- or 10-
day) deployments of pop-up satellite
archival tags were used to estimate
survival of white marlin \Tetrapturus
albidus) released from the western
North Atlantic recreational fishery.
Forty-one tags, each recording tem-
perature, pressure, and light level
readings approximately every two
minutes for 5-day tags (n = 5) or four
minutes for 10-day tags (« = 36), were
attached to white marlin caught with
dead baits rigged on straight-shank
("J") hooks (rc = 21) or circle hooks
(?i=20) in offshore waters of the U.S.
Mid-Atlantic region, the Dominican
Republic, Mexico, and Venezuela.
Forty tags (97.8%) transmitted data
to the satellites of the Argos system,
and 33 tags (82.5%) transmitted data
consistent with survival of tagged ani-
mals over the deployment duration.
Approximately 61% (range: 19-95%)
of all archived data were successfully
recovered from each tag. Survival was
significantly (P<0.01) higher for white
marlin caught on circle hooks (100%)
than for those caught on straight-
shank ("J") hooks (65%). Time-to-
death ranged from 10 minutes to 64
hours following release for the seven
documented mortalities, and five ani-
mals died within the first six hours
after release. These results indicate
that a simple change in hook type
can significantly increase the sur-
vival of white marlin released from
recreational fishing gear.
Application of pop-up satellite archival tag
technology to estimate postrelease survival
of white marlin iTetrapturus albidus)
caught on circle and straight-shank ("J") hooks
in the western North Atlantic recreational fishery4
Andrij Z. Horodysky
John E. Graves
Virginia Institute of Marine Science
College of William and Mary
Route 1 208 Greate Rd.
Gloucester Point, Virginia 23062
E mail address (for J. E. Graves, contact author): graves(S>vims edu
Manuscript submitted 20 January 2004
to the Scientific Editor's Office.
Manuscript approved for publication
2 August 2004 by the Scientific Editor.
Fish. Bull. 103:84-96 (2005).
Atlantic white marlin (Tetrapturus
albidus Poey, 1860) are targeted by a
directed recreational fishery and occur
as incidental bycatch in commercial
fisheries throughout the warm pelagic
waters of the Atlantic Ocean. Total
reported recreational and commercial
landings of white marlin peaked at
4911 metric tons (t) in the mid-1960s,
declined steadily during the next 15
years, and have since fluctuated with-
out trend between 1000 and 2000 t
despite substantial increases in fish-
ing effort (ICCAT, 2003). Recent popu-
lation assessments conducted by the
Standing Committee for Research and
Statistics (SCRS) of the International
Commission for the Conservation of
Atlantic Tunas (ICCAT) indicate that
the Atlantic-wide white marlin stock
is currently at historically low levels
and has been severely overexploited
for over three decades (ICCAT, 2003).
In the 2002 white marlin assessment,
the 2001 biomass was estimated to
be less than 12% of that required for
maximum sustainable yield (MSY)
under the continuity case (ICCAT,
2003). Current harvest is estimated to
be more than eight times the replace-
ment yield (ICCAT, 2003).
In response to the overfished status
of white marlin, ICCAT has adopted
binding international recommendations
to decrease overall Atlantic landings of
this species by 67% from 1996 or 1999
levels (whichever is greater) through
the release of all live white marlin
from commercial pelagic longline and
purse-seine gears (ICCAT, 2001). How-
ever, even these dramatic reductions
may be ineffective in rebuilding the
white marlin stock. Goodyear (2000)
estimated that a 60% decrease from
1999 fishing mortality levels would be
required to halt the reduction of At-
lantic blue marlin (Makaira nigricans).
Because white marlin experience high-
er levels of fishing-induced mortality,
it is expected that the reduction in
mortality required to stabilize this
stock will be even greater.
Management measures within the
United States, established by the At-
lantic Billfish Fishery Management
Plan (FMP) (NMFS, 1988) and sub-
sequent Amendment 1 (NMFS, 1999),
have also been implemented to reduce
white marlin fishing mortality. U.S.
commercial fishermen have been pro-
hibited from landing or possessing
all Atlantic istiophorids since 1988.
Dead discards of white marlin from
the U.S. commercial pelagic longline
fishery peaked at 107 t in 1989, and
have decreased to 40-60 t over the
last several years (White Marlin
Status Review Team1). Management
♦Contribution 2610 from the Virginia
Institute of Marine Science, College of
William and Mary, Gloucester Point, VA
23062.
1 White Marlin Status Review Team.
2002. Atlantic white marlin status
review document, 49 p. Report to
the National Marine Fisheries Ser-
vice. Southeast Regional Office,
September 3, 2002. www.nmfs.gov/
prot_res/readingrm/Candidate_Plus/
wh it e„m a rl in/ whm_status_review.pdf
Horodysky and Graves: Estimation of survival of Tetrapturus albidus caught and released in the North Atlantic recreational fishery 85
measures for U.S. recreational anglers include a mini-
mum size of 66 inches lower jaw fork length (NMFS,
1999) and mandatory reporting of landed billfishes
(NMFS, 2003). White marlin landings by U.S. recre-
ational anglers ranged between 40 and 110 t from 1960
to the mid-1980s (Goodyear and Prince, 2003) and have
decreased to about 2 t in recent years. At present, over
99% of the 4000-8000 white marlin estimated to be
caught annually by U.S. recreational fishermen are
released (Goodyear and Prince, 2003).
The benefit of current management measures that
rely on the release of white marlin cannot be evaluated
because levels of postrelease survival are not known for
this species. Recapture rates of billfishes tagged with
conventional tags are very low (0.4-1.83%; Prince et
al., 2003; Ortiz et al., 2003), which may result from
high postrelease mortality, tag shedding, or a failure
to report recaptures (Bayley and Prince, 1994; Jones
and Prince, 1998). Little acoustic tracking has been
conducted on white marlin (Skomal and Chase, 2002;
n=2 tracks), but similar work on other istiophorid spe-
cies indicates relatively high postrelease survival for
periods ranging from a few hours to a few days for fish
released from recreational fisheries (e.g., sailfish: Jolley
and Irby, 1979; blue marlin: Holland et al, 1990; Block
et al., 1992; black marlin: Pepperell and Davis, 1999).
However, data from acoustic tracking studies bear limi-
tations and biases that preclude their use in estimating
billfish postrelease survival (Pepperell and Davis, 1999;
Graves et al., 2002). In the absence of better data, all
recreationally released billfishes have been assumed
to survive (Peel, 1995), and estimates of white marlin
postrelease mortality are currently not incorporated
into ICCAT landing statistics or assessments (White
Marlin Status Review Team, 2002).
Developments in pop-up satellite archival tag (PSAT)
technology have greatly improved scientific under-
standing of the behavior, movements and postrelease
survival of highly migratory marine fishes, including
bluefin tuna (Block et al., 2001), swordfish (Sedber-
ry and Loefer, 2001), white sharks (Boustany et al.,
2002), blue marlin (Graves et al., 2002; Kerstetter
et al., 2003), black marlin (Gunn et al., 2003), and
striped marlin (Domeier et. al, 2003). To estimate the
postrelease survival of billfishes, researchers have
used PSAT deployment durations ranging from five
days to seven months (Graves et al., 2002; Domeier
et al., 2003; Kerstetter et al., 2003). Goodyear (2002)
cautioned that longer duration deployments increase
the potential for tag shedding, tag malfunction, and
data corruption, and may bias postrelease survival
estimates by including additional sources of mortality
other than the capture event. Graves et al. (2002) con-
sidered five days to be an appropriate window to detect
mortality in blue marlin released from recreational
gear in offshore waters of Bermuda, citing recaptures
of blue marlin tagged with conventional tags within
five days of the initial tagging event as evidence that
some istiophorids may recover sufficiently to resume
feeding shortly after capture.
Survival estimates for other istiophorid species re-
leased from recreational fishing gear may not be ap-
plicable to white marlin. One reason may involve body
size: recreationally caught blue marlin and striped
marlin are generally larger than white marlin. Inter-
and intra-specific differences in body size may affect
feeding behavior, fight time, handling time, as well as
postrelease recovery (Kieffer. 2000). Another reason
may involve the different angling techniques used to
catch certain istiophorid species. Blue marlin often hook
themselves in the mouth and head while aggressively
pursuing high speed trolled lures (Graves et al., 2002).
In contrast, as white and striped marlin approach a
specific baitfish in the trolling spread, many anglers
free-spool (i.e., "drop-back") rigged natural baits to
feeding marlin to imitate stunned baitfish (Mather
et al., 1975). This process increases the probability
that straight-shank ("J") hooks rigged with natural
baits will damage vital internal areas such as the gills,
esophagus, and stomach (Prince et al., 2002a). Recently,
several studies have documented a reduction in hook-
induced trauma associated with the use of circle hooks
in fisheries targeting estuarine and pelagic fishes (Lucy
and Studholme, 2002). However, there is little research
specifically comparing levels of postrelease survival of
pelagic fishes caught on circle and straight-shank ("J")
hooks. Prince et al. (2002a) and Skomal et al. (2002)
examined hooking locations and injuries in sailfish
and bluefin tuna caught on both hook types but lacked
postrelease survival data from study animals. Domeier
et al. (2003) did not detect a significant difference be-
tween striped marlin caught on circle and straight-
shank ("J") hooks, although the authors did observe
significantly decreased rates of deep-hooking and tissue
trauma with circle hooks compared to straight-shank
("J") hooks.
We used data recovered from PSATs to estimate
the survival of 41 white marlin caught on circle and
straight-shank ("J") hooks in the recreational fishery
and released in the western North Atlantic Ocean dur-
ing 2002-2003. In addition, differences in hooking
locations and hook-induced trauma for white marlin
caught on circle and straight-shank ("J") hooks were
assessed.
Methods
Tags
The Microwave Telemetry, Inc. (Columbia, MD) PTT-100
HR model PSAT tag was used in our study. This tag is
slightly buoyant, measures 35 cm by 4 cm, and weighs
<70 grams. The body of the tag contains a lithium com-
posite battery, a microprocessor, a pressure sensor,
a temperature gauge, and a transmitter, all housed
within a black resin-filled carbon fiber tube. Flotation
is provided by a spherical resin bulb embedded with
buoyant glass beads. This tag model is programmed to
record and archive a continuous series of temperature,
86
Fishery Bulletin 103(1)
Figure 1
White marlin {Tetrapturus albidus) tagged with a Microwave Telemetry PTT-100 HR pop-up
satellite tag lA) and conventional streamer tag (B).
light, and pressure (depth) measurements, and can
withstand pressure equivalent to a depth of 3000 m.
Tags programmed to disengage after five days (n = 5)
recorded measurements approximately every two min-
utes, whereas tags programmed to disengage after ten
days («=35) recorded measurements about every four
minutes. Additionally, both 5-day and 10-day tag models
transmitted archived and real-time surface temperature,
pressure, and light level readings to orbiting satellites
of the Argos system for 7-10 days following release from
the study animals.
PSATs were attached to white marlin by an assembly
composed of 16 cm of 400-pound test Momoi® brand
(Momoi Fishing Co., Ako City, Japan) monofilament
fishing line attached to a large hydroscopic, surgical-
grade nylon intramuscular tag anchor according to the
method of Graves et al. (2002). Anchors were implanted
with 10-cm stainless steel applicators attached to 0.3-m,
1-m, or 2-m tagging poles (the length of the tagging pole
varied depending on the distance from a boat's gun-
whales to the water) and were inserted approximately
9 cm deep into an area about 10 cm posterior to the
origin of the dorsal fin and 5 cm ventral to the base of
the dorsal fin (Fig. 1). In this region, the nylon anchor
has an opportunity to pass through and potentially
interlock with pterygiophores supporting the dorsal fin
well above the coelomic cavity (Prince et al., 2002b;
Graves et al., 2002). When possible, a conventional tag
was also implanted posterior to the PSAT.
Deployment
White marlin were tagged in the offshore waters of
the U.S. Mid-Atlantic Bight, the Dominican Repub-
lic, Mexico, and Venezuela (Table 1). These locations
were chosen for vessel availability and seasonal concen-
trations of white marlin. All tagging operations were
conducted on private or charter recreational fishing
vessels targeting billfishes and tunas. White marlin
were caught on 20-40 lb class sportfishing tackle and
fought in a manner consistent with typical recreational
fishing practice (G. Harvey, personal commun.2). The
first 41 white marlin caught and successfully positioned
boatside were tagged. Fish were not brought to the boat
until they were sufficiently quiet to facilitate optimal
tag placement. When possible, crew members positioned
white marlin for tagging by holding them by the bill and
dorsal fin in the water alongside the boat, a technique
often used when controlling a billfish to remove hooks.
On boats with high gunwhales that prohibited holding
the captured fish by the bill, the marlin were "leadered"
to the boat's side and moved into position for tagging
when calm. Six hooked white marlin escaped prior to
tagging because frayed leaders broke or hooks slipped
during this process. Hooks were removed when feasible;
2 Harvey, G. 2002. Personal commun. Guy Harvey Enter-
prises. 4350 Oakes Rd. Suite 518. Davie, FL 33314.
Horodysky and Graves: Estimation of survival of Tetrapturus albidus caught and released in the North Atlantic recreational fishery 87
Table 1
Summary of white marlin {Tetrapturus albidus) tagging locations
during 2002-
2003.
Location Dates of tagging
Tag deployment
duration (in days)
Number of tags
deployed
Mid-Atlantic Coast 2002: 18-22 Aug, 5-21 Sep
10
11
2003: 22 Aug
10
1
Punta Cana, Dominican Republic 2002: 15-19 May
5
5
Isla Mujeres, Mexico 2003: 10-12 June
10
3
La Guaira, Venezuela 2002 : 23-25 Nov
10
6
2003: 12-13 Sep 1 Oct
10
15
otherwise, they were left in the fish and the leader was
cut as close to the animal as possible prior to release.
Both practices are common in the recreational billfish
fishery. After capture and positioning alongside tagging
vessels, six white marlin were observed to have lost color,
and were lethargic and unable to maintain vertical posi-
tion in the water. These fish were resuscitated alongside
the moving boat for 1-5 minutes prior to release — also
a common practice in the recreational fishery.
Gear type, fight time, handling time, fight behav-
ior, hooking location, overall fish condition, estimated
weight, and GPS coordinates of the release location
were recorded for each tagged white marlin. Fight time
was defined as the interval from the time the fish was
hooked to the time it was "leadered" alongside the boat
prior to tagging. Handling time included tagging and
resuscitation, if applicable. In accordance with Prince
et al. (2002a), straight-shank ("J") hooks were defined
as those with a point parallel to the main hook shaft,
whereas circle hooks were defined as having a point
perpendicular to the main hook shaft. All circle and
straight-shank ("J") hooks were rigged with dead bal-
lyhoo (Hemiramphus brasiliensis) bait. Size 7/0 Mustad
straight-shank ("J") hooks (models 9175 and 7731) were
rigged with the hook exiting the ventral surface of the
ballyhoo. Two models of circle hooks were employed in
this study: Mustad Demon Fine Wire (model C39952BL,
size 7/0; 5° offset, «=9) and Eagle Claw Circle Sea
(L2004EL, sizes 7/0-9/0; non-offset, n = ll). All circle
hooks were rigged so that they pointed upwards from
the head of the ballyhoo (see Prince et al., 2002a). The
rigging designations and fishing techniques unique to
each hook type were maintained in our study to reflect
the usual application of circle and straight-shank ("J")
hooks in the white marlin recreational fishery. Other
than these differences, all handling, tagging, and re-
cording methods were the same for both treatments.
Hooking locations were pooled into two categories:
jaw, externally visible (including all lip-hooked, foul-
hooked, and bill-entangled white marlin) and deep, not
externally visible (including all white marlin hooked
in the palate, gills, esophagus, and everted stomachs).
Bleeding was recorded as present or absent, and the
general location of bleeding was recorded when it was
possible to identify the source.
Data analysis
Survival of released white marlin was determined from
two distinct lines of evidence provided by the satellite
tags: net movement, and water temperature and depth
profiles. Time series of water temperature and depth
measurements taken about every 2 minutes (5-day tags)
or 4 minutes (10-day tags) were used to discriminate
surviving from moribund animals. Net movement was
determined as a minimum straight line distance trav-
eled between the coordinates of the initial tagging event
and the coordinates of the first reliable satellite contact
with the detached tag (inferred to be the location of
tag pop-up) derived from Argos location codes 1, 2, or
3 for the first or second day of transmission. In cases
where tags did not report more precise location codes,
an average of all location code 0 readings for the first
day of transmission was used as a proxy for the loca-
tion of the tag pop-up. To determine the directions (and
magnitudes) of observed surface currents in areas where
fish were tagged, GPS coordinates (Argos location codes
of 1, 2, or 3, or a daily mean of location code 0, for tags
lacking these) were plotted for the 7-10 days that the
tags were floating at the surface and transmitting data
to satellites. Maps, tracks, and distances were generated
by using MATLAB (version 6.5, release 13.1, Mathworks
Inc, Natick, MA).
Cochran-Mantel-Haenszel (CMH) tests were used
to address the effect of circle and straight-shank ("J")
hooks on survival, hooking location, and the degree
of hook-induced trauma. A Yates correction for small
sample size was applied when expected cell values were
less than 5 (Agresti, 1990). The effects of fight time
and total handling time on survival were assessed with
Wilcoxon-Mann-Whitney exact tests, with the null hy-
pothesis that there was no difference between surviving
and moribund white marlin. All statistical analyses
were conducted by using SAS (version 8, SAS Institute,
Cary, NC). The lone nonreporting tag observed in our
study was excluded from all subsequent analyses.
88
Fishery Bulletin 103(1)
We conducted bootstrapping simulations
to examine the effect of sample size on the
95% confidence intervals of the release mor-
tality estimates using software developed by
Goodyear (2002). Distributions of estimates
were based on 10,000 simulations with an
underlying release mortality equivalent to
that observed for straight-shank ("J") hooks
for experiments containing 10-200 tags and
no sources of error (e.g., no premature re-
lease of tags, no tagging-induced mortality,
and no natural mortality).
Results
Forty-one white marlin were tagged in four
geographic locations during 2002-2003
(Table 1). Information for each fish is summa-
rized in Table 2. Fight times were fairly typi-
cal for this fishery (mean: 15.8 min, range:
3-83 min), although two animals required
more than 30 minutes before they were suf-
ficiently calm at boatside for tag placement.
Overall, forty tags (97.6%) transmitted data
to the satellites of the Argos system and of
these, thirty-seven tags remained attached
to study animals for the full five- or ten-
day duration. One five-day tag was released
prematurely from a surviving white marlin
after 2.5 days, presumably because it had
not been attached securely. This individual
showed behavior similar to other surviving
white marlin while the tag was attached
and was presumed to have survived for the
purposes of our study. Additionally, two 10-
day tags attached to moribund white marlin
disengaged from the carcasses prior to the
expected date after an extended amount of
time at a constant depth and temperature
on the seafloor. Approximately 61% of data
(range: 19-95%) were successfully transmit-
ted from reporting tags.
Overall, 33 of 40 tags (82.5%) returned
data that indicated the survival of tagged
animals throughout the duration of tag de-
ployment. Surviving white marlin exhib-
ited daily variations in water temperature
and depth data while carrying PSATs (Fig.
2A). The net movement of surviving ani-
mals could not be explained by the speed or
direction of current patterns alone over
the course of the tag deployment (Table 2,
Fig 3A). In contrast, moribund white mar-
lin (Fig. 2B) sank to the seafloor (237-1307
m) and to constant water temperatures (3.7-12.5°C),
where they remained until the tags disengaged and
floated to the surface not far from the initial tag-
ging location (Fig 3B). Five of the seven moribund
white marlin died within the first six hours of release;
Surviving white marlin
30
25
15
10
rr
S. "60
80
120
08/22 08/23 08/24 08/25 08/26 08/27 08/28 08/29 08/30 08/31 09/01 09/02
Moribund white marlin
08/18 08/19 08/20 08/21 08/22 08/23 08/24 08/25 08/26 08/27 09/28 09/29
Figure 2
Depth and temperature tracks for a surviving (A) (MA12) and
moribund (B) (MA01) white marlin (Tetrapturus albidus). Filled
symbols correspond to measurements taken while tags were attached
to animals, hollow symbols refer to measurements taken after pop-
up while tags were transmitting data to Argos satellites. Gray bars
denote periods of local night.
four of these five animals died within the first hour
(Table 2).
The two white marlin that experienced the longest
fight times (46 and 83 min) died more than 24 hours
following their release. White marlin VZ03-11 had a
Horodysky and Graves: Estimation of survival of Tetrapturus albidus caught and released in the North Atlantic recreational fishery 89
Table 2
Summary information for tagged white marlin (Tetrapturus albidus) released from recreational fishing gear in the western
North Atlantic Ocean. Total fight time is defined as the interval between the time that the fish was hooked and the time that it
was brought to the side of the boat prior to tagging. Handling time included tagging and resuscitation, where applicable. "D/N"
refers to deep, not externally visible hooking locations, "foul" refers to a white marlin hooked in the dorsal musculature. Tail-
wrapped fish are denoted with the symbol "T", resuscitated marlin are denoted with the symbol "R".
Estimated
Fight
Handling
Location
Fate
Movement
weight
time
time
Hook
of hook
Bleeding
(living or
(nmi/km
Tag number
<kg)
(minutes)
(minutes)
type
in or on fish
(Yes/No)
dead)
direction)
DR02-01
23
19
"J"
D/N
N
L
23/43 NW
DR02-02
20
29
"J"
D/N
N
L
39/72 NW
DR02-03
20
29
"J"
D/N
Y
L
33/61 NE
DR02-04
25
83
"J"
D/N
Y
D
—
DR02-05
20
6
"J"
D/N
N
L
60/111 SE
MA01
18
7
"J"
D/N
Y
D
—
MA02
20
24
"J"
jaw
N
L
63/117 S
MA03
18
9
"J"
D/N
Y
L
51/94 S
MA05
20
17
"J"
D/N
Y
L
24/44 S
MA06
18
7
"J"
D/N
Y
D
—
MA07
20
7
"J"
jaw
Y
D
—
MA08r' «
25
17
"J"
jaw
N
D
—
MA09
23
9
"J"
jaw
N
L
103/191 NE
MA10
23
13
"J"
jaw
Y
L
102/189 SE
MA11T
27
16
"J"
jaw
N
L
260/482 SE
MA12«
23
11
"J"
jaw
N
L
59/109 SE
VZ02-01
27
8
circle
jaw
N
L
118/219 NW
VZ02-02
23
12
circle
jaw
N
L
80/148 NE
VZ02-03r R
20
4
circle
jaw
N
L
69/128 NW
VZ02-04
18
9
circle
jaw
N
L
63/117 NE
VZ02-05
20
7
circle
jaw
N
L
67/124 N
VZ02-06
23
9
circle
jaw
N
L
98/181 NW
MX03-017'
27
15
circle
jaw
N
L
172/319 NW
MX03-02
18
14
circle
jaw
N
L
422/782 NW
MX03-037" R
23
21
circle
jaw
N
L
211/391 NW
VZ03-01
20
3
circle
jaw
N
L
85/157 NE
VZ03-02
30
6
circle
jaw
N
L
127/235 NE
VZ03-03
23
12
circle
jaw
N
L
16/30 N
VZ03-04
27
10
circle
jaw
Y
L
114/211 NE
VZ03-05
34
23
circle
jaw
N
L
40/74 W
VZ03-06
23
9
circle
jaw
N
L
49/91 NE
VZ03-07
23
15
circle
jaw
N
L
23/43 NE
VZ03-08
23
7
circle
jaw
N
L
39/72 NE
VZ03-097'
23
10
circle
jaw
N
L
127/235 NE
VZ03-107--*
23
28
2
"J"
jaw
N
L
81/150 NE
VZ03-llTfi
23
46
3
"J"
foul
N
D
—
VZ03-12
18
23
1
"J"
jaw
N
L
19/35 NW
VZ03-13
16
17
1
"J"
D/N
Y
D
—
VZ03-14
20
14
1
circle
jaw
N
L
131/243 NW
VZ03-15
20
8
1
circle
jaw
N
L
128/237 NE
90
Fishery Bulletin 103(1)
40°N r
38°N
36°N
34° N
32°N
78°W
75°W
72°W
69°W
66°W
Figure 3
Minimum straight line distances traveled by a surviving white marlin iTetrapturus albi-
dus) (solid line) (A) and the drifting track of a transmitting tag (dotted line) in offshore
waters of the U.S. Mid-Atlantic Bight. The cross (B) denotes a moribund white marlin
that sank to the seafloor shortly after it was released, illustrating that dead fish did
not travel far from the initial tagging coordinates.
fight time of 46 minutes and died 27 hours after tag-
ging, and DR02-04 had a fight time of 83 minutes and
died 64 hours after tagging (Fig. 4). There was no
significant difference in fight time (Z=0.4996, P=0.62)
between surviving and moribund white marlin, largely
due to the large range of fight times for moribund
animals. Handling times ranged from 1 to 5 minutes
per fish.
Hook type had a highly significant effect on the
postrelease survival of white marlin (Fig. 5). Fish
caught on circle hooks experienced significantly higher
survival (20 of 20; 100%) than those caught on straight-
shank ("J") hooks (13 of 20; 65%) (Yates's corrected
CMH x2=7-386, P<0.007). There were also highly sig-
nificant differences in hooking locations and hook-in-
duced trauma between hook types (Fig. 5). Odds ratios
revealed that white marlin caught on straight-shank
("J") hooks were 41 times more likely to be hooked
deeply (Yates's corrected CMH x2=H-48, P<0.001) and
over 15 times more likely to sustain hook-induced tissue
trauma resulting in bleeding (CMH x2=8-3, P<0.005)
than fish caught on circle hooks. Of the white marlin
caught on straight-shank ("J") hooks, half were hooked
in deep locations, and 70% of these fish were bleeding.
Four of the seven observed mortalities were those of
deep-hooked and bleeding fish. Overall, 56% of bleed-
ing, 40% of deep-hooked, and 57% of deep-hooked and
bleeding white marlin perished following release. In
contrast, all white marlin caught on circle hooks were
hooked in the jaw, and bleeding was evident only in a
single animal in which the hook point exited the edge
of the eye socket but did not damage the eye. Addition-
ally, 20%' (8 of 40) of the white marlin in our study
became entangled in the line during the fight and were
"leadered" to the boat tail-first, a condition known as
"tailwrapped" (Holts and Bedford, 1990). This phenom-
enon was equally distributed with respect to hook type.
Five tailwrapped white marlin required resuscitation,
and two tailwrapped white marlin hooked in the jaw
with straight-shank ("J") hooks died.
With the model developed by Goodyear (2002), the re-
sults of 10,000 simulated experiments at an underlying
true mortality rate of 35% indicated that approximate
95% confidence intervals for mortality estimates for an
experiment deploying 20 tags on white marlin caught
on straight-shank ("J") hooks range from 15%' to 59% in
the absence of confounding factors. A dramatic increase
in sample size would be required to improve the preci-
sion of mortality estimates (Fig 6). Doubling the sample
size (n=40) would decrease the 95% confidence intervals
to about ±15% of the true value and quadrupling the
number of tags (n = 80 PSATs) would reduce confidence
intervals to about ±10% of the true value. More than
200 PSATs would have to be deployed to lower the con-
fidence intervals to ±5% of the true value.
The net displacement of released white marlin was
variable among individuals and across locations and
was used as an independent line of evidence to assess
survival. Surviving white marlin demonstrated move-
ment patterns that cannot be explained by surface cur-
rents alone. Distances and directions of displacement
are summarized in Table 2. White marlin tagged with
Horodysky and Graves: Estimation of survival of Tetrapturus albidus caught and released in the North Atlantic recreational fishery 91
o
-10
•20
•30
•40
■50
-60
05 1 6 02
B
6 12 1
05/17/02
0 6 12
05/1 9/02
O-i
-1UO-
-200-
-300-
-400-
-500-
-600
/
-700-
^.
-800-
-900-
3 6 12 18 (
) ff 12 18
3 6 12 18
) 6 12 18 \ 0 6 12 18 0 6 12
05/16/
02
/ 05/17/02
05/18/02
05/19/02
\ 05/20/02
05/21/02
Final 4 hours
0-i
-10-
"!
""I
»4 «U
-20-
-30-
I
-40-
-50-
l
1
c
Figure 4
Track of DR02-04 showing mortality 64 hours after release: (A) the first 20 hours following
release, (B) the next 40 hours showing behavior similar to other surviving tagged marlin, and
(C) the four hours prior to mortality.
10-day PSATs moved an average of 101 (±84) nautical
miles (nmi) or 188 km (±155) and those tagged with
5-day PSATs moved an average of 38.8 nmi (±15.6) or
72 km (±29).
Discussion
The results of this study clearly indicate that hook
type significantly affects the survival of white marlin
released from recreational fishing gear. White marlin
caught on circle hooks were much more likely to survive
release from recreational fisheries than those caught on
straight-shank ("J") hooks. These results concur with
previous research across a broad range of fishes caught
by diverse recreational fishing techniques (Muoneke
and Childress, 1994; Diggles and Ernst, 1997; Lukaco-
vic and Uphoff, 2002; Malchoff et al., 2002; Skomal et
al., 2002; Zimmerman and Bochenek, 2002). However,
the results of our study differ with those of Domeier
et al. (2003), who noted differences in deep-hooking
and bleeding between striped marlin caught on circle
hooks and those caught on "J" hooks but did not detect
a significant difference in mortality between hook types.
Differences between the two studies may result from a
disparity in body size between the two species, specific
bait types (white marlin were caught on dead baits in
the present study, Domeier et al. [2003] used live baits),
92
Fishery Bulletin 103(1)
or sampling error (or a combination of these factors). It
should be noted that Domeier et al. (2003) and the crew
of the present study both used non-offset and 5° offset
circle hooks.
The survival rate observed for white marlin caught
on straight-shank ("J") hooks in our study (65%) is
slightly lower than that reported for other istiophorid
species (blue marlin 89%, Graves et al., 2002; striped
marlin 71%, Domeier et al., 2003) caught on this type
of hook. Differences in the recreational fishing practices
for these species may account for the variation in lev-
els of istiophorid postrelease survival. In recreational
fisheries that target striped marlin and white marlin,
longer drop-back durations with natural baits rigged
on "J" hooks increase the probability of deep-hooking
and internal damage, which influence mortality. The
postrelease mortality rates of white marlin and striped
Hook
type
Hook
location
Bleeding
Fate
"J" hook
20
<
Circle
hook
20
<
r
No
- 8
{
Live 6
(80%)
Dead 2
Jaw, ext. J
f visible |
10 L
(50%)
Yes
- 2
(20%)
{
Live 1
Dead 1
r
No
- 3
{
Live 3
v^ Deep, not I
(30%)
Dead 0
ext. visible i
10 L
(50%)
Yes
- 7
(70%)
{
Live 3
Dead 4
No
{
Live 19
c
- 19
(95%)
Dead 0
Jaw, ext. J
/"" visible
20 I
(100%)
Yes
1
(5%)
{
Live 1
Dead 0
{
Li ve n/a
r
No
n/a
Dead n/a
l^__ Deep, not J
ext. visible |
0 I
Yes
{
Li ve n/a
n/a
Dead n/a
Figure 5
Effects of circle and straight-shank ("J") hooks on hook-
ing location, trauma, and fate. Ext. = externally, n/a =
not applicable.
marlin from drop-back fisheries are similar and are
notably higher than that of blue marlin caught on high-
speed trolled baits.
The results of our study also agree with previous
research documenting increased deep-hooking and tis-
sue trauma associated with the use of straight-shank
("J") hooks. In contrast to circle hooks, "J" hooks are
over 20 times more likely to cause bleeding in sailfish
(Prince et al., 2002a), five times more likely to cause
bleeding in striped marlin (Domeier et al., 2003), and
15 times more likely to cause bleeding in white marlin
(present study). Slightly more than half of the bleeding
white marlin and less than half of the deep-hooked fish
caught on "J" hooks died in our study. Observations of
rusted hooks encapsulated in the viscera of otherwise
healthy istiophorids (Prince et al., 2002a) have indicated
that wounds resulting from deep-hooking are not neces-
sarily lethal. Furthermore, the results of the present
study also indicate that jaw hooking locations are not
exclusively nonlethal. Straight-shank ("J") hooks can
cause lacerations to vital organs such as the eye, brain,
pharynx, esophagus, and stomach before detaching from
the initial hooking location and rehooking in regions
that are typically considered less lethal, such as the
jaw and bill (Prince et al., 2002a). These internal inju-
ries are difficult to record without additional handling
and internal examination and confound relationships
between hooking location and mortality in the absence
of other predictors. Regardless, the significantly higher
survival rate for white marlin caught on circle hooks,
coupled with reduced rates of deep-hooking and tissue
trauma, indicate that this terminal gear may decrease
postrelease mortality rates in drop-back fisheries that
currently use "J" hooks.
None of the white marlin caught on circle hooks in
this study were hooked deeply. Despite documenting
significantly lower deep-hooking rates with circle hooks,
previous studies have nonetheless observed that both
non-offset and offset circle hooks may occasionally hook
fish deeply (Prince et al., 2002a; Skomal et al. 2002).
This is especially true of severely offset (e.g., 15°) circle
hooks, which are highly associated with increased levels
of deep hooking and which may mitigate any conserva-
tion benefits associated with the use of this terminal
gear (Prince et al., 2002a).
Resuscitation of exhausted istiophorids is a common
practice in the recreational fishery. Five white mar-
lin that were tailwrapped and unable to ram-ventilate
during the fight were resuscitated in our study. For ex-
ample, white marlin MX03-03 was tailwrapped for the
final seven minutes of the 21-minute fight and appeared
to be severely exhausted at boatside. This fish was
unable to regulate its position in the water when the
PSAT was implanted, and required the longest resusci-
tation of any white marlin in this study (~5 min.). After
release, a diver confirmed that this marlin regained
color and actively swam away upon reaching cooler
water at a depth of about 20 m (G. Harvey2). Depth
and temperature data showed that this fish survived
for the entire 10-day tag deployment duration. Failure
Horodysky and Graves: Estimation of survival of Tetrapturus albidus caught and released in the North Atlantic recreational fishery 93
—I 1 1 1 1 1 r 1 1 1 1 1 1 r-
0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200
Number of tags
Figure 6
Effect of sample sizes ranging from 10 to 200 PSATs on the 959c confidence intervals
for estimates of release mortality. Estimates were derived from 10,000 simulations of
hypothetical experiments with increasing numbers of tags (by using software developed
by Goodyear [2002]). The dashed line represents the underlying true value of 0.35.
to revive any of the exhausted or tailwrapped white
marlin in this study would have biased the mortality
estimate upwards if any of these animals perished as
a result of exhaustion.
It is unlikely that trauma induced by boatside han-
dling or tagging contributed to the difference between
the mortality of white marlin caught on circle hooks and
those caught on "J" hooks. Holts and Bedford (1990) and
Domeier et al. (2003) suggested that striped marlin in
their studies may have died as a result of striking the
tagging vessel rather than from hook-induced injury.
We observed only one white marlin (DR02-01) strike the
side of a tagging vessel; this fish survived and exhibited
behavior similar to other healthy white marlin for the
full five-day tag deployment duration.
The implications for stomach eversion on billfish sur-
vival are unclear because of fairly few observations in
studies assessing survival. Stomach eversion appears
to be a natural behavioral mechanism by which unde-
sired food items and remnants may be expelled, and
stomachs quickly retracted (Holts and Bedford, 1990).
In addition, the generally weakened condition of some
marlin with everted stomachs indicates that this condi-
tion may occur in response to stress (Holts and Bedford,
1990; Pepperell and Davis, 1999). A striped marlin
with an everted stomach tracked by Holts and Bed-
ford (1990) survived, whereas a black marlin with an
everted stomach tracked by Pepperell and Davis (1999)
and a white marlin in this condition tagged by Ker-
stetter et al. (2004) were both attacked by sharks and
died. In the present study, two white marlin (DR02-03
and MA01) everted their stomachs during the fight.
White marlin DR02-03 showed behavior consistent with
survival until the tag was prematurely released after
2.5 days. In contrast, white marlin MA01 was hooked
in its everted stomach and bled profusely during the
fight. Depth data recovered from the PSAT attached
to this animal indicated that it died less than 10 min-
utes after release. The survival of some istiophorids
with everted stomachs supports the release of fish in
this condition; however, without further observations
of animals in this condition, the relevance of stomach
eversion in predicting mortality of released billfishes
remains uncertain.
The majority of mortalities observed in our study
occurred within the first six hours of release; however
two mortalities (DR02-04 and VZ03-13) occurred more
than 24 hours after tagging. Insights into the behavior
of VZ03-13 prior to mortality are compromised by large
sections of missing data; however, it should be noted
that the final four hours prior to death were associated
with surface waters. Likewise, white marlin DR02-04
(Fig. 3A) spent the majority of the first day almost
entirely within nearsurface waters following release.
Similar prolonged surface associations have been docu-
mented in blue marlin (Block et al., 1992) and striped
marlin (Brill et al., 1993) — a behavioral pattern that
has been attributed to that of a badly injured fish (Brill
et al., 1993). White marlin DR02-04 resumed diving
behavior similar to that observed in healthy tagged fish
(Fig. 3B) after 20 hours, indicating possible recovery
from catch-and-release procedures. This white marlin
again returned to the surface for four hours prior to its
death 64 hours after release.
The two white marlin that had the longest fight times
in our study, DR02-04 and VZ03-11 (83 and 46 min,
respectively), may have experienced delayed postrelease
mortality associated with physiological stress, such
as intracellular acidosis following exhaustive exercise
(Wood et al., 1983) or haemodilution (Bourke et al.,
94
Fishery Bulletin 103(1)
1987). These mortalities appear to have occurred too
soon to have been caused by infection (Bourke et al.,
1987) and too late to have been caused by lactic aci-
dosis. Postexertion recovery in istiophorid billfishes is
poorly studied, but Skomal and Chase (2002) reported
significant perturbations in blood chemistry, includ-
ing elevation in blood Cortisol levels in bluefin tuna
iThunnus thynnus), yellowfin tuna (Thunnus albacares),
and white marlin exposed to prolonged angling bouts
(mean=46 min). Acoustic tracks of these animals re-
vealed recovery periods characterized by limited diving
behavior for two hours or less after release. The death
of white marlin DR02-04 after apparent recovery (Fig.
3C) may be the result of natural mortality, another
capture event, or delayed mortality associated with
release from recreational fishing gear. Mortality associ-
ated with the trauma induced by retained fishing hooks
need not be immediate. Blue sharks with fishing hooks
embedded in the esophagus or perforating the gastric
wall have been found to experience systemic debilitat-
ing disease that may affect survival over longer time
intervals (Borucinska et al., 2001, 2002).
We also cannot discount predation as a possible cause
of mortality for any of the white marlin that died in our
study. Acoustic tagging studies have described preda-
tion on tagged and released sailfish (Jolley and Irby,
1979), blue marlin (Block et al., 1992) and black marlin
(Pepperell and Davis, 1999) by sharks. Recently, Ker-
stetter et al. (2004) observed results consistent with
scavenging and predation on PSAT-tagged white marlin
and opah (Lampris guttatus) by sharks. Both Block et
al. (1992) and Kerstetter et al. (2004) documented at-
tacks on tagged marlin that exhibited prolonged surface
associations — the same pattern shown by DR02-04 im-
mediately following its release and prior to mortality.
One tag (MA04) in our study failed to transmit data
and was eliminated from all analyses. In previous PSAT
studies demonstrating billfish survival, mortalities of
tagged istiophorids were not directly observed (Graves
et al., 2002; Kerstetter et al., 2003), and the authors
conservatively regarded nonreporting tags to be evidence
of mortality. The early tag models used in these stud-
ies may have failed to transmit data because moribund
animals were located at depths that exceeded the toler-
ance limit (650 m) of the tags or because of other factors,
including tag malfunction, mechanical damage (Graves
et al., 2002; Kerstetter et al., 2003) or tag ingestion
(Kerstetter et al., 2004), or a combination of these fac-
tors. Other authors, using newer models of PSATs rated
to withstand pressure equivalent to a depth of 3000 m,
have clearly documented several mortalities and have
chosen to eliminate nonreporting tags from their analy-
ses (Domeier et al, 2003, present study). Treating nonre-
porting tags as mortalities will bias mortality estimates
upwards if tags fail to report for reasons other than
catch-and-release-induced mortality (Goodyear, 2002).
Relatively small sample sizes and fairly limited spa-
tial coverage in the present study precluded the use of
these data to infer Atlantic-wide estimates of postrelease
mortality rates for white marlin. Given the need to ac-
count for geographical differences in body sizes of white
marlin, fishing gears, drop-back durations, angler skill
level, habitat variables, predator densities, and loca-
tions, the sample size needed to generate an accurate
estimate of postrelease mortality for the entire Atlantic
recreational sportfishery could easily require more than
a thousand tags (Goodyear, 2002). Results of simulated
experiments suggest that if the true underlying J-hook
mortality rate is 35%, more than 200 PSATs would have
to be deployed on white marlin caught on this terminal
tackle to reduce the 95% confidence intervals to ±5% of
the true value. The cost of such an experiment (~$1 mil-
lion for tags alone) is presently prohibitive, particularly
considering that these estimates are derived under the
assumption of ideal conditions (no premature releases,
no tag-induced mortality, and no natural mortality)
(Goodyear, 2002). The presence of any confounding fac-
tors would increase the necessary sample size and the
total cost of such an experiment (Goodyear, 2002).
Despite a relatively small sample size, the present
study clearly demonstrates the importance of hook type
for the postrelease survival of white marlin. Our results
indicate that a highly significant proportion of released
white marlin caught on straight-shank ("J") hooks per-
ish and that these hooks are significantly more likely
to hook fish deeply and cause internal damage. In con-
trast, the survival rate of all white marlin caught on
circle hooks indicates that a simple change in terminal
tackle can significantly reduce postrelease fishing mor-
tality in the recreational fishery.
Acknowledgments
The authors would like to thank Captains Mike Adkins
(South Jersey Champion), O. B. O'Bryan (Sea-D), Jimmy
Grant (Vintage), Gene Hawn (Ocean Fifty Seven), Ryan
Higgins (Caliente), Ken Neill (Healthy Grin), Steve Rich-
ardson (Backlash), Rod Ryan (White Witch), and Rom
Whittaker (Release), as well as their crews, for their skill
in finding white marlin and for their patience with us as
we deployed PSATs. We thank Phil Goodyear for kindly
providing the bootstrapping software for simulations, Eric
Prince (NMPS) for suggestions regarding bait rigging
techniques, Paul Howey and Lissa Werbos (Microwave
Telemetry, Inc) for technical assistance with the tags,
Lorraine Brasseur (VIMS) for assistance with MATLAB
programming, Robert Diaz (VIMS) for advice with sta-
tistical methods, and David Kerstetter (VIMS) for helpful
comments on this manuscript. We gratefully acknowledge
the logistical support of Guy Harvey, Dick Weber, and
John Wendkos. This project was funded by the National
Marine Fisheries Service and Marine Ventures, Inc.
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97
Abstract — Rockfishes {Sebastes spp. i
support one of the most economically
important fisheries of the Pacific
Northwest and it is essential for sus-
tainable management that age esti-
mation procedures be validated for
these species. Atmospheric testing
of thermonuclear devices during the
1950s and 1960s created a global
radiocarbon (14C) signal in the ocean
environment that scientists have iden-
tified as a useful tracer and chrono-
logical marker in natural systems.
In this study, we first demonstrated
that fewer samples are necessary for
age validation using the bomb-gener-
ated 14C signal by emphasizing the
utility of the time-specific marker-
created by the initial rise of bomb-
14C. Second, the bomb-generated 14C
signal retained in fish otoliths was
used to validate the age and age
estimation method of the quillback
rockfish iSebastes maliger) in the
waters of southeast Alaska. Radio-
carbon values from the first year's
growth of quillback rockfish otoliths
were plotted against estimated birth
year to produce a 14C time series
spanning 1950 to 1985. The initial
rise in bomb-14C from prebomb levels
(- -90%e) occurred in 1959 [±1 year]
and 14C levels rose relatively rapidly
to peak AUC values in 1967 (+105.4<2c)
and subsequently declined through
the end of the time series in 1985
(+15.4% ). The agreement between the
year of initial rise of 14C levels from
the quillback rockfish time series
and the chronology determined for
the waters of southeast Alaska from
yelloweye rockfish (S. ruberrimus)
otoliths validated the aging method
for the quillback rockfish. The concor-
dance of the entire quillback rockfish
14C time series with the yelloweye
rockfish time series demonstrated
the effectiveness of this age valida-
tion technique, confirmed the longev-
ity of the quillback rockfish up to a
minimum of 43 years, and strongly
confirms higher age estimates of up
to 90 years.
Age validation of quillback rockfish
(Sebastes maliger) using bomb radiocarbon
Lisa A. Kerr
Allen H. Andrews
Moss Landing Marine Laboratories
California State University
8272 Moss Landing Road
Moss Landing. California 95039
Present address (for L A, Kerr) Chesapeake Biological Laboratory
University of Maryland Center
for Environmental Science
P.O. Box 38.
Solomons. Maryland 20688
E-mail address (for L A Kerr, contact author): kerng>cbl umcesedu
Kristen Munk
Alaska Department of Fish and Game
Division of Commercial Fisheries
1255 W. 8th Street
Juneau, Alaska 99801
Kenneth H. Coale
Moss Landing Marine Laboratories
California State University
8272 Moss Landing Road
Moss Landing, California 95039
Brian R. Frantz
Center for Accelerator Mass Spectrometry
Lawrence Livermore National Laboratory
7000 East Avenue
Livermore, California 94551
Gregor M. Cailliet
Moss Landing Marine Laboratories
California State University
8272 Moss Landing Road
Moss Landing, California 95039
Thomas A. Brown
Center for Accelerator Mass Spectometry
Lawrence Livermore National Laboratory
7000 East Avenue
Livermore, California 94551
Manuscript submitted 11 April 2003
to the Scientific Editor's Office.
Manuscript approved for publication
24 August 2004 by the Scientific Editor.
Fish. Bull. 103:97-107 (2005).
Rockfishes {Sebastes spp.) comprise
one of the most commercially impor-
tant fisheries in the northeast Pacific
Ocean. Some rockfish species possess
life history characteristics, such as
long life, slow growth, late age at
maturity, low natural mortality, and
variable juvenile recruitment success,
all of which make them particularly
vulnerable to overfishing (Adams,
1980; Archibald et al., 1981; Leaman
and Beamish, 1984; Cailliet et al.,
2001.1. Rockfish population biomass
and size composition have declined
to very low levels today in part
because of continued high exploita-
tion rates (Love et al., 2002). Preven-
tion of further population declines is
a management imperative. Sustain-
able management of marine fisheries
requires accurate life history infor-
mation, of which validated age and
growth characteristics can be one of
the most important aspects.
Underestimated age can lead to
inflated estimates of total allow-
able catch for a fishery that is un-
sustainable at that level of exploita-
tion (Beamish and McFarlane, 1983;
Campana, 2001). For example, un-
derestimated longevity and improper
management allowed overfishing that
accelerated the decline of the Pacific
ocean perch (Sebastes alutus) of the
northeastern Pacific Ocean (Beamish,
1979; Archibald et al., 1983). Reliable
estimates of age are also essential
for understanding life history traits,
98
Fishery Bulletin 103(1)
such as age at maturity, rate of growth, longevity, and
reproduction frequency (Beamish and McFarlane, 1983).
For production (large-scale) aging purposes, age vali-
dation is especially important because it provides a
standardized basis for ongoing aging efforts to identify
strong and weak cohorts (Campana, 2001).
The most common method of age estimation of bony
fishes is counting growth zones in their calcified in-
ner ear bones, or otoliths (Chilton and Beamish, 1982;
Beamish and McFarlane, 1987). A pair of translucent
and opaque growth zones is often assumed to represent
one year of growth (Williams and Bedford, 1974). By
counting growth zones an estimate of fish age is possi-
ble; however, growth patterns are not easily discernible
for all species. Age interpretations in long-lived species
can be particularly difficult and subjective because
of the compression of growth zones within the otolith
(Munk, 2001). Therefore, it is necessary to validate the
periodicity of growth zones in otoliths with an indepen-
dent and objective method. Despite the importance of
accurate age estimates for understanding and manag-
ing fish populations, validated age and growth charac-
teristics are often not available (Beamish and McFar-
lane, 1983; Campana, 2001). Traditional age validation
techniques, such as captive rearing, mark-recapture,
and tag-recapture, can be difficult or impractical for
long-lived and deep-dwelling fishes.
An alternative technique to traditional age valida-
tion methods uses radiocarbon (14C) produced by the
atmospheric testing of thermonuclear devices in the
1950s and 1960s as a time-specific marker (Kalish,
1993). This established method of validating otolith-
derived age estimates of fishes involves relating the
discrete temporal variation of 14C recorded in otoliths
to an established 14C chronology. Otoliths are closed
systems, accreting calcium carbonate throughout the
life of the fish and this calcium carbonate is conserved
through time. The measurement of bomb-produced 14C
in otoliths of fishes is considered one of the best objec-
tive means to validate otolith-based age estimates in
long-lived fishes (Campana, 2001).
This technique is most reliable for fishes that inhabit
the surface mixed layer of the ocean, at least during a
portion of their life history. Uncertainty regarding mix-
ing rate at depth and limited data on the 14C signal in
deeper waters make it difficult to use this technique for
organisms that live below the mixed layer throughout
their lives (Kalish, 1995, 2001). Studies indicate that
the main source of carbon (70-90%) for otoliths is from
dissolved inorganic carbon (DIC) in seawater and that
the remainder (10-30%) is dietary (Kalish, 1991; Far-
rell and Campana, 1996; Schwarcz et al., 1998). An
understanding of the life history of the fish (in par-
ticular diet, movement, and habitat) and the regional
oceanography of the area are integral for interpreting
otolith 14C data. One caveat of this technique is that it
must use otoliths with birth dates, including the period
of initial increase in 14C (mid-1950s to mid-1960s; Ka-
lish, 1995). Consequently, this technique is well suited
for age validation of long-lived species or species for
which there is an archived otolith collection with birth
years that span this period. The application of bomb 14C
for age validation of long-lived species is advantageous,
in that it provides a minimum longevity and verifies
the periodicity of growth zones in otoliths with only
a small amount of material and with a high degree of
precision (Kalish, 1993; Campana, 2001). However, the
high cost of 14C analysis (~$400-$500 per sample) has
been a limiting factor in the widespread application of
this technique.
The quillback rockfish (Sebastes maliger) is a com-
mercially important rockfish that represents a portion
(~8%) of the demersal shelf rockfish assemblage land-
ings in the Gulf of Alaska (O'Connell et al.1). Species
within the demersal shelf group are considered long-
lived, late maturing, and sedentary as adults, making
them highly susceptible to fishing pressure (O'Connell
et al.1). Estimated exploitation rates are low; once ex-
ploited beyond a sustainable level, recovery is slow (Lea-
man and Beamish, 1984; Francis, 1985; O'Connell et
al.1). Longevity estimates for the quillback rockfish are
wide ranging, from 15 to 90 years (38 years. Barker,
1979; 55 years, Richards and Cass, 1986; 15 years,
Reilly et al.2; 76 years, Yamanaka and Kronland, 1997;
>32 years, Casillas et al., 1998; 90 years, Munk, 2001),
and no age validation has been performed for this spe-
cies to date.
Quillback rockfish are found associated with rocky
substrate in relatively shallow continental shelf waters
(9 to 146 m) — their abundance decreasing with increas-
ing depth below 73 m (Kramer and O'Connell, 1995). As
juveniles, quillback rockfish inhabit nearshore benthic
habitat. Tagging studies confirmed that they do not
demonstrate migratory behavior and are residents in
their shallow-water habitat (Matthews, 1990). Because
1) most longevity estimates indicate that some present-
day adult quillback rockfish were born in the prebomb
era, 2) quillback rockfish in the juvenile stage are found
in the ocean mixed layer, and 3) a suitable 14C time
series exists for the waters off southeast Alaska (previ-
ously determined from yelloweye rockfish [S. ruberri-
mus] otoliths [Kerr et al., 2004]), the quillback rockfish
is an ideal candidate for 14C age validation.
The objectives of our study were 1) to develop a meth-
od for determining the minimum number of samples
required for bomb 14C age validation to minimize cost,
2) to validate both age and age estimation methods of
the quillback rockfish by measuring 14C in aged otoliths
and to compare the timing of the initial rise in 14C with
1 O'Connell, V. M., D. W. Carlile, and C. Brylinsky. 2002. De-
mersal shelf rockfish assessment for 2002. Stock assessment
and fishery evaluation report for the groundfish resources of
the Gulf of Alaska, 36 p. North Pacific Fishery Management
Council (NPFMCl, P.O. Box 103136, Anchorage AK 99510.
2 Reilly, P. N., D. Wilson-Vandenberg, R. N. Lea, C. Wilson,
and M. Sullivan. 1994. Recreational angler's guide to
the common nearshore fishes of Northern and Central
California. California Department of Fish and Game, Marine
Resources Leaflet, 57 p. Calif. Dep. Fish and Game, 20
Lower Ragsdale Drive, Suite 100, Monterey, CA 93940.
Kerr et al.: Age validation for Sebastes maliger with bomb radiocarbon
99
the chronology determined for the waters of southeast
Alaska (i.e., yelloweye rockfish), and 3) to analyze 14C
in aged quillback rockfish otoliths, spanning the pre-
to postbomb era, in order to examine the complete 14C
time series and demonstrate the effectiveness of using
the timing of the initial rise in UC as an age valida-
tion method.
Materials and methods
Sample size assessment
Because of the considerable cost of accelerator mass
spectrometry (AMS) analyses, the minimum number of
14C samples required to validate the aging method of
the quillback rockfish was mathematically determined
from a previously determined yelloweye rockfish otolith
14C time series for the waters of southeast Alaska (Kerr
et al., 2004). To assess minimum sample size, estimated
years of initial rise in 14C levels (and associated errors)
were determined for different numbers of data points
(n = 3, 5, 7, 9, and 11) subsampled from the bomb-rise
region of the yelloweye rockfish data set. The estimated
years of initial rise from each subsample set were then
compared to the initial year of rise and error deter-
mined from all bomb-rise yelloweye rockfish 14C samples
(n=23). Because the error associated with the yelloweye
rockfish bomb-rise data set is limited by the uncertainty
associated with age estimates for yelloweye rockfish, a
maximum error of ±2 years for fish with birth years
during the bomb rise (1956 to 1971; Kerr et al., 2004)
was our precision criterion for defining the minimum
number of quillback rockfish otolith samples.
Twenty-three yelloweye rockfish otolith 14C values
with birth years from 1956 to 1971 were divided into
data sets of 3, 5, 7, 9, and 11 data points. A stratified
sampling approach was applied by creating bomb 14C
linear regressions from repeated selection of 3, 5, 7, 9,
and 11 data points at uniform intervals from 1956 to
1971. Random selection of data points was not practi-
cal because it is established that the careful choice of
sample year during the rapid rise in 14C is required for
this technique (Baker and Wilson, 2001). The year of
initial rise in 14C, and associated error, was determined
from the bomb 14C regressions. The year of initial 14C
rise was calculated with the following formula:
x = (y - b)lm,
where x = year of initial rise in 14C values;
y = average prebomb 14C value;
m = slope of the line; and
b = y-intercept.
The error associated with the year of initial rise in 14C
values (ox) was calculated by using the delta method
(treating 6 as a scaler; Wang et al., 1975):
°y/°m>
where av = error associated with average prebomb 14C
value
am = error associated with the slope of the line.
Radiocarbon analysis
Sagittal otoliths of quillback rockfish were collected from
a random subsampling of catches from commercial long-
line fishing vessels in the coastal waters off southeast
Alaska by the Alaska Department of Fish and Game
(ADFG), Juneau, AK in 2000 (Fig. 1). A single otolith
from a pair taken from each fish was aged by using the
break-and-burn method developed by researchers at the
Mark, Tag, and Age Laboratory, ADFG in Juneau, AK,
and the corresponding intact otolith was analyzed for
14C. Whole and broken-and-burned otoliths were stored
dry in paper envelopes. Year of capture, estimated final
age, assigned year class, readability code, and reader
identification information were archived and provided
by ADFG for each sample.
Fifteen quillback rockfish otoliths, with estimated
birth years ranging from the prebomb 1950s to the
postbomb mid-1980s were selected for 14C analysis. The
core of each otolith, which constitutes the first year of
growth, was analyzed for 14C. From life history infor-
mation, it is known that the core was formed while the
fish inhabited the ocean mixed layer during its early
growth stage (Yoklavich et al., 1996). To determine the
average length and width, and minimum depth of the
core, whole and broken-and-burnt otoliths from adult
quillback rockfish were examined under a Leica- dis-
secting microscope with an attached Spot RT® video
camera and were measured using Image Pro Plus® im-
age analysis software (version 4.1 for Windows, Media
Cybernetics, Silver Spring, MD). Cores were extracted
with a milling machine with a 1.6-mm (1/16") diam-
eter end mill. To minimize the extraction of material
deposited after the first year of growth, length, width,
and depth parameters of the otolith core were used to
guide coring. Because the first year of growth in quill-
back rockfish otoliths is clearly visible from the distal
surface of the otolith we were able to visually correct for
individual variability in otolith core size. The core (first
year of growth in the otolith) was reduced to powder,
collected, and weighed to the nearest 0.1 mg.
For 14C analysis, otolith calcium carbonate (CaC03)
was converted to pure carbon in the form of graphite
(Vogel et al., 1984, 1987) and measured for 14C content
by using AMS at the Center for Accelerator Mass Spec-
trometry, Lawrence Livermore National Laboratory. The
14C values were reported as 414C (Stuvier and Polach,
1977).
The 14C values measured in quillback rockfish otolith
cores were plotted with respect to corresponding birth
years assessed from break-and-burn age estimates,
taking into consideration the potential variation of the
age estimate (coefficient of variation=2.6%, rounded to
the nearest whole number; Chang, 1982). The 14C time
series for the waters of southeast Alaska established
from the otoliths of the age-validated yelloweye rockfish
100
Fishery Bulletin 103(1)
137° 136° 135° 134° 133° 132° 131° 130°
Figure 1
Map of southeast Alaska with regions where quillback rockfish
(Sebastes maliger) used for otolith radiocarbon analyses were
captured. Quillback rockfish were collected from random subsam-
pling of catches from commercial longline fishing vessels in the
coastal waters off southeast Alaska (CSEO: Central Southeast
Offshore (outside), SSEI: Southern Southeast Inshore, SSEO:
Southern Southeast Offshore, and NSEI Northern Southeast
Inshore (inside)) by the Alaska Department of Fish and Game,
Juneau, AK, in 2000. Note that the specific geographic location
for individual fish during the first year of life is unknown; how-
ever, life history information indicates that quillback rockfish
are not migratory and exhibit residential behavior in shallow-
water habitat. Hence, the general location of the fish collected
and used in this study may be useful in a broad context.
(rc=43) was used for temporal calibration of the quill-
back rockfish record (Andrews et al., 2002; Kerr et al.,
2004). The level of concordance between the years of
initial rise in 14C in the two time series was the basis
for validating the otolith-based age estimates of the
quillback rockfish. The degree of agreement between
the 14C time series, spanning the pre- to postbomb era,
for the quillback and yelloweye rockfishes was examined
to demonstrate the effectiveness of determining the year
of initial rise in 14C as an age validation method, and
whether the entire time series for the quillback provided
any further information relevant to age validation. To
do this, the yelloweye rockfish 14C time series was di-
vided into three intervals (prebomb, bomb rise, and
postbomb) and fitted with confidence intervals. The pre-
bomb era 14C values (1950-57) were fitted with an aver-
age (±2 SD); the bomb rise (1959-71) and postbomb era
values (1966-85) were fitted with a linear regression
and corresponding 95% prediction intervals. A qualita-
tive comparison of the quillback rockfish 14C record was
made with other existing marine records: two Hawaiian
Islands coral records — Oahu (Toggweiler et al., 1991)
Kerr et al.: Age validation for Sebastes maliger with bomb radiocarbon
101
Table 1
Range of the year of calculated initial rise in radiocarbon and the associated range of error calculated for bomb radiocarbon
regressions. Each regression comprised varying numbers of yelloweye rockfish radiocarbon data points (n = 3, 5, 7, 9, and 11) and
was compared to the year of initial 14C rise and error was determined from all bomb-rise yelloweye rockfish 14C samples (n=23,
last row) to determine the minimum number of quillback rockfish otolith samples sufficient to achieve the desired degree of
precision (±2 years).
Number of data points
in regression
3
5
7
9
11
23
Number of
regressions
Range of the year of
calculated initial rise in 14C
Error range (± years)
1954.1-1960.3
1956.0-1959.4
1956.5-1957.9
1957.1-1957.3
1957.0-1957.8
1957.3
0.8-6.8
1.3-2.9
1.0-2.5
0.9-1.8
1.2-1.5
n/a
and Kona (Druffel et al., 2001)— and two otolith-based
northern hemisphere 14C records — for northwest At-
lantic haddock (Campana, 1997) and the Barents Sea
Arcto-Norwegian cod (Kalish et al., 2001).
Results
Sample size assessment
The estimated years of initial rise in 14C calculated for
the bomb-14C regressions, composed of 3, 5, 7, 9, and
11 yelloweye rockfish data points spanning 1956 to
1971, converged towards the calculated year for all 23
data points as the number of samples comprising the
regressions increased (Table 1). In parallel, the errors
associated with the estimated years of initial rise in 14C
decreased as the number of 14C samples increased (Table
1). The degree of precision within the quillback rock-
fish record was limited by the uncertainty associated
with age estimates for yelloweye rockfish (a maximum
error of ±2 years based on growth zone counts for fish
with birth years from 1956 to 1971; Kerr et al., 2004).
Examination of the error (years) associated with the
year of initial rise in 14C for the number of data points
comprising each regression in relation to our ±2 year
criterion indicated that a sample size of nine data points
resulted in error values that ranged below 2 years (Table
1). Therefore, it was concluded that nine 14C samples
spanning 1956-71 would be sufficient to provide a suit-
able degree of precision in the quillback rockfish record.
In addition, a limited number of samples, in this case
4, were required to establish an average prebomb level
for the intercept year.
Radiocarbon analysis
The 14C measured in 15 previously aged quillback rock-
fish otoliths with presumed birth years from 1950 to
1985 varied considerably over time (Table 2). Otoliths
Table 2
Summary offish and otolith data from qui
llback rockfish
collected off the coast of southeast Alaska
. Resolved age
is the final age estimate given by Alaska
Department of
Fish and Game. Birth
year is the collection year (2000)
minus the resolved age
Age error is the uncertainty asso-
ciated with the age estimate (CV=2.6%; year rounded to
the nearest whole number). Radiocarbon
values in the
otolith cores of yelloweye rockfish are expressed as 414C
with the AMS analytical uncertainty.
Resolved age
Birth year
414C
(years)
(± age error)
(%c)
50
1950 ±1
-76.9 ±3.3
46
1954 ±1
-104.8+3.2
45
1955 ±1
-89.0 ±4.0
43
1957 ±1
-92.2 ±3.8
41
1959 ±1
-66.9 ±3.3
40
1960 ±1
-54.7 ±4.2
39
1961 ±1
-57.8 ±3.7
37
1963 ± 1
-49.1 ±3.3
35
1965 ±1
28.2 ±3.7
33
1967 ±1
105.4 ±4.2
31
1969 ±1
19.4 ±4.0
30
1970 ±1
47.5 ±3.6
25
1975 ±1
43.9 ±4.0
20
1980 ±1
76.3 ±5.5
15
1985 ±0
15.4 ±3.7
from quillback rockfish with birth years 1950-57 con-
tained prebomb 14C levels. Although there was more
variation in these prebomb values than expected from
14C uncertainties, the level was relatively consistent over
time, averaging -90.7 (±11.5)%c (mean ±SD). A sharp
rise in otolith 14C values was evident in 1959 (±1 year);
102
Fishery Bulletin 103(1)
200
150
100
~ 50
O
< 0
-50
-100
-150
° Quillback rockfish (n=15)
^^— Exponential Rise
- - - Mean prebomb value (-907 %o)
Two sigma value (-67.7 %„)
*
^
1930
1940
1950
1 960 1 970
Birth year
1980
1990
2000
Figure 2
Radiocarbon (414C) values for quillback rockfish iSebastes maliger) otolith cores
(n = 15) in relation to estimated birth year. Horizontal error bars represent the
age estimate uncertainty from growth zone counts (CV=2.6%, year rounded
to the nearest whole number) and vertical error bars represent the 1-aAMS
(accelerator mass spectometry) analytical uncertainty. The solid line represents
the exponential curve fitted to the data that was used to determine the year of
initial rise in 14C levels from prebomb levels (the fitted function had the form
Y=A+B exp(CX) with Y =14C, X=birth year, and A, B, and C as fitted param-
eters). The dashed line represents the +2 SD level (-67.7%r) associated with the
average prebomb 14C value (-90.7 ±11.5r/rr ; dotted line); the intersection of the +2
SD line and the curve was used to define the year-of-initial-rise in 14C values.
this sample was the first to have a 14C value (-66.9
[±3.3]%e) that was above prebomb radiocarbon levels
with a +2 SD criteria (upper limit of-67.7%r). This first
indication of a rise in 14C related to the rise of the bomb
was in agreement with the exponential fit of the quill-
back rockfish 14C times series (Fig. 2). The 14C record
for quillback rockfish otoliths peaked in 1967 with a
maximum 14C concentration of +105.4 (±4)%e. This peak
was followed by a generally declining, but inconsistent,
trend in 14C values to 1985 (last birth year sampled).
The 14C values measured in quillback rockfish oto-
liths plotted against estimated birth years produced
a characteristic increasing and decreasing curve rep-
resentative of bomb-generated 14C changes over time
(Fig. 3). The quillback rockfish 14C record was syn-
chronous with a 14C time series for southeast Alaskan
waters determined from yelloweye rockfish otoliths
(Kerr et al., 2004); the average prebomb 14C values for
the quillback rockfish were in close agreement with
the average yelloweye rockfish prebomb levels (-102.2
[±9.3]%c [mean ±SD]). The year of initial rise in the
quillback and yelloweye rockfish records (1959 [±1 year]
cf. 1958 [±2 years]) and peak in 14C values (1967 cf.
1966) for these two species coincided within one year, a
period encompassed within the uncertainty associated
with break-and-burn age estimates. Furthermore, the
postbomb decline in quillback rockfish 14C values was
similar to that of the yelloweye rockfish. In addition,
thirteen of the fifteen quillback rockfish 14C values fell
within the confidence intervals of the yelloweye rockfish
14C curve (Fig. 3).
The comparison of the quillback rockfish 14C record
with that for Hawaiian Islands corals (Toggweiler et al.,
1991; Druffel et al., 2001) and two otolith-based north-
ern hemisphere 14C chronologies (northwest Atlantic
haddock [Campana, 1997] and Barents Sea Arcto-Nor-
wegian cod [Kalish et al., 2001]) revealed similarities in
the year of initial rise and rate of rise of 14C values, and
differences in the pre- and postbomb eras that can be
explained by regional oceanographic effects (Fig. 4).
Discussion
Sample size assessment
Although the 14C technique has great potential for vali-
dating the age of many long-lived fishes, one of the
main disadvantages has been the high cost of AMS
14C analyses. By providing a means of defining the
Kerr et al.: Age validation for Sebastes maliger with bomb radiocarbon
103
200-
150-
100-
_ 50
o 0
* -50
-100
-150
-200
• Yelloweye rocktish (n=43)
□ Quillback rockfish (n=15)
1930 1940 1950
1960 1970
Birth year
1980 1990 2000
Figure 3
Radiocarbon (414C) values from quillback rockfish [Sebastes
maliger) otoliths and the yelloweye rockfish (S. ruberrimus) 14C
time series for the waters of southeast Alaska. The yelloweye
rockfish 14C data were divided into three intervals (prebomb,
bomb rise, and postbomb) and fitted with confidence intervals.
The prebomb era 14C values (1950-571 were fitted with an
average (±2 SD), and the bomb rise (1959-71) and postbomb
era values (1966-85) were fitted with a linear regression and
corresponding 95% prediction intervals.
minimum number of samples required to achieve the
desired degree of precision, the present study takes a
step toward reducing the number of prescribed samples,
(i.e., 20-30 otoliths; Campana, 2001), effectively making
age validation more affordable.
To determine the number of samples necessary for
an age validation study, an assessment of the degree
of precision is required. The degree of precision may
be defined by the level of variation in the chronology
or the uncertainty associated with age estimates. It
can also be dependent on the estimated longevity of the
fish and the resolution of age that is sufficient for the
purposes of the study. For example, a resolution of ±5
years may be sufficient for a species estimated to live
100 years, but would not be satisfactory for a species
estimated to live 20 years. The higher degree of preci-
sion, the greater the cost will be for a study. However,
a maximum precision can be attained at a minimum
cost by taking into consideration the precision of the
14C time series, the error associated with age estimates,
and the age resolution necessary to accomplish the
goals of the study.
In our study, the ±2-year variation of the yelloweye
rockfish 14C time series limited the precision to which
the age of the quillback rockfish could be determined
through comparison. Stratified sampling of nine quill-
back rockfish 14C values between 1956 and 1971 re-
vealed an average year of initial rise in 14C of 1959
(±1 year) that was in close agreement with the year of
initial rise determined for the yelloweye rockfish time
series. Thus, given the unique circumstances for this
species, we have quantitatively reduced the number
of samples required for age validation to 9 (given that
some sampling or additional information is used to es-
tablish prebomb levels). It can also be envisioned that
14C analysis of a single fish otolith could establish a
minimum longevity for a species if the 14C levels mea-
sured in the otolith core of an adult fish with a known
capture year were consistent with established prebomb
14C levels for the regional waters in which that fish
spent its first year. This exercise illustrates the neces-
sity of defining precision on a species-by-species basis
prior to beginning a 14C study. Despite the high cost
of AMS analyses, the overall project cost may be lower
and of shorter duration than traditional age validation
studies because of the relatively short time required to
prepare and process the minimum number of otoliths.
Currently, the 14C technique is considered one of the
most effective methods for age validation of long-lived
fishes (Campana, 2001) and as costs are minimized,
future application of the bomb 14C age-validation tech-
nique of marine fishes should increase.
Radiocarbon analysis
To interpret radiocarbon values recorded in marine or-
ganisms it is essential to put them in the context of
the regional oceanography. The Alaska coastal current,
driven by wind stress and enriched with freshwater
runoff, is the driving force behind the coastal dynamics
off southeast Alaska (Royer, 1982). The coastal environ-
ment off southeast Alaska is characterized by significant
104
Fishery Bulletin 103(1)
200 i
□ Quillback rockfish •* • *>
150 ■
O Hawaiian Island corals * ""
V
A Arcto-Norwegian cod fii * *
100 -
• North Atlantic haddock » ,
> * \ '
1 50 -
• :r;-
o
V** -
J ° n
< 0 -
•>
■ t
-50 -
-J
*'**.. K—ff' \ ten.10
1 * . • *ta
-100 -
nn
-150 J
1 1 1 ' 1
1900 1920 1940 1960 1980 2000
Year
Figure 4
Radiocarbon data (zl14C) from otolith cores of quillback rockfish tSebastes maliger),
Hawaiian hermatypic corals (Toggweiler et al., 1991; Druffel et al., 2001), and
two age-validated fishes, the northwest Atlantic haddock iMelanogrammus
aeglefinus; Campana, 1997) and the Arcto-Norwegian cod (Gadus morhua;
Kalish et al., 2001). Note the strong agreement in the timing of the year of
initial rise in 14C values.
downwelling, high wind stress, eddies, and storm activ-
ity, resulting in a high degree of mixing. The rapid rise
and early peak recorded in quillback rockfish otoliths,
followed by a postbomb decline, indicated rapid ocean-
atmosphere gas exchange in the shelf waters off south-
east Alaska. Shallow continental shelf waters, such as
the environment inhabited by juvenile quillback rock-
fish, have a thin mixed layer and relatively long surface
residence time, resulting in a relatively fast response
and build up of bomb-14C from the atmospheric signal.
In addition, low prebomb 14C values in the quillback
rockfish record may indicate the influence of upwelled
14C-depleted waters on southeast Alaskan coastal sur-
face waters. This is expected because surface waters
sampled off the Alaskan Peninsula (GEOSECS; Ostlund
and Stuvier, 1980) in 1973 had low 14C values (+62%c) in
relation to the subtropical Pacific (Oahu coral, +174. 5%r
in 1973, Toggweiler et al., 1991), indicating the influence
of upwelled 14C-depleted waters.
A comparison of the 14C time series determined from
quillback rockfish otoliths to the established 14C time se-
ries exhibited synchronicity with the global rise in radio-
carbon. The quillback rockfish record and high latitude
northern hemisphere records from Arcto-Norwegian cod
and haddock exhibited nearly identical years of initial
rise and rates of 14C increase. Note that there are differ-
ences among these records in the prebomb and peak 14C
levels attained and the behavior of bomb-14C after the
peak, but it is irrelevant to the utility of the technique
as an age validation tool. The quillback rockfish record
was also temporally similar to a Hawaiian Island corals
record (Oahu, Toggweiler et al., 1991; Hawaii, Druffel et
al., 2001), both increasing rapidly from the late 1950s.
However, as expected, the corals had higher prebomb
levels (-50%o cf. -90%o), a later peak (1971 cf. 1967) at
a higher value (YlA%c cf. 105%c), and the indication of
a more rapid decline in the postbomb years. These dif-
ferences are indicative of the different oceanographic
influences on the subtropical waters (e.g., lesser relative
influence of upwelled, 14C-depleted, deep water).
Possible sources of error in the quillback rockfish 14C
record are the specific location of each fish during its
first year of growth, possible inaccuracies in the method
of extracting the core, age estimate uncertainty, and
variable oceanographic conditions during the year of
otolith formation. The unknown geographic location of
individual fish during the first year of life is a potential
source of 14C variation. Although juvenile quillback
rockfish occupy relatively limited regions, factors such
as local bathymetry, coastal upwelling, and freshwater
input are likely to impact the 14C content of the lo-
cal waters. Two of the quillback otolith samples (birth
years 1967 and 1980) had considerably higher (~50%o)
14C values when compared to the highest yelloweye
rockfish value for that same year. These elevated 14C
values may indicate that the individuals resided in
different water masses. The variability of otolith 14C
values from regional effects is evident in the observed
±11.5%o (1 SD) associated with prebomb values, a higher
variability than expected from the analytical uncertain-
Kerr et al.: Age validation for Sebastes maliger with bomb radiocarbon
105
ties of the AMS 14C measurements (~±3-4%o). Elevated
14C levels have also been recorded in otoliths of the
black drum {Pogonias cromis), known to reside in es-
tuaries during the juvenile stage (Campana and Jones,
1998); these elevated values are attributed to the rapid
exchange of atmospheric 14C in the well-mixed estuarine
environment and the influence of river input. Quillback
rockfish are known to inhabit more nearshore waters
than those inhabited by yelloweye rockfish (Love et al.,
2002), which could explain the elevated 14C levels.
The core-extraction method was designed to limit the
inclusion of more recently formed material (older than
age 1); however, the inclusion of some of this material
may have inadvertently occurred, perhaps introducing
error to the quillback rockfish 14C record. This kind
of error could alter the 14C value from the actual core
year value depending on the time of otolith formation
in relation to the bomb 14C signal. A small addition of
material with 14C content different from the core ma-
terial, however, may not produce a significant change
in the timing of the initial rise and the shape of the
rise. We feel that in most cases this would lead to an
underaging of the fish and provide us with a minimum
age estimate.
Perhaps the most significant potential source of er-
ror is the uncertainty associated with age estimation
methods (coefficient of variation=2.6%). Growth zone
counting error could have contributed to variation in
the quillback rockfish record; however, the otoliths used
in our study were chosen specifically to provide clearly
definable growth zones and the highest rank in age-es-
timate confidence. The samples chosen were best-case
examples of precise age determinations.
Short-term regional-scale changes in oceanographic
conditions, such as upwelling events, may have affected
14C levels at the time of otolith formation. The variation
in postbomb measurements exemplifies this factor.
Considering the discussions above and the similar
biology, ecology, and distribution of the two rockfish
species, we believe that the use of the yelloweye rockfish
14C time-series (Kerr et al., 2004) as a means of tempo-
ral calibration for the quillback rockfish record is well
supported. The year of initial rise in 14C for quillback
rockfish otoliths (1959 [±1 year]) is in agreement with
the yelloweye rockfish record (1958 [±2 years]); this
finding validates the age estimates of the quillback
rockfish and the accuracy of the break-and-burn age
estimation method. In addition, the concordance of the
quillback time series (1950 to 1985) provides further
support for the age validation. Note that the 14C levels,
timing of the peak, and the subsequent decline were
similar between species. In addition, all but two of
the quillback rockfish 14C values (sample years 1967
and 1980) fell within the confidence intervals for the
yelloweye rockfish 14C curve, further supporting the
concordance of the two rockfish records. If there had
been consistent underaging or overaging of quillback
rockfish otoliths, this discrepancy would have resulted
in a chronology that was not in phase with the yellow-
eye rockfish time series (Campana et al., 2002).
This application of the bomb-14C technique has con-
firmed the longevity of quillback rockfish to a minimum
of 43 (±1) years. This minimum age estimate is based on
the last individual fish sample (estimated birth year of
1957 from growth zone counting) to have prebomb levels,
immediately preceding the significant rise in 14C levels
observed in 1959 (±1) year. These findings effectively
refute previous longevity estimates less than 43 years
(Barker, 1979; Reilly et al.2). In addition, it is reasonable
to assume that the annual growth pattern continues
throughout life; hence, these findings strongly support
longevity estimates exceeding 43 years and ranging up
to 90 years (Richards and Cass, 1986; Yamanaka and
Kronland, 1997; Casillas et al., 1998; Munk, 2001).
Conclusions
It is our intention to not only validate the age and age
estimation method for the quillback rockfish, but to
determine the most effective number of samples for age
validation with bomb radiocarbon. From our results, it
appears that the concordance of the full 14C time series
is not entirely necessary for validating the age of fish,
and perhaps of any other organism. Because the evolu-
tion and magnitude of the bomb-14C rise from the pre-
bomb to postbomb era is subject to variations due to the
specific oceanography of the region, the 14C time series
are in fact regional and are not universally applicable
to all validation studies. The agreement of the entire
14C time series does not provide additional information
relevant to age validation. Hence, we propose that the
year-of-initial-rise method be considered an effective
14C age validation approach. This method both reduces
the number of samples required for age validation and
effectively precludes the perceived need to establish a
pre- to postbomb 14C reference time series for every
region of the world's oceans. Because the year of initial
rise in 14C levels in surface waters is well defined (1958
[±2 years]), it should be treated as a time-specific marker
for organisms that inhabit the mixed layer of the oceans
for some or all of their life cycle.
Acknowledgments
We thank the Alaska Department of Fish and Game
for providing aged otolith samples. This article was
supported in part by the National Sea Grant College
Program of the U.S. Department of Commerce's National
Oceanic and Atmospheric Administration under NOAA
Grant no. NA06RG0142, project number R/F-190,
through the California Sea Grant College Program,
and in part by the California State Resources Agency.
This work was performed, in part, under the auspices
of the U.S. Department of Energy by University of Cali-
fornia, Lawrence Livermore National Laboratory under
contract no. W-7405-Eng-48. This research was also
funded in part by the Pacific States Marine Fisheries
Commission, Earl H. and Ethel M. Myers Oceanographic
106
Fishery Bulletin 103(1)
and Marine Biological Trust, Packard Foundation, and
Project AWARE.
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108
Abstract — Seasonal and cross-shelf
patterns were investigated in larval
fish assemblages on the continental
shelf off the coast of Georgia. The
influence of environmental factors on
larval distributions also was exam-
ined, and larval transport processes
on the shelf were considered. Ichthyo-
plankton and environmental data were
collected approximately every other
month from spring 2000 to winter
2002. Ten stations were repeatedly
sampled along a 110-km cross-shelf
transect, including four stations in
the vicinity of Gray's Reef National
Marine Sanctuary. Correspondence
analysis (CA) on untransformed com-
munity data identified two seasonal
(warm weather [spring, summer, and
fall] and winter) and three cross-shelf
larval assemblages (inner-, mid-, and
outer-shelf). Five environmental
factors (temperature, salinity, den-
sity, depth of the water column, and
stratification) were related to larval
cross-shelf distribution. Specifically,
increased water column stratification
was associated with the outer-shelf
assemblage in spring, summer, and
fall. The inner shelf assemblage was
associated with generally lower tem-
peratures and lower salinities in the
spring and summer and higher salini-
ties in the winter. The three cross-
shelf regions indicated by the three
assemblages coincided with the loca-
tion of three primary water masses
on the shelf. However, taxa occurring
together within an assemblage were
transported to different parts of the
shelf; thus, transport across the con-
tinental shelf off the coast of Georgia
cannot be explained solely by two-
dimensional physical factors.
Cross-shelf and seasonal variation
in larval fish assemblages
on the southeast United States
continental shelf off the coast of Georgia
Katrin E. Marancik
Department of Biology
East Carolina University
East Fifth Street
Greenville. North Carolina 27858
Present address: Center for Coastal Fisheries and Habitat Research
NOAA Beaufort Laboratory
101 Pivers Island Road
Beaufort, North Carolina 28516
E mail address: Katey Marancikiffinoaa.gov
Lisa M. Clough
Department of Biology
East Carolina University
East Fifth Street
Greenville, North Carolina 27858
Jonathan A. Hare
Center for Coastal Fisheries and Habitat Research
NOAA Beaufort Laboratory
101 Pivers Island Road
Beaufort, North Carolina 28516
Manuscript submitted 20 December 2003
to the Scientific Editor's Office.
Manuscript approved for publication
June 25 2004 by the Scientific Editor.
Fish. Bull. 103:108-129(2005).
The study of larval fish assemblages
provides information on community
structure, spawning, and larval
transport. Larval fish assemblages
are groups of larvae with similar
temporal and spatial distributions
(Cowen et al., 1993). Larval distribu-
tion patterns are initially determined
by spawning time and location; larvae
of species with similar spawning pat-
terns are initially in the same larval
assemblage (Rakocinski et al., 1996).
Physical forcing and larval behavior
then modify the structure of larval
assemblages and ultimately deter-
mine the outcome of larval transport
(Cowen et al., 1993; Smith et al., 1999;
Hare et al., 2001).
Marine protected areas (MPAs) are
portions of the marine environment
designated to "provide lasting protec-
tion for part or all of the natural and
cultural resources therein" (Federal
Register, 2000). A number of specific
conservation objectives are encom-
passed by this definition, such as
protecting small areas with histori-
cal significance or aesthetic quality,
or protecting much larger areas to
enhance fisheries through increases
in spawning stock biomass and the
supply of recruits to surrounding ar-
eas (Crowder et al., 2000). However,
whether an MPA provides recruits
to other areas is difficult to quantify
and involves determining the fate
of larvae and juveniles spawned in
a protected area (Stephenson, 1999;
Warner et al., 2000).
MPAs are under consideration as
a fisheries management tool on the
southeast United States continental
shelf (Plan Development Team, 1990),
and larval assemblage studies would
provide useful information regard-
ing spawning and larval transport.
Although substantial larval fish re-
search has been conducted on the
southeast U.S. continental shelf, no
studies have examined the dynamics
Marancik et al .: Fish assemblages on the southeast United States continental shelf
109
of larval fish assemblages in this area. For example,
during the RV Dolphin cruises, the Marine Resources
Monitoring, Assessment, and Prediction (MARMAP)
cruises, and the Southeast Area Monitoring and As-
sessment Program (SEAMAP) cruises, ichthyoplankton
surveys were conducted on the southeast United States
continental shelf. From these surveys, spawning time
was denned for a large group of species (Fahay, 1975),
and the temporal and spatial distribution of larvae
were described for a few select species (Kendall and
Walford, 1979; Collins and Stender, 1987; 1989; Smith
et al., 1994) and for multiple taxa, but mostly at the
family level (Powles and Stender, 1976). Similarly, other
programs (e.g., the South Atlantic Bight Recruitment
Experiment) examined spawning and larval transport
of "estuarine-dependent" species such as Atlantic men-
haden (e.g., Judy and Lewis, 1983; Hoss et al., 1997;
Hare et al., 1999; Checkley et al., 1999), but results for
the entire suite of species sampled were not reported.
For studies where the broader community of larval fish
on the southeast U.S. shelf was addressed, the structure
and dynamics of larval assemblages were not defined
(Powell and Robbins, 1994, 1998; Govoni and Spach,
1999; Powell et al., 2000).
The purpose of this study was to examine larval fish
assemblages on the continental shelf off the coast of
Georgia, USA. This region of the continental shelf was
targeted because of 1) the nature of the broad shallow
shelf, 2) the location of Gray's Reef National Marine
Sanctuary 20 km from shore, and 3) the location of sev-
eral proposed deepwater MPAs (70-200 m water depth)
in the region. Temporal and spatial patterns in larval
distributions were described to explain spawning and
larval transport processes on the continental shelf off
the coast of Georgia, and the implications for MPAs in
the region were addressed.
Materials and methods
Study site
The southeast United States continental shelf extends
from West Palm Beach, Florida, to Cape Hatteras, North
Carolina. Moving north from West Palm Beach (15 km),
the shelf widens to Georgia (200 km) and then narrows
to Cape Hatteras (35 km). Physical forcing by the Gulf
Stream, which is part of the North Atlantic Western
Boundary Current system, varies along the shelf. As
the Gulf Stream flows northward along the shelf edge, it
meanders, and cyclonic frontal eddies form in meander
troughs (Lee et al., 1991). Meanders and frontal eddies
grow in dimension from just north of the Straits of Florida
(27°N latitude) to St. Augustine, Florida (30°N latitude),
and then decrease from St. Augustine to just south of
Charleston, South Carolina (32°N latitude). Meanders and
frontal eddies grow in dimension again downstream of the
Charleston Bump (32-33°N latitude), and then decrease
again from Cape Fear, North Carolina (33°N latitude), to
Cape Hatteras, North Carolina (36°N latitude).
Table 1
Year,
month, and season of ichthyoplan
kton sampling
and number of stations sampled in
the
Georgia Bight
region
of the southeast United States continental shelf.
Year
Month Season
Number of stations
2000
April spring
4
2000
August summer
8
2000
October fall
7
2001
January winter
8
2001
March winter
8
2001
May spring
7
2001
June summer
7
2001
August summer
10
2001
October fall
8
2002
February winter
10
In addition to along-shelf variation in geophysical
structure and Gulf Stream forcing, the southeast Unit-
ed States continental shelf can be divided into three
cross-shelf zones based on physical circulation dynamics
(Boicourt et al., 1998). Circulation on the inner-shelf
(0-20 m water depth) is influenced by tidal currents,
river inflow, and wind (Atkinson and Menzel, 1985; Pi-
etrafesa et al., 1985a). Wind-driven flow predominates
on the mid-shelf (20-40 m water depth) and there is
only minor Gulf Stream and tidal influence (Atkin-
son and Menzel, 1985). Flow on the outer-shelf (40-75
m water depth) is dominated by the passage of Gulf
Stream frontal eddies and upwelling at the shelf break
(Pietrafesa et al„ 1985b).
Inner and mid-shelf physical processes are relatively
more important off the coast of Georgia compared to
other segments of the southeast United States conti-
nental shelf (Boicourt et al., 1998). The continental
shelf off the coast of Georgia is the area of diminish-
ing meanders and eddies from St. Augustine, Florida,
to Charleston, South Carolina. Tidal range and fresh-
water inflow is greatest in the Georgia portion of the
southeast shelf (Atkinson and Menzel, 1985). Further,
because the shelf is widest off the coast of Georgia (ap-
proximately 200 km), the Gulf Stream is less influential
on mid- and inner-shelf dynamics compared to the rest
of the southeast United States continental shelf (Lee
et al., 1991).
Collection of larval fish and CTD data
Ichthyoplankton sampling was conducted approximately
every other month from April 2000 through February
2002 (Table 1). A maximum of ten stations, approxi-
mately 18.5 km apart, were sampled during each cruise.
Stations were missed on some cruises owing to weather
and equipment failure. The transect was 110 km long
and spanned 10 to 50 m water depth (Fig. 1). Four sta-
110
Fishery Bulletin 103(1)
32°0'N -
31 ON
31°0'W
I
80°0'W
pBrtglarWV^SUdv ares
South Carolina
| Gray's Reef National Marine Sanctuary
Ichthyoplankton station
Depth contour (m)
25 50
Kilometers
- 32°0'N
Georgia
- -
20 m
30 m
40 m
[Brunswick
2-+ 23/ •
50 m
200m
• 5
7.'
•
1
81°0'W
1
80°0'W
- 31°0N
Figure 1
Map of the study area and the cross-shelf transect used for sampling larval abundance
and environmental data bimonthly from April 2000 to February 2002 (see Table 1).
Four stations (stations 2.1-2.4) were located around Gray's Reef National Marine
Sanctuary.
tions were placed immediately adjacent to the four sides
of Gray's Reef National Marine Sanctuary. At each
station, temperature, salinity, density, and water depth
were measured from the water's surface to one meter
above the bottom with a Seabird conductivity-tempera-
ture-depth (CTD probe (SBE19, Seabird Electronics, Inc.,
Bellevue, WA). Ichthyoplankton was collected at each sta-
tion with a five-minute single oblique net tow to within
one meter of the bottom. For all but one cruise (August
2000), a 61-cm paired bongo frame fitted with 333-fim
or 505-/xm mesh nets was used. During the remain-
ing cruise, a 1-m ichthyoplankton sled with 333-|um
mesh net was used because of the smaller size of the
research vessel. A flow meter (General Oceanica) was
used to measure the volume of water filtered.
A gear comparison study, conducted during October
2000, showed that ichthyoplankton samples collected
with the two gear types (61-cm bongo versus 1-m2 ich-
thyoplankton sled) were similar. An analysis of variance
(ANOVA) on the mean larval concentration revealed no
significant differences between the two gear types (one-
way ANOVA: F=0.489; df=l; P>0.5). Also, an analysis
of similarities (ANOSIM, Clarke and Warwick, 2001)
determined that the community structure varied more
within than between gear types (ANOSIM: i? = -0.11;
S=77.57). Similarly, preliminary analysis of the effect
of gear selectivity due to mesh size indicated that the
larval communities collected by 333-f<m mesh and by
505-f<m mesh nets were similar. Thus, data from all
cruises were combined in the subsequent analyses (see
Marancik, 2003, for more details).
Preparation of ichthyoplankton data
All ichthyoplankton samples were sorted and larval fish
were identified to the lowest possible taxonomic level
by using previously published descriptions (e.g., Fahay,
1983; Johnson and Keener, 1984; Richards, 2001) and
descriptions developed as part of this study. Identifica-
tion to species was not easy given the diversity of spe-
cies along the southeast United States continental shelf
(see Kendall and Matarese, 1994), yet every effort was
made to identify larvae to species-level (46.3% to species,
27.4% to genus, 6.7% unidentified). Larval concentra-
tions were calculated as number of larvae/100 m3.
Two data sets were used for statistical analyses, dif-
fering in the inclusion of rare taxa. Rare taxa pose a
problem in community analyses. Some rare taxa occur
because of transport anomalies (Cowen et al., 1993),
and their inclusion in data analyses can confound the
definition of larval assemblages. However, rare taxa can
also be indicative of consistent, but low larval abun-
Marancik et al.: Fish assemblages on the southeast United States continental shelf
111
Table 2
Taxa collected duri
ng two years of sampling (Apr
ll 2000-February 2002) constituting one or ten percent of any one sample from
the continental shelf off the coast of Georgia and
nclu
ded in the ana
[yses.
The taxonomic codes used
in the figures of this article
are also shown. Taxa included in the one percent
and ten percent data sets
are marked by an "X." Also indicated are the seasonal
assemblage (warm weather [WA] and winter IWI]) and larval assem
blage dinner-
shelf, M=mid-shelf, O = outer-
shelf) in which
larvae were collected (based on correspondence analy
ses).
Included in
Included in
Family
Species
Taxonomic code
1% data set
10% data set
Season
Assemblage
Muraenidae
Gymnothorax sp.
X
WA/WI
I/O
Ophichthidae
Ophichthus sp.
X
WA/WI
M/O
Myrophis punctatus
Mpun
X
X
WI
M
Clupeidae
Brevoortia tyrannus
Etrumeus teres
Btyr
X
X
X
WI
WI
M
0
Opisthonema oglinum
Oogl
X
X
WA
I/O
Engraulidae
Anehoa hepsetus
Engraulis eurystole
Ahep
X
X
X
WA
WA
I/M
0
Gonostomatidae
Cyclothone spp.
X
WA
0
Phosichthyidae
Vinciguerria nimbaria
X
WA
o
Paralepidae
Lestidium atlanticum
X
WI
0
Myctophidae
Diaphus spp.
Lepidophanes spp.
Ceratoscopelus maderensis
Ceratoscopelus warmingii
Electrona risso
Hygophum hygemii
Hygophum reinhardtii
Lampadena urophaos
Myctophum affini
Myctophum selenops
X
X
X
X
X
X
X
X
X
X
WA/WI
WA
WA/WI
WI
WI
WI
WA
WA
WA
WA
M/O
0
M/O
M
0
0
0
M
O
O
Bregmacerotidae
Bregmaceros atlanticus
Bregmaceros cantori
Bregmaceros houdei
X
X
X
WA
WA/WI
WA/WI
O
I/O
M
Gadidae
Urophycis sp.
X
WI
M
Ophidiidae
Ophidion antipholus 1 holbrooki
X
WA/WI
I/M
Ophidion josephi
X
WA/WI
I/O
Ophidion marginatum
Omar
X
X
WA
M
Ophidion selenops
X
WA
M
Otophidium omostigmum
Oomo
X
X
WA/WI
M
Holocentridae
Holocentridae
X
WA
0
Syngnathidae
Hippocampus sp.
X
WA
I
Syngnathus fuscus /louisianae
X
WA
I
Syngnathus louisianae
X
WA
I
Scorpaenidae
Scorpaenidae
X
WA/WI
M/O
continued
dance (Leis, 1989); excluding these taxa could remove
data useful in defining larval assemblages. Thus, two
taxa inclusion data sets were selected. The first data set
comprised taxa that made up greater than one percent
abundance at any one station, and the second data set
included those taxa that made up at least 10 percent
abundance at any one station (Table 2).
The data sets were further truncated by eliminating,
with a few exceptions, all taxa not identified to genus
or species level. Priacanthidae, Scaridae, Scorpaenidae,
and Epinephalinae were included because, despite po-
tential inclusion of multiple species, these larvae rep-
resent some of the only reef taxa collected, and larval
assemblage data including these taxa would be useful
112
Fishery Bulletin 103(1)
Table 2 (continued)
Included in
Included in
Family
Species
Taxonomic code
1% dataset
10% dataset
Season
Assemblage
Serranidae
Epinephalinae
X
WA/WI
M/O
Serraninae
X
WA/WI
M/O
Diplectrum spp.
X
WA/WI
I/M/O
Hemanthias vivanus
X
WA
O
Serraniculus pumilio
X
WA
M
Priacanthidae
Priacanthidae
X
WA
M/O
Pomatomidae
Pomatomus saltatrix
X
WA
0
Carangidae
Elagatus bipinnulata
X
WA
M/O
Coryphaenidae
Coryphaena hippurus
X
WA
I/O
Lutjanidae
Lutjanus sp.
X
WA
O
Rhomboplites aurorubens
X
WA
O
Sparidae
Lagodon rhomboides
Lrho
X
X
WI
I
Sciaenidae
Bairdiella chrysura
X
WA
I
Cynoscion nothus
X
WA
I/M
Cynoscion regalis
X
WA
I
Larimus fasciatus
X
WA
I/M
Leiostomus xanthurus
Lxan
X
X
WI
I/M
Menticirrhus americanus
Mame
X
X
WA
I
Micropogonias undulatus
Mund
X
X
WA/WI
I/M
Pogonias cromis
X
WA
I
Sciaenops ocellatus
X
WA
I
Pomacentridae
Abudefdufsp.
X
WA
0
Chromis spp.
X
WA
0
Mugilidae
Mugil curema
X
WI
M
Labridae
Halichoeres sp.
X
WA/WI
M
Xy rich thy s spp.
Xyr
X
X
WA
M/O
Scaridae
Scaridae
X
WA/WI
I/M/O
Dactyloscopidae
Dactyloscopidae type 1 (D. i
noorei)
X
WA
I
Dactyloscopidae type 2
X
WA
M
Dactyloscopidae type 3
X
WA/WI
0
Callionymidae
Diplogrammus pauciradiatus Dpau
X
X
WA/WI
M
Scombridae
Euthynnus alletteratus
X
WA
O
Seomberomorus cavalla
X
WA
O
Seomberomorus macula! us
X
WA
I
Auxis rochei
Aroc
X
X
WA
0
Scomber japonicus
X
WA/WI
M/O
Stromateidae
Ariomma sp.
X
WA/WI
M/O
Bothidae
Bothus ocellatus Irobinsi
Boce
X
X
WA/WI
M/O
Paralichthyidae
Cyclopsetta sp.
X
WA/WI
M/O
Engyophrys spp.
X
WA
O
Syacium spp.
X
WA
M/O
Paralichthys albigutalletho
stigma
X
WI
O
Citharichthys arctifrons
X
WI
I
Citharichthys cornutus
X
WA
0
Citharich thys gym n orh in us
X
WA/WI
I/M/O
Citharichthys spilopterus
Cspi
X
X
WI
M
Etropus crossotus
Ecro
X
X
WA
M
Hippoglossina oblongatta
X
WA
M
Paralichthys lethostigma
X
WI
M
Soleidae
Trinectes maculatus
X
WA
I
Balistidae
Monocanthus hispidus
X
WA
0
Maranak et al.: Fish assemblages on the southeast United States continental shelf
113
Table 3
Mean values for each station (station 2 is the average of stations 2.1-2.4) of the sixteen environmental variables used in canonical
correspondence analysis to determine which environmental variables were most significantly linked to the larvae of the Georgia
Bight. Temperature, salinity, and density gradients are horizontal gradients based on the difference between adjacent stations.
Stratification of the water column was calculated by using Simpson's stratification parameter and is a measure of vertical change
in density.
Environmental variables
Code
Station
1
2
3
4
5
6
7
Depth (m)
DEP
12.44
18.51
23.15
33.05
37.03
41.48
45.94
Average temperature (°C)
AVGTEM
19.51
20.76
21.67
22.33
21.97
22.73
23.10
Temperature gradient (°C)
TEMGRAD
-0.29
-0.67
-1.10
-0.82
-0.52
-1.33
-0.59
Average salinity
AVGSAL
34.78
35.70
36.11
36.32
36.35
36.30
36.24
Salinity gradient
SALGRAD
-0.88
-1.13
-0.56
-0.25
0.03
0.12
0.19
Average density ( kg/m3 )
AVGDEN
24.56
24.97
25.04
25.05
25.18
24.92
24.79
Density gradient (kg/m3)
DENGRAD
-0.64
-0.74
-0.18
0.01
0.16
0.44
0.31
Stratification
STRAT
3.10
1.47
3.37
6.19
13.41
42.41
98.44
for managing reef fish on the southeast United States
continental shelf (see Powell and Robbins, 1994; 1998).
Serraninae were also included because the majority of
these larvae are likely one type: Serranus subligarius.
In contrast, larvae identified to some genera were ex-
cluded because there are multiple species common in
the area within each genus, and each species likely
has different larval distributions: Etropus spp. (3 spe-
cies), Prionotus spp. (14 species), Sphoeroides spp. (11
species), Symphurus spp., (22 species), and Syngnathus
spp. (10 species). In summary, 86 taxa were included in
the one percent data set, and 16 taxa were included in
the ten percent data set (Table 2).
Preparation of environmental data
Season, water mass, and eight environmental variables
(mostly derived from temperature and salinity data)
were chosen in an attempt to explain variation in the
ichthyoplankton data (Table 3). For subsequent use in
multivariate analyses, all environmental variables were
standardized to a mean of zero and a standard devia-
tion of one.
CTD data were processed with the manufacturer's
software (Seasave vers. 5.3, Seabird Electronics, Inc.,
Bellevue, WA) and averaged into 0.5-m bins. Two pa-
rameters were derived to describe each hydrographic
variable (salinity, temperature, density): an average
value through the entire water column and a horizontal
gradient value (calculated as the difference in value
between the two adjacent stations). Vertical stratifica-
tion was estimated by using Simpson's stratification
parameter (Simpson and James, 1986):
<t> = l/h j (p-p)gzdz,
where /) = water column depth;
7? = average water column density;
p = water density;
g = acceleration due to gravity; and
z = depth.
The stratification parameter, <f>(jowles/m3), is a measure
of the resistance of water to mixing; higher numbers
signify higher resistance to mixing.
Temperature and salinity data were further used to
define water masses on the continental shelf off the
coast of Georgia. Pietrafesa et al. (1994) defined four wa-
ter masses on the southeast U.S. continental shelf: Geor-
gia Bight Water, Carolina Capes Water, Virginia Coastal
Water, and Gulf Stream Water. However, temperature
data collected on the continental shelf off the coast of
Georgia exhibited greater seasonal variability (10-29°C)
than reported by Pietrafesa et al. (1994; 14-29°C). As
a result, water mass definitions for our study, although
based largely on the definitions of Pietrafesa et al.
(1994), reflect the greater range of temperature and
reflect the natural breaks in temperature, salinity, and
stratification data. Specifically, two water masses (inner-
shelf water and mid-shelf water) and two mixes (inner-
shelf-mid-shelf mixed water and mid-shelf-Gulf Stream
mixed water) were defined (Fig. 2). Inner-shelf water was
characterized by salinities <35 ppt and seasonally vari-
able temperatures. This water mass was found during
winter and spring and was distributed inside the 20-m
isobath (Fig. 3). Mid-shelf water, with salinities >36
(Fig. 2), was typically well mixed vertically (Simpson's
stratification parameter value <10). Mid-shelf water
was found year round over large sections of the shelf,
particularly in the fall (Fig. 3). A mixture between in-
ner-shelf and mid-shelf water was defined with salinities
between 35 and 36 (Fig. 2). A mixture was also defined
114
Fishery Bulletin 103(1)
30.0
Georgia Bight
Wat:
Watermass
/ Inner-shelf water
O Inner-shelf- mid-shelf mixed water
+ Mid-shelf water
A Mid-shelf-Gulf Stream mixed water
33 35
Average salinity
Figure 2
The average temperature and salinity for each station; symbols used represent
the water mass designation for each station. The black polygons represent the
temperature and salinity boundaries (data for all seasons bounded by one polygon)
of three water masses defined by Pietrafesa et al. (1994; Georges Bight water;
Carolina Capes water, and Gulf Stream water). Four water masses were defined
in our study (inner-shelf water, inner-shelf-mid-shelf water, mid-shelf water, and
mid-shelf-Gulf Stream mixed water).
as mid-shelf water and Gulf Stream water (Fig. 2). Gulf
Stream water was not encountered, but its temperature
and salinity properties are well documented (Churchill
et al., 1993; Pietrafesa et al., 1994). Mid-shelf-Gulf
Stream mixed water was highly stratified (Simpson's
stratification parameter value >10), with warm highly
saline water intruding on the surface during fall, win-
ter, and spring and cool highly saline water intruding
at depth during summer. Mid-shelf-Gulf Stream mixed
water was encountered on most cruises and was found
farthest offshore (Fig. 3).
Cruises were assigned to one of four seasons (Ta-
ble 1) based on wind and temperature regimes. Al-
though Blanton et al. (1985) identified five seasons for
the southeast United States based on wind regimes
(Spring [March-May], summer [June- July], transition
[August], autumn [September-October], and winter
[November-February]), the temperature data collected
in our study supported classifying both August cruises
as summer and the March cruise as winter.
Data analyses
Multivariate analyses were used to define larval assem-
blages and to explore the factors that influence distri-
bution of larval assemblages on the continental shelf
off the coast of Georgia. Multivariate analyses arrange
sites and species along environmental gradients creating
a low dimensional map (an ordination). Analyses can
be conducted for samples where the distance between
points in the ordination represents the similarity of
species abundance between samples. Analyses also can
be conducted for species where the distance between
points in the ordination represents the similarity in the
sample distribution between species. Ordinations, then,
can be analyzed in two ways: with regard to proximity
and dimensionality. Points that occur in close proximity
can be considered similar based on similar composition.
Points that occur on the same dimension define gradients
in the data.
The effects of data transformation (untransformed,
square root transformed, and fourth root transformed)
and species inclusions (1% and 10% data sets) on the
ordination of community and environmental data by
two multivariate ordination techniques, multidimen-
sional scaling and correspondence analysis (CA), were
compared to determine which method was more effec-
tive at analyzing the larval fish data collected on the
continental shelf off the coast of Georgia (Marancik,
2003). Overall, the two analytical methods produced
similar ordinations and were robust to the inclusion of
rare species and to the type of data transformation.
Correspondence analysis on untransformed larval
fish concentration data was used to define larval as-
semblages in relation to season and the entire two-year
data set. One of the strengths of CA is that it allows
one to plot analyses of species and station data simul-
taneously on one ordination, thereby, allowing immedi-
ate comparisons between those stations that occur in
close proximity in ordination space and those taxa that
influence that proximity. Eigenvalues are a measure
of the importance of each CA dimension (ter Braak
and Smilauer, 2002). Thus, the dimensions needed to
describe patterns in the data can be determined by an
abrupt drop in the magnitude of eigenvalues from one
dimension to the next.
Marancik et al.: Fish assemblages on the southeast United States continental shelf
115
B .
Summer
:iM--J.
X
»m
■
•
•
c
c
°o
o
o
o
o
^^^o,
.
c .
Fall
:>
•'M,
"JOO,
D
Winter
20-
*"
■
•
•
0
o
o
u
o
° ^
***>■**
Water masses
Salinity Stratification
# Inner-shelf water <35
# Inner-shelf-mid-shelf mixed water 35-36
O Mid-shelf water >36
O Mid-shelf-Gulf Stream mixed water
r~l No data collected
<10
>10
Figure 3
Water mass designations for each station for each cruise. Cruises within a season
were put together in one map with transects offset from center: (Al spring, (B)
summer, (C) fall, and (D) winter. Inner-shelf water was the least saline and found
farthest inshore. Mid-shelf-Gulf Stream mixed water was a highly stratified mix
of Gulf Stream water and mid-shelf water and was found farthest offshore.
Canonical correspondence analysis (CCA), which in-
corporates environmental variables by aligning species
and station data along environmental gradients, was
used to explore the relationship between larval assem-
blages and the environment. The species-environment
correlation is a measure of the strength of the rela-
tion between the species data and the environmental
data for each CCA dimension (ter Braak and Smilauer,
2002). The product of the species-environment correla-
tion and the eigenvalue can be used to describe the
variance in the data. CA and CCA were performed by
using the statistical package CANOCO (Ter Braak,
1988).
Multivariate analyses were used to determine which
fish species spawn on the continental shelf off the coast
of Georgia, to examine what environmental factors in-
fluence larval distribution, and to explore the physical
factors affecting the transport of larvae spawned on
the shelf. Specifically, six objectives were addressed:
1) cross-shelf patterns in the larval fish community; 2)
larval assemblages associated with cross-shelf patterns
in the larval fish community; 3) the relation among
cross-shelf patterns in the larval fish community, larval
assemblages, and environmental variables; 4) the rela-
tion between water mass and larval assemblages; 5)
seasonal patterns in the larval fish community and lar-
val assemblages; and 6) the relation between seasonal
larval assemblages and environmental variables.
In addition to addressing the six specific objectives,
the implications for larval transport were considered.
By comparing the distributions of specific taxa to the
patterns discerned by addressing the objectives above,
some insights were gained into larval transport pro-
cesses. The distribution of taxa representative of each
larval assemblage was examined for patterns through
space and time. Mechanisms driving larval transport
were then explored by linking these patterns to water
mass and other environmental variables.
116
Fishery Bulletin 103(1
Results
Two dimensions were sufficient to explain the majority of
the variance in the larval concentration data (Table 4).
The winter data eigenvalues indicated the relevance of
a third dimension; yet, inspection of three dimensions
did not define any patterns not indicated by the first
two dimensions. Thus, two dimensions were analyzed for
each season in both the CA and CCA analyses.
Cross-shelf patterns in the larval fish community
A cross-shelf pattern in the larval community was
observed. In spring, summer, and fall, the inshore sta-
tions (stations 1-3) were in close proximity, forming an
inner-shelf station group in the ordination resulting
from the CA (Fig. 4). Along the same dimension (axis)
as the inner-shelf group was a mid-shelf station group of
stations 3-6 (stations 2.1-2.4 were also included in this
group in spring, summer, and winter). An outer-shelf
group composed of offshore stations (stations 5-7) was
distributed along a nearly perpendicular dimension, and
the mid-shelf group was at the intersection of the two
dimensions (Fig. 4). Analysis of the one-percent species
data set revealed an identical pattern for each season
(not shown).
The winter station ordination resulted in a less dis-
tinct cross-shelf pattern (Fig. 4D). In January 2001,
stations 1, 2, 3, and 6 were in the inner-shelf group;
whereas, stations 4 and 7 from the same cruise were in
the mid-shelf group, and station 5 was in the outer-shelf
group. Some of this blurring of the cross-shelf pattern
in the ordination may be explained by a lower total
catch, giving the taxa found across the shelf {Brevoor-
tia tyrannus and Leiostomus xanthurus) more influence
over the data. In addition, most of the variance was
explained by the first dimension (Table 4), meaning that
the separation of the outer-shelf group (stations 5 and
6) from the mid- and inner-shelf groups is based on a
weak relationship among the stations.
Larval assemblages associated with cross-shelf patterns
in the larval fish community
Three larval assemblages were defined that corre-
sponded to the three station groups (Fig. 5). The inner-
shelf assemblage was composed of species that spawn in
coastal and estuarine habitats. Larvae in this assem-
blage were distributed within the 20-m isobath and con-
fined largely to stations classified as inner-shelf (Fig. 6).
The inner-shelf assemblage was primarily represented
by Menticirrhus americanus during spring, summer,
and fall, and by Micropogonius undulatus and Lagodon
rhomboides during winter (Table 5). Taxa included in
the mid-shelf assemblage were generally found between
the 20- and 40-m isobaths. Some mid-shelf taxa, how-
ever, were found across the shelf (stations 1-7) and a
large percentage of the larvae occurring in each region
were mid-shelf taxa (Fig. 6). The outer-shelf assemblage
comprised offshore or deepwater spawned taxa and was
CA1
Figure 4
Correspondence analysis ordinations (portraying the first
and second dimension scores) of the larval fish community
data showing station groups in each season (A) spring,
(B) summer, (C) fall, and (D) winter. Three cross-shelf sta-
tion groups were identified within each season. Solid lines
enclose the boundary of each station group with three or more
stations. Station groups comprising one or two stations are
not enclosed by a solid line. Each station group is labeled and
portrayed with a different symbol. The dashed lines intersect
at the origin of the plot. Analyses were conducted with larval
concentration data only. Data from each cruise within a season
are shown together.
Marancik et al.: Fish assemblages on the southeast United States continental shelf
117
Table 4
Eigenvalues and species-environment correlations (r2l for each axis analyzed (correspondence analysis [CA] and canonical cor-
respondence analysis [CAA]) by season and the entire year. A sharp drop in the eigenvalue marks the axes that explain most
of the data. Species and environment correlations represent the strength of the relation between the species data and the envi-
ronmental data for each axis within each season. Values of zero denote no relation; values of one denote a perfect relation. The
product of the species-environment correlation and the eigenvalue explains the variance in the data for CCA. Eigenvalues alone
explain the variance in the data for CA.
Season
CA axis
CCA axis
Spring
Eigenvalue
r2
Summer
Eigenvalue
r2
Fall
Eigenvalue
r2
Winter
Eigenvalue
r2
Year
Eigenvalue
0.932
0.674 0.348
0.792 0.621
0.738 0.544
0.537
0.273
0.526
0.937
0.287 0.197
0.788 0.607
0.107
0.292
0.106
0.165
0.54
0.89
0.631
0.329
0.068
0.98
0.969
0.969
0.796
0.703
0.564
0.409
0.159
0.959
0.959
0.889
0.799
0.707
0.443
0.228
0.053
0.983
0.909
0.935
0.946
0.42
0.104
0.059
0.041
0.894
0.665
0.645
0.496
0.773
0.61
0.319
0.276
0.923
0.899
0.8
0.735
Table 5
Three cross-shelf larval assemblages
(inner-shelf,
mid-shelf, and outer-shelf) were persistent in
the Georgia Bight with sea-
sonal changes in membership. Shown
are the assemblages from the ten-percent data set.
"Bothus ocellatus 1 robinsi" means B.
ocellatus and B.
robinsi or one of either of them.
Season
Inner
Mid
Outer
Spring
Menticirrhus americanus
Diplogrammus pauciradiatus
Auxis rochei
Otophidium omostigmum
Opisthonema oglinum
Bothus ocellatus 1 robinsi
Xyrichthys spp.
Micropogonias undulatus
Etropus crossotus
Anchoa hepsetus
Summer
M. americanus
D. pauciradiatus
A. rochei
O. oglinum
O. omostigmum
Ophidion marginatum
Xyrichthys spp.
E. crossotus
M. undulatus
A. hepsetus
B. ocellatus 1 robinsi
Fall
M. americanus
D. pauciradiatus
Xyrichthys spp.
A. hepsetus
M. undulatus
B. ocellatus 1 robinsi
O. marginatum
E. crossotus
Leiostomus xan
hurus
O. omostigmum
Winter
M. undulatus
L. rhomboides
B. tyrannus
M. punctatus
C. spilopterus
D. pauciradiatus
O. omostigmum
L. xanthurus
B. ocellatus 1 robinsi
118
Fishery Bulletin 103(1)
Oomo DPau
Outjer
Oog\
Aroc'
. 4hep~
, Mame
Inner
"D
3
CO
Oomi
Omi'
Mid /Wura
B
<rOo§p/
"^Mame
Inner
c
3
3
CD
<
Outer
Oomo*
Dbau*
Ecro'
Outer
Inner
Omar/
Ahep • fWame
Lxan
Mid
"n
0)
D
zBoce
Oomp*
?Dpau
Mid
;.
Cspi
F 1/Bf
'B(yr
CA 1
Figure 5
Correspondence analysis (CA) ordinations (portraying the first
and second dimension scores) of the larval fish community data
showing species in each season: (A) spring, (B) summer, (C) fall,
and (D) winter. A larval fish assemblage was associated with
each cross-shelf station group. Each station group is outlined
and labeled as in Figure 4. The dashed lines intersect at the
origin of the plot. Analyses were conducted by using larval
concentration data only. Refer to table 2 for definitions of larval
taxa codes. Three larval fish assemblages were defined based
on species association with station groups (see table 5).
found primarily at outer-shelf stations (Fig. 6). Auxis
rochei and Bothus ocellatuslrobinsi [where the slash (/)
means "B. ocellatus and B. robinsi" or one of these spe-
cies] represented the outer-shelf assemblage (Table 5).
The region of the shelf with the highest species rich-
ness depended on the inclusion of rare taxa and season.
With the exception of fall, species richness was highest
in the mid-shelf group when only abundant taxa were
included in analyses (Table 5, Fig. 7A). When rare taxa
were included (the 1% data set), species richness was
highest in the mid-shelf group during spring and sum-
mer and highest in the outer-shelf group during fall
and winter (Fig. 7B).
Relationship among cross-shelf patterns in
the larval fish community, larval assemblages,
and environmental variables
Five environmental variables were correlated to the cross-
shelf pattern in station groups and larval assemblages.
Water density, salinity, temperature, depth, and strati-
fication of the water column had a significant relation
to the structure of larval assemblages and the grouping
of stations in the CCA (P<0.05 for each variable, Monte
Carlo permutation test; Table 6). The species-environment
correlation for the first two axes of the ordination was
greater that 0.79, indicating a strong association between
the environment and larval assemblages (Table 6).
Although the portrayal of station groups and larval
assemblages in ordination space was not identical when
environmental data were included (compare Figs. 4 and 5
to 8), the cross-shelf pattern in station groups and larval
assemblages was maintained (Fig. 8).
The first CCA dimension, in all seasons, was most
highly influenced by the depth, temperature, salinity, and
density of the water (Fig. 8). In spring, summer, and win-
ter, the mid- and outer-shelf stations were aligned along
CCA 1 and separated from the inner-shelf stations along
this gradient (Fig. 8). Similarly, in fall, the three station
groups were arranged separately along this gradient
with the mid-shelf groups intermediate to the inner- and
outer-shelf stations. Thus, the separation between inner-
shelf and mid- and outer-shelf stations is related to a
gradient in depth, temperature, salinity, and density.
The second dimension separated outer-shelf stations
from inner- and mid-shelf station groups. In spring and
summer, the second dimension (CCA 2) was clearly influ-
enced by stratification (Fig. 8). The outer-shelf stations
experienced a higher degree of stratification, separating
them from the inner- and mid-shelf stations. During fall
and winter, stratification still impacted the second di-
mension, but less dramatically. In summary, outer-shelf
stations were distinguished from mid- and inner-shelf
stations by increased stratification of the water.
Relation between larval assemblages and
water mass distributions
When hydrographic variables were combined to define
water mass, a possible explanation for the cross-shelf
Marancik et al.: Fish assemblages on the southeast United States continental shelf
119
Larval
assemblage
□ Inner
•//. Mid
■ Outer
Inner Mid Outer
Station group
Inner Mid Outer
Station group
Percent
(inner-.
Figure 6
abundance of taxa in larval assemblages associated with each station group
mid-, and outer-shelf) in (A) spring, (B) summer, (C) fall, and (D) winter.
8
-a 40
A 10% data set Season
B 1% data set
7
A. ,a"
6
/'A\, sPnn9 30
/
f taxa
Ol
/// y y. summer
\y ll \ '. winter
/
E 4
<D
.Q
1 3
z
//V \\ 20
^P/^
2
l; \> 10
1
\
//
0
i i i i o
i i i
i
Inner Mid Outer Inner Mid Outer
Station group
Figure 7
The number of taxa collected in each station group during each season for the (A) ten-percent
and
(B) one-percent data sets.
pattern in the larval community was revealed. Physical
data delineated four water masses (Fig. 3). Larval fish
assemblages differentiated only three of these water
masses. Stations associated with inner-shelf water (the
inshoremost water mass) and mid-shelf-Gulf Stream
mixed water (the offshoremost water mass) formed dis-
tinct groups in the ordination of larval community data
(Fig. 9). Stations associated with mid-shelf water also
120
Fishery Bulletin 103(1)
STRAT
DEP„-_SALGRA£
. AYGQER . . .
AVGSAL
DENGRA_
AVGTEM
o Outer
"O
3
CO
AVGTEM
c
3
3
YOuter
c
STOAT
te^grad A inner
!/ M / AVGDE.N
AVGJE^^
^0<f 1/
SALGHAD
DENGRAD
//| AVGSAL
1 ,
D OuterK
DENGRAD J '/
\lnner
AVGTEM
.*.Ai/G§AL_ _ _
^~T*AVGDEN
SALGRATJ^-
DEP /'\ 'L
temgrad*/ y*
/lid
STRAT/ 1
3
5>
CCA 1
Figure 8
Canonical correspondence analysis (CCA) ordinations (portray-
ing the first and second dimension scores) of the larval fish
community data showing the correlations between environ-
mental variables, species, and station groups: (A) spring. (B)
summer, (C) fall, and (D) winter. The solid triangles mark the
location of taxa (as in Fig. 5), and the polygons surround the
three cross-shelf station groups (as in Fig. 4). The arrows depict
the gradient of each environmental variable. The dashed lines
intersect at the origin of the plot. Analyses were conducted
with both larval and environmental data. Refer to Table 3
for definitions of environmental variable codes.
Table 6
The P values from a Monte Carlo permutation test on
the environmental variables for each season. Significant
values (P<0.05) are shown in bold font. See Table 3 for
definitions of variable codes.
Variable code
Season
Spring
Summer
Fall
Winter
AVGDEN
0.002
0.01
0.34
0.494
AVGSAL
0.002
0.022
0.016
0.004
AVGTEM
0.152
0.1
0.04
0.016
DENGRAD
0.836
0.076
0.466
0.958
SALGRAD
0.456
0.086
0.78
0.634
TEMGRAD
0.074
0.076
0.38
0.574
DEP
0.468
0.002
0.002
0.68
STRAT
0.036
0.014
0.012
0.504
formed distinct groups. The fourth water mass, inner-
shelf-mid-shelf mixed water overlapped with either
inner-shelf or mid-shelf water depending on season. In
summary, the cross-shelf distribution and assemblages
of water masses coincided with the three cross-shelf
regions described: inner-shelf, mid-shelf, and outer-shelf
characterized by inner-shelf water, mid-shelf water, and
mid-shelf-Gulf Stream mixed water, respectively.
Seasonal patterns in the cross-shelf distributions
of the larval fish community
The ten percent data set revealed two distinct seasonal
station groups (Fig. 10). The winter stations occurred in
close proximity and were separate from stations sampled
during the rest of the seasons (Fig. 10A). However, inner-
shelf stations sampled during fall overlapped with the
winter stations because of the presence of winter and
fall spawning species (L. xanthurus and M. undulatus).
There was also overlap of the winter and the warm
weather outer-shelf stations (Fig. 10, A and B).
Similarly, the ten percent data set revealed two
seasonal assemblages in the larval community data
(Fig. 10, C and D). The warm weather assemblage com-
prised taxa associated with the warm weather station
group and were collected during spring, summer, and
fall. The winter assemblage was associated with the
winter station group and comprised taxa collected dur-
ing winter. Taxa from the warm weather inner- and
mid-shelf assemblages were different from those rep-
resenting the winter inner- and mid-shelf assemblages
(Table 5). The outer-shelf assemblage, however, was less
seasonally distinct, represented by Bothus ocellatus/rob-
insi in summer, fall, and winter and by Auxis rochei in
spring, summer, and fall (Table 5).
Marancik et al .: Fish assemblages on the southeast United States continental shelf
121
Relation between seasonal larval assemblages and
environmental variables
The seasonal pattern in the larval concentration data
described above was maintained when constrained by
environmental variables in the CCA. The community
data clearly showed a seasonal influence on the first
dimension in ordination space; winter taxa were sepa-
rate from taxa collected during the rest of the seasons.
This seasonal pattern was also reflected in the environ-
mental data (Fig. 11). Salinity, density, temperature,
depth, and stratification of the water column were again
the most significant environmental variables for explain-
ing variance in the species data (P<0.05, Monte Carlo
permutation test, Table 6). The warm weather stations
and taxa coincided with higher water temperature,
lower density, and a lower density gradient. In addition,
the cross-shelf pattern evident in the second and third
dimensions of the full larval concentration data (Fig. 10,
A and B) appeared to correlate with depth of the water
column, the degree of stratification in the water column,
and salinity (Fig. 11).
Implications for larval transport
The structure of larval assemblages was linked to water
mass distributions and the cross-shelf zonation of physi-
cal circulation processes. Three cross-shelf zones of
physical dynamics have been defined previously (Atkin-
son and Menzel, 1985; Pietrafesa et al., 1985a, 1985b;
Lee et al., 1991; Boicourt et al., 1998). Three analogous
cross-shelf zones were delineated in the larval com-
munity data. The cross-shelf larval assemblages were
linked to three water masses with cross-shelf structure,
and to the physical-chemical characteristics of the region
(temperature, salinity, density, and stratification of the
water column). The three cross-shelf zones identified pre-
viously in terms of physical dynamics coincided with the
station groups and larval assemblages identified in our
study. Thus, larval distribution and physical properties
of the ocean are linked and indicate a strong influence
of physical properties and processes on the distribution
of larval fish on the southeast United States continental
shelf.
Retention on the inner-shelf was a clear larval trans-
port pattern identified in the analyses. Menticirrhus
americanus represents the inner-shelf group (Table 5)
and were always found inshore of the 20-m isobath in
inner-shelf water, in inner-shelf-mid-shelf mixed water,
or in mid-shelf water, (Fig. 12). Spawning likely occurs
on the inner-shelf (Cowan and Shaw, 1988), and larvae
are retained in the inner-shelf region.
The analyses also demonstrated that transport from
offshore onto the shelf is limited on the continental
shelf off the coast of Georgia. Ceratoscopelus maderensis
and Auxis rochei were found only at offshore stations
(Fig. 13), representing the outer-shelf group (Table 5)
and the mid-shelf-Gulf Stream mixed water mass. The
presence of C. maderensis identified transport of a me-
sopelagic fish to waters inshore of the shelf break; how-
_M3GS
MSGS
ISMS
D
ISMS
'■1 -■■'•.-
CA1
Figure 9
Correspondence analysis (CA) ordinations (portraying the first
and second dimension scores) of the larval fish community
data showing the full ten-percent data set: (A) spring, iBi
summer, (C) fall, and (D) winter. The points represent stations
classified by water mass. Solid lines enclose the boundary of
each station group with three or more stations. Station groups
comprising one or two stations are not enclosed by a solid line.
Each station group is labeled and portrayed with a different
symbol. Stations with inner-shelf water are labeled with IS
(inner-shelf), inner-shelf-mid-shelf mixed water with ISMS,
mid-shelf water with MS, and mid-shelf-Gulf Stream mixed
water with MSGS. The dashed lines intersect at the origin of
the plot. Analyses were conducted using larval data only.
122
Fishery Bulletin 103(1)
CM
<
O Warm
• Winter
<
O Inner □ Mid ir Outer
I)
St
-Mpvn^Lxari
Lrtia
Winter
CA 1
CA 1
Figure 10
Correspondence analysis (CA) ordinations of the larval fish community data showing (A) the
first and second dimension scores and (B) the first and third dimension scores of the station
groups (inner, mid, and outer) defined within each season when the 10% data set was used.
Open symbols denote stations sampled during the warm weather season and filled symbols
denote stations sampled during the winter season. (C) The first and second dimensions and
(D) the first and third dimensions of the station and species groups in the full data set are
shown without the incorporation of the environmental data. The dashed lines intersect at the
origin of the plot.
ever, the rarity of this species on the continental shelf
off the coast of Georgia provides evidence for relatively
limited onshore transport from off the shelf. Powell and
Robins (1994, 1998) and Govoni and Spach (1999) also
collected tropical and deepwater taxa inshore of the
shelf break. The presence of these taxa was likely due
to frequent but variable exchange of larvae across the
Gulf Stream front (Govoni and Spach, 1999). Less is
known about spawning of A. rochei but the species' lar-
val distribution represents restriction to offshore waters
(always collected offshore of the 40-m isobath).
During winter, when B. tyrannus was found across
the shelf (Fig. 14), Bothus ocellatus /robinsi was col-
lected only on the outer part of the shelf (Fig. 14). Both
B. tyrannus and B. ocellatus /robinsi likely spawn on the
outer shelf. However, unlike B. tyrannus, Bothus ocel-
latus /robinsi was never collected inshore of station 3
(the boundary between the inner- and mid-shelf zones),
indicating that the two taxa may experience different
transport pathways or different seasonal spawning pat-
terns (see "Discussion" section).
Discussion
Three cross-shelf regions were defined on the continental
shelf off the coast of Georgia based on the distribution
and abundance of larval fish: inner-shelf, mid-shelf, and
outer-shelf. Each region was dominated by a distinct
group of species (i.e., larval assemblage). The inner-shelf
Marancik et al.: Fish assemblages on the southeast United States continental shelf
123
A
l Summer
B DEP
\ AVG&AL
^V\ 'STRAT
DENGBA^ALGRAlf
\ * AV
A/ V \a
\ /^ \\l\i TEMGRAD
\WinteK
FairV
Spring
i
Figure 11
The correlation between environmental variables and station groups portrayed by canoni-
cal correspondence analysis (Fig. 10). (A) The proximity of seasonal station groups (black
polygons) and taxa (black triangles) when environmental and larval concentration data were
analyzed. (B) The relationship between the environmental variables (black arrows) and the
seasonal station groups (gray polygons). The direction of the arrows depicts the gradient of
each environmental variable. The dashed lines intersect at the origin of the plot.
region was defined inshore of the 20-m isobath (Figs. 4,
5, 12). The inner-shelf larval assemblage was the least
diverse taxonomically (Table 2, Fig. 7B), and most taxa
in the assemblage were nearshore or estuarine spawning
species (e.g., Cynoscion regalis, Menticirrhus americanus.
Table 2). Gradients in salinity and density were associ-
ated with the separation of the inner-shelf region but
the direction of the gradient varied among seasons; in
the spring and summer the inner-shelf region was char-
acterized by lower salinity and density, whereas in the
fall and winter, the inner-shelf region was characterized
by higher salinities and densities (Fig. 8). The restricted
inshore distribution of the assemblage indicated mecha-
nisms of larval retention in the inner-shelf zone.
The mid-shelf region was defined between the 20- and
40-m isobaths (Figs. 4, 5, 12). The mid-shelf larval as-
semblage was distributed over the widest area (Figs. 4,
5, 12) and species in the assemblage were found in all
three regions defined (Fig. 6). The mid-shelf region and
larval assemblage were related to the average environ-
mental parameters encountered on the shelf (Fig. 8),
which varied seasonally. The broad distribution of the
assemblage indicated either broad spawning distribu-
tions of member species or mechanism of larval trans-
port to both the inner- and outer-shelf regions.
The outer-shelf region was defined as the area off-
shore from the 40-m isobath (Figs. 4, 5, 12). The outer-
shelf region was related to increased stratification of
the water column, which was likely a result of Gulf
Stream waters mixing onshore. These periodic intru-
sions would help explain the higher species richness of
rare taxa found on the outer-shelf during fall and win-
ter (Fig. 7B). Taxa in the outer-shelf assemblage were
either spawned on the outer-shelf (e.g., Hemanthias
vivanus), spawned offshore of the shelf break and trans-
ported onto the shelf (e.g., Ceratoscopelus maderensis),
or spawned south of the study area and transported
onto the shelf (e.g., Abudefduf sp.). Most outer-shelf
taxa, however, were restricted to outer-shelf stations
indicating limited onshore exchange between the outer-
and mid-shelf regions.
Larval assemblages on the continental shelf off the
coast of Georgia are derived from a combination of
spawning distributions and larval transport; Brevoor-
tia tyrannus and Bothus ocellatus I robinsi provide an
example. Brevoortia tyrannus spawn in water tempera-
tures between 16° and 23°C during winter (Checkley et
al. 1999); these temperatures were experienced in the
mid- and outer-shelf regions during winter. Bothus ocel-
latus/robinsi adults also occur on the mid- and outer-
shelf of the continental shelf off the coast of Georgia
(Gutherz, 1967). Thus, during winter the spawning
distribution of these two species are likely similar. The
larval distributions, however, are different: B. tyrannus
larvae were collected in all three regions of the shelf
during winter, whereas B. ocellatus /robinsi were col-
lected on the mid- and outer-shelf (Fig. 14). The verti-
cal distributions of the two species also are different.
B. tyrannus larvae occur higher in the water column
than do B. ocellatus /robsini (Hare and Govoni1). The
observed differences in horizontal distribution could
result from the differences in vertical distributions.
Alternatively, the distributional differences could result
from physiological differences that allow B. tyrannus
larvae to survive cooler inshore waters or could result
from seasonal cross-shelf spawning patterns that result
1 Hare, J. A., and J. J. Govoni. 2004. In review. Vertical
distribution and the outcome of larval fish transport along
the southeast US continental shelf during winter.
124
Fishery Bulletin 103(1)
B
Summer
o
+**<
two
■ o>
v«>
-
c
■ •
Fall
oo
•e
' ""--•.■,.;
a
^^
" -=-
D
Winter
"z»,
'«*.*
.<-.
SJO;
Water mass
•
Inner-shelf water
•
Inner-shelf-mid-shelf mixed water
o
Mid-shelf water
o
Mid-shelf-Gulf Stream mixed water
□
No water mass data
Fish abundance
(larvae/100 m3)
0
• 0.001-1
£ 1001-10
ft 10.001-100
100.001-1000
Figure 12
Distribution of Menticirrhus americanus in (A) spring, (B) summer, (C) fall,
and (D) winter. Transects for each cruise within a season are offset from one
another. The size of the circle for each station varies with larval fish concentra-
tion (larvae/100 m3). The fill color for each circle varies with water mass.
in B. tyrannus spawning inshore during the fall. This
example demonstrates that there are multiple mecha-
nisms or pathways that affect the transport of larval
fish, and that each species may be subject to different
transport regimes. Therefore, to understand larval
transport, many factors, including physical forcing
mechanisms, the horizontal and vertical distributions
of larvae, seasonal patterns, and the physiology of a
species, need to be considered.
Temporal larval assemblages were defined in addi-
tion to the spatial assemblages. Larvae clearly sepa-
rated into two seasonal spawning groups: winter and
warm seasons (Fig. 10). The winter assemblage was
associated with cool, denser water, whereas the warm
water assemblage was associated with warmer, less
dense water (Fig. 11). The cross-shelf structure in lar-
val assemblages was still evident in the two seasonal
assemblages, but there was overlap in the winter and
warm-weather outer-shelf assemblages (Fig. 10). This
overlap occurred in waters with the least seasonal vari-
ability in temperature and salinity and likely results
from year-round spawning by species in the outer-shelf
assemblage or year-round supply of larvae to the outer-
shelf region by the Gulf Stream.
Marancik et al.: Fish assemblages on the southeast United States continental shelf
125
Auxis rochei
KJ
Spring
i -
3B«
. 0 *»**
on.
.,,
"
B
Summer
□
•o
□
**-,
■ o
Jooo
'Vl
3*)j
Ceratoscopelus
maderensis
<LJ
Spring
JUT
1
□
^^ooo
■
" ° ■*»*»
D
Winter
O *«,,,
'Joo,
'■^
A>u?
Water mass
•
Inner-shelf water
•
Inner-shelf-mid-shelf mixed water
o
Mid-shelf water
o
Mid-shelf-Gulf Stream mixed water
□
No water mass data
Fish abundance
(larvae/100 m3)
0
• 0.001-1
£ 1.001-10
ft 10.001-100
100.001-1000
Figure 13
Distribution of Auxis rochei in (A) spring, (B) summer, and distribution of Cera-
toscopelus maderensis in (C) spring ID) winter, across the shelf and across water
masses. Transects for each cruise within a season are offset from one another. The
size of the circle for each station varies with fish concentration (larvae/100 m3).
The fill color for each circle varies with water mass.
Winter-spawning species that use estuaries are fre-
quently grouped together as "estuarine-dependent" taxa
(sensu Warlen and Burke, 1990). However, Hare and
Govoni1 found that vertical distributions of these winter
taxa are different. In addition, our study demonstrated
that the horizontal distributions of these species are
distinct: Lagadon rhomboides and Micropogonias un-
dulatus were members of the inner-shelf assemblage
and Leiostomus xanthurus, Myrophis punctatus, and
Brevoortia tyrannus were members of the mid-shelf
assemblage. These findings imply that often grouped
"estuarine-dependent" species have different spawning
locations or experience different larval transport pro-
cesses (or both) and may not reflect a single group.
The definition of three regions based on larval fish
distributions is consistent with the division of the shelf
into three cross-shelf zones based on physical dynamics.
The inner-shelf (0-20 m) is dominated by freshwater
discharge, tides, and winds; the mid-shelf (20-40 m)
is influenced by wind and tides; and the outer-shelf
(40-75 m) is affected by the Gulf Stream and wind (At-
kinson and Menzel, 1985; Pietrafesa et al., 1985a, 1985b;
Lee et al., 1991; Boicourt et al., 1998). Thus, the physical
dynamics of the shelf appear to be closely linked to spa-
126
Fishery Bulletin 103(1)
Bothus ocellatus/robinsi
B
Summer
o
o
o
°00
'o.
*»«.
•">«
'■Wo,
***«,
2P07
Brevoortia tyrannus
D
Winter
Vn
»■
'■"■"•ad
•
•
O
( )
° e
^a*
Water mass
•
Inner-shelf water
•
Inner-shelf-mid-shelf mixed water
o
Mid-shelf water
o
Mid-shelf-Gulf Stream mixed water
D
No water mass data
Fish abundance
(larvae/100 m^)
0
• 0.001-1
£ 1.001-10
ft 10.001-100
100.001-1000
Figure 14
Distribution of Bothus ocellatus/robinsi in (A) spring, (B) summer, (C) fall, and ID) winter, and Brevoortia
tyrannus (E) in winter, across the shelf and across water masses. Transects for each cruise within a season are
offset from one another. The size of the circle for each station varies with fish concentration (larvae/100 m3).
The shading for each circle varies with water mass.
tial patterns in the distribution of larval fish. Further
physiochemical characteristics of the environment (e.g.,
temperature, salinity, water masses) are highly associ-
ated with the structure of larval assemblages (Tables 4,
6, Fig. 9), again indicating a strong link between physi-
cal dynamics and larval distribution. However, patterns
in spawning and behaviorally modified vertical distribu-
tions also have an influence on larval distributions and
thus a simple two-dimensional passive model will not
adequately explain the distribution of larval fish on the
continental shelf off the coast of Georgia.
The three regions defined in our study have impor-
tant implications for the consideration of MPAs on the
southeast United States shelf. The described cross-shelf
zones (inner-, mid-, or outer-shelf) provide information
needed to protect spawning habitat of specific species
(e.g., Rhomboplites aurorubens spawns on the outer-
shelf; Table 2). Conversely, the species included in an
area under consideration for protection can also be
derived (e.g., Gray's Reef National Marine Sanctuary
potentially protects species spawning at the interface
between the inner- and mid-shelf. Table 2). Further,
spawning location information can be derived for sev-
eral species protected under the South Atlantic Fish-
eries Management Council's coastal migratory pelag-
ics management plan (e.g., Rachycentron canadum,
Scomberomorus cavalla, Scomberomorus maculatus,
or Coryphaena hippurus. Table 2), but individuals of
Marancik et al.: Fish assemblages on the southeast United States continental shelf
127
these species range so widely (Sutter et al., 1991), only
very large MPAs would afford protection from fishing
(Parrish 1999, Beck and Odaya 2001). Unfortunately,
many species in the snapper-grouper complex, a more
sedentary group of species of particular importance in
the southeast United States, were not collected. Either
these taxa do not spawn on the continental shelf off the
coast of Georgia and their larvae are rarely transported
into the area, or snapper-grouper spawning on the con-
tinental shelf off the coast of Georgia is at a very low
level and larvae are quite rare.
Another aspect of MPAs designed for fisheries man-
agement is production of individuals in the MPA and
their supply to surrounding areas; larval transport is
a major mechanism of supply. On the continental shelf
off the coast of Georgia, larval assemblages suggest
that the supply of larvae from the south (by the Gulf
Stream) and even between cross-shelf zones is limited.
Members of the outer-shelf assemblage rarely occurred
on the mid- and inner-shelf, and members of the inner-
shelf assemblage rarely occurred on the mid- and outer-
shelf. Thus, larvae spawned on the inner-shelf and to
a lesser degree on the mid-shelf likely remain on the
continental shelf off the coast of Georgia and appear to
be subject to local retention. MPAs in the region, there-
fore, could provide a local benefit by supplying recruits
to nonprotected areas on the continental shelf off the
coast of Georgia.
Acknowledgments
We would like to thank all who helped with sample
collections, sorting, and analyses: G. Bohne, R. Bohne,
C. Bonn, J. Burke, M. Burton, B. Degan, M. Duncan,
J. Govoni, M. Greene, E. Jugovich, S. Lem, J. Loefer,
R. Mays, R. McNatt, A. Powell, R. Rogers, S. Shoffler,
S. Varnam, H. Walsh, and T. Zimanski. We appreciate
the hard work and dedication of the officers and crew of
the NOAA Ship Ferrel, NOAA Ship Jane Yarn, NOAA
Ship Oregon II, and RV Cape Fear. Frank Hernandez
provided invaluable help with the CTD processing and
stratification calculations. We would also like to thank
J. Johnson, S. Norton, A. Powell, F. Hernandez, E. Wil-
liams, P. Marraro, W. Richards, and an anonymous
reviewer for their comments on previous drafts. Most of
all, we thank Gray's Reef National Marine Sanctuary
and the National Marine Sanctuary Office for funding
the project.
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130
Abstract — Inter and intra-annual var-
iation in year-class strength was ana-
lyzed for San Francisco Bay Pacific
herring (Clupea pallasi) by using oto-
liths of juveniles. Juvenile herring
were collected from March through
June in 1999 and 2000 and otoliths
from subsamples of these collections
were aged by daily otolith increment
analysis. The composition of the year
classes in 1999 and 2000 were deter-
mined by back-calculating the birth
date distribution for surviving juve-
nile herring. In 2000, 729% more
juveniles were captured than in 1999,
even though an estimated 12% fewer
eggs were spawned in 2000. Spawn-
ing-date distributions show that
survival for the 2000 year class was
exceptionally good for a short (approx-
imately 1 month) period of spawn-
ing, resulting in a large abundance
of juvenile recruits. Analysis of age at
size shows that growth rate increased
significantly as the spawning season
progressed both in 1999 and 2000.
However, only in 2000 were the bulk
of surviving juveniles a product of
the fast growth period. In the two
years examined, year-class strength
was not predicted by the estimated
number of eggs spawned, but rather
appeared to depend on survival of
eggs or larvae (or both) through the
juvenile stage. Fast growth through
the larval stage may have little effect
on year-class strength if mortality
during the egg stage is high and few
larvae are available.
Year-class formation in Pacific herring
(Clupea pallasi) estimated from
spawning-date distributions of juveniles
in San Francisco Bay, California
Michael R. O Fan ell
Ralph J. Larson
Department of Biology
San Francisco State University
1600 Holloway Avenue
San Francisco, CA 94132
Present address (for M. R. O'Farrell, contact author): Department of Wildlife.
Fish and Conservation Biology
University of California, Davis
One Shields Avenue
Davis, California 95616
E-mail address (for M R O'Farrell)' mrofarrellffi'ucdavis edu
Manuscript submitted 27 February 2003
to the Scientific Editor's Office.
Manuscript approved for publication
2 August 2004 by the Scientific Editor.
Fish. Bull. 103:130-141 (2005).
Both biological and physical sources
of mortality have been suggested as
important in determining year-class
strength in fish populations. Food lim-
itation at first feeding (Hjort, 1914;
Cushing, 1975; Lasker, 1975; Cushing,
1996), larval retention (lies and Sin-
clair, 1982; Sinclair and lies, 1985),
a juvenile critical period (Bollens et
al„ 1992; Thorisson, 1994), as well as
predation and environmental condi-
tions may ultimately affect recruit-
ment. Egg development time and
larval growth rate have the capacity
to adjust the relative impacts of these
mortality sources on individual prop-
agules by modifying stage duration
(Houde, 1989; Yoklavich and Bailey,
1990).
Juvenile fishes can be used to as-
sess both inter- and intra-annual
variation in egg and larval survival.
Interannual variation in year-class
strength is often inferred from mea-
sures of juvenile abundance (e.g.,
Baxter et al., 1999). In addition, when
the total number of eggs spawned is
known, juvenile abundance can be
used to assess overall variation in
egg and larval survival. Intra-annual
variation in egg and larval survival
can be estimated from the birth-date
distribution of surviving juveniles,
as determined from otolith daily in-
crement analysis. Particularly when
data on actual spawning-date distri-
butions are available, the birth date
distribution of survivors can be used
to identify periods of spawning that
contributed differentially to juvenile
recruitment (Methot, 1983; Rice et
al., 1987; Yoklavich and Bailey, 1990;
Moksness and Fossum, 1992; Fox,
1997; Takahashi et al., 1999).
Recruitment of juvenile Pacific her-
ring (Clupea pallasi) varies interan-
nually by over an order of magnitude
in San Francisco Bay (Baxter et al.,
1999) and is the culmination of sever-
al processes. Schools of adult herring
enter San Francisco Bay in discrete
batches during the fall and winter.
These schools shoal and deposit eggs
and milt during spawning events that
often correspond to the quarter moon
phase. Spawning events can vary in
duration from approximately one day
to one week, and simultaneous events
may occur at different spawning sites
throughout the bay. Herring lay adhe-
sive eggs intertidally and subtidally
on rocks, algae, aquatic plants, pier
pilings, and other substrates (Alderd-
ice and Velsen, 1971; Hay, 1985). Eggs
can experience extremely high mortal-
ity due to predation (McGurk, 1986;
Bishop and Green, 2001), suboptimal
temperature and salinity conditions
(Alderice and Velsen, 1971; Griffin et
al., 1998), as well as reduced hatch-
ing and developmental abnormalities
associated with certain substrate se-
O'Farrell and Larson: Year-class formation in Clupea palllasi
131
lection (Vines et al., 2000). Larvae hatch from eggs
after an incubation period, and the San Francisco Bay
estuary can serve as a larval nursery area until after
metamorphosis into the juvenile stage (Hay, 1985).
Our objectives were 1) to identify periods in the
spawning season that lead to successful (or unsuc-
cessful) juvenile recruitment and 2) to evaluate larval
and juvenile growth variation for two herring year
classes. We used otoliths of juvenile herring from the
1999 and 2000 year classes to back-calculate spawn-
ing-date distributions and determine spawning times
that lead to successful recruitment. Distributions of
spawning were obtained from management surveys.
Growth was then evaluated to determine its role in
year-class formation.
Methods
Surveys
All information on adult herring spawning events and
juvenile herring specimens were obtained from ongoing
monitoring and management surveys conducted by the
California Department of Fish and Game (CDFG).
Data on timing, location, and magnitude of her-
ring spawning events for the 1998-99 and 1999-2000
spawning seasons were obtained from the herring
spawn survey conducted by the California Department
of Fish and Game (CDFG). The survey is conducted
from November through March throughout central San
Francisco Bay, the area of most herring spawning (Wat-
ters et al., 2004). The central bay region is searched for
herring spawning on a daily basis from a small boat,
and the entire spawning region is covered at least once
per week. Eggs are located visually at low tide and
by rake in shallow subtidal areas. When a spawning
area is located, the number of eggs per square meter
is measured from a subsample of the spawning area
and is expanded to an estimate of total eggs spawned
(for spawning survey method details, see Spratt, 1981;
Watters et al., 2004). At the end of the 1998-99 and
1999-2000 spawning seasons, information on date,
location, spawning area, average eggs/m2, total eggs,
and the spawning biomass estimate was provided for
the purpose of this study (Watters1).
Juvenile (age-0) herring were sampled monthly from
30 stations in San Francisco Bay aboard the RV Long-
fin as part of CDFG's Bay/Delta Division's Bay study
(Fig. 1). Each station was visited once a month and
juvenile herring were retained from catches during
the months of April- June 1999 and March- June 2000.
Stations were sampled by mid-water trawl with a 3.7-m2
mouth and 1.3-cm mesh codend, towed against the cur-
rent, for 12 minutes. Volume of water filtered was cal-
culated by using a flowmeter and was used to calculate
-122°30'W
38'00'N
37°30'N
1 Watters, D. 2000. Personal commun. Calif. Dep. Fish
and Game, 411 Burgess Dr., Menlo Park, CA 94025.
Figure 1
Midwater trawl sampling stations in
San Francisco Bay.
catch per unit of effort (CPUE) for each station. Juve-
nile herring were measured onboard, sorted from the
catch, kept on ice, and transported to the laboratory,
where they were frozen. Relative recruitment in each
year was calculated by summing the CPUE at each sta-
tion for the months of March-June in 1999 and 2000.
Otolith preparation and analysis
Frozen juvenile herring, separated by date and station,
were thawed in batches and all fish were re-measured
for standard length to the nearest mm. If the catch was
small at a particular station (less than approximately
10 individuals), all specimens from that station were
reserved for otolith analysis. If the catch was large, a
subsample of the measured catch was reserved for otolith
analysis. Subsampling consisted of randomly selecting
at least two specimens from each 1-mm length bin in
the catch.
Both sagittal otoliths were extracted from each fish,
cleaned with fresh water, and transferred to a micro-
scope slide where they were allowed to dry. When com-
pletely dry, both otoliths were mounted on the slide,
convex side up, with clear nail polish.
Otoliths were read with a compound microscope. Be-
cause otoliths were too thick to allow sufficient light
transmission for increment reading, all otoliths were
132
Fishery Bulletin 103(1)
ground with 2000 grit sandpaper. Otoliths were al-
ternately ground and examined under the microscope
at 100 x to ensure that the section was thin enough to
allow sufficient light transmission, yet not over-ground
so that the edges of the otolith were lost.
Daily increment deposition in herring begins at
yolksac absorption, corresponding with the first heavy
ring near the nucleus (Geffen, 1982; McGurk, 1984a;
McGurk, 1987; Moksness and Wespestad, 1989). This
heavy ring was located in all herring examined and
increment counts were initiated there. Increment counts
were made at 1000 x (with an oil immersion objective)
and 400x (without oil immersion) magnification along
the axis of maximum resolution. All increments were
counted from the first heavy ring until the last ring on
the edge of the otolith.
Several days after the first reading, the same reader
performed a reading on the second otolith. If the two
increment counts differed by more than a value of 7,
a third reading was conducted at a later date on the
highest quality otolith. If the three increment counts
differed from each other by more than a value of 7,
otolith data from that fish were not used in further
analyses. Where two readings differed by 7 or fewer in-
crements, the final increment number for each fish was
determined by averaging the two increment counts.
Daily otolith increment deposition has been demon-
strated in Pacific herring larvae reared in captivity
(McGurk, 1984a; Moksness and Wespestad, 1989) and
in the field (McGurk, 1987). In our study, otolith in-
crements were assumed to be deposited daily and the
validity of this assumption is treated in the "Results"
and "Discussion" sections. Precision of otolith incre-
ment counts was determined by computing the average
percent error for each otolith examined (Beamish and
Fournier, 1981).
Spawning-date distributions
Spawning-date distributions were constructed from
specimens retained for otolith analysis in 1999 and
2000. Distributions were calculated 1) by adding a con-
stant of 14 days to the otolith increment count and 2)
by subtracting that value (otolith increments+14) from
the Julian date of capture. Because Pacific herring begin
daily increment deposition at yolksac absorption, the
constant of 14 days was added to the increment value to
account for egg incubation and the yolksac larval period.
Taylor (1971) reported a 9-day egg incubation period
for a British Columbia Pacific herring stock between
13.4°C and 13.8°C. For San Francisco Bay spawned
herring, Griffin et al. (1998) found developmental rate
to be influenced by salinity; the greatest hatching rate
occurred 10 days after fertilization at a salinity of 14
ppt. Yolksac absorption occurs in Pacific herring 4-7
days after hatching (McGurk, 1987; Griffin et al., 2004,
and references therein). The final value of 14 days for egg
incubation and yolksac absorption used in our study was
determined 1) from laboratory-derived values reported
for British Columbia (Taylor, 1971; McGurk, 1987) and
San Francisco Bay (Griffin et al., 1998) herring popu-
lations and 2) by visually matching back-calculated
spawning-date distributions with the observed spawn-
ing-date distribution from the CDFG spawn-deposition
survey.
The back-calculated spawning-date distributions
determined from specimens used for otolith analy-
sis were extrapolated to include as many herring as
possible caught in the juvenile surveys of 1999 and
2000. Length-frequency distributions were converted
to spawning-date distributions by using age-length
keys. Separate age-length keys were constructed for
each survey in both 1999 and 2000. In some cases,
the monthly survey was split into two legs separated
by several days. When the monthly survey was split
into legs, separate age-length keys were constructed
for each leg.
It was not possible to fit all herring caught between
the months of March and June into age-length keys
because some samples were inadvertently discarded
after measurement in the field. If the range of lengths
in the discarded samples extended beyond the sizes of
samples aged, a complete age-length key could not be
constructed. To avoid ascribing a possibly inaccurate
age to a fish outside the size range of the age-length
key, those fish were not included in the spawning-date
distribution. Table 1 displays the number of herring
caught in each leg, the number of otoliths used to con-
struct the age-length key for that survey leg, and the
total number and proportion of juveniles caught that
are represented in the spawning-date distribution. The
number of juveniles caught was greater than the num-
ber of juveniles in the spawning-date distribution for
all but one survey leg. This discrepancy was due to
discarded fish (in the field) with lengths not within
the range of the age-length key constructed from the
subsampled individuals.
Mortality estimate corrections are often superimposed
upon spawning-date or hatching-date distributions to
account for different size juveniles captured (Methot,
1983). Presumably a larger juvenile is older, and thus
has been exposed to mortality factors for a longer pe-
riod of time than has a smaller juvenile. The lack of a
correction for juvenile mortality can lead to an under-
representation of larger juveniles in the distribution.
Because of the noncontinuous mid-water trawl sampling
schedule, mortality rates could not be estimated from
the data used in our study. As a result, mortality cor-
rections were calculated by using an instantaneous
mortality rate value of 0.016/d, corresponding to the
greater of two mortality rates calculated from juve-
nile Pacific herring in Prince William Sound, Alaska
(Stokesbury et al., 2002).
Spawning-date distributions were corrected for mor-
tality by calculating abundance at age 100 days (N100).
For fishes aged at less than 100 days:
M - M e-0.0161100 -al
JV100 _ JVne '
(1)
where a is the age of the fish in days.
O'Farrell and Larson: Year-class formation in Clupea palllasi
133
Table 1
Summary of the catch.
number of Clupea pallaai otoliths examined fi
om the catch.
number and percent available for
use in the
spawning-date dist
ributions. and catch per unit of effort ( CPUE ) for the midwater trawl survey in
1999 and 2000.
iUPUE repre-
sents summed CPUE for all stations in each survey
leg. Juveniles were not used in analysis if they
were inadvertently
discarded
in the field and if a
complete age-length key could not be constructed.
Juveniles
Otoliths
Used in
Percent
Survey dates
Area surveyed
caught
examined
analysis
used
ZCPUE
1999
Mar 99
entire bay
0
0
0
0
0
21 Apr 99
central and north
41
0
0
0%
1653
26-28 Apr 99
south and north
66
53
60
91%
2360
18-19 May 99
north
19
4
2
11%
771
24-27 May 99
north, central, and south
280
251
273
98%
12,856
9-10 Jun 99
north and central
91
25
45
49%
3457
15 Jun 99
south
61
0
0
0%
2551
Total
558
333
380
68%
23,648
2000
8-9 Mar 00
north and central
11
0
0
0%
637
13-14 Mar 00
south
7
7
6
86%
294
4-5 Apr 00
north
25
25
25
100%
1053
10-11 Apr 00
central and south
302
115
284
94%
14,712
10 May 00
north
898
77
740
82%
38,270
22-24 May 00
central and south
2244
77
2237
100%
102,516
6-7 Jun 00
central and south
569
74
569
100%
25,352
13 Jun 00
north
13
0
0
0%
539
Total
4069
375
3861
95%
183,373
For fishes aged greater than 100 days:
N = N-
■"100 „-0.016la-100l
(2)
Combining the results of Equations 1 and 2 produced the
mortality-corrected spawning-date distributions.
Growth
To evaluate correlates of both inter- and intra-annual
variation in survival to the juvenile stage, we wanted to
compare growth rates of herring up to the juvenile stage.
However, because it was apparent that growth rates may
have differed for specimens spawned at different times of
the year, either a linear or nonlinear growth curve fitted
to size-at-age data would be erroneous (O'Farrell, 2001).
Larger (older) and smaller (younger) individuals would
have experienced different growth histories; therefore a
plot of size versus age for any sample of fish would not
reflect the growth history of any one cohort. Further-
more, consecutive samples rarely contained individuals
from any given cohort because older juveniles appeared
to leave San Francisco Bay. Finally, we did not have
data on size at age of larvae; therefore growth curves
would be incomplete.
Instead, we used age at size to compare growth with-
in and between years. To do this, we computed the num-
Table 2
Summary statistics and distribution of juvenile Clupea
harengus lengths
within the 40-50 mm size
bin
for sam-
pling events where size-at
-age data were
used. Other
sampling events
were not
ncluded in growth
analyses
because they did
not contain
juvenile herring bel
ween the
sizes of 40 mm and 50 mm.
Survey leg
n
Mean (mm)
SD(mm)
26-27 Apr 99
15
43.80
2.54
24-27 May 99
162
45.02
2.63
9 Jun 99
10
42.20
2.82
5 Apr 00
16
46.25
3.00
10-11 Apr 00
23
46.43
2.94
10 May 00
9
43.67
3.04
22-24 May 00
36
44.81
3.19
6-7 Jun 00
36
46.56
2.82
ber of otolith increments (days after yolksac absorption)
present in fish between 40 mm and 50 mm standard
length. This size group was chosen to analyze growth
because it was well represented in both in the 1998-99
and 1999-2000 spawning seasons. The mean and stan-
134
Fishery Bulletin 103(1
dard deviation of the length distribution within the
40-50 mm bin for each sampling event is provided in
Table 2. Thus, the amount of time (measured by otolith
increments) needed for fish to grow to the 40 mm-50
mm size group was used to compare growth. Differences
in age at length were evaluated and compared with
observed variation in juvenile abundance.
distributed throughout the bay (Fig. 3). Peak abun-
dances occurred in May for both 1999 and 2000, and
juveniles were caught throughout the study area. By
June, abundances decreased and herring became more
concentrated in the central Bay region, presumably ag-
gregating in this area prior to exiting San Francisco
Bay for the coastal ocean (Fig. 3).
Results
Egg and juvenile abundance
Both the magnitude and timing of estimated egg deposi-
tion differed little between the 1998-99 and 1999-2000
spawning seasons (Fig. 2). Total egg deposition was esti-
mated to be 9.66 x 1011 eggs for 1998-1999 and 8.59 x 1011
eggs for 1999-2000 (Watters2). Peak egg deposition in
both spawning years occurred in January (Fig. 2).
Abundance of juvenile herring resulting from these
two spawning seasons differed greatly. The cumula-
tive estimated relative recruitment (ICPUE) of juve-
nile herring was 7.75 times greater in 2000 than 1999
(Table 1).
General patterns of juvenile herring distribution were
similar in 1999 and 2000. Juvenile herring recruited to
the sampling gear in March and April and were widely
Watters, D. 2000. Unpubl. data. Calif. Dep of Fish and
Game, 411 Burgess Dr., Menlo Park, CA 94025.
7x10"
6x10"
■a 5x10
CD
cd 4x10
"D
cfl
lu 3x10
2x10"
1x10"
1998-1999
1999-2000
Nov
Dec Jan Feb Mar
Spawning month
Figure 2
Total egg deposition by Pacific herring [Clupea pal-
lasi), summed by spawning month for the 1998-99 and
1999-2000 spawning seasons. Data provided by the Cali-
fornia Department of Fish and Game, Menlo Park.
Spawning-date distributions
The temporal distribution of successful spawning-dates
differed between the 1999 and 2000 year classes (Fig. 4,
A and B). In 1999, the earliest spawning-date that
resulted in juvenile recruitment was 30 November 1998.
The greatest numbers of juvenile recruits were a product
of the middle of the spawning season, from approxi-
mately early January 1999 though early February 1999,
and the highest recruitment occurred from spawnings
between 10 January and 14 January 1999 (Fig. 4A).
An additional spike of recruitment was observed from
spawning events at the end of the season (early March).
The period of highest recruitment came at the same time
as the highest spawning intensity. Spawning events
early in the spawning season (November-December)
appeared to produce few juveniles (Fig. 4A).
In 2000, juveniles recruited from much earlier spawn-
ing events. Back-calculated spawning dates indicated
that spawning may have occurred as early as 13 Octo-
ber 1999 (Fig. 4B). Both the March 2000 and April 2000
juvenile surveys contained herring with back-calculated
spawning dates that ranged from mid to late October,
indicating that a spawning event occurred extremely
early in the spawning season and was undetected by
the spawn-deposition survey (which commences in No-
vember). Although early spawnings appeared to produce
some recruitment success, a near lack of success was
noted for many of the mid-season spawnings that oc-
curred from mid-November through mid-January 2000
(Fig. 4B). This period of poor survival was then followed
by the period of highest recruitment; spawning dates
ranged from mid-January to early March and peak re-
cruitment resulted from February spawning (Fig. 4B).
Juvenile mortality corrections superimposed upon
the spawning-date distributions had little effect on
the general results. An instantaneous juvenile mortal-
ity rate of 0.016/d produced minor adjustments on the
percent recruitment resulting from particular spawning
periods in both years (Fig. 4, A and B). This mortality
correction did not alter the general spawning periods
that resulted in juvenile recruitment. Increasing the in-
stantaneous juvenile mortality rate to 0.05/d (O'Farrell.
unpubl. data) also had negligible effects on the general
results of the spawning-date distributions.
Data for both 1999 and 2000 are not totally complete.
The spawning-date distribution for 1999 was based on a
total of 380 herring, whereas 558 herring were caught
between the months of March and June. Similarly, the
2000 spawning-date distribution was based on a total
of 3861 herring, whereas 4069 herring were caught dur-
ing the same months (Table 1). Fish were omitted from
O'Farrell and Larson: Year-class formation in Clupea palllasi
135
>N<mC
0 0N^C
ONCJ
°NC
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O
o
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Apr 99
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NC
%.
: nc
o
NC°.
D
NC NC
o
NO?*
NCN©
o
Mar 00 NC
oo*nc
°o9-#
o o
CNC
oNS°
OqNC
B
May 99
NC
NC
NC,
NC
E
NC*N(NC
O
NC
N(Nfic
Apr 00 Nc
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NC
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NC
NC» NC
NCN'
^C
May Qfl
CPUE
f~) > 1 0.000
O 5001-10,000
O 1001-5000
o 1-1000
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NCN^C
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Jun 00 NC)
Figure 3
Juvenile herring {Clupea pallasi) CPUE distribution by station and month for 1999
and 2000. April 1999 (A) dark bubbles represent the 21 April survey leg and light
bubbles represent the 28-28 April survey leg. May 1999 (B) dark bubbles represent
the 18-19 May survey leg and light bubbles represent the 24-27 May survey leg.
June 1999 (C) dark bubbles represent the 9-10 June survey leg and light bubbles
represent the 15 June survey leg. March 2000 (D) dark bubbles represent the 8-9
March survey leg and light bubbles represent the 13-14 March survey leg. April 2000
(E) dark bubbles represent the 4-5 April survey leg and light bubbles represent the
10-11 April survey leg. May 2000 (F) dark bubbles represent the 22-24 May survey
leg and light bubbles represent the 10 May survey leg. June 2000 (G) dark bubbles
represent the 6-7 June survey leg and light bubbles represent 13 June survey leg.
the spawning-date distribution because some samples
were discarded and otoliths were unavailable. Because
of evidence for intrayear growth-rate variation, other
age-at-length data were not used to infer spawning
dates for these fish. The standard length data for the
fish not included in this analysis were used for all other
analyses in our study.
Precision of multiple otolith readings was calcu-
lated for all otoliths examined. Average percent error
(Beamish and Fournier, 1981) was 3.60% in 1999 and
1.64% in 2000, indicating that aging precision was less
than 4 days for 100-day old herring in both years.
Growth
Different patterns of age at length (40-50 mm) were
observed in 1999 and 2000. In 1999, specimens between
40 mm and 50 mm were captured in three survey legs.
A significant decrease in the number of otolith incre-
ments for juveniles 40 mm-50 mm standard length
was detected in 1999 (Fig. 5A; Kruskal-Wallis test;
r7=27.93, P<0.0001). Nonparametric multiple compari-
sons indicated that there was a nonsignificant difference
in otolith increment counts for herring caught in the
April 1999 and the May 1999 surveys, but herring from
these surveys had significantly higher median otolith
increment counts than those from the June 1999 survey.
In this later survey, juvenile herring were caught that
were a product of spawning events occurring late in
the spawning season. Figure 5C displays the median
and range of spawning dates of the specimens aged
for Figure 5A. Juvenile herring that were a product of
spawning between 27 February 1999 and 7 March 1999
reached a 40-50 mm size range significantly faster than
136
Fishery Bulletin 103(1)
20
15
10
5 -
with mortality correction
without mortality correction
eggs
0
10/1/98
6x10'
5x10"
4x10'
3x101
2x10'
1x10"
12/1/98
2/1/99
4/1/99
25
20
15 -
10 -
5 -
with mortality correction
without mortality correction
eggs
B
o
10/1/99
^l MJ
6x10'
_ 5x10'
4x10'
3x10'
2x10'
1x10'
12/1/99 2/1/00
Spawning date
4/1/00
Figure 4
Spawning-date distributions for juvenile herring (Clupea pallasi) caught in (A) 1999
and (B) 2000. Vertical bars represent dates and magnitude of observed spawning (eggs
deposited), heavy lines represent the spawning-date distribution of juveniles without
the mortality correction, and light lines represent the spawning-date distribution
corrected for juvenile mortality at an instantaneous rate of 0.016/d. Distributions are
smoothed with a cubic spline interpolation. Data on observed spawning were provided
by D. Watters, CDFG (see Footnote 2 in the text).
O'Farrell and Larson: Year-class formation in Clupea palllasi
137
160
140 -
S 120 -
E
o
5
15 162
160
140 -
120 -
100
80
60
40
3/1/99 4/1/99 5/1/99 6/1/99 7/1/99
B
\
36 Jb
40
3/1/00 4/1/00 5/1/00 6/1/00 7/1/00
Collection date
- 12
140 -
- 10
- 8
120 -
- 6
100 -
- 4
80 -
- 2
60 -
40
D
i — ■ 1
NL
9/1/98 11/1/98 1/1/99 3/1/99 5/1/99
9/1/99 11/1/99 1/1/00 3/1/00 5/1/00
Spawning date
Figure 5
The upper panels display otolith increments present in 40 mm-50 mm juvenile
herring {Clupea pallasi) arranged by capture date for (A) 1999 and (B) 2000.
Boxes represent median number of otolith increments, bars indicate ±1 SD,
and the number above each point is the sample size. The lower panel displays
growth histories for juvenile herring originating from various periods within
the spawning season for (C) 1999 and (D) 2000. Boxes represent median spawn-
ing-dates and bars represent range of spawning dates at that growth rate. The
spawning-date distribution (uncorrected for juvenile mortality) is superimposed
upon C and D to ascertain how changes in growth are reflected in survival to
the juvenile stage.
specimens recruiting from earlier spawning periods.
The period of greatest recruitment occurred during the
slower growth period in 1999 (Fig. 5C).
In 2000, 40 mm-50 mm juvenile herring were caught
in five survey legs conducted during three months (April,
May, and June). The data are displayed by survey leg;
pooling the data by month, however, does not change the
result. Median increment counts differed significantly
for the 2000 surveys (Fig. 5B; #=76.39, P<0.0001). Oto-
lith increment counts for 40 mm-50 mm specimens did
not differ for the 5 April 2000 and 10-11 April 2000
surveys. However, the age at length for these surveys
was significantly greater than for the three later survey
legs (10 May 2000, 22-24 May 2000, and 6 June 2000),
which did not significantly differ from each other. Her-
ring caught in the three later surveys grew significantly
faster than herring caught in the two earlier surveys.
The significant decrease in age at length indicates that
juvenile herring that were a product of spawning be-
tween 15 January 2000 and 18 March 2000 grew faster
than specimens recruiting from earlier spawning events.
The majority of juvenile recruits in 2000 were a product
of the fast growth period (Fig. 5D).
Accuracy of growth-rate estimates determined from
growth increments on otoliths
The above analyses depended upon the assumption that
increments were deposited daily in the otoliths exam-
ined. Two lines of evidence point to the validity of this
assumption. First, back-calculated spawning-dates gen-
erally agreed with the known spawning season of San
Francisco Bay herring, and several peaks in back-cal-
culated spawning dates match known spawning events
quite closely (Fig. 4, A and B).
Second, juvenile growth rates appear to be high
enough for daily growth (McGurk, 1984b). Clear length-
frequency modes were visible for three sampling events
138
Fishery Bulletin 103(1)
in 2000. Assuming linear growth between these time
periods, the advancement of these length-frequency
modes resulted in growth rates of 0.75 mm/d (Fig. 6,
arrow in A), 0.83 mm/d (arrow in B), and 0.64 mm/d
(arrow in C). McGurk (1984b) demonstrated daily in-
crement deposition in herring if the larval growth rate
exceeded 0.36 mm/d. Our data did not allow us to es-
timate growth rates of larvae; however, the estimated
juvenile growth rates presented above are much greater
than necessary for daily increment deposition.
Discussion
Catches of juvenile herring were much greater in 2000
than in 1999. Between the months of March and June
2000, cumulative CPUE was more that seven times
greater than during the same period in 1999, yet an
estimated 12% more eggs were deposited during the
10 May 2000
20
30 40 50 60
Standard length (mm)
Figure 6
Length frequencies for juvenile herring (Clupea pallasi)
captured on 10 May 2000, 22 May 2000, and 6 June 2000.
Arrows represent the estimated propagation of length modes
through time. Linear growth rates, calculated from each
trajectory, are as follows: A=0.75 mm/d; trajectory B = 0.83
mm/d); and C = 0.64 mm/d.
1988-99 spawning season. Because observed differences
in recruitment between 1999 and 2000 far exceeded dif-
ferences in the total eggs spawned, differential survivor-
ship during the egg or larval stages (or both) must be
responsible for disparate year-class strengths.
The spawning-date distributions presented for 1999
and 2000 did not contain all herring caught by the mid-
water trawl survey between the months of March and
June. Because they could not be accurately assigned
ages with an age-length key (Table 1), 178 herring were
omitted from the distribution in 1999. Most specimens
omitted from this distribution were caught in the early
April 1999 and late June 1999 survey legs. As a result,
the spawning-date distribution likely underestimated
the recruitment from very early and very late season
spawnings. In 2000, 208 specimens, from a variety of
survey legs, were omitted from the spawning-date dis-
tribution (Table 1). Because a large number of herring
were caught in 2000, it is unlikely that these omissions
would significantly change the shape of the spawn-
ing-date distribution. The loss of data in this case
does not change the overall result of large year-class-
strength variation.
The noncontinuous sampling schedule for juve-
niles may have resulted in either an underestima-
tion or overestimation of CPUE and thus year-class
strength. In several months, the mid-water trawl sur-
vey was conducted over two legs separated by several
days (Table 1, Fig. 3). This noncontinuous sampling
could have produced error in our estimates because
aggregations of juveniles, through movement between
areas, could conceivably have escaped detection by
trawls (resulting in CPUE underestimation) or have
been sampled twice in the same month (resulting in
CPUE overestimation). However, O'Farrell (2001)
showed that dispersal of herring from a successful
spawning event could occur through much of San
Francisco Bay. Therefore, we do not believe that ag-
gregations of juveniles were completely missed by
the mid-water trawl survey. The degree to which ag-
gregations of juveniles were sampled more than once
in a sampling month is not known.
Variation in age estimates undoubtedly produced
back-calculated spawning-dates that did not match
exactly with true spawning dates. Yet, for some
spawning events, very good matches between back-
calculated and reported spawning events indicate
that the age estimations were accurate for many of
the cohorts examined (O'Farrell, 2001). Other cohorts
that did not match as well with reported spawnings
may be the result of 1) a spawning event undetected
by the spawn-deposition study, 2) a small, "spot"
spawning that did not qualify as a true spawning
event for the spawn-deposition study, or 3) very slow
or fast growth through a portion of the larval life
history that interrupted daily increment deposition
(McGurk, 1984b, 1987).
Increased survival did not occur throughout the
entire 2000 spawning season. Instead, periods of
good survival and poor survival were present, yet the
O'Farrell and Larson: Year-class formation in Clupea palllasi
139
periods of good survival in 2000 led to a much stronger
year class than that of 1999. Detecting a "match" of
favorable conditions that led to recruitment success was
not possible in our study because of the myriad factors
that can determine recruitment success. Rather than
attempting to explain the observed survival differences
with specific mechanisms, we suggest what may pos-
sibly contribute to the observed patterns.
Larval survival
The degree to which larval survival depends upon biotic
or abiotic factors is difficult to estimate. Fox (2001)
presented data showing that year-class strength in the
Blackwater stock of Atlantic herring {Clupea harengus
L.) was determined by survival after the egg stage. How-
ever, it is not clear whether variation in survival was due
to density-dependent or environmental factors. A recent
study has shown that salinity can affect larval survival
after hatching in San Francisco Bay herring (Griffin et
al., 20041. Here, the salinity during embryonic develop-
ment was a factor in yolksac larval survival in different
salinity treatments. Regardless of the form of mortality
operating on larvae, small changes in larval growth
rate can lead to large changes in levels of recruitment
(Houde, 1987). Faster larval growth results in shorter
larval stage duration and thus decreased exposure to
the characteristically high mortality of the larval stage.
Age at size for herring in this study decreased signifi-
cantly as the spawning season progressed both in 1999
and 2000. From this finding, we infer that positive
changes in growth rate occurred during the spring and
summer. Seasonal positive shifts in growth have also
been observed in Pacific herring populations in Prince
William Sound, Alaska, between the months of June and
October (Stokesbury et al., 1999).
In 1999, the greatest number of recruits came from
mid to late-season spawning events. The late February
to early March spike in recruitment (Fig. 4 A) may be
partially explained by within-year growth variation. This
group of survivors appeared to be derived from a rela-
tively small number of eggs. Recruits from that spawn-
ing period grew significantly faster than recruits from
earlier spawning events. The largest spawning events
of the 1998-99 spawning season produced recruits that
grew slower than the recruits spawned in early March
and thus may have experienced lower relative survival.
Within-year growth rate variation also partially ex-
plains the 2000 year class. The 2000 year class was
dominated by late season recruitment, primarily from
spawning in February 2000. Herring from spawning
events occurring between late October 1999 and mid-
January 2000 had a significantly higher median age at
length than herring produced from subsequent spawn-
ing times. This slow growth may in part explain the
near lack of recruitment from the two highest magni-
tude spawns occurring from 1 to 3 Jan 2000 and from
19 to 24 Jan 2000. However, age at length decreased
(and thus growth rate increased) for spawning events
occurring from late January 2000 to early March 2000.
The timing of the growth rate switch (from slow to fast)
coincided closely with the spawning period producing
the greatest amount of recruitment. The general trend
of high levels of recruitment from late season spawning
events indicates that increased growth rate played a
role in the good survival during this period. However,
recruitment from very early spawning events and the
small number of recruits resulting from late March
2000 spawning was not explained solely by this within-
year growth variation.
Egg mortality
Variation in mortality during the egg stage may also
affect recruitment in San Francisco Bay herring. Fertil-
ization, embryonic development, and hatching success of
Pacific herring are strongly tied to environmental condi-
tions (Alderdice and Velsen, 1971, Griffin et al., 1998).
The optimal range for fertilization and development of
the San Francisco Bay population is between 12 ppt
and 24 ppt, and both percent fertilization and percent
hatching is maximized at 16 ppt (Griffin et al., 1998).
The herring spawning season in San Francisco Bay is
a time of rapidly changing salinities. High salinities
generally persist through the fall months. In winter,
rapid decreases in salinity due to freshwater from the
San Joaquin-Sacramento Delta, storm drain runoff and
local creek purges (Oda3) are common, yet the magnitude
varies between years (Conomos et al., 1985). In the two
years examined, salinity during the winter spawning
season varied both above and below the optimum range
determined by Griffin et al. (1998). These salinity fluc-
tuations could have a large effect on the supply of larvae
into the San Francisco Bay system.
Mortality during the egg stage can be exceedingly
high in Pacific herring due to predation and other biotic
interactions (Alderdice and Velsen, 1971; McGurk, 1986;
Rooper et al., 1999, Bishop and Green, 2001). As a re-
sult, egg incubation time may have a significant effect
upon eventual recruitment. The length of times of egg
incubation and the yolksac larval stage were combined
in our study and the combined period was given a con-
stant value of 14 days. In actuality, egg incubation time
(Taylor, 1971; McGurk, 1987) and embryonic develop-
ment (Alderdice and Velsen, 1971; Griffin et al., 1998)
are strongly linked to environmental factors and likely
have a significant effect upon recruitment before growth
rates can determine survival. Analysis of egg incubation
and yolksac larval duration for separate cohorts was not
performed in our study. It may, however, play a large
role in larval abundance.
Conclusion
The 1999 and 2000 spawning-date distributions indicate
that year classes can be shaped by periods of good and
3 Oda, K. 2000. Personal commun. Calif. Dep. Fish and
Game, 411 Burgess Dr., Menlo Park, CA 94025.
140
Fishery Bulletin 103(1)
poor survival lasting shorter than the duration of the
spawning season, yet longer than the duration of an
individual spawning event. The distributions indicated
that variation in survivorship was not only a function
of individual spawn success. Rather, periods of good
and poor survivorship in 1999 and 2000 were of longer
duration than one spawning event. The period of excep-
tionally good survival that led to the majority of the
strong 2000 year class was approximately one month in
duration and incorporated several spawning events. Yet
this window of good survival was much shorter than the
entire 2000 spawning season. Variation in survivorship
between individual spawnings may be less important in
shaping the year class than survivorship variation on
a longer time scale.
Visual examination of the spawning-date distribu-
tion superimposed upon juvenile age at length indicate
that faster growth had a positive effect on recruitment
in 2000, and a negligible effect in 1999. For larval
growth to affect recruitment, larvae must be available
from hatching eggs. Year-class strength variation in
Pacific herring could depend upon both egg and larval
survival.
The timing of peak herring spawning in San Fran-
cisco Bay may be a tradeoff between maximizing larval
growth rates and spawning when hydrographic condi-
tions are optimal for embryonic development. In the two
years examined, growth rate increased with the progres-
sion of the spawning season. It follows that the herring
population could maximize recruitment by spawning
later so that larvae grow faster. However, because delta
outflow is generally high in February and March on
account of winter storms, late season spawning may ex-
pose eggs to low salinities and thus decreased hatching
rates. Peak spawning may occur in January as a trade
off between growth-rate and egg-hatching success.
Acknowledgments
This research would not have been possible without the
extensive cooperation of the California Department of
Fish and Game Belmont and Stockton offices. In par-
ticular, we would like to thank Diana Watters, Ken Oda,
Sara Peterson, Kathy Hieb, Kevin Fleming, Tom Greiner,
Suzanne Deleon, and the entire crew of the RV Longfin.
Stephen Bollens, Steven Obrebski, Ken Oda, and three
anonymous reviewers provided very helpful comments
on various drafts of this manuscript.
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142
Abstract — Diet analysis of 52 log-
gerhead sea turtles (Caretta caretta)
collected as bycatch from 1990 to 1992
in the high-seas driftnet fishery oper-
ating between lat. 29.5°N and 43°N
and between long. 150°E and 154°W
demonstrated that these turtles fed
predominately at the surface; few
deeper water prey items were pres-
ent in their stomachs. The turtles
ranged in size from 13.5 to 74.0 cm
curved carapace length. Whole tur-
tles (n = 10) and excised stomachs
(n = 42) were frozen and transported
to a laboratory for analysis of major
faunal components. Neustonic species
accounted for four of the five most
common prey taxa. The most common
prey items were Janthina spp. (Gas-
tropoda); Carinaria cithara Benson
1835 (Heteropoda); a chondrophore,
Velella velella (Hydrodia); Lepas spp.
(Cirripedia), Planes spp. (Decapoda:
Grapsidae), and pyrosomas (Pyrosoma
spp.).
Diet of oceanic loggerhead sea turtles
(Caretta caretta) in the central North Pacific
Denise M. Parker
Joint Institute for Marine and Atmospheric Research
8604 La Jolla Shores Drive
La Jolla, California 92037
Present address: Northwest Fisheries Science Center
National Marine Fisheries Service, NOAA
Newport, Oregon 97365-5275
E-mail address Denise Parkers noaa gov
William J. Cooke
AECOS, Inc.
970 N. Kalaheo Avenue, Suite C311
Kailua. Hawaii 96734
George H. Balazs
Pacific Islands Fisheries Science Center, Honolulu Laboratory
National Marine Fisheries Service
2570 Dole Street
Honolulu, Hawaii 96822-2396
Manuscript submitted 15 July 2003
to the Scientific Editor's Office.
Manuscript approved for publication
8 July 2004 by the Scientific Editor.
Fish. Bull. 103:142-152 12005).
Loggerhead sea turtles are circum-
global, inhabiting temperate, sub-
tropical, and tropical waters of the
Atlantic, Pacific, and Indian Oceans.
In the Pacific, loggerhead sea turtles
have been found in nearshore waters
of China, Taiwan, Japan, Australia,
and New Zealand and are seen in off-
shore waters of Washington, Califor-
nia, and northwestern Mexico (Dodd,
1988; Pitman, 1990). Nesting in the
North Pacific Ocean occurs in Japan;
there is no known nesting in the east-
ern North Pacific (Marquez and Vil-
lanueva, 1982; Frazier, 1985; Bartlett,
1989). Trans-Pacific migrations of
juveniles have been documented from
mitochondrial DNA analyses of indi-
viduals found feeding off Baja Cali-
fornia. Bowen et al. (1995) identified
these Baja sea turtles as originating
from Japanese rookeries, although a
a small percentage come from Aus-
tralia. Recent research indicates that
all loggerhead sea turtles found in the
oceanic realm of the central North
Pacific Ocean are of Japanese stock
(Dutton et al., 1998). Tagging studies
in Japan and the Eastern Pacific also
demonstrate transpacific migrations
of loggerhead sea turtles between the
east and west Pacific (Balazs, 1989;
Resendiz et al., 1998; Uchida and
Teruya1).
Recent oceanic satellite tracking
studies of loggerhead sea turtles in-
dicate that they are active in their
oceanic movements. These turtles
follow subtropical fronts as they
travel toward Japan from east to
west across the Pacific Ocean, often
swimming against weak geostrophic
currents (Polovina et al., 2000; Po-
lovina et al., 2004). One hypothesis
discussed in Polovina et al. (2000;
2004) suggests that this species ob-
tains prey items from the subtropi-
cal fronts along which they travel. A
sharp gradient in surface chlorophyll
is observed along the main frontal
area where these turtles are com-
monly encountered. This frontal area,
the transition zone chlorophyll front
Uchida, S., and H. Teruya. 1991. A)
Transpacific migration of a tagged log-
gerhead, Caretta caretta. B) Tag-return
result of loggerhead released from Oki-
nawa Islands, Japan. In International
symposium on sea turtles '88 in Japan
(I. Uchida, ed.), p. 169-182. Himeji City
Aquarium, Tegarayama 440 Nishinobu-
sue, Himeji-shi, Hyoyo 670, Japan.
Parker et al.: Diet of Caretta caretta in the central North Pacific
143
60 N
40CN
20° N
0°N
20°N
40'N
O less than 50 cm CCL
• 50 cm CCL or greater
120°E
160°E
160W
120°W
80°W
Figure 1
Distribution of loggerhead sea turtles {Caretta caretta) incidentally captured in the
international high seas driftnet fishery in the central North Pacific Ocean. Turtles
smaller than 50 cm curved carapace length (CCL) are shown as open diamonds
and those larger than 50 cm CCL are shown as black circles.
(TZCF), is an area of concentrated phytoplankton that
also collects and attracts a variety of neustonic and oce-
anic organisms — many of which may be potential prey
times, as well as predators, of oceanic-stage loggerhead
sea turtles in the Pacific. Polovina et al. (2000, 2004)
have suggested that the turtles are foraging along the
TZCF.
The duration of the juvenile oceanic stage for logger-
head sea turtles in the Pacific is currently unknown. In
the Atlantic, juvenile turtles inhabit the oceanic zone
for approximately 10 years (Bjorndal et al., 2000). Based
on growth analyses (Zug et al., 1995; Chaloupka, 1998),
it is probable that this sea turtle from the Pacific can
have a similar extended oceanic stage, which in some
cases may last until sexual maturity (30+ years).
Understanding the diets of sea turtles is important
for their conservation. Foraging studies have been done
with oceanic-stage turtles in the Atlantic (Van Nierop
and den Hartog, 1984). However, there is a paucity of
information regarding the foraging ecology of oceanic-
stage loggerhead sea turtles in the Pacific. Such infor-
mation can help identify important food resources and
foraging areas necessary for guiding decisions regarding
the management of endangered sea turtle populations
(Bjorndal, 1999). The objective of the present study is to
determine the diet composition of loggerhead sea turtles
from the central North Pacific Ocean and to discuss the
possibility of interactions between these turtles and
commercial fisheries that may occur as a result of the
foraging behavior of these sea turtles.
Method
National Marine Fisheries Service (NMFS) observers
between 1990 and 1992 obtained 52 dead loggerhead
sea turtles. These specimens were taken as bycatch
in the international high-seas driftnet fishery, which
targeted squid and albacore (Wetherall et al., 1993).
NMFS observers recorded capture position and sea sur-
face temperature aboard commercial driftnet vessels.
Samples were collected between latitude 29.5°N and
43°N and longitude 150°E and 154°W (Fig. 1). A total of
10 whole specimens and 42 excised stomachs were frozen
and transported to a Honolulu laboratory for analysis.
Stomachs were removed from whole specimens and all
stomachs were examined from anterior to posterior.
Gross observations of stomach contents were made and
the contents were sorted to the lowest identifiable taxo-
nomic level by using a dissecting microscope. Major fauna
were identified, quantified by volume, and the percent
contribution (to stomach contents) of each major organ-
ism was calculated (Forbes, 1999). Presence of jellyfish
or other jellies were identified by presence of tentacles,
nematocysts, and whole or partial individuals. Planes
spp. were identified from descriptions of Spivak and Bas
(1999). Frequency of occurrence of major components was
calculated by dividing the number of stomachs in which
the prey item occurred by the total number of turtle
stomachs examined. Percent sample volume was calcu-
lated for all prey items by summing the total volume of
each prey item and dividing it by the total volume of all
144
Fishery Bulletin 103(1)
prey collected. Summing the total volume of each prey
item and dividing it by the total stomach volume for those
samples, where the prey item was present, yielded the
mean percent volume. Regression analysis was done to
determine if any correlation existed between sea surface
temperature, sample volume, and size of turtle.
Results
Loggerhead sea turtles collected in our study were found
widely distributed over the central North Pacific Ocean
and there was no apparent difference in distribution
16
14
12
10-19 cm 20-29 cm 30-39 cm 40-49 cm 50-59 cm
Curved carapace length (cm)
60-69 cm 70-79 cm
Figure 2
Size distribution for the 52 loggerhead sea turtles [Caretta caretta) obtained
as samples in the high-seas driftnet fishery. Sizes were grouped into
10-cm size classes.
21 0
20.0
19.0
180
17.0
16.0
15.0
• • • I
• •* * •
• • * '•
• • • ym •••
0.0 10.0 20.0 30.0 40.0 50 0
Curved carapace length (cm)
60.0
700
Figure 3
Relationship between curved carapace length (CCL, cm) of loggerhead sea
turtles [Caretta caretta) and sea surface temperature iSST, n = 52).
between size classes (Fig. 1). The turtle specimens
ranged from 13.5 cm to 74.0 cm curved carapace length
(CCL, Fig. 2); the mean was 44.8 [±14.5] cm CCL. Figure
2 shows the distribution of turtles in each 10-cm size
class. Sea surface temperatures in the area of cap-
ture ranged from 16° to 20°C. There was no correlation
between size of turtle and sea surface temperature in
the area of capture (F=0.58, r2=0.01, Fig. 3).
All 52 stomachs examined contained prey items; the
level of fill varied from 6 mL to 1262 mL. Items found
in the anterior portion of the stomach were the most
identifiable and contents varied between turtles. Un-
identifiable remains were located mainly in the poste-
rior end of the stomach or the intes-
tines if a whole gastrointestinal tract
was analyzed. Only one of the samples
analyzed included an entire gastroin-
testinal tract.
A taxonomic listing of diet items
identified for the loggerhead sea turtles
of the central North Pacific is shown in
Table 1 along with frequency of occur-
rence and mean percent sample volume
of each prey item. The six most com-
mon (frequent) prey items were iden-
tified. These included Janthina spp.,
which occurred in 75% of samples, and
Planes spp., which occurred in 56% of
samples. Lepas spp. occurred in 52%
of the samples, and Carinaria cithara
was found in 50% of samples. Velella
velella, was found in 25% of the sam-
ples, and pyrosomas were found in 21%
of samples (Table 1). Other common
food items found in stomachs were fish
eggs (25% of stomachs), salps, amphi-
pods (46% of stomachs), small fish, and
plastic items (35% of stomachs. Table
1). Some plastic items included small
plastic beads, thin plastic sheets, poly-
propylene line, and even a small plastic
fish, which had been an individual soy
sauce container. Although Velella, py-
rosomas, and salps were represented
as prey items in our samples, other
types of jellies may not have been well
represented because their soft bodies
may dissolve more quickly in stomach
acids. It is also possible that unidenti-
fied jellies may comprise the unidenti-
fied remains, which occurred in 71%
of stomachs and comprised 13.8% of
total sample volume; however, a por-
tion of the unidentified remains were
likely masticated portions of identified
prey items. Table 2 shows the mean
percent prey item volumes for the six
most common prey items. The six most
common prey items can be ranked from
largest to smallest mean volumes in
80.0
Parker et al .: Diet of Caretta caretta in the central North Pacific
145
Table 1
Percent occurrence and percentage of total sample volume (volume of prey for all stomachs
combined) for
prey items (listed to
lowest taxonomic order) found in loggerhead sea turtles {Caretta caretta, n = 52 turtles).
Occurrence
Percent volume
Prey group
(%)
(%)
Carinaria eithara Benson 1835
50.0
43.8
Janthina spp. (includes J.janthina and J. prolongata = J. globosa)
75.0
14.4
Lepas spp. (includes L.anserifera Linnaeus 1767 and L.anatifera anatifera Linnaeus 1758)
51.9
6.7
Velella velella Linneaus 1758 (by-the-wind-sailor)
25.0
10.6
Planes spp. Dana 1852
55.8
1.2
Pyrosoma spp.
21.0
3.4
Fish eggs iHirundicthys speculiger and unidentified spp.)
25.0
1.9
Cephalopoda (squid and octopus fragments and paralarvae)
21.2
0.5
Debris (plastic, styrofoam, paper, rubber, polypropylene, etc.)
34.6
0.3
Debris (wood, bird feathers)
11.5
<0.1
Salpidae
13.5
0.5
Family Sternoptychidae (hatchetfish)
7.7
0.1
Electrona sp. — Myctophidae
1.9
0.1
Gammaridea and Hyperiidea amphipods
46.2
<0.1
Thecosomate pteropods
13.5
<0.1
Cavolinia globulosa (Gray 1850)
11.5
<0.1
POLYCHAETA (polychaete worms)— Alciopidae
5.8
<0.1
ISOPODA
3.8
<0.1
MYSIDACEA— mysid
3.8
<0.1
Creseis sp.
1.9
<0.1
PHAEOPHYTA (brown algae )—Cystoseira sp.
1.9
<0.1
EUPHAUSIACEA— euphausiid
1.9
<0.1
Unidentified tunicate spp.
13.5
1.0
Unidentified jellies
13.5
0.5
Unidentified crustaceans
5.8
0.5
Unidentified remains
71.2
13.8
the following order: 1) Carinaria eithara, 2) Pyrosoma
spp., 3) Janthina spp., 4) Velella velella, 5) Lepas spp.,
and 6) Planes spp.
Mean sample volume was 370.2 [±319.4] mL. Size of
loggerhead sea turtles did not influence the volume of
prey items for turtle sizes 35-70+ cm (F=0.11, r2=0.05).
However, the smaller turtles did have smaller volumes
of prey items present in their stomachs, because all
turtles 13-34 cm had less than 80 mL total stomach
volume (Fig. 4). The size of the turtle did not appear to
be a factor in the type of prey ingested. The one excep-
tion may be Velella velella. Turtles smaller than 30 cm
CCL in our sample did not ingest this prey item, albeit
sample size for less than 30-cm turtles was relatively
small compared to the number of 40- and 50-cm size
class turtles (Fig. 2); therefore, this apparent trend may
not be the case for the general population.
Of the six most common prey items, Carinaria ei-
thara had the highest percent sample volume, 43.8%
of total sample volume. In general, percent volumes
of C. eithara were high; 20 of the 27 turtle stomachs
Table 2
Mean percent volume and percent
volume ranges for the
six most frequently observed prey
items found in
driftnet
captured loggerhead
sea turtles (Caretta caretta)
Mean
Standard
percent
deviation
Prey item
volume
(±%)
Range
Janthina spp.
30.7%
34.8%
1-97%
Carinaria eithara
52.8%
33.1%
1-98%
Lepas spp.
19.1%
24.7%
1-99%
Velella velella
22.7%
29.4%
1-84%
Planes spp.
5.6%
10.1%
1-38%
Pyrosoma spp.
44.7%
33.7%
1-88%
had percent volumes greater than 30% with this prey
item and a number of stomachs had percent volumes
greater than 90%. Janthina spp. had the next highest
146
Fishery Bulletin 103(1)
percent sample volume at 14.4%. The percent volume of
Janthina was generally high; 15 of 37 turtle stomachs
had greater than 30% volume of this species. Only 4 of
the 13 stomachs with Velella velella had greater than
30% sample volume; yet Velella made up almost 11% of
total sample volume, and one of the stomach samples
was almost entirely filled (84% volume) with Velella
prey. In the samples that contained pyrosomas, this
prey item often comprised a high percent of the total
gut content — up to 88% stomach volume — and 7 out of
11 stomachs had greater than 30% stomach volume of
pyrosomas. Planes spp. comprised more than 30% of
stomach volume in only 2 of the 29 stomachs contain-
ing this species. Lepas spp. often occurred in very high
percent volumes (up to 99% of total gut content in one
sample), although only 6 of 21 stomachs had percent
volumes greater than 30% for Lepas.
Discussion
Prey items
Loggerhead sea turtles in North Pacific oceanic habi-
tats are opportunistic feeders that ingest items floating
at or near the surface. Availability of prey in the oce-
anic realm is generally characterized as patchy. This
means that the majority of the ocean contains little to
no forage, but in some areas high densities of prey can
be found. This unpredictability of prey availability likely
contributes to the opportunistic feeding behavior of the
loggerhead sea turtle. The TZCF, an area of convergence
created within the subtropical frontal zone by cooler
denser water masses converging and sinking below
warmer lighter water masses (Roden, 1991), may serve
to help concentrate different prey items. Prey items such
as Velella can often concentrate in large numbers in such
areas (Evans, 1986). All size classes of this sea turtle
1400-,
f 1200
•
sz
•
S 1000-
•
E
•
o
to 800 ■
g 600-
Q.
• . •
• •
° 400-
• • •
E
id
o 200-
;• : • . •
• • • • •
0 -I 1 w ■ 1 1 1 1 1 1 1
00 10.0 200 30.0 40.0 50.0 60.0 70.0 80.0
Curved carapace length (cm)
Figure 4
Relationship between curved carapace length (CCL, cm) of loggerheads
(Caretta caretta) and stomach volume IraL, n = 52)
collected in our study were found between 16° and 21°C
(Fig. 3), which typically are the temperatures that define
the subtropical frontal zone and TZCF (Roden, 1991).
Eighty-three percent of prey items that were recorded
were found floating on the surface or were found on
floating objects and would also likely be concentrated
at convergent fronts such as the TZCF, driven there by
the currents and winds (Polovina, et al., 2000; Polovina
et al., 2004). It is suggested that this concentration of
prey, along the convergent fronts, may be aggregating
the loggerhead sea turtles traveling along this area,
which are likely foraging on the increased densities
of prey (Polovina et al., 2003a). Turtles in our study
smaller than 30-cm CCL had very low volumes of prey
in their stomachs. It is unknown whether the paucity of
prey items in these turtle stomachs was related to the
individual's size, e.g. they were physically not able to
capture or ingest certain types of prey items, or perhaps
to a lack of experience in foraging due to youth, given
that turtles in this size range were determined to be
between 1 and 4 years of age by Zug et al. (1995), or to
other mitigating factors.
Another indication that loggerhead sea turtles are
opportunistic feeders is the presence of oceanic, me-
sopelagic fish as prey items. The total number of fish
(lanternfish and hatchetfish) in the samples was low
(only 0.1 % of total stomach volume). These species of
fish tend to stay below the photic zone usually at depths
greater than 300 m during the day and migrate up near
the surface at night. Lanternfish make diel vertical mi-
grations where they reach maximum densities at 100 m
at night. During nightly movements some species can
also come directly to the surface (Hulley, 1990). Some
species of hatchetfish also make diel vertical migrations,
which would bring them to within 100 m of the surface
at night (Weitzman, 1986; Froese and Pauly, 2003).
Because of the low numbers, it is likely that loggerhead
sea turtles ingest only dead or debilitated fish rather
than actively hunt and chase such spe-
cies. The presence of these species also
indicates that the turtles may be feeding
at night when they would be more likely
to encounter the fish during their diel
movement. Another prey item exhibiting
diel vertical migration is the pyrosomas.
Pyrosomas, which are a part of Pacific
leatherback sea turtle diets (Davenport
and Balazs, 1991), were also present in
loggerhead sea turtle stomach samples.
Pyrosomas are colonial tunicates com-
prising individual zooids embedded in
the walls of a gelatinous tube. These
colonies can become quite large (some
greater that 4 meters in length) and
tend to drift with ocean currents and
accumulate along frontal zones which
make them accessible to the sea turtle
that forages opportunistically. At least
one species (P. atlanticum) has been re-
corded to stay below 300 m during the
Parker et al : Diet of Caretta caretta in the central North Pacific
147
day and move up near the surface at night (Andersen
and Sardou, 1994); this activity again may indicate ac-
tive night foraging by the loggerhead sea turtle.
Loggerhead sea turtles may feed by swallowing float-
ing prey whole and also by biting whole prey (or por-
tions off a whole prey) found on large floating objects. A
commonly ingested prey item, Velella velella, known as
"by-the-wind-sailor" (Eldredge and Devaney, 1977), typi-
cally was found intact. Janthina spp.. predatory gastro-
pods whose main prey item is Velella velella, were also
frequently found whole in stomachs. Small Janthina
spp. have been observed directly on Velella, and it has
been hypothesized that Janthina use Velella to settle
on and use the Velella as floatation until they become
too large for the host (Bayer, 1963). This behavior may
be a reason why whole Janthina and Velella were often
found together in stomach samples. Janthina spp. had
been previously noted as a prey item of loggerhead sea
turtles in the Azores and South Africa (Dodd, 1988)
but was first identified as a prey item in the Pacific
Ocean in a preliminary unpublished report by Cooke in
19922 — data that are included in the present study. The
high frequency of occurrence of Velella velella and whole
Janthina spp. support the hypothesis that loggerhead
sea turtles will feed on the surface, swallowing their
prey whole. Distribution of Velella velella is patchy; den-
sities range from <1/1000 m3 to 1000/1000 m3 and den-
sities of Janthina spp. are considerably less than those
of Velella. When optimum combinations of prevailing
winds and currents converge, densities of Velella velella
have been observed to be in concentrations upward of
10,000/1000 m'-, forming patches so large and dense
they have been likened to oil tanker sludge by mariners
(Evans, 1986; Parker, personal observ.). It is possible
that the one turtle that had a stomach volume of 84%
Velella found one of these patches on which to feed.
Velella velella was the one common prey item that was
not found in stomachs of turtles less than 30-cm CCL.
Because Velella were commonly swallowed whole, it is
possible that an average size Velella, which range from
5 to 10 cm (Evans, 1986), might have been too large for
a 13-29 cm CCL turtle to swallow whole.
The epibiotic oceanic crabs and the gooseneck bar-
nacles (Lepas spp.) usually occur on floating objects;
Planes sometimes even rides on Velella (Chace, 1951).
Planes spp. also have been observed and collected from
the tail area of loggerhead sea turtle themselves (Dav-
enport, 1994; NMFS observers3). Although approximate-
ly 80% of stomach samples with Planes spp. contained
whole crabs, which were identified as P. cyaneus, there
2 Cooke, W. J. 1992. A taxonomic analysis of stomach contents
from loggerhead turtles (Caretta caretta ). AECOS report no.
697, 12 p. Prepared for NOAA, NMFS, Honolulu Laboratory,
2570 Dole Street, Honolulu, Hawaii 96822. (Available from
AECOS, Inc., 45-939 Kamehameha Hwy., Rm. 104, Kaneohe,
Hawaii 96744.]
:) NMFS (National Marine Fisheries Service) observers. 1997-
2000. Personal commun. Pacific Islands Fisheries Science
Center. 2570 Dole Street, Honolulu, HI 96822-2396.
were also numerous masticated crabs and pieces of
crabs. These pieces could have been P. marinus because
whole specimens are necessary to identify Planes spp.
(Spivak and Bas, 1999); therefore the lowest taxonomic
identification for this study was limited to Planes spp.
Densities of Planes spp. and Lepas spp. are not well
documented but are likely limited by the amount of
substrate on which they can settle or on the amount of
floating objects available. Natural drifting objects such
as tree logs or pumice from volcanic eruptions have
been documented since the nineteenth century (Kew,
1893, cited in Jokiel, 1990). The "floating islands," as
they have been called, continue to be important for
transporting organisms, from corals to reef fish across
the oceans (Jokiel, 1990). Man-made objects also sup-
ply substrate and habitat on which different organisms
can settle. Buoys and logs that wash ashore often have
Lepas spp. attached to them, some with Lepas spp. cov-
ering 100% of the area that was underwater (Parker,
personal observ.). Although the frequency of occurrence
of Planes spp. in stomach samples was high, the percent
sample volume of Planes was relatively low (1.2% total
volume) and the mean volume of Planes found was also
low (5.6%, Table 2), indicating that this prey was either
taken opportunistically or accidentally. It is not known
whether the Planes were ingested along with other
prey items or were actually grazed from larger floating
objects. In contrast, Lepas spp. often occurred in very
high percent volumes, indicating that the turtles were
actively grazing these prey. The constant presence of
Lepas spp. in samples strongly supports the hypothesis
that loggerhead sea turtles feed not only by swallowing
prey whole, but also by biting prey off larger floating
objects. Small chunks of Styrofoam were still attached
to the bases of some Lepas specimens indicating that
the turtle had bitten off some of the floating object itself
while grazing on prey found on the floating debris.
Among other floating items that often occurred in the
turtles' stomachs, one common element was fish eggs.
Some of these fish eggs were identified as Hirundicthys
speculiger or flying fish eggs. Amphipods were another
common item but comprised a very small fraction of
total gut content (<1%), indicating that they were not a
targeted prey item. Amphipods were possibly ingested
incidentally as epiphytes on other items or as part of
the gut contents of other prey items. The proportion
of man-made drift debris in our sample was low in
contrast to prior studies (Balazs, 1985; Allen, 1992;
Bjorndal et al., 1994; Kamezaki, 1994; Tomas et al.,
2002). Plastics and other man-made debris were com-
monly found, occurring in about 35% of stomachs, but
they comprised a very small fraction of the total gut
content (<1%).
Loggerhead sea turtles also actively forage at deeper
depths if high densities of prey items are present. An
initial study of pelagic dive behavior of this species
(Polovina et al., 2003) indicates that they regularly
dive down to depths of 100 m and may also forage
at those depths, which may account for the high fre-
quency of occurrence and high total percent volume of
148
Fishery Bulletin 103(1)
the heteropod Carinaria cithara. Okutani (1961) first
recorded sea turtles consuming Carinaria (including
Carinaria cithara, Benson 1835), in the western North
Pacific. Heteropods are found in the upper photic zone
(within 100 m of the surface) but are not typically
a neustonic or floating species. Recorded heteropod
densities in the Pacific are variable (<1/1000 m3 to
150/1000 m3, Seapy, 1974, cited in Lalli and Gilmer,
1989). Although these densities seem very low, it is
clear that in this area of the central North Pacific
heteropods are numerous enough within diving depths
of loggerhead sea turtles to make this an attractive
prey item for the turtles.
Conclusion — Interactions with fisheries
The bycatch of nontargeted species in different fisher-
ies has been an issue for many years (Wetherall et al.,
1993; Wetherall, 1996; Gardner and Nichols, 2001;
Suganuma4). Bycatch of sea turtles has also been an
issue for the conservation management of most sea
turtle species. Sea turtle mortalities have occurred in
nearly all fisheries (gillnet, driftnet, trawl, and long-
line). During their transpacific migrations loggerhead
sea turtles move through areas of multinational long-
line fishing (Lewison et al., 2004). Mortalities of sea
turtles after longline fishery interactions have been
estimated between 28% and 50% by both U.S. and Japa-
nese researchers (Nishemura and Nakahigashi, 1990;
Kleiber,5 McCracken'M and loggerhead sea turtles com-
prise a large percentage of the sea turtle interactions
in longline fisheries, as high as 59% of sea turtles cap-
tured in the Hawaii-based longline fleet. The longline
fishery as well as various other fisheries in the Pacific
(Gardner and Nichols, 2001) have been implicated as
part of the reason for recent declines in the loggerhead
sea turtle populations both in Japan (Kamezaki and
Matsui, 1997; Sato et al., 1997; Suganuma4) and also
in Australia, and southern nesting areas (Limpus and
Couper, 1994; Limpus and Reimer7). Research on feed-
ing behavior may help with the mitigation of fisheries
interactions.
4 Suganuma, H. 2002. Population trends and mortality of
Japanese loggerhead turtles, Caretta caretta, in Japan. In
Proc. Western Pacific Sea Turtle Coop. Res. and Mgmt.
Workshop (I. Kinan, ed.). p. 74-77. Western Pacific Regional
Fishery Management Council, 1164 Bishop Street, Suite
1400, Honolulu, HI 96813.
5 Kleiber, P. 1998. Estimating annual takes and kills of
sea turtles by the Hawaiian longline fishery, 1991-1997,
from observer program and logbook data. Administrative
report H-98-08, 21 p. Southwest Fisheries Science Center,
Nat. Mar. Fish. Serv., NOAA, 2570 Dole St., Honolulu, HI
96822.
6 McCracken, M. L. 2000. Estimation of sea turtle take and
mortality in the Hawaiian longline fisheries. Administrative
report H-00-06, 29 p. Southwest Fisheries Science Center,
Nat. Mar. Fish. Serv., NOAA, 2570 Dole St., Honolulu. HI
96822.
Learning more about the life history of loggerhead
sea turtles and understanding more about the move-
ments, foraging behavior, and prey of these turtles
are important for making well-informed management
decisions because foraging behavior may change as
seasons change and as these turtles move through dif-
ferent habitats (Bjorndal, 1997). Although our study
indicates that these turtles forage mainly on floating
or near-surface prey in the open ocean, studies in dif-
ferent areas show different feeding habits. The oceanic,
near-surface feeding behavior of loggerhead sea turtles
is likely one reason for the numerous longline fishery
interactions in the central North Pacific. The recorded
dive data for these turtles indicate that they spend a
large percentage of their time near the surface — as
much as 78% of their time is spent within 10 m of the
surface (Polovina et al., 2003b). Juvenile loggerhead sea
turtles are rarely found in the waters adjacent to Japan
(Uchida, 1973); the juvenile turtles are thought to use
the Kuroshiro Current to move out into the Pacific and
the southern edge of the Subartic Gyre during their
eastward movement toward foraging grounds in the
Eastern Pacific (Bowen et al., 1995). In the Atlantic,
however, small neonate loggerhead sea turtles have
been found associated with drifts of floating material,
especially Sargassum rafts (Witherington, 2002), and
although large, regular drifts of floating material are
rare in the Pacific, small loggerhead sea turtles may
also be associated with floatsam (Pitman, 1990).
Studies have indicated that foraging changes through-
out the lifecycle of loggerhead sea turtles (van Nierop
and den Hartog, 1984; Plotkin et al., 1993; Godley et
al., 1997; Tomas et al., 2001). In the Pacific, oceanic
immature turtles (present study) forage on different
prey from that foraged by subadults in the pelagic and
neritic areas off Baja California (Nichols et al., 2000;
Peckham and Nichols, 2003; Seminoff et al., 2004),
and adults in benthic neritic habitats, in turn, forage
on different prey near Japan and China (Hitase et al.,
2002). Japanese loggerhead sea turtles foraging in the
Eastern Pacific target Pleuroncodes planipes, the pelagic
red crab, which occurs year round off Baja California.
These turtles interact with the artisanal fisheries in
the area which are both pelagic and benthic fisheries
(Gomez-Gutierrez and Sanchez-Ortiz, 1997; Bartlett,
1998; Gomez-Gutierrez et al., 2000; Peckham and Nich-
ols, 2003). Loggerhead sea turtles have also been found
on the Gulf of California side of Baja California, likely
foraging on the large abundance of invertebrate fauna
found there (Brusca, 1980), and these turtles face fish-
ing pressure from the artisanal gillnet fishery in this
area (Seminoff et al., 2004).
7 Limpus, C. J., and D. Reimer. 1994. The loggerhead turtle,
Caretta caretta, in Queensland: a population in decline. In
Proceedings of the Australian marine turtle conservation
workshop iR. James, compiler), p. 39-59. Queensland Dep.
Environ and Heritage and Aust. Nat. Conserv. Agency, GPO
Box 787, Canberra ACT 2601, Australia.
Parker et al .: Diet of Caretto caretta in the central North Pacific
149
Converting CCL to straight carapace length (SCL;
using the conversion equation: CCL=1.388+(1.053) SCL,
in Bjorndal et al., 2000), size classes found in our study
ranged from 11.5 cm to 68.9 cm SCL with a mean of
41.2 [±12.4] cm SCL. The East Pacific recruits were
slightly larger with means of 46.9-61.9 cm SCL (Semi-
noff et al., 2004). Most of these turtles were immature
to subadult turtles, and only a few were adult-size tur-
tles. According to Zug et al. (1995), the loggerhead sea
turtles recruiting to the nearshore and neritic habitats
of Baja California are likely 10 years of age or older,
indicating that these turtles might spend as many as
10 years before arriving at their East Pacific foraging
habitat. After returning to the West Pacific, satellite
telemetry has found that adult loggerhead sea turtles
also reside in both neritic and pelagic habitats (Baba
et al., 1992, 1993; Kamezaki et al., 1997; Sakamoto
et al., 1997) putting them at risk of interaction with
nearshore gillnet fisheries as well as pelagic longline
fisheries. Hitase et al. (2002) found a size difference
between adults in neritic and oceanic habitats — the
postnesting females that chose oceanic habitats were
smaller (mainly <80.0 cm) than those that used neritic
habitats for postnesting foraging — and also suggested
that some adult turtles may not recruit to neritic areas
near Japan and China. This may be evidence that some
loggerhead sea turtles remain in the oceanic habitat
their whole life cycle, returning nearshore only to mate
or nest. In the Atlantic, juveniles as well as adults of
this species can be found in neritic foraging habitats of
the Gulf of Mexico, and these turtles can have interac-
tions with coastal trawl and other coastal fisheries in
the area (Plotkin et al., 1993). Juvenile turtles have
also been observed and captured in areas along the
eastern coast of the United States where they have
been found feeding on benthic invertebrates (Burke et
al., 1990; Epperly et al., 1990). Very small, neonate
loggerhead sea turtles have been found associating
with and foraging in Sargassum drifts while they are
transported by the Gulf Stream into the mid-Atlantic
(Witherington, 2002); therefore, the harvest of Sargas-
sum or trawling through this area would affect these
juveniles. There is some evidence that juvenile Atlantic
loggerhead sea turtles may move between coastal and
pelagic forage habitats, which would expose them to
both coastal and pelagic fisheries (Witzell, 2002). In
the Mediterranean, both juvenile and adult loggerhead
sea turtles also have variety of foraging behaviors. In
the eastern Mediterranean, postpelagic juveniles and
adults forage mainly in neritic habitats on benthic prey
items where they would interact with coastal trawl and
other artesianal fisheries (Godley et al., 1997). In the
western Mediterranean, juvenile turtles of this species
forage in both pelagic as well as neritic habitats, where
they are at risk of fishery interactions in many differ-
ent fisheries including longline, trawling, and coastal
fisheries (Tomas et al., 2001). Postpelagic juveniles in
the Mediterranean may be recruits from the Atlantic
Ocean or may come from the endemic Mediterranean
population. Adult loggerhead sea turtles have been
noted to also move between the eastern and western
basins of the Mediterranean in response to seasonal
temperature changes (Bentivegna, 2002). During this
migration between two benthic feeding areas, some
of the turtles would spend extensive amounts of time
in the pelagic habitat likely foraging on pelagic prey
items. This intra-Mediterranean movement puts these
turtles at risk of interactions with a multinational
fishery contingent of pelagic as well as coastal fisheries
(Bentivegna, 2002).
One possible way to mitigate increased fisheries in-
teractions in the Pacific and other areas might be to
identify specific loggerhead foraging areas for protec-
tion, such as the area around Baja California, Mexico.
In the central North Pacific, our study (Fig. 1), as well
as recent satellite tracking studies of juvenile and adult
loggerhead sea turtles (Hitase et al., 2002; Parker et
al., 2003; Polovina et al., 2004), has indicated that
the area west of and around the Emperor seamounts,
between 160° and 180°E might also be an important
foraging habitat. Most of the turtles in our study were
collected from this area (Fig. 1) and one juvenile spent
10 months west of the Emperor Seamounts, between
160° and 170°E, before its satellite transmitter stopped
transmitting data (Parker et al., 2003). In this area,
the southern edge of the Kuroshiro Extension Current
forms numerous eddies that are semipermanent fea-
tures throughout the year. Reduction of fishing effort
or other fishery mitigation techniques in this area may
greatly decrease the number of fisheries interactions
that Pacific loggerhead sea turtles experience. Interna-
tional cooperation is needed in order to manage these
foraging habitats. More studies also need to be done
on the ecology of these turtles so that fishery interac-
tions at all life stages can be addressed and so that a
total picture of the life history of this species can be
obtained.
Acknowledgments
We would like to acknowledge the hard work of all the
NMFS fishery observers for obtaining the samples, Russ
Miya and Bryan Winton for their help in the initial
sorting, and Mike Seki and Kevin Landgraf for their
help in identifying prey items. We would also like to
acknowledge the review and comments of Alan Bolten,
Jeffrey Seminoff, George Antonelis, Jerry Wetherall,
Colin Limpus, Judith Kendig, Francine Fiust, Shawn
Murakawa, and two anonymous reviewers.
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1973. Pacific loggerhead turtle — pursuing its mysterious
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1986. Sternoptychidae. In Smith's sea fishes (M. M.
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1996. Assessing impacts of Hawaiian longline fishing
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dental take in the Hawaii-based pelagic longline fishery
(A. Bolten, J. A. Wetherall, G. H. Balazs, and S. G.
Pooley, comps.), p. 57-75. NOAA Tech. Memo. NMFS-
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1993. Bycatch of marine turtles in North Pacific high-
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519-538. Int. N. Pac. Fish. Comm., Vancouver, Canada.
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2002. Ecology of neonate loggerhead turtles inhabiting
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Witzell, W. N.
2002. Immature Atlantic loggerhead turtles (Caretta
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Van Nierop, M. M., and J. C. den Hartog.
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153
Abstract — Two examples of indirect
validation are described for age-read-
ing methods of Pacific cod [Gadus
macrocephalus). Aging criteria that
exclude faint translucent zones
(checks) in counts of annuli and cri-
teria that include faint zones were
both tested. Otoliths from marked
and recaptured fish were used to
back-calculate the length of each
fish at the time of its release by
using measurements of the area of
annuli. Estimated fish size at time
of release and actual observed fish
size were similar, supporting the
assumption that translucent zones
are laid down on an annual basis. A
second method for validating read-
ing criteria used otolith age and von
Bertalanffy parameters, estimated
from the tagging data, to predict
how much each fish grew in length
after tagging. We found that otolith
aging criteria applied to otoliths from
tagged and recovered Pacific cod pre-
dicted quite accurately the growth
increments that we observed in these
specimens. These results provide fur-
ther evidence that the current aging
criteria are not underestimating the
age of the fish and support our cur-
rent interpretation of checks (i.e., as
subannual marks). We expect these
indirect validations to advance age
determination for Pacific cod, which
in turn would enhance development
of stock assessment methods based
on age structure for this species in
the eastern Bering Sea.
Indirect validation of the age-reading method
for Pacific cod (Gadus macrocephalus)
using otoliths from marked and recaptured fish
Nancy E. Roberson
Daniel K. Kimura
National Marine Fisheries Service, NOAA
Alaska Fisheries Science Center
7600 Sand Point Way, NE
Seattle, Washington 98115
E-mail address (for N E Roberson): Nancy Roberson (a1 noaa gov
Donald R. Gunderson
University ol Washington
School of Aquatic and Fishery Sciences
1122 NE. Boat Street
Seattle, Washington 98105
Allen M. Shimada
National Marine Fisheries Service, NOAA
Office of Research
1315 East- West Hwy
Silver Spring, Maryland 20910 3282
Manuscript submitted 7 November 2002
to the Scientific Editor's Office.
Manuscript approved for publication
20 September 2004 by the Scientific Editor.
Fish. Bull. 103:153-160 (2005).
Pacific cod (Gadus macrocephalus
Tilesius, 1810) is an important spe-
cies in eastern Bering Sea commercial
fisheries and is second only to walleye
pollock (Theragra chalcogramma) in
landings (Thompson and Dorn1). It is
also considered to be one of the most
difficult of all commercially impor-
tant Alaska groundfish species to age.
Scientists from both Canada and the
United States have experienced simi-
lar difficulties in finding an appro-
priate aging structure, which can
be consistently interpreted to track
large year classes of cod through time.
Historically, scales and otoliths have
been the two most common struc-
tures used for determining the ages
of fish species. Unfortunately, age-
readers employing these structures
have experienced limited success in
the case of Pacific cod (Kimura and
Lyons, 1990).
The Pacific Biological Station in
Canada stopped aging Pacific cod
in 1978, after age estimates derived
from scale readings began yielding
year classes that were inconsistent
with length-frequency time series
from field surveys (Westrheim and
Shaw, 1982). The Alaska Fisheries
Science Center's (AFSC) Resource
Ecology and Fisheries Management
(REFM) Division is responsible for
stock assessment of Pacific cod in the
Gulf of Alaska and eastern Bering
Sea. The REFM Division's Age and
Growth Program used scales for de-
termining the age of Pacific cod from
1976 to the early 1980s. Thereafter,
the program used the break-and-burn
method with otoliths to age Pacific
Thompson, G. G., and M. W. Dorn.
1999. Pacific cod. In Stock assessment
and fishery evaluation report for the
groundfish resources for the Bering Sea/
Aleutian Islands regions (plan team for
groundfish fisheries of the Bering Sea/
Aleutian Islands), p. 151-205. North
Pacific Fishery Management Council,
605 W. 4th Avenue Suite 306, Anchor-
age, AK 99501.
154
Fishery Bulletin 103(1)
cod (Thompson and Methot2). In the otoliths of young
Pacific cod (under 6 years), there is a tendency for sub-
annual marks (also known as "checks") to be very dark
and evenly spaced, making them difficult to distinguish
from annuli. This confusion makes it difficult to age the
species to an exact age.
From 1990 through 1992, the AFSC noticed that the
average length at a specific age was smaller than it
had been in previous years. The decrease was noticed
in ages 1-6 but was especially dramatic in 1-, 2-, and
3-year-olds. It is generally theorized that the shift was
the result of one of two scenarios: either the fish popu-
lation experienced an actual decrease in length-at-age
or the age readers were over-aging fish by counting
marks other than annuli. Unable to pinpoint the reason
for the shift and given the inherent difficulty of aging
cod, production (large-scale) aging of Pacific cod was
indefinitely suspended at the AFSC.
Pacific cod stock assessments in Alaska have since
depended largely on length-frequency data alone to
model population age structure because of the difficul-
ties in obtaining age estimates (Thompson and Dorn1).
However, the use of length-frequency data as proxies for
age data can be problematic. If external factors such as
ocean conditions affect somatic growth to such a degree
that length-at-age within the population is highly vari-
able, such as appears to be the case for Pacific cod, then
the population becomes difficult to model. Otoliths, on
the other hand, are permanent records of growth that
are more independent of external factors.
Consequently, the Age and Growth Program initiated
a new study in 1998 to re-examine the otolith aging
structure for Pacific cod. This study used otoliths from
tagged Alaska Pacific cod to validate aging criteria for
otoliths.
Methods
Otoliths and length data were collected during a tag-
ging study conducted by the AFSC. Between 1982 and
1990, 12,396 Pacific cod were tagged and released in the
eastern Bering Sea during summer bottom-trawl surveys
(See Shimada and Kimura, 1994). Fish were measured
to the nearest 0.5 cm fork length, tagged with uniquely
marked spaghetti tags, and set free. Over a period of
13 years, commercial fishing vessels recaptured 375
(3%) of the tagged fish and returned otoliths from 112
fish (106 of which were usable) (Table 1). More details
on the tagging methods can be found in Shimada and
Kimura (1994).
2 Thompson, G. G., and R. D. Methot. 1993. Pacific cod.
In Stock assessment and fishery evaluation report for the
groundfish resources for the Bering Sea/Aleutian Islands
regions as projected for 1994 (plan team for groundfish fish-
eries of the Bering Sea/Aleutian Islands), p. 2-28. North
Pacific Fishery Management Council, 605 W. 4lh Avenue
Suite 306, Anchorage, AK 99501.
Otolith preparation
One sagittal otolith from each recaptured fish was
selected for our study. We did not discriminate between
left and right otoliths based on the results of Sakurai
and Hukuda (1984) who were unable to detect any con-
sistent differences between the weight and length of
right and left Pacific cod otoliths.
Each otolith was cleaned and preserved in 95% etha-
nol. After having been preserved for approximately one
month, a line was penciled across the otolith center
from the dorsal apex to the ventral apex to ensure that
the otoliths would later be sectioned at the core.
The otolith was then placed in a polyester mold and
set in black resin (Technovit 3040, Energy Beam Sci-
ences, Agawam, MA), forming a block of resin. A slow-
speed saw was used to cut the blocks in half. This pro-
duced two smaller blocks, each with an exposed view
of the otolith in the transverse plane and cut through
the center. One of the two blocks was selected and
glued (otolith side down) to a glass slide. The glass
slide was mounted to a Hillquist thin section machine
(Hillquist Inc., Fall City, WA) and the section was
ground down to a thickness of 0.25 mm. A coverslip
was permanently glued on the top of the section with
marine-grade epoxy.
Sections were placed on a piece of black velvet (which
added contrast) on the stage of a 50x dissecting micro-
scope, and reflected light was used for illumination.
The sections were viewed on a computer monitor by
using a Cohu 6500 monochrome video camera, Integral
Flashpoint 128 frame grabber and Optimas 6.5 imaging
software (Media Cybernetics, Silver Spring, MD).
Age-reading criteria
Traditional qualitative aging criteria were used to distin-
guish annuli from checks. The criterion for identification
as an annulus was a continuous translucent band that
could be seen along the entire structure or as a ridge or
groove on the structure (Secor et al., 1995). Checks (i.e.,
subannual marks) are translucent zones that appear
very similar to annuli. They were determined primarily
by the incompleteness of the zone around the entire sec-
tion, by zone darkness, and by spacing between zones.
When translucent zones could be classified as either
annuli or additional subannular marks, they were clas-
sified as checks. Annuli, checks, and edges (the space
between the last annulus and the edge of the otolith)
were traced by using the Optimas 6.5 software package
and measurements of their areas and major axis lengths
were collected (Fig. 1). All otoliths were read blind; that
is, information about fish length and date of capture
(Table 1) was withheld from the reader to prevent bias.
When all the otoliths had been aged and measured,
the age reader returned to each otolith section to es-
timate the area and length of the otolith when the
fish was tagged. This was accomplished by following a
two-step process. The first step was to approximate the
location of the otolith cross-section that corresponded to
Roberson et al .: Indirect validation of the age-reading method for Gadus macrocephalus
155
Table 1
Mark and recapture data for spaghetti-tagged Pacific cod [Gadus macrocephalus). L, = fork length at tagging (mm), L., = fork
length at recapture (mm), </, = time at liberty (months), a1 = age estimated from Ll and dv a2 = age at recapture estimated by
using the fish's otolith and age-reading criteria, and NR = not reported.
h
L,
d,
ai
a 2
at-a2
^i
L,
rfi
ai
a2
dj-a.
430
480
9
4
3
1
625
550
3
6.5
5
1.5
680
875
21
8
7
1
740
850
26
8
8
0
690
830
30
8
8
0
650
670
4
6
7
-1
590
500
4
6
7
-1
525
550
5
5
4
1
530
690
30
7
7
0
645
720
9
7
6
1
430
500
10
4
4
0
835
890
14
7
8
-1
600
620
8
6
7
-1
560
600
5
5
4
1
390
490
11
3.5
3
0.5
645
830
38
9
8
1
630
660
5
6.5
4
2.5
405
412
4
3.5
2
1.5
670
750
9
7
8
-1
460
550
8
4
3
1
630
850
49
9.5
10
-0.5
735
760
1
6
7
-1
590
650
7
6
6
0
620
650
1
5
6
-1
450
570
25
5
6
-1
545
550
4
4
6
-2
630
660
7
6.5
6
0.5
555
560
2
4
5
-1
440
525
14
4.5
5
-0.5
680
730
19
7.5
6
1.5
705
890
35
9
8
1
640
680
4
6.5
4
2.5
556
680
25
6
8
-2
730
730
6
7
7
0
480
540
7
5.5
3
2.5
540
655
12
5
5
0
620
660
2
5
9
-4
600
720
14
6
6
0
630
730
17
7
8
-1
540
700
17
5
6
-1
600
730
44
8.5
7
1.5
530
920
50
8
9
-1
630
623
1
5.5
6
-0.5
610
691
16
6
8
-2
702
760
11
7
8
-1
690
800
10
7
5
2
330
530
22
4
3
1
555
630
7
5
6
-1
540
706
20
6
5
1
790
NR
21
8
7
1
390
578
22
4.5
4
0.5
560
630
8
5
5
0
670
710
4
6
9
-3
520
550
2
4
4
0
820
825
2
6
8
-2
535
NR
18
5.5
6
-0.5
690
710
8
7
8
-1
460
530
7
4
3
1
725
850
17
7.5
6
1.5
590
930
93
12.5
15
-2.5
530
590
9
5
5
0
690
742
5
6.5
6
0.5
660
690
3
6
7
-1
720
770
8
7
9
-2
580
770
57
9.5
10
-0.5
870
924
7
7
8
-1
450
695
25
5
5
0
520
523
7
5
3
2
815
860
10
7
8
-1
470
530
6
4.5
3
1.5
540
670
22
6
7
-1
630
740
13
6.5
7
-0.5
740
670
7
7
6
1
510
630
13
5
6
-1
670
705
2
6
8
-2
650
720
13
7
6
1
650
640
0
6
7
-1
570
675
20
6
8
-2
710
860
19
8
7
1
690
660
20
7.5
8
-0.5
670
810
20
8
7
1
660
760
23
8
8
0
780
770
1
6
8
-2
690
750
7
7
7
0
810
850
7
7
8
-1
560
630
8
5
5
0
485
640
21
5.5
6
-0.5
530
700
7
5
7
-2
305
850
39
4.5
8
-3.5
600
620
10
5.5
4
1.5
695
710
9
7
6
1
595
970
50
8.5
9
-0.5
610
810
30
8
6
2
520
910
32
6.5
7
-0.5
660
820
30
9
7
2
540
800
30
6
7
-1
610
725
26
7
7
0
820
830
2
6
6
0
580
720
30
7.5
7
0.5
585
782
34
7.5
6
1.5
530
830
33
7
6
1
680
790
9
7
6
1
600
760
17
7
6
1
676
1080
70
11.5
11
0.5
515
730
26
6
5
1
585
590
0
4.5
5
-0.5
156
Fishery Bulletin 103(1)
Figure 1
Transverse cross-section of a Pacific cod (Gadus macrocephalus) otolith with an unusually clear
annulus pattern. The otolith was taken from a 830-mm, 8-year-old fish that was recaptured 30
months after tagging. Annuli (black dots), checks, and edges (the space between the last annulus
and edge [white dot]) were traced and measurements of their areas (from the center of the oto-
lith to the outer margin of the translucent zone [dotted line]) and major axis lengths (from the
smallest rectangular box that will hold the translucent zone) were collected. T is the estimated
otolith size (length and area) at the time of tagging and was used to back-calculate fish length
at tagging. W corresponds to the annulus preceding T.
the time of tagging. The second step was calculating the
area and length of that region, producing an estimated
otolith size at the time of tagging
First, to approximate the location of the otolith that
corresponded to the time of tagging required the reader
to know how long (years) the fish had been at liberty,
after tagging. Using this knowledge and starting from
the last annulus before the edge, the reader counted
towards the center of the otolith, the number of years
(as represented by annuli) that the fish had been at
liberty. (In cases where the fish had been at liberty for
less than one year before being caught again, the reader
began at the edge rather than at the last annulus before
the edge). Assuming that all annuli are laid down by
late winter, the reader would end up on the annulus
that preceded the summer of tagging. This annulus
represents the size of the otolith just prior to tagging
and for sake of further explanation, its area and length
will be identified as W (Fig. 1). To complete the proce-
dure, the reader needed only to measure the summer
increment which followed W, divide it in half and add
it to W. These calculations were assumed to reflect the
size of the fish's otolith at time of tagging and were
used as Of values (the size of the otolith at tagging) to
back-calculate fish size at initial capture.
Estimating fish length by using tagged fish and
back-calculations
Annuli on tagged fish otoliths can be used to estimate
the length of each fish at an earlier age. Smedstad
and Holm (1996) compared six different back-calcula-
tion formulae on tagged Atlantic cod (Gadus morhua)
and found that the age-independent, nonlinear, body
proportional (nbp) hypothesis worked the best. Pacific
cod is a gadid closely related to the Atlantic cod; there-
fore we also used the nonlinear, body proportional
formula
L^iOJOJL,
where Lt = the predicted fish length at tagging or de-
sired age;
O, = the size (either radius or area) of otolith at
tagging;
Or = the size of otolith at time of recapture;
v = the slope from the regression of Ln(L) on
Ln(O); and
Lc = the fish length at recapture.
This analysis was performed by using two different mea-
sures of otolith size, the cross-sectional area and major
axis (i.e., length) of otolith increments (Fig. 1).
Estimating growth increments in fish length
from tagged fish
We can use tagged fish otolith ages to estimate how
much each fish grew in length after tagging, in a manner
similar to Fabens' equation (Ricker, 1975), using the von
Roberson et al.: Indirect validation of the age-reading method for Gadus macrocephalus
157
Table 2
Results of regressing Ln fish length on Ln otolith area and Ln fish length
mi
Ln otolith major axis
by using tagged fish data.
Fish length was measured in mm, otolith area in mm'2, and otolith major axis in mm, rc=96.
Coefficients
Standard error
t stat
P-value
Regression of Ln Fish length on Ln Otolith area
Intercept 4.637299
0.117551
39.44929
2.75E-60
Slope (v) 0.65732
0.040471
16.24168
4.96E-29
Regression of Ln Fish length on Ln Otolith major axis
Intercept 4.27009
0.229693
18.5904
3.01E-33
Slope (v) 1.012865
0.102305
9.900426
2.99E-16
Bertalanffy equation (Ricker, 1975). However, because
we could estimate the age of fish at time of recapture,
we were able to manipulate the von Bertalanffy equation
to obtain the following equation:
4-A = A„,n
[(■
-KicL,-d-t„
-iV— > )],
where Lx = length at tagging;
L2 = length at recapture;
Linf = maximum size;
K = growth rate;
a2 = estimated age at recovery determined from
our otolith ages;
d = time at liberty; and
r0 = age at length 0 mm.
Given von Bertalanffy parameters and age at recovery,
a (fish) length increment for time after tagging can be
predicted. Using published Lln{ and K estimates from
tagging data, Linf= 1043 mm, K = 0.222 (Kimura et
al., 1993), we estimated L2-Lv One weakness in these
estimates is that the growth parameters estimated by
Kimura et al. (1993) were based on only positive growth
increments (there were some instances where recaptured
fish were smaller than they were at tagging, demonstrat-
ing negative growth increments).
A value for t0 was estimated iteratively in the von
Bertalanffy equation by using the subroutine Solver
(Frontline Systems Inc., Incline Village, NE) from the
Excel software package with the following parameter
values: K = 0.222, t = 1 year old, Llnf= 1043 mm (Kimu-
ra et al., 1993), /, = length at age one = 180 mm (from
the 1977 year class [Foucher et al., 1984]). Because
these von Bertalanffy parameters are not based on
age determination, they provide an indirect method for
validating aging criteria. In addition, ages determined
by readers were scaled smaller (by 0.75) and larger (by
1.25) in order to simulate the results of younger and
older aging criteria. Plots of observed and predicted
growth increments should agree if the aging criteria
for a2 reflect the true age of fish.
E
c
.2
2.5 3
Ln Otolith area (mm2)
Figure 2
Relationship between Ln fish length and Ln otolith area
based on tagged and recaptured Pacific cod (r2 = 0.735,
y=4.6+0.66X, n = 96).
Results
Predicting fish length from tagged fish and
back-calculations
The parameter v used in all back-calculations in our
study was estimated by using otolith area and again by
using the major axis of the otolith (Fig. 1). Based on the
slopes from the regression of Ln fish length on Ln otolith
size (Table 2, [Fig. 2]), the coefficients should be v=1.01
for otolith length and v=0.66 for otolith areas.
Back-calculations were performed by using the otolith
area and were repeated by using the major axis. Scatter
plots of estimated and observed fish lengths were used
to visually inspect how well back-calculation determines
fish length (Fig. 3). Assuming that the residuals of the
back-calculated length at tagging have independent
chi-square distributions, an F-test indicates that back-
calculations derived from otolith areas are significantly
more accurate than back-calculations derived from the
major axis (P<0.05). However, because we used the two
158
Fishery Bulletin 103(1)
different methods on the same otoliths, the residuals
were correlated and thus this result can be considered
only approximate.
Predicting growth increments of fish length from
tagged fish
Using the von Bertalanffy curve fitted with the data
from the tagged fish sample, we estimated the value of
t0 to be 0.147.
1000 -i
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jf*
800-
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ra
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Back-calculated lengths at tagging (mm)
Figure 3
Fish length at tagging was back-calculated from estimated otolith
size at tagging and time at liberty. Two separate back-calculations
were performed, each with a different measure of the otolith size
at tagging: one using (A) the area; the other using (B) the major
axis.
The amount that each tagged fish grew after tagging
was calculated three times by using fish age at recovery
and the von Bertalanffy equation (Fig. 4). The calcu-
lated sums of squared deviations for the three sets of
predicted values are as follows: 433,955 when fish age
is scaled by 0.75, 419,477 when fish age is scaled by 1.0,
and 761,545 when fish age is scaled by 1.25. The lowest
sum of squared deviations accompanied ages that were
scaled by 0.86. Assuming that the residuals of the esti-
mated growth increments have independent chi-square
distributions, an F-test indicates that residu-
als were significantly larger (P<0.05) when
ages were scaled 25% older and there was
no significant difference (P<0.05) between
reader-determined ages and ages scaled 25%
younger. The three sets of residuals came
from the same otoliths and would be corre-
lated; therefore, this result can be considered
only approximate.
Another test of our reading criteria was
performed through a more direct compari-
son: simply "aging" the tagged fish from esti-
mated age at tagging (based on length), plus
the time after tagging (Table 1). Out of 106
samples, 75% of these fish were within one
year of the age that we had determined from
otolith readings, and 94% were within two
years. The average percent error (Beamish
and Fournier, 1981) was 8.70, and the aver-
age deviation from tagged-based age was
-0.075. Results of a Z-test indicated that
the average deviation was not significantly
different from zero (P= 0.724) and indicated
no bias in the age estimates.
Discussion
Beamish and McFarlane (1983) noted that
"validating a method of age determination is
as important in fishery biology as standard-
izing solutions or calibrating instruments are
in other sciences." Age determination must
reflect the actual age of each fish in order to
be a useful tool for use in stock assessments.
Although much effort has been devoted in the
past to finding an appropriate aging struc-
ture for Pacific cod, particularly with dorsal
fin rays (Beamish, 1981; Lai et al., 1987;
Kimura and Lyons, 1990), scales and otoliths
(Lai et al., 1987; Kimura and Lyons, 1990), a
directly validated method of age determina-
tion has yet to be found ( Westrheim, 1996).
The otolith seems to be the most promising
structure for production (large-scale) age
reading of Pacific cod (Kimura and Lyons,
1990); however it is not without weaknesses
(i.e., the faint patterns of some translucent
zones can lead to low precision between read-
ers and are a constant concern in regard to
Roberson et al Indirect validation of the age-reading method for Gadus macrocephalus
159
under- or overestimated ages). The key difficulty of the
cod otolith patterns is differentiating the translucent
zones that are annual from the translucent zones that
are checks, particularly in young fish. It is necessary to
have validated criteria in order to confidently eliminate
checks without under-aging the fish. In our study, we
have given two examples of indirect validation for Pacific
cod age determination by using otoliths from marked
and recaptured fish.
In the first example, we used back-calculations to test
our reading criteria, which exclude counting lighter
translucent zones. Early in the study, we found a strong
relationship between otolith size and fish length, which
supported using back-calculations as a vehicle to test
accuracy. Overall, using strong translucent zones to
back-calculate fish length at tagging gave fairly accu-
rate results. This finding supports the assumption that
translucent zones are laid down on an annual basis.
An ancillary finding was that otolith area measure-
ments provided more accurate estimates of fish length
than otolith lengths. Although back-calculations are
typically performed by using radial or diametral mea-
surement, the more accurate estimates of fish length
from otolith area measurements are not surprising in
that otolith area is a more comprehensive measure of
otolith three-dimensional growth.
A second indirect validation of reading criteria was
possible by estimating how much each tagged fish grew
(millimeters) between tagging and recapture by its
estimated age at recovery and von Bertalanffy growth
parameters (derived only from tagging data). When
compared to the observed growth increments, we found
that the results support our proposed aging criteria
(which exclude lighter translucent zones) because these
criteria give the best fit to growth increments based on
the mark-recapture growth increments. Aging the fish
older (by counting light translucent zones) or younger
(counting less annuli by banding translucent zones to-
gether) increases the residual fit to the mark-recapture
growth increments. Large growth increments of fish
length were difficult to estimate (Fig. 4). A possible
explanation is that the longer a fish remains at liberty,
the more likely that the growth becomes asymptotic,
making the relationship between the growth increment
and time at liberty less exact.
The final test for reading criteria was performed
through a more direct comparison: simply "aging" the
tagged fish by its length-at-release plus its time at
liberty after tagging and comparing that age to the
otolith-based age at recovery. Dwyer et al. (2003) also
used this method in their study of yellowtail flounder
(Limanda ferruginea). Average deviation from tag-based
age was -0.075; 75% of these fish were found to be
within one year of our age according to otolith readings,
and 94% were within two years. These results provide
further evidence that the current criteria do not result
in the underestimation of the age of the fish and sup-
port the practice of not counting checks.
We found that growth information residing in oto-
liths from tagged and recovered Pacific cod provided
200 400
600
600 -,
400
™ 200-
200 400
600
600
400
200
0 200 400 600
Observed growth Increments (mm)
Figure 4
Three plots comparing predicted and observed
fish-length growth increments by using recap-
tured fish from tagging experiments (n = 97).
Estimated ages at recovery (B) were scaled 25%
smaller (A) and 25% larger (C). The lines indi-
cate theoretical 1:1 line of perfect agreement.
significant information applicable to indirectly validat-
ing otolith aging criteria. Therefore, it seems that oto-
liths from other species that were tagged and recovered
might be useful for indirect age validation as well. The
160
Fishery Bulletin 103(1)
information provided in our study indicates that our
aging criteria for Pacific cod are roughly correct and
that errors are probably within plus or minus 1 or 2
years. However, the problem of the shift in length at
age alluded to in the introduction is more difficult to
elucidate. Analysis made during this study seems to
indicate that both environmental growth factors and
changes in otolith aging criteria could have played a
role in this apparent shift.
Acknowledgments
This work was performed in partial fulfillment of the
requirements for an M.S. degree at the School of Aquatic
and Fishery Sciences at the University of Washington
and was supported by the National Marine Fisheries
Service. We would like to express our appreciation to
those individuals who assisted in the tagging and recap-
ture process and to the two anonymous reviewers for
their helpful comments on the manuscript.
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1981. Use of sections of fin-rays to age walleye pol-
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method. Trans. Am. Fish. Soc. 110:287-299.
Beamish, R. J., and D. A. Fournier.
1981. A method for comparing the precision of a set of
age determinations. Can. J. Fish. Aquat. Sci. 38:982-
983.
Beamish, R. J., and G. A. McFarlane.
1983. The forgotten requirement for age validation in
fisheries biology. Trans. Am. Fish. Soc. 112:735
Dwyer, K. S., S. J. Walsh, and S. E. Campana.
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Foucher, R. P., R. G. Bakkala, and D. Fournier.
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frequency analysis and scale reading for Pacific cod in
the North Pacific Ocean. Int. North Pac. Fish. Comm.
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Kimura, D. K., and J. J. Lyons.
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Kimura, D. K., A. M. Shimada, and S. A. Lowe.
1990. Estimating von Bertalanffy growth parameter of
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macrocephalus) using tag-recapture data. Fish. Bull.
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Lai, H. L., D. R. Gunderson, and L. L. Loh.
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816.
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ish Columbia waters, and a comparison with Pacific cod
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Westrheim, S. J., and W. Shaw.
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161
Abstract — The northwest Atlantic
population of thorny skates (Ambly-
raja radiata) inhabits an area that
ranges from Greenland and Hudson
Bay, Canada, to South Carolina.
Despite such a wide range, very little
is known about most aspects of the
biology of this species. Recent stock
assessment studies in the northeast
United States indicate that the bio-
mass of the thorny skate is below
the threshold levels mandated by the
Sustainable Fisheries Act. In order
to gain insight into the life history
of this skate, we estimated age and
growth for thorny skates, using verte-
bral band counts from 224 individuals
ranging in size from 29 to 105 cm
total length (TL). Age bias plots and
the coefficient of variation indicated
that our aging method represents a
nonbiased and precise approach for
the age assessment of A. radiata. Mar-
ginal increments were significantly
different between months (Kruskal-
Wallis P<0.001); a distinct trend of
increasing monthly increment growth
began in August. Age-at-length data
were used to determine the von Ber-
talanffy growth parameters for this
population: Lx = 127 cm (TL) and
6 = 0.11 for males; Lr = 120 cm (TL)
and 6 = 0.13 for females. The oldest
age estimates obtained for the thorny
skate were 16 years for both males
and females, which corresponded to
total lengths of 103 cm and 105 cm,
respectively.
Age and growth estimates of the thorny skate
(Amblyraja radiata) in the western Gulf of Maine
James A. Sulikowski
Jeff Kneebone
Scott Elzey
Zoology Department, Spaulding Hall
46 College Road
University of New Hampshire
Durham, New Hampshire 03824
E mail address !for J A Sulikowski, senior author):
isulikowigihotmail.com
Joe Jurek
Yankee Fisherman's Cooperative
P.O. Box 2240
Seabrook, New Hampshire 03874
Patrick D. Danley
Department of Biology
University of Maryland
College Park, Maryland 20724
W. Huntting Howell
Zoology Department, Spaulding Hall
46 College Road
University of New Hampshire
Durham, New Hampshire 03824
Paul C.W. Tsang
Department of Animal and Nutritional Sciences
Kendall Hall
129 Main St.
University of New Hampshire
Durham, New Hampshire 03824.
Manuscript submitted 21 August 2003
to the Scientific Editor's Office.
Manuscript approved for publication
8 July 2004 by the Scientific Editor.
Fish. Bull. 103:161-168(2005).
The northeast skate complex consists
of seven species endemic to the waters
off the New England coast of the
United States (New England Fisheries
Management Council (NEFMC1-2). In
the past, these skates were generally
discarded because of their low commer-
cial value (NEFMC1-2). More recently,
the rapidly expanding markets for
human consumption of skate wing
and for use as lobster bait have made
three of these species (winter skate
[Leucoraja ocellata], little skate [L.
erinacea], and thorny skate [Amblyraja
radiata]) commercially more viable
(Sosebee, 2000; NEFMC1-2). Despite
an increasing commercial importance,
harvests for skate in the U.S. portion
of the western north Atlantic remain
unregulated and have the potential to
over-exploit the stocks. Moreover, life
history information is almost nonex-
istent for most of these elasmobranch
fishes (Frisk, 2000 NEFMC1-2).
The available information from the
few skates that have been studied cat-
egorizes them as equilibrium strate-
gists (K selected) because they reach
sexual maturity at a late age, have a
low fecundity, and are relatively long-
lived (Holden 1977; Winemiller and
Rose, 1992; Zeiner and Wolfe, 1993;
Francis et al., 2001; Frisk et el.,
2001, Sulikowski et al., 2003). These
characteristics, coupled with the prac-
tice of selective removal of large in-
dividuals, make these animals more
likely to be over-exploited by commer-
cial fisheries (Brander 1981; Hoenig
and Gruber, 1990; Casey and Myers
1998; Dulvey et al., 2000; Frisk et
al., 2001).
The thorny skate (Amblyraja radi-
ata) is a cosmopolitan species found
on both sides of the Atlantic ocean
from Greenland and Iceland to the
English Channel in the eastern At-
lantic (Compagno et al., 1989) and
from Greenland and Hudson Bay,
Canada, to South Carolina, United
States, in the western Atlantic (Rob-
ins and Ray, 1986; Collette and Klein,
2002). Along with this broad geo-
graphic range, marked differences in
size exist for specimens captured in
different regions of the Atlantic. For
1 NEFMC (New England Fishery Man-
agement Council. 2001. 2000 stock
assessment and fishery evaluation
(SAFE) report for the northeast skate
complex. NEFMC, 50 Water Street, Mill
2 Newburyport, MA 01950.
2 NEFMC (New England Fishery Man-
agement Council). 2003. Skate fish-
eries management plan. NEFMC, 50
Water Street, Mill 2 Newburyport, MA.
01950.
162
Fishery Bulletin 103(1)
example, the thorny skate reaches total lengths of over
100 cm in the Gulf of Maine (Collette and Klein, 2002),
whereas specimens captured off the Labrador coast do
not reach total lengths >72 cm (Templeman, 1987).
Although no directed fisheries for this species exists in
the Gulf of Maine, this skate meets the minimum 1*4
pound-cut pectoral-fin size sought after by wing proces-
sors (Sosebee, 2000; NEFMC1-2). Unfortunately, because
landings are not reported by species, the proportion of
thorny skates to the total wing market is unknown. Re-
cent assessment studies in the northeast United States
(NEFSC3) indicate that the biomass of thorny skates
is declining, and is below threshold levels mandated
by the Sustainable Fisheries Act (SFA; NMFS4). Thus,
owing to the recent commercial interest in this species
and the concomitant decline in population size, obtain-
ing life history information for this species has become
more important. In order to provide insight into the
biology of this species and to determine the stock status
(Simpfendorfer, 1993; Frisk et al., 2001), our objectives
were to estimate age and growth rates of A. radiata
based on banding patterns in vertebral centra from
specimens collected in the western Gulf of Maine.
Marine Laboratory (CML). There, individual fish were
euthanized (0.3g/L bath of MS222). Total length (TL in
cm) was measured as a straight line distance from the
tip of the rostrum to the end of the tail, and disc width
(DW in cm) as a straight line distance between the tips
of the widest portion of pectoral fins. Total wet weight
(kg) was also recorded.
Preparation of vertebral samples
Vertebral samples, taken from above the abdominal
cavity, were removed from 320 thorny skates ( 154 females
and 166 males), labeled, and stored frozen. After having
been thawed, three centra from each specimen were
removed from the vertebral column, stripped of excess
tissue and air dried. Large centra were cut sagittally
with a Dremel™ tool fitted with a mini saw attachment
while held with a vice-like device. Smaller centra were
sanded with a Dremel™ tool to replicate a sagittal cut.
Processed vertebrae were mounted horizontally on glass
microscope slides and ground with successively finer-grit
(no. 180, no. 400, no. 600) wet-dry sandpaper. Each ver-
tebra was then remounted and the other side ground to
produce a thin (300-micrometer) hourglass section.
Materials and methods
Sampling
Thorny skates were captured by otter trawl in an approx-
imate 900 square mile area centered at 42°50'N and
70°15'W in the Gulf of Maine between June 2001 and
May 2002. These locations varied from 30 to 40 km off
the coast of New Hampshire. Approximate depths at
this location ranged between 100 and 120 m. This area
was chosen for two reasons: 1) these waters support
the vast majority of commercial fishing in New Hamp-
shire and can be easily accessed during normal fishing
operations; and 2) because of rolling closures within
the Gulf of Maine, an experimental fishing permit was
granted to us by the National Marine Fisheries Service
(NMFS) to collect thorny skates in this location during
the months of April, May, and June, when these waters
are closed to commercial fishing. Although our sam-
pling was conducted in a small portion of the species'
range, the sizes of thorny rays collected corresponded to
those collected during the NEFSC bottom trawl surveys
conducted throughout the Gulf of Maine and Georges
Bank (NEFMC1 ; NEFSC3). From this information, it is
unlikely that differences in other biological parameters
exist.
Skates were maintained alive on board the vessel un-
til arrival at the LTniversity of New Hampshire's Coastal
3 NEFSC (Northeast Fisheries Science Center). 1999. 30th
Northeast regional stock assessment workshop. NEFSC,
166 Water Street, Woods Hole, MA 02543-1026.
4 NMFS (National Marine Fisheries Service). 2002. Annual
report to Congress on the status of U.S. fisheries 2001, 142
p. NMFS, NOAA, Silver Spring, MD 20910.
Band counts
Vertebral sections were digitally photographed with a
Canon Powershot S40 attached to a Leica S8PO dis-
secting microscope and reflected light. Magnification
depended on the size of the section and varied from 4x
to 12x (Fig. 1). A growth ring (band count) was defined
as one opaque and translucent band pair that traversed
the intermedialia and that clearly extended into the
corpus calcareum (Casey et al., 1985; Brown and Gruber,
1988; Sulikowski et al., 2003). The birth mark (age zero)
was defined as the first distinct mark distal to the focus
that coincided with a change in the angle of the corpus
calcareum (Casey et al., 1985; Wintner and Cliff, 1996;
Sulikowski et al, 2003).
Precision and bias
Nonconsecutive band counts were made independently
by two readers for each specimen used in the study with-
out prior knowledge of the skate's length or of previous
counts. A Tukey test was used to test for differences
between ages. Age determination bias between read-
ers was assessed through the use of an age-bias plot.
This type of graph displays band counts of one reader
against a second reader in reference to an equivalence
line. Specifically, reader 2 is represented as mean age
and 95% confidence intervals corresponding to each
of the age classes estimated by reader 1 (Campana et
al., 1995). Divergence from the equivalence line, where
reader 1 = reader 2, would indicate a systematic dif-
ference between readers. Precision estimates of each
reader were calculated by using the coefficient of varia-
tion (CV) as described by Chang (1982) and Campana
et al. (1995).
Sulikowski et al.: Age and growth of Amblyro/a rodiata
163
Marginal increment analyses
The annual periodicity of band pair formation
was investigated using marginal increment
analyses (MIA). Because the annuli in older
adult specimens were compressed, marginal
increments were calculated from randomly
selected juvenile specimens (Simpfendorfer,
1993; Sulikowski et al., 2003). For MIA. the
distance of the final opaque band and the
penultimate opaque band, from the centrum
edge, was measured with a compound micro-
scope and optical micrometer. The marginal
increment was calculated as the ratio of the
distance between the final and penultimate
bands (Branstetter and Musick, 1984; Cail-
liet, 1990; Simpfendorfer, 1993; Simpfendorfer
et al., 2000; Sulikowski et al., 2003). Average
increments were plotted by month of capture
to identify trends in band formation, and a
Kruskal-Wallis one-way analysis of variance
on ranks was used to test for differences in
marginal increment by month (Simpfendorfer
et al., 2000; Sulikowski et al., 2003).
Growth estimates
A von Bertalanffy growth function (VBGF)
was fitted to the data with the following equa-
tion (von Bertalanffy, 1938):
Lt=LJl -e
-kit - t„\
V),
where /, = total length at time t (age in
years);
L = theoretical asymptotic length;
k = Brody growth constant; and
t0 = theoretical age at zero length.
Figure 1
Longitudinal cross-section of a vertebral centrum from a 97-cm-TL
female Amblyraja radiata estimated to be 12 years. BM = birth
mark; Black dots represent age in years.
The VBGF was calculated by using FISH-
PARM, a computer program for parameter
estimation of nonlinear models with Marquardt's (1963)
algorithm for least-square estimation of nonlinear
parameters (Prager et al., 1987).
Results
Morphological measurements
Out of the 320 specimens collected, a total of 224 were
used for our study (Table 1). Males (rc=103) ranged
between 29 and 103 cm TL, 18-75 mm DW, and 0.125-
10.5 kg body weight (data not shown), whereas females
(n=121) ranged between 31 and 105 cm TL, 18-74 cm
DW, and 0.170-11.4 kg body weight (data not shown).
Total length, disk width, and body weight were strongly
correlated in males, females, and when data from the
sexes were combined (all coefficient of determination [r2]
values were greater than 0.87).
Vertebral analyses
Comparison of counts between two readers indicated
no appreciable bias in the counting process (Fig. 2) and
the coefficient of variation for all sampled vertebrae was
2.8% This level of precision is considered acceptable
(Campana, 2001) and counts generated by both readers
were combined (averaged) for the analyses (Skomal and
Natanson, 2003).
The relationship between TL and centrum diameter
was linear (r2=0.93; P<0.05) and there were no signifi-
cant differences in this relationship (ANCOVA, P<0.05)
between males and females. Because no significant
difference existed between TL and centrum diameter
between the sexes, these data were combined (Fig. 3).
A total of 120 skates (10 per month) were used for
marginal increment analyses. Marginal increments
were significantly different between months (Kruskal-
Wallis P<0.001); there was a distinct trend of increasing
164
Fishery Bulletin 103(1)
Number of bands (age) of reader one
Figure 2
Age bias graph for pair-wise comparison of 224 thorny skate
{Amblyraja radiata) vertebral counts by two independent readers.
Each error bar represents the 95% confidence interval for the
mean age assigned by reader 2 to all fish assigned a given age by
reader 1. The diagonal line represents the one-to-one equivalence
line. Sample sizes are given above each corresponding age.
Table 1
Average
total length (TL) and d
isc width (DW) at age
for male and female thorny skates
(A. radiata). Sizes
are presented as
mean ±1 SEM
sample sizes are
given in parentheses.
Age (yes
rs)
Male TL (cm)
Female TL (cm) S
exes combined
Male DW (cm)
Female DW (cm)
Sexes combined
2
33 (5) ±1
33 (5) ±1
23±1
2±1
3
37 (3) ±1
37 (7) ±1
37(10)±1
26 ±1
27 ±0
27 ±1
4
43 (5) ±1
42 (2) ±2
42 (7) ±1
29 ±0
29 ±1
29 ±1
5
48(2)±2
49 ( 7) ±2
48 (9) ±1
33 ±0
35 ±0
34 ±1
6
64(1)±1
54(17)±1
54(18)±1
44 ±0
39 ±2
39 ±2
7
69 (5) ±1
62 (5) ± 3
64(10)±1
50 ±1
44 ±2
47 ±1
8
71 (6) ±1
73 (11) ±2
72 (17) ±2
52 ±1
53 ±2
53 ±1
9
78 (9) ±1
78 (8) ±2
78(17)±1
57 ±2
57 ± 1
57 ±1
10
86 (14) +1
82(15)±1
84(29)±1
63 ±2
60+1
61 ±1
11
88(17)±1
89<17)±1
89(34)±1
65 ±1
65 ±1
65 ±1
12
93(18)±1
92(19)±0
92(37)±1
68 ±1
66 ±1
67 ±1
13
99(10)±1
95 (8) ±1
97(18)±1
73 ±1
68 ±1
70+1
14
97 (3) ±3
98(1)±0
96 (4) ±2
70 ±2
70 ±0
70 ±1
15
102 (2) ±1
101 (3) ±0
101 (5) ±1
70 ±1
74 ±2
74 ±1
16
101 (3) ±2
105(1)±0
102 (4) ±2
75 ±1
70 ±1
75 ±1
monthly increment growth that peaked in July, followed
by a large decline in August (Fig. 4). Based on this
information, the increment analyses support the likeli-
hood that a single opaque band may be formed annually
on vertebral centra during August or September. The
marginal analysis was only conclusive for juvenile-size
animals (skates s80 cm TL). As thorny skates matured,
their growth slowed dramatically and the band counts
in older specimens became compressed, making it dif-
ficult to discern monthly changes in margin width.
Suhkowski et al.: Age and growth of Amblyra/a radiata
165
Age and growth estimates
The von Bertalanffy growth curves (VBGC)
fitted to total length-at-age data (Fig. 5) pro-
vided a reasonable fit with a low standard error
for males, females, and both sexes combined
(Table 2). Furthermore, the VBGC parameters
for males, females, and the sexes combined were
similar, and because no differences in age-at-
size existed between males and females (P>0.05
ANOVA), those data were combined (Fig. 5).
Discussion
Precision estimates, the relationship between
TL and centrum diameter, and marginal incre-
ment analysis support the use of vertebral
centra for age analyses of thorny skates cap-
tured in the Gulf of Maine (Conrath et al.,
2002; Sulikowski et al., 2003). Furthermore,
the 2.8% coefficient of variation indicates that
our aging method represents a precise approach
for the age assessment of A. radiata (Cam-
pana, 2001). Minimal width of the marginal
increment for thorny skates captured in August
and September (Fig. 4) supports the hypoth-
esis of annual band formation in this species.
Moreover, these results compare favorably to
cycles in marginal increments (Sulikowski et
al., 2003) and to annual vertebral band pat-
terns in other skate species (Holden and Vince,
1973; Waring, 1984; Natanson, 1993; Zeiner
and Wolfe, 1993; Walmsley-Hart et al., 1999;
Francis et al., 2001). However, because the
band counts of the largest and oldest animals
in the population were compressed (too small
for us to discern marginal increments from
their widths), the marginal increment analysis
included only juvenile skates that were s80
cm total length and the annular nature of the
growth bands was verified for only those length
groups. Nevertheless, we assumed that as the
skates grew larger and older, the annual nature
of growth ring deposition continued throughout
their lifetime (Conrath et al, 2002).
During 42 sampling trips from June 2001
through May 2002 (approximately three trips
per month), individuals <30 cm TL were rarely
captured. The lack of specimens in this size
class and smaller size classes was most like-
ly due to the mesh size of the commercial trawl nets.
Trawl nets used by commercial fishermen in the Gulf
of Maine are restricted to a 6V2-inch diamond mesh-
size opening, which facilitates the release of most fish
below 30 cm TL.
Our estimates of Lr exceed the largest specimens in
our field collections for both females and males. Growth
parameters estimated from the Gompertz and logistics
equations also produced over-estimations of La for the
140 -i
r2 = 0.93
120 -
P<0.05
100 -
•jtfS^
?
u
— 80 -
^ 60-
ro
40 -
S*
20 -
^
0 2 4 6 8 10 12
Centrum diameter (mm)
Figure 3
The relationship of total length (cm) to centrum diameter (mm)
for combined sexes of thorny skate (Amblyraja radiata).
0 9 -|
0.8 -
nal increment
o o
| 0.5 -
Relative
o
0 3 -
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Figure 4
Mean monthly marginal increments of opaque bands for Ambly-
raja radiata from the Gulf of Maine. Marginal increments were
calculated each month from 10 specimens whose centra contained
less than 10 annuli. Error bars represent 1 +SEM.
thorny skates in our study. Because the von Bertalanffy
growth curve (VBGC) is most widely used and accepted
in elasmobranch age and growth studies, we chose to
use this function to fit our data. Over estimation of L^
with the VBGC has been documented in most skate
species studied to date (Table 3). Campana (2001) sug-
gested that the smallest and largest specimens are the
most influential in the estimation of growth. Moreover,
both Walmsley-Hart et al. (1999) and Sulikowski et
166
Fishery Bulletin 103(1)
al. (2003) suggested that rareness of large in-
dividuals was most likely responsible for their
over estimation of Lx. Similarly, in a study of the
blue shark (Prionace glauca) in the northwest
Atlantic, Skomal and Natanson (2003) suggested
that earlier studies on the same species contained
artificially inflated Lx estimates and lower growth
rates because of the lack of maximum-size fish.
The rareness of large specimens in our study may
have been due to these larger individuals being
able to avoid the fishing gear or may indicate that
mortality, natural or fishing induced, prevents
them from attaining these lengths. Exploratory
manipulation of our data indicated that inclusion
of maximum observed sizes (i.e., thorny skates
over 103 cm TL) produced divergent results with
regard to von Bertalanffy parameters. For ex-
ample, the addition of maximum-size fish, using
20 years as the maximum age (Templeman, 1984)
and 105 cm as the maximum total length (from
the present study), reduced the combined sex Lx
from 124 cm TL to 116 cm TL. However, the same
effect was not documented when adding hatching
size (age zero) fish (note: because no documented
size for thorny skates exists within the Gulf of
Maine, the authors used known hatching sizes for
a similar congener species, the winter skate [Leucoraja
ocellata]). Be that as it may, the reasonable fit of the
thorny skate data (Table 2) to the VBGC (Fig. 5) for
A. radiata, along with a comparison with other batoid
studies (Table 3), indicates that this is an appropriate
model for this skate species.
Growth rates were similar for both sexes of thorny
skate (£ = 0.13 for females and 6 = 0.11 for males) and
commensurate with other skate species of a similar
size. The oldest age obtained for male and female
thorny skates was 16 years (Table 1). These data are
in agreement with the assumption that larger batoids,
such as A. radiata, R. pullopunctata (Walmsley-Hart et
al„ 1999), and L. ocellata (Sulikowski et al., 2003) are
longer lived and slower growing than smaller species.
For instance, R. erinacea, which reaches a total length
of 52 cm, has been aged to 8 years and found to have
110 -i
100 -
90 -
80 -
.lit 'Jr^^
? 70-
Jf\ • Females
£ 60 -
J5 50 -
2 40-
30 -
*/• * Males
20 -
/
10 -
/
0 2 4 6 8 10 12 14 16
Band count (age in years)
Figure 5
Von Bertalanffy growth curve generated from combined ver-
tebral data for female and male thorny skates iAmblvraja
radiata) from the western Gulf of Maine. Individual VBGC
parameters are given in Table 2.
Table 2
Calculated von
and combined
Bertalar
sexes of A
ffy parameters
radiata.
for male, female.
Parameter
Male
Female
Combined sexes
L.(cmTL)
127.00
120.00
124.00
K (/year)
0.11
0.13
0.12
t0 (year)
-0.37
-0.4
-0.35
r2
0.96
0.92
0.94
SE
0.01
0.01
0.001
n
103.00
121.00
224.00
a corresponding k value of 0.352 (Johnson, 1979; War-
ing, 1984).
The reduction in biomass of the thorny skate below
threshold levels mandated by the SFA necessitates the
development of management measures to rebuild these
stocks in accordance with the Magnuson-Stevens Fish-
ery Conservation and Management Act. However, the
development and implementation of a successful fisher-
ies management plan for the species require in-depth
analyses of appropriate biological information. More-
over, accurate stock assessment data for skates is dif-
ficult to collect in the northeast U.S. because individual
species are rarely differentiated in landings information
(NEFMC1 2). As a result, fluctuations in stock size will
continue to be difficult to detect and successful imple-
mentation of fisheries management plans will remain
problematic. This article is the first in a series aimed
at providing life history data for the management of
thorny skates indigenous to the Gulf of Maine. The
basic age and growth parameters for the thorny skate
provided in the present study support the hypothesis
that A. radiata, like other elasmobranchs, require con-
servative management because of their slow growth rate
and susceptibility to over-exploitation (Brander, 1981;
Kusher et al., 1992; Zeiner and Wolf, 1993; Frisk et al.,
2001; Sulikowski et al., 2003).
Acknowledgments
Collection of skates was conducted on the FV Mystique
Lady. We thank Noel Carlson for maintenance of the fish
at the U.N.H. Coastal Marine Laboratory and Matt Ayer
for his help in digitizing the vertebrae samples. This
Sulikowski et al.: Age and growth of Amblyra/a radiata
167
Table 3
Comparison of von Bertal
inffy derived Lx
to the observed total lengths (L) for
a number of skate
species, i, (mm) = disk width.
Scientific name
Sex
L, tmml
L observed (mm)
Max. age (yr)
Source
Raja microocellata
9 a
1370 (TL)
875'
9
Ryland and Ajayi, 1984
Raja montagui
9 a*
978 (TL)
710'
7
Ryland and Ajayi, 1984
Raja clavata
9
1047 (TL)
1392
7
Ryland and Ajayi, 1984
Raja erinacea
9 o"
527 (TL)
520
8
Waring, 1984
Raja rhina
O*
967 (TL)
1322
13
Zeiner and Wolf, 1993
Raja rhina
9
1067 (TL)
1047
12
Zeiner and Wolf. 1993
Raja wallacei
o*
405 (DW)
512
15
Walmsley-Hart et al., 1999
Raja wallacei
9
435 (DW)
571
15
Walmsley-Hart et al., 1999
Raja pullopunctata
o*
771 (DW)
696
18
Walmsley-Hart et al., 1999
Raja pullopunctata
9
1327 (DW)
747
14
Walmsley-Hart et al., 1999
Raja pullopunctata
9
1327 (DW)
747
14
Walmsley-Hart et al., 1999
Dipturus nasutus
9 o*
700 (TL)
913
9
Francis et al., 2001
Dipt unit: innominatus
9 o*
1330 (TL)
1505
24
Francis et al., 2001
Leucoraja ocellata
9 o*
1314 (TL)
936'
19
Sulikowski et al., 2003
Amblyraja radiata
9 o*
1240 (TL)
1020'
16
Present study
' Average of male and female
observed TL.
project was supported by a Northeast Consortium grant
(no. NA16FL1324) to PCWT, JAS, and PDD.
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169
Abstract — Age estimates for striped
trumpeter (Latris lineata) from Tas-
manian waters were produced by
counting annuli on the transverse
section of sagittal otoliths and were
validated by comparison of growth
with known-age individuals and
modal progression of a strong recruit-
ment pulse. Estimated ages ranged
from one to 43 years; fast growth
rates were observed for the first five
years. Minimal sexual dimorphism
was shown to exist between length,
weight, and growth characteristics of
striped trumpeter. Seasonal growth
variability was strong in individuals
up to at least age four, and growth
rates peaked approximately one month
after the observed peak in sea surface
temperature. A modified two-phase
von Bertalanffy growth function was
fitted to the length-at-age data, and
the transition between growth phases
was linked to apparent changes in
physiological and life history traits,
including offshore movement as fish
approach maturity. The two-phase
curve was found to represent the
mean length at age in the data better
than the standard von Bertalanffy
growth function. Total mortality
was estimated by using catch curve
analysis based on the standard and
two-phase von Bertalanffy growth
functions, and estimates of natural
mortality were calculated by using
two empirical models, one based on
longevity and the other based on the
parameters L, and k from both growth
functions. The interactions between
an inshore gillnet fishery targeting
predominately juveniles and an off-
shore hook fishery targeting predomi-
nately adults highlight the need to
use a precautionary approach when
developing harvest strategies.
Age validation, growth modeling,
and mortality estimates for striped trumpeter
(Latris lineata) from southeastern Australia:
making the most of patchy data
Sean R. Tracey
Jeremy M. Lyle
Marine Research Laboratories
Tasmanian Aquaculture and Fisheries Institute
Private Bag 49
Hobart 7001, Tasmania, Australia
E-mail address (for S R Tracey): straceyigutas edu au
Manuscript submitted 20 December 2003
to the Scientific Editor's Office.
Manuscript approved for publication
7 September 2004 by the Scientific Editor.
Fish. Bull. 103:169-182 (2005).
Striped trumpeter (Latris lineata) are
widely distributed around the tem-
perate latitudes of southern Austra-
lia, New Zealand (Last et al., 1983),
the Gough and Tristan Da Cunha
Island groups in the southern Atlan-
tic Ocean (Andrew et al, 1995), and
the Amsterdam and St. Paul Island
groups in the southern Indian Ocean
(Duhamel, 1989). They are opportu-
nistic carnivores associated with epi-
benthic communities over rocky reefs
at moderate depths from 5 to 300 m
along the continental shelf. The spe-
cies can grow to a relatively large
size, 1200 mm in total length and 25
kg in weight (Gomon et al., 1994).
Spawning apparently occurs offshore,
and females are highly fecund mul-
tiple-spawners (Furlani and Ruwald,
1999). Although there have been a
number of ichthyoplankton surveys in
Tasmanian waters, only a few striped
trumpeter larvae have been collected,
caught during the late austral winter
through early spring months at near-
shore (30-50 m) and shelf edge sites
(-200 m) (Furlani and Ruwald, 1999).
Larval rearing trials have shown that
the presettlement phase is complex
and extended; individuals can remain
in this neritic-pelagic phase for up
to 9 months after hatching before
metamorphosis into the juvenile stage
takes place (Morehead1). As juveniles
striped trumpeter settle on shallow
rocky reefs.
In Tasmania striped trumpeter
are taken commercially over inshore
reefs (5 to 50 m), generally as a by-
catch of gillnetting, and are targeted
with hook methods (handline, drop-
line, longline, and trotline) on deeper
reefs (80 to 300 m). Small, subadult
individuals dominate inshore catches,
whereas larger individuals are taken
from offshore reefs. In recent years
the combined annual commercial
catch has been typically less than 100
metric tons (Lyle2). Striped trumpeter
also attract significant interest from
recreational fishermen, who use both
hooks and gill nets. Furthermore,
the aquaculture potential for this
species is currently being assessed
in Tasmania (Furlani and Ruwald,
1999; Cobcroft et al., 2001). Despite
wide interest in this species, there is
a general paucity of information on
age, growth, and stock structure of
wild populations.
Assessing the growth of a species is
a fundamental part of fisheries popu-
lation dynamics. Ever since Beverton
and Holt (1957) introduced the von
Bertalanffy growth model to fisheries
research it has become ubiquitous in
descriptions of the increase in size
1 Morehead. D. 2003. Personal commun.
Tasmanian Aquaculture and Fisheries
Institute, Univ. Tasmania. GPO Private
Bag 49, Hobart, Tasmania, Australia
7001.
2 Lyle. J. M. 2003. Tasmanian scale-
fish fishery — 2002. Fishery assessment
report of the Marine Research Laborato-
ries, Tasmanian Aquaculture and Fish-
eries Institute, Tasmania. [Available
from TAFI GPO Private Bag 49, Hobart,
Tasmania, Australia 7001.]
170
Fishery Bulletin 103(1)
of a species as a function of age. The parameters com-
mon to the von Bertalanffy growth function (VBGF)
are used in stock assessment models such as empiri-
cal derivatives of natural mortality (Pauly, 1980) and
assessments of yield per recruit and spawning stock
biomass (Beverton and Holt, 1957). Despite the von
Bertalanffy growth parameters being well established
as cornerstones of many stock assessment models, sev-
eral authors have highlighted limitations of the original
derivation of the growth function to adequately repre-
sent growth of a population (Knight, 1968; Sainsbury,
1979; Roff, 1980; Schnute, 1981; Bayliff, et al, 1991;
Hearn and Polacheck, 2003). This limitation becomes
especially evident with limited or patchy data. The
limitations of the von Bertalanffy growth function have
created three scenarios: 1) use the VBGF and retain the
use of the parameters to derive per-recruit estimates
at the possible expense of physiological integrity; 2)
derive or employ a model that is not based on the von
Bertalanffy parameters (such as a linear or logistic
model) or another polynomial function (for instance,
the Gompertz equation [Schnute, 1981]) and in doing
so the expediency of the von Bertalanffy parameters
in stock assessments is compromised; 3), use or develop
an extension of the von Bertalanffy equation with the
caveat that, by introducing additional parameters, the
problem of reduced parsimony by over parameterisation
would need to be considered.
While investigating the life history characteristics of
striped trumpeter, we became aware that the original
description of the VBGF would not adequately represent
growth of this species, in part because of the patchy
data available for analysis.
This study aims to describe the age and growth of
striped trumpeter from Tasmania. Seasonal growth
oscillations are considered for the first four years by
using actual length-at-age data from a strong cohort.
We then employ and evaluate an extension of the VB-
GF that offers a better fit to the sample population of
aged individuals and allows the flexibility of assigning
representative growth and mortality parameters to
different life phases of the population. Growth param-
eters derived from both the standard von Bertalanffy
and extended von Bertalanffy models are used in our
catch curve analyses, and the empirical models of Pauly
(1980) and Hoenig (1983) are used to allow comparison
of mortality estimates.
Materials and methods
Striped trumpeter were collected opportunistically from
various sites off the east and southeast coasts of Tasma-
nia from a variety of fisheries dependent and indepen-
dent sources spanning the period 1990-2002 (Table 1).
Inshore catches were predominately taken with gill nets
ranging in mesh sizes from 64 to 150 mm. Offshore
catches were taken by hook-and-line methods. Samples
ranged from intact specimens, for which the full range of
biological information was collected, to processed frames
Table 1
Composition of Tasmanian sampling data from 1990
through 2002 showing data from inshore gill net and off-
shore hook fisheries. Numbers in parentheses represent
the number of individuals aged from each particular sam-
pling regime.
Year
Gill net
Hook
Total
1990
45
45
1991
—
332
332
1992
—
126
126
1994
3
8
11
1995
228
12
240
1996
529
55
585
1997
193
2
195
1998
7
171
178
1999
205
902
1107
2000
—
91
91
2001
—
60
60
2002
—
97
99
Total
1165
1901
3069
(268)
(508)
(776)
from which length and, depending on condition of the
body, sex and gonad weight were recorded. All specimens
were measured for fork length (±1 mm) and, where pos-
sible, total weight was recorded (±1 gram). Otoliths were
collected when possible. This ad hoc sampling approach
created a temporally irregular data set.
Kolmogorov-Smirnov tests (o=0.05) were used to de-
termine whether significant differences existed between
male and female length-frequency distributions or be-
tween length-frequency distributions by depth strata.
Analysis of residual sums of squares (Chen, 1992)
was used to determine whether a significant difference
existed between the sex-specific length-weight rela-
tionships that were fitted by minimizing the sum of
square residuals and that are described by the power
function
W=aLb, (1)
where W = whole weight (g);
L = fork length (mm); and
a and b = constants.
Sex ratios were compared for significant deviation from
1:1 by chi-square tests.
Aging technique
Sagittal otoliths were removed from 873 individuals and
a subsample of 295 otoliths were individually weighed
to the nearest milligram. One randomly selected oto-
lith from each fish was embedded in clear polyester
casting resin. A transverse section was taken through
Tracey and Lyle: Age validation, growth modeling, and mortality estimates for Latris lineata
171
the primordial region (width approximately 300 ^m)
and mounted on a microscope slide. A stereo dissector
microscope at 25 x magnification was used to aid the
interpretation of increments in the mounted sections.
Increment measurements were made by using Leica IM "
image digitization and analysis software (Leica Micro-
systems, Wetzlar, Germany). All counts and increment
measurements were made without knowledge offish size,
sex, or date at capture to avoid reader bias.
Position of the first annual increment was determined
by testing the close correspondence of otolith micro-
structure and body size between known-age individuals
reared from eggs in aquaria and wild-caught specimens.
To ensure that growth in cultured individuals also re-
flected growth in wild specimens, a hypothesis of com-
parable growth was tested by fitting traditional VBGFs
to the length-at-age data of 288 cultured individuals
(maximum known age: 4 years) and 268 wild specimens
(maximum otolith-derived age: 4 years). A likelihood
ratio test (Kimura, 1980) was then used to test for sig-
nificance. The VBGF model was in the form
sampled from the strong 1993 cohort over the period
1995 through 1997, where the model was described as
L, = LAI - <r« " V)+e.
(2)
where L, = length at age t;
hv = average asymptotic length;
k = a constant describing how rapidly L„ is
achieved;
t0 = the theoretical age where length equals
zero; and
f = independent normally distributed (O, a2)
error term.
Modal progression of length frequencies from a strong
cohort of juvenile fish was sampled over a three-year pe-
riod (1995-97). This cohort provided an opportunity to
validate annual periodicity in increment deposition. By
applying an aging protocol based on position of the first
increment and assuming that each opaque+translucent
zonal pair represented one year of growth, this recruit-
ment pulse could be tracked over seven years in age-
frequency progression.
A random subsample of 335 otoliths was read a sec-
ond time by the primary reader, and a second subsam-
ple of 46 otoliths by a second reader, both experienced
in otolith interpretation. Precision was assessed by
determining percentage agreement between repeated
readings, age bias plots (Campana et al., 1994), and
calculating the average percent error (APE) (Beamish
and Fournier, 1981).
Growth modeling
The length-frequency progression of a strong and dis-
crete cohort of fish indicated that striped trumpeter
may be subject to seasonal growth variability. This
variability was described by integrating a sinusoidal
function (Pitcher and MacDonald, 1973; Haddon, 2001)
into a standard VBGF and by applying this function
to the actual weekly length-at-age data of individuals
L =L 1
+ £,
(3)
where C = the magnitude of the oscillations above and
below the nonseasonal growth curve of the
sinusoidal cycle;
S = the starting point in weeks of the sinusoidal
cycles; and
52 = the cycle period in weeks.
The timing of seasonal growth was compared with
weekly average sea surface temperature (SST) on the
southeast coast of Tasmania over the sampling period,
calculated by using optimum interpolation (Reynolds
et al., 2002) of raw remotely sensed data from the ar-
ea (NOAA-CIRES3). A sine function was fitted to the
weekly average SST by using least squares regression
to compare the timing and phase of growth and tem-
perature and test for a significant correlation.
All individuals aged were assigned a "decimal" age,
where the decimal portion represented the proportion of
the year between a nominal average date of spawning
(1st October) and the date of capture. We assumed a
nominal peak spawning date of 1 October based on an
assessment of monthly averaged gonadosomatic index
(Tracey, unpubl. data), which is consistent with that
observed for wild-caught broodstock held under ambient
conditions (Morehead1).
Growth of the sampled population was initially de-
scribed by using the standard von Bertalanffy growth
function (Eq. 2). However, a preliminary visual assess-
ment of the fit suggested it did not produce an adequate
representation of the entire data set. In an attempt to
find a model that better represented the data, the fit of
the standard von Bertalanffy growth function (VBGFS)
was compared with an extension of the traditional von
Bertalanffy growth model fitted by minimization of the
sum of negative log-likelihood; normal distribution of
the error term. The model chosen was similar to that
used by Hearn and Polacheck (2003) and involved fit-
ting a VBGF function either side of an age at transfer-
ence, described as
L ,=
'L_i(l-e-^«-«o.»)+£
for t < t"
(4)
(Ls + ( L,2 - If )(1 - e*-"-'"; ')+ e for t > ts
3 Data sourced from the NOAA-CIRES Climate Diagnostics
Center, Boulder, CO 80305. http://www.cdc.noaa.gov/.
[Accessed 15 Sep. 2002)
172
Fishery Bulletin 103(1)
where Lxl, kv t01
VBGF parameters applied to the
first growth phase;
Ll2, k2, t02 = VBGF parameters applied to the
second growth phase;
Ls = length of transference from one
growth phase to the next; and
ts = age of transference from one growth
phase to the next; calculated as.
* =v
In
A
L,
(5)
Having fitted Equation 4, we smoothed the discon-
tinuity from the first growth stanza to the second, as-
suming normal distribution around the age at transfer-
ence by integrating a normal probability cumulative
distribution function (PDF) where the mean is equal
to the age of transference (4.4 years) and where the
standard deviation is arbitrarily set at 1.0. This model
is referred to as the two-phase von Bertalanffy growth
function (VBGFTP) and is now represented as
♦''' i
-■<-(„, f)\
,1, Os/2k
(L_1(l-e-*'"-'»,)+£)+
, (6)
(*•.
" 1
', o-n/2/t
(L6+(L,2-L')a-e-k'"'"') + e)
where tmax = maximum age present in the sample;
and
a2 = standard deviation of cumulative density
function with mean t6.
The model that best represented the data was judged
on a combination of parsimony as determined by the
Akaike information criterion (AIC) (Akaike, 1974), qual-
ity of fit by minimization of the negative log-likelihood
value derived from each model, visual inspection of the
residuals, and as an index of fit, the percent deviation
of Lx for each model from the maximum observed length
The hypothesis of sexual dimorphism in growth was
tested by using likelihood ratio tests (Kimura, 1980)
for both the VBGFS and VBGFTP models fitted to the
length-at-age data of all individuals whose sex had been
determined.
Mortality estimation
Mortality estimates were calculated by using the param-
eters of both the VBGFS and VBGFTP functions. An esti-
mate of instantaneous rate of total mortality (Z) for the
offshore hook fishery was calculated for 1998 by applying
a length converted catch curve analysis (LCCCA sensu
Pauly, 1983) to the length-frequency data.
Estimates of instantaneous rate of natural mortality
(M) were calculated by using two empirical equations.
The first equation, derived by Pauly (1980), is described
log10M = -0.0066 - 0.279 log^L^y
+ 0.6543 log10 ky + 0.4634 log10 T,
(7)
where L„ and ky = parameters derived from the VBGFS
or from the second growth phase of
the VBGFTP; and
T = average annual sea surface tempera-
ture (°C) at the area of capture.
The mean annual sea surface temperature on the east
coast of Tasmania in 1998 was estimated as 14°C
(NOAA-CIRES3). The second equation used was the
regression equation of Hoenig (1983):
In Z = 1.46 - 1.01 In tmax; M~Z assuming F~0, (8)
where tmax = the maximum age for the species in years.
Estimates of fishing mortality (F) were calculated by
subtracting natural mortality from total mortality.
Results
Males ranged in length from 203 mm to 815 mm (n = 504)
and females ranged from 269 mm to 950 mm (n = 565).
Length-frequency distributions did not differ signifi-
cantly between sexes (Kolmogorov-Smirnov; Z = 0.91
P=0.38).
Pooling the length-frequency data of all individuals
produced a bimodal frequency distribution. However,
when grouped by depth (Fig. 1), the data revealed a
significant depth-based stratification between the shal-
low (<50 m stratum) and the deeper strata (Kolmogorov-
Smirnov; Z=13.8 P<0.001), occurring at around 450 mm
in length.
Analysis of residual sums of squares indicated no
significant difference between the sex-specific length-
weight relationships (F=0.02 df=2 P=0.10); consequently
a power regression was applied to the length-weight
data of all individuals combined (Table 2).
The sex ratio of males to females (1.0:1.3) from the
inshore net fishery showed a low level of significant
difference from 1:1 (x" = 3.88 P=0.049 n=232), whereas,
the ratio of males to females (1.0:1.1) caught from the
offshore hook fishery did not show significant difference
from 1:1 (x~ = 0.933 P=0.334 n = 840).
Age estimates
Age was successfully estimated for 776 (89%) individu-
als. Transverse otolith sections showed typical distinct
alternate light and dark zone formations within the
Tracey and Lyle: Age validation, growth modeling, and mortality estimates for Latns lineata
173
30
25
20
15
10
5
0
30
25
20
15
10
5
0
30
25
20
15
10
5
0
30
25
20
15
10
5
0
Length
(Latris
Depth: 0 - 50 m
n = 1039
K
Depth: 51 - 100 m
n = 244
J\^n\ P
— — i I i rrr-| cC.
Depth: 101 - 150 m
n=246
Tr-fl^TTr^
n Gill net
□ Hook and line
Depth: 151 -200 m
n= 147
Qh
j~|hi-^ t n n
— i 1 1 1 —
0 100 200 300 400 500 600 700 800 900 1000
Length class (20-mm bin category)
Figure 1
-frequency distribution by 50-m depth strata for striped trumpeter
lineata) samples collected from 1990 through 2002.
Table 2
Predictive equations used to compare
weight and length, otolith weight and
age, and reader variability across age
classes, for
striped trumpeter (Latris lineata).
Dependent variable
Independent variable
n
Equation
r2
Weight ( W I
Fork length IL)
491
ff = 2x 10"5 x L3-00
0.99
Otolith weight (OW)
Age it)
295
OW = 7.32 + (1.70 xn
0.89
Primary reader, count 2 (P9)
Primary reader, count 1 (Pj)
339
P2 = 0.05 + (0.99 xP,)
0.99
Secondary reader, count 1 (Sj)
Primary reader, count 1 (P,)
46
S, =0.27 + 10.97 xP,)
0.97
174
Fishery Bulletin 103(1)
B
0
Figure 2
Photomicrograph of transverse otolith sections of striped trumpeter (Latris
lineata) from (A) a 5-year-old male (515 mm, FL), and (B) a 15-year-old
female (724 mm, FL), using transmitted light. Scale bar = 1 mm.
otolith matrix. Viewed under transmitted light the zones
showed as dark (opaque) and light (translucent) (Fig.
2). A robust linear relationship existed between otolith
mass and individual age (Table 2).
The core area of each section consisted of an opaque
region. Immediately adjacent to this was a faint thin
translucent zone followed by the first broad opaque an-
nual increment. In some cases the transition from core
to the first expected increment could not be discerned
because of a continuation of the opaque region (the
expected thin translucent zone was too faint to see).
In such cases, increment measurements were required
to ensure that the annulus was not overlooked. Mean
increment radius (±SD) from the primordia to the first
annulus was 491 ±63 f<m (/!=122); and the deposition
of the second annulus occurred at a mean radius of
733 ±55 jim (n=122). The next four opaque and trans-
lucent zone pairs were relatively broad compared with
subsequent zones that consistently narrowed as they
approached the growing edge (Fig. 2).
To validate the first increment we compared somatic
and otolith growth of wild individuals with that of indi-
viduals cultured under ambient conditions. Larval-rear-
ing trials of striped trumpeter juveniles have produced
mean lengths of 190 mm at 14 months and 261 mm at
24 months. The smallest individuals recorded from the
wild in our study were 190-220 mm and were captured
in January 1995. From the rearing trials it seemed
reasonable to assume that the wild-caught individuals
of this size were between 1 and 2 years of age. If a
birth date of 1 October is assumed, these individuals
would have been about 16 months old and therefore
were spawned in 1993. Viewing the sectioned otoliths
of these small wild-caught individuals revealed only one
increment within the margin, analogous to the incre-
ment composition of cultured individuals at a similar
length.
To test for comparable growth between wild and cul-
tured individuals as a means to facilitate confident vali-
dation of the first increment deposition, von Bertalanffy
growth curves were fitted to length-at-age data of both
wild (based on otoliths) and cultured individuals (of
known age) to age four. A likelihood ratio test indicated
that wild-caught individuals increased in length slightly
faster than those cultured to the same age (x~ = 5.3 df=6
P=0.51); however, this trend was not significant (F=4.4
df=23 P=0.04).
Tracking length-frequency distributions (Fig. 3) from
1995 through 1997, from inshore gillnet samples, re-
vealed progression of a strong cohort. Based on its size
structure, the spawning year for this cohort was as-
sumed to be 1993. A second cohort was evident in the
last quarter of 1996, assumed to have been spawned in
1994. The progression of the cohort spawned in 1993
was clearly evident in the age structure of the samples
over the period 1995-2001, proving useful in the valida-
Tracey and Lyle: Age validation, growth modeling, and mortality estimates for Latns lineata
175
100 -| Jan 1995 50 ] _ Apr-Jun 1996
n= 9
n = 34
80
40
60
30
40
20
20
10
0
70
1
rrg r
-,
Apr-Jun 1995 100]
Jul-Sep 1996
60
n
n = 40
n = 6
50
80
40
60
30
40
20
20
10
0
_ 50
r
F3 r\
i . ^ . . . . y
Jul-Sep1995 35 I
Oct-Dec 1 996
* 40
-
n = 23 30
n = 201
25
S 30
3
-
20
O"
g 20
15
n
c
_J
10
8 10
s
5
n
k
"- 0
50 -I
Oct-Dec 1 995 30
Jan-Mar 1997
40
p
"=157 25
20
n
n= 101
30
1 15
1
20
10
10
5
0
60
ll~ n
n r-, r^
Jan -Mar 1996 40
Apr-Jun 1 997
50
n = 289
n=73
30
40
-
30
20
20
10
-
-
10
. 1
n
0 ^ ■< 1 1 1 1 1 1
100 200 300 400 500 600 700 100 200 300 400 500 600 700
Fork length (mm)
Figure 3
Quarterly length-frequency distribution (by 20-mm size class) of striped
trumpeter iLatris lineata) sampled from January 1995 to June 1997.
tion of annual periodicity (Fig. 4). However, inferences
about population age structure cannot be drawn from
the age-frequency histograms because some sample siz-
es were low and there was discriminatory sampling (by
gear type) over the period. For instance up to 1996-97
most of the aged samples were from inshore gillnet
catches, whereas subsequent samples were derived pri-
marily from hook catches.
Precision of repeated age estimation was high. Second
readings by the primary reader were 79% in agreement
with first readings, yielding an APE of 0.93%. Eighteen
percent of second readings gave rise to a one-year dif-
ference and 3% of second readings differed by 2 years,
and no significant tendency to overestimate or underes-
timate age was evident. An age bias plot did not differ
significantly from 1:1 for the primary reader (Table 2).
176
Fishery Bulletin 103(1)
1.0
0 8
06
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
1.0 l
0.8
0.6
0.4
02
0.0
1.0 n
0.8
0.6
0.4
0.2
0.0
JL
1994-1995
n = 47
1995-1996
n= 146
1996-1997
n = 74
1997-1998
n = 7
1
6 7 8
Age (yr)
9 10 11 12 13 14
1.0
0.8
0.6
0.4-
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
1.0 i
0.8
0.6
0.4
0.2-
0.0
- I 1
1998-1999
n = 207
1999-2000
n=90
2000-2001
n = 46
I
m
12 3 4 5
6 7 8
Age (yr)
9 10 11 12 13 14
Figure 4
Age-frequency distribution (based on biological year. October-September) for striped trumpeter (Latris line-
ata) from 1994 through 2001. Gillnet-caught fish are represented by unshaded columns, hook-caught fish
are represented by shaded columns. Arrows represent the progression of the cohort spawned in 1993.
Precision of the second reader's age estimates when
compared with those of the primary reader were also
satisfactory, yielding an APE of 1.59%, and no signifi-
cant bias was revealed at any age class (Table 2).
The maximum observed ages for males and females
were 29 and 43 years, respectively. From the available
data, it is unclear whether apparent differences in lon-
gevity between the sexes are representative because
very few individuals over the age of 25 were sampled.
However, there was no significant difference in the age-
frequency composition of the pooled samples based on
sex (Kolmogorov-Smirnov; Z=1.05 P=0.22).
Growth modeling
The strong 1993 cohort, allowed us to closely monitor the
actual length at age of striped trumpeter. Average size
increased from 190 mm (1.3 years) in January 1995 to
300 mm (2.1 years) by November 1996 (Fig. 3) and 420
mm (4.0 years) by November 1997. The seasonal VBGF
model indicated that the majority of observed growth
in this cohort occurred between January and May (late
austral summer through autumn) and that there was
little growth apparent between June and December
(Fig. 5). The sine wave representing seasonal fluctua-
tions indicated that the peak growth rate occurred in
May. Comparing this sine function with that derived for
SST (Fig. 6), we identified a first-order serial correla-
tion— the strongest correlation identified when a 34-day
lag period was incorporated in the growth phase.
The parameters of the VBGFS and VBGFTP fitted
to the aged individuals are presented in Table 3. The
VBGFTP gave the more parsimonious fit to the pooled
length-at-age data according to the deterministic AIC
value and underestimated Lx in relation to Lmax to a
lesser extent than the VBGFS (Table 3), reflecting a
better fit to the data in the older age classes. In con-
junction with a visual assessment of residuals, it was
apparent that the VBGFS underestimated length at age
above 20 years (Fig. 7). The better fit by the VBGFTP
Tracey and Lyle: Age validation, growth modeling, and mortality estimates for Latns lineata
177
500 -|
r 19
450 ■
h L 8
- 18
400 -
fl if-^ft
- 17
^1
?
E, 350 -
Q.
Y 16 01
•<
3
jj 300 -
o
"" 250 -
Xt\Jv
- Id q)
o>
■14 W
-13 B
200 -
t V v
- 12
Jan 95 Jul 95 Jan 96 Jul 96 Jan 97 Jul 97 Jan 98
Date
Figure 5
Length-at-age data (O) of the 1993 striped trumpeter (Latris lineata)
cohort fitted with a modified von Bertalanffy growth function to rep-
resent seasonal growth (black line), plotted against a 7-day average
SST at the time of sampling (gray line).
19-1 r 0 15
c
o
g 18-
/' i
ZJ
/i/\ /A /\
- 0.10 >
CD
J / \ / \ / V \
3
C 17 -
1 w \ / \ / \
-g_
(/)
1 ;i \ / \ Is \
.C
\J\ \ A \ W/A \
c
- 0.05 9-
i 16-
y\\ /A \ // \ \
o
"O
/ \ \ / / \ \ // \ \
(1)
/ l\ \ /// A \ // A \
tfl
— 15 -
/ i\ \ /l / M \ // Sv \
/ i \ / i / V<\ \ /l / ^t \
- 000 ^
o
\A \ /J/ u \ /(/ \ \
(Q
\ \ U\ \ \ hi \ \
o
H 14-
w \ is 1 A \ /i/ \\
£
01
X \ ' a \ / '/ v\
- -0.05 =r
w
\w V\// Wi
c 13 -
o
CD
\w \#/ \>y
E
--0.10 §
» 12-
\'\|
ra
j
TJ
K 11
Jan 95 Jul 95 Jan 96 Jul 96 Jan 97 Jul 97 Jan 98
Date
Figure 6
Seven-day mean SST (broken gray line) fitted with a sine wave (gray
line) plotted against the sine function (black line) extracted from the
seasonal von Bertalanffy growth function fitted in Figure 5.
supports the hypothesis that a more complex growth
model was required for striped trumpeter.
The VBGFTP was sensitive to the value age at trans-
ference. A profile of negative log likelihood for a range of
age-at-transference values (Fig. 8) assisted in determin-
ing the correct absolute minima. The negative log-like-
lihood profile revealed a low minima range across age
at transference from 3.5 to 4.6 years, which, however,
converged to a lowest value at age 4.4 years. Fitting the
PDF to the growth curve substantially smoothed the
point of transition, producing a curve that represented
the data well. Setting an arbitrary standard devia-
tion of 1.0 around the age at transference provided a
normally distributed two-tailed range at transference
(90 percent confidence adjusted for bias) from 1.3 to
7.8 years.
178
Fishery Bulletin 103(1)
A likelihood ratio test (LRT) identified a slight sig-
nificant difference between male and female VBGFS
growth curves (/2=13.20 df=3 P=0.04), but there was
no significant difference when the VBGFTP was tested
(X2=10.83 df=6P=0.09).
Mortality estimation
Ages 9-23 and 7-25 were included in the LCCCA regres-
sions of the VBGFS and the VBGFTP, respectively, to
n = 776
100
10
15
20 25
Age (yrs)
30
35
40
Figure 7
Pooled length-at-age data for striped trumpeter (Latris lineata).
The black line represents the optimal two-phase von Bertalanffy
growth function (VBGFTP), with a mean age at transference of 4.4
years and a standard deviation equal to 1; the gray line represents
the optimal standard von Bertalanffy growth function (VBGFS).
estimate Z (Fig. 9). Individuals below these ranges were
assumed, by their respective model, not to have fully
recruited to the offshore fishery, and individuals over
the age of 25 were excluded due to poor sample size.
These age ranges effectively excluded the strong 1993
recruitment pulse from the regression, thereby avoiding
the complication of including a known strong year class
in the analysis.
Application of the VBGFTP model resulted in lower
estimates of Z and M (based on the Pauly equation),
compared with those calculated by using the
VBGFS parameters (Table 4). The estimate
of Z based on the Hoenig (1983) equation
was assumed to be close to M because F is
low for this species. The Hoenig M was very
similar to the Pauly estimate when VBGFTP
parameters were used. In this case M was
just below 0.1, indicating an annual natural
mortality rate of about 9%. The VBGFTP
estimates indicate that F was slightly higher
than M in the offshore fishery. By contrast,
the standard VBFGS parameters produced
a substantially higher estimate of M (0.15)
based on the Pauly equation than predicted
by the Hoenig approximation, indicating an
annual natural mortality rate of about 14%.
Derived estimates of F with the VBGFTP
were slightly higher than M, whereas F in
relation to M was variable for the VBGFS,
depending on the equation used to derive M.
45
2 3 4 5 6 7 8 9 10 1 1 12 13 14 15 16 17 18 19
Age at transference
Figure 8
Negative log-likelihood profile plot of increasing age-at-transference
values for striped trumpeter iLatris lineata).
Discussion
The present study represents the first report
of age and growth of striped trumpeter.
Despite having available a patchy data set,
we were able to validate age and overcome
the limitations of the von Bertalanffy equa-
tion to represent these data by the use of a
robust growth model. Striped trumpeter are
long lived, have a maximum age in excess of
40 years, and growth is particularly rapid up
to age five, after which it slows dramatically.
The species has a complex early life his-
tory involving a long planktonic larval phase
of around nine months (Morehead1), an in-
shore juvenile phase, and then movement
offshore into deepwater.
Gear selectivity (gill nets in the shallow
and hook catches in the deeper waters) may
have influenced the fish-size structure of our
samples, especially when grouped by depth,
although it is highly unlikely that the size
differences could be completely attributed
to gear type alone. For instance, small indi-
viduals (<400 mm) were occasionally taken
by hooks in the deeper strata and individu-
als over 500 mm were taken by gill nets in
less than 50 m. The commercial hook fishery
Tracey and Lyle: Age validation, growth modeling, and mortality estimates for Latns lineata
179
I 6-
CD
O)
CO
61
° • y = -0.253* + 6.881 7
• r2 = 0.853 5 .
o°» y = -0.192x + 5.977
• r2 = 0.860
O)
c
CO
o 4 _
0 ^W
•N. 4
•^.
irithm (frequency [F
• >v 3
o N^
o • »^
0 ^s. •
^v •
^"S.
a, 1 -
o \ 1 -
*
2
A
B
m D -
z 0 5 10 15 20 25
Ane fvearsi
Figure 9
Length-converted catch curve analysis for striped trumpeter iLatris lineata) length and age data from 1998. (A) Age
composition was based on the standard von Bertalanffy growth function (VBGFS), (B) age composition was based on the
second stanza of the two-phase von Bertalanffy growth function (VBGFTp). Solid points were included in the respective
linear regressions.
for striped trumpeter is largely restricted to depths of
greater than 50 m, and despite considerable hook-fish-
ing effort at shallower depths targeting other demersal
reef species, notably the wrasses Notolabrus fucicola
and N. tetricus, minimal catches of striped trumpeter
are taken and those that are caught tend to be small
in size (Lyle2). Rather, size structuring by depth is
believed to reflect the movement of striped trumpeter
offshore into deeper water as they grow and mature.
Seasonal growth was dramatic in young striped trum-
peter (Fig. 5 1. This phenomenon is common in temper-
ate species (Haddon, 2001; Jordan, 2001; McGarvey
and Fowler, 2002), and has been linked to fluctuations
in environmental factors, such as water temperature
and oceanographic conditions, as well as biotic factors,
such as seasonality in primary productivity (Harris et
al., 1991; Jordan, 2001). Our study supports a correla-
tion between water temperature and seasonal growth
(Fig. 6); maximum growth was observed to take place
consistently over a three-year period, approximately one
month after the peak sea-surface temperatures.
Knowledge of growth and growth variability is es-
sential to the understanding of a stock's population
dynamics. To achieve an accurate assessment of these
characteristics, several issues need to be addressed.
Foremost, is a rigorous approach to the validation and
precision testing of age estimates (Campana, 2001). In
this study, a combination of age validation protocols
outlined by Fowler and Doherty (1992) and Campana
(2001) were subscribed to: 1) otoliths must display an
internal structure of increments, (Fig. 3); 2) otoliths
must grow throughout the lives of fish at a perceptible
rate, which was confirmed by the otolith weight-at-age
Table 3
Parameter estimates derived
from the
;wo growth
functions (standard von Berta
anffy growth function,
[VBGFS] and
the two-phase von Bertala
nffy growth
function tVBGFTP|) applied to the length-at
-age data of
striped trumpeter tLatris lineata) in Tasmania. Growth
parameters are defined in the text, NOP =
= number of
parameters in
the model, AIC =
Akaike information cri-
terion, and Lmax = the maximum
length of all individuals
included in th*
growth models.
VBGFS
VBGFTP
Growth
i-l
773.27
532.77
parameters
*i
0.15
0.43
'oi
-1.46
0.03
L"
—
450.11
i-2
—
871.59
*2
—
0.08
?02
—
3.49
r"
—
4.4
a2 oft"
—
1.0
Diagnostics
NOP
3.0
9.0
-log likelihood
3759.98
3700.13
AIC
5335.12
5211.30
% deviation of
-13.7
-2.7
Lm2bomLmal
regression (Table 2); 3) the age of first increment forma-
tion must be determined; and 4) increment periodicity
across the entire age range of interest must be veri-
180
Fishery Bulletin 103(1)
Table 4
Estimates of instantaneous rates of total (Z), natural (M), and fishing IF) mortality for striped trumpeter (Latris lineata) deter-
mined with age-based catch curve analysis and the empirical equations of Hoenig ( 1983 ) and Pauly ( 1980 ). VBGFTP = estimates
derived from the parameters of the two-phase von Bertalanffy growth function, VBGFS = estimates derived from the parameters
of the standard von Bertalanffy growth function and LCCCA = length converted catch curve analysis.
Z
M
F
Method VBGFS VBGFTP VBGFS
VBGFTP VBGFS
VBGFTP
LCCCA 0.253 0.192 —
Hoenig 0.096
Pauly 0.151
0.096 0.157
0.092 0.102
0.096
0.100
fled. We used cultured individuals to determine which
opaque or translucent zone represented the first growth
increment, although the accuracy of age validation with
cultured individuals has been questioned by Campana
(2001). In our study, the close correspondence between
the growth of cultured and wild fish over a period of
several years gives us confidence in using this approach
to validate first increment position. The slightly slower
growth rate observed in cultured striped trumpeter
can be attributed to jaw malformation — a phenomenon
that has been shown to affect feeding ability (Cobcroft
et al., 2001).
Modal progression of the 1993 cohort through time
provided indirect validation for annual periodicity in in-
crement formation up until age seven. Validation across
all age classes was not possible in our study, although
validation after the age of five years was significant.
That is, validation was achieved past the average age
at which fish moved offshore into deeper water, and
past the age at which there was a significant reduction
in growth rate.
The second consideration to address when studying
animal growth is model selection. Akaike's information
criterion is a standard method for model selection that
provides an implementation of Occam's razor, in which
parsimony or simplicity is balanced against goodness-of-
fit (Forster, 2000). However, model selection should not
rely on statistical fit alone; it should also provide a bio-
logically sensible interpretation across the entire range
of ages in the sampled population (Haddon, 2001). In
the case of striped trumpeter, the standard von Berta-
lanffy function provided a poor representation of growth
in older individuals, resulting in an unrealistically low
L r. This problem was largely overcome by the applica-
tion of a two-phase growth function. Similar to that
used on large pelagics, such as Thunnus maccoyii (Bay-
liff et al., 1991; Hearn and Polacheck, 2003). In their
application of the model, Hearn and Polacheck (2003)
considered biological traits when discussing the justi-
fication for age at transference, namely the reduction
in growth rate, and inshore to offshore migration. In
the present study we have considered analogous traits
to seed the age of transference for striped trumpeter.
In this species there is a marked transition in size
structure between shallow and deeper reefs that occurs
at around 450 mm or between 4 and 5 years (Fig. 8).
In addition, a visual assessment of the length-at-age
data highlighted a marked decrease in growth rate at
a similar age.
Solving for the age at transference produced a point
estimate that results in a sharp discontinuity in the
growth curve; an observation that Hearn and Polacheck
(2003) highlighted as biologically unrealistic. The range
of low negative log likelihood values described by the
age at transference profile is due to the patchiness of
data around these ages, creating uncertainty in the
model. We have assumed in this case that the converged
value of 4.4 years is accurate and that the variability
around this point is normally distributed with a stan-
dard deviation equal to one. By including the normal
probability distribution function we have effectively
created a smooth transition between growth phases.
This function implies that age at transference has some
level of inherent variability, which is likely to be more
biologically plausible than knife-edge transition.
A further extension of the two-phase model was test-
ed by applying the seasonal growth version of the VBGF
(described in Eq. 3) to the first phase and a standard
VBGF to the second phase, but was disregarded because
of the effect of over parameterization on parsimony.
However, this approach did highlight the flexibility of
the two-phase model to allow for a more dynamic rep-
resentation of population growth characteristics.
This study supports the assertion by Hearn and Po-
lacheck (2003) that discontinuity in growth rate may
be a more common phenomenon in fish than implied
by growth models reported in the literature. Such a
two-phase growth model, where age at transference
coincides with the transition phase from one fishery to
another, has proven useful. It allows separate growth
parameters to be tracked to each fishery, and as such,
provides a precursor to developing a more biologically
robust production model with dynamic parameters at
age and for fishing method.
The predictive regression developed by Pauly (1980)
that estimates natural mortality is based on the direct
Tracey and Lyle: Age validation, growth modeling, and mortality estimates for Latns lineata
181
relationship between longevity (.tmax) and the magnitude
of the physiological growth parameters k and Lr. As
such, it would be reasonable to assume that if a good
fit exists between length at age that the growth param-
eters, when employed in such an empirical model, would
yield a natural mortality estimate approximately equal
to that determined by a regression model that is based
on tmax (Hoenig, 1983). The two-phase growth function
also provided a more conservative estimate of M than
the standard von Bertalanffy model. Overestimates of
M can lead to unrealistically high estimates of produc-
tivity and a potential yield that may in turn lead to
overexploitation of a stock.
Protracted longevity, slow growth in later life, large
body size, recruitment variability, and relatively low
natural mortality once individuals reach adulthood are
all characteristics typical of a K-selected species (where
equilibrium is the biological strategy). Such species are
often regarded as being susceptible to growth over-fish-
ing and stock depletion (Booth and Buxton, 1997). For
instance, increased fishing effort on the inshore fishery,
as has been observed with the recruitment of strong
cohorts, will affect subsequent recruitment to the off-
shore fishery and spawning stock. The current analysis
indicates that fishing mortality is slightly higher than
natural mortality and, in the absence of further strong
recruitment, a decline in the stock size is likely if fish-
ing pressure is not reduced.
Acknowledgments
The authors gratefully acknowledge Ray Murphy and
Alan Jordan who collected many of the earlier samples
and undertook preliminary examination of the otoliths.
The assistance of the captain and crew of FRV Challenger
in collecting samples is also thankfully acknowledged.
Philippe Ziegler, Dirk Welsford, and Malcolm Haddon
provided constructive criticism and ideas in terms of the
analyses and reviewed the manuscript; Sarah Irvine and
an anonymous reviewer provided constructive feedback
on final versions of this manuscript.
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183
Abstract — Morphological develop-
ment of the larvae and small juve-
niles of estuary perch {Macquaria
colonorum) 1 17 specimens, 4.8-13.5
mm body length) and Australian bass
(M. novemaculeata) (38 specimens,
3.3-14.1 mm) (Family Percichthyidae)
is described from channel-net and
beach-seine collections of both species,
and from reared larvae of M. novemac-
uleata. The larvae of both are charac-
terized by having 24-25 myomeres, a
large triangular gut (54-67% of BL)
in postflexion larvae, small spines
on the preopercle and interopercle,
a smooth supraocular ridge, a small
to moderate gap between the anus
and the origin of the anal fin, and
distinctive pigment patterns. The two
species can be distinguished most
easily by the different distribution
of their melanophores. The adults
spawn in estuaries and larvae are
presumed to remain in estuaries
before migrating to adult freshwa-
ter habitat. However, larvae of both
species were collected as they entered
a central New South Wales estuary
from the ocean on flood tides; such
transport may have consequences for
the dispersal of larvae among estuar-
ies. Larval morphology and published
genetic evidence supports a reconsid-
eration of the generic arrangement of
the four species currently placed in
the genus Macquaria.
Larval development of estuary perch
(Macquaria colonorum) and Australian bass
(M novemaculeata) (Perciformes: Percichthyidae),
and comments on their life history
Thomas Trnski
Amanda C Hay
Ichthyology. Australian Museum
6 College Street
Sydney, New South Wales 2010, Australia
E-mail address (for T Trnski, senior author): tomt@austmus gov au
D. Stewart Fielder
New South Wales Fisheries
Port Stephens Fisheries Centre
Private Bag 1
Nelson Bay, New South Wales 2315, Australia
Manuscript submitted 20 November 2003
to the Scientific Editor's Office.
Manuscript approved for publication
15 June 2004 by the Scientific Editor.
Fish. Bull. 103:183-194 (2005).
The Percichthyidae is a family of
freshwater fishes restricted to Aus-
tralia (8 genera, 17 species) and South
America (2 genera, 7 species) (John-
son, 1984; Nelson, 1994; Allen et al.,
2002; Paxton et al., in press). There is
continuing debate regarding the mono-
phyly of the family; several genera are
variously allocated to separate fami-
lies: Gadopsis is allocated to Gadop-
sidae (Allen et al., 2002; see Johnson,
1984 for a history of the systematic
placement of the genus) and Edelia,
Nannatherina, and Nannoperca are
allocated to Nannopercidae (Allen et
al., 2002). Other Australian genera
of Percichthyidae include Bostockia,
Guyu, Maccullochella , and Macquaria
(Pusey and Kennard, 2001; Allen et
al., 2002; Paxton et al., in press). The
genera Percolates and Plectroplites
were synonymized with Macquaria,
based on morphological and biochemi-
cal characters (MacDonald, 1978),
and although this arrangement was
accepted by Paxton and Hanley (1989),
Paxton et al. (in press), Eschmeyer
(1998), Johnson (1984), and Nelson
(1994) recognized both Percolates and
Plectroplites as valid genera.
There are four described species in
the genus Macquaria, all confined to
southeastern Australia. Macquaria
ambigua occurs naturally in fresh-
waters of the Murray-Darling river
system and has been translocated
outside of its natural range (Kai-
lola et al., 1993; Allen et al., 2002).
There is genetic evidence for an ad-
ditional undescribed freshwater spe-
cies closely related to M. ambigua
from central Australian drainages
(Musyl and Keenan, 1992). Mac-
quaria australasica is also confined
to freshwater of the Murray-Darling
river system, and an isolated popu-
lation exists from the Shoalhaven
and Hawkesbury Rivers, New South
Wales (Allen et al„ 2002) that may be
a separate species (Dufty, 1986). The
other two species (M. colonorum and
M. novemaculeata) are catadromous
and occur in coastal southeastern
Australian drainages between south-
ern Queensland and eastern South
Australia (Paxton et al., in press).
They are sympatric from northern
New South Wales (NSW) to eastern
Victoria. Adults of M. novemaculeata
occur in freshwater, whereas M. colo-
norum prefers brackish water of estu-
aries (Williams, 1970). Both species
migrate to estuarine areas to breed
in winter (Allen et al., 2002). Both
species are protected from commer-
cial fishing but are highly prized by
recreational fishermen (Harris and
Rowland, 1996; Allen et al., 2002)
and M. novemaculeata is an impor-
tant aquaculture species.
184
Fishery Bulletin 103(1)
Of the 17 Australian percichthyids, larvae of only
Maccullochella macquariensis, M. peelii peelii, and
Macquaria ambigua have been described (Dakin and
Kesteven, 1938; Lake, 1967; Brown and Neira, 1998).
Larval and early juvenile development of the estuary
perch (Macquaria colonorum) and the Australian bass
(Macquaria novemaculeata) is described from specimens
collected from the central and southern coast of NSW,
and from reared larvae of the latter species obtained
from brood stock from central NSW. This is the first
description of the morphological development of the
early life history of these two species.
Materials and methods
Morphological definitions, measurements, and abbrevia-
tions follow Neira et al. (1998) and Leis and Carson-
Ewart (2000). Larvae and juveniles were examined and
measured under a dissecting microscope at magnifica-
tions from 6 to 50x. Precision of the measurements
varied with magnification but ranged from 0.02 to 0.16
mm. Where morphometric values are given as a percent-
age, they are as a proportion of body length (BL) unless
otherwise indicated. All pigment described is external
unless otherwise specified. The juveniles collected are
in transition from larvae to juveniles because they
retain some of their larval characters and squamation
is incomplete; these are called "transitional juveniles"
( Vigliola and Harmelin-Vivien, 2001). Illustrations were
prepared with a Zeiss SR with an adjustable drawing
tube.
Field-caught larvae were collected in a fixed 2-m2
channel net with about 1-mm mesh in Swansea Chan-
nel, Lake Macquarie, central NSW. The net filtered
surface waters to 1 m depth during night flood tides
(Trnski, 2002). Small juveniles were collected in a 30-m
beach seine dragged over sand, mud, and Zostera sea-
grass in the Clyde River, southern NSW. Reared larvae
of M. novemaculeata were obtained from rearing tanks
at the Port Stephens Fisheries Centre, an aquaculture
research facility of NSW Fisheries. Brood stock came
from the Williams River, central NSW. All specimens
were initially fixed in 10% formalin and subsequently
transferred to 70% ethanol.
Field-caught larvae were restricted to a narrow size
range: 4.8-7.1 mm body length (BL) for M. colono-
rum (n=12), and 4.6-7.6 mm BL for M. novemaculeata
(n=15). Juveniles of both species ranged from 10.3 to
13.5 (n = 5) and from 10.1 to 14.1 mm BL (n = 5), respec-
tively. Reared larvae of AT. novemaculeata were available
to confirm the identification of the larvae and to extend
the developmental series for this species to 3.3-10.2
mm BL (ra=18).
All material examined is registered in the fish collec-
tion at the Australian Museum. Registration numbers
of M. colonorum larvae are AMS 1.20052-010, 1.41690-
005 to -008, 1.41691-002, 1.41692-001, 1.41693-001;
M. novemaculeata are AMS 1.20052-012, 1.27051-013,
1.41561-001 to -008, 1.41590-001, 1.41641-001, 1.41661-
001 and -002, 1.41662-001, 1.41668-001, 1.41690-001 to
-0004, 1.41691-001, 1.41694-001.
Identification
Field-caught larvae and juveniles were identified as per-
cichthyids by using the characters in Brown and Neira
(1998), particularly the combination of a relatively large
gut, the small to moderate gap between the anus and
origin of the anal fin prior to complete formation of the
anal-fin, continuous dorsal fin, fin-ray, and vertebral
counts, and head spination including small preopercular
spines, a small interopercular spine, and a smooth supra-
ocular ridge. The larvae and juveniles described here
were confirmed as being Macquaria colonorum and M.
novemaculeata because of their coastal distribution and
meristics; all other species in the family are restricted
to freshwater. The overlap in meristics between M. colo-
norum and M. novemaculeata made separation of the
species difficult. The availability of reared M. novemacu-
leata from positively identified adults determined the
species allocations.
Results
Development of Macquaria colonorum
Adult meristic data Dorsal (D) IX-X,8-11; Anal (A)
111,7-9; Pectoral (Pj) 12-16; Pelvic (P2) 1,5; Vertebrae 25
17 specimens: 4.8-7.1 and 10.3-13.5 mm BL
General morphology (Tables 1 and 2, Fig. 1) Larvae
and transitional juveniles are moderately deep bodied
(body depth, BD 30-35%). The body and head are lat-
erally compressed. There are 24-25 myomeres (12-14
preanal and 11-13 postanal). The large, triangular gut
is fully coiled in the smallest larva examined. The pre-
anal length ranges from 60% to 67%. The conspicuous
gas bladder located over the midgut is small to moder-
ate in size but difficult to distinguish in transitional
juveniles. The round to slightly elongate head is large
(head length, HL 32-41%). The snout is slightly concave
to straight. The snout is approximately the same length
as the eye diameter but becomes shorter from 7 mm.
The eye is round and moderate in size (27-32% of HL)
in larvae but becomes moderate to large in transitional
juveniles (32-36% of HL). The large mouth reaches to
the middle of the pupil. Small canine teeth are present
in both jaws in all larvae examined. The nasal pit closes
shortly after settlement, by 12.5 mm.
Head spination is weak. Three short spines are pres-
ent on the posterior preopercular border in the small-
est larva examined; a fourth spine is present in some
postflexion larvae from 6.3 mm and in all transitional
juveniles. The spine at the angle of the preopercle is
longest but remains shorter than the pupil diameter.
A minute interopercular spine is present from 6.0 mm
and persists in all transitional juveniles. A low, smooth
Trnski et al : Larval development of Macquana colonorum and M. novemaculeata
185
Table 1
Morphometric
data for Macquaria colonorum la
•vae from channel-net samples
and juveniles
from beach-seine
samples.
Measurements
are in mm. VAFL =
: vent to anal-fin
length.
Preanal
Predorsal
Body
Head
Snout
Eye
Body length
length
length
depth
length
length
diameter
VAFL
Flexion
4.80
3.40
2.48
1.49
1.96
0.58
0.58
0.04
5.10
3.40
3.00
1.60
1.88
0.60
0.56
0
5.40
3.40
2.80
1.60
1.72
0.50
0.50
0
5.48
3.32
2.91
1.74
1.80
0.56
0.56
0
Postflexion
5.73
3.49
2.80
1.99
2.08
0.56
0.60
0
5.98
3.68
3.24
1.99
2.04
0.60
0.60
0
6.00
3.72
2.60
1.92
2.00
0.50
0.60
0
6.31
3.98
2.57
2.16
2.20
0.60
0.68
0
6.60
4.00
3.00
2.20
2.40
0.64
0.64
0
6.81
4.15
3.07
2.16
2.32
0.66
0.66
0
7.00
4.32
3.32
2.08
2.24
0.60
0.72
0
7.10
4.36
2.91
2.32
2.28
0.60
0.72
0
Settled
10.29
6.81
4.81
3.15
3.74
0.91
1.25
0
10.62
6.81
4.98
3.24
3.90
0.95
1.25
0
11.29
7.47
5.56
3.74
4.48
1.00
1.58
0
12.45
7.97
5.64
4.15
4.57
1.00
1.66
0
13.45
8.70
6.64
4.48
5.23
1.41
1.83
0
Table 2
Meristic data for Macquaria colonorum
arvae and juveniles. ( ) indicates only fin
bases present, [ ] incipient rays or spines, 1 1 ray
transforming to a spine
d = damaged.
Body length
Dorsal
Anal
Pectoral
Pelvic
Caudal
Myomeres
Flexion
4.80
(V), 9
(D,8[l]
9+711]
14+11=25
5.10
d, (10)
(I),9
[1]8+7[1]
13+11=24
5.40
d, (9)
(II), 9
[2]
9+8
13+12=25
5.48
(III), 9
(II), 8
3
9+8
12+12=25
Postflexion
5.73
(IV), 11
(II), 8
5
9+8
13+12=25
5.98
(V), 10
(II),8
2
9+8
13+12=25
6.00
(IV), 10
(II), 8
3
9+8
13+12=25
6.31
(IV)I, 11
[II], 9
9
buds
9+8
13+12=25
6.60
IV, 11
11,9
5
buds
9+8
13+12=25
6.81
VII, 11
II, 10
9
buds
9+8
13+12=25
7.00
VII, 11
II, 10
5(d)
buds
9+8
12+13=25
7.10
VIII, 10
11111,9
inn
buds
9+8
14+11=25
Settled
10.29
VIII II), 10
11111,8
15
1,5
7+9+8+6
13+12=25
10.62
VIII III, 10
Hill, 8
13
1,5
7+9+8+4
12+13=25
11.29
IX, 10
111,8
15
1,5
7+9+8+8
12+13=25
12.45
IX, 10
111,8
14
1,5
12+9+8+7
12+13=25
13.45
IX, 10
111,9
14
1,5
9+9+8+8
12+13=25
186
Fishery Bulletin 103(1)
A 4.8 mm
B 7.1 mm
C 10.3
D
12.5 mm
Figure 1
Larvae of Macquaria colonorum. (A and B) postflexion larvae from Swansea Chan-
nel, central New South Wales (NSW) (C and D) recently settled juveniles from the
Clyde River, southern NSW.
supraocular and supracleithral ridge form by the time
notochord flexion is complete. A weak posttemporal
ridge is present from 7 mm, and a small spine develops
in transitional juveniles from 11.3 mm. A small spine
develops on the supracleithrum from 10.6 mm. An oper-
cular spine is present in transitional juveniles.
Dorsal-fin soft rays are ossified by the completion of
notochord flexion, the posteriormost rays being the last
to ossify. The pterygiophores of the spinous rays of the
dorsal fin develop from posterior to anterior and begin
to form during notochord flexion. Spines begin to ossify
in postflexion larvae by 6.3 mm, and the full comple-
ment of dorsal-fin elements is present by 7.1 mm. All
soft rays of the anal fin are ossified by the completion
of notochord flexion, by which time 1-2 pterygiophores
of the spinous rays are present. The first two anal-fin
spines are ossified by 6.6 mm. The last spinous soft ray
of the dorsal and the third spinous ray of the anal fin
transforms from a soft ray after settlement and they
are fully transformed by 11.3 mm. Incipient rays begin
to form in the pectoral fin during notochord flexion,
and the rays ossify from dorsal to ventral in postflex-
ion larvae. A few pectoral-fin rays remain unossified
at 7.1 mm and are fully ossified prior to settlement.
Trnski et al.: Larval development of Macquana colonorum and M. novemaculeata
187
Pelvic-fin buds appear in postflexion larvae from 6.3
mm, but no elements have formed in the largest speci-
men; they are all ossified in the transitional juveniles.
All primary caudal-fin rays are ossified by the end of
notochord flexion. Procurrent caudal rays are present in
the transitional juveniles. Notochord flexion commences
before 4.8 mm, and is complete by 5.7 mm. Scales have
not begun to develop in the largest transitional juvenile
examined (13.5 mm).
Pigment (Fig. 1, A-D) Larvae are moderately to heav-
ily pigmented; melanophores are concentrated on the
dorsal and ventral midlines, and midlateral surface of
the trunk and tail. Small expanded melanophores are
present at the tips of the upper and lower jaws, and
there are one or two melanophores ventral to the nasal
pit. Additional internal melanophores are present along
the roof of the mouth, and posterior to the eye below
the mid- and hindbrain. External melanophores may
be present on the operculum in line with the eye. One
or two melanophores are present on the ventral midline
of the lower jaw, and there is one at the angle of the
lower jaw.
Four to seven large, expanded melanophores are pres-
ent along the dorsal midline of the trunk and tail, from
the nape to just posterior to the dorsal-fin base. There
are one or two melanophores on the nape and four or
five along the dorsal-fin base. A series of large, expand-
ed melanophores is present along the lateral midline of
the trunk and tail, commencing at the gas bladder and
extending to the posterior end of the dorsal and anal
fins. In postflexion larvae, this series extends onto the
anterior third of the caudal peduncle. Internal melano-
phores are present over the gas bladder, the mid- and
hindgut, and may be present along the notochord. The
external and internal pigment series thus give the im-
pression of a line of heavy pigment from the tip of the
snout, across the head and trunk, to the tail.
Small melanophores are present along the ventral
midline of the gut; one melanophore on the isthmus
immediately anterior to the cleithral symphysis, usually
three (range: 2-4) melanophores between the cleithral
symphysis and pelvic-fin base, and usually three (range:
1-4) melanophores between the pelvic-fin base and the
anus. Expanded melanophores are present along the
ventral midline of the tail, from above the anus to the
posterior end of the anal-fin base. Between one and
three melanophores occur along the anal-fin base. A
small melanophore is occasionally present in early post-
flexion larvae at the base of ventral primary caudal-fin
rays 1-2.
In transitional juveniles, the expanded melanophores
are relatively smaller, and are most prominent midlat-
erally along the trunk and tail. The expanded melano-
phores along the dorsal and ventral midlines become
small to absent during the juvenile stage. Additional ex-
panded melanophores develop laterally on the head and
body, and the dorsal and anal fins become pigmented.
Small melanophores cover the head and body — coverage
lightest ventrally on the head and gut. Three broad
vertical bands become apparent dorsally on the nape,
below the center of the spinous dorsal fin and below the
center of the soft dorsal fin by 13.5 mm.
Development of Macquaria novemaculeata larvae
Adult meristic data D VIII-X,8-11; A 111,7-9; Pj 12-16;
P2 1,5; Vertebrae 25; 38 specimens: 3.3-14.1 mm BL
Eggs and hatching Eggs are approximately 900 pm
in diameter and have multiple oil globules. Larvae are
3.3 mm SL at time of hatching.
General morphology (Tables 3 and 4, Fig. 2) Yolksac
and early preflexion larvae are elongate (BD 15-18%),
but in late preflexion and flexion larvae, body depth
becomes moderate (BD 26-34%). Body depth of field-
caught postflexion larvae ranges from 29%. to 35%,
and in transitional juveniles from 33% to 34%. Reared
postflexion larvae and transitional juveniles are deeper
than wild larvae, ranging from 32% to 44%, which is an
artifact of the extremely full guts in the reared larvae.
Body depth decreases abruptly posterior to the anus,
although this becomes less marked with development.
The head and body are laterally compressed. There
are 25 myomeres (10-13 preanal+12-15 postanal). In
general, there are 10-12 preanal myomeres in preflex-
ion and flexion larvae, and 12-13 preanal myomeres in
postflexion larvae and transitional juveniles. The gut
is initially straight in yolksac larvae but is coiled by
3.9 mm. The gut is oval to triangular in shape; preanal
length reaches 44-56% of BL in yolksac and preflexion
larvae, 54-60% in flexion stage larvae, and 54-66% in
postflexion larvae and transitional juveniles. The gut
mass is large, particularly in reared postflexion larvae
and transitional juveniles. The conspicuous gas blad-
der, which is located over the midgut, is moderate to
large in size, except in the yolksac larvae where it is
small and inconspicuous. The head is round and small
in yolksac larvae (HL 15-16%), moderate in preflexion
larvae (HL 22-31%), and becomes moderate to large in
flexion (29-35%) and postflexion larvae and transitional
juveniles (32-38%). The snout is always shorter than the
eye diameter and is initially concave, but becomes convex
to straight in postflexion larvae. The eye is moderate to
large (27-36% of HL) but is relatively larger in yolksac
larvae (42-45% of HL). The eye is initially unpigmented,
but is fully pigmented by 3.6-3.8 mm, prior to the com-
plete absorption of the yolk. The moderate mouth reaches
to the middle of the pupil. Small canine teeth appear
in both jaws in late preflexion larvae by 4.4 mm. The
number of teeth increases with development. The nasal
pit begins to close by 8.6 mm, and both nostrils are
developed by 10.3 mm.
Head spination is weak. A small spine appears at
the preopercular angle by the end of the preflexion
stage. By the time notochord flexion is complete, there
are three spines on the posterior preopercular border,
and the spine at the angle is the longest. All spines
are shorter than the pupil diameter. Additional spines
188
Fishery Bulletin 103(1)
Table 3
Morphometric data for Macquaria
by "R"), and juveniles from beach-
novemaculeata larvae from channel net samples
seine samples. Measurements are in mm. VAFL
and reared in aquaria (body length preceded
= vent to anal-fin length.
Body length
Preanal
length
Predorsal
length
Body
depth
Head
length
Snout
length
Eye
diameter
VAFL
Yolksac
R3.32
1.48
0.52
0.53
0.16
0.24
R3.60
1.60
0.58
0.53
0.16
0.22
Preflexion
R3.60
2.00
0.92
0.96
0.24
0.34
R3.80
2.00
1.00
1.04
0.30
0.38
R3.90
1.76
0.64
0.84
0.18
0.30
R4.20
2.00
0.64
0.93
0.20
0.33
R4.40
2.00
0.78
1.06
0.26
0.34
4.57
2.36
2.16
1.20
1.40
0.28
0.40
0.22
Flexion
5.00
2.72
2.40
1.52
1.48
0.32
0.48
0.12
5.14
2.90
2.32
1.48
1.76
0.44
0.48
0.10
R5.31
2.84
2.60
1.40
1.60
0.48
0.56
0.20
5.39
2.74
2.66
1.58
1.60
0.40
0.48
0.12
R5.39
2.90
2.66
1.36
1.56
0.40
0.56
0.20
5.47
2.80
2.74
1.60
1.72
0.44
0.48
0.12
R5.47
3.00
2.60
1.56
1.76
0.52
0.60
0.12
5.70
3.40
2.92
1.96
2.00
0.52
0.56
0.06
5.90
3.32
2.90
1.80
1.88
0.52
0.56
0.04
Postflexion
5.64
3.07
2.41
1.66
2.00
0.52
0.60
0.08
5.89
3.52
2.64
2.00
2.00
0.52
0.60
0.06
6.06
3.32
2.81
1.99
2.00
0.52
0.56
0.10
6.30
3.40
2.57
1.91
1.99
0.50
0.60
0.20
6.60
3.73
2.91
2.24
2.08
0.50
0.66
0
6.72
3.74
2.82
2.24
2.16
0.60
0.64
0.08
R6.72
3.74
2.60
2.16
2.16
0.52
0.76
0.08
R7.20
3.98
3.00
2.32
2.28
0.52
0.68
0.08
7.40
4.15
3.02
2.49
2.32
0.66
0.72
0
R7.47
4.15
3.04
2.49
2.48
0.64
0.72
0.08
7.55
4.30
3.15
2.66
2.57
0.66
0.72
0
R8.18
5.31
3.49
3.07
2.91
0.75
0.91
0
R8.60
5.56
4.15
3.24
3.24
0.83
1.08
0
R9.20
5.56
3.98
3.75
3.50
0.75
1.21
0
Settled
10.13
6.64
4.81
3.49
3.65
0.83
1.33
0
R 10.20
6.64
4.57
3.74
3.74
0.83
1.33
0
R 10.30
6.64
4.57
3.99
3.82
1.05
1.33
0
11.62
7.55
5.56
3.82
4.23
1.00
1.49
0
11.62
7.55
5.47
3.98
4.39
1.07
1.49
0
13.28
8.30
5.98
4.56
4.98
1.41
1.66
0
14.10
8.63
6.47
4.65
5.15
1.41
1.74
0
Trnski et al.: Larval development of Macquana colonorum and M novemaculeata
189
Table 4
Meristic data of Macquaria novemaculeata larvae and juveniles. Body length preceded by
ium. ( ) indicates only fin bases present. [ 1 incipient rays or spines, 1 1 ray transforming to a
'R" indicates larvae
spine.
reared in aquar-
Body length
Dorsal
Anal
Pectoral
Pelvic
Caudal
Myomeres
Yolksac
R3.32
10+15=25
R3.60
11+14=25
Preflexion
R3.60
12+13=25
R3.80
11+14=25
R3.90
11+14=25
R4.20
10+15=25
R4.40
10+15=25
4.57
(9)
(8)
[2+3]
10+15=25
Flexion
5.00
(VI), (6)
(8)
7+6
10+15=25
5.14
(VI), (8)
(9)
8+7
10+15=25
R5.31
(III), (9)
(8)
[7+6]
12+13=25
5.39
(IV), [9]
(I), 19]
8+7
11+14=25
R5.39
(III), (9)
(9)
6+6
12+13=25
5.47
(V), [8]
[II, [7]
[1]7+7[1]
11+14=25
R 5.47
(VI), [101
(I), |8](1)
[1)8+7[1]
12+13=25
5.70
VI, 10
(I),8
6
9+8
13+13=26
5.90
[I]V, 10
(I), 8
6
9+8
12+13=25
Postflexion
5.64
VI, 10
(I),9
5
9+8
10+15=25
5.89
[VI], 10
(I), 9
5
9+8
12+13=25
6.06
VI, 10
(I), 9
6
9+8
12+13=25
6.30
VI, 11
1,9
6
buds
9+8
11+14=25
6.60
VI, 11
1,9
8
9+8
12+13=25
6.72
VI, 11
1,9
8
buds
9+8
12+13=25
R6.72
VI, 10
1,9
12
buds
9+8
12+13=25
R7.20
VII, 11
11,9
10
buds
9+8
12+13=25
7.40
VII, 11
11.9
12
buds
9+8
13+12=25
R7.47
VII, 11
11,9
13
buds
9+8
12+13=25
7.55
VII, 11
11,9
12
buds
9+8
12+13=25
R8.18
VIII. 11
11,9
13
1,5
9+8
13+12=25
R8.60
VIII, 11
11,8
13
1,5
9+8
13+12=25
R9.20
IX, 10
11111,7
15
1,5
9+8
13+12=25
Settled
10.13
IX, 10
11111,8
14
1,5
7+9+8+7
12+13=25
R 10.20
IX, 10
11111,8
14
1,5
9+8
13+12=25
R 10.30
IX, 10
11111,8
14
1,5
9+8
13+12=25
11.62
VIII 111,10
11111,8
14
1,5
9+9+8+8
13+12=25
11.62
IX, 9
11111,8
14
1,5
8+9+8+7
13+12=25
13.28
IX, 10
111,8
14
1,5
7+9+8+9
12+13=25
14.1
IX, 10
111,8
14
1,5
9+9+8+7
12+13=25
190
Fishery Bulletin 103(1)
A 4.4
B 46
C 5.4
D 67
E 10.3 mm
13.3
Figure 2
Larvae of Macquaria novemaculeata. (A) yolksac larva, 10 days after hatching, note
remnant of yolk below pectoral-fin base; (B) preflexion larva; (C) flexion stage larva;
(D) postflexion larva; (E) postflexion larva, 57 days after hatching; (F) recently
settled juvenile. Specimens A and E were reared at Port Stevens Fisheries Centre,
New South Wales (NSW); B-D from Swansea Channel, central NSW; specimen F is
a recently settled juvenile from the Clyde River, southern NSW.
Trnski et al.: Larval development of Macquana colonorum and M. novemaculeata
191
form as larvae develop; four or five spines are present
in larvae and transitional juveniles from 7.5-8.2 mm.
A minute spine (rarely two) develops on the anterior
preopercular border from 9 mm; a third spine devel-
ops in transitional juveniles from 13.3 mm. A small
interopercular spine develops by the time notochord
flexion is complete. Low posttemporal and supraocular
ridges, but no spines, develop during notochord flexion;
they both become inconspicuous in postflexion larvae
from 8.2 and 8.6 mm, respectively. An opercular spine
is present from 8.6 mm. A small supracleithral spine is
present in transitional juveniles from 10.1 mm.
The pterygiophores of all the soft rays and up to six
of the pterygiophores of the first dorsal fin form during
notochord flexion. Soft rays of the dorsal fin are ossi-
fied by the time notochord flexion is complete, whereas
spinous rays ossify from posterior to anterior in late
flexion and early postflexion larvae by 5.7-6.1 mm. The
full complement of spines is present by 8.2 mm. Anal-
fin pterygiophores form during notochord flexion, and
all soft rays are ossified by the time notochord flexion
is complete. Spinous rays of the anal fin begin to ossify
in postflexion larvae by 6.3 mm, and all anal-fin ele-
ments are present by 7.2 mm. The last spinous ray of
the dorsal fin and the third spinous ray of the anal fin
transform from a soft ray between 7.6 and 9.2 mm. Pec-
toral-fin elements begin to ossify by the time notochord
flexion is complete, and all rays are present in postflex-
ion larvae by 7.5 mm. Pelvic-fin buds form in postflexion
larvae by 6.7 mm, and all elements are ossified by 8.2
mm. Caudal-fin rays first appear in preflexion larvae
from 4.6 mm, and all principal rays are ossified by the
time notochord flexion is complete. Procurrent caudal
rays are present in field-caught transitional juveniles.
Notochord flexion commences between 4.6 and 5.0 mm,
and is complete by 5.6-6.1 mm. There is a prominent
gap between the anus and anal fin while the anal fin
forms (vent to anal-fin length [VAFL] up to 5% of BL).
The gap reduces in size as the anal fin develops, and it
is absent by 7.6 mm. Scales have not developed in the
largest specimen examined.
Pigment (Fig. 2, A-F) Larvae are moderately to heav-
ily pigmented. An expanded melanophore is present on
the tip of the snout and a small melanophore develops
under the tip of the lower jaw in preflexion larvae from
3.6 mm. A second melanophore on the snout develops
posterior to the first by the time notochord flexion is
complete. A single melanophore is present at the angle
of the lower jaw. A few small melanophores develop
ventrally along the lower jaw in postflexion larvae from
7.2 mm. A series of internal melanophores underlie the
mid- and hindbrain.
There are two very large expanded melanophores
on the dorsal midline of the tail; the first is on the
trunk centered over the hindgut, and the second is
mid way along the tail. Once the dorsal fin forms they
are centred under the middle of the spinous portion of
the dorsal fin and under the posterior end of the soft
dorsal fin, respectively. An additional smaller expanded
melanophore is present from 7.2 to 7.5 mm on the dorsal
midline of the nape above the pectoral-fin base.
Two very large expanded melanophores occur ven-
trally, opposite the two large dorsal melanophores. The
anteriormost of these melanophores reduces in promi-
nence as larvae develop and is inconspicuous to absent
by metamorphosis. Internal expanded melanophores
over the gas bladder may have filaments that emerge
externally, particularly in preflexion and flexion lar-
vae. Internal melanophores along the notochord may
be apparent on the caudal peduncle in postflexion lar-
vae from 7 mm. There is an expanded melanophore on
the midline of the isthmus, immediately anterior to
the cleithral symphysis. A series of three to six small,
expanded melanophores is present along the ventral
midline of the gut. In postflexion larvae there is a bi-
laterally paired melanophore anterior to the pelvic-fin
base, and two to four melanophores along the midline
of the gut between the pelvic-fin base and the anus. A
small contracted melanophore ventrally on the posterior
margin of the caudal-fin base develops between 5.0 and
6.1 mm, and is located between ventral rays 1-5. This
melanophore expands from 6.7 to 7.6 mm and spreads
across up to four ray bases.
Pigment distribution spreads rapidly over most of the
head from 7.2 to 7.5 mm, and laterally on the trunk,
gut and tail from 8.2 mm. The expanded melanophores
on the dorsal and ventral midlines of the trunk and
tail remain large as the larvae develop; the posterior-
most of these increases in intensity in reared larvae.
The expanded melanophores on the dorsal and ventral
midlines of the body become relatively smaller after
settlement. By settlement, small melanophores develop
on the membranes of the pectoral, pelvic, anal, and cau-
dal fins, and the membrane of the spinous portion of the
dorsal fin becomes heavily pigmented. After settlement,
small melanophores cover most of the head and body,
but the heaviest cover is seen dorsally. Three broad
vertical bands become apparent dorsally on the nape,
below the center of the spinous dorsal fin, and below
the center of the soft dorsal fin in the largest specimen
examined (14.1 mm).
Discussion
Adults of M. colonorum and M. novemaculeata, which
have only minor morphological differences, such as the
relative length of the snout, the profile of the head dor-
sally, postorbital head length, and gill-raker counts, are
difficult to distinguish (Williams, 1970). None of these
characters are useful for distinguishing larvae. The
larvae of these two species could be positively identified
only by comparison with reared larvae derived from
positively identified brood stock.
Melanophore distribution is the most distinguishing
character between the larvae of M. colonorum and M.
novemaculeata. Macquaria colonorum has between four
and seven expanded melanophores along the dorsal
midline of the trunk and tail between 4.8 and 7.1 mm.
192
Fishery Bulletin 103(1)
Macquaria novemaculeata has only two melanophores,
and these are much larger; a third expanded melano-
phore develops on the nape from 7.2 mm. In addition,
M. novemaculeata lacks a midlateral series of melano-
phores along the tail until settlement, and it is never
as well developed as that in M. colonorum. On the other
hand, M. colonorum has a prominent midlateral series
until after settlement. One other morphological char-
acter that distinguishes the larvae is a snout length
which is about equal to eye diameter in M. colonorum
larvae until 7 mm, but snout length is always smaller
than the eye diameter in M. novemaculeata.
Within the genus Macquaria, larval development of
only M. ambigua has been described (Lake, 1967; Brown
and Neira, 1998). There are several differences in the
life history and development of the larvae of M. ambig-
ua compared with M. colonorum and M. novemaculeata.
Macquaria ambigua is restricted to freshwater, the eggs
are large (3.3-4.2 mm in diameter, compared with 0.9
mm in reared M. novemaculeata) and the yolk sac in
M. ambigua is large in small larvae and is not resorbed
until the flexion stage (Brown and Neira, 1998). Com-
pared with the larvae described in the present study,
larvae of M. ambigua have more myomeres (24-28, but
typically 26-27), and these larvae are relatively large
by the time they complete notochord flexion (7.3 mm).
They also lack an interopercular spine and supraocular
ridge, and lack dorsal and lateral pigment on the tail
until the postflexion stage.
Larvae of several other generalized percoid families
are morphologically similar to Macquaria, including
Latidae (Trnski et al., 2000), Microcanthidae (Walker et
al., 2000a), Kyphosidae (Walker et al., 2000b), and some
Apogonidae (Leis and Rennis, 2000). The latid genus
Lates is morphologically most similar to the Macquaria
larvae described in the present study but is tropical
and does not have an overlapping distribution with
Macquaria. Lates can be distinguished by the small size
at notochord flexion (3.0-3.8 mm), dorsal and pectoral
fin-ray counts when complete, and heavier melanophore
distribution at a given size. Microcanthid and kyphosid
larvae can be distinguished from coastal percichthyid
larvae by the higher number of fin elements in the
dorsal and anal fins, and the presence of supracleithral
spines that are absent in larval percichthyids until the
juvenile stage. Some deep-bodied apogonids resemble
Macquaria larvae but can be distinguished by having
separate spinous and soft dorsal fins and a large, con-
spicuous gas bladder.
Larvae of M. colonorum and M. novemaculeata were
collected in Swansea Channel from July to August. This
collection period coincides with adults of M. novemacu-
leata spawning from June to September in central New
South Wales (Harris, 1986). Macquaria colonorum prob-
ably spawns at a similar time (McCarraher and McK-
enzie, 1986), and eggs have been collected from June to
November in western Victoria (Newton, 1996). Adults of
both species are thought to spawn in the middle reaches
of estuaries at salinities above 8-10 g/kg (Harris, 1986;
McCarraher, 1986), but M. novemaculeata will spawn in
waters up to 35 g/kg in culture (Battaglene and Selosse,
1996). The optimal conditions for incubation and hatch-
ing of M. novemaculeata eggs are 18 [±1]°C and salinity
at 25 to 35%r (van der Wal, 1985). Eggs are buoyant
within this salinity range and hatch in 42 h at 18 C.
The presence of field-caught larvae of both species
on incoming tides in Swansea Channel indicates that
the larvae have spent some time in the ocean and that
the eggs were potentially spawned in the ocean rather
than in an estuary if they were not carried out to sea
by outgoing tides. Macquaria novemaculeata adults
move downstream into estuaries to spawn in water of
suitable salinity. In low rainfall years, the spawning
location is further upstream than in wet years, when
spawning can occur in shallow coastal waters adjacent
to estuaries (Searle1). Mature M. novemaculeata adults
can be found outside of estuaries in wet years (Williams
1970). This is verified by the collection of mature adults
by trawl in July 1995 in 11-17 m of water off Newcastle,
NSW (AMS 1.37358-001). Macquaria colonorum adults
have also been collected on the continental shelf (Mc-
Carraher and McKenzie, 1986). In addition, larvae can
tolerate waters of marine salinity in culture, and late in
their larval phase wild larvae can tolerate marine sa-
linity as shown from our field collections. The presence
of larvae and adults in continental shelf waters may
provide two modes of dispersal among estuaries. Thus,
these two species of Macquaria may not be confined to
freshwater and estuarine conditions as often assumed
(Harris and Rowland, 1996; Allen et al., 2002).
The smallest juveniles of M. colonorum and M.
novemaculeata collected in the wild are from the Clyde
River estuary, southern NSW. These range in size from
10 to 14 mm SL, and were collected among Zostera sea-
grass. They are morphologically similar to the largest
pelagic larvae collected in the channel net in Swansea
Channel. Based on the largest larvae and smallest
juveniles, settlement occurs between 7.1 and 10.3 mm
SL in M. colonorum and between 9.2 and 10.1 mm in
M. novemaculeata. Transition to the juvenile stage is
gradual, because scales are not present and juvenile
pigmentation is still forming at about 15 mm. Juveniles
of both species have been collected in estuarine waters
until at least 100 mm SL (AMS fish collection). Juve-
niles of M. novemaculeata would be expected to migrate
to freshwater because this is the nominal adult habitat
(Williams, 1970), but the size at which this migration
occurs is unclear.
The two species described in the present study were
the only members of the genus Percolates, until this
genus (along with Plectroplites) was synonymized with
Macquaria by MacDonald (1978). Analyzing morpho-
logical and biochemical similarities of the three genera,
MacDonald (1978) listed eight morphological differences
that distinguished Percolates from Macquaria and Plec-
troplites. Protein electrophoresis similarities were stron-
1 Searle, G. 2002. Personal commun. Searle Aquaculture,
255 School Rd, Palmers Island NSW 2463.
Trnski et al.: Larval development of Macquana colonorum and M novemaculeata
193
ger between Pe. (currently Macquaria) colonorum and
Pe. (Macquaria) novemaculeata (similarity coefficient
0.95), and M. australasica and PL {Macquaria) am-
bigua (0.71) than between the Percolates and Macquaria
+ Plectroplites (0.63) (MacDonald, 1978). The species
of Percolates are euryhaline, whereas Macquaria and
Plectroplites are strictly freshwater. This fact, combined
with the difference in larval morphological features be-
tween Macquaria ambigua (Brown and Neira, 1998) and
M. colonorum and M. novemaculeata, provides evidence
that the genus Macquaria as defined by MacDonald
may be polyphyletic. Recent phylogenetic analysis of
the Percichthyidae with the use of molecular data in-
dicates that M. colonorum and M. novemaculeata are
more closely related to Maceullochella species than to
Macquaria (sensu stricto) (Jerry et al., 2001). Molecular
and larval evidence indicates the two catadromous spe-
cies (M. colonorum and M. novemaculeata) belong in a
genus separate from the freshwater species (M. ambigua
and M. australasica).
Acknowledgments
Comments by Dave Johnson, Jeff Leis, and Tony Miskie-
wicz improved the manuscript. Sue Bullock illustrated
the larvae from camera lucida sketches by TT Glen Searle
provided information on spawning habits that aided
interpretation of larval distributions. Mark McGrouther
provided access to specimens held in the Fish Collection
at the Australian Museum (AMS). Larval collections in
the field were supported by funds from Lake Macquarie
City Council. Preparation of this paper was supported
by a NSW Government Biodiversity Enhancement Grant
to AMS, and by AMS.
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195
Abstract — The Argentine sandperch
Pseudopercis semifasciata (Pinguipe-
didae) sustains an important commer-
cial and recreational fishery in the
northern Patagonian gulfs of Argen-
tina. We describe the morphological
features of larvae and posttransition
juveniles of P. semifasciata and ana-
lyze the abundance and distribution
of early life-history stages obtained
from 19 research cruises conducted on
the Argentine shelf between 1978 and
2001. Pseudopercis semifasciata larvae
were distinguished from other larvae
by the modal number of myomeres
(between 36 and 38), their elongated
body, the size of their gut, and by
osteological features of the neuro- and
branchiocranium. Pseudopercis semi-
fasciata and Pinguipes brasilianus
(the other sympatric species of pin-
guipedid fishes) posttransition juve-
niles were distinguished by their head
shape, pigmentation pattern, and by
the number of spines of the dorsal fin
(five in P. semifasciata and seven in
P. brasilianus). The abundance and
distribution of P. semifasciata at
early stages indicate the existence
of at least three offshore reproductive
grounds between 42-43°S, 43-44°S,
and 44-45°S, and a delayed spawning
pulse in the southern stocks.
Early life history of the Argentine sandperch
Pseudopercis semifasciata (Pinguipedidae)
off northern Patagonia
Leonardo A. Venerus
Centra Nacional Patagonico-Conseio Nacional de Investigaciones Cientificas y Tecnicas
Boulevard Brown s/n, (U9120ACV)
Puerto Madryn, Chubut, Argentina
E-mail address leoigicenpat edu ar
Laura Machinandiarena
Martin D. Ehrlich
Institute Nacional de Investigacion y Desarrollo Pesquero
PO Box 175, (B7602HSA)
Mar del Plata, Buenos Aires, Argentina
Ana M. Parma
Centra Nacional Patagonico-Conseio Nacional de Investigaciones Cientificas y Tecnicas
Boulevard Brown s/n, (U9120ACV)
Puerto Madryn, Chubut, Argentina
Manuscript submitted 20 November 2003
to the Scientific Editor's Office.
Manuscript approved for publication
16 September 2004 by the Scientific Editor.
Fish. Bull. 103:195-206 (2005).
The family Pinguipedidae (Osteich-
thyes, Perciformes) includes six genera
and about 50 marine species and one
freshwater species (Froese and Pauly,
2004). On the Argentine continental
shelf this family is represented by
two species, Pseudopercis setJiifasciata
(Cuvier, 1829) and Pinguipes brasilia-
nus Cuvier, 1829.
The Argentine sandperch P. semi-
fasciata is an important incidental
catch in the bottom trawl and long-
line commercial fisheries that target
hake (Merluccius hubbsi) in the north-
ern Patagonian coast off Argentina
(Otero et al., 1982; Elias and Bur-
gos, 1988; Gonzalez, 1998). In recent
years, the reported annual landings
have oscillated between 1900 and
3780 metric tons (official statistics,
SAGPyA-DNPyA1). In northern Pata-
gonia, P. semifasciata is also targeted
by sport anglers and spear fishermen
and represents a tourist attraction
for recreational divers. It inhabits
rocky and sandy bottoms, from 23°S
in Brazil to 47°S in Argentina (Cous-
seau and Perrotta, 2000), mainly in
coastal waters, although it has been
found in depths of up to 100 m (Mene-
zes and Figueiredo, 1985).
Very little is known about the ecol-
ogy and behavior of P. setnifasciata,
and most of what is known is based
on limited observations during un-
derwater visual censuses on shal-
low reefs where adults concentrate
(Gonzalez, 1998). Previous studies
have focused on morphological fea-
tures (Herrera and Cousseau, 1996;
Rosa and Rosa, 1997; Gosztonyi and
Kuba2), age and growth (Elias and
Burgos, 1988; Fulco, 1996; Gonzalez,
1998), diet (Elias and Rajoy, 1992;
Gonzalez, 2002), and reproductive
traits, including reproductive sea-
son, spawning modality, and age at
first maturity (Macchi et al., 1995;
SAGPyA-DNPyA. 2003. Capturas
maritimas totales 1992-2002. Manu-
script, 71 p. [Available from Sec-
retaria de Agricultura, Ganaderia y
Pesca de la Nacion, Direccibn de Pesca
y Acuicultura, Paseo Colon 982 P.B.
Of. 59 - (C1063ACW) Buenos Aires,
Argentina.] http://www.sagpya.mecon.
gov.ar (Accessed July 2004. J
Gosztonyi, A. E„ and L. Kuba. 1996. At-
las de huesos craneales y de la cintura
escapular de peces costeros patagonicos.
Inf. Tec. FPN 4, 29 p. [Available from
CENPAT, Blvd. Brown s/n (U9120ACV),
Puerto Madryn, Chubut, Argentina.)
196
Fishery Bulletin 103(1)
Fulco, 1996; Gonzalez, 1998). Pseudopercis semifas-
ciata is a multiple spawner with low batch fecundity
and an extended reproductive season (Macchi et al.,
1995; Gonzalez, 1998). There is little information on the
early life history of the species because only specimens
>20-25 cm are found on reefs and the habitat of juve-
niles has not been described. In general, information
about the early stages of pinguipedid fishes from the
southwest Atlantic Ocean is scarce. De Cabo3 reported
pinguipedid larvae from the Argentine shelf but did not
identify the specimens to species level.
In the present study, we describe development of P.
semifasciata from larvae to the posttransition juvenile
stage {sensu Vigliola and Harmelin-Vivien, 2001) and
analyze data on distribution and abundance on the
northern Patagonian shelf. This information is needed
to locate main reproductive and nursery grounds for
the species.
3 De Cabo, L. 1988. Descripcidn de tres larvas de peces teleos-
teos del Mar Argentino: Mugiloididae, Ophidiidae (Genypterus
blacodes) y Tripterygidae (Tripterygion eunninghami). Un-
publ. manuscript, 58 p. Facultad de Ciencias Exactas y Natu-
rales, Universidad de Buenos Aires-INIDEP. lAvailable from
INIDEP: P.O. Box 175 (B7602HSA) Buenos Aires, Argentina.]
Materials and methods
Fish larvae and posttransition juveniles were collected
during 19 research cruises conducted by INIDEP (Insti-
tuto Nacional de Investigacion y Desarrollo Pesquero)
between 1978 and 2001. A total of 592 ichthyoplankton
samples and 277 juvenile trawl samples were analyzed
(Table 1).
Larvae
Ichthyoplankton was sampled by using Bongo, Nack-
thai, and PairoVET nets. The Bongo net was fitted with
300-/<m mesh and a flowmeter. The Nackthai sampler, a
German modification of the Gulf V high-speed sampler
(Nellen and Hempel, 1969), was fitted with a 400-fim
mesh net and a flowmeter. Both samplers were towed
obliquely from bottom to surface. The PairoVET sampler,
a Bongo-type version of the CalVET, was fitted with
two 200- ;<m mesh nets to sample fish eggs (Smith et
al., 1985) and was towed vertically. Samples were fixed
in a solution of 5% formalin to seawater. During most
cruises, depths at which P. semifasciata were located
were determined by a SCANMAR sensor mounted on
the sampler.
Table 1
Research cruises in the Argentine Sea during 1978-2001. Only those cruises with at least one positive station containing
larvae or posttransition juveniles of Pseudopercis semifasciata were included in the analysis. EH=RVDr. Eduardo L. Holmberg;
OB=RV Capitdn Oca Balda; SM= RV Shinkai Maru.
Year
Cruise
Dates No.
of stations
Lat. S range
Long. W range
Ichthyoplankton
1978-79
surveys
SM-IX
26 Dec-07 Jan
28
42°27'-45°30'
61°58'-66°01'
1982
EH-05/82
19 Nov-03 Dec
65
ss^s'^o^s'
54°45'-61°57'
1983
EH-01/83
14 Jan-26 Jan
43
38°30'-44°32'
58"00'-65o07'
1985
OB-02/85
25 Mar-04 Apr
30
44°4r-46°52'
65°05'-67c18'
1986
OB-01/86
20 Jan-03 Feb
40
41°34'-44°36'
61°27'-65°05'
OB-07/86
09 Dec-22 Dec
43
43°01'-46°50'
62°40'-66°51'
1991
OB-07/91
01 Nov- 11 Nov
35
35°49'-36°51'
56°03'-56°59'
1995
OB-14/95
05 Dec-18 Dec
75
41°16'-45°22'
60°00'-67°00'
1996
EH-17/96
12 Dec-21 Dec
18
42°29'-44°01'
62°03'-65°16'
1998
OB-10/98
07 Dec-20 Dec
87
42°21'-45°36'
61°00'-65°44'
1999
OB-09/99
11 Dec-17 Dec
15
43o21'-44°01'
62°59'-65012'
2000
OB-14/00
09 Dec-21 Dec
27
43°19'-46°24'
63°37'-66°48'
2001
EH-01/01
06 Jan-29 Jan
28
43°19'-46°54'
62°12'-67°33'
OB-02/01
12 Feb-25 Feb
40
42°54'-45°25'
62°30'-66°12'
OB-13/01
10 Nov 13 Nov
18
42°21'-43°42'
61°55'-65°01'
Posttransition juvenile trawls
1992
EH-02/92
02 Mar-21 Mar
45
42°04'-45°43'
62°45'-66°14'
1998
EH-04/98
01 Apr-10 Apr
41
43°18'-47°02'
63°51'-66°43'
1999
EH-04/99
20 May-31 May
56
43°10'-47(>01'
63°51'-66c42'
2000
OB-05/00
01 Jun-20 Jun
112
43°45'-47°02'
61°53'-67°25'
2001
OB-02/01
12 Feb-25 Feb
23
42°54'-45°25'
62o30'-66°12'
Venerus et al .: Early life history of Pseudoperas semifasciata
197
A total of 68 preserved larvae, ranging in body length
(BL) from 3.3 to 11.7 mm, were used to describe larval
development. Terminology for morphometries followed
Neira et al. (1998). Additionally, head depth (HD) was
defined as the maximum depth of the head. Preserved
larvae were measured to the nearest 0.1 mm with an
ocular micrometer fitted to a dissecting microscope,
and their pigmentation pattern was recorded. Possible
shrinkage was not considered in the measurements.
Whenever possible, the number of vertebrae and num-
bers of dorsal, anal, caudal, pectoral, and pelvic fin rays
were recorded. In addition, 14 larvae from 3.4 to 11.7
mm BL were cleared and stained following the methods
of Potthoff (1984) and Taylor and Van Dyke (1985), and
then examined for meristics and osteological features.
Myomere and fin-ray counts and morphometric measure-
ments were made on the left side of the body. Larval
abundance was expressed as the number of larvae/
10 m2 of sea surface as recommended by Smith and
Richardson (1977).
Posttransition juveniles
Posttransition juveniles were collected with a small
bottom trawl called "Piloto," with the following features:
6 m total length, 6-m headrope and groundrope, 25-mm
wing mesh size, 10-mm codend mesh size, 0.25-m2 otter
board surface and 12 kg weight, 10-m bridles and 0.80-
m vertical opening. In Argentina, commercial fishing
vessels use this gear for locating shrimp concentra-
tions. Additionally, an epibenthic sampler (Rothlisberg
and Pearcy, 1976) fitted with 1-mm mesh was used on
one cruise (EH-02/92). We believe that individuals up
to 12 cm total length were well represented in samples
obtained with this gear.
A total of 27 posttransition juveniles, ranging from
22 to 83 mm body length (BL), were used to describe
Argentine sandperch developmental stages. Samples
were either frozen or fixed in 5% formalin to seawater
solution. Measurements and degree of pigmentation
were recorded after preservation.
Total length (TL), body length ( = standard length),
head length (HL), predorsal length (PDL), and preanal
length (PAL) were measured to the nearest 1 mm. Head
depth (HD), body depth (BD), and eye diameter (ED)
were measured to the nearest 0.2 mm. Three juveniles
between 22 and 33 mm BL were cleared and stained
(Potthoff, 1984; Taylor and Van Dyke, 1985) and exam-
ined for meristics.
The density of posttransition juveniles, expressed as
individuals/square nautical mile (nmi2), was estimated
from swept area. The family Pinguipedidae includes two
species (morphologically very similar as juveniles) that
overlap in the Argentine Sea. Unfortunately, not all
individuals caught during the cruises were examined
by us; therefore, to avoid biases caused by identifica-
tion errors, the posttransition juveniles of both species
were considered as a group. Distributional centroids
and ellipses were calculated by following the method
of Kendall and Picquelle (1989), that is by weighting
30 -
A
8 25-
-3 20 -
CQ
I 15 -
Aa AA
£. A A* fak A AA
10
n =55
■
0 5 10 15
30 -
8 25-
1 15-
if^A^
10 ■
n =53
1
0 5 10 15
BL (mm)
Figure 1
Relative head length (HL/BLxlOO)
and relative head depth (HD/BLx 100)
against body length (BL) in Pseudoper-
cis semifasciata larvae, regardless of
the flexion stage of the notochord. Solid
line represents a linear trend (rc = 53;
r2 = 0.2576; P<0.001).
each station by the density of juveniles caught. For this
purpose each density value was standardized with re-
spect to the maximum density observed for each survey
season over all years.
Results
Description of larvae
General morphological features The larval body was
elongate and relative BD was <25% in all stages of
development (Table 2). The smallest larva collected
(yolksac larva) was 3.3 mm BL. Its yolk sac was small
and the single oil globule was located on the anterior
part of the yolk mass. Notochord flexion began at 6
mm and was complete by 7-8 mm BL. As development
proceeded, larvae became slightly deeper and laterally
compressed. The head was small, with a rounded snout
and no spines. The oblique mouth was open by the end of
the yolksac larval stage. By 10 mm BL, premaxilla and
dentary bones were covered with caniniform teeth. The
premaxilla was an elongated bone with three processes
on its dorsal margin — the first one perpendicular to the
premaxilla. Relative head length remained constant,
whereas relative head depth diminished during develop-
ment (Fig. 1). The eyes were pigmented and their relative
diameter decreased during the preflexion stage, and
198
Fishery Bulletin 103(1)
Table 2
Body proport
ions of Pseudopercis semifasciata larvae,
according to the flexion stage of the notochord. Mean (±SE), range and
number of observations are shown in the table. BD
=body depth; BL=body length; ED=eye
diameter
; HD=head depth; HL=head
length; PAL =
preanal length.
BD/BLxlOO
HD/BLxlOO
Preflexion
3.3-7.1 mm BL;o = 36:
16.4 ±3.1 (12.4-25.5)71=27
18.5 ±2.3 (14.8-23.1) o=25
Flexion
6.2-8.7 mm BL;o = 8:
14.5 ±1.4 (12.2-16.1) n=5
17.1 ±1.2(15.9-19.4)0 = 8
Postflexion
7.3-11.7 mm BL;o=20:
16.8 ±1.3 (14.3-19.5) o=20
PAL/BLxlOO
17.4 ±1.4 (15.2-19.8) o=20
ED/BLxlOO
Preflexion
53.6 ±4.1 (45.0-62.5)n = 29
7.8 ±1.1 (5.9-10.9) o=29
Flexion
52.0 ±2.2 (49.4-56.5) o = 8
6.1 ±0.3(5.6-6.5)0 = 8
Postflexion
52.5 ±2.7 (47.3-57.5)n=20
HL/BLxlOO
6.1 ±0.7(4.9-7.6)0 = 20
Preflexion
21.2 ±2.4 (17.0-27.7) o = 27
Flexion
20.5 ±1.9 (18.2-24.2) ra=8
Postflexion
23.4 ±1.5 (19.3-26.0)»=20
then remained constant (Fig. 2, A and B). The gut was
initially straight but began to constrict at 4 mm BL and
was loosely constricted throughout development (Fig. 3,
A-C). It was moderate to long and extended to near
the midpoint of the body, resulting in a relative preanal
length of 0.45 to 0.62 BL.
15 -
A
10 -
Wa
5 -
2pfeeA
n =29
o U -
o
x (
_l
m
) 5 10 15
Q
w 15 -
B
10 -
5 -
A A
0 -
n =28
■ . i
0 5 10 15
BL (mm)
Figure 2
Relative eye diameter (ED/BLxlOO)
against body length (BL) in Pseudoper-
cis semifasciata larvae. (A) Preflexion
larvae. Solid line represents a linear
trend (rc=29; r2 = 0.6228; P<0.001). (B)
Flexion and postflexion larvae.
Body pigmentation Argentine sandperch larvae were
lightly pigmented during all stages of development
(Fig. 3; A-C). The pigmentation on the ventral body
surface, between the isthmus and the anus, consisted of
small stellate melanophores. Several small melanophores
were scattered on the lateral surface of the anterior part
of the gut. A double row of minute melanophores along
the ventral surface ended in a single melanophore at the
constriction of the gut. Pigmentation along the lateral
midline of the tail consisted of four to seven stellate
melanophores.
In preflexion larvae (Fig. 3A), small spots were evi-
dent along the lower jaw and the ventral part of the
head. Several small stellate melanophores were present
on the dorsal surface of the gut. A few melanophores
were scattered at the base of the pectoral fin bud.
Preflexion and flexion larvae (Fig. 3, A and B) showed
a distinct pattern of 12 to 23 small postanal melano-
phores serially arranged, about one per myomere, along
the ventral midline. A total of 11 to 18 melanophores,
about one melanophore per anal fin pterygiophore, was
observed in postflexion larvae (Fig. 3C). As flexion pro-
gressed (Fig. 3, B and C), the number of melanophores on
the ventral part of the head and over the gut diminished.
Fins and meristic features Modes of preanal and post-
anal myomeres were 14 and 23, respectively. All speci-
mens examined had 33-40 total myomeres (mode:36-38
myomeres). Vertebral column ossification started anteri-
orly. A total of 38-39 vertebrae were recorded in 10-12
mm BL postflexion larvae (n = 2).
In yolksac larvae, finfold and pectoral buds were the
first fin development distinguished. In preflexion and
flexion larvae, the finfold was present and it was gradu-
ally lost as the true fins developed. The sequence of
fin-ray formation, characterized by initial development
of fin elements, was caudal (7-8 mm BL), then pectoral
Venerus et a\ .: Early life history of Pseudopercis semifasciata
199
Figure 3
Larvae and posttransition juvenile of Pseudopercis semifasciata. (A) Preflexion
(4.3 mm BL). (B) Flexion (8.7 mm BL). (C) Postflexion (10.7 mm BL). (Dl transi-
tion juvenile (22 mm BL).
(9-10 mm BL), anal (9-10 mm BL), dorsal (9-10 mm
BL), and pelvic (10-11 mm BL). Elements of the cau-
dal fin began forming at flexion stage, and remaining
fins at the postflexion stage. By 9-10 mm BL, dorsal
(V+26-27) and anal (11+20-22) fin elements reached
their full complement.
Description of posttransition juveniles
The posttransition juvenile stage was characterized
by the acquisition of complete fin-ray complements and
by morphological similarities with the adults (Table 3,
Fig. 4). The transition from pelagic to benthic habitat in
this species, i.e. settlement, probably occurred at about
20 mm BL because the smallest benthic juvenile of Pseu-
dopercis semifasciata reported was 22 mm BL.
Table 3
Body proportions (mean [±SE| and range) of Pseudoper-
cis semifasciata posttransition juveniles. BD=body depth;
BL=body length; ED = eye diameter; HD=head depth;
HL=head length; PAL = preanal length; PDL=predorsal
length.
BD/BLxlOO
15.1 ±1.4(12.7-19.3)
PAL/BLxlOO
41.7 ±2.2 (37.7 -48.0)
HL/BLxlOO
23.0 ±2.4 (17.6-31.6)
HD/BLxlOO
13.8 ±1.5 (11. 9-19.31
ED/BLxlOO
8.4 ±1.1 (6.4-11.9)
PDL/BLxlOO
27.8 ±1.3 (25.7-30.2)
200
Fishery Bulletin 103(1)
Individuals became more thick bodied as they devel-
oped. The body was elongate and relative body depth
remained fairly constant throughout development. The
snout was longer and rounded, and relative head length
was moderate. The mouth was terminal, reaching to
the middle of the eye, and had fleshy lips. Both jaws
presented only caniniform teeth. Two opercular spines
were also present in all specimens studied. Relative
head depth decreased slightly during development, but
not relative eye diameter. Gut length was moderate
(PAL/BL 0.38-0.48), and the anus was situated near
the midpoint of the body (Fig. 3D). Relative predorsal
length (0.26-0.30) diminished during development.
The scales were ctenoid. Smaller posttransition juve-
niles (BL s33 mm) retained some of the larval pigmen-
tation pattern. Larger juveniles showed several dark
vertical bars, not completely defined at this stage of de-
velopment, and three horizontal stripes along the body
(Fig. 3D). Vertical bars developed progressively from the
caudal peduncle to the head. Two lateral stripes formed
continuous bands along each side of the body, almost
entirely above the midline. The upper stripe developed
from the tip of the snout and the lower one began below
the eye, both extending to the anterior caudal peduncle.
Another stripe developed from the dorsal region of the
head between the eyes and extended along the dorsal
fin, joining the upper lateral stripe at the posterior
third part of the body. In large posttransition juveniles
(a47 mm BL), the membrane of the dorsal fin was pig-
mented more densely between the spines than between
the rays; there were also dark blotches on the mem-
brane between the rays. Anal-fin membranes were more
pigmented than those of the dorsal fin. The membranes
of the pectoral, pelvic, and caudal fins, and the external
border of the membranes of the dorsal fin, were yellow
in frozen individuals. By 22 mm BL, the conspicuous
50 -i
~ 40
30 ■
20
10 ■
t
r
BD/TLx100 HL/TLx100 PAL/TLx100 PDL/TLx100
Body proportions
Figure 4
Comparisons between body proportions in posttransition
juveniles (white bars) and adults (gray bars) of Pseudopercis
semifasciata. Relative measures were taken with respect
to total length (TL). Body depth (BD), head length (HLi,
preanal length (PAL), predorsal length (PDL). Proportions
for adults were estimated from 99 individuals between <30
cm and 90 cm TL (Gonzalez, 1998).
dark blotch observed in adult P. semifasciata on the
base of the caudal fin upper lobe (Herrera and Cous-
seau, 1996) was already present (Fig. 3D). The pelvic
fin was large and slightly shorter than the pectoral fin,
whose margin was rounded.
Abundance and distribution
Larvae Larvae of Argentine sandperch occurred between
36°42'S and 46°30'S, mainly in coastal waters, in the
vicinity of the 50-m isobath (Fig. 5). The southernmost
limit where larvae were collected was within San Jorge
Gulf, which was surveyed in late March (fall). Larvae
were present in only 3.55% of the stations in densities
that varied between two and 74 larvae/10 m2 of sea
surface (Table 4). Greater densities (>20 larvae/10 m2
of sea surface) were obtained in December 1986, 1996,
and 1999, off the coast between Engano Bay and Isla
Escondida. Positive stations formed scattered clumps
along the whole distributional area of the species. Min-
imum and maximum depths sampled were 20 and 71 m,
respectively. Water temperature at 10 m depth at posi-
tive stations varied between 12.3°C (March 1985) and
18.7°C (December 1999) (mean temperature [±SE]:
15.2°C [±2.1°C]).
Posttransition juveniles Posttransition pinguipedid
juveniles were found between 42°27'S and 43°37'S in
February and March, and between 43°17'S and 44°58'S
from April to June, primarily in the vicinity of the 50-m
isobath (Fig. 6, A and B). The percentages of positive
stations were 5.9% and 7.7% in summer and fall surveys,
respectively. Maximum juvenile densities were 4410
individuals/nmi- in summer and 27,027 individuals/nmi2
in fall (Table 5).
The grid of stations used during the summer and
fall cruises overlapped (Fig. 6, A and B), cover-
ing the main area of concentration of P. semifas-
ciata (Otero et al., 1982). Minimum and maximum
depths were 54 and 74 m in summer surveys (mean
depth [±SE]: 64.5 [±10.0] m), and 34 and 79 m in
fall surveys (mean depth [±SEJ: 60.4 [+13.7] m).
The distributional ellipses calculated for summer
and fall from the positive stations were small and
widely separated. Maximum summer densities of
posttransition pinguipedids were found southeast
of Peninsula Valdes, whereas greatest fall densities
were detected northeast of Camarones Bay (Fig. 6,
A and B).
Discussion
Literature describing the early stages of species
belonging to the family Pinguipedidae (formerly
Mugiloididae) is scarce. The few available studies
refer to the larval development of Parapercis spp.
(Leis and Rennis, 1983; Watson et al., 1984; Houde
et al., 1986; Neira, 1998; Leis and Rennis, 2000)
Venerus et al.: Early life history of Pseudoperas semifasciata
201
and Prolatilus jugularis (Velez et al., 2003). Larval
abundance and distribution have been studied for
a few species of Parapercis (Houde et al., 1986;
Gaughan et al., 1990; Neira et al., 1992) and,
more recently, for Prolatilus jugularis (Velez et al.,
2003); no information is available for posttransi-
tion pinguipedid juveniles.
Larvae of P. semifasciata resembled the larvae
of other pinguipedids in their gut size, meristics,
and general pattern of pigmentation. They differed
from Parapercis spp. and P. jugularis larvae in
some relevant features:
• The head had no spines and was less rotund,
rather moderate instead of large (HL ranged from
0.17 to 0.30 BL; mean HL/BL = 0.22 [±0.02]);
• The body was rather elongate instead of mod-
erate (BD ranged from 0.12 to 0.26 BL; mean
BD/BL = 0.16 [±0.03]);
• The notochord flexion occurred between 6.2
and 8.7 mm BL, at a relatively large size range
compared to that for Parapercis spp. (3.7-4.8
mm BL) and to P. jugularis (5.7-6.9 mm BL).
Pseudopercis semifasciata is a larger and more
rotund species;
• The finfold was still present in preflexion and
flexion larvae.
De Cabo3 described some osteological, meristic,
and morphological characteristics of Argentine Sea
pinguipedid larvae. Like De Cabo3 we found that
the first cranial bones that appeared during larval
development in P. semifasciata were the premax-
illa, the dentary and the cleithrum. These struc-
tures were already ossified in 3.4 mm BL preflexion
larvae. From the adult osteological descriptions by
Herrera and Cousseau (1996) and Gosztonyi and
Kuba,2 we determined that the larvae studied were
P. semifasciata. The only other sympatric species
of Pinguipedidae in the Argentine shelf is the
Brazilian sandperch (Pinguipes brasilianus), which
shares several similarities in meristic counts with
P. semifasciata (Rosa and Rosa, 1987; Herrera
and Cousseau, 1996). However, some osteological
features from the neuro- and branchiocranium are
of great value for identification of larval stages
of P. semifasciata. The two species could be dis-
tinguished by the placement of the first process
of the premaxilla, which is perpendicular to the
premaxilla in the Argentine sandperch, and back-
inclined in the Brazilian sandperch, drawing an
acute angle with the premaxilla (Herrera and
Cousseau, 1996). The dentary in P. semifasciata
has a quadrangulate anterior end and a margin
almost straight, whereas the margin of the dentary
in P. brasilianus is oblique (Herrera and Cousseau,
1996). In addition, the head and the teeth patch
of the vomer are quadrangulate in Pinguipes and
triangular in Pseudopercis (Herrera and Cous-
seau, 1996).
35°S
70°W
35°S
70°W
Figure 5
Distribution of ichthyoplankton stations (upper) and Pseu-
dopercis semifasciata larvae (lower) in the Argentine Sea in
the period 1978-2001. Dot diameter, classified into four cat-
egories, is proportional to larval abundance at each station
(expressed as larvae/10 m2 of sea surface).
202
Fishery Bulletin 103(1)
Table 4
Positive stations for Pseudopereis semifasciata larvae in the Argentine Sea, during 1978-2001.
ses indicate that only surface temperature was registered. W/d=missing data.
Temperature values
in parenthe-
Abundance
Water
Cruise
Date
Sampler
Lat. S
Long. W
(larvae/10 m2
of sea surface)
temperature
(at 10 m depth)
Depth (m)
SM-IX
28 Dec 1978
Bongo
42°27'
63°08'
7.36
w/d
70
EH-05/82
22 Nov 1982
Bongo
4039'
60=40'
5.85
(12.8)
53
EH-01/83
21 Jan 1983
Bongo
43°44'
65°00'
4.82
16.7
52
OB-02/85
30 Mar 1985
Bongo
46c30'
67°18'
Presence
12.3
56
OB-07/86
20 Dec 1986
Nackthai
43°25'
64'45'
73.91
14.2
34
OB-07/86
20 Dec 1986
Nackthai
43°50'
64" 17'
19.78
14.0
47
OB-01/86
22 Jan 1986
Nackthai
41°33'
62 = 15'
13.76
18.7
45
OB-01/86
22 Jan 1986
Nackthai
41c35'
63=40'
8.64
17.6
51
OB-07/91
02 Nov 1991
Nackthai
36=42'
56°21'
15.33
w/d
20
OB-14/95
12 Dec 1995
Pairovet
43°04'
63°59'
Presence
13.0
65
EH-17/96
15 Dec 1996
Nackthai
43°30'
65=05'
23.92
14.3
24
OB-10/98
10 Dec 1998
Nackthai
42 = 21'
62=40'
Presence
w/d
66
OB-09/99
12 Dec 1999
Nackthai
43°21'
64°52'
17.22
(14.6)
20
OB-09/99
12 Dec 1999
Nackthai
43 = 30'
64 = 29'
41.00
(21.0)
49
OB-14/00
11 Dec 2000
Bongo
43°19'
64°35'
1.81
(12.8)
37
OB -14/00
11 Dec 2000
Bongo
43°30'
64=24'
8.44
13.8
52
EH-01/01
26 Jan 2001
Bongo
43 = 29'
64°35'
2.51
15.9
47
OB-02/01
16 Feb 2001
Bongo
43°18'
64=08'
5.20
15.8
59
OB-13/01
10 Nov 2001
Bongo
42°30'
62°30'
9.30
w/d
71
OB-13/01
11 Nov 2001
Bongo
42°50'
62°55'
9.36
w/d
71
OB-13/01
13 Nov 2001
Bongo
43°25'
64°49'
7.99
w/d
38
The modal number of myomeres (36-38; n = 47) in P.
semifasciata larvae matched the number of vertebrae
reported for adults (36-37; ?? = 50) by Gonzalez (1998).
The dorsal and anal fin elements reached their full
complement by 9-10 mm BL, whereas the caudal-, pel-
vic-, and pectoral-fin elements were still incomplete in
the size range analyzed in this study (3.3 to 11.7 mm
BL). Pseudopereis semifasciata and P. brasilianus post-
transition juveniles differ in their head shape, pigmen-
tation pattern, and in the number of spines of the dorsal
fin. The snout is larger in the Brazilian sandperch and
the dorsal profile of the head is less convexly shaped
than in P. semifasciata. These head shape differences
increased with size. In P. brasilianus, the lateral stripes
were less conspicuous than in P. semifasciata, and the
vertical bars appeared earlier in the development (seven
vertical bars were present in ca. 50 mm BL individu-
als). Furthermore, vertical bars in P. semifasciata were
more defined at the base of the dorsal fin, whereas they
extended below the midline in P. brasilianus. Pseu-
dopereis semifasciata had five dorsal-fin spines, and P.
brasilianus had seven spines, both in the range reported
by Herrera and Cousseau (1996).
Both the epibenthic sampler and the "Piloto" trawl
used to collect juveniles sample the fauna from the bot-
tom to approximately one meter above the bottom. The
fact that juveniles were caught in the lowest strata of
the water column indicates that juveniles had settled to
benthic habitat, even though the P. semifasciata post-
transition juveniles still conserved some larval pigmen-
tation, had not completely developed adult pigmentation
pattern, and had already acquired morphological pro-
portions similar to adults.
Even though the abundance and distribution data
used in our study came from cruises that targeted other
species, they provide satisfactory spatiotemporal cover-
age. This was particularly true for the ichthyoplancton
surveys, which covered a great portion of the distribu-
tional area of P. semifasciata in the northern Patago-
nian shelf, mainly during the peak of the reproductive
season (November-December). Among the Piloto posi-
tive stations (« = 20), P. brasilianus was found by itself
only at three stations. Also, P. brasilianus was far less
abundant than P. semifasciata posttransition juveniles
in the trawl samples. As a consequence, we consider
that the abundance and distribution patterns of post-
transition pinguipedid juveniles adequately reflect the
abundance and distribution of P. semifasciata posttran-
sition juveniles in the Argentine shelf.
The abundance and distribution of P. semifasciata
larvae and posttransition juveniles indicate the pres-
ence of at least three main reproductive grounds, one
Venerus et al .: Early life history of Pseudopercis semifasciata
203
Posttransition
Pinguipedidae
summer surveys
70°W
41 °S
43:
41 °S
70°W
B
Posttransition
Pinguipedidae
fall surveys
Camarones
Bay
41 S
70°W
1-2702 Juvemles/nmr' O
2703-6757 Juveniles/nmi2 O
6758-13.514 Juveniles/nmP Q
13,515-27.027 Juveniles'nmpr J
Camarones
Bay
70°W
41 °S
Figure 6
Distribution of "Piloto" or epibenthic sampler stations (left) and Pinguipedidae posttransition juveniles (right) in the
Argentine Sea by season. (A) Summer surveys. (B) Fall surveys. Dot diameter, classified into four categories, is pro-
portional to posttransition juvenile abundance at each station (expressed as no. of juveniles/nmi2).
located off Peninsula Valdes (42-43°S, 63°W), another
off the coast between Engano Bay and Isla Escondida
(43-44°S, 64°W to the coast), and the third off north-
eastern Camarones Bay (44-45°S, 65°W to the coast).
These areas are linked to a frontal zone, the Northern
Patagonia frontal system, which is highly productive
during the spring and summer and could offer reten-
tion mechanisms for larvae (Bogazzi et al., in press). In
December 1978, Argentine sandperches of both sexes
were observed running near Isla Escondida (Ehrlich,
personal observ.). In addition, Elias and Burgos (1988)
reported great concentrations of Argentine sandperches
off Peninsula Valdes (42-44°S) between October and De-
cember, based on commercial fishery data for the period
1981-88. These reproductive grounds are consistent with
the principal areas of summer concentration described
by Otero et al. (1982). Furthermore, Elias and Burgos
(1988) attributed the decline in yields and average size
observed in January and February to the dispersal of
postspawning individuals. However, initial results from
an ongoing tag-recapture program in San Jose Gulf indi-
cate that this species may have a high site fidelity and a
limited dispersal (Venerus et al., 2003). In this case, the
declines in yield and average size as the fishing season
progresses could be a consequence of the fishing effort
itself. Macchi et al. (1995) detected a decrease in the
proportion of females in January, which also may imply
an emigration from the reproductive sites.
204
Fishery Bulletin 103(1)
Table 5
Positive stations for posttransition pinguipedids in the Argentine Sea, during 1992-2001. The "Species" column show the catego-
ries assigned in the survey reports. Underlined items in the "Abundance" column indicate that some or all of the specimens were
preserved and at least one individual was correctly identified as Pseudopercis semifasciata. EBS= epibenthic sampler.
Cruise
Date
Season
Sampler
Lat. S
Long. W
Species
Abundance
individuals/nmi')
Depth
(m)
EH-02/92
18 Mar 1992
Summer
EBS
42=27'
62°45'
Pseudopercis
Presence
71
OB-02/01
14 Feb 2001
Summer
P
loto trawl
43°08'
63°32'
Both
4409.5
74
OB-02/01
16 Feb 2001
Summer
P
loto trawl
43 16'
6407'
Pinguipedidae
2572.2
59
OB-02/01
17 Feb 2001
Summer
P
loto trawl
43°37'
64° 28'
Pinguipedidae
1286.1
54
EH-04/98
07 Apr 1998
Fall
P
loto trawl
44°40'
65°13'
Pseudopercis
1492.6
74
EH-04/98
07 Apr 1998
Fall
P
loto trawl
44°43'
65°00'
Pseudopercis
10,204.1
79
EH-04/98
07 Apr 1998
Fall
P
loto trawl
44°38'
6501'
Pseudopercis
4761.9
78
EH-04/98
07 Apr 1998
Fall
P
loto trawl
44°34'
65°20'
Pseudopercis
3448.3
52
EH-04/98
07 Apr 1998
Fall
P
loto trawl
44°28'
65°14'
Pseudopercis
1587.3
61
EH-04/99
28 May 1999
Fall
P
loto trawl
44°12'
65°14'
Pseudopercis
1449.3
34
EH-04/99
28 May 1999
Fall
P
loto trawl
43°50'
64°44'
Pinguipes
1315.8
64
EH-04/99
29 Mayl999
Fall
P
loto trawl
43°54'
64c30'
Pinguipes
1265.8
65
EH-04/99
29 May 1999
Fall
P
loto trawl
4317'
63°51'
Pseudopercis
1250.0
73
OB-05/00
HJun 2000
Fall
P
loto trawl
44°27'
65'' 13'
Pinguipes
2631.6
64
OB-05/00
HJun 2000
Fall
P
loto trawl
44°34'
65:19'
Pseudopercis
1250.0
58
OB-05/00
HJun 2000
Fall
P
loto trawl
44°41'
65°31'
Pseudopercis
1351.4
43
OB-05/00
11 Jun 2000
Fall
P
loto trawl
44°43'
65°37'
Both
27.027.0
38
OB-05/00
15 Jun 2000
Fall
P
loto trawl
44°15'
6459'
Pinguipes
1449.3
72
OB-05/00
18 Jun 2000
Fall
P
loto trawl
43°50'
64°44'
Both
5194.8
59
OB-05/00
18 Jun 2000
Fall
Piloto trawl
43°46'
65°01'
Pseudopercis
1388.9
52
The low number of positive stations in spite of the
intense sampling conducted within the area of distribu-
tion of P. semifasciata suggests a reduced spawning site.
Both the area off Peninsula Valdes and the one near
Isla Escondida have rocky bottoms, which complicates
trawling operations. A few experienced captains were
able to target P. se?nifasciata by trawling along sandy
corridors between rocky outcrops off Peninsula Valdes
during the reproductive season (Elias4). Likewise, where
running Argentine sandperches were observed near Isla
Escondida, trawling is possible only in one orientation
(Ehrlich, personal observ. ). This could indicate that
spawning grounds are associated with rocky outcrops.
Spawning associated with rocky reefs and the existence
of chromatic sexual dimorphism is compatible with Mac-
chi et al.'s (1995) and Gonzalez's (1998) suggestions of a
complex mating system involving sexual courtship.
Spawning activity of P. semifasciata in northern
Patagonia (42-44°S) peaks in November and Decem-
ber (Elias and Burgos, 1988; Macchi et al., 1995), and
in October within San Matias Gulf (Gonzalez, 1998).
Maximum densities of larvae (>20 larvae/10 m2 of sea
surface) were found in December 1986, 1996, and 1999.
The temperature at 10 m depth at positive ichthyo-
plankton stations varied between 12.3°C and 18.7°C.
Such a wide range of temperature reflects the wide
latitudinal range in the distribution of P. se?nifasciata
and the extended time period (November-March) in
which larvae were collected.
Posttransition pinguipedid juveniles were mainly col-
lected at depths between 60 and 65 m, in both sea-
sons sampled (summer and fall). A total of seven P.
semifasciata juveniles ranging in total length from
66 to 82 mm were collected in fall (June), near the
northern coast of San Matias Gulf (40°58'S-41°00'S;
64°18'W-64024'W), at 29-54 m depth, associated with
rib mussel beds (Aulacomya ater) (Gonzalez5). Our dis-
tributional data indicate that settlement and nursery
grounds could be located near shore. The absence of
posttransition juveniles off northeast of Camarones
Bay during summer and their presence in the fall could
be a consequence of a delayed spawning pulse in the
southern stocks. Some independent observations sup-
port this hypothesis: 1) back-calculations of hatching
date based on daily growth increments from 19 post-
4 Elias, I. 2004. Personal commun. Centra Nacional Pata-
gonico, Puerto Madryn, Chubut, Argentina.
5 Gonzalez, R. A. C. 2004. Personal commun. Instituto
de Biologia Marina y Pesquera "Alte. Storni," San Antonio
Oeste, Rio Negro, Argentina.
Venerus et al .: Early life history of Pseudopercis semifasaata
205
transition juveniles collected in northeast Camarones
Bay, between 43°50'S and 44°43'S, indicated birth dates
between February and March (Venerus and Brown,
2003); 2) the collection of one P. se/nifasciata larva in
San Jorge Gulf (46°30'S 67°18'W) on 30 March 1985;
and 3) macroscopic observations of the ovaries from 24
mature females angled near Islas Blancas. Camarones
Bay (ca. 44°46'S 65°38'W) on 26 and 27 January 2002,
most of which (58.3%) were in the late developing stage
(rc = 4) or in the gravid and running stage (;;=10) (mac-
roscopic maturation stages sensu Gonzalez, 1998). This
delayed spawning pulse in the southern stocks appar-
ently follows the annual cycle of seawater warming on
the Argentine shelf (Ciancio6). Similar delays have been
reported for the Argentine hake (Merluccius hubbsi)
(Pajaro and Macchi7; Machinandiarena et al.8).
Further investigations focused on the seasonal distri-
bution of spawners are needed to confirm the existence
of spawning aggregations indicated by the presence of
larvae and posttransition juveniles. Mark-recapture and
telemetry studies could be used to investigate the spa-
tial dynamics of reproductive activity of this species in
the Argentine Sea. Given the relative sedentary habits
of adult Argentine sandperches, the use of reproductive
refuges appear a priori to provide a suitable approach
to protect this species.
Acknowledgments
We thank the crew and scientific staff on board for col-
lecting the material. We also thank Atila Gosztonyi,
Raul Gonzalez, and two anonymous reviewers for pro-
viding useful comments on the manuscript. L.A.V. was
supported by a fellowship from Consejo Nacional de
Investigaciones Cientificas y Tecnicas (CONICET).
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207
Abstract — Nurseries play an impor-
tant part in the production of marine
fishes. Determining the relative
importance of different nurseries in
maintaining the parental population,
however, can be difficult. In the west-
ern Gulf of Alaska, the Kodiak Island
vicinity may be particularly well
suited as a pollock nursery because of a
prey-rich nearshore environment. Our
objectives were 1) to examine age-0
pollock body condition, growth, and
diet for evidence of a nearshore-shelf
effect, and 2) to determine if variation
in the potential prey field of zooplank-
ton was associated with this effect.
This was a pilot study that occurred
in three bays and over the adjacent
shelf off east Kodiak Island during
5-18 September 1993. Sampling
occurred only during night at loca-
tions where echo sign indicated the
presence of age-0 pollock. Echo sign
was targeted to increase the chance of
collecting fish given the limited vessel
time. Fish condition was indicated by
length-specific body weight. Growth
rate indices were estimated for three
different periods by using fish length-
age data and daily otolith increment
widths: 1) from hatching date to cap-
ture, 2) 1-5 d before capture, and 3)
6-10 d before capture. Fish diet was
determined from gut content analysis.
Considerable variation among areas
was evident in zooplankton composi-
tion, and fish condition, growth, and
diet. However, relatively high prey
densities, as well as fish condition
and growth rates indicated that Chin-
iak Bay was particularly well suited
as a pollock nursery. Hatching-date
distributions indicated that most of
the age-0 walleye pollock from bays
were spawned earlier than were those
from the shelf. The benefit of being
reared in nearshore areas is therefore
realized more by individuals that were
spawned early than by individuals
spawned relatively late.
Geographic variation among age-0
walleye pollock (Theragra chalcogramma)'.
evidence of mesoscale variation in nursery quality?*
Matthew T. Wilson
Annette L. Brown
Kathryn L. Mier
Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
7600 Sand Point Way. NE
Seattle, Washington 98115
E-mail address (for M T Wilson) matt wilson(a>noaa gov
Manuscript submitted 20 November 2003
to the Scientific Editor's Office.
Manuscript approved for publication
16 September 2004 by the Scientific Editor.
Fish. Bull. 103:207-218 (2005).
The location of suitable fish nurseries
has long been of interest to fishery
scientists (Kendall and Duker, 1998).
Such areas are a link in the chain of
resources that sustain the produc-
tivity of a population and shape its
evolution. Although the presence of
juvenile fish in an area may indicate
a nursery, relative importance among
nursery areas ultimately depends
on the number and reproductive fit-
ness of reared individuals that con-
tribute to the parental population.
These qualities, however, are usually
not measurable. Instead, we focus
on measuring the size of juveniles,
their body condition, diet, growth, and
other characteristics that are acces-
sible and relevant to fish survival.
However, because these indices are
not free of measurement error, it is
advisable to consider more than one
index (Suthers, 1998).
In the North Pacific Ocean, wall-
eye pollock {Theragra chalcogramma)
have adapted to the heterogeneity and
productivity of coastal areas; they
now support one of the world's most
productive fisheries. Walleye pollock
are a semidemersal gadid. Spawning
typically occurs in mid-water during
the spring at locations near, or over,
the continental shelf (Kendall and
Picquelle, 1989; Bailey et al., 1997).
Fertilization is external. The eggs
and larvae are pelagic, remaining in
the plankton for ca. 4 months while
they are dispersed over large areas.
At 25-40 mm standard length (SL),
larvae transform to juveniles (Brown
et al., 2001) and become increasingly
nektonic. Juveniles are referred to as
"age-0" when they are between tran-
sition and 12-months old (40-130 mm
SL, Brodeur and Wilson, 1996a). They
are zooplanktivorous, feeding mostly
on copepods and euphausiids, but
other taxa sometimes dominate their
diet (Brodeur and Wilson, 1996a).
Age-0 juveniles commonly occur in
various habitats from nearshore to
the outer continental shelf (Nakatani
and Maeda, 1987; Sobolevskiy et al.,
1992; Carlson, 1995; Natsume and
Sasaki, 1995; Brodeur and Wilson,
1996a; Wilson, 2000). Occasionally,
they are found farther offshore (Tang
et al., 1995), but probably in small
numbers (Brodeur et al., 1999; Shida
et al., 1999).
The early life stages of walleye pol-
lock have been extensively studied in
the Gulf of Alaska (GOA) (Kendall et
al., 1996). In the Gulf, young pollock
are most abundant in the western
region (Brodeur and Wilson, 1996a).
This region is naturally divided into
two areas by the Shelikof Sea Val-
ley, which cuts through the shelf at
ca.l56°N longitude (Fig. 1). To the
east, the Kodiak vicinity includes the
continental shelf around the Kodiak
Island Archipelago. To the west, the
lower Alaska Peninsula vicinity ex-
tends to Unimak Pass at the Penin-
sula's southwestern terminus. During
the 1980s, age-0 abundance in the
Contribution FOCI-0417 to NOAA's
Fisheries- Oceanography Coordinated
Investigations, 7600 Sand Point Way
NE, Seattle, WA 98115.
208
Fishery Bulletin 103(1)
165'OOTM 160°0'OW 155'0'OW ISO'O'CTW 145J0'0W
Alaska /' _■ ,. V /"
57.8
57.6 -
57.4 -
57 2
NE shelf
Sampling gear
+
CTD
o
plankton
u
trawl
Vkv>
152.8 152 4 152.0
Longitude (°W)
151.6
151 2
Figure 1
Location of sampling operations (CTD, plankton, and trawl) conducted
during 5-18 September 1993, Kodiak Island, Alaska, to examine geo-
graphic variation among age-0 walleye pollock I Theragra chalcogramma I.
The ocean currents, shown as arrows on upper map, are adapted from
Reed and Schumacher (1986).
Kodiak vicinity was related to the recruitment of pollock
to the GOA fishery (Wilson, 20001. Furthermore, age-0
juveniles in this vicinity were large in comparison to
those collected elsewhere (Wilson, 2000). The large size
of the "Kodiak" juveniles may reflect faster growth (Bai-
ley et al., 1996) due to a rich diet of euphausiids (Me-
rati and Brodeur, 1996). In contrast, the diet of age-0
pollock along the Lower Peninsula was dominated by
larvaceans (Merati and Brodeur, 1996). Interestingly,
high densities of age-0 pollock were closer to shore in
the Kodiak vicinity than along the Lower Peninsula
where the shelf is relatively broad.
The apparent richness of the Kodiak Island vicinity
may reflect its relative upstream position in the Alaska
Coastal Current (ACC) (Fig. 1). Stabeno et al. (2004)
integrated much research on the ACC to provide a com-
prehensive view of its importance in circulation over
the GOA shelf. The ACC is wind driven and structured
by seasonal influxes of fresh water. Flow is generally
southwestward over the shelf but there is considerable
topographic influence. For example, landmasses at the
northern entrance to Shelikof Strait (Kennedy-Steven-
son Entrance) allow only about 70% of the ACC water
to enter the Strait. The remaining 30% of the water
flows south around the northeastern end of the Kodiak
Archipelago. This bifurcation of flow occurs in an area
of vigorous tidal mixing and localized upwelling, both
of which contribute to increased biological productiv-
ity. Off the northeastern Archipelago, Stabeno et al.
(2004) have shown that the ACC follows bathymetric
contours into and out of sea valleys, thus, providing
some across-shelf movement of water. Advection of wa-
ter was found by Coyle et al. (1990) to be important in
the enhancement of zooplankton in Auke Bay, which is
in the eastern GOA. Less is known about the exchange
of water and zooplankton between the bays and fjords
of the western GOA and the adjacent shelf. Thus, the
ACC probably helps enrich the waters off northeastern
Wilson et al.: Geographic variation among age-0 Theragra chakogramma
209
Kodiak Island, but we do not yet understand how this
actually affects walleye pollock in nearshore nurseries.
In this article, we present information from a pilot
study to better understand the environmental basis for
the apparent richness of the Kodiak Island vicinity as
a pollock nursery. Our objectives were 1) to examine
age-0 pollock size, body condition, growth, and diet for
evidence of geographic effect (nearshore versus shelf),
and 2) to determine if their potential prey field (i.e.,
zooplanktonl was associated with this effect.
Materials and methods
This study was conducted as an ancillary project during
a research cruise off east Kodiak Island, 5-18 Septem-
ber 1993 (Fig. 1). In this area, the shelf is about 50 nmi
wide and has an offshore bank (Albatross Bank) crossed
by deep gullies (Barnabas and Chiniak gullies) extend-
ing from the slope to the coast. Bays form the upper
reaches of these troughs and receive seasonal influxes of
freshwater (Rogers et al.1). Over the shelf, net transport
is southwestward (ca. 5 em's) (Stabeno et al., 1995). A
boundary current, the Alaska Stream, exists farther
offshore and flows rapidly to the southwest (Reed and
Schumacher, 1986).
Sampling was conducted from the NOAA ship Miller
Freeman (Fig. 1). Sampling occurred only at night to
avoid complications of diel fish movement (Brodeur and
Wilson, 1996b) and feeding patterns (Merati and Bro-
deur, 1996). A 38-kHz, Simrad-EK500 echo-sounder
system was used to help guide our sampling to locations
where age-0 pollock were likely present. The targeting
of echo signs resulted in an irregular sample-location
pattern and biased estimation of fish abundance; how-
ever, it focused our sampling at locations where age-0
pollock were likely present and thereby contributed to
successful fish collections. Sampling was accomplished
in four areas: Chiniak Bay, Ugak Bay, Kiliuda Bay, and
over the adjacent shelf. All data analyses included these
four areas as geographic strata; finer divisions (e.g., in-
ner and outer Kiliuda Bay, and NE and Albatross Bank)
were not possible given the available data and chosen
analytical methods.
Age-0 pollock were obtained from the four areas with
a bottom trawl and a midwater trawl (Wilson et al.,
1996). The codend of each trawl was lined with a 3-mm
mesh net. Towing speed averaged 4.5 k/h. Previous
comparisons between these trawls indicated no sig-
nificant difference with regard to estimation of age-0
pollock size or abundance (Brodeur and Wilson, 1996a;
Wilson et al., 1996). Differences in the sampling effort
Rogers, D. E., D. J. Rabin, B. J. Rogers, K. J. Garrison, and
M. E. Wangerin. 1979. Seasonal composition and food web
relationships of marine organisms in the nearshore zone of
Kodiak Island — including ichthyoplankton, meroplankton
(shellfish), zooplankton, and fish. Annual rep. OCSEAP
RU553, FRI-UW-7925. 291 p. Fish. Res. Inst., Univ. Wash-
ington, Seattle, WA.
used to collect each sample were corrected by dividing
the age-0 catch by the volume filtered. Volume filtered
was estimated by multiplying the distance fished (me-
ters traveled while at depth) by the mouth opening of
the trawl (m2) (Wilson, 2000). Thus, age-0 catches are
reported as number of fish per m3.
Size composition of walleye pollock for each area was
estimated by measuring the standard length (SL) of
fresh age-0 pollock to the nearest millimeter. For large
catches, a random subsample of about 300 individuals
was used to represent the entire catch; otherwise, SL
on every individual was measured. Length frequencies
were expanded to the standardized catch estimates.
Age-0 juveniles were clearly distinguishable from older
pollock (<130 mm versus >150 mm SL) as indicated by
Brodeur and Wilson (1996a). Random subsamples of
age-0 pollock were also frozen at sea for subsequent de-
termination of body condition, age, growth, and diet.
In the laboratory, length-specific weights of 776 age-0
pollock were used to examine area differences in body
condition (Table 1). The fish were thawed within four
months of collection. Excess water was blotted from each
individual, and each specimen was measured to the
nearest millimeter SL and weighed whole to the nearest
0.01 gram. Afterwards, each carcass was stored in 95%
ethanol for eventual gut content analysis. Lengths and
somatic weights, obtained from the subset of fish used
in the gut analysis, were also analyzed to verify that
geographic differences in condition were not dependent
on whole versus somatic weight.
Growth rate was estimated for 128 individuals by
using fish length and age data. Age, in days, was esti-
mated as the number of daily increments visible in the
microstructure of sagittal otoliths following Brown and
Bailey (1992). Length-age relationships were examined
for evidence of an area effect on growth rates integrated
over the period from hatching to capture. We used these
relationships to convert the length composition for each
sample to a hatching-date distribution, and by summing
across samples we then obtained area-specific hatching-
date distributions.
To estimate growth rate realized near the point of
capture we measured the width of recent daily otolith
increments. Following Bailey (1989), we measured the
width of the two outermost, nonoverlapping 5-increment
bands on each of 97 sagittal otoliths. These widths
were assumed to relate directly to body growth during
the first (1-5 days) and second (6-10 days) 5-d periods
before capture, and that the increments were deposited
while individuals were near the point of capture. Thus,
growth rate indices were obtained for three different
periods: 1) hatching date to capture date, 2) 1-5 days
before capture, and 3) 6-10 days before capture.
Gut content analysis was conducted on 300 individu-
als according to the method of Merati and Brodeur
(1996) to determine feeding intensity and taxonomic
composition of age-0 prey. No more than 15 fish per
sample were examined. Each fish was measured (SL),
blotted dry, and weighed immediately prior to dissec-
tion. Stomachs were excised between the esophagus and
210
Fishery Bulletin 103(1)
Table 1
Number of age-0 walleye pollock (Theragra chalcogramma) collected near Kodiak Island, Alaska, September 1993, measured
for standard length, and examined in the laboratory to estimate condition, growth, and the weight and taxonomic composition of
stomach contents. Sample is the number of trawl hauls.
At-sea
collections
Laboratory examinations (no. offish)
Growth
(no
offish)
Condition
Band
width
Evaluated for
gut content
Sample
Measured
whole'
somatic-
weight and
Location
(n)
Caught
forSL
wt.
wt.
Age
1-53
6-10'
composition
Chiniak Bay
7
1858
709
223
75
23
17
17
75
Ugak Bay
4
2506
773
218
91
28
12
12
91
Kiliuda Bay
7
562
279
165
66
41
33
33
66
Shelf
14
358
358
170
68
36
35
35
65
All combined
32
5284
2119
776
300
128
97
97
297
; Whole wet weights from thawed fish.
- Somatic wet weights from fish preserved in 95f4 ethanol after freezing at sea.
3 Collective width of daily otolith increments 1-5; numbering begins with the most peripheral increment.
4 Collective width of daily otolith increments 6-10.
pylorus. Gut contents were dissected from the speci-
mens and weighed to the nearest 0.001 gram. Somatic
weight represented whole wet weight minus the gut
content weight. Three fish were omitted from further
consideration because of apparent regurgitation. Taxo-
nomic composition of age-0 diets was determined by
counting the organisms in the gut after sorting them
into broad taxonomic groups.
Zooplankton was collected by using a 1-m Tucker net
(333-/mi mesh) to sample where age-0 pollock had been
collected. The net was fished through acoustic echo lay-
ers believed to be age-0 pollock in order to characterize
their immediate prey field. Potential prey items were
sorted into broad taxonomic groups and enumerated at
the Polish Plankton and Identification Center, Szezcin,
Poland.
Temperature and salinity profiles (near surface to 10
m off bottom) were obtained by using a Seabird SBE-
911+ CTD system. Profile data were collected during
deployment at a descent rate of ca. 0.5 m/s.
Statistically significant differences in age-0 condition,
growth, and feeding intensity among geographic areas
were detected with split-plot analysis of covariance (AN-
COVA) and post hoc multiple comparison tests (Proc
Mixed, SAS software, Littell et al., 1996). The covari-
ates were fish length or age (days since hatching). Fol-
lowing Milliken and Johnson (2002), we first tested for
covariate significance (H0: all slopes = 0) and homogene-
ity of slopes (H(): equal slopes) to ensure appropriateness
of the following reduced, common-slope model:
Y = a + (5x:j + Area ( + Sample, I Area 1 1 + eljk ,
where Y = dependent variable;
a = intercept parameter;
P = slope parameter;
x = covariate for sample i and area,/'; and
e k = replicate error for sample /', area./', and fish k.
A split-plot design was necessary to account for the
nesting of samples (trawl catches) within area, and
individuals within sample. To avoid pseudoreplication,
trawl catch was the sampling unit instead of individual
fish. Area was a fixed effect; sample was a random
effect. For body condition, lengths and weights were
log(,-transformed according to the method of Patterson
(1992); two points were omitted because of suspiciously
low length-specific, whole-body weight. For feeding in-
tensity, gut content weights (GCW) were fourth-root
transformed (GCW025) to linearize the GCW-length
relationship and remove heteroscedasticity (Clarke and
Warwick. 2001). Significance of post hoc pairwise dif-
ferences was based on a Bonferroni-corrected, 0.05-level
of significance. The standardized catch data were not
incorporated into these tests; therefore the conclusions
pertain to the samples not weighted by catch.
Nonmetric multidimensional scaling (NMS, PC-Ord,
McCune and Mefford, 1999) was used to ordinate the
diet and plankton samples according to taxonomic
composition. Each diet sample represented the aver-
age numerical composition of the diet of all fish in the
sample. This value was calculated by dividing the sum
of all items within each taxonomic category by the num-
ber of fish in the sample. The ordinations, one for diet
and another for plankton, were based on Bray-Curtis
similarity coefficients of fourth root-transformed data.
Differences among the four areas were statistically
tested by using a two-way nested analysis of similarity
Wilson et al.: Geographic variation among age-0 Theragra chalcogramma
211
Salinity (psu)
30 31 32 33 34 30 31 32 33 34 30 31 32 33 34 30 31 32 33 34
0 -
if
25 -
psu I J «c
/
I50:
u
Depth
00
25 -
Ugak Bay
I i
8 10 12
Chiniak Bay
8 10 12 4 6 8 10 12 4 6 8 10 12
Temperature (°C)
Figure 2
Water salinity and temperature profiles obtained in 10 casts at locations where
age-0 walleye pollock {Theragra chalcogramma) were collected near Kodiak
Island, Alaska, during 5-18 September 1993.
(ANOSIM, PRIMER, Clarke and Warwick, 2001) ap-
plied to the Bray-Curtis similarity matrices.
Results
Overall, salinity ranged from 30.3 to 33.0 ppt, and water
temperature ranged from 4.4 to 11.3°C (Fig. 2). Shal-
low surface layers of relatively fresh water were evident
from low near-surface salinities in Ugak Bay and in the
inner part of Kiliuda Bay. This part of Kiliuda Bay was
also well stratified thermally. Unfortunately, it was not
possible to include inner Kiliuda Bay as a fifth area in
subsequent statistical analyses because of insufficient
sampling. Thermal stratification was also evident at
shelf sampling locations.
A total of 5284 age-0 pollock were collected in 25
of the 32 successful trawl hauls (Table 1). These fish
were absent only at the four most-offshore locations
over Albatross Bank and Chiniak Gully (Fig. 3 1. In ad-
dition, no age-0 pollock were caught in shallow (<35-m
depth) tows at locations on Albatross Bank; a dense
and expansive school of capelin (Mallotus villosus) may
have displaced them downward. Median age-0 density
was 0.0006 fish/m3; the maximum (0.095 fish/m3) was
found in Ugak Bay.
Standard lengths of 2119 age-0 pollock ranged from
25 to 121 mm SL (Table 1, Fig. 4). The fish in Chiniak
Bay (91 mm SL), Ugak Bay (90 mm SL), and Kiliuda
Bay (89 mm SL) all had a median SL that were larger
than the median length of fish collected over the shelf
(71 mm SL). A surprising number of individuals <50
mm SL were collected in Ugak Bay and inner Kiliuda
Bay.
Body condition, based on the reduced, common-slope
ANCOVA model, varied among the four areas (Table 2).
Because of this effect, area-specific equations were used
to describe the length-weight relationship (Table 3,
Fig. 5A). After accounting for differences in length, we
found that fish from the shelf weighed less than the
individuals collected in Chiniak Bay and Ugak Bay.
Individuals from Kiliuda Bay were intermediate in
weight, differing only from the Ugak Bay fish (Table
4). Similar conclusions from the somatic-weight data of
fish used in the diet examinations indicated that gut-
content weight was not responsible for the relatively low
length-specific weights of fish from Kiliuda Bay and the
shelf (Tables 2 and 4).
The fish age-length relationship also varied by area.
The relationship was described by using a reduced,
common-slope model (Table 2). The common slope was
0.78 mm/d (Table 3, Fig. 5B). Differences in line eleva-
tion, or age-specific length, indicated that fish from
the shelf grew more slowly during the hatch-to-capture
period than did the fish from Chiniak or Kiliuda bays
(Table 4). Applying these equations to the length data
resulted in hatching-date distributions that ranged
from mid March to mid July (Fig.6). The fish collected
in Chiniak Bay (17 April), Kiliuda Bay (20 April), and
Ugak Bay (25 April) all had earlier median hatching
212
Fishery Bulletin 103(1)
578
576
57.4 -
57.2
152 8
152 4
152 0
Longitude (°W)
151.6
151.2
Figure 3
Geographic distribution of standardized catches (no. of individuals/m3)
of age-0 walleye pollock iTheragra chalcogramma) collected in trawl
hauls conducted near Kodiak Island during 5-18 September 1993.
dates in comparison to fish from the shelf (8 May). In-
terestingly, the hatching dates of the cohort of small in-
dividuals from Ugak Bay and inner Kiliuda Bay ranged
from June to July.
Mean otolith increment width varied with area. It
was not necessary to include fish length as a covariate
(Table 2). For the 1-5 d precatch period, the large mean
increment width associated with fish from Chiniak Bay
(0.036-mm band width) was different from the means of
Chiniak Bay
Ugak Bay
Kiliuda Bay
Shelf
30 40 50 60 70 80 90 100 110 120
Standard length (mm)
Figure 4
Size composition (mm SL) of age-0 walleye pollock (Thcr-
agra chalcogramma) by area from samples collected
near Kodiak Island, 5-18 September 1993.
each other area (Table 4). The only other difference was
between the Kiliuda Bay (0.026 mm) and shelf (0.030
mm) areas. The only difference for the 6-10 d precatch
period was again between the Kiliuda Bay (0.029 mm)
and shelf (0.036 mm) areas.
No area effect on gut content weight (GCW) was de-
tected (Table 2). There was, however, a significant fish
length effect (Fig. 5C), and this was incorporated in the
final model (Table 3). After adjusting for length, area-
specific mean GCW agreed in rank with area-specific
fish weight (Table 4).
Differences in taxonomic composition of age-0 pollock
diets resulted in a good separation of samples by area
(Fig. 7A, ANOSIM, K = 0.533, P=0.001). Each pair-wise
comparison of areas resulted in a significant difference
(P<0.05) (the one sample of small fish from Kiliuda
Bay, and two samples from the shelf of fish with empty
stomachs were omitted from the ANOSIM). The diet of
fish from Ugak Bay and Kiliuda Bay were mostly crab
larvae or copepods, depending on fish size (Table 5A).
Over the shelf, fish diets comprised mostly euphausiids
(74%). In contrast, fish from Chiniak Bay had a much
more varied diet; no single prey category exceeded 40%
of the items per stomach. Note the correspondence be-
tween the number of prey per fish (Table 5A) and mean
gut-content weight (Table 4); both were lowest for fish
from the shelf.
Differences in taxonomic composition also resulted in
separation of the plankton samples by area (Fig. 7B,
ANOSIM, i? = 0.886, P=0.001). Pair-wise comparisons
indicated a difference between Chiniak Bay and the
shelf (fl = 0.813, P=0.029). Ugak Bay was not included
in the comparisons because only one sample was avail-
Wilson et al.: Geographic variation among age-0 Theragra chalcogramma
213
Table 2
Summary results of six ANCOVA tests of an area effect on six
pollock: body condition (whole or somatic weight), three indices
and denominator degrees of freedom for the F test, respectively
dependent
of growth,
variables obtained from laboratory analysis of age-0
ind gut content weight. NDF and DDF are numerator
Dependent variable
H0: all
slopes = 0
Ho: equal
slopes
Reduced model
Source
NDF
DDF
Type III F
P>F
Condition
whole weight
P=0.0001
P=0.3340
Area
3
14.2
6.81
0.0045
ln(SL)
1
769
105824
0.0001
somatic weight
P=0.0001
P=0.3115
Area
3
17.8
10.01
0.0004
ln(SL)
1
294
31000
0.0001
Growth
age-specific length
P=0.0001
P=0.4140
Area
3
4.3
14.43
0.0106
Age
1
117
475.39
0.0001
1-5 d band width
P=0.2645
Area
3
93
8.05
0.0001
6-10 d band width
P=0.2267
Area
3
5.76
3.89
0.0768
Gut content weight
P=0.0001
P=0.7208
Area
SL
3
1
16.2
285
0.36
201.99
0.7850
0.0001
able. Copepods dominated the
catches in Chiniak Bay and over
the shelf, whereas larval crabs
were most prevalent in the Ugak
and Kiliuda samples (Table 5B).
In terms of overall abundance,
mean prey densities were lowest
among samples collected from the
shelf and highest for the Chiniak
Bay samples.
Discussion
The presence of age-0 pollock in
bays and over the inner shelf, but
not over the outer shelf, indicates
that the principal pollock nurs-
ery off east Kodiak Island during
autumn is relatively close to shore.
Earlier studies of age-0 pollock in
the western GOA focused on near-
shore areas (Smith et al., 1984;
Wilson, 2000) and did not docu-
ment the absence of age-0 pollock
over the outer shelf. Our results
point to prey resource as a likely explanation for the
observed distribution of and differences among age-0
walleye pollock.
Seasonal declines in zooplankton density underscore
the importance of nearshore areas as pollock nurseries.
Rogers et al.1 and Kendall et al.2 observed an order-of-
magnitude autumnal decline in prey3 density off Kodiak
Island during 1977-79 (Fig. 8). This decline was accom-
panied by a shoreward shift in the region of highest eu-
Table 3
Least-squares linear
relationships used
to
describe the condition, growth, and
feeding intensity of age-0 walleye pollock
collected September 1993, Kodiak Island,
Alaska. GCW = gut content weight.
Relationship
Location
Equation
Condition
whole weight
Chiniak Bay
ln(£) = 3.228(ln SLmm) - 12.646
Ugak Bay
ln(£) = 3.228(ln SLmm) - 12.609
Kiliuda Bay
\n(g) = 3.2281 In SLmm) - 12.659
Shelf
ln(£) = 3.228(ln SLmm) - 12.698
somatic weight
Chiniak Bay
ln(g) = 3.127* In SLmm) - 12.708
Ugak Bay
ln(g) = 3.127(ln SLmm) - 12.702
Kiliuda By
ln(£) = 3.127(ln SLmm) - 12.774
Shelf
ln(g) = 3.127(ln SLmm) - 12.816
Growth
length-at-age
Chiniak Bay
age(d) = 0.782(SLmm) - 22.294
Ugak Bay
age(d) = 0.782(SLmm) - 26.928
Kiliuda Bay
age(rf) = 0.782(SLmm) - 21.346
Shelf
age(rf) = 0.782(SLmm) - 31.011
Gut content weight
All combined
GCW(£025) = 0.007(SLmm) - 0.192
2 Kendall, A. W., Jr., J. R. Dunn, R. J. Wolotira Jr., J. H.
Bowerman Jr., D. B. Dey, A. C. Matarese, and J. E. Munk.
1980. Zooplankton, including ichthyoplankton and deca-
pod larvae, of the Kodiak shelf. NOAA NWAFC proc. rep.
80-8, 393 p. Alaska Fishery Science Center, Seattle, WA.
3 All invertebrate zooplankters are considered potential age-0
pollock prey except cnidarians, ctenophores, siphonophores,
and larval shrimps and crabs. Shrimp and crab were omitted
from Figure 8 because density estimates were not available
separately for the shelf and slope regions.
214
Fishery Bulletin 103(1)
phausiid density. Similar to our findings, the estimates
of larval crab densities from Rogers et al.'s and Kendall
et al.'s studies were always highest in bays. In autumn.
18
16
14
12
10
all locations
Chiniak Bay
Ugak Bay
Kiliuda Bay
Shelf
50 75 100
Standard length (mm)
125
B
I^U -
100 ■
ojljj
80 -
"J^Be*
t
60 -
t
' Chiniak
y^^
a Ugak
40 ■
o Kiliuda
• Shelf
80 100 120 140
Age (d)
c
160 180
0.5 •
V
Chiniak Bay
Ugak Bay
CO
04 •
G
Kiliuda Bay
•
Shelf
D)
0.3 ■
all locations
1
c
c
o
o
02 ■
0
3
0.1 ■
00 ■
Jgjfc
^
k.' *
•*,
20 40 60 80
Standard length (mm)
100
Figure 5
Least-squares regressions of age-0 walleye pollock
tTheragra chalcogramma) length on weight (Al, length
on age (B), and gut content weight on length (C) for
individuals collected from four areas off east Kodiak
Island, 5-18 September 1993.
the larger zooplankters are of principal importance to
age-0 pollock because of size-related changes in diet
(Table 5A, Merati and Brodeur, 1996).
By all accounts, age-0 pollock collected from Chiniak
Bay fared as well or better than individuals in each of
the other areas sampled. Wilson (2000) found that the
density of age-0 pollock in the Chiniak Bay vicinity
predicted Gulf-wide recruitment. However, these fish
represent a minuscule part of the Gulf-wide population
of age-0 pollock. Even if two cohorts, from spring- and
summer-spawnings, were produced, it seems unreason-
able to expect that local production would dramati-
cally affect gulf-wide recruitment. Alternatively, the
abundance and condition of age-0 pollock in this vicin-
ity might reflect larger-scale processes that relate to
gulf-wide recruitment. Identifying large-scale processes
based on small-scale sampling, however, is complicated
by variation at high spatial and temporal frequencies.
For example, the relatively high density of pea crab
(Fabia subquadrata) megalopae in combination with
influxes of freshwater (Epifanio, 1988) indicate that
local dynamics are important in sustaining prey popu-
lations in Ugak and Kiliuda bays. In contrast, Chiniak
Bay might be more affected by influxes of oceanic prey.
Such influxes could be facilitated by cross-shelf sea val-
leys, which extend into all the fjords that we sampled.
Indeed, Kendall et al.,2 Lagerloef (1983), and Stabeno et
al. (2004) have all shown that the local sea valleys in-
duce cross-shelf flow in the ACC. Furthermore, Inzce et
al. (1997) found that zooplankton density was elevated
in the Shelikof Sea Valley above the density found at
adjacent shelf areas; a similar phenomenon, however,
was not observed off northeastern Kodiak Island (Ken-
dall et al.2). Compared to the other bays, Chiniak Bay
might be best positioned to receive enriched ACC water
that flows south from where it bifurcates at the en-
trance to Shelikof Strait. Such enriched water may also
be an important transport mechanism for immigrating
larval and juvenile pollock (Wilson, 2000).
Because of the inconsistency among our various indi-
ces (i.e., weight-at-length, length-at-age, otolith incre-
ment width), it is difficult to conclude that fish over
the shelf and in Ugak and Kiliuda bays were prey
limited. Over the shelf, recent growth rates were not
low despite relatively small individual size and low
prey density. For example, the low prey densities and
small fish sizes over the shelf contrasted with recent
fish growth that was not low. Age-0 pollock are capable
of social foraging behavior to compensate for food scar-
city (Ryer and Olla, 1992), but it is unclear that the
associated energetic cost (Ryer and Olla, 1997) would
depress body weight before slowing otolith growth. In
contrast, fish in Kiliuda Bay had relatively slow recent
growth and low body weight, but age-specific length
was large. The observed differences in age-specific
length are somewhat discounted by the fact that such
differences may have arisen any time after hatching
and are not necessarily indicative of recent differences
in growth. Another complication was our inability to
reconstruct the spatial history of the sampled fish;
Wilson et al.: Geographic variation among age-0 Theragra chalcogramma
215
Table 4
Least-squares ad
lected September
comparison tests.
usted means of indices of body condition, growth, and gut content weight (GCW)
1993, Kodiak Island, Alaska. Means sharing the same superscript letter are not
P>0.05).
of age-0 walleye pollock col-
different (post hoc multiple
Location
Condition
Growth
GCW
(„0.25)
whole
wt. (lng)
somatic
wt. (\ng)
age-specific
SL (mm)
1-5 d band
width (mm)
6-10 d band
width (mm)
Chiniak Bay
1.47"6
0.82"
82.3°
0.036"
0.033°*
0.40
LTgak Bay
1.50*
0.83°
77.6°*
0.027*''
0.032°*
0.43
Kiliuda Bay
1.45ac
0.76*
83.2"
0.026*
0.029°
0.39
Shelf
1.42c
0.72*
73.6*
0.030'
0.036*
0.36
Chiniak Bay
Ugak Bay
Kiliuda Bay
Shelf
n~~ 1 1 r^ r~
21 Mar 10 Apr 30 Apr 20 May 9 Jun 29 Jun
Hatching date during 1993
Figure 6
Hatching-date composition of age-0 walleye pollock (Theragra
chalcogramma) by area from samples collected near Kodiak
Island, 5-18 September 1993.
in other words, we did not know where they had been
prior to capture.
As evidenced by geographic variation in hatching-date
distributions, cohort-specific differences persisted well
into the juvenile stage and had important implications
for inter-cohort differences in survival. The median
hatching dates of fish in bays were similar to those es-
timated for north Kodiak Island by Brown and Bailey
(1992). In contrast, fish over the shelf had substantially
later hatching dates. There is little evidence of pollock
spawning within our study area; therefore it seems
likely that the differences in hatching dates reflect suc-
cessive immigration of sequential cohorts. However, the
presence of the youngest cohort, fish hatched during
A
▲
▲
▲
2.0
1.0
s
■
_!_
V Chiniak B
A Ugak B
□ Kiliuda B
O Shelf
stress=17.84
r2=0.81
■
0 0 -
O
ov
V
A
A
□
D
D
10 -
o
o
O
□ D
-2 0
-1 5
-1.0 -0 5 0 0 0.5 10 1.5
E
CO
B
15
1 0
05 1
0.0
-0.5
-1.0 -I
-1 5
stress=9.79
r2=0.87
V
O
O
-15 -10 -0.5 0 0 0 5
NMS dimension 1
1 0
Figure 7
Nonmetric multidimensional scaling (NMS) of
samples based on age-0 walleye pollock (Theragra
chalcogramma) diet composition (A), or zooplankton
composition (B). Symbols indicate four different
sampling areas. For diet, the small (<66 mm SL)
fish in bays are represented by filled symbols.
216
Fishery Bulletin 103(1)
Bays (Rogers el al 1)
Nearshore (Kendall et a! *)
1000
A -
^
T
Middle shelf (Kendall etal )
.A
B
Slope (Kendall et al.3)
<| 800 -
/ s
/ \
«
' * \
CO
/ .••••. \
3
/ •• ■■ \
? 600 -
/ •••' '■•■ \
/ •■' '•■ v
c
/ • \
„_
/.■' ■ \
d 400
/ A \\
c
>>
/ / \ \
'to
/ \ V
S 200
•i— -^ ^~^\ \^~
J£— ■- -*" ^""--^.^^ D — ■***
-^
T**Tt
Spring Summer Fall
Winter
Figure 8
Seasonal variability in densities (no. of indiv
iduals/m3) of inverte-
brate zooplankton near Kodiak Island based
on samples collected
with 60-cm bongo nets with 0.333-mm mesh (
modified from Rogers
et al.1, Kendall et al.2).
June and July, only in the innermost parts of
Kiliuda Bay and Ugak Bay, may indicate an
alternative mechanism such as local spawn-
ing and geographic differences in retention.
Regardless, the relationship between fish
size and hatching date indicates that large
individuals were spawned early; thus, early
spawned individuals might experience higher
overwinter survival, which often increases
with fish size (Sogard, 1997).
We chose to track echo sign in our study
to reduce the sampling effort expended in
areas devoid of age-0 pollock. This meth-
od maximized our chance of collecting the
samples needed to study differences among
age-0 pollock given the limited vessel time.
Unfortunately, this method also introduced
a bias, thereby reducing the utility of den-
sity estimates to indicate habitat suitability
(Brown et al., 2000; Stoner et al., 2001) and
to extrapolate from samples to at-sea popu-
lations. Our focus, however, was on other
measures that might eventually provide a
Table 5
Numerical composition of age-0 pollock diet
samples (B) concurrently collected during 5-
by location and predator SL (A), and composition of the plankton in 1-m2
-18 September 1993, Kodiak Island, Alaska, "t" signifies trace (<0.05).
Tucker
A
Prey (number of individuals/fish )'
No. of
Area
Sample
(ra)
no. of
fish
amphipod
chaetognath
copepod
crab
larvae
cumacean
euphausiid
mysid
shrimp
larvae
prey/
fish
Chiniak Bay
5
75
2.8
t
4.1
0.1
0.0
3.7
0.4
t
11.0
Ugak Bay
<66 mm
3
31
0.1
0.6
11.2
0.6
0.0
0.1
t
0.0
12.6
>66 mm
4
60
0.1
t
5.9
15.9
t
3.3
0.2
t
25.6
Kiliuda Bay
<66 mm
1
5
0.0
0.2
2.2
1.0
0.0
0.2
0.0
0.0
3.6
>66 mm
6
61
t
t
t
6.4
t
2.7
t
t
9.2
Shelf
6
65
0.3
0.0
0.1
0.1
t
2.8
0.4
0.1
3.8
' 0</<0.05.
B
Zooplankton (number of individuals/m3)'
total
Area
Sample
in)
amphi-
pod
chaeto-
gnath
copepod
crab
larvae
euphau-
siid
fish
larva
larvacean
mysid
shrimp
larvae
no./
m3
Chiniak Bay
4
t
9
332
1
23
t
4
2
4
375
Ugak Bay
1
t
13
12
48
2
t
3
1
t
80
Kiliuda Bay
2
t
13
40
82
28
t
17
4
3
188
Shelf
4
t
1
51
1
4
t
15
t
2
74
' 0</<0.05. In
zooplankton samples
cumaceans were not enumerated.
Wilson et al.: Geographic variation among age-0 Theragra chalcogramma
217
useful supplement to abundance distribution data (Beu-
tel et al., 1999).
This study enabled us to conclude that Chiniak Bay
is particularly well suited for rearing pollock probably
because of influxes of zooplankton. It remains to be
seen if Chiniak Bay contributes relatively high num-
bers of recruits, or if other counteracting factors such
as predation exist. Nevertheless, we have demonstrated
that differences among juvenile pollock exist at meso-
geographic scales and that these differences are useful
for inferring how specific areas might relate to the
population dynamics of walleye pollock.
Acknowledgments
R. Brodeur provided the initial impetus for this study.
P. Munro and D. Somerton accommodated our request
to share ship time. The captain and crew of the NOAA
ship Miller Freeman helped make our at-sea operations
efficient and pleasurable. M. Busby assisted with field
operations. We gratefully appreciate the comments of
many people: K. Bailey, J. Napp, A. Stoner, S. Syrjala,
N. Bartoo, the AFSC Publications Unit, and several
anonymous reviewers.
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219
Tagging studies on the jumbo squid
(Dosidicus gigas) in the Gulf of California, Mexico
Unai Markaida
Deparlamento de Ecologia, Centra de Investigacion Cientifica y
de Educacion Superior de Ensenada (CICESE)
Ctra. Ti|uana-Ensenada km 107
Ensenada. Ba|a California, Mexico
Present address: Departamento de Aprovechamiento y Maneio de Recursos Acuaticos
El Colegio de la Frontera Sur
Calle 10x61 No 264
Colonia Centra. 24000 Campeche, Mexico
Joshua J. C. Rosenthal
Institute of Neurobiology
University of Puerto Rico
201 Blvd del Valle
San Juan. Puerto Rico 00901
William F. Gilly
Hopkins Marine Station
Stanford University
Pacific Grove, California 93950
Email address (for W F Gilly. contact author): lign|eia'stan(ord edu
Dosidicus gigas, the only species in
the genus Dosidicus, is commonly
known as the jumbo squid, jumbo
flying squid (FAO, see Roper et al.,
1984), or Humboldt squid. It is the
largest ommastrephid squid and
is endemic to the Eastern Pacific,
ranging from northern California
to southern Chile and to 140°W at
the equator (Nesis, 1983; Nigmatul-
lin, et al., 2001). During the last two
decades it has become an extremely
important fisheries resource in the
Gulf of California (Ehrhardt et al.,
1983; Morales-Bojorquez et al., 2001),
around the Costa Rica Dome (Ichii
et al., 2002) and off Peru (Taipe et
al., 2001). It is also an active preda-
tor that undoubtedly has an impor-
tant impact on local ecology in areas
where it is abundant (Ehrhardt et al.,
1983; Nesis, 1983; Nigmatullin et al.,
2001; Markaida and Sosa-Nishizaki,
2003).
Ommastrephid squid, including the
jumbo squid, are largely pelagic and
may migrate long distances as part
of their life cycle (Mangold, 1976). A
general pattern of long-distance mi-
gration for the jumbo squid over its
entire range was proposed by Nesis
(1983) and smaller-scale migrations
within the Gulf of California have
also been proposed according to the
distribution of the fishery during
1979-80 (Klett, 1982; Ehrhardt et
al., 1983). During this period squid
were reported to enter the Gulf from
the Pacific in January, to reach their
northernmost limit (29°N) by April,
and to remain in the central Gulf
from May through August; the high-
est concentrations were found along
the western (Baja California) coast.
From September onward these squid
appear to migrate eastward to the
Mexican mainland coast and then
southwards, to the mouth of the Gulf
and back into the Pacific (Klett, 1982;
Ehrhardt et al., 1983).
Since 1994 a seasonal pattern in
the jumbo squid fishery has emerged
in which large squid are abundant in
the central Gulf essentially all year.
During November to May, the fishery
is centered in the area of Guaymas.
In Sta. Rosalia the fishery oper-
ates from May to November, which
is also the period of peak landings
(see Fig. 1; SEMARNAP, 1996, 1997,
1998, 1999, 2000; SAGARPA, 2001;
SAGARPA1) (see also Markaida and
Sosa-Nishizaki, 2001). These gener-
ally reciprocal landing patterns are
consistent with the abundance pat-
terns described by Klett (1982), al-
though the exact migrations proposed
by Ehrhardt et al. (1983) have never
been directly observed (Morales-Bo-
jorquez et al., 2001).
All these studies concerning jumbo
squid migrations have relied on anal-
yses of landing statistics and catch
data acquired by fishing stations on
commercial squid-jigging vessels. Al-
though migratory patterns of several
other ommastrephid species of com-
mercial importance have been directly
demonstrated with conventional tag-
and-recapture methods (Nagasawa et
al., 1993), to our knowledge jumbo
squid has not been studied in this
manner. Given the commercial and
ecological importance of this spe-
cies, such studies would be valuable.
This paper describes conventional
tag-and-recapture experiments on
jumbo squid in the central Gulf of
California. Tag-return rates were
higher than in most previous stud-
ies of other ommastrephid species,
and seasonal migrations between
the Sta. Rosalia and Guaymas areas
were directly demonstrated. Growth
rates were also directly determined
for the first time.
SAGARPA (Secretaria de agricultura,
ganaderia, desarrollo rural, pesca y
alimentacidn). Anuario Estadistico
de Pesca, http://www.sagarpa.gob.mx/
conapesca/planeacion /anuario /a nu-
ario2001.zip and http://www.sagarpa.
gob.mx/conapesca/planeacion/anuario
2002. [Accessed 26 July 2004.]
Manuscript submitted 21 March 2003
to the Scientific Editor's Office.
Manuscript approved for publication
8 September 2004 by the Scientific Editor.
Fish. Bull. 103:219-226(2005).
220
Fishery Bulletin 103(1)
0 '(*i | i i | i i | i i | i i | i i | i i | i i | i i | i i | i i | i i | IT] i i | i i | i ifnyf i | i i | i i | i i | i i | i i | i r | I r ! i i ! i i| i i | i i | i i | i i | i
Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct
1995
1996
1997
1998 1999
Month
2000
2001
2002
Figure 1
Monthly landings (in metric tons) of Dosidicus gigas in Mexico from 1995 through 2002.
Materials and methods
Santa 1_,
Rosalia ?
BAJA
CALIFORNIA
SUR
Fieldwork was carried out in two sepa-
rate experiments along both coasts of the
Guaymas basin (see Fig. 2). This area of
the central part of the Gulf of California
accounts for more than 95% of Mexican
jumbo squid landings. A total of 996 squid
were tagged between 9 and 16 October
2001, in the general vicinity of Sta. Rosa-
lia, Baja California Sur (B.C.S.), as indi-
cated in Figure 2. Another 997 squid were
tagged off Guaymas, Sonora, between 3
and 7 April 2002. Both experiments were
conducted close to the anticipated end of
the respective fishing seasons for each
zone, because we hoped to obtain recap-
tures both locally and from more distant
sites after the squid had migrated away
from the fishing areas.
Squid were caught by commercial fish-
ermen using hand-lines with 30-cm jigs
and were tagged on deck with spaghetti-
type, plastic cinch-up tags (Floy Tag Co.,
Seattle, WA) through the anterior edge of
the dorsal mantle. This process took about
30 seconds, and the squid was then imme-
diately released. All squid quickly jetted away with no
obvious sign of trauma or physical impairment. Animals
with any visible damage, primarily form cannibalistic
attacks by other squid, were not tagged. In addition,
dorsal mantle length (ML) was measured to the nearest
mm for all squid in the Guaymas experiment.
Tag-return information was imprinted on the tag, and
posters announcing the experiment were distributed at
squid-landing ports and at local processing facilities in
Sta. Rosalia, San Lucas, San Bruno, Mulege, Loreto
and La Paz (B.C.S.), as well as in San Carlos, Guay-
Tag recoveries:
' 1 C 11-16
© 2-3 f
» 5-6 *
SONORA
juaymas
Figure 2
Map of the Guaymas basin in the central Gulf of California showing both coasts
where the tagging experiments were performed. Area of detailed main map is
indicated by a gray rectangle in upper leftmost inset. Numbers of tags deployed
are in bold type in main map. Symbols for the numbers of tags recovered are
indicated in the inset "Tag recoveries." Black symbols represent squid tagged
off Sta. Rosalia; white symbols represent squid tagged off Guaymas. Depth
contours are in meters. Adapted from Bischoff and Niemitz (1980).
mas, Yavaros (Sonora) and Mazatlan (Sinaloa) (Fig. 2).
A monetary reward ($50 US) was offered for each tag
returned with information on recapture date and lo-
cation. During the second experiment an additional
reward was offered for information on squid ML and
stage of sexual maturity as defined by Lipinski and
Underhill (1995): immature (stages I— II ), maturing
(III) and mature (IV-V). Average daily growth rate
(DGR) was calculated from the increase in ML between
tagging and recapture divided by the number of days
elapsed during this period.
NOTE Markaida et al.: Tagging studies on Dosidicus gigas
221
9 I
Sta. Rosalia, 9-16 October 2001
Ml Sta. Rosalia n=71
Guaymas n=9
ii i mi
L
■ ( ■ ■ ■ ■ i ■
0 10
October
20 30 40 50 60 70 80 90 100 110
I
November
I December
January
Guaymas, 3-7 April 2002
^^™ Guaymas n=61
Sta. Rosalia n=19
nil , i
JU
0 10
April
vrHk
20 30 40 50 60 70 80 90 100 110 120 130 140 210 220
May June July August Oct [ Nov
June
Days after tagging
I
Figure 3
Time course for recapture data for squid tagged off Santa Rosalia (A) and off Guaymas
(B). In both sections, black bars represent squid recaptured from the same coast where
tagging was done, and gray bars represent squid recaptured from the opposite coast.
Note that a gap exists between August and October in panel B.
Results
Timing of tag returns
A total of 80 tags (8.03%) were recovered for the squid
tagged off Sta. Rosalia. Of these, 71 were recovered in
the general vicinity of this port. More than a third of
these tags (25) were discovered at commercial squid
processing plants, where the mantles are manually
cleaned before final processing. Squid were captured
generally shortly after tagging; most of the tags (52)
were recovered during the first 15 days (Fig. 3A). The
shortest recapture period was only several hours. In this
case, a squid tagged by the crew of one of our boats was
caught about one km away by our second boat.
In addition to the Sta. Rosalia returns, another nine
squid (0.9%) were recaptured off Guaymas, from 39 to
108 days after tagging (Fig. 3A). The temporal overlap
in returns from the two localities (days 39-55) and the
total lack of any subsequent Sta. Rosalia returns would
indicate that a significant number, if not most, of the
squid migrated from Sta. Rosalia to Guaymas and po-
tentially elsewhere during this period (17 Nov-4 Dec).
In the second experiment, conducted off Guaymas, 80
tags (8%) were also recovered. Sixty-one were recovered
in the Guaymas area over an extended period from 2 to
224 days after tagging (Fig. 3B). In this case, the squid
were recaptured more or less constantly at a low rate
over the first 60 days. Surprisingly, only one tag was
recovered at a processing plant during this period. Spo-
radic returns then continued in Guaymas over the next
three months. It should be noted that there was little
squid fishing activity in the area during September
because of the beginning of the commercial shrimp sea-
son. The final three tags were recovered after 219-224
days (8-13 Nov). These squid were tagged on the same
night and location seven months earlier.
Of the tags deployed in Guaymas, 19 (1.9%) were
recovered in the Sta. Rosalia area in summer 2002
(28 May-29 August) from 54 to 207 days after tagging
(Fig. 3B). Seven of these tags were recovered at squid
factories. A period of overlapping returns occurred over
days 54-72, and we interpreted this overlap in returns
as being consistent with a seasonal mass migration
form Guaymas to Sta. Rosalia. A second period of over-
lapping returns of similar duration occurred in July.
However, in this case, returns from Guaymas continued
throughout the entire summer and into the fall. It thus
appears that some squid remained in the Guaymas area
during this period.
222
Fishery Bulletin 103(11
Dependence of recapture rate on squid size
Squid tagged off Guaymas ranged from 32.7 to 83 cm ML
(mean [±SD] of 56.6 [±7.5] cm ML [Fig. 4]). Recapture
rate is clearly size dependent. No squid smaller than
46 cm ML were recaptured, and recapture rates were
low (1.3-3.4%) for squid of 46-50 cm ML. However,
recapture increased in roughly direct proportion to ML,
reaching 15-20% for squid >70 cm ML.
come from the four squid that grew from 47-53 to 71-74
cm ML in 207-224 days, and these measurements yield
a mean DGR of 1.05 [±0.05] mm/day (Fig. 5 and V in
Fig. 6). Solid and dashed curves in Figure 6 represent
DGR independently determined for both sexes through
analysis of statolith increments (Markaida et al., 2004)
for squid of a comparable size range. These growth
rates are about twice those determined in the present
study by direct ML measurements.
Determination of daily growth rate (DGR)
Dorsal ML was measured from forty-four squid tagged
off Guaymas after recapture at 4 to 224 days. ML values
ranged between 46 and 80.7 cm. Variability in DGR
determination, as indicated by the standard devia-
tion (SD) of binned data from 20-day intervals, clearly
decreased as the time to recapture increased. Thus, a
significant negative correlation exists between the SD of
DGR and recovery time (r2=0.88, P<0.01, n = 6) (Fig. 5).
Six measurements of squid caught before 40 days yielded
negative growth rates. This finding indicates that large
discrepancies in DGR calculations exist in measure-
ments on squid with short recapture times, because any
errors in ML measurement are generally much larger.
Growth rate estimates from squid captured after 40 days
yielded values of 1.0-1.5 mm/day (SD of 0.05-0.6). We
regard these as the only reliable data.
Further analysis of DGR was limited to squid cap-
tured after 40 days. Figure 6 illustrates DGR versus
"mean" ML (average of ML at times of tagging and re-
capture) for selected squid of different sexes and stages
of maturity. Probably the most reliable DGR estimates
Tagged off Guaymas n = 995
Recaptured off Guaymas n = 58
Recaptured off Sta Rosalia n=18
Recapture rate
0.20
- 0.15
0.10
0.05
000
Discussion
Tag return rates
High recovery rates obtained in our study clearly demon-
strate that D. gigas in the Gulf of California is suitable
for tagging studies. This large species is relatively easily
tagged with conventional plastic tags, and the tagging
operation produced no obviously deleterious effects on
the squid. These features make jumbo squid an attrac-
tive species for application of archival electronic tags or
telemetry devices.
Despite extensive tagging efforts and intense com-
mercial fisheries, recapture rates for other species of
ommastrephid squid have generally been much lower.
In the extreme case, no recaptures whatsoever were ob-
tained for the northern shortfin squid (lllex illecebrosus)
tagged in offshore waters of Newfoundland (Hurley and
Dawe, 1981). In other studies recaptures ranged from
0.03-0.1% for the Argentine shortfin squid (/. argenti-
nus) in the Southwest Atlantic (Brunetti et al., 2000), to
1.0-6.2% for the European flying squid (Todarodes sag-
ittatus) off Norway (Wiborg et al.2). The neon
flying squid iOmmastrephes bartramii) from the
North Pacific also yielded low rates (0.1-0.5%;
Murata and Nakamura, 1998; see also Nagasa-
wa et al., 1993). In 62 years of tagging studies
of Japanese flying squid (Todarodes pacificus),
only a few experiments carried out in the Sea
of Japan and Tsugaru Strait yielded return
rates that match those of the present study
(up to 16.4%; see Nagasawa et al., 1993). The
highest tag recovery rate (19-32%) was found
for the northern shortfin squid in Newfound-
land inshore areas (Hurley and Dawe, 1981).
Recapture rates of up to 12.7% have also been
reported for large, neritic loliginid squid (Naga-
sawa et al., 1993; Sauer et al., 2000).
In the present study, recapture rate was
found to be directly proportional to mantle
length, ranging from <3.5% for squid <50 cm
ML (cm) at tagging
Figure 4
Mantle length (ML) distribution for all squid tagged off Guay-
mas (white bars) and for those recaptured off Guaymas (gray
bars) and Santa Rosalia (black bars). Black circles represent
recapture rate.
2 Wiborg, K. F., J. Gjosaeter, I. M. Beck, and P.
Fossum. 1982. The squid Todarodes sagittatus
(Lamarck). Distribution and biology in Northern
waters, August 1981-April 1982. Council Meet. Int.
Coun. Explor. Sea (K:30):l-17. ICES, Palaegade
2-4, DK-1261, Copenhagen K, Denmark.
info@ices.dk.
NOTE Markaida et al .: Tagging studies on Dosidicus gigas
223
ML to 20% for squid close to 80 cm ML (Fig.
4). Reasons for this strong size-dependence
are not clear. Smaller squid may either suffer
a higher natural mortality rate or migrate
southward out of the Guaymas basin more
readily than the larger squid. We do not be-
lieve that the tagging process itself leads to
such a difference in mortality rate, but this
possibility cannot be ruled out.
Several factors are relevant to evaluating
differences in recapture rates for jumbo squid
and other ommastrephids. First, squid of the
other species are not as large as jumbo squid.
We are not aware of any other published data
on size-dependence of recapture rates, but
this phenomenon may be relevant. Second,
the localized nature of the fisheries surround-
ing the Guaymas basin equates with high
concentrations of squid in relatively small ar-
eas that are intensively fished. Most recent
tagging studies of other ommastrephids have
taken place in oceanic waters in the Sea of
Japan and North Pacific, where the fishing
zone is extremely large and far from any lo-
calized coastal fishing areas (Nagasawa et
al, 1993). The extreme disparity in return
rates for nearshore versus offshore studies
in Newfoundland supports this idea. Third,
an ambitious advertising campaign (posters)
and the substantial reward offered for tag
returns undoubtedly stimulated a high degree
of cooperation in the largely artisanal Mexi-
can fishery that is highly concentrated in Sta.
Rosalia and Guaymas. A strong dependence
of tag-return rate on rewards and advertis-
ing has been previously noted (see Nagasawa
et al., 1993).
Seasonal migration
Results from this study directly demonstrate
that jumbo squid in the Guaymas basin
migrate across the Gulf on a seasonal basis.
Squid appear to migrate from Sta. Rosalia to
Guaymas during the second half of November
and early December and to make the reverse
trip in late May and early June. Thus, large
squid (40-80 cm ML) remain available to fish-
eries surrounding the Guaymas basin through-
out the year. These data support the idea
that these fishing areas are feeding grounds
(Markaida and Sosa-Nishizaki, 2001). What
fraction of squid, if any, migrate southward out
of the Guaymas basin and potentially into the
Pacific cannot be ascertained from our data.
Transit time across the Gulf for the migrat-
ing squid appears to be fairly brief — proba-
bly less than 16 days based on the overlap of
recaptures in both fishing areas. Assuming
a straight-line distance of 130 km between
CO 1
XI '
E
E
DC
O
a
• . • *T
• 6 *
□ • •
0 --
-2
-3 -I
0 10 20 30 40 50 60 70 80 90 100 210 220
Days elapsed between tagging and recapturing
Figure 5
Daily growth rate (DGR) in mantle length (ML) determined for
squid recaptured at different times after tagging. Black circles
represent measurements from individual animals. Gray squares
represent means ±1 SD for squid grouped in 20-day bins. Note
that a gap exists between 100 and 200 days.
v Recaptured after 200 days
o Immature Female
• Mature Female
Maturing Male
Mature Male
Mean ±SD for each 5-cm ML bin
Females (Markaida et al.. 2003)
Males
ra 2.0
E
E
rr
a
60 65 70
Mean ML (cm)
80
Figure 6
Relationship of daily growth rate (DGR) and mean mantle length (ML)
(average of measured ML at time of tagging and time of recapture).
Small symbols represent measurements from selected individual
animals as follows: squid recaptured after >200 days (V), immature
female (Ol, mature female (•), maturing male (A), mature male (A).
Larger squares (■) indicate means ±1 SD for all data pooled into
5-cm bins. Analysis was limited to squid recaptured after 40 days
and of identified sex. Curves represent DGR vs. ML relationship
as determined by counting statolith increments for females (solid)
and males (dashed) and are adapted from Markaida et al. (2004).
224
Fishery Bulletin 103(1)
these areas, the average maintained speed during the
migration would be about 8 km/day. A comparable fig-
ure can be derived from one of our first squid to be
recaptured. This animal was tagged at Pt. Prieta (see
Fig. 2) and recaptured 20 km away off Sta. Rosalia (Fig.
2) after three days.
This estimated velocity for a trans-Gulf migration is
well within the range of rates observed in other studies
of ommastrephids (O'Dor, 1988). Jumbo squid tracked
with acoustic telemetry off Peru covered 3-5 miles in
8-14 hours, or about 14 km/day (Yatsu et al., 1999).
Neon flying squid tracked in the same way covered up
to 22 km per day (Nakamura, 1993). Migration rates
obtained from tagging studies yielded even higher es-
timates. Maximum speed for migrating short-finned
squid has been estimated at 20-30 km/day (Dawe et al.,
1981; Hurley and Dawe, 1981), and high rates have also
been reported for the Japanese squid (see Nagasawa et
al., 1993). Large loliginid squid have been reported to
migrate at rates of 3 to 17 km/day (see Sauer et al.,
2000).
Daily growth rates
Variance in DGR estimates from ML measurements
decreased dramatically after 30 days after tagging, and
became fairly consistent by 50 days. Clearly, estimates of
DGR in our study are only reliable for these later times,
and a DGR of 1-1.5 mm/day in ML is evident for squid
in the 50-70 cm range of ML (Fig. 6). These absolute
rates would correspond to relative rates of 0.15-0.22%
increase in ML per day.
There are few comparable estimates of growth rates
for other ommastrephid squids based on tag-recapture
studies. However, the neon flying squid grows 0.5-2.7
mm/day in the 18-48 cm ML range (Araya, 1983), and
good agreement exists between growth rates obtained
from tag-recapture studies and those from statolith ag-
ing studies (Yatsu et al., 1997). When converted to rela-
tive growth rate, this species would thus appear to grow
substantially faster than the jumbo squid. The common
Japanese squid grows 0.45 mm/day (Nagasawa et al.,
1993), but for this species, mantle lengths were not
given; therefore relative rates cannot be estimated.
More importantly, absolute growth rates determined
by direct ML measurements in the present study dis-
agreed with those derived from statolith aging methods
(Markaida et al., 2004), and this discrepancy merits
re-evaluation of previous longevity estimates. Squid of
50 cm ML are thought to be about 260 days old based
on statolith ring counts, and our tag-recapture study
revealed that it can take another 200 days to grow to 70
cm ML. The estimated age at this size would therefore
be 460 days, about 100 days more than that estimated
by statolith aging for squid of 70 cm ML (Markaida et
al., 2004). Thus, the largest squid found in the Gulf of
California (about 90 cm ML) might be up to 2 years
old.
Reasons for the apparent underestimates in longevity
with statolith aging are unclear. Difficulty in resolving
discrete rings late in life of a specimen is one possibil-
ity. Another is that the assumed daily ring deposition
may not occur throughout the lifetime of a jumbo squid.
No successful validation studies have been reported for
this species, either in the laboratory or in the wild.
Squid distributions in the Gulf in relation
to commercial landings
Although large-scale migrations of jumbo squid within
the Guaymas basin are apparently responsible for the
seasonal pattern in the commercial landings (Fig. 1; see
also Markaida and Sosa-Nishizaki, 2001), the biological
and oceanographic reasons for these migrations are not
well established. The reciprocal pattern in squid distri-
bution between the eastern and western central Gulf is
correlated with the wind-driven upwelling seasonality
in this area (Roden and Groves, 1959) and is probably
highly influenced by this oceanographic feature. A simi-
lar situation exists in the life cycle of another important
pelagic resource, the Pacific sardine (Sardinops caeru-
leus) (Hammann et al., 1988).
However, other biological factors are also probably
important. Summer upwelling in the western Gulf is
actually less intense than off the eastern coast in win-
ter (Hammann et al., 1988; Santamaria-del-Angel et
al., 1999), yet 80% of squid landings were made at Sta.
Rosalia between 1995 and 1997 (Markaida and Sosa-
Nishizaki, 2001). We propose that concentrations of
spawning myctophids (lanternfishes) off Baja California
in the summer (Moser et al., 1974) may be largely re-
sponsible for this disparity because these fish are a ma-
jor prey item for squid in the Guaymas basin (Markaida
and Sosa-Nishizaki, 2003).
Data in the present study also indicate that jumbo
squid may be available to commercial fishing efforts off
each coast for a longer period than previously thought.
Our data indicate that squid were recovered in the
waters off Guaymas throughout the year; therefore it
is likely that some squid do not undergo the westward
spring migration (Fig. 3B). However, it is not certain
that the final returns from Guaymas after 7 months
were of this resident stock, because they would have
had time to migrate to Sta. Rosalia and back again. It
is also unclear whether a resident stock of squid exists
in the Sta. Rosalia area year-round. Strong northern
winds in this area lead to a cessation of commercial
fishing efforts during the winter months, and the lack
of tag returns during winter may simply reflect this
fact.
Long-distance migrations into and out of
the Gulf of California
Although data in this paper have demonstrated seasonal
migrations of jumbo squid within the Guaymas basin,
migration patterns into this region from the southern
Gulf and open Pacific (and back out) remain unknown.
The much lower level of commercial fishing effort in
these latter areas will greatly constrain efforts to elu-
NOTE Markaida et al : Tagging studies on Dosidicus gigas
225
cidate migrations over these longer distances using
conventional tag-and-recapture approaches.
Presumably, as the largest eunektonic squid, jumbo
squid should be able to perform large-scale migrations
covering its whole geographic range as do other om-
mastrephids (O'Dor, 1988). The high tag return rates
achieved in the present study, in conjunction with the
large size of the squid, make application of a variety of
archival electronic tagging devices an attractive pos-
sibility. Such devices could reveal long-distance migra-
tions across the large range of jumbo squid in a fishery-
independent manner.
Acknowledgments
We acknowledge funding for this project by the Tagging
of Pacific Pelagics (TOPP) program and the Census of
Marine Life (COML). We thank Oscar Sosa-Nishizaki
(CICESE, Ensenada) for administering this project
in Mexico and providing laboratory space and facili-
ties. Volunteer field workers in Sta. Rosalia included A.
Novakovic, J. Schulz, S. Sethi (Stanford Univ.), and L.
Roberson (California State University, Northridge). We
are also indebted to personnel of Centro Regional de
Investigacion Pesquera, especially Manuel O. Nevarez,
Paco Mendez, and Araceli Ramos, for their support
during tagging and tag recovering at Guaymas, and
to Sandra Patricia Garaizar and Vicente Monreal for
recovering tags in Sta. Rosalia. We extend our sincere
gratitude to all fishermen and squid factory personnel
for their cooperation.
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Fishery Bulletin 103(1)
227
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Fishery
Bulletin
Contents
MAY 1 0 2005
The conclusions and opinions expressed
in Fishery Bulletin are solely those of the
authors and do not represent the official
position of the National Manne Fisher-
ies Service (NOAA) or any other agency
or institution.
The National Manne Fisheries Service
(NMFS) does not approve, recommend, or
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of this NMFS publication.
Articles
229—245 Alonzo, Suzanne H., and Marc Mangel
Sex-change rules, stock dynamics, and the performance of
spawmng-per-recruit measures in protogynous stocks
246-257 Brandon, Elisif A. A., Donald G. Calkins,
Thomas R. Loughlin, and Randall W. Davis
Neonatal growth of Steller sea lion (Eumetopias jubatus) pups
in Alaska
258-269 Brouwer, Stephen L, and Marc H. Griffiths
Reproductive biology of carpenter seabream (Argyrozona
argyrozona) (Pisces: Sparidae) in a marine protected area
270-279 Burn, Douglas M., and Angela M. Doroff
Decline in sea otter (Enhydra lutris) populations along the
Alaska Peninsula, 1986-2001
280-291 Carlson, John K„ and Ivy E. Baremore
Growth dynamics of the spinner shark (Carcharhinus
brevipinna) off the United States southeast and Gulf of Mexico
coasts: a comparison of methods
292-306 Domeier, Michael L, Dale Kiefer, Nicole Nasby-Lucas,
Adam Wagschal, and Frank O'Brien
Tracking Pacific bluefin tuna (Thunnus thynnus orientalis) in
the northeastern Pacific with an automated algorithm that
estimates latitude by matching sea-surface-temperature data
from satellites with temperature data from tags on fish
307-319 Fischer, Andrew J., M. Scott Baker Jr., Charles A Wilson,
and David L. Nieland
Age, growth, mortality, and radiometric age validation of
gray snapper (Lut/anus gnseus) from Louisiana
320-330 Grabowski, Robert C, Thomas Windholz, and Yong Chen
Estimating exploitable stock biomass for the Maine green
sea urchin {Strongylocentrotus droebachiensis) fishery using
a spatial statistics approach
Fishery Bulletin 103(2)
331—343 Lowry, Mark S., and Karin A. Forney
Abundance and distribution of California sea lions (Zalophus caltfornianus) in central and northern
California during 1998 and summer 1999
344—354 Mackie, Michael C, Paul D. Lewis, Daniel J. Gaughan, and Stephen J. Newman
Variability in spawning frequency and reproductive development of the narrow-barred Spanish mackerel
(Scomberomorus commerson) along the west coast of Australia
355—370 Ruggerone, Gregory T., Ed Farley, Jennifer Nielson, and Peter Hagen
Seasonal marine growth of Bristol Bay sockeye salmon (Oncorhynchus nerka) in relation to competition
with Asian pink salmon (O. gorbuscha) and the 1977 ocean regime shift
371—379 Shoji, Jun, and Masaru Tanaka
Distribution, feeding condition, and growth of Japanese Spanish mackerel (Scomberomorus niphonius) larvae
in the Seto Inland Sea
380-391 Wang, You-Gan, and Nick Ellis
Maximum likelihood estimation of mortality and growth with individual variability from multiple
length-frequency data
392-403 Williams, Erik H., and Kyle W. Shertzer
Effects of fishing on growth traits: a simulation analysis
Notes
404-406 Burton, Michael L, Kenneth J. Brennan, Roldan C. Muhoz, and Richard O. Parker Jr.
Preliminary evidence of increased spawning aggregations of mutton snapper (Lut/anus ana/is)
at Riley's Hump two years after establishment of the Tortugas South Ecological Reserve
411—416 Carpentieri, Paolo, Francesco Colloca, Massimiliano Cardinale, Andrea Belluscio,
and Giandomenico D. Ardizzone
Feeding habits of European hake (Mer/ucaus mer/uccius) in the central Mediterranean Sea
417—425 Gobert, Bertrand, Alain Guillou, Peter Murray, Patrick Berthou, Maria D. Oqueli Turcios, Ester Lopez,
Pascal Lorance, Jerome Huet, Nicolas Diaz, and Paul Gervain
Biology of the queen snapper (Etelis oculatus: Lutjanidae) in the Caribbean
426—432 Graham, Rachel T., and Daniel W. Castellanos
Courtship and spawning behaviors of carangid species in Belize
433—437 Hewitt, David A., and John M. Hoenig
Comparison of two approaches for estimating natural mortality based on longevity
438-444 Lindquist, David C, and Richard F. Shaw
Effects of current speed and turbidity on stationary light-trap catches of larval and juvenile fishes
445—452 Macchi, Gustavo J., Marcelo Pajaro, and Adrian Madirolas
Can a change in spawning pattern of Argentine hake (Merlucaus hubbsi) affect its recruitment?
453—460 Raymundo-Huizar, Alma R., Horacio Perez-Espana, Maite Mascaro, and Xavier Chiappa-Carrara
Feeding habits of the dwarf weakfish (Cynosaon nannus) off the coasts of Jalisco and Colima, Mexico
461-466 Wood, Anthony D.
Using bone measurements to estimate the original sizes of bluefish (.Pomatomus saltatnx)
from digested remains
467 Subscription form
229
Abstract— Predicting and under-
standing the dynamics of a popula-
tion requires knowledge of vital rates
such as survival, growth, and repro-
duction. However, these variables are
influenced by individual behavior,
and when managing exploited popu-
lations, it is now generally realized
that knowledge of a species' behav-
ior and life history strategies is
required. However, predicting and
understanding a response to novel
conditions — such as increased fish-
ing-induced mortality, changes in
environmental conditions, or specific
management strategies — also require
knowing the endogenous or exogenous
cues that induce phenotypic changes
and knowing whether these behaviors
and life history patterns are plastic.
Although a wide variety of patterns of
sex change have been observed in the
wild, it is not known how the specific
sex-change rule and cues that induce
sex change affect stock dynamics.
Using an individual based model, we
examined the effect of the sex-change
rule on the predicted stock dynamics,
the effect of mating group size, and
the performance of traditional spawn-
ing-per-recruit (SPR) measures in a
protogynous stock. We considered four
different patterns of sex change in
which the probability of sex change is
determined by 1) the absolute size of
the individual, 2) the relative length
of individuals at the mating site, 3)
the frequency of smaller individuals
at the mating site, and 4) expected
reproductive success. All four pat-
terns of sex change have distinct
stock dynamics. Although each sex-
change rule leads to the prediction
that the stock will be sensitive to the
size-selective fishing pattern and may
crash if too many reproductive size
classes are fished, the performance of
traditional spawning-per-recruit mea-
sures, the fishing pattern that leads
to the greatest yield, and the effect of
mating group size all differ distinctly
for the four sex-change rules. These
results indicate that the management
of individual species requires knowl-
edge of whether sex change occurs,
as well as an understanding of the
endogenous or exogenous cues that
induce sex change.
Manuscript submitted 22 September 2003
to the Scientific Editor's Office.
Manuscript approved for publication
20 December 2004 by the Scientific Editor.
Fish. Bull. 103:229-245 (2005).
Sex-change rules, stock dynamics,
and the performance of spawning-per-recruit
measures in protogynous stocks
Suzanne H. Alonzo
Institute ol Marine Sciences and the Center for Stock Assessment Research (CSTAR)
University of California Santa Cruz
1156 High Street
Santa Cruz. California 95064
Present address: Department of Ecology and Evolutionary Biology
Yale University
165 Prospect St., OML 427
New Haven, Connecticut 06511
Email address Suzanne Alonzoia'yaleedu
Marc Mangel
Department of Applied Mathematics and Statistics
Jack Baskm School of Engineering and the Center for Stock Assessment Research (CSTAR)
University of California Santa Cruz
1156 High Street
Santa Cruz California 95064
Growth, survival, and reproduction
all affect the dynamics of a population
and its response to fishing and man-
agement (Quinn and Deriso, 1999;
Haddon, 2001). However, these three
key variables are influenced by many
aspects of a species' biology, environ-
ment, and evolutionary history. There
is an increasing realization that the
management of populations requires
an understanding of their behavior,
life history strategies, and repro-
ductive patterns (Sutherland, 1990;
Huntsman and Schaaf, 1994; Col-
lins et al„ 1996; Greene et al„ 1998;
Sutherland, 1998; Beets and Fried-
lander, 1999; Coleman et al., 1999;
Fulton et al., 1999; Kruuk et al.,
1999; Constable et al., 2000; Cowen
et al., 2000; Koeller et al„ 2000; Fu
et al., 2001; Apostolaki et al., 2002;
Levin and Grimes, 2002). Although it
is important to document the normal
patterns of behavior and reproduction
within a population, predicting and
understanding a stock's response to
novel conditions also requires knowl-
edge of the degree of plasticity in
behaviors that affect growth, survival,
and reproduction, and the cues that
induce phenotypic changes. Numer-
ous examples exist of context- and
condition-dependent behavior in fish
(e.g., Metcalfe et al., 1989; Snyder and
Dingle, 1990; Schultz and Warner,
1991; Wainwright et al., 1991; Mit-
telbach et al., 1992; Nishibori and
Kawata, 1993; Ridgeway and Shuter,
1994; Breden et al., 1995), and this
kind of plasticity has the potential
to affect the dynamics of a stock. For
example, many commercially impor-
tant species of fish change sex from
female to male. Researchers have
argued that this life history pat-
tern will lead to different population
dynamics and responses to fishing and
management strategies than will the
life history pattern of dioecious (sep-
arate-sex) species (e.g., Snyder and
Dingle, 1990; Schultz and Warner,
1991; Wainwright et al., 1991; Nishi-
bori and Kawata, 1993; Ridgeway and
Shuter, 1994; Alonzo and Mangel,
2004). However, it is important to
consider not only whether sex change
occurs, but also how it occurs; whether
plasticity in sex change exists and
what cues determine sex change in
an individual species.
A variety of patterns of sex change
have been observed in the wild (War-
ner and Lejeune, 1985; Charnov,
1986; Shapiro, 1987; Charnov and
Bull, 1989; Iwasa, 1990; Warner and
Swearer, 1991; Lutnesky, 1994, 1996;
230
Fishery Bulletin 103(2)
Kuwamura and Nakashima, 1998; Koeller et al., 2000;
Nakashima et al., 2000). At one extreme, sex change
may occur at a fixed size or age threshold. However,
sex change is known in many species to be mediated
by local factors such as population density, reproduc-
tive skew, sex ratio, and size distribution (Warner and
Lejeune. 1985; Warner and Swearer, 1991; Lutnesky,
1994, 1996; Kuwamura and Nakashima, 1998; Koeller
et al., 2000; Nakashima et al., 2000). In many sex-
changing species, overlap exists between the sexes in
size and age and this overlap indicates that sex change
may also depend on individual experience and local
conditions (Munoz and Warner, 2003). The pattern of
sex change may have important implications for a spe-
cies' response to fishing. For example, if the size at sex
change is fixed, then the population sex ratio may be
affected by size-selective fishing of males, resulting
in sperm limitation and decreased larval production
(Alonzo and Mangel, 2004). In contrast, if sex change is
mediated at the level of the spawning group in single-
male harems and mating group size remains the same,
sex ratios are maintained if the largest female always
changes sex. In such a case, larval production will be
reduced only because of the decreased size distribution
of the population due to fishing. However, if sex change
is controlled by the reproductive skew in the group (e.g.,
the expected potential for reproduction as a male versus
present fecundity as a female), then the largest individ-
ual might not change sex and the spawning group could
be without a male (Munoz and Warner, 2003). This re-
sult would clearly lead to a much greater effect on the
productivity of the stock. A detailed understanding of
the factors determining sex change and the cascading
effects on sperm production, fecundity, and sex ratio can
be critical to predicting stock dynamics. Furthermore,
most animals have "rules-of-thumb" which determine
their behavior and reproduction. Although these rules
will have evolved under normal conditions, in the pres-
ence of fishing or other human-induced disturbances,
animals are likely to continue to use these behavioral
rules on ecological time scales even if they no longer
function to maximize reproduction.
Although previous fisheries models have examined
sex change, a consensus does not exist regarding how
sex change is predicted to affect stock dynamics. Some
research has suggested that sex-changing stocks will
be more sensitive to fishing and cannot be managed as
if they were identical to separate-sex stocks (Bannerot
et al., 1987; Punt et al., 1993; Huntsman and Schaaf,
1994; Coleman et al., 1996; Beets and Friedlander,
1999; Brule et al., 1999; Coleman et al., 1999; Arm-
sworth, 2001; Fu et al., 2001). However, it has also
been argued that, in the absence of sperm limitation,
protogynous stocks should be less sensitive to size-selec-
tive fishing because female biomass and thus population
fecundity should not decrease as much as in a dioecious
population, making traditional management and theory
conservative when applied to these species. In general,
protogynous stocks have been predicted to be at risk of
population crashes because of their potential for nonlin-
ear population dynamics in the presence of exploitation,
yet there is no consensus regarding the importance of
the exact pattern of sex change. For example, Arms-
worth (2001) examined protogynous stock dynamics
when the probability of sex change was a fixed func-
tion of individual age and when the probability of sex
change depended on the mean age of individuals in the
population. He found that these two patterns of sex
change had similar general dynamics and argued that
management of a protogynous stock might not require
knowledge of the precise pattern of sex change. In con-
trast. Huntsman and Schaaf (1994) and Coleman et al
(1999) have argued that a consideration of the pattern
of sex change can be important to managing stocks.
But, past theory has generally focused on comparing
fixed patterns of sex change with fully compensating
reproductive patterns that maintain a fixed sex ratio
or ratio of female to male biomass. However, a variety
of patterns of sex change exist and there is no reason
to believe that all species have evolved to exhibit full
compensation under natural conditions, let alone un-
der new situations. Thus, it is important to consider
how specific sex change rules will affect the dynamics
and management of protogynous stocks and whether
knowledge of the cues that determine sex change will
be important.
We (Alonzo and Mangel, 2004) developed a general
modeling approach for examining the impact of repro-
ductive behavior and life history pattern on stock dy-
namics. Using this approach, we then compared the
dynamics of a protogynous population with fixed size at
sex change and an otherwise identical dioecious species
(Alonzo and Mangel, 2004). These analyses showed that
although dioecious and protogynous stocks clearly have
distinct dynamics, simple statements arguing that one
life history pattern is more or less sensitive to fishing
cannot be made. Protogynous stocks with fixed patterns
of sex change were predicted to experience sperm limi-
tation and lowered larval recruitment at high fishing
pressure, whereas the dioecious stock was predicted to
show a large drop in mean population size even at low
fishing mortality, but was not predicted to experience
lowered fertilization rates due to size-selective fishing.
Both stocks were predicted to be sensitive to fishing
pattern, but a fixed pattern of sex change was predicted
to put a population at risk of crashing if all male size
classes were fished even at relatively low fishing mor-
tality. Finally, classic spawning-per-recruit (SPR) mea-
sures were not predicted to be good indicators of chang-
es in the mean population size of protogynous stocks
because they cannot indicate whether a population is
experiencing sperm limitation and whether this limita-
tion may lead to decreased population size or cause the
stock to crash with small changes in fishing mortality.
Although we found that whether or not a stock changes
sex was important, that knowledge alone was not suf-
ficient to understand and predict the response of the
stock to fishing or management. We also found that
sperm production and mating system were important
variables affecting the probability that a population
Alonzo and Mangel: Sex-change rules, stock dynamics, and the performance of spawning-per-recruit measures in protogynous stocks 231
would experience sperm limitation and would affect the
performance of traditional spawning-per-recruit mea-
sures. However, we did not consider the possibility that
size at sex change may be plastic and depend on local
social conditions or relative rather than absolute size.
Plastic sex change may allow a protogynous species to
compensate for any effect of size-selective fishing on the
sex ratio of the population, rendering its dynamics iden-
tical to the dynamics of a dioecious species. However,
as described above, a wide variety of patterns of sex
change have been observed in the wild and have been
proposed to occur. Therefore, the exact pattern of sex
change and cue driving phenotypic changes may lead to
unique stock dynamics. In this study we apply the same
general method we used previously (Alonzo and Mangel,
2004) to examine the effect of four different patterns
of sex change (one fixed and three plastic) on the stock
dynamics of a protogynous species.
Methods
We applied the same general method and individual-
based population dynamic model as our previous study
(Alonzo and Mangel, 2004). However, we now included
the effect of four different patterns of sex change on the
stock dynamics and performance of spawning-per-recruit
measures in a protogynous species. Individuals vary in
age, size, sex, and location (i.e. mating site). We assumed
annual time periods and determined individual survival,
size, and reproduction as described below. We simulated
100 years prior to examining the impact of fishing on
stock dynamics and then simulated 100 more years in
the presence of fishing with a constant mean fishing-
induced mortality. This allowed the population to reach
a stable age, sex, and size distribution prior to fishing
which is independent of initial conditions. Because a
number of elements of the model are stochastic, we
examined 20 simulations for each scenario and set of
parameter values, which was more than sufficient in
all cases to lead to low variability in the key measures
of interest.
Fishing and adult survival
We assume age and size do not affect natural adult
mortality, i.iA and that adult mortality is density-inde-
pendent. The fishery is size selective; if L represents fish
size, F annual fishing mortality, Lf the size at which
there is 50% chance an individual of that size will be
taken, and r the steepness of the selectivity pattern, the
fishing selectivity per size class s(L) is given by
11)
SiL) = - — r
l+eiq)y-r(L-Lf)\
and adult annual survival is
a(L) = exp(-fiA - Fs(D).
Population dynamics
The number of larvae that enter the population is deter-
mined by larval survival and the total production of fer-
tilized eggs Pit), which is determined by total fecundity
and fertility within each mating site as described below.
Larval survival is assumed to have both density-inde-
pendent and density-dependent components (e.g., Cowen
et al., 2000; Sale, 2002), and we use a Beverton-Holt
recruitment function (Quinn and Deriso, 1999; Jennings
et al., 2001) to calculate larval survival . The number
of larvae surviving to recruit in any year t, N0(t), is
given by
NQ(t) = (aPit))/(l + pP(t))
if(aP(t))/(l + l3P(t))+'£Nn{t)<Nn
(3)
N0(t) = max
0,Nmax-^NnU
o=l J
if(aP(t))/(l + liP(t))+^Njt)>Nn
where a gives density-independent survival, ft deter-
mines the strength of the density-dependence in the
larval phase, and Nmax represents the maximum popula-
tion size. We assume that the population is open between
mating sites, a single larval pool exists, larval recruit-
ment is random among mating sites, and there is no emi-
gration to or immigration from outside populations.
Growth dynamics
Larvae that survive to recruit begin at size L0 and
growth is assumed to be deterministic and indepen-
dent of sex or reproductive status. We calculate growth
between age classes using a discrete time version of the
von Bertalanffy growth equation (Beverton, 1987, 1992)
where Llnf represents the asymptotic size and k is the
growth rate. Then an individual of length Lit) at time t
will grow in the next time period to size LU+1):
LU + 1) = Linf (1 - exp(-&)) + LU)exp(-£).
(4)
Mating system
(2)
As in our previous model, we assume that reproduction
occurs at the level of the mating group, and we examine
the effect of varying mating group size and the number
of mating sites. Juveniles and adults are assumed to
exhibit site fidelity and larvae settle randomly among
mating sites. The carrying capacity of the population
is split equally among the mating sites and the total
capacity of all mating sites exceeds the maximum popu-
lation size in the absence of fishing as determined by
232
Fishery Bulletin 103(2)
adult mortality and the recruitment function. As before
(Alonzo and Mangel, 2004), we examine the following
three cases: 1) the entire population mates at one site
(1 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). We assume that within a
mating site, individuals mate in proportion to their
fertility and fecundity and that males that are large
enough to change sex have a chance of reproducing that
is proportional to their fertility and thus a large male
reproductive advantage exists. This is equivalent to
assuming that females exhibit a mate choice threshold
(Janetos, 1980) that has evolved with the size at pat-
tern of sex change and that male fertilization success
is proportional to fertility.
Reproduction
We assume female fecundity E(L) and male sperm pro-
duction SiL) can be represented by the allometric rela-
tionships EiL)=aLh and SiL)=cLb respectively where a, b
and c are constants. We assume that at any body length
males produce 1000 times more sperm than females
produce eggs. This leads to the realistic pattern that
(in the absence of fishing) fertilization rates are high
and that multiple males are needed to fertilize all the
eggs produced by females. We calculate the average
expected fertilization rate per mating site based on the
total production of sperm and eggs at the site, where S
represents the number of sperm released (in millions)
and E the number of eggs released at each mating site.
The proportion of eggs fertilized per mating site pF is
given by
PF =
1 + IkE + x)S
(5)
examples represent four plausible patterns that differ
in the cues or mechanisms that induce sex change,
the degree of compensation or plasticity assumed, and
encompass the diversity that has been observed and
hypothesized for a variety of sex-changing fish popula-
tions (Helfman, 1997).
Rule 1 : Fixed For the first sex-change rule, we assume
that the probability of sex change pc(L) is determined
by the absolute length of the individual and is
pc(L)--
1
l + exp(-p(L-Lc))
(6)
where Lc represents the size at which 50% of mature
females change sex and p is a constant that determines
the steepness of the probability function. With this sex
change rule, we also assume that the probability an
individual matures p^L) is determined by absolute size.
Once an individual matures, she remains female until
sex change. LM represents the length at which 50% of
juveniles are expected to mature.
PM&)
l + exp(-<j(L-LM))
(7)
where q determines the steepness of the probability
function and where LC>LM.
Rule 2: Relative size For the second sex change rule, the
mean size of all individuals in the mating group deter-
mines the probability of sex change for an individual.
First, we find the mean size of all individuals at each
mating site. We let Lt represent the mean size in the
mating site i. Then the probability of sex change for an
individual of length L is
where k and % are constants fitted to data. The pro-
portion of eggs fertilized (pF) depends on both total
sperm production (S) and egg production (E). If sperm
production is very high in relation to egg production,
fertilization rates will be at or near 100%. However, if
total sperm production (S) decreases and egg production
remains the same, fertilization rates will decrease. Simi-
larly, as egg production (E) increases in relation to total
sperm production (S) fertilization rates will decrease
(see Fig. 2, Alonzo and Mangel, 2004). The number of
eggs fertilized per group is pFE and the total production
of fertilized eggs Pit) is the sum of the number of eggs
fertilized in all mating groups. For more details on the
fertilization function and individual sperm production
see Alonzo and Mangel ( 2004).
Patterns of sex change
We examine four possible patterns of sex change, deter-
mined by absolute or relative size of the individual.
Although a variety of other possibilities exist, these
Pc(L) =
l + exp(-p(L-(L, +ALr))
(8)
where ALC represents the difference from the mean at
which the probability of sex change is 0.5. For these
analyses, we also assumed that the probability an
individual matures also depends on the mean size of
individuals at the mating site. Then the probability of
maturity is
Pm
<L)
1
1 + exp(-q(L - ( L, + ALM )))
(9)
where ALM represents the difference from the popula-
tion mean at which the probability an individual will
mature is 0.5.
Rule 3: Relative frequency Sex change may also be
induced by the social conditions at the mating site. For
example, sex change may depend on the frequency of
Alonzo and Mangel: Sex-change rules, stock dynamics, and the performance of spawmng-per-recruit measures in protogynous stocks 233
other mature individuals or the frequency of smaller
individuals. We examine the case where sex change
depends on the frequency of smaller mature individu-
als. For each mature female, we find the frequency of
mature individuals at the same mating site that are
smaller. We let Ft represent the frequency of mature
individuals that are smaller than the mature female
and Fc represents the frequency at which 50% of the
individuals are expected to change sex. Then the prob-
ability of sex change is
Pc(L) =
l + exp(-p(F,-F, ))
(10)
The probability of maturing depends on the frequency of
smaller individuals. We let /j represent the frequency of
all smaller individuals at mating site i and fM represent
the frequency at which there is a 50% probability of an
individual maturing. Then the probability of maturing
is
PM(L) =
1
l + exp(-q(f,-fM)
(11)
Rule 4: Reproductive success Finally, we consider the
case where sex change occurs when an individual's
size-dependent expected reproductive success is greater
as a male than as a female (Charnov, 1982). This pat-
tern of sex change has been proposed to explain the
observation that individual variation exists in size at
sex change and that it is not always the largest indi-
vidual in a group that changes sex (Munoz and Warner,
2003). We assume that a fish will change sex when its
expected egg production at its current length (E(L)=aLh
as given above) is exceeded by its expected paternity at
the mating site which is given by the total egg produc-
tion of all other females at the site multiplied by the
focal individual's relative sperm production. This value
is given by expected fertility S(L) divided by the total
sperm production (by all males at the site plus their
own expected fertility) at the same mating site. We
further assume that sex change occurs once a year in
rank order from the largest to smallest female at the
site. (For this scenario we assumed that the probability
of maturing depends on absolute size as in Equation
7.) However, we still assume that individuals can only
change sex once during their lifetime and only mature
females can change sex. Thus, mature females change
sex when their current expected fertilization success as
a male is greater than their current expected fecundity
as a female.
Measures of spawning stock biomass per recruit
We examine the same spawning-per-recruit measures
as in our previous paper (Alonzo and Mangel, 2004) and
compare the results of the patterns of sex change con-
sidered here with one another and with a hypothetical
dioecious species, where sex is determined stochastically
at birth and the primary sex ratio is fixed. We compute
the total spawning stock biomass per recruit starting
from the beginning of fishing for the next 50 years. We
use the generally recognized pattern that fish wet weight
tends to be approximately proportional to the cube of
fish length (Gunderson, 1997) to convert fish length, L,
into relative biomass, B(L)~ZA Then we calculate total,
female, and male spawning stock biomass per recruit
(SSBR). We also keep track of the total fecundity (egg
production per recruit), fertility (sperm production per
recruit), and eggs fertilized per recruit.
Parameter values
We use parameters based on previous research (Warner,
1975; Cowen, 1985; Cowen, 1990) on California sheep-
head (Labridae, Semicossyphus pulcher), a commercially
important sex-changing fish, to provide evolutionary
and ecologically 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 mediated. For the first
sex-change rule, we assume that individuals have a
50% chance of maturing (L,„) at 20 cm (the mean size
of maturity observed in natural populations) and of
changing sex at (Lc) 30 cm. This leads to a sex ratio of
2/3 mature females to 1/3 males on average and a mean
length of 20 cm in the absence of fishing as is observed in
the wild. For consistency, we also assume for the second
sex-change rule, that individuals have a 50% chance
of changing sex at 10cm (z\L(,=10) above the mean size
and have a 50% chance of maturing at the mean size in
the mating site (ALm = 0). Similarly, for the third rule,
the frequency of smaller mature individuals at which
there is a 50% of sex change is assumed to be 0.67 and
when 50% of all individuals are smaller, an individual
will have a 0.5 probability of maturing. Therefore in the
absence of fishing all four sex change rules lead to the
same maturity and sex-change patterns as a function
of age and size. For more information on the parameter
values considered here, see Table 1.
Individual-based simulations are computationally
very intensive. As a result, it was not feasible to explore
a wide range of values for all parameters. Furthermore,
because growth, mortality, reproduction, maturity, and
sex change are coevolved characters within any spe-
cies, it does not make sense in this context to vary
them independently. Instead, we used estimates from
California sheephead for as many parameters as pos-
sible (mortality, growth, fecundity, size at maturity, and
sex change) and when necessary from a closely related
species (fertilization rate). We then focused on exploring
the effect, for this species, of varying the sex-change
rule and fishing pattern while all other parameters
remained the same. Our focus was on determining the
impact of the sex change rule on the predicted stock
234
Fishery Bulletin 103(2)
Table 1
The parametei
values used in the model were
based on available data for California sheephead iSemicossyphus pulcher). See
text for details
Parameter
Parameter values
Definition and source
Growth
k
0.05
Growth rate (based on Cowen, 1990)
*1nf
90 cm
Asymptotic size (based on Cowen. 1990)
1*0
8 cm
Larval size at recruitment
Population
N
max
1000
Maximum population size
f'A
0.35
Adult mortality (based on Cowen, 1990)
a
0.0001
Density-independent larval mortality
ft
a/(l-exp(-|iiA)) Nmax
(3.33xl0"7>
Larval recruitment function parameter (see text)
Fishing
r
1(0.1)
Steepness of selectivity curve
h
30(25,35)
Length at which 50% chance a fish will be removed
F
0-3
Fishing mortality
Reproduction
a
7.04
Constant in the fecundity relationship (Warner, 1975)
b
2.95
Exponent in the allometric relationship (Warner, 1975)
c
10"3a
Constant in the sperm production function (measured in millions of sperm)
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
Rule 1
L.
30 cm
Length at which 50% offish change sex
P
1
Shape parameter in the sex-change function
K
20 cm
Length at which 50% of fish mature
q
1
Shape parameter in the maturity function
Rule 2
ALC
10 cm
Difference from the mean size at which p(,(L)= 0.5
P
1
Shape parameter in the sex change function
ALm
0 cm
Difference from the mean size at which pM(L)= 0.5
Q
1
Shape parameter in the maturity function
Rule 3
Fc
0.67
Frequency of smaller mature individuals wherepl.(L) = 0.5
P
50
Shape parameter in the sex-change function
Fm
0.50
Frequency of smaller individuals at whichpw(L) = 0.5
Q
50
Shape parameter in the maturity function
Rule 4
No additional parameters required
dynamics rather than on exploring all possible param-
eter combinations. However, it would certainly be use-
ful in the future to examine the same question using
parameter estimates based on other commercially ex-
ploited species that change sex.
Results
We present the average across simulations of the mean
population measures of the last 50 years for each simu-
lation. The variation around the mean in all measures
considered is 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 under consideration had
died before the end of the simulation. Parameter values
used are given in Table 1
General dynamics
In all cases, size-selective fishing is predicted to decrease
population size and decrease the mean length offish in
the population. Although all scenarios are predicted
to lead to the same change in average fish length, the
effect of fishing on predicted population size and the
mechanisms leading to changes in population size
differ between the four sex-change rules (Figs. 1 and 2,
Table 2). The largest differences occur between the fixed
rule and the three plastic patterns of sex change. How-
Alonzo and Mangel; Sex-change rules, stock dynamics, and the performance of spawnmg-per-recruit measures in protogynous stocks 235
80.000 -,
A Rule 1: Fixed
60.000 -
40.000 -
20,000 -
0 0.5 1 15 2 2.5 3
80.000 -,
B Rule 2: Relative size
in 60.000 -
® 40,000 -
tu
|= 20,000 -
^ 0
0 0.5 1 1.5 2 2.5 3
o
u
3
1. 80.000 -,
C Rule 3: Relative frequency
| 60.000 -
< 40,000 -
20,000 -
0 0.5 1 1.5 2 2.5 3
80.000 n
D Rule 4: Reproductive success
60,000 -
40,000 -
20.000 -
U I 1 I 1 I 1
0 0.5 1 1.5 2 2.5 3
Fishing mortality (F)
Figure 1
The predicted effect of fishing mortality on the production of fertilized
eggs. Results are shown for the case where one mating group exists and
the fishing selectivity is characterized by Lf— 30 and r=l. The same basic
pattern is predicted for multiple mating sites as well.
ever, the exact pattern of sex change has an important
and qualitative effect on the predicted stock dynamics
(Table 2). All three plastic patterns of sex change are
predicted to show lower sperm limitation and higher fer-
tilization rates in the presence of fishing than the fixed
pattern of sex change (Table 2). However, associated
with plastic sex change is also a greater predicted drop
in egg production (total and fertilized) and mean popula-
tion size than when the effect of size on the probability
of sex change is fixed (Fig. 1, Table 2). This drop in egg
production and mean population size occurs because
female biomass is predicted to decrease as a result of the
combination of fishing on larger individuals and smaller
sizes at sex change (Fig. 2). The basic patterns are the
same for the case with multiple mating sites. Most of
the significant reductions in stock size are predicted
at high fishing mortality. However, it is important to
remember that we have assumed that the stock is very
resilient (Table 1), and our focus is on the differences
among sex-change rules and fishing patterns rather than
on absolute fishing mortality.
The effect of mating group size
Although mating group size is predicted to have an effect
in most cases on the stock dynamics of the population.
236
Fishery Bulletin 103(2)
E
o
20,000 1 A Rule 1: Fixed
16,000 ' \
\
12.000 ; \
8,000
4,000 ■
V^
20,000
16.000
12,000
8,000
4.000
0 5
1
1.5
2.5
B Rule 2: Relative size
\
05
1.5
2.5
20,000 -X
16,000 '
12,000
8,000
4,000 H
C Rule 3: Relative frequency
0.5
1.5
2.5
20,000
16,000
12,000 ■
8,000 •
4.000
0
l) Rule 4: Reproductive success
0 5 1 1.5 2
Fishing mortality (F)
25
Figure 2
The predicted effect of fishing mortality on the spawning stock biomass
per male recruit (dashed lines) and per female recruit (solid lines) for all
four patterns of sex change. Results are shown for the case of one mating
group and the fishing selectivity is characterized by L^=30 and r=l. The
same basic pattern is predicted for multiple mating sites as well.
the strongest effect is predicted when size at sex change
is fixed or determined by the frequency of small fish in
the population (Fig. 3, A and C). When the size at sex
change is fixed, populations are predicted to crash when
mating sites are very small (Fig. 3A). In the case where
size at sex change is determined by expected reproduc-
tive success, group size is predicted to have no effect on
the relative production of eggs and mean population size
(Fig. 3D). However, for all the other rules of sex change
considered, smaller mating sites are predicted to experi-
ence sperm limitation in the presence of fishing, lead-
ing to a decrease in the relative production of fertilized
eggs and a decrease in mean population size (Fig. 3).
However, unlike in the case of fixed size at sex change,
the smaller mating groups (20 mating sites with up to
50 individuals per site) are stable both in the presence
and absence of fishing and are not predicted to collapse
for most fishing patterns.
Sensitivity to fishing pattern
Rule 1 The size-selective pattern of the fishery has a
large effect on the predicted stock dynamics when the
size at sex change is fixed. When the selectivity of the
Alonzo and Mangel: Sex-change rules, stock dynamics, and the performance of spawning-per-recruit measures in protogynous stocks 237
Table 2
A comparison of stock dynamics for four sex-change rules. Results are reported for the situation where the fishing selectivity
pattern and the probability of sex change are both centered at the same size (L^30). These results assume a near knife-edge
selectivity (r=l) and that one mating site exists. Numbers given are for the predicted relative change as a result of fishing (when
F=3 compared to F=0\. SSBR = spawning stock biomass per recruit.
Rule 1:
Fixed
Rule 2:
Relative size
Rule 3:
Relative frequency
Rule 4:
Reproductive success
Mean population size
90%
90%
73%
72%
Total SSBR
40%
45%
44%
39%
Male SSBR
11%
22%
39%
397r
Female SSBR
98%
92%
58%
39%
Sex ratio
0.67 - 0.92
0.67^0.84
No change
0.8 - 0.66
Mean size
88%
88%
88%
88%
Sperm production
11%
23%
40%
40%
Egg production
98%
93%
59%
41%
Fertilized egg production
88%
86%
59%
41%
fishery is centered below the mean size at sex change
(L^=25, r=l), the stock was predicted to crash at high
fishing mortality (F>1, Fig. 4A). Furthermore, when
the selectivity pattern was not steep (L,= 30, r=0.1), the
population was always predicted to crash even at low
fishing mortality (and thus this case is not shown in
Figs. 4A-6A). When the steepness of the fishery's selec-
tivity changes, the size range over which fish are targeted
also changes. Thus, smaller and younger fish are removed
by the fishery when r=0.1 and hence a greater number
of age classes are affected by fishing. At an extreme,
fishing mortality could be high enough that all of the
individuals in any size classes targeted by the fishery
are removed. As a result, although the steepness of the
selectivity function only affects the spread of the function
mathematically, it has the biological effect of decreasing
the size at which fish experience fishing mortality and
can have a large effect on the size and age distribution
of the population. In contrast, when the fishery's selectiv-
ity is steep (r=l) and only fish at or above the mean size
at sex change (L^&30) are targeted, the effect of fishing
on the population is predicted to be much less (Fig. 4A).
Independent of the selectivity pattern, the population
sex ratio is predicted to be more female-biased in the
presence of fishing than in the absence of fishing. The
lower the mean size removed by the fishery, the greater
the predicted change in population sex ratio as a result
of fishing (Fig. 5A). For situations in which the stock is
not predicted to crash (i.e., L^30 and r=l), yield is pre-
dicted to increase with diminishing returns with fishing
mortality (Fig. 6A), catch is not predicted to decline with
increased fishing mortality (at least up to F=3), and steep
size-selective fishing patterns with lower size thresholds
are predicted to lead to more yield (Fig. 6A).
Rule 2 When sex change is determined by the mean
size of individuals in the mating site and the size-selec-
tivity is weak (r=0.1), the population is predicted to
crash when F^l.67 (Fig. 4B). This crash occurs because
individuals do not escape fishing mortality even at small
sizes. However, unlike when sex change is fixed (Fig. 4A),
the population is predicted not to crash when the size
selected by the fishery is less than the mean size at sex
change in the absence of fishing (L,=25, Fig. 4B). The
larger the mean size selected by the fishery, the smaller
the predicted effect of fishing on the mean population
size and the population sex ratio (Figs. 4B and 5B).
Although catch is predicted to increase with diminishing
returns as fishing mortality increases from zero to three,
the difference between the size-selectivity patterns is
predicted to decrease and yield will be greater annually
if larger fish are targeted (Fig. 6B).
Rule 3 As above, when the probability of sex change
depends on the relative frequency of smaller mature
individuals, the population is predicted to crash when-
ever size-selectivity is weak because fish do not escape
fishing even when small (r=0.1, Fig. 4C). Although the
population is predicted not to crash when the size tar-
geted by the fishery is less than the mean size at sex
change in the absence of fishing (L/=25, Fig. 4C), this
fishing pattern is predicted to lead to a large decrease
in mean population size and a marked decrease in popu-
lation sex ratio (Figs. 4C and 5C). In contrast fishing
selectivity that is centered at or above the mean size of
sex change in the absence of fishing (L,— 30 and L^35)
is predicted to lead to a weaker effect on mean popula-
tion size and to almost no effect on the population sex
ratio (Figs. 4C and 5C). However, in contrast to the two
scenarios described above this pattern of sex change
leads to the prediction that targeting fish at or larger
than the normal mean size of sex change (Zy=30 and
r=l) will lead to the greatest annual yield over time for
most fishing mortalities (Fig. 6C).
238
Fishery Bulletin 103(2)
A Rule 1: Fixed
o> o
a. 1.0
ft 0.8
15 Rule 2: Relative size
Egg production Fert. egg production Mean population
per recruit per recruit size
1.0
08
06
0.4
02-
C Rule 3: Relative frequency
D Rule 4: Reproductive success
en £ 2
Egg production Fert. egg production Mean population
per recruit per recruit size
Figure 3
Effects of mating group size on the response of egg production per recruit, fertilized egg production per recruit, and mean
population size to fishing pressure. Large (one large mating aggregation), medium 1 10 medium-sized mating aggrega-
tions) and small (20 small mating aggregations) situations are compared. Percent change in the presence of fishing (from
F =0 to F=l) is given. Total population fecundity and mean body size are lower for smaller mating aggregations as well.
Results are shown for Z^— 30 and r=l. No bars are shown for small mating groups with fixed size at sex change because
these populations are predicted to crash.
Rule 4 As with all of the other patterns of sex change,
populations with sex change based on expected reproduc-
tive success are predicted to crash whenever small fish
experience fishing mortality (r=0.1, Fig. 4D). Further-
more, as with the other two plastic sex change rules,
populations are predicted not to crash when fish below
the normal mean size at sex change are included in the
fishery because the population can compensate with
smaller sizes at sex change in the presence of fishing
(Fig. 4D). Although only small differences among fish-
ing patterns are predicted in the mean population sex
ratio, the effect on the population size is predicted to be
greatest when many size classes are fished, and large
differences are predicted between the fishing patterns in
mean population size (Fig. 5D). Finally, in the scenario
of sex change based on expected reproductive success.
the fishing pattern predicted to lead to the greatest catch
is to target only fish above the normal mean size at sex
change (1^=35, Fig. 6D).
In summary, fishing is always predicted to decrease
total production of fertilized eggs and mean population
size. However, the strength of the effect depends both
on fishing selectivity and the pattern of sex change (see
above and Figs. 4-6). Although populations with fixed
patterns of sex change are predicted to crash in the pres-
ence of fishing below the mean size at sex change, plastic
patterns of sex change are predicted to lead to more
resilience since these populations can compensate for
the removal of large males more effectively. However,
all scenarios are predicted to crash in the presence of
fishing across a broad range of size classes (when r=0.1)
even in completely compensatory patterns of sex change.
Alonzo and Mangel: Sex-change rules, stock dynamics, and the performance of spawning-per-recruit measures in protogynous stocks 239
1
A Rule 1: Fixed
L,=35 r=1
800
600 '
L,=30r=1
400 '
200 '
\ L,=25 r=1
0.5
1.5
2.5
800
600
400
200 '
0
B Rule 2: Relative size
r
L,=35 r=1
I
---
; ,-
1
L,=25 r=1
. L,=30 r=1
1 *i 1-
i
0 0.5 1 15
C Rule 3: Relative frequency
2.5
S 800
L,=30r=1
0.5
1.5
2.5
D Rule 4: Reproductive success
2.5
Fishing mortality
Lj=35 r=1
"77=30 r=1
L,=25 r=1
L,=35 r=1
Figure 4
The effect of size-selective fishing on the predicted mean population
size for all four patterns of sex change. We present results for a sex-
changing stock with one mating site. Means across 20 simulations are
given. For details see text. The same basic patterns are predicted with
multiple mating sites. A line is not shown in panel A (when sex change
is fixed) where L^— 30 and r=0.1 because the population is predicted to
crash at any fishing mortality in this scenario.
Yet, the exact response depends greatly on the specific
pattern of sex change. For example, the population sex
ratio is not predicted to change much in the presence of
fishing when sex change is based on expected reproduc-
tive success and fishing pattern has little effect on the
sex ratio (Fig. 5). However, when sex change is based on
expected reproductive success, the annual yield is greater
for fishing patterns with larger size thresholds (Fig. 6). In
contrast, when sex change is determined by the mean size
of individuals at the mating site, sex ratio is predicted
to increase with fishing and increase more when smaller
size classes are fished. However, for this pattern of sex
change, the smallest size threshold is also predicted to
lead to the largest yield of the fishery, although as fishing
mortality increases the difference between fishing pat-
terns with differing size thresholds decreases. Therefore,
the fishing pattern that will produce optimal yield will
depend on the exact pattern of sex change (Fig. 6).
240
Fishery Bulletin 103(2)
1 o i A Rule 1 : Fixed
0
L,=30r=1
1 0
08
0.6
0.4 '
02
0
L» Huie •£
: Heia
ive size
L,=25 r=1
^r=~-
-z=~-
:-t==-="""
\ /_,=35r=1
\ L,=30r=0.1
\
X
0
0.5
1
1.5
1 C Rule 3: Relative frequency
0.8-
0.6- . ..„■■....
04
0.2
0
1.0
2.5
Lr=35 r=1
L,=25 r=1
\ L,=30r=0.1
0.5
1.5
2.5
0.5 1 1.5 2
Fishing mortality
2.5
L,=30r=1
L,=30r=1
0.8.
L,=35r=1
0.6-
0.4.
0.2.
0
-""^ —
\
\ L,=30 r=0.1
\
1 1 1 > 1 r
L,=25r=1
1 r
L,=30r=1
Figure 5
The effect of size-selective fishing on the predicted population sex ratio
for all four patterns of sex change. We present results for a sex-changing
stock with one mating site. Means across 20 simulations are given. For
details see text. The same basic patterns are predicted with multiple
mating sites. A line is not shown in panel A (when sex change is fixed I
where L,= 30 and r=0.1 because the population is predicted to crash at
any fishing mortality in this scenario.
Spawning-per-recruit (SPR) measures and
a comparison of protogynous and dioecious stocks
Our previous results (Alonzo and Mangel. 2004) have
shown that whether species change sex or are dioecious
is predicted to have dramatic effects on both the stock
dynamics and performance of classic SPR measures.
However, our results show that the exact pattern of
sex change, and not just whether the pattern is plastic
or fixed, can have a strong effect on these measures as
well (Fig. 7). Because of the population dynamics of the
model, all the scenarios represented in the present study
show a great resiliency to fishing. Hence, the predicted
changes in stock size are all above the common threshold
of allowing a reduction of spawning per recruit mea-
sures to 40% of their values in the unfished condition.
However, our aim is not determine if this population is
overfished. Instead, it is to determine whether classic
Alonzo and Mangel: Sex-change rules, stock dynamics, and the performance of spawning-per-recruit measures in protogynous stocks 241
OJ
A Rule 1: Fixed
L,30r=1
L,=35r=1
L,=25 r=1
0 0 5 1 1.5
B Rule 2 Relative size
25
Z.,=25r=1
L,=30 r=1
L,=35 r=1
L,=30r=0.1
0 0.5 1 15
(_> Rule 3: Relative frequency
— i —
2.5
L,=30r=1
L,=35r=1
L,=25 r=1
D Rule 4: Reproductive success
35 r=1
1.5 2
Fishing mortality
Figure 6
The effect of size-selective fishing on the predicted annual yield for
all four patterns of sex change. We present results for a sex-changing
stock with one mating site. Means across 20 simulations are given. For
details see text. The same basic patterns are predicted with multiple
mating sites. A line is not shown in panel A (when sex change is fixed)
where Zy=30 and r = 0.1 because the population is predicted to crash at
any fishing mortality in this scenario.
spawning per recruit measures based on egg produc-
tion or fecundity could accurately assess the status
of sex-changing stocks. Although the fixed pattern of
sex change is predicted to show the greatest difference
between egg production per recruit and fertilized eggs
produced per recruit, each population shows deviations
between egg production and the production of fertilized
eggs. Thus egg production alone cannot tell us how
the population is being affected by fishing and classic
SPR measures based on population fecundity may be
misleading for sex-changing stocks in cases where the
sex-change rule is not completely compensatory (rules
1-3). It is also interesting to ask whether consistent
differences exist (as has been suggested) in the resil-
iency of sex-changing stocks, compared to stocks with
separate sexes. Our results indicate that sex change
based on expected reproductive success is predicted to
have very similar dynamics to the dioecious population,
242
Fishery Bulletin 103(2)
Rule 1; Fixed
0.9
Q. 0.7
o 06
05
0.4
650 700 750
Mean population size
900
950
Figure 7
Spawning-per-recruit (SPR) measures for all four patterns of sex change and an otherwise
identical dioecious stock: mean egg production per recruit (filled) and mean fertilized
eggs per recruit (open) are shown for a population with one large mating group when
Zy=30 and r=l. The same basic patterns are predicted for multiple mating sites. Each
line represents the same range of fishing mortalities, and each point represents fishing
mortality increasing from 0 to 3 in increments of 1/3 moving from the right to the left. For
the fourth rule (expected reproductive success), the two lines (eggs produced per recruit
and eggs fertilized per recruit) overlap.
whereas sex change based on relative size or the relative
frequency of individuals in a mating site is predicted
to have similar dynamics to those for the fixed pat-
tern of sex change. Thus, it is not possible to say that
sex-changing stocks tend to be more or less resilient to
fishing than are dioecious populations. However, the
sex change rule clearly affects the predicted relation-
ship between fishing mortality and the response of the
stock to fishing.
Discussion
We apply a general approach using individual-based
simulation models to determine the predicted effect of
the pattern of sex change on the stock dynamics of a
protogynous species. Although the model structure and
parameter values considered will not apply to all com-
mercially important protogynous species, it is important
to realize that all the scenarios considered are identical
except for the pattern of sex change. As a result, any
predicted differences that arise between these situa-
tions are a result of the sex-change rule and indicate
that knowing simply that a species exhibits sex change
but not what the behavioral rule of sex change is will
lead to an incomplete ability to understand and predict
the dynamics of the stock and its response to fishing or
management strategies.
Independent of the sex-change rule, the protogy-
nous stocks are always predicted to be sensitive to the
size-selective fishing pattern. Mean population size
is always predicted to decrease as fishing mortality
increases, despite the fact that we have assumed that
recruitment is strongly density dependent and that
the species is very productive. Stocks are predicted
to crash even at low fishing mortality when the size-
selective fishing pattern targets all reproductive size
classes and for the fixed sex change rule whenever all
male sizes sizes are targeted by the fishery. It will
be necessary but not sufficient to avoid overfishing at
spawning aggregations. Our results indicate that it will
also be important to allow smaller and nonreproductive
individuals to escape fishing as well. These results
indicate that independent of the exact pattern of sex
change, management strategies for all protogynous
stocks need to be sensitive to the size-selectivity of
Alonzo and Mangel: Sex-change rules, stock dynamics, and the performance of spawning-per-recruit measures in protogynous stocks 243
the fishing pattern in relation to size at maturity and
size at sex change observed in the population, and a
failure to do so can lead to a sudden and unexpected
collapse of the fishery — a collapse from which it may
be difficult to recover.
We assume in all cases that the same cues determine
both the probability of maturity and the probability of
sex change within a species. For example, when sex
change was affected by the relative size of individuals
at the mating site, we assume that this same cue af-
fected the probability of maturing. This assumption has
a large effect on the predicted dynamics of the stock.
Alternatives exist. For example, the size at which fish
mature could be determined by endogenous rather than
exogenous factors even in a population where the prob-
ability of sex change is affected by external cues. If this
were the case, the population can easily be fished into a
situation where it cannot compensate for size-selective
fishing and is predicted to crash for any fishing pat-
tern that targets reproductive individuals. For example,
when L,= 30 and r=l, populations with plastic size at
maturity and sex change were not predicted to crash
independent of fishing mortality. In contrast, simula-
tions where populations were assumed to have fixed size
at maturity rules (Lm=20) but plastic patterns of sex
change crashed at most fishing mortalities with L^=30
and r=l. Hence, knowledge of the cues determining both
maturity and sex change will be important in predict-
ing and understanding larval production and the effect
of fishing on a population.
It is possible to argue that a protogynous species with
fixed patterns of sex change may have very different
dynamics than dioecious stocks, but the compensatory
patterns of sex change will be less sensitive to fishing
and exhibit dynamics very similar to their dioecious
counterparts. However, our results indicate that even
stocks with plastic patterns of sex change are predicted
to have dynamics distinctly different from otherwise
identical dioecious populations. For example, sperm
limitation is predicted to occur for all sex change rules,
except for the pattern where sex change is determined
by expected reproductive success (rule 4). However,
even a stock exhibiting the reproductive sucess rule
has dynamics that are distinctly different from those
of a dioecious species because a change in the size dis-
tribution of the population due to size-selective fishing
is predicted to have a large effect on the productivity
and sex ratio of the protogynous population. Similarly,
mating group size is predicted to affect the stock dy-
namics in all cases except for the reproductive success
rule. Therefore, although knowing the pattern of sex
change is predicted to be important in understanding
stock dynamics, it is also clear that the pattern of sex
change must be considered in the context of the mat-
ing system of the stock, as well as in the context of the
basic biology of the stock.
Protogynous stocks are thus predicted to be sensitive
to the fishing pattern, and nonlinear stock dynamics
are possible when fishing operations target a wide range
of fish sizes. However, each stock is also predicted to
have a unique response to the same fishing pattern
(Figs. 4-6) and to have different relationships between
traditional spawning-per-recruit measures and changes
in mean population size with fishing mortality (Figs. 1,
2, and 7). As a result, monitoring changes in spawn-
ing stock biomass per recruit or egg production per
recruit alone will not make it possible to determine the
relationship between these measures and mean popula-
tion size or to know whether the population is at risk
for large and sudden declines in population size. Our
results indicate that although it is important to know
whether sex change occurs when managing a stock,
it will also be important to know what endogenous or
exogenous cues induce sex change and how behavioral
patterns and life history strategies affect the demo-
graphic rates of the stock.
Plasticity is not predicted to yield populations that
have stock dynamics that are identical to those of di-
oecious species, and the performance of spawning-per-
recruit measures and the relationship between egg pro-
duction and population size differed greatly between all
four patterns of sex change, despite the fact that the
basic patterns of growth, survival, and fecundity where
identical between all the scenarios considered. Because
sperm limitation is more common with the fixed and
relative size rules of sex change, these situations are
predicted to have the greatest difference between clas-
sic SPR measures and the production of fertilized eggs.
Clearly it is not just whether a population changes sex
or not, but also how sex change is induced, that deter-
mines the population's predicted response to fishing
and the performance of spawning-per-recruit measures
in predicting and indicating the effect of fishing on the
population.
Although it is important to know what life history
strategy and behavioral patterns are observed in a
species, these alone will not always be sufficient to
predict expected changes in population size and pro-
ductivity under new conditions. Instead, knowledge of
the plasticity of behavioral and life history patterns,
as well as information about the internal and exter-
nal cues that induce phenotypic changes, may also be
necessary. Phenotypic plasticity is often expressed as a
threshold response (such as sex change) to a continuous
endogenous or exogenous cue. Therefore, as predicted by
our model, plasticity can generate nonlinear changes in
important demographic characters. An understanding
of the natural variation in behavior and life history
combined with knowledge of fish vital rates and envi-
ronmental conditions will lead to a better understand-
ing of and ability to predict the response of a stock to
fishing mortality, environmental changes, and specific
management strategies.
Acknowledgments
This research was supported by National Science Foun-
dation grant IBN-0110506 to Suzanne Alonzo and the
Center for Stock Assessment Research (CSTAR).
244
Fishery Bulletin 103(2)
Literature cited
Alonzo, S. H., and M. Mangel.
2004. Size-selective fisheries, sperm limitation and
spawning per recruit in sex changing fish. Fish. Bull.
102:1-13.
Apostolaki, P., E. J. Milner-Gulland, M. K. McAllister, and
G. P. Kirkwood.
2002. Modelling the effects of establishing a marine
reserve for mobile fish species. Can. J. Fish. Aquat.
Sci. 59:405-415.
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246
Abstract— The growth rate of Steller
sea lion (Eumetopiasjubatus) pups was
studied in southeast Alaska, the Gulf
of Alaska, and the Aleutian Islands
during the first six weeks after birth.
The Steller sea lion population is cur-
rently stable in southeast Alaska but
is declining in the Aleutian Islands
and parts of the Gulf of Alaska. Male
pups (22.6 kg [±2.21 SD]) were sig-
nificantly heavier than female pups
(19.6 kg [±1.80 SD]) at 1-5 days of
age, but there were no significant dif-
ferences among rookeries. Male and
female pups grew (in mass, standard
length, and axillary girth) at the same
rate. Body mass and standard length
increased at a faster rate for pups in
the Aleutian Islands and the western
Gulf of Alaska (0.45-0.48 kg/day and
0.47-0.53 cm/day, respectively) than
in southeast Alaska (0.23 kg/day and
0.20 cm/day). Additionally, axillary
girth increased at a faster rate for
pups in the Aleutian Islands (0.59 cm/
day) than for pups in southeast Alaska
v(0.25 cm/day). Our results indicate a
greater maternal investment in male
pups during gestation, but not during
early lactation. Although differences
in pup growth rate occurred among
rookeries, there was no evidence that
female sea lions and their pups were
nutritionally stressed in the area of
population decline.
Neonatal growth of Steller sea lion
(Eumetopias jubatus) pups in Alaska
Elisif A. A. Brandon
Department of Marine Biology
Texas A&M University at Galveston
5007 Avenue U
Galveston, Texas 77551
Present address: 97A Lowell Ave
Newton, Massachusetts 02460
Donald G. Calkins
Alaska SeaLife Center
P.O. Box 1329
Seward. Alaska 99664
Thomas R. Loughlin
National Marine Mammal Laboratory
Alaska Fisheries Science Center, NMFS
7600 Sand Point Way, NE
Seattle, Washington 98115
Randall W. Davis
Department of Marine Biology
Texas A&M University at Galveston
5007 Avenue U
Galveston, Texas 77551
E-mail address (for R. W Davis, contact author): davisngitamug edu
Manuscript submitted 26 April 2004
to the Scientific Editor's Office.
Manuscript approved for publication
2 December 2004 by the Scientific Editor.
Fish. Bull. 103:246-257 (2005).
Sea lion (order Carnivora, family
Otariidae) pups depend entirely on
milk for neonatal growth (Bonner,
1984). Studies of sea lions and fur
seals have shown that if a pup does
not obtain enough milk from its
mother, it will exhibit poor body condi-
tion (i.e., reduced lean mass and total
lipid mass for a given age or standard
length) and a reduced growth rate
(Trillmich and Limberger. 1985; Ono
et al., 1987). Poor body condition and
reduced growth rate, in turn, may
have lifelong consequences because
neonatal growth is an important
factor in determining adult size and
survival (Bryden, 1968; Innes et al.,
1981; Calambokidis and Gentry, 1985;
Albon et al., 1992; Baker and Fowler,
1992; Gaillard et al., 1997; Boltnev et
al., 1998; Tveraa et al„ 1998; Burns,
1999). Because of their large size,
aggressive behavior, sensitivity to
disturbance, and the remote location
of their rookeries, less is known about
the early growth of Steller sea lions
(SSL) than of most other pinniped
(seals, sea lions, and walrus) species.
Higgins et al. (1988) measured body
mass of SSL pups on Ano Nuevo Island
in California but only reweighed five
pups to measure growth rates. Mer-
rick et al. (1995) weighed SSL pups
at a number of locations throughout
the Gulf of Alaska and the Aleutian
Islands but did not reweigh them to
assess individual growth rates.
Genetic studies show that there are
distinct eastern and western popula-
tions of SSL (Bickham et al., 1996,
1998) (Fig. 1). The eastern population
comprises animals in California, Ore-
gon, British Columbia, and southeast
Alaska. The western population com-
prises animals in the Gulf of Alaska,
the Aleutian Islands, the Bering Sea,
the Commander Islands, Kamchatka,
and the Kuril Islands. A severe popu-
Brandon et al.: Neonatal growth of Eumetopias /ubatus
247
~65°N
- 60°
-55°
180°
1
Bering Sea
Sequam
Island Yunaska
>j^ Kl, Hid
■to.*.*
\
^teutian Islands
Chinkof Island
Lowrie -
Island
250 miles
170°
/
160°
I
150°W
I
250 kilometers
1
Figure 1
Study sites for Steller sea lions iEumetopias jubatus) in Alaska. The Lowrie Island rookery in south-
east Alaska has a stable population but rookeries at Fish, Marmot and Chirikof Islands in the Gulf of
Alaska and Yunaska and Seguam Islands in the Aleutian Islands are areas where the population of
Steller sea lions has declined.
lation decline (>80'7f) occurred in the western popula-
tion between the 1970s and the 1990s. In 1997, these
population changes led to the reclassification of the
western population from "threatened" to "endangered"
and a classification of the eastern population as "threat-
ened" under the Endangered Species Act (U.S. Federal
Register 62:24345-24355).
One hypothesis for the decline in population of SSLs
is a decrease in food availability or quality in the Gulf
of Alaska and the Aleutian Islands (Pascual and Adki-
son, 1994; York, 1994; Calkins et al., 1999; NMFS1-2).
If females are unsuccessful in obtaining sufficient food,
pups will develop more slowly or die because of a de-
crease in milk supply. To examine the potential effects
NMFS (National Marine Fisheries Service). 1992. Re-
covery plan for the Steller sea lion tEumetopias jubatus),
92 p. Prepared by the Steller Sea Lion Recovery Team for
the National Marine Fisheries Service, Silver Spring, MD.
[Available from the National Marine Mammal Laboratory,
7600 Sandpoint Way. NE, Seattle, Washington 98115.)
; NMFS (National Marine Fisheries Service). 1995. Sta-
tus review of the United States Steller sea lion (Eumeto-
pias jubatus) population. 61 p. Prepared by the National
Marine Mammal Laboratory, Alaska Fisheries Science
Center. [Available from the National Marine Mammal Labo-
ratory, 7600 Sandpoint Way, NE, Seattle, Washington 98115.]
of food availability on pup development, we measured
growth rates of male and female pups from stable and
declining populations of SSL in Alaska from 1990 to
1997. Our null hypothesis was that there was no differ-
ence in pup growth rates among rookeries in southeast
Alaska, the Gulf of Alaska, and the Aleutian Islands.
The alternative hypothesis was that pups grew at a
faster rate in southeast Alaska, the area of stable popu-
lation. However, our results showed that pups grew
faster in the area of declining population during the
first six weeks after birth. In addition, females invested
more energy in male pups at all locations during gesta-
tion, but not during early lactation.
Materials and methods
Animals and study sites
From 1990 to 1997, SSL pups were studied at loca-
tions in southeast Alaska, the Gulf of Alaska, and the
Aleutian Islands (Fig. 1 and Table 1). At Lowrie Island
<54°51'N, 133°32'W) in southeast Alaska, measure-
ments were made in 1993, 1994, and 1997. The rookery
at Lowrie Island is in the area of the stable population
(Calkins et al., 1999). In the Gulf of Alaska, measure-
248
Fishery Bulletin 103(2)
Table 1
Locations
dates, and the number of Steller sea lior
lEumetopias jubatus)
pups captured (/i).
Location
Dates
n
Stable population
Lowrie Island (1993)
26 May-5 June
15-19 June
3 July
25
5
1
Lowrie Island (1994)
15-22 June
24-30 June
13-14 July
28
9
3
Lowrie Island (1997)
5-12 June
16-29 June
25
11
Declining population
Fish Island (1995)
9-10 June
24-26 June
13-14 July
20
13
12
Marmot Island (1990)
27 June
8
Marmot Island (1991)
30 June
11
Marmot Island (1994)
27 June
15 July
21'
11-'
Chirikof Island (1993)
11-17 June
27-28 June
7 July
18 July
20
14
11
4
Yunaska and Seguam Islands
(1997)
8-16 June
22-24 June
4 July
16
12
5
; Nine known-age pups.
2 Six known-age pups.
merits were made in 1990, 1991, and 1994 on Marmot
Island (58°12'N, 151°50'W), in 1993 on Chirikof Island
(55°10'N, 155°8'W) and in 1995 on Fish Island (59°53'N,
147°20'W). On the Aleutian Islands of Seguam (52°30'N,
172°30'W) and Yunaska (52°45'N, 170°45"W), pups were
studied in 1997. Data from Seguam and Yunaska Islands
were combined because the islands are geographically
close and can be considered part of one rookery complex.
Rookeries in the Gulf of Alaska and the Aleutian Islands
are in the area of declining population, although the
rookery on Fish Island has not shown as precipitous a
decline. Samples could not be obtained from all rooker-
ies in all years because of logistical constraints and the
need to minimize disturbance to rookeries. However,
concurrent data were obtained from the declining and
stable populations in 1993, 1994, and 1997.
Only pups that had an attached umbilical cord or an
unhealed umbilicus were selected for study. The fresh-
ness of the umbilical cord was used as a rough estimate
of age between 1 and 5 days (Davis and Brandon3).
3 Davis, R. W, and A. A. Brandon. Unpubl. data. I Data are
on file at Texas A&M University, 5007 Avenue U, Galveston,
Texas 77551.1
Choosing only pups with fresh umbilical cords mini-
mized the age bias (Trites, 1993) that occurs when pups
are captured at different times and rookeries (Table 1).
Although pups were not selected by sex, sex was
noted and used as a factor in analyses. Body mass
(BM), standard length (SL), axillary girth (AG) (Am.
Soc. Mammalogists, 1967) and body composition were
measured for each pup. BM was measured to the near-
est kilogram with a mechanical spring scale (Chatillon
160, Ametek, FL) on Marmot Island in 1990 and 1991
and on Lowrie Island in 1993. Body mass of pups at all
other sites and years was measured to the nearest tenth
of a kilogram by using an electronic scale (Rice Lake
Weighing Systems, Rice Lake, WI; Ohaus I-20W, Ohaus,
Pine Brook, NJ). Standard length was measured as a
straight line from tip-of-nose to tip-of-tail, ventral sur-
face down. Pups were restrained by hand and marked
for later identification with hair bleach (Lady Clairol
Maxi Blond, Clairol, Inc.) and with flipper tags attached
in the axillary area of the fore-flippers.
Body composition was measured by using the labeled
water method (Nagy 1975; Nagy and Costa, 1980; Cos-
ta, 1987; Bowen and Iverson, 1998). In this study, water
labeled with a stable isotope of hydrogen (deuterium)
Brandon et al.: Neonatal growth ot Eumetopias /ubatus
249
was used to estimate total body water (TBW in kg and
%TBW as a percentage of BM). Background concentra-
tion of deuterium was determined from blood samples
taken from pups that were subsequently injected intra-
muscularly with 10 mL deuterium oxide (D._,0) (99% en-
riched, Cambridge Isotope Laboratories, Andover, MA).
After a two-hour equilibration period (Costa, 1987),
blood samples were taken to determine the dilution of
injected deuterium in total body water.
Pups were recaptured at approximately two-week
intervals over periods ranging in length from 18 to
38 days (average measurement period was 29.6 days)
(Table 1) and were weighed, measured, and a blood
sample was taken from each pup. Similar protocols were
used at all rookeries, except Marmot Island in 1990 and
1991, when only BM and SL were measured, and the
age of pups was not estimated. Therefore, no growth
rates were obtained from these data.
Labeled water sample analysis
Blood samples were centrifuged in the field in serum
separator tubes, and the serum was transferred to cryo-
vials that were frozen at -20°C until analysis. Isotope-
ratio mass spectrometry was used to determine the
ratio of deuterium (2H) to hydrogen (H) (Laboratory of
Biochemical and Environmental Studies at University
of California, Los Angeles, CA). The hydrogen-isotope
dilution space was calculated from this ratio by using
Equation 3 in Schoeller et al. (1980). However, the hydro-
gen-isotope dilution space has been shown to underesti-
mate TBW in a number of pinniped species (Reilly and
Fedak, 1990; Arnould et al., 1996b), leading Bowen and
Iverson (1998) to develop a single predictive equation to
estimate '/'< TBW from hydrogen-isotope dilution space in
pinnipeds for which data on the accuracy of the hydro-
gen-isotope method are lacking. The equation
9cTBW = 0.003 + 0.968 H-dilution space
(1)
was used in the present study to correct the overesti-
mated %TBW by 3.3% (Bowen and Iverson, 1998, Eq. 5).
Percent total body lipid (%TBL, as a percentage of BM)
was calculated by using predictive equations derived
from the relationship between %TBW and 7cTBL for
Antarctic fur seals (Arnould et al., 1996b):
%TBL = 66.562 - 0.845 %TBW.
(2)
9cTBL was then compared between male and female pups
and among rookeries.
Statistical analyses
Statistics were performed by using Systat (version 11,
SPSS, Inc, Chicago, ID, and by first treating each study
site and year as a separate "location," then combining
data for multiple years at a location (e.g., Marmot Island
and Lowrie Island) when no significant interannual
differences were found. Significance was determined
at PsO.05. Data were examined for heteroscedasticity
(unequal variances) before analysis (Zar, 1984). A\\ post
hoc pairwise comparisons were made with the Tukey
multiple comparison test. Data from the first capture
(1-5 days of age) were analyzed for comparison by loca-
tion and sex by using two-way ANOVA. Pup growth rate
was estimated by performing a linear regression for each
pup and extrapolating to t = 0 to estimate birth mass.
Differences among means of pup growth rate and birth
mass were then analyzed by using two-way ANOVA to
determine differences by location and sex.
Results
Neonatal size
There were no significant differences by rookery in
pup mass at 1-5 days of age (Table 2) and no signifi-
cant interaction between rookery and sex. The only
significant difference in SL of 1-5 day old pups was that
both genders were significantly longer on Seguam and
Yunaska Islands than on Fish Island (P=0.0395). Pups
on Chirikof Island had significantly smaller AG than
pups on Lowrie, Fish, and Seguam and Yunaska Islands
(P<0.02). Male and female pups were significantly differ-
ent for all three morphometric measurements. Overall,
male pups averaged 22.6 kg (±2.21 SD, ?i=71) and female
pups averaged 19.6 kg (±1.80 SD, ;?=74) at first capture
( 1-5 days of age).
There was no significant difference by rookery or sex
and no significant interaction between rookery and sex
in %TBW or %TBL of pups at first capture. When all
pups at all rookeries were combined ( « =116), %TBW
was 72.1% of BM (±3.17 SD) and %TBL was 5.6% of
BM (±2.68 SD). Male pups had a significantly greater
absolute TBW than female pups (P<0.0001), as would be
expected because of the difference in BM at birth. There
was a significant correlation between TBW and BM
(Pearson r=0.945, P<0.001, ra=116; TBW (kg) = 0.6895
xBM + 0.6618).
Neonatal growth
Growth rates were treated as linear over the period
monitored; there were not enough data to determine
if growth was nonlinear. Male and female pups on the
same rookery grew at the same rate (in BM, SL, and
AG) during the first six weeks after birth (Fig. 2). When
compared by rookery, BM increased at a faster rate for
pups on Chirikof Island (P=0.0005) and on Seguam
and Yunaska Islands (P= 0.0002) than on Lowrie Island
(Fig. 3 and Table 3). The increase in BM for pups on
Fish Island did not differ significantly from that at
other rookeries. Marmot Island pups grew significantly
more slowly than pups on Seguam and Yunaska Islands
(P= 0.0382) but did not differ significantly from growth
of pups at other rookeries.
Standard length increased at a faster rate for pups
on Chirikof Island (P=0.0068) and Seguam and Yu-
250
Fishery Bulletin 103(2)
naska Islands (P= 0.0050) than it did for pups on Low-
rie Island (Table 3). Growth in SL was also faster on
Chirikof (P=0. 0383) and Seguam and Yunaska Islands
(P=0.0230) than on Fish Island, whereas the increase
in SL on Marmot Island did not differ significantly
from the other rookeries. The increase in AG was sig-
nificantly greater on Seguam and Yunaska Islands
(P=0.0021) and Marmot Island (P=0.0364) than on
Lowrie Island. There was no significant interaction
between rookery and sex in the growth rate of BM,
SL, and AG.
Body mass at birth extrapolated to t = 0 from growth
rates did not differ by rookery. There was no significant
interaction between rookery and sex, but extrapolated
birth mass did differ by sex (P<0.0001). Male pups at all
rookeries averaged 22.4 kg (±2.36 SD, rc = 39), whereas
female pups averaged 18.7 kg (±2.08 SD, n = 35). These
extrapolated birth masses were similar to the average
BM measured on the rookery for male (22.6 kg) and
female (19.6) pups 1-5 days old. There was no correla-
tion between extrapolated birth mass and growth rate
(Pearson r=-0.09, P=0.45).
Table 2
Body mass (BM), standard length (SL),
and
ixillary girth (AG) of neonatal li-
5 day old) Steller sea lion (Eumetopias
jubatus)
pups in the stable (Lowrie Island I a
rid declini
ng (Fish
s.. Marmot I
s., Chirikof Is., Seguam Is.
Yunaska
Is.) populations (mean
±SD). An asterisk (*)
ndicates sign
ificant differences
Tom all other sites, and
t indicates a significant difference between two
sites. Standard length
from Fish Is
was
sign
ificantly different from SL on Seg
jam and Yunaska Is. Ax
llary girth on
Chirikof
Is. was significantly different from AG at
all other sites
In all cases.
males were significantly larger than females. There were no
significant interannua
1 differences;
therefore data from all years at Lowrie Is. were combined.
Location
n
BM
kg)
SL(cm)
AG (cm)
male
female
male
female
male
female
Lowrie Is. (1993-97)
39M
22.1
19.5
98.3
94.1
64.9
64.3
41F
±2.20
±1.67
±4.56
±3.96
±3.33
±5.01
Fish Is. (1995)
11M
22.6
19.2
96. 2t
93. 3t
68.5
64.0
9F
±1.69
±2.39
±26.76
±6.39
±2.96
±4.00
Marmot Is. (1994)
3M
21.7
20.2
101.7
97.4
65.5
61.8
6F
±1.80
±2.42
±1.53
±2.67
±2.78
±5.38
Chirikof Is. (1993)
11M
23.21
19.02
99.1
94.9
62.7*
60.1*
9F
±2.59
±1.05
±5.24
±2.40
±3.52
±2.15
Aleutian Is.
( Seguam and Yunaska Is. ) ( 1997 )
7M
24.2
20.5
101.4+
96.3t
67.7
63.9
9F
±1.97
±1.88
±4.29
±2.55
±3.50
±3.66
Table 3
Steller sea lion (Eumetopias jubatus) pup growth from 0 to 40 days of age (mean
between male and female pups. BM=body mass; SL = standard length; AG = axillar>
no significant differences within an underlined grouping (e.g., for body mass grow
and A was significantly different from M and L).
±SD).
girth.
:h rate
There were no significant differences
Underlining indicates that there were
, C was significantly different from L,
Location n
BM
growth rate
(kg/day)
SL
growth rate
(cm/day)
AG
growth rate
(cm/day)
Lowrie Is. (L) 26
Fish Is. (F) 13
Marmot Is. (M) 6
Chirikof Is. (C) 17
Aleutian Is. (A) (Seguam and Yunaska Is.) 12
0.23 ±0.176
0.35 ±0.171
0.28 ±0.141
0.45 ±0.126
0.48 ±0.168
0.20 ±0.322
0.22 ±0.183
0.22 ±0.287
0.47 ±0.171
0.53 ±0.163
0.25 ±0.244
0.41 ±0.235
0.59 ±0.510
0.47 ±0.187
0.59 ±0.257
ANOVA results
LMFCA
LFMCA
LFCMA
Brandon et al.: Neonatal growth of Eumetopias /ubatus
251
A
D male
■ female
10 15 20 25 30 35 40
E
>,
13
c
□ male
■ female
I ' ' ' ' I ' ' ' ' I i | i i i i | i i i i | i i i i |
5 10 15 20 25 30 35 40
B
1 ' i ' > ■ ' i ■ > > > i > > ' ■ i ' ' > > i ' > ■ > i > > ' > i > > ' ' i
0 5 10 15 20 25 30 35 40
Age (days)
Figure 2
Change in body mass of individual Steller sea lion (Eumetopias jubatus) pups captured on I A) Lowrie Island
in 1993, 1994, and 1997, (B) Fish Island in 1995, (C) Marmot Island in 1994, (D) Chirikof Island in 1993,
and (E) Yunaska and Seguam Islands in 1997.
252
Fishery Bulletin 103(2)
Discussion
Compared to other species of sea lions and fur seals, SSL
pups are large, although this species produces smaller
pups in relation to adult size than do smaller otariids
(Kovacs and Lavigne, 1992; McLaren, 1993). In the
present study, male pups averaged 22.6 kg and female
pups averaged 19.6 kg at 1-5 days of age, which is in
the range of birth masses reported in the literature. Two
studies conducted before the recent population decline
reported 17 kg for male pups at birth (Scheffer, 1945)
and a range of 9.1-21.8 kg for male and female pups
(Mathisen et al., 1962). Late in the population decline,
studies reported a range of 16-23 kg for pups at birth in
Alaska (Calkins and Pitcher, 1982) and an extrapolated
birth mass of 17.9 kg for five pups for which growth rates
were measured in California (Higgins et al., 1988).
This is the first, large-scale (in terms of sample size
and geographic area) longitudinal study of growth in
Steller sea lion pups. Growth rates reported in our
study are the highest absolute growth rates reported for
any sea lion or fur seal. This is to be expected because
adult SSLs are the largest otariids (Kovacs and Lavi-
gne, 1992). The growth rate of 0.38 kg/day measured
for five SSL pups at Afio Nuevo Island in California
(Higgins et al., 1988) falls within the range of average
growth rates measured in the present study (0.23-0.48
kg/day). The only other measurement of pup growth in
SSLs was conducted on captive pups that were already
Chmkof Island
1993
Lowne Island
1993-94, 1997
Marmot Island
1994
15 20 25
Age (days)
35
Figure 3
Summary of Steller sea lion lEumetopias jubatus) pup growth (body
mass) during the first six weeks after birth for all five rookeries.
The length of each line indicates the length of the study period at
that location. Pups from Seguam, Yunaska, and Chirikof Islands,
in the declining population, grew significantly faster than pups
from Lowrie Island, in the stable population. Pups from Seguam
and Yunaska Islands also grew significantly faster than pups from
Marmot Island.
several months old. In terms of growth rate in relation
to size at birth, SSL pups gained 1-2.3% of their birth
weight per day (Lowrie Island and Seguam and Yu-
naska Islands, respectively, based on an average birth
mass of 21.1 kg), which was faster than the relative
growth rates reported for other otariid species (Kovacs
and Lavigne, 1992, calculated from Table 1), except for
northern fur seals. In contrast, seals (order Carnivora,
family Phocidae) exhibit faster growth rates (1.3-5.6
kg/day or 8-26% birth weight per day) (Stewart and
Lavigne, 1980; Bowen et al., 1985; Kovacs and Lavigne,
1985; Bowen et al., 1987; Bowen et al., 1992; Campagna
et al., 1992). Although adult SSLs are larger than many
species of phocid seals, phocids have much shorter lacta-
tion periods and their pups grow at a more accelerated
rate than do otariids.
Male-female differences
Male pups weighed 159c more than females at birth, indi-
cating a difference in maternal investment during gesta-
tion, which has been found in other otariids including
Antarctic fur seals (Doidge et al., 1984; Lunn and Boyd,
1993; Goldsworthy, 1995; Boyd, 1996), South American
fur seals (Arctocephalus australis) (Lima and Paez. 1995),
California sea lions (Ono and Boness, 1996), and southern
sea lions (Otaria byronia) (Cappozzo et al., 1991). These
results are consistent with the predictions of Maynard-
Smith's (1980) theory on sexual investment. Steller sea
lion adults are extremely sexually dimorphic;
females weigh 263 kg on average (maximum
of approximately 350 kg); males weigh more
than twice as much (average of 566 kg, maxi-
mum of approximately 1120 kg) (Calkins and
Pitcher, 1982). In view of this dimorphism
and the fact that size is more important to
male fitness than to female fitness in a polyg-
ynous species (McCann, 1981) such as the
SSL, theory predicts that males would be
heavier than females at birth. Northern fur
seal females with male fetuses are in poorer
condition than mothers with female fetuses
(Trites, 1992), and male fetuses grow at a
faster rate than female fetuses (Trites, 1991),
indicating that mothers invest more in male
offspring during gestation.
However, there were no male-female dif-
ferences in neonatal growth (BM, SL, and
AG) rate in SSL during the first six weeks
after birth. In a species as sexually dimor-
phic as SSL, one would expect males to grow
at a faster rate than females during devel-
opment. However, this difference may not
occur until the animals are older. There is
some evidence that male otariids undergo a
sharp increase in growth rate near sexual
maturity (McLaren, 1993; Bester and Van
Jaarsveld, 1994), after females have already
reached sexual maturity and their growth
has slowed.
"H
40
Brandon et al.: Neonatal growth of Eumetopias jubatus
253
Conflicting results have been reported in other
growth studies of otariids. Several studies reported
that male pups grew faster than female pups (Antarctic
fur seals: Payne, 1979; Doidge et al.. 1984; Antarctic
and Subantarctic fur seals: Kerley, 1985; New Zealand
fur seals: Mattlin 1981). However, cross-sectional data
on growth rate were used in these studies. Conversely,
longitudinal data, considered to be more accurate, dem-
onstrate no differences in neonatal growth rate between
male and female Antarctic fur seal pups (Doidge and
Croxall, 1989; Lunn et al., 1993; Lunn and Arnould,
1997); Goldsworthy (1995), however, is the exception.
Ono and Boness (1996) collected longitudinal growth
data on California sea lion pups and found that males
grew faster than females, but they found no other evi-
dence of differential maternal investment. In phocids,
most studies have found no difference in neonatal male
and female growth rates, regardless of whether the
data were longitudinal or cross sectional (Stewart and
Lavigne, 1980; Innes et al., 1981; Bowen et al., 1992).
This is true for species with extreme sexual dimor-
phism such as elephant seals (McCann et al., 1989;
Campagna et al., 1992). The only other study where
growth rates for SSL pups were measured did not have
a large enough sample size for a comparison between
males and females (Higgins et al., 1988). No differences
between male and female pups were found for suckling
behavior or maternal attendance behavior (Higgins et
al., 1988).
Total body lipid
Average %TBL of neonatal pups was low (5.6% BM).
Steller sea pups are born with small energy stores and
normally fast for short periods (about one day) while
their mothers make foraging trips to sea. There have
been few measurements of lipid content in otariid neo-
nates. Jonker and Trites (2000) found a blubber content
of 9.7% BM in five SSL pups in the first month after
birth. However, this measurement does not correspond
directly to body fat content because they measured blub-
ber content by weighing the sculp (skin plus blubber) and
then calculating the fraction of sculp that was blubber by
measuring skin and blubber thicknesses. Using the same
labeled water method as in the present study, Arnould et
al. (1996b) found a %TBL of 9.4% BM in four Antarctic
fur seal pups in the first month after birth. In a similar
study of one-day-old Antarctic fur seal pups, Arnould et
al. (1996a) found a %TBL of 7.0% BM for female pups
and 4.9% BM for male pups. Also using labeled water,
Oftedal et al. (1987a) found an average %TBL of 5% BM
for neonatal California sea lion pups.
Arnould et al. (1996b) suggested two explanations
for the higher lipid content that they found in Antarc-
tic fur seal pups in comparison to California sea lion
pups (Oftedal et al. 1987b). First, in colder habitats, a
larger subcutaneous lipid store may be necessary for
thermoregulation. The data here do not support that
explanation. SSL live in a colder habitat than Cali-
fornia sea lions, but have a similar %TBL. The more
likely explanation is that larger lipid stores are found
in species in which pups normally fast longer while
their mothers are foraging. Steller sea lion pups have
the smallest lipid stores and shortest fasting periods
(Brandon, 2000) of the three species.
Differences in pup size among rookeries
Although male and female pups differed significantly
in size, there were no significant differences in pup size
at birth among the rookeries studied. Rookery location
should have less influence on pup size at birth than on
neonatal growth because maternal foraging range is
much greater during gestation than during lactation
(Merrick and Loughlin, 1997). This greater maternal
foraging range during gestation reduces, among rook-
eries, variation in maternal size and feeding conditions
(quantity and quality of prey available) during gestation,
both of which have been shown to influence pup birth
mass in pinnipeds (Calambokidis and Gentry, 1985;
Kovacs and Lavigne, 1986; Trites, 1991; Trites 1992).
The lack of a difference in pup BM at birth among rook-
eries could also be explained by the fact that females
that are "successful" (i.e.. carry their fetuses to term)
have a significantly better body condition than females
that do not carry their fetuses to term (Pitcher et al.,
1998). As a consequence of our study design, only those
females that were successful were used, and therefore
our sample was biased toward females in the population
with better body condition. In addition, gestation is less
energetically expensive than early lactation; therefore
differences in food availability would have less of an
effect during gestation (Robbins and Robbins, 1979;
Albon et al., 1983; Oftedal, 1984).
Although most pup morphometries at first capture did
not differ among rookeries, growth parameters differed
significantly (Table 3). Growth rates of pups on Seguam
and Yunaska Islands (0.48 kg/day) and on Lowrie Is-
land (0.23 kg/day) represented the extremes, whereas
growth rates of pups on Chirikof, Marmot, and Fish
Islands fell between these two extremes. In general,
faster growth rates occurred in the west and slower
growth rates in the east. In terms of mass, Seguam and
Yunaska Islands and Chirikof Island pups grew twice
as fast as Lowrie Island pups. A concurrent study of
the attendance patterns of lactating females (Brandon,
2000) showed that foraging trip duration decreased
from east (25.6 hours on Lowrie Island) to west (an
average of9.4 hours on Chirikof and Seguam Islands).
Therefore, it is possible that the higher growth rates in
SSL pups in the western Gulf of Alaska and Aleutian
Islands resulted from shorter periods of fasting while
females were foraging at sea (Arnould et al., 1996a;
Goldsworthy, 1995).
Is food limiting growth in Steller sea lion pups
in the area of population decline?
If the cause of the population decline were decreased
food availability, which is one of the leading hypotheses
254
Fishery Bulletin 103(2)
(Pascual and Adkison, 1994; York, 1994; NMFS2!, one
might expect the animals in the declining population
to show signs of nutritional stress compared to those
in the stable population. The results for pup size and
growth give no indication of food stress during early
lactation. In fact, pups from the declining population
on Seguam, Yunaska, and Chirikof Islands grew faster
than pups from the stable population on Lowrie Island
during the first six weeks. Similar results were also
found in a study of pup BM (Merrick et al., 1995), in
which pups were weighed on rookeries from Oregon to
the Aleutian Islands in late June and early July from
1987 to 1994. Although the pups' ages were unknown,
weighing date was used as a covariate in the analysis.
Merrick et al. (1995) found a continuous increase in
pup BM from Oregon to southeast Alaska and to the
Aleutian Islands. These investigators also concluded
that pup BM was on average greater in the declining
population.
In most other studies of declining populations or dif-
ferences among rookeries, such contradictory results
have not been seen. A study of California sea lion pups
during an ENSO (El Nino Southern Oscilliation) event
revealed lower pup growth during the period of food
stress (Boness et al., 1991). Trillmich and Limberger
(1985) have also seen clear effects of low food avail-
ability during an ENSO in Galapagos fur seals and
sea lions. Antarctic fur seals are affected in predictable
ways (increased pup mortality and increased female for-
aging time) during times of decreased food availability
(Costa et al., 1989). Hood and Ono (1997) found that in
the declining California population of SSLs, pups spent
less time suckling when adult females made longer for-
aging trips in 1992 than in 1973 when the population
was larger. The longer foraging trips suggested less
abundant food resources.
Considering the results for SSL pup growth in light
of the population decline, we suggest three alternative
hypotheses: 1) food availability was never a factor in
the population decline; 2) food availability caused the
overall decline, but lactating females and their pups
were not affected during early lactation; or 3) our study
was conducted when pups and lactating females were no
longer experiencing decreased food availability.
Faster rates of pup growth may be normal for the
Aleutian Islands and western Gulf of Alaska despite
the population decline. The declining and stable popula-
tions are genetically distinct (Bickham et al., 1996), and
perhaps the differences seen in our study are normal
differences between the two populations. It is impos-
sible to determine if growth and foraging behavior have
changed over time because historical data on maternal
investment are sparse. Juveniles rather than neonates
may be the affected age class in the declining popula-
tion (Merrick et al., 1988), whereas lactating females
are feeding on either different prey or age classes and
not experiencing decreased food availability. York (1994)
constructed a population model for SSLs in Alaska and
concluded that the current population decline could be
accounted for by increased juvenile mortality.
Alternatively, because our study was performed late in
the decline, the higher growth rates could be the result
of lower population density and less competition for food
in the declining population. Trites and Bigg (1992) re-
ported larger body sizes in northern fur seal populations
during a period of decline. The northern fur seal popula-
tion in the Pribilof Islands in the Bering Sea increased
from the early 1900s to the 1950s. During this period,
adult body size decreased. From 1950 to the 1970s the
population declined and there was a concurrent increase
in individual body size (Trites and Bigg, 1992). Scheffer
(1955) hypothesized that increased body size was due
to decreased competition for food, which in turn would
be due to the lower population density. It is possible
that the same density-dependent effects are occurring
in the declining SSL population because our study was
performed late in the decline, after the original cause
may have abated. More information will be needed to
determine the cause of the SSL decline and whether it
is related to availability of food, especially for different
age classes, and to different times of the year.
Acknowledgments
We thank T. Adams, R. Andrews , D. Bradley, J. Burns,
M. Castellini, J. K. Chumbley, W. and S. Cunningham,
J. Davis, F. Gulland, D. Gummeson, B. Heath, D. John-
son, S. Kanatous, D. Lidgard, R. Lindeman, R. Merrick,
D. McAllister, L. Milette, K. Ono, L. Polasek, T. Porter,
D. Rosen, J. Sease, T. Spraker, U. Swain, W. Taylor, A.
Trites, D. van den Bosch, T Williams, and the captain
and crew of the RV Mecleia for assistance in the field.
We thank K. Andrews for the map and D. Brandon for
assistance in data collection and analysis. G. Worthy, A.
Trites, T. Lacher, D. Owens, and M. Reynolds reviewed
an early version of this manuscript. Funding and logis-
tical support in the field were provided by the Alaska
Department of Fish and Game, the National Marine
Fisheries Service/National Marine Mammal Labora-
tory, Texas A&M University, and the Texas Institute
of Oceanography. This research was conducted under
Marine Mammal permit no. 846 and 963.
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258
Abstract— The carpenter seabream
(Argyrozona argyrozona) is an
endemic South African sparid that
comprises an important part of the
handline fishery. A three-year study
(1998-2000) into its reproductive biol-
ogy within the Tsitsikamma National
Park revealed that these fishes are
serial spawning late gonochorists.
The size at 50% maturity (L50) was
estimated at 292 and 297 mm FL for
both females and males, respectively.
A likelihood ratio test revealed that
there was no significant difference
between male and female L50 (P>0.5).
Both monthly gonadosomatic indices
and macroscopically determined ovar-
ian stages strongly indicate that A.
argyrozona within the Tsitsikamma
National Park spawn in the astral
summer between November and April.
The presence of postovulatory follicles
(POFs) confirmed a six-month spawn-
ing season, and monthly proportions
of early (0-6 hour old) POFs showed
that spawning frequency was highest
(once every 1-2 days) from December
to March. Although spawning season
was more highly correlated to photo-
period (r = 0.859) than temperature
(r = -0.161), the daily proportion of
spawning fish was strongly correlated
(r=0.93) to ambient temperature over
the range 9-22°C. These results indi-
cate that short-term upwelling events,
a strong feature in the Tsitsikamma
National Park during summer, may
negatively affect carpenter fecundity.
Both spawning frequency and dura-
tion (i.e., length of spawning season)
increased with fish length. As a result
of the allometric relationship between
annual fecundity and fish mass a 3-kg
fish was calculated to produce fivefold
more eggs per kilogram of body weight
than a fish of 1 kg. In addition to pro-
ducing more eggs per unit of weight
each year, larger fish also produce
significantly larger eggs.
Manuscript submitted 22 September
2003 to the Scientific Editor's Office.
Manuscript approved for publication
30 August 2004 by the Scientific Editor.
Fish. Bull. 103:258-269 (2005).
Reproductive biology of carpenter seabream
(Argyrozona argyrozona) (Pisces: Sparidae)
in a marine protected area
Stephen L. Brouwer
Marc. H. Griffiths
Department of Marine and Coastal Management
Private Bag X2
Rogge Bay 8012, South Africa
E-mail (for S. L. Brouwer): sbrouwer'5'deat gov 23
The carpenter seabream (Argyrozona
argyrozona), known as "carpenter"
regionally, is an endemic South Afri-
can sparid found between St Helena
Bay and KwaZulu-Natal (Fig.l) (Smith
and Heemstra, 1986). Although the
third most important species in the
line-fishery in terms of landed mass,
catch per unit of effort (CPUE) on
traditional fishing grounds, declined
by 95% during the twentieth century
(Griffiths, 2000). Despite the impor-
tance of this resource, little research
attention has been given to this spe-
cies. The only previous study on the
reproductive biology of carpenter was
based on specimens collected towards
the western extreme of the distribu-
tion range (west of Cape Agulhas),
where most of the fish examined were
reproductively inactive (Nepgen, 1977).
As a result spawning seasonality was
not accurately delineated and sizes
at 50% maturity were not calculated.
Assuming carpenter to be determi-
nate spawners, Nepgen (1977) overes-
timated batch fecundity by counting
immature oocytes.
The objective of the present study
was to provide information on spawn-
ing seasonality, size at maturity, and
annual fecundity of carpenter in the
Tsitsikamma National Park (TNP),
a 75-km no-take marine protected
area (MPA) that has existed for 38
years (Fig. 1). It was envisaged that
in conjunction with other studies on
carpenter (Brouwer and Griffiths1)
in exploited areas this information
would assist in determining the af-
fects of fishing on the life history of
carpenter.
Materials and methods
Fish were caught from a research
vessel at depths between 20 and 90 m
by using handlines with baited hooks of
2/o-6/o in size. An attempt was made
to sample 60 fish per month between
March 1996 and June 1999, although
weather conditions did not always
allow this number. Sampling involved
measuring total and fork length (FL)
(mm), whole mass (g), gutted mass
(g), determining the sex of fish, and
removing the gonads. Gonads were
staged macroscopically according to a
seven-stage maturity index (Table 1)
and weighed to the nearest 0.1 g. The
whole gonads were preserved in 10%
neutrally buffered formalin or alter-
natively fixed in Bouin's solution for
48 hours and then stored in 60% etha-
nol. Preserved samples were processed
for histological analysis according to
the techniques described by Osborne
et al. (1999).
Length at maturity was modelled
by using a 2-parameter logistic ogive
of the form
Pi
1
1 + exp
-<L,-L,„)/a
where p, = the proportion of mature
fish in size class i, sam-
pled during the spawn-
ing season (November to
April);
1 Brouwer, S. L., and M. H. Griffiths. In
prep. Stock separation and life history
of Argyrozona argyrozona (Pisces: Spari-
dae) on the South African east coast.
Brouwer and Griffiths: Reproductive biology of Argyrozona argyrozona
259
WESTERN
CENTRAL
Figure 1
Map of the study area showing the position of the Agulhas Bank. Tsitsikamma National Park, 100- and
200-m isobaths and the places mentioned in the text.
Table 1
Classification and descriptions of macroscopic and microscopic ovary
^nd testis stages of carpenter {Argyrozona argyrozona)
sampled in the Tsitsikamma National Park.
Stage
Macroscopic
Microscopic
1 Juvenile female
Ovotestis appears as a thin transparent
Both ovarian and testicular tissues are present in
vessel.
equal proportions; however in the later stages ovar-
ian tissue becomes dominant.
1 Juvenile male
Ovotestis appears as a thin transparent
Both ovarian and testicular tissue present in equal
vessel.
proportions; however in the later stages ovarian
tissue becomes dominant.
2 Immature,
Translucent orange tubes, no eggs visible
Cells in the perinucleolus stage have a large nucleus
resting female
to naked eye.
containing 8-15 nucleoli located along the periphery
of the nucleus. There may be remnants of the testes
on the periphery of the ovary.
2 Immature,
Testes thin white and flaccid but larger
No sperm cells are noticeable and the seminiferous
resting male
than those in stage 1, no sperm in tissue.
tubules appear to be empty. Remnants of ovarian
tissue may be present in the centre of the testes.
3 Active female
Oocytes visible to naked eye as tiny gran-
Vitellogenesis begins in the oocytes, which become
ules in gelatinous orange matrix; little
more rounded and begin to accumulate yolk (yolk
increase in diameter of ovary.
vesicles). Yolk appears as a narrow ring of small yolk
vesicles in the periphery of the cytoplasm.
continued
260
Fishery Bulletin 103(2)
Lt = length of size class i;
L50 = the length at which 50% of the fish are sexu-
ally mature (stage 4+>; and
A = the width of the ogive.
The ogive was fitted by minimizing the negative log-like-
lihood. Differences in male and female L50 and a were
tested by using a ratio test that minimizes the binomial
log-likelihood of the form
:ln
Pi
I- Pi)
+ nt xlnd-p, ) + ln
where n = the number of samples in size class i\ and
mt = the number of mature fish in size class i.
Spawning frequency was estimated by using daily
proportions of ovaries containing early postovulatory
follicles (POFs), hereafter referred to as the spawn-
Table 1 (continued)
Stage
Macroscopic
Microscopic
3 Active male
4 Developing female
4 Developing male
5 Ripe female
5 Ripe male
6 Ripe, running female
6 Ripe, running male
7 Spent female
7 Spent male
Testes wider and triangular in cross
section.
Ovary larger and orange-yellow in color.
Eggs clearly discernible. Veins and arter-
ies large and plentiful.
Testes wider and deeper, creamy white in
colour, obvious presence of sperm in main
sperm duct.
Ovaries are large in diameter, may have
a few hydrated eggs. Yellow oocytes take
up all the space. Veins and arteries large
and plentiful.
Sperm present in main sperm duct and
in tissue. Gonad soft and breaks when
lightly pinched.
Ovary amber in colour. Large with sub-
stantial proportion of gonad with hy-
drated eggs, which fill the lumen. Veins
and arteries large and plentiful.
Free-flowing sperm extruded from fish
when the abdomen is lightly squeezed.
Testes very delicate and break easily when
handled. Copious amounts of sperm pres-
ent in main sperm duct and in tissue.
Ovary reduced in size similar to stage-2
flaccid ovary. Few yolked oocytes remain-
ing. Ovary bloodshot.
Testes white in color, smal
and bloodshot.
shrivelled.
The seminal vesicles expand and become filled with
spermatogonia.
Yolk vesicles are common and primary yolk oocytes
begin to appear, which are characterized by the for-
mation of small spherical yolk granules.
The seminiferous tubules of the testes are filled with
spermatozoa, which are also present in the primary
sperm duct.
Tertiary yolk oocytes, characteriszed by large yolk
plates, appear along with primary yolk and yolk
vesicles. The nucleus becomes irregular in shape and
smaller in size. The nucleus migrates to the animal
pole of the cell after which hydration begins, result-
ing in increased transparency of the cells and an
increase in cell size.
The seminiferous tubules expand with copious
amounts of spermatozoa that fill the lumen of the
primary sperm duct.
Filled with hydrated oocytes. Due to dehydration
during the histological preparation, these oocytes
appear as collapsed bags. Hydrated oocytes may
squash and reshape the immature oocytes that sur-
round them.
The seminiferous tubules of the testes appear dis-
tended and are filled with mature spermatozoa as is
the lumen of the primary sperm duct.
Cells in various stages of atresia, and some hydrated
and mature oocytes may be present in the tissue.
The seminiferous tubules are no longer distended
and have thicker walls than stage-6 tubules. They
contain few spermatozoa, which are present in the
lumen of the primary sperm duct. Large blood ves-
sels are apparent in the tissue.
Brouwer and Griffiths: Reproductive biology of Argyrozona argyrozona
261
ing fraction (Hunter and Macewicz, 1985). POFs were
aged by comparing them with known age POFs from
spawning females under captive conditions. Female
carpenter were held in a flow-through system at ambi-
ent sea temperature (mean 16C, range 9.5-20°C) in
5000-liter circular tanks, were stimulated to ovulate
with a commercially available GnRH-analogue (Davis,
1996). Three fish were sacrificed immediately after
ovulation and then three fish every six hours over the
following 48-hour period. Histological analysis of ova-
ries revealed three clearly defined POF stages (Fig. 2).
The proportions of wild-caught fish with stage-1 POFs
(the spawning fraction) were inverted to produce an
estimate of spawning frequency (Wilson and Nieland,
1994).
Batch fecundity was estimated from counts of hy-
drated oocytes from ovaries without POFs or atretic
oocytes (Hunter and Macewicz, 1985). A ±1.00-g section
was removed from the middle of the right ovary. This
was weighed to the nearest 0.01 g and the hydrated oo-
cytes were separated according to the method described
by Lowerre-Barbieri and Barbieri (1993). Hydrated
oocytes were suspended in water and counted at 8-10
times magnification in a Bokkeroff tray and measured
to 0.1 mm with an ocular micrometer along the longest
diameter.
Annual fecundity was calculated as follows:
Aft
xfbt,
where Aft = the annual fecundity for fish t;
Is = the length of the spawning season (days)
for fish of size class j;
sf = the spawning frequency (days) for fish of
size class j (all months combined); and
fbt = the batch fecundity of fish t.
Spawning season was established by calculating the
monthly proportions of macroscopic gonad stages and
mean monthly gonodosomatic index (GSI) for fish larger
than L50:
GSI-
xlOO,
where m = the gonad mass (g); and
ms = the somatic mass (g) (minus gonad and
stomach mass).
In order to investigate the relationship between
spawning and temperature, temperature data were
collected at the sampling site with a Seamon Mini (Hu-
grun, Iceland) recorder stationed at at a depth of 35 m
on the reef from which the biological samples were col-
lected. A thermistor array consisting of four underwater
temperature recorders (UTRs) at depths of 12 m, 19 m,
27 m, and 35 m recorded the temperature every minute
Figure 2
Postovulatory follicle (POF) stages deter-
mined from carpenter [Argyrozona argyro-
zona) chemically induced to spawn in an open
circulating system housed at the Tsitsikamma
National Park. (A) = stage 1 (0-6 hours),
( B ) = stage 2(7-24) hours and ( C I = stage 3
125-48) hours.
262
Fishery Bulletin 103(2)
and stored an hourly average (Roberts-). Photoperiod
data were downloaded from the South African Astro-
nomical Observatory database.3 Pearson Rank correla-
tion was used to measure the correlation between GSI
and temperature, and GSI and photoperiod trends.
Results
Histological examination of the gonads revealed that
although juveniles possess both testicular and ovarian
tissue simultaneously (i.e., as hermaphrodites) they
mature as either a male or female (Table 1) and are
therefore late gonochorists (rudimentary hermaphro-
dites). Gametogenesis was similar to that described for
other late gonochoristic sparids e.g., Pterogymnus lania-
rius (Booth and Hecht, 1997). The size at 50% maturity
was estimated at 292 and 297 mm FL for females and
males, respectively (Fig. 3), and in both cases is equiva-
lent to an age of about five years (Brouwer and Griffiths
2004). A likelihood ratio test revealed that there was
no significant difference between male and female L50
(P>0.5)or or (P>0.1). Complete ( 100% ) maturity for both
sexes occurred at 480 mm FL, an age of about 15 years
(Brouwer and Griffiths 2004). The sex ratio was 1F:1.3M
(n=1776); a chi-square test with Yates' correction factor
revealed that this sex ratio was a significant difference
from unity (P<0.01).
Three age-related POF stages were identified within
the ovaries of captive spawned carpenter (Fig. 2). Stage-
1 POFs (0-6 hours) were very loosely arranged and ap-
peared as a long convoluted string with a large clearly
defined lumen. The granulosa cells were clearly visible
and widely spaced and had clearly visible nuclei (Melo,
1994). Stage-2 POFs (7-24 hours) are smaller and more
densely packed but still have a visible lumen. The gran-
ulosa cells are closely packed and dense. Stage-3 POFs
(25-48 hours) are small and densely packed. There is
no lumen and the granulosa cells are closely arranged
and no longer distinguishable from one another. After
48 hours at 16°C, POFs were no longer detectable.
Mean GSI and the proportions of ripe (stage-5) and
ripe, running (stage-6) fish increased in November and
remained high until April (Figs. 4 and 5), indicating
that carpenter are summer spawners. The presence of
early POFs from November to March (sample numbers
being too low for April) supported the macroscopically
determined spawning season. The monthly spawning
fraction did, however, reveal that spawning frequency
was highest in January and February when the fish
spawned at two-day intervals and lowest in November
and April when they were found to spawn every 2-3
days (Table 2).
o
1B0 230 280 330 380 430 480 530 580
1 ■
Female
0 9 ■
n=778
L50=292
•
0 8 ■
• /
■
•
07 -
0.6 '
•
05 ■
•
04 ■
03 ■
02 ■
0 1 ■
n ■
— • — • — •— i-
130 180 230 280 330 380 430 480 530 580
Fork length (mm)
Figure 3
The proportion of mature carpenter (Argyrozona argy-
rozona) in length classes sampled in the Tsitsikamma
National Park. The curves were fitted with a 2-parameter
logistic ogive.
2 Roberts, M. J. 1999. CD-ROM, Tsitsikamma National Park
oceanographic data, version 1.0. Marine and coastal man-
agement. Private Bag X2, Rogge Bay 8012, South Africa.
:l http://www.saao.ac.za [Accessed August 2000],
Batch fecundity was positively correlated with both
fish mass (r=0.71) and fork length (r=0.71). No correla-
tion was found between fish length and relative batch
fecundity (eggs/fish somatic mass) (Fig. 6). The propor-
tion of fish with stage-1 POFs revealed that spawning
frequency and length of the spawning season increased
with fish length (Table 3). Accounting for size-related
patterns in spawning season (Fig. 7) and frequency, we
found that annual fecundity increased allometrically
with mass (Fig. 8) and age (Table 4). Hydrated egg size
was significantly smaller and more variable (average 1.0
mm ±0.16) in fish below the length at 100% maturity
(480 mm FL) than those above this length (1.1 mm
±0.09) U-test, P<0.005).
Brouwer and Griffiths: Reproductive biology of Argyrozona argyrozona
263
100
90
80
70
60
50
40
30
20
10
0
100
90
80
70
60
50
40
30
20
10
0
Male
m m m
Saj
1
ABS
12 3 4 5
9 10
11 12
12 3 4 5
6 7
Months
10 11 12
n=998
□ 1
□ 3
□ 4
Female
n=778
pri f
"H F
E
f I
D1
3
- 1
3 2
s
□
— :
: h
j
III
D3
□ 4
mm
^ i
s
: :
si
ni e
Mr
Figure 4
Monthly variation in the proportion of macroscopic gonad stages of carpenter
{Argyrozona argyrozona) >L50 caught in the Tsitsikamma National Park (March 1996-July
1999). Numbers in the legend refer to the gonad stages in Table 1. 1 = juvenile, 2 =
immature. 3 = active, 4 = developing, 5 = ripe. 6 = ripe, running, and 7 = spent.
Table 2
Spawning frequency determined for carpenter
cally determined from hydrated oocytes.
(A.
argyrozona)
from
the proportion of ovaries with stage
-1 POFs or macroscopi-
Month
Spawning frequency (days)
% ovaries with
hydrated oocytes
% ovaries with
stage-1 POFs
Macroscopic
POFs
November
2.1(441
4.6(23)
48
22
December
1.9(53)
3.5(21)
53
28
January
1.5(119)
1.6(5)
66
60
February
1.5(160)
1.5(35)
68
66
March
1.6(99)
—
64
Not enough data
April
2.6(49)
—
39
Not enough data
A positive relationship between temperature at the
time of spawning (back-calculated from stage-1 POFs,
assuming a delay of 6 hours) and the proportion of ova-
ries with stage-1 POFs indicated that spawning events
were positively correlated with temperature (r=0.93)
over the range 9°C and 22°C (Fig. 9). GSI was how-
264
Fishery Bulletin 103(2)
Male
1
. ;;
0
1
•
i 1
",T
T.
— — 1 1 1 1 1 1
CO
o
6
5
4
3 +
2
1
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Female
i f
— i 1 — i 1 1 1 — i 1 1 1 — i 1
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Month
Figure 5
Seasonal variation of the standard deviation in the gonadosomatic index (GSI)
and mean values (•) for male and female carpenter (Argyrozona argyrozona)
sampled in the Tsitsikamma National Park.
ever strongly correlated (/-=0.86) with photoperiod but
exhibited a weak negatively relationship with seasonal
temperature (Fig. 10).
Discussion
Late gonochorism, protandry, protogyny, and hermaphro-
ditism are the recognized reproductive styles of sparids
(Smale, 1988; Buxton and Garratt, 1990). Although
carpenter were previously described as gonochoristic
(Nepgen, 1977), microscopic examination of the gonads
revealed that they are late gonochorists. The sex ratio
calculated during this study (1 female:1.3 male) was
typical for those observed for other late gonochorists
(Griffiths et al., 2002).
Upon reviewing 90 species of reef fish, Sadovy (1996)
concluded that although GSIs reflect the gonad maturity
patterns for a species, they are poor indicators of peak
spawning times. By way of example, in red hind grouper
(Epmephelis guttatus) yolked oocytes are present in the
ovaries for four months of the year but actual spawning
Table 3
Spawning frequency (averaged over all months) and
length of the spawning season calculated from the pres-
ence of stage-1 POFs in carpenter (Argyrozona argyro-
zona) ovaries in three size classes.
Size class
(mml
Average
spawning frequency
( days )
Spawning
season
(months)
250-339
340-479
480+
9
4
3.9
is limited to a period of 10 days (Sadovy, 1996). In the
case of carpenter, however, the presence of POFs from
November to April supports the six-month spawning
season indicated by macroscopic methods (although
in some larger individuals [>480 mm FL] hydrated
Brouwer and Griffiths: Reproductive biology of Argyrozona argyrozona
265
180000
160000
"> 140000
Ol
Ol
* 120000
"o
^ 100000
a>
£ 80000 ■
Z 60000
40000
20000
0
1
= 360. 22x- 9741
r* = 0 5046
•
•
•
• ^^
• •
o
*%J
o
•
o
•
©Numbefoleggs n = 51
ODavis (1997) n = 10
250
450 550
Fork length (mm)
1250 1750 2250 2750
Gonad free mass (g)
3000 ■
•
•
2500 •
•
in
>, jo
•
•
S fc
2000 •
•
c >■
3 3
3 o
1500 ■
•
•
I.-
•
£ o>
to x
0) Ol
C£ Ol
en
1000 -
• • " •
ft
•
•
•
•
ai
500 "
•
•
250 350 450 550 650
Fork length (mm)
Figure 6
The relationships for carpenter (Argyrozona argyrozona) between (A)
fish length and batch fecundity including data from fish spawned
artificially in a previous study (Davis, 1996 I. (B) fish mass and
batch fecundity and (C) fish length and relative batch fecundity.
oocytes and POFs were found from October to May).
Monthly spawning fraction and percentage of ovaries
with hydrated oocytes nevertheless reached a peak dur-
ing January and February (Table 2); these trends were
not detected in the monthly GSIs. But given that the
macroscopic determinations of stage followed trends in
the proportions of POFs that were present, we conclude
that expensive and time-consuming histological analy-
sis is not necessary for determining spawning peaks
for this species.
266
Fishery Bulletin 103(2)
7 -
250-339 mm FL
II
6 ■
n=179
1 s
1
5 -
"1
3
2
1 i
o -
1
i!
• •
:
•
' 1 1 • •
i!
•
1 1 •
I
»
2
2 3
4 5 6 7 8
9 10 11 1
7 -
6 -
■I
2i
•
I
1
340-479 mm FL
n=421
•
•
|
•
• •
5 i
1 <
•
9
1 1 | • 1
1 1 •
1
2 3
4 5 6 7 8
9 10 11 12
7 -
480+ mm FL
6 -
n=67
1
5 -
4I
3 1
* •
1 : .
i :
* •
• •
•
1
•
2 -
1 -
0 -
1
1
•
•
. • * *
1 1 1
•
1 1 *
2
2 3
4 5 6 7 8
9 10 11 1
Months
Figure 7
Seasc
nal variation in the gonadosomati(
index (GSI) fo
r
femal
e carpenter (Argyrozona argyrozona
) from three size
classt
s samplec
in the Tsitsikamma National Park.
Apart from being indicators of spawning seasonality,
GSI trends can provide insight into the mating patterns
of a species (Sadovy, 1996). Pair-spawning sparids such
as Chrysoblephus laticeps have low male GSI (±10% of
female) during the spawning season (Buxton, 1990).
Although the spawning behavior of carpenter has not
been documented, the GSI of males (average 3.0 ±1.4)
was similar to that of females (average 3.3 ±1.4) dur-
ing the spawning season (Fig. 4). The large testes size
suggests that carpenter are group spawners and that
sperm competition is high (Sadovy, 1996). Further evi-
dence for group spawning is the lack of sexual dimor-
phism in this species (Smale, 1988; Mann and Buxton,
1998; Griffiths et al., 2002).
Like many other South African sparids, carpenter are
summer spawners (Buxton and Clarke, 1986; Buxton
and Clarke, 1991; Buxton, 1993). Although various en-
vironmental cues have been suggested for this seasonal
spawning, it is probably a combination of events that
leads to gonad maturation and spawning. Smale (1988)
and Garratt (1985) speculated that increases in gonad
activity of Petrus rupestris and Chrysoblephus puniceus
were attributed to an increase in photoperiod and water
temperature respectively; Scott and Pankhurst (1992),
Brouwer and Griffiths: Reproductive biology of Argyrozona argyrozona
267
16 -
14 -
| 12-
I 10 -
g 8 ■
ai
y = 5E-06x
r1 = 0.966
# • • •*
n = 50
• /
•^ *
•
° 6 1
n
E 4 ■
2 •
jS»
j4*
^■»
0 1000 2000
3000
Mass (g)
Figure 8
The relationship between annual fecundity and fish weight
for carpenter (Argyrozona argyrozona} in the
Tsitsikamma
National Park.
however, showed that seasonal temperature regulated
gonad development for Pagrus aratus. Based on the data
collected during our study, photoperiod appears to be
responsible for the onset of gonad maturation in carpen-
ter; when day length increases (but water temperature
is variable) in September and October, and their gonads
begin to develop (Fig. 10). Photoperiod was also highly
correlated with GSI (r = 0.86), whereas temperature
showed a weakly negative relationship (r=-0.16).
Nepgen (1977) calculated spawning frequency for
this species with an oocyte-size-frequency analysis of
inactive females. Finding only one peak in the oocyte-
size-frequency distribution, he assumed that carpen-
ter spawned only once a year. In our study POFs and
various yolk stage oocytes were found to occur simul-
taneously, proving that carpenter are serial spawners.
Accounting for monthly trends in spawning frequency
and the length of the spawning season, carpenter in
the Tsitsikamma National Park are estimated to spawn
at least 30 times per year. This spawning frequency is
similar to other predatory reef fishes, e.g., Mycteroperca
microlepis (30-40 times per year) (Collins et al., 1998).
Nevertheless, as with other species (Danilowicz, 1995),
spawning fraction in carpenter during the spawning
season was highly correlated with water temperature
(r=0.931) (Fig. 9), indicating that short-term cold water
upwellings, a common feature of the TNP during sum-
mer (Schumann et al., 1982), may negatively impact
annual carpenter fecundity in this area.
Although fecundity in fishes is highly variable be-
tween individuals (Sadovy 1996), absolute fecundity
increases with size (Hunter et al., 1985; Davis and
West, 1993; Wilson and Nieland, 1994; Collins et al.,
1998). In our study absolute annual fecundity increased
markedly with fish size (Table 4) and spawning season
was longer for large fish (Fig. 7) (Table 3). The positive
Table 4
Age-based
annual fecundity of carpenter (Argyrozona
argyrozona
) in the Tsitsikamma
National Park.
Age (yr)
Number of eggs (millions I
1
0
2
0
3
0
4
0.143
5
0.288
6
0.367
7
0.441
8
0.870
9
1.014
10
1.228
11
1.498
12
1.706
13
1.763
14
2.260
15
2.233
16
2.427
17
3.132
18
3.175
19
5.363
20
6.308
21
6.308
22
7.815
23
7.430
24
6.480
25
7.421
26
8.363
27
8.363
28
8.064
29
10.397
30
11.808
correlation of batch fecundity and fish size (r=0.71),
coupled with the increased length of the spawning sea-
son for the older fish, greatly increases the absolute
annual fecundity of larger fishes (Fig. 8). Sadovy (1996)
noted that for red snapper (Lutjanus compechatius) one
large female (601 mm FL) will produce as many eggs
as 212 small (420 mm FL) females. Similarly, one large
female carpenter of 3.3 kg will produce as many eggs as
72 small ones of 0.3 kg. In addition to higher fecundity,
the larger fish produce significantly larger eggs and
presumably more viable larvae (Ojanguren et al., 1996;
Pepin and Anderson, 1997).
Exploited populations were traditionally managed
to maximize growth (Griffiths, 1997). However it is
imperative to maintain sufficient numbers of reproduc-
268
Fishery Bulletin 103(2)
tive adults to ensure egg production and avoid recruit-
ment failure. To address proper management of line-
caught fish in South Africa, spawner biomass per re-
cruit models have been used (Griffiths, 1997). One as-
sumption of this approach is that fecundity is linearly
related to spawning biomass, regardless of individual
size (Buxton, 1992). Because our study has shown
that fecundity in carpenter is allometrically related to
individual mass, egg-per-recruit models would be
more appropriate for future stock assessment of this
species.
Acknowledgments
We thank the staff at South African National Parks,
for accommodation at the Tsitsikamma National Park
and for use of their vessel. John Allen and Karoels
Piterse are thanked for many hours at sea. Yolande
Melo is thanked for her assistance with histological
preparation and interpretation and Jeanine Van der
Pol for assistance in laboratory and Tony Booth and two
anonymous referees for constructive comments on this
manuscript. This research was funded by the Marine
Living Resources Fund.
100 ■
90 ■
y = 3.2928X- 6.5009
80 ■
r* = 0.8672
70 ■
en
.£ 60 ■
c
1 50 •
Q.
"1 40-
6
5 6 6
• •*-*
20 ^-^^^ 2*8
30 ■
•^^^-"^23
20 ■
^ •
10 ■
8 10 12 14 16 18 20 22 24
Temperature
Figure 9
The relationship between proportion of carpenter (Argyrozona
argyrozona) spawning (back calculated from stage-1 POFs, 0-6
hours 1 and temperature in the Tsitsikamma National Park. Num-
bers above symbols refer to number offish sampled with POFs.
20 -I
- 15:24
A A
.A
18 ■
°v .' '.
▲'
■ 14:12
O
~Z 16 ■
=3
CD
Q. 14 -
1
12 -
A
"-A, / \-*
A"
- 13 00 g
o
■ 11 48 m
5"
■ 10:36 S
o
■ 9 24 |
■ 8:12
- - - A- - - Temperature
- 7:00
1
'
January
February
March
April
May
S June
o
1 July
August
September
CD
O
O
November
December
Figure 10
Monthly average temperature and photop
eriod for the Tsitsi-
kamma National Park.
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270
Abstract— During the 1990s, sea otter
i En hydra lutris) counts in the Aleu-
tian archipelago decreased by 70%
throughout the archipelago between
1992 and 2000. Recent aerial surveys
in the Aleutians did not identify the
eastward extent of the decline; there-
fore we conducted an aerial survey
along the Alaska Peninsula for com-
parison with baseline information.
Since 1986, abundance estimates
in offshore habitat have declined
by 27-49% and 93-94% in north-
ern and southern Alaska Peninsula
study areas, respectively. During this
same time period, sea otter density
has declined by 63% along the island
coastlines within the south Alaska
Peninsula study area. Between 1989
and 2001, sea otter density along the
southern coastline of the Alaska Pen-
insula declined by 35% to the west of
Castle Cape but density increased by
4% to the east, which may indicate an
eastward extent of the decline. In all
study areas, sea otters were primar-
ily concentrated in bays and lagoon,
whereas historically, large rafts of
otters had been distributed offshore.
The population declines observed
along the Alaska Peninsula occurred
at roughly the same time as declines
in the Aleutian islands to the east
and the Kodiak archipelago to the
west. Since the mid-1980s, the sea
otter population throughout south-
west Alaska has declined overall by
an estimated 56-68%, and the decline
may be one of the most significant
sea otter conservation issues in our
time.
Decline in sea otter (Enhydra lutris) populations
along the Alaska Peninsula, 1986-2001
Douglas M. Burn
Angela M. Doroff
Marine Mammals Management Office
U.S. Fish and Wildlife Service
10H East Tudor Road
Anchorage, Alaska 99503
E-mail address (for D M Burn): douglas_burnifi'fws gov
Manuscript submitted 2 September
2003 to the Scientific Editor's Office.
Manuscript approved for publication
30 August 2004 by the Scientific Editor.
Fish. Bull. 103:270-279 (2005).
During the 1990s, the sea otter
(Enhydra lutris) population in the
Aleutian archipelago declined at a
rate of 17.5%/yr and, overall, counts
decreased by 70% throughout the
archipelago between 1992 and 2000
(Doroff et al., 2003). By modeling
population trends back to the mid-
1980s, Burn et al. (2003) estimated
the population in the Aleutian Island
chain decreased by 65,000 sea otters
and was at about 10% of its carry-
ing capacity in 2000. The 2000 aerial
survey of Doroff et al. (2003) did not
identify an eastward extent of the
population decline however; therefore
additional sea otter surveys along the
Alaska Peninsula were needed.
Historic information on population
status and trends is sparse for sea
otters along the Alaska Peninsula.
Sea otters were exploited to near ex-
tinction in the commercial fur trades
(1742-1911) and were removed from
large portions of their historic range
worldwide (Kenyon, 1969; Lensink,
1962). At the time of their protec-
tion in 1911 by an international fur
seal treaty, there were 13 remnant
populations remaining worldwide, 11
of which persisted and grew to re-
colonize much of the former range of
this species (Kenyon, 1969). Studies
of both remnant native and translo-
cated sea otter populations have in-
dicated a pattern of colonization with
high population growth rates up to
20% per year, and an expansion into
adjacent, unoccupied habitat (Estes,
1990).
One remnant population survived
on the north side of the Alaska Pen-
insula near Unimak Island (Kenyon,
1969; Schneider, 1976). Sea otter
habitat in this area is unique in that
shallow water (less than 100 m) ex-
tends up to 50 km offshore, covering
more than 10,000 km of open water.
The remnant population in this ar-
ea likely numbered fewer than 100
sea otters in 1911 (Kenyon, 1969).
This population grew steadily and
expanded its range to the northeast
along the Peninsula until 1970, when
extreme sea ice conditions temporar-
ily reduced the range and likely the
size of the population (Schneider and
Faro, 1975). By 1976, most of the sea
otters in this area were concentrated
between Cape Mordvinof and Cape
Leontovich (Schneider, 1976).
In addition to the remnant popu-
lation on the north side of Unimak
Island, there were also two remnant
populations of sea otters located to
the south of the Alaska Peninsula
in the Sandman Reefs and the outer
Shumagin Islands (Kenyon, 1969).
Sea otter habitat along the southern
Alaska Peninsula differs from the
northern side and comprises primar-
ily rocky, mixed substrate, and ex-
tensive offshore reefs (Brueggeman et
al.1). In the Sandman Reefs a small
number of sea otters were sighted in
1 Brueggeman, J. J., G. A. Green, R. A.
Grotefendt, and D. G. Chapman.
1988. Aerial surveys of sea otters in
the northwestern Gulf of Alaska and
the southeastern Bering Sea. Minerals
Management Service and NOAA final
report, 87 p. Minerals Management
Service, Anchorage, AK. [Contract no.
85-ABCV-00093.]
Burn and Doroff: Decline of Enhydra lutns along the Alaska Peninsula
271
1922, and by 1962 the population had grown to an es-
timated 1625 sea otters (Lensink, 1962; Kenyon, 1969).
Around the same time, the population in the Shumagin
Islands was estimated to be 2724 sea otters (Kenyon,
1969).
The first systematic surveys of sea otter abundance
along the north side of the Alaska Peninsula were con-
ducted in the mid-1970s (Schneider, 1976), followed by
surveys in 1982 and 1983 by Cimberg et al.2 Bruegge-
man et al.1 conducted quarterly surveys of both the
northern and southern Peninsula in 1986 to assess
sea otter abundance and seasonal distribution. The
surveys conducted in 1986 provided seasonal estimates
of abundance during a single, ice-free year, and a clear
picture of habitat use in the mid-1980s along the Alaska
Peninsula (Brueggeman et al.1).
The sea otter surveys described above were concen-
trated along the western end of the Alaska Peninsula
where remnant populations existed and appeared to
have recovered. By the late 1980s, sea otters had also
returned to the nearshore waters of the entire penin-
sula as far east as Cape Douglas (DeGange et al.3).
Prior to this survey in 1989, little was known about
sea otter distribution and abundance on the Alaska
Peninsula east of Kupreanof Point.
The objectives of our study were 1) to assess current
sea otter distribution and abundance along the north-
ern and southern Alaska Peninsula, 2) to contrast our
results with prior surveys conducted in 1986 and 1989,
and 3) to relate these data to the observed sea otter
population declines observed elsewhere in southwest
Alaska. We repeated the aerial survey methods devel-
oped by Brueggeman et al.1 for sea otter habitat along
the Alaska Peninsula which consisted of a combination
of strip transects in offshore habitat (to the 70-m iso-
bath) and coastline surveys (si km of shore) of island
groups within the study area. We also repeated the
coastline surveys of DeGange et al.2 to determine the
eastward extent of the decline.
Materials and methods
Offshore survey areas
The north Alaska Peninsula (NAP) study area ranged
from Cape Mordvinof on Unimak Island in the west to
Cape Seniavin in the east. This area was further subdi-
2 Cimberg, R. L., D. P. Costa, and P. A. Fishman. 1984. Eco-
logical characterization of shallow subtidal habitats in the
north Aleutian Shelf. OCSEAP Final Rep. no. 4197, 99 p.
U.S. Dept. of Commerce, National Oceanographic and Atmo-
spheric Administration, Anchorage, Alaska 99501.
3 DeGange, A. R., D. C. Douglas, D. H. Monson and C. M.
Robbins. 1994. Surveys of sea otters in the Gulf of Alaska
in response to the Exxon Valdez oil spill. Final report to
the Exxon Valdez Oil Spill Trustee Council, Marine Mammal
Study 6-7, 11 p. U.S. Fish and Wildlife Service, Anchorage,
Alaska 99503.
vided into two subunits (NAPa and NAPb), and a line at
162°W longitude divided the two subunits (Brueggeman
et al.1). The south Alaska Peninsula (SAP) study area
ranged from the Ikatan Peninsula in the west to the
Shumagin Islands in the east. The seaward extent of
both the NAP and SAP study areas was the approximate
70-m depth contour (Fig. 1A).
The strip transect method developed by Brueggeman
et al.1 consisted of a series of transects oriented north-
south which were spaced every three minutes of longi-
tude throughout the study area. In 1986, surveys were
flown in a DeHavilland Twin Otter aircraft equipped
with bubble windows at an altitude of 92 m and an
airspeed of 185 km/h. Two observers, one on each side
of the aircraft, relayed sea otter sighting information to
a data recorder seated in the aft section of the aircraft.
Sea otter sightings were grouped into three distance
intervals spaced at right angles to the transect line:
0.0-0.23 km, 0.23-0.46 km, and 0.46-0.93 km. These
distance zones were determined by using a clinometer
to place marks on the inside of the bubble windows.
Environmental information on sea state, visibility, and
glare was recorded throughout the survey.
In May 2000 and April 2001, we repeated the survey
conducted by Brueggeman et al.1 using similar meth-
ods, with the exception that our survey aircraft was
an Aero Commander equipped with bubble windows
and we grouped sea otter sightings into five distance
intervals: 0.0-0.115 km, 0.115-0.23 km, 0.23-0.345 km,
0.345-0.46 km, and 0.46-0.575 km.
Coastline survey areas
In 1986, Brueggeman et al.1 also surveyed the coastlines
of 22 islands on the south side of the Alaska Peninsula
quarterly at a distance of 0.46 km from shore, using
the same aircraft, altitude, and airspeed as in the off-
shore area surveys (Fig. IB). In 1989, DeGange et al.2
surveyed the coastlines of these same islands and the
Alaska Peninsula from False Pass to Cape Douglas
(Fig. 1C). The 1989 survey was conducted from Bell
206 and Hughes 500 helicopters at a distance of 0.2
km from shore at an altitude of 92 m and an airspeed
of 130 km/h. We used similar methods (0.23 km from
shore, altitude 92 m, airspeed 185 km/h) to survey the
coastlines of these 22 islands and the Alaska Peninsula
in April and May 2001. The area of the offshore surveys
was adjacent to, but did not overlap, the area of the
coastline surveys. Coastline surveys were not conducted
in the NAP study area.
Offshore survey analyses
Prior to the analysis of the 2000-01 offshore survey data,
we tested several assumptions made in the 1986 analysis
regarding the detectability of sea otters as a function
of 1) survey strip width, 2) survey conditions, and 3)
time of day. We examined the distribution of sea otter
sightings by distance zone using a chi-square analysis
to determine the appropriate survey strip width to use
272
Fishery Bulletin 103(2)
_Ukolnoi wosnesensk. (^opoP
Korovm
^ Andronica
Spectacle
UiLBig Koniuji
-&endfi?-l"lfi KQn'"JI
TiJrner *-/V. o
£? Simeonof
Bird*** £jChernabura
-Sanak/
A
0 25 50 100
I I I I I I I I I
Kilometers
Figure 1
Sea otter {Enhydra lutris) survey areas along the Alaska Peninsula. (Al
Offshore areas. (Bl South Alaska Peninsula Islands. (C) Alaska Peninsula
coastline. Surveyed areas in (B) and (C) include a 0.46-km zone adjacent
to shore.
for estimating abundance. We calculated an
encounter rate as the number of sea otter
groups per km of survey effort and used
this rate to examine the effects of time of
day and environmental conditions (wave
height, and visibility) on detectability of
sea otters.
At the time of the surveys in 1986, re-
searchers had documented a core resting
period for sea otters which occurs about
mid-day (Garshelis and Garshelis, 1984;
Estes, 1977). As a result, Brueggeman et
al.1 subset the 1986 data using only effort
and observations recorded between 0830
and 1430 hours local sun time for their
abundance estimates. Recent studies in-
dicate activity patterns for sea otters are
strongly linked to sex, age, weather condi-
tion, season, and time of day (Gelatt et al.,
2002). We tested the assumption that sea
otters were more visible during the core
resting period using a /-test of the encoun-
ter rate for each transect during presumed
rest and nonrest periods for the 1986 and
the 2000-01 data.
We measured the area of the NAP and
SAP study areas using a geographic infor-
mation system (Arc/Info). Our measure-
ments differed from those of Brueggeman
et al.,1 presumably because the original
researchers had not used an equal-area
map projection in their calculations. Like
Brueggeman et al.,1 we estimated abun-
dance of sea otters in the Alaska Peninsula
offshore areas using the modified ratio of
means estimator (method I) of Estes and
Gilbert (1978). Noting computational er-
rors in the original analysis, we recalcu-
lated abundance estimates from the origi-
nal 1986 data of Brueggeman et al.1 The
proportion of sea otters within the survey
swath that went undetected by observers
was not estimated in either our survey or
the surveys of Brueggeman et al.1; there-
fore all abundance estimates were biased
low to an unknown degree. We computed
the proportional change in abundance be-
tween survey periods ((Nt2—Nn)INn) as a
range, using the minimum and maximum
estimates from 1986 as a baseline and
assuming no significant difference in the
proportion of sea otters detected between
surveys.
Coastline survey analyses
We calculated the area surveyed as the
product of the coastline length and the
survey strip width and calculated the den-
sity of sea otters per km2 surveyed. Once
Burn and Doroff: Decline of Enhydra lutris along the Alaska Peninsula
273
again assuming no significant difference
in the proportion of sea otters detected
between surveys, we computed the propor-
tional change in density between survey
periods UD,,-Dn)/Dn) of sea otter den-
sity at each island within the study area
between 2001 and 1986 (Brueggeman et
al.1) and each Alaska Peninsula coastline
segment between 2001 and 1989 (DeGange
et al.2).
Results
Offshore surveys
In 1986, Brueggeman et al.1 flew four sur-
veys and an average of 3676 km of transect
effort per survey. The majority (599? ) of the
1986 survey effort was conducted in Beau-
fort sea state 2 (wind less than 7.4-11.1
km/h, no whitecaps) or less; and 95% of the
survey effort was conducted with visibility
categorized as good or better. In May 2000
and April 2001, we flew 6334 km of tran-
sects and 56% of our effort was conducted
in Beaufort sea state 2 or less; 97% of our
effort was conducted in visibility catego-
rized as good or better.
In 1986, sea otter detection probability
was not uniform between sighting zones
(X2 = 1796, df=2, P<0.0001) and substan-
tially more sea otters were observed than
expected in the 0.0-0.23 km distance zone
(Fig. 2A). As a result, Brueggeman et al.
(1988) used only this zone in their cal-
culation of sea otter abundance. In our
2000-01 surveys, sea otter detection prob-
ability was also not uniform <x2=217, df=5,
P<0.0001i. The observed frequency of sea
otter sightings exceeded the expected val-
ue in our second (0.115-0.230 km) and
third zones (0.230-0.345 km) but in the
first zone (0.0-0.115 km) we recorded on-
ly half as many sea otter sightings as in
the second zone (Fig. 2B). Therefore, only
sightings from the second and third zones
were used in our calculation of sea otter abundance.
As a result, the overall width of the survey strip was
the same for the 1986 and the 2000-01 surveys (0.46
km), but our strip was offset by 0.115 km from the
trackline. The proportion of all sea otter sightings was
similar between the usable zones in 1986 (62.8%) and
2000-01 (62.4%).
Sea otter encounter rate (otter groups/km) decreased
as wave height increased and visibility conditions be-
came worse in both the 1986 and 2000-01 surveys. As
noted by Kenyon (1969), wave height has a profound
influence on the ability of observers to detect sea ot-
ters. Prior to calculating abundance estimates for both
BO -
A
V777i Zone(s) used in abundance estimation
/U -
2,619
60 -
50 -
jfj
40 -
30 -
1,117
20 -
'///
435
10 -
0 -
y///,
000
0.23
0 46
093
4U -
B
35 -
158
'//////
30 -
HP
128
25 -
20 -
80
58
15 -
10 -
34
5 -
0 -
W///
0.00 012 0.23 035 0 46 0.58
Distance from trackline (km)
0.93
Figure 2
Distribution of sea otter (Enhydra lutris) sightings in offshore areas
grouped according to perpendicular distance from the survey track-
line. (A) 1986 data from Brueggeman et al.1 (Bl 2000-01 data from
this study. Values above bars represent total number of sightings in
each zone.
1986 and 2001, we subset both data sets to include
only those transects where Beaufort sea state was s2
and visibility was categorized as good or excellent for
counting sea otters. This procedure reduced the 1986
usable survey effort by 42%, and the 2000-01 survey
efforts by 44%.
Sea otter encounter rates did not differ significant-
ly between rest and nonrest periods in the 1986 data
(£=1.63, df=79, P<0.1064). Likewise, there was no differ-
ence in encounter rates for rest and nonrest periods in
2000-01 (*=-0.79, df=71.6, P<0.4327). As a result, we
did not exclude any survey effort and sea otter sightings
based on time of day.
274
Fishery Bulletin 103(2)
Table 1
Sea otter {Enhydra lutris) population estimates for Alaska Pen
nsula offshore study
areas. Study areas
north Alaska Peninsula
a [NAP
a] = 6257 km2; and b [NAPb] =
= 5531 km2; sol
th Alaska Peninsula
lSAP] = 9469km2.
Total
Area
Number
Density
Mean
95%
Survey
Survey
number of
sampled
of otter
(groups/
Group
group
Estimated
confidence
area
date
transects
(km2)
groups
km2)
abundance
size
abundance
interval
NAPa
March 1986
35
446.2
243
0.545
3408
2.082
7096
±2558
Late June- early July 1986
39
398.8
124
0.311
1945
2.177
4236
±1818
August 1986
31
421.7
225
0.534
3338
2.169
7240
±2978
October 1986
36
511.6
274
0.536
3351
1.982
6642
±2050
May 2000
40
552.3
18
0.033
204
1.833
374
±318
NAPb
Late June-early July 1986
29
469.5
98
0.209
1155
1.939
2238
±840
August 1986
6
120.4
23
0.191
1056
1.870
1975
±2212
October 1986
14
314.3
42
0.134
739
1.214
897
±467
May 2000
40
443.3
184
0.415
2296
1.897
4354
±3007
SAP
March 1986
26
358.3
254
0.709
6712
2.071
13,900
±6456
Late June- early July 1986
33
424.8
227
0.534
5060
2.775
14,042
±5178
October 1986
33
442.6
418
0.944
8943
1.957
17,500
±5768
April 2001
38
631.2
22
0.035
330
3.045
1005
±1597
The estimated abundance of sea otters decreased by
91-94% in the NAPa study area, which ranged from
4236-7240 in 1986 to 374 in 2000 (Table 1). Estimated
abundance increased by 95-385% in the NAPb study
area, which ranged from 897 to 2238 in 1986 to 4354 in
2001. Overall, abundance estimates in the NAP study
area declined by 27-49% between 1986 and 2000. With-
in the NAP area, sea otters were distributed primar-
ily near the coast rather than further offshore as was
observed in 1986 (Fig. 3). In May 2000, the majority
of sightings occurred in the Port Moller and Nelson
Lagoon areas, which had contained few otters during
the 1986 surveys. Estimated abundance within the SAP
study area declined by 93-94%, from 13,900-17,500 in
1986 to 1005 in 2001. Similar to the NAP results, areas
that had previously supported dense aggregations of
sea otters were largely vacant in 2001 and the areas of
highest concentrations were in bays and lagoons.
Coastline survey analyses
Between 1986 and 1989 there was considerable variabil-
ity in sea otter counts at islands in the south Alaska Pen-
insula study area (Table 2). Some areas had increased
(Sanak, Caton, and the Pavlof Islands) while others
decreased (Deer Island, Shumagin Islands). However
by 2001, sea otter counts and density had decreased
at nearly all islands and net losses of over 100 otters
occurred at Deer, Dolgoi, Goloi, Unga, and Nagai islands.
Overall, sea otter counts at these islands declined from
2174 in 1986 to 402 in 2001— a 63% decline in density.
In April and May 2001 we surveyed approximately
3800 km of coastline from Cape Douglas to False Pass
(Table 3). Sea otter density in 2001 was 35% lower than
in 1989 for the three westernmost coastline segments
from False Pass to Castle Cape (1782 km of coastline).
To the east of Castle Cape, sea otter density was 4%
greater in 2001 than in 1989 (2018 km of coastline).
These results indicate that an eastward extent of the de-
cline along the Alaska Peninsula may occur in the area
of Castle Cape. Overall, sea otter density declined by
12.4% along the coastline of the Alaska Peninsula from
False Pass to Cape Douglas between 1989 and 2001.
Discussion
When compared to surveys conducted in 1986, our results
indicated that sea otter abundance has declined severely
in the SAP and NAPa study areas along the Alaska
Peninsula, whereas sea otter abundance increased in
the NAPb study area (specifically Port Moller) and east
of Castle Cape along the south side of the Peninsula. To
determine the geographic extent and magnitude of the
sea otter population decline, current data were needed
to assess population abundance and trends along the
Alaska Peninsula.
Variations in survey methods limited our ability to
assess population trends for the Alaska Peninsula prior
to 1986. In 1976, the sea otter population along the
NAP was estimated to be 17,000 and continued range
expansion was expected (Schneider, 1976). In 1982-
83, seasonal estimates of sea otter abundance in the
NAP study area varied between March (1454), August
(10,325), and October (1880) which led Cimberg et al.2
to speculate that there was a large-scale seasonal mi-
gration of sea otters between the Bering Sea and North
Pacific Ocean. Sea otter distribution and abundance
Burn and Doroff: Decline of Enhydra lutris along the Alaska Peninsula
275
Figure 3
All survey transects and sea otter (Enhydra lutris) sightings in offshore areas. (A) Late
June-early July 1986. (B) May 2000 (north Alaska Peninsula [NAP], a and b), April 2001
(south Alaska Peninsula [SAP]).
remained relatively constant over the spring, summer,
and fall seasons for both the NAP and SAP study areas
in 1986 which led Brueggeman et al.1 to conclude that
there was no indication that sea otters were redis-
tributed from the northern to the southern Peninsula
during the winter months. Instead, Brueggeman et al.1
attributed the differences in the survey results between
1982-83 and 1986 to the viewing conditions and wind
speed in which Cimberg et al.2 conducted their March
and October surveys. Although both the 1976 and 1983
estimates were adjusted for sea otters missed by ob-
servers, the 1986 estimates were not. Evans et al.4
276
Fishery Bulletin 103(2)
Table 2
Alaska Peninsula island coastline lengths, sea otter tEnhydra lutris) cou
change. Survey strip width for the 1986 survey was 0.92 km, for 1989 it was
nts, sea otter densities, and estimatec
0.4 km, and for 2001 it was 0.46 km.
population
Island name
Coastline
length
(km)
Sea otters counted
Sea otter density
(otters/km-)
% change
in density
1989-2001
1986
1989
2001
1986
1989
2001
Sanak and Caton
178
13
168
12
0.08
2.36
0.15
+ 84.6
Deer Island
61
245
71
19
4.35
2.90
0.67
-84.5
Dolgoi
94
185
93
15
2.14
2.47
0.35
-83.8
Colul
14
113
62
1
8.77
11.07
0.16
-98.2
Inner Illiask
13
77
68
9
6.44
13.07
1.51
-76.6
Outer Illiask
17
82
305
4
5.24
44.85
0.51
-90.2
Wosnesenski
32
29
28
3
0.99
2.19
0.20
-79.3
Ukolnoi
38
54
133
21
1.54
8.75
1.20
-22.2
Poperechnoi
22
80
26
1
3.96
2.95
0.10
-97.5
Unga
231
568
275
182
2.67
2.98
1.71
-35.9
Popof
72
72
73
4
1.09
2.53
0.12
-88.9
Korovin
65
101
47
9
1.69
1.81
0.30
-82.2
Andronica
22
31
15
0
1.53
1.70
0.00
-100.0
Nagai
342
184
141
52
0.58
1.03
0.33
-43.5
Big Koniuji
160
52
18
33
0.35
0.28
0.45
+26.9
Turner and the Twins
16
6
9
0
0.41
1.41
0.00
-100.0
Bendel
17
35
7
2
2.24
1.03
0.26
-88.6
Spectacle
15
17
12
7
1.23
2.00
1.01
-17.6
Little Koniuji
95
65
20
0
0.74
0.53
0.00
-100.0
Simeonof
49
65
5
24
1.44
0.26
1.06
-26.2
Chernabura
30
20
2
0
0.72
0.17
0.00
-100.0
Bird
31
80
11
4
2.81
0.89
0.28
-90.0
Total
1614
2174
1589
402
1.46
2.46
0.54
-63.0
Table 3
Alaska Peninsula coastline segment lengths, sea otter iEnhydra lutri
change. Survey strip width for the 1989 survey was 0.4 km; for 2001 it
s) counts, sea
was 0.46 km.
otter densities.
and estimated population
Coastline segment 1989-2001
Coastline
length
(km)
Sea otters counted
Sea otter density
(otters/km2)
% change
in density
1989
2001
1989
2001
False Pass to Seal Cape
715
622
461
2.17
1.40
-35.6
Seal Cape to Kupreanof Point
370
196
50
1.32
0.29
-77.8
Kupreanof Point to Castle Cape
697
48
25
0.17
0.08
-54.7
Castle Cape to Cape Kuyuyukak
639
1007
1193
3.94
4.06
+3.0
Cape Kuyuyukak to Cape Aklek
495
177
352
0.89
1.55
+72.9
Cape Aklek to Cape Douglas
814
570
497
1.75
1.33
-24.2
Sutwick Island
70
12
73
0.43
2.27
+429.0
Total
3800
2632
2651
1.73
1.52
-12.4
Burn and Doroff: Decline of Enhydra lutns along the Alaska Peninsula
277
estimated that observers flying in a Twin Otter aircraft
recorded 42% of the sea otters present within the area
surveyed. Adjusting the 1986 results by this amount
yields a range of 10,086-17,238; therefore the popula-
tion may not have changed substantially between 1976
and 1986. By 2000 however, it is clear that sea otters
had declined within the NAP study area, and although
the data history for the SAP study area is even more
sparse, there is little doubt that the population in this
area has also declined severely since 1986.
The distribution of sea otters along the north side of
the Alaska Peninsula is rather unique. Because of the
broad shelf, large rafts of otters have been observed
at distances of 50 km or more from shore. The area is
also subject to seasonal sea ice that can have a pro-
found impact on sea otter distribution, and in extreme
ice years, result in significant mortality (Schneider
and Faro, 1975). It is unclear if behavior and move-
ment patterns in the NAP area are different from other
areas in the north Pacific. In the 1960s and 1970s it
was thought that sea otters along the northern Alaska
Peninsula spent much, if not all, of their life in offshore
waters (Kenyon, 1969; Lensink, 1962; Schneider. 1976).
Cimberg et al.2 suggested that sea otters may migrate
through False Pass from the Bering Sea to the north
Pacific Ocean during the winter months to avoid be-
ing trapped by shore-fast sea ice. Of the two study
areas along the north side of the Alaska Peninsula,
the NAPa study area located farther south and west
is more likely to remain ice-free, and therefore may be
important for the overall survival of sea otters in this
area (Schneider and Faro, 1975). If sea otters remain
concentrated throughout the year in Port Moller, which
is in the NAPb study area, they may be vulnerable to
mortality by extensive sea ice events in the future.
Information derived from sea ice data with spatial and
temporal resolution suitable for evaluating the impacts
of extensive sea ice on sea otters is not readily available.
Detailed sea ice data for the NAP study area from the
National Ice Center is only available for the period from
1997 to the present. In March 1999 shore-fast ice was
present in both Port Moller and Izembek Lagoon, and
nearshore areas were almost totally covered by sea ice.
Similar conditions also occurred in January 2000. In
both instances, sea otter mortality was reported by resi-
dents of Port Heiden, Alaska, located to the northeast
of the NAP study area (Esslinger5; Snyder6). Human
habitation in the NAP study area is extremely sparse in
winter, which may explain why there were no reports of
4 Evans, T. J., D. M. Burn, and A. R. DeGange. 1997. Dis-
tribution and relative abundance of sea otters in the Aleu-
tian archipelago. Tech. Rep. MMM 97-5, 29 p. U. S. Fish
and Wildl. Serv. Mar. Mamm. Manage. Office 1011 E Tudor
Road, Anchorage, AK 99503.
5 George Esslinger. 1999. Personal commun. U.S. Geologi-
cal Survey. Alaska Science Center. 1011 East Tudor Road.
Anchorage, AK 99503-6103.
6 Jonathan Snyder. 2000. Personal commun. U.S. Fish
and Wildl. Serv., Mar. Mamm. Manage. Office, 1011 East
Tudor Road, Anchorage, AK 99503-6103.
sea otter mortality in this area. Given the degree of sea
ice present, it is possible that the extreme ice conditions
in 1999 and 2000 may have resulted in the death of
some sea otters within our study area. The geographic
pattern of the decline does not exactly fit what would
be expected from sea ice however, because the decline
occurred in the NAPa study area, which is presumed
to be less vulnerable to these events. Although it is
possible that extreme sea ice conditions may have been
a contributing factor, it was likely not the sole cause of
the decline in the NAP study area.
In our surveys of the NAP study area, sea otter abun-
dance declined severely in NAPa but had increased in
NAPb. It is unclear to what degree otters may move
between these respective study areas. Quarterly surveys
in 1986 did not indicate seasonal changes in distribu-
tion between the NAPa and NAPb portions of the study
area. Monnett et al.' used radio telemetry to study sea
otter movements in the NAPa study area from 1986
through 1988 and found that study animals did not
move between NAPa and NAPb or to the SAP study
area as previously hypothesized by Cimberg et al.2 The
average distance between extreme locations was only
18.4 km; however, the sample size of sea otters in the
Monnett et al." study was small (n=14). The large con-
centration of sea otters observed in Port Moller and Nel-
son Lagoon in May 2000 may be a seasonal event; large
numbers of sea otters are typically observed in that
area in May, but disperse by June (Murphy*). Compared
to the ecology of other areas, the ecology of sea otters
along the north side of the Alaska Peninsula is poorly
understood and additional study is warranted.
In addition to changes in abundance there were also
changes in sea otter distribution in the 2000-01 sur-
veys. In 1986, sea otters were observed up to 50 km
from shore during all surveys. In the 1970s and 1980s,
large rafts of up to 1000 sea otters were distributed
well offshore (Kenyon, 1969; Schneider, 1976; Bruegge-
man et al.1). By 2001 sea otters were, with rare excep-
tion, located in bays and lagoons along the Peninsula
rather than in the offshore habitat in both the NAP and
SAP study areas. Estes et al. (1998) hypothesized that
declines in sea otters in the Aleutian islands during the
1990s may have been caused by increased predation by
killer whales (Orcinus orca). One line of evidence that
led to this conclusion was a lower sea otter mortality
in the sheltered area of Clam Lagoon than in the ex-
posed area of Kuluk Bay on Adak Island. The observed
distribution of sea otters within bays and lagoons along
the Alaska Peninsula in 2000-01 is not inconsistent
with the predation hypothesis of Estes et al. (1998). Al-
ternatively, nearshore waters may constitute preferred
Monnett, C, L. M. Rotterman, D. B. Sniff, and J. Sarvis.
1988. Movement patterns of western Alaska Peninsula
sea otters. Minerals Management Service. OCSEAP (Off-
shore Continental Shelf Engineering Assessment Program I
Research Unit 688, 51 p.
Murphy, B. 2002. Personal commun. Alaska Department
of Fish and Game, Division of Commercial Fisheries, 211
Mission Road. Kodiak, AK 99615-6399.
278
Fishery Bulletin 103(2)
habitat for sea otters, and at low densities it is possible
that these may be the only areas where they occur.
We are reasonably confident that the 2000-01 sur-
veys yielded results that were comparable to baseline
surveys because the methods were closely repeated. The
difference in distribution of sea otter sighting zones
may have been a result of different aircraft configura-
tions. Although both aircraft were equipped with bubble
windows, the size and shape of these windows were
probably not identical. We accounted for any differences
by selecting the zones best suited to estimate sea otter
abundance for each survey period. In our data analysis,
we also accounted for the effects of survey conditions
(Beaufort sea state and viewing condition) in both data
sets. Our results indicate that in addition to changes in
sea otter abundance, distribution had changed markedly
between study periods as well. Because sea otter distri-
bution is currently concentrated closer to the coast, we
recommend revising the survey design for future popu-
lation surveys in this area. Rather than considering the
offshore area as a single survey stratum, it would be
more efficient to define nearshore and offshore survey
strata and allocate survey effort accordingly.
To the west of the Alaska Peninsula study areas,
the sea otter population in the Aleutian archipelago
has declined to less than 10% of the estimated carry-
ing capacity (Burn et al., 2003). Further westward in
the Commander Islands, Russia, the sea otter popula-
tion appears to have remained stable over the same
time period (Burkanov and Burdin9). To the east of
the Alaska Peninsula, sea otters have declined by an
estimated 569r in the nearby Kodiak archipelago since
1989 (Doroff et al.10), but they appear to have remained
relatively stable in the areas of Cook Inlet and Kenai
Fiords (Bodkin et al.11) According to the most recent
population surveys, the geographic extent of the sea ot-
ter decline does not appear to have exceeded the range
of the southwest Alaska population stock as described
by Gorbics and Bodkin (2001), where the overall decline
has been estimated at 56-68%. Because the cause of
the decline remains unknown, areas at the periphery
of the current decline should be regularly monitored
in the future. Given the close proximity between the
Aleutian Islands and the Commander Islands, Russia,
future research there may improve our understanding
of the cause of the decline in southwest Alaska.
9 Burkanov, V. N., and A. M. Burdin. 2002. Distribution and
abundance of sea otter, steller sea lion, and killer whale in
the Commander Islands (Russia) during 2002. North Pacific
Wildlife Consulting, LLC Interim Report, 37 p. North
Pacific Wildlife Consulting , 12600 Elmore Rd., Anchorage,
AK 99516.
10 Doroff, A. M., D. M. Burn, R. A. Stovall, and V. A. Gill. In
prep. Unexpected population declines of sea otters in the
Kodiak archipelago, Alaska.
11 Bodkin, J. L. D. H. Monson, and G. E. Esslinger. 2003. A
report on the results of the 2002 Kenai Peninsula and Lower
Cook Inlet aerial sea otter survey, 10 p. U.S. Geological
Survey, Alaska Science Center Report. 1011 East Tudor
Road, Anchorage, Alaska 99503.
The sea otter decline, which has occurred over a
broad geographic area, encompasses different habi-
tat types in southwest Alaska. The Aleutian Island
chain is primarily volcanic in origin and the majority
of habitat for foraging (waters <40 m) is concentrated
relatively near shore and is primarily a rocky substrate.
The Alaska Peninsula includes extensive soft-sediment
offshore habitat available to sea otters. Despite these
differences, the declines in sea otter populations are
similar between the Alaska Peninsula and the Aleutian
archipelago in both severity and time period, which may
imply a common cause. In addition to sea otters, severe
declines of harbor seals (Phoca vitulina), Steller sea
lions (Eumetopias jubatus), and fur seals (Callorhinus
ursinus) have also been documented within the same
general region, which suggests broader ecosystem-level
changes may be involved. Our survey results, along
with evidence of a declining sea otter population in the
Kodiak archipelago, prompted the U.S. Fish and Wild-
life Service to propose listing sea otters in southwest
Alaska as threatened under the U.S. Endangered Spe-
cies Act. The population decline in southwest Alaska is
one of the most significant conservation issues for the
sea otters in our time.
Acknowledgments
We thank the following individuals and organizations for
their contributions to 2000-01 surveys: Linda Comerci,
Thomas Evans, Susanne Kalxdorff, and Rosa Meehan
for their work as observers and data recorders during
survey operations; Ralph Aiken, Tom Blaesing, and Dave
Weintraub for their incomparable piloting skills; Izembek
National Wildlife Refuge manager Rick Poetter and his
staff for logistical support. Jay Brueggeman and Greg
Green provided the original 1986 aerial survey informa-
tion and assisted with data interpretation. We thank
John Haddix for assistance with GIS analysis of the
1986 survey data. We also thank James Bodkin, Verena
Gill, Mark Udevitz, and two anonymous reviewers for
comments on an earlier draft of this manuscript.
Literature cited
Burn, D. M., A. M. Doroff, and M. T. Tinker.
2003. Carrying capacity and pre-decline abundance
of sea otters (Enhydra lutris kenyoni) in the Aleutian
Islands. Northwest. Nat. 84:145-148.
Doroff, A. M., J. A. Estes, M. T. Tinker, D. M. Burn, T J. Evans.
2003. Sea otter population declines in the Aleutian
archipelago. J. Mammal. 84:55-64.
Estes, J. A.
1977. Population estimates and feeding behavior of sea
otters. In The environment of Amchitka Island, Alaska
(M. L. Merritt and R. G. Fuller, eds.), p. 511-526. U.
S. Energy Resource and Development Administration,
Springfield, VA.
1990. Growth and equilibrium in sea otter populations. J.
Anim. Ecol. 59:385-401.
Burn and Doroff: Decline of Enhydra lutns along the Alaska Peninsula
279
Estes, J. A., and J. R. Gilbert.
1978. Evaluation of an aerial survey of Pacific walruses
(Odobenus rosmarus divergens). J. Fish. Res. Board
Can. 53:1130-1140.
Estes, J. A., M. T. Tinker, T. M. Williams, and D. F. Doak.
1998. Killer whale predation on sea otters linking oceanic
and near shore ecosystems. Science 282:473-476.
Garshelis, D. L., and J. A. Garshelis.
1984. Movements and management of sea otters in
Alaska. J. Wild. Manag. 48(31:665-678.
Gelatt, T. S., D. B. Siniff, and J. A. Estes.
2002. Activity patterns and time budgets of the declining
sea otter population at Amchitka Island, Alaska. J.
Wild. Manag. 66:29-39.
Gorbics, C. S., and J. L. Bodkin.
2001. Stock structure of sea otters (Enhydra lutris ken-
yoni) in Alaska. Mar. Mamm. Sci. 1713 1:632-647.
Kenyon, K. W.
1969. The sea otter in the eastern Pacific Ocean. N.
Am. Fauna 68:1-352.
Lensink C. J.
1962. The history and status of sea otters in Alaska. Ph. D.
diss., 188 p. Purdue Univ., West La Fayette, IN.
Schneider, K. B.
1976. Assessment of the distribution and abundance of
sea otters along the Kenai Peninsula, Kamishak Bay,
and the Kodiak archipelago. OCSEAP (Offshore Con-
tinental Shelf Engineering Assessment Program) final
rep. no. 37, p. 527-626. Dept. of Commerce, National
Oceanographic and Atmospheric Administration, Anchor-
age, AK.
Schneider, K. B„ and J. B. Faro.
1975. Effects of sea ice on sea otters (Enhydra lutris). J.
Mammal. 56:91-101.
280
Abstract— The age and growth dynam-
ics of the spinner shark (Carcharhinus
brevipinna) in the northwest Atlan-
tic Ocean off the southeast United
States and in the Gulf of Mexico were
examined and four growth models
were used to examine variation in
the ability to fit size-at-age data. The
von Bertalanffy growth model, an
alternative equation of the von Ber-
talanffy growth model with a size-at-
birth intercept, the Gompertz growth
model, and a logistic model were fitted
to sex-specific observed size-at-age
data. Considering the statistical cri-
teria (e.g., lowest mean square error
[MSE], high coefficient-of-determina-
tion, and greatest level of significance)
we desired for this study, the logistic
model provided the best overall fit
to the size-at-age data, whereas the
von Bertalanffy growth model gave
the worst. For "biological validity,"
the von Bertalanffy model for female
sharks provided estimates similar to
those reported in other studies. How-
ever, the von Bertalanffy model was
deemed inappropriate for describing
the growth of male spinner sharks
because estimates of theoretical
maximum size (L„) indicated a size
much larger than that observed in the
field. However, the growth coefficient
(£ = 0.14/yr) from the Gompertz model
provided an estimate most similar to
that reported for other large coastal
species. The analysis of growth for
spinner shark in the present study
demonstrates the importance of fit-
ting alternative models when stan-
dard models fit the data poorly or
when growth estimates do not appear
to be realistic.
Growth dynamics of the spinner shark
(Carcharhinus brevipinna)
off the United States southeast and
Gulf of Mexico coasts: a comparison of methods
John K. Carlson
Ivy E. Baremore
Southeast Fisheries Science Center
National Marine Fisheries Service, NOAA
3500 Delwood Beach Road
Panama City, Florida 32408
E-mail address (for J K Carlson): |ohn carlsoniSnoaa gov
Manuscript submitted 3 May 2004
to the Scientific Editor's Office.
Manuscript approved for publication
29 December 2004 by the Scientific Editor.
Fish. Bull. 10.3:280-291 (2005).
Virtually every study concerned
with describing the growth of elas-
mobranchs uses the von Bertalanffy
growth equation (von Bertalanffy,
1938). despite criticism of the model
(Knight, 1968; Roff, 1980). A review
of the existing literature from 1962
to 2002 indicates that only about 12%
of the published papers concerned
with elasmobranch age and growth
provide or have examined an alter-
native model (I.E.B., unpubl. data).
Most studies on elasmobranch age and
growth have simply fitted the von Ber-
talanffy model to observed or back-
calculated size-at-age data without
much concern about goodness-of-fit. In
addition, appropriate age-structured
assessments require accurate mea-
sures of the growth coefficient ik) of
the population when calculating, for
example, indirect estimates of natural
mortality. A complete study on the age
and growth of a species may require
the application of multiple growth
models, especially when data do not
appear to fit a given model (e.g., when
there is no statistical significance or
when there is poor goodness-of-fit) or
when results do not appear to be bio-
logically realistic.
The spinner shark (Carcharhinus
brevipinna) is a cosmopolitan species
occurring in warm-temperate areas of
the Atlantic Ocean, the Indian Ocean,
and the western Pacific Ocean (Com-
pagno, 1984). Off the United States
east and Gulf of Mexico coasts, the
spinner shark is managed under a
large coastal shark complex (NMFS,
1993). Sharks within this complex are
considered to be relatively large, slow
growing, long lived, and are currently
overfished (Cortes et al.1).
Although Allen and Wintner (2002)
recently examined the age and growth
of the spinner shark off South Africa,
the only existing information on spin-
ner sharks from U.S. waters is from
Branstetter (1987), who examined
just 15 animals from the Gulf of Mex-
ico. The purpose of the present study
is to re-examine the age and growth
dynamics of the spinner shark off
the U.S. southeast and Gulf of Mex-
ico coasts. We compare and contrast
four growth models to determine the
model that best describes the growth
data of the spinner shark.
Materials and methods
Sharks (n = 273) were collected from
1995 to 2003 in the U.S. Exclusive
Economic Zone from Galveston, Texas
to Key West, Florida, in the Gulf of
Mexico and in the U.S. south Atlantic
Ocean from Charleston, South Caro-
lina, to West Palm Beach, Florida
(Fig. 1). Precaudal (PC), fork (FL)
or total (TL) length (cm) were mea-
sured, and sex and maturity state
were determined for each shark. Total
1 Cortes, E„ L. Brooks, and G. Scott.
2002. Stock assessment of large coastal
sharks in the U.S. Atlantic and Gulf of
Mexico. Sustainable Fisheries Divi-
sion contribution SFD-02/03-177, 64
p. Southeast Fisheries Science Center,
3500 Delwood Beach Rd.. Panama City,
FL, 32408.
Carlson and Baremore: Growth dynamics of Corcharhinus brevipmna
281
Figure 1
Map of the sampling area for spinner sharks iCarcharhinus brevipinna) showing areas and locations
stated in the text.
length was measured as a straight line from the tip of
the snout to the tip of the tail in a natural position. The
weight (kg) of each shark was obtained when sampling
conditions permitted. Vertebrae were removed from an
area anterior to the first dorsal fin.
Vertebral sections were placed on ice after collection
and frozen upon return to the laboratory. Thawed ver-
tebrae were cleaned of excess tissue and soaked in a 5%
sodium hypochlorite solution for 5-30 min to remove
remaining tissue. After cleaning, vertebrae were soaked
in distilled water for 30 minutes and stored in 959f
isopropyl alcohol. Prior to examination, one vertebra
from each shark was chosen at random, removed from
alcohol, and dried. The vertebra was fixed to a clear
glass slide with resin and sectioned with a Buehler 82
Isomet low-speed saw.
Sagittal sections of different thicknesses were cut
from the vertebral centrum and stained with crystal
violet, or alizarin red, or left unstained according to
the methods of Carlson et al. (2003). Each vertebral
section was mounted on a glass microscope slide with
ProTex cytoseal (Lerner Laboratories, Pittsburg, PA)
and examined by using a dissecting microscope under
transmitted light. The banding pattern was found to
be most apparent on unstained sagittal sections with a
thickness of 0.3 mm.
Opaque bands representing summer growth and
translucent bands representing winter growth were
identified following the description and terms in Cail-
liet and Goldman (2004) (Fig. 2). Because no validation
is available for this species, verification of the annual
period of band formation was performed by using the
relative marginal increment analysis (Branstetter and
Musick, 1994; Natanson et al., 1995):
MIR = {VR-Rn)l{Rn-Rn_1),
where MIR = the marginal increment ratio;
VR = the vertebral radius;
Rn = distance to the outer edge of the last
complete band; and
Rn_i = distance to the outer edge of the next-to-last
complete band.
Mean MIR was plotted against month to determine
trends in band formation. A single factor analysis of
variance was used to test for differences in arcsine-
transformed (Zar, 1984) MIR data among months.
282
Fishery Bulletin 103(2)
Figure 2
Sagittal section from a 3.5+ year-old spinner shark tCarcharhinus brevipinna) illustrating the band-
ing pattern and winter marks (annuli) used to assign age.
Both authors randomly read vertebrae independently
without knowledge of sex or length of specimens. Verte-
bral age estimates for which the readers disagreed were
reread simultaneously by using a digital camera and
software (Pixera Studio version 2, Pixera Corporation,
Los Gatos, CA). If no agreement between readings was
reached, samples were discarded.
Several methods were used to evaluate precision and
bias among age determinations following the recom-
mendations in Cailliet and Goldman (2004). Percent
agreement (PA=number agreed/number read)x 100 and
percent agreement plus or minus one year were cal-
culated for 10 cm (e.g. 76-85 cm FL) length intervals
to evaluate precision (Goldman, 2002). The index of
average percent error (APE: Beamish and Fournier,
1981) was calculated to compare the average deviation
of readings from the means of all readings for each
vertebral section:
IAPE^-%
■M
R
-v—
where n = number of sharks aged;
r = number of readings;
Xy = ith age estimation of jth shark at /th reading;
and
x = mean age calculated for the j'th shark.
Chi-square tests of symmetry following Hoenig et al.
(1995) were used to determine if differences between
readers were systematic or due to random error.
Several models were fitted to sex-specific observed
size-at-age data to estimate the growth dynamics in
spinner shark. Although back-calculated size-at-age
length data would increase sample sizes for some ages
(Cailliet, 1990), multiple back-calculated lengths-at-age
are not independent samples and violate statistical as-
sumptions in estimating parameters for a growth model
(Vaughan and Burton, 1994). Vaughan and Burton (1994)
pointed out that estimates of the model parameters
may be biased because multiple back-calculated lengths
cause an inaccurate number of degrees of freedom.
Thus, we used data only from observed size-at-age.
In developing theoretical growth models, we assumed
that 1) the birth mark is the band associated with a
pronounced change in angle in the intermedialia, and
we assigned an arbitrary birth date of 1 June, the ap-
proximate mid-point date when neonates were present
in field collections, 2) translucent bands representing
Carlson and Baremore: Growth dynamics of Carcharh/nus brevipmna
283
winter growth form approximately six months later
(i.e., 0.5 years) and 3) subsequent translucent bands
representing winter growth form at yearly intervals,
thereafter. Thus, ages (yr) were calculated by following
the algorithm of Carlson et al. (1999): age = birth mark
+ number of translucent winter bands-1.5. If only the
birth mark was present, the age was 0+ years. All age
estimates from growth band counts were based on the
hypothesis of annual growth band deposition (Branstet-
ter, 1987).
The von Bertalanffy growth model (von Bertalanffy,
1938) is described by using the equation
Lt=LJl-
-k<t-t,,)
where L, = mean fork length at time t;
Lr = theoretical asymptotic length;
k = growth coefficient; and
r0 = theoretical age at zero length.
An alternative equation of the von Bertalanffy growth
model, with a size-at-birth intercept rather than the r0
parameter (Van Dykhuizen and Mollet, 1992, Goosen
and Smale, 1997; Carlson et al., 2003) is described as
Lt = LJl-be~
where b
L
(L^-L^IL^ and
- length at birth.
Estimated median length at birth for spinner shark is
52 cm FL (Carlson, unpubl. data).
We also used the modified form of the Gompertz
growth model (Ricker, 1975). The model is expressed
following Mollet et al. (2002) as
L.
-Lo(t
G(l-
where G
ln(L0/L3
For the Gompertz model, the estimated median asymp-
totic length for spinner shark is 220 and 200 cm FL for
females and males, respectively (Carlson, unpubl. data).
A logistic model (Ricker, 1979) was also considered
in the form
w =w ja + e
-k(t-a) ,
where Wt = mean weight (kg) at time r;
Wx = theoretical asymptotic weight;
k = (equivalent tog in Ricker, 1979) instanta-
neous rate of growth when w—*0; and
a = (equivalent to tQ in Ricker, 1979) time at
which the absolute rate of increase in weight
begins to decrease or the inflection point of
the curve.
If weight was not available, length was converted to
weight by using the regression: weight= 0.0000209 x
FL29524 (/2=226, r2=0.98, range: 1.1-66.1 kg).
Table 1
A summary
of the
number of spinner
sharks
(Car eh ci-
rhinus brevispinna)
by month and sex.
used for
our esti-
mates of age
Month
Male
Female
January
8
3
February
0
0
March
(1
13
April
0
3
May
25
6
June
15
47
July
35
22
August
30
35
September
4
13
October
0
0
November-
0
0
December
0
0
All growth model parameters were estimated with
Marquardt least-squares nonlinear regression. All mod-
els were implemented by using SAS statistical software
(SAS version 6.03, SAS Institute Inc., Cary, NO. The
goodness-of-fit of each model was assessed by examin-
ing residual mean square error (MSE), coefficient-of-
determination (r2), F from analysis of variance, level
of significance (P<0.05), and standard residual analysis
(Neter et al., 1990).
Results
Morphometric relationships were developed to convert
length measurements. Linear regression formulae were
determined as PC=0.880(FL) + 1.503, «=163, r2 = 0.88,
P<0.0001; and FL = 0.847(TL)-3.497, rc=260, r2 = 0.99,
P<0.0001.
Of the original 273 samples, 14 were deemed unread-
able and were discarded (Table 1). The index of average
percent error for the initial reading between authors
was 10.6%. When grouped by 10-cm length intervals,
agreement for combined sexes was reached for an aver-
age of 30.2% and 58.2% (±1 band) of band counts for
sharks less than 115 cm FL (Table 2). Above 115 cm
FL, agreement was reached for 33.5% and 74.0% (±1)
of band counts for samples initially read. Hoenig's et al.
(1995) test of symmetry indicated that there was bias
between readers (x2=98.33, df=40, P<0.001).
Relative marginal increment analysis indicated that
bands form annually during winter months (Fig. 3). The
smallest relative increment was found in January and
the greatest in July. The relative marginal increment
ratio increased through spring months (March-May),
peaked in summer (June-August), and then declined to
fall. However, no statistical difference was found in MIR
284
Fishery Bulletin 103(2)
values among months (F=1.63, df=7, P=0.129), likely
because of the large variation in increment by months.
Under the statistical criteria established in our study,
all growth models fitted the data well (Table 3). For
males and females, models were highly significant
(P<0.001) and exhibited high coefficients of determina-
tion (r2a0.88). Residual mean square error (MSE) was
lowest for the logistic models. Notably, MSE was much
1 4 -
1.2 -
24
t
11
10 -
0.8 -
1
3
'.7
3
0.6 -
11
3
7
04 -
i
0.2 -
nn -
,
,
,
— i
— i 1 1 1
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Figure 3
Mean marginal increment analysis (MIR) by month for combi
of spinner sharks (Carcharhinus brevipinna). Vertical bars
standard deviation of the mean and numbers above each m
resent the sample size.
higher for the von Bertalanffy model males than for
any other model. Plots of the residuals against pre-
dicted sizes indicated no pattern in the residuals for
any model. The standard deviation of the residuals was
lowest for the logistic models (Table 3).
Estimates of the asymptotic size varied depending
on sex and model (Table 3; Figs. 4 and 5). For males,
the highest asymptotic length was produced by the von
Bertalanffy model (L5. = 421 cm FL), inter-
mediate lengths came from the von Berta-
lanffy model with a size-at-birth intercept
(Lx=279 cm FL) and the Gompertz model
(L,=200, G = 1.38), and lowest length was
produced by the logistic model (Wx = 60.2
kg, -161 cm FL). For females, asymptotic
sizes were highest and similar with the
von Bertalanffy, von Bertalanffy model
with a size-at-birth, and the Gompertz
models (226, 202, and 220 cm FL, respec-
tively) and lowest with the logistic model
(62.6 kg or -162 cm FL).
Among models with comparable growth
coefficients, the von Bertalanffy model
produced the lowest growth coefficient for
both males and females (& = 0.03 and 0.08/
yr, respectively). Growth coefficients were
higher and fairly similar for the other two
length models. The growth coefficient from
the logistic weight model was 0.44 and
0.37 for males and females, respectively.
ned sexes
are ± the
onth rep-
Table 2
Percent agreement and
percent agreement
(±1 band)
from the
initial set of read
ings for spinner shark {Carcharhinus
brevispinna).
Sexes combined
Males
Females
Percent
Percent
Percent
Total
Percent agreement
Total
Percent
agreement
Total
Percent
agreement
FL interval
read
agreement
±1 band
read
agreement
±1 band
read
agreement
±1 band
46-55
8
75.0
100.0
2
100.0
100.0
6
66.7
100.0
56-65
62
32.3
83.9
25
20.0
64.0
37
40.5
81.1
66-75
10
20.0
60.0
4
0.0
50.0
6
33.3
66.7
76-85
36
30.6
66.7
17
29.4
47.1
19
31.6
84.2
86-95
28
14.3
28.6
13
23.1
30.8
15
6.7
26.7
96-105
15
20.0
40.0
5
0.0
40.0
10
30.0
40.0
106-115
21
19.0
28.6
10
10.0
20.0
11
27.3
36.4
116-125
16
37.5
68.8
10
40.0
90.0
6
33.3
33.3
126-135
12
41.7
75.0
2
50.0
50.0
10
40.0
80.0
136-145
5
60.0
100.0
5
60.0
100.0
0
—
—
146-155
10
40.0
60.0
6
50.0
83.3
4
25.0
25.0
156-165
12
41.7
58.3
8
62.5
87.5
4
0.0
25.0
166-175
11
36.4
63.6
4
50.0
75.0
7
28.6
57.1
176-185
12
16.7
66.7
6
33.3
83.3
6
0.0
50.0
186-195
1
0.0
100.0
0
—
—
1
0.0
100.0
Carlson and Baremore: Growth dynamics of Carcharhinus brevipmna
285
The Gompertz model estimated size-at-birth (61 cm
FL) within the range reported for spinner sharks. Size-
at-birth off the United States southeast and Gulf of
Mexico coasts has been reported to range from 50 to
65 cm FL depending on the study (Branstetter, 1987;
Castro, 1993; Carlson, unpubl. data).
Observed size-at-age and longevity were different
between males and females (Table 4). For most ages, fe-
males were larger. The oldest animals aged were 17.5 +
years (female) and 13.5+ years (male).
Discussion
Considering our statistical criteria (e.g., lowest MSE,
high r2, and level of significance), logistic models pro-
vided the best fits to the size-at-age data. The von Berta-
lanffy growth models, on the other hand, gave the worst
fits. However, the criteria used to evaluate the models in
this study may not be adequate. Because statistical fits
have not been reported by other elasmobranch age and
growth studies, we were not able to compare our criteria
with other studies. Although not directly comparable,
goodness-of-fit criteria used to select the best nonlinear
gastric evacuation models have employed a combination
of r2, residual sum of squares, standard deviation, or
coefficient of variation of residuals (review in Cortes,
1997). Until a more rigorous criterion is developed for
growth models, efforts should continue to identify a
best-fitting growth model.
We feel the von Bertalanffy model is inappropriate
for describing the growth of male spinner shark. As-
ymptotic values indicated an unreasonable theoretical
maximum size of 421 cm FL — much larger than sizes
from recent fishery-dependent and fishery-independent
sources (176-220 cm FL; Grace and Henwood, 1997;
Morgan3; Carlson, unpubl. data). Asymptotic values from
other models approach those actual values. Because of
the relationship between k and L„, the von Bertalanffy
growth coefficient was also much lower than expected.
The growth coefficient from the Gompertz model was
0.14/yr, similar to those reported for other large coastal
species in general (Cortes, 2000) and to those reported
by Allen and Wintner (2002) for spinner sharks from
South Africa.
The poor statistical fit and unrealistic biological es-
timates of the von Bertalanffy growth model for male
spinner shark illustrates the importance of fitting alter-
native models to the data when estimates do not appear
to be biologically real. Although sample size was well
represented for most ages, the von Bertalanffy growth
model did not reach an asymptote until well beyond the
3 Morgan, A. Personal commun. Program for Shark Research,
Florida Museum of Natural History, Univ. Florida, P.O. Box
117800, Gainesville, FL, 32611.
Table 3
Estimates of growth and goodness-of-fit from four growth models fitted to observed size-at-age data for
sharks (Carcharhinus brevispinna). Values in parentheses are standard errors. L0 = size at birth. The st
the residuals is from standard residual analysis. MSE=mean square error. n/a=not available.
nale and female spinner
andard deviation (SD) of
Model
Asymptotic
size'
(cm FL)
Growth
coefficient
(/yr)
<o2
(yr)
L0
(cmFL)
F
P
r2
MSE
SDof
residuals
Male
von Bertalanffy
421.0 (±157.6)
0.03 (±0.02)
-4.58 (±0.65)
—
543.91
<0.001
0.91
543.91
11.91
von Bertalanffy
with size-at-
birth
279.1 (±39.4)
0.07 (±0.02)
n/a
52
946.24
<0.001
0.89
163.65
12.49
Gompertz
200(G = 1.38±0.09>
0.14 (±0.02)
n/a
60.5 (±1.9)
557.83
<0.001
0.91
141.23
11.78
Logistic
60.2 (±39.4)
0.44 (±0.05)
6.75 (±0.47)
483.00
<0.001
0.93
47.44
6.83
Female
von Bertalanffy
226.2 (±18.6)
0.08 (±0.02)
-3.84 (±0.40)
—
612.20
<0.001
0.90
150.70
12.19
von Bertalanffy
with size-at-
birth
202.7 (±10.9)
0.11 (±0.01)
n/a
52
1047.19
<0.001
0.88
173.07
12.78
Gompertz
220(G = 1.17±0.4)
0.16 (±0.02)
n/a
60.7 (±1.6)
609.09
<0.001
0.90
151.39
12.21
Logistic
62.6 (±3.2)
0.37 (±0.03)
7.62 (±0.43)
572.84
<0.001
0.93
43.82
6.57
1 Asymptotic size for the von Bertalanffy, von
logistic model is in kg.
2 t0 is the theoretical age at zero length for th
increase in weight begins to decrease.
Bertalanffy with size-at-birth, and Gompertz models are in cm, whereas asymptotic size for the
; von Bertalanffy whereas tu for the logistic model represents time at which the absolute rate of
286
Fishery Bulletin 103(2)
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288
Fishery Bulletin 103(2)
Table 4
Mean size-at-
age (cm FL) for male and female spinner sharks (C
arch a i
hi mis
brevispmna I
SD = standard deviation.
Age (yrl
0.0
0.5
1.5
2.5
3.5
4.5
5.5
6.5
7.5
8.5
9.5
10.5
11.5
12.5
13.5
14.5 15.5 16.5 17.5
Male
Size
60.7
64.1
81.2
84.6
99.9
105.8
115.5
146.3
138.9
154.2
165.3
165.9
—
176.3
178.0
— — — —
SD
5.3
5.9
11.4
13.8
17.9
11.0
4.2
23.4
13.9
13.4
3.0
—
3.1
_ _ _ _
n
29
1
12
8
21
7
7
3
6
10
7
2
—
3
1
— — — —
Female
Size
59.0
69.3
84.4
86.9
106.9
106.9
117.1
116.2
—
136.3
160.8
173.7
158.3
—
164.7
165.5 182.0 — 184.0
SD
4.1
11.5
2.9
8.7
13.3
13.9
19.1
20.7
—
19.6
16.4
14.8
11.2
—
21.7
21.9 — — 1.4
n
42
7
12
18
11
14
6
5
—
6
6
3
3
—
4
2 1 — 2
expected maximum size, resulting in an inflated asymp-
tote and low growth coefficient. Branstetter and Stiles
(1987) also encountered this problem with bull sharks
(Carcharhinus leucas) but rather than fit an alterna-
tive growth model, those authors hand-fitted a curve
through the upper data points. Results such as these
may seriously bias estimates of k and any resulting
population models because several indirect estimates
of natural mortality (M) and longevity rely heavily on
accurate estimates of k from a growth model (Fabens,
1965; Pauly, 1980; Chen and Watanabe, 1989; Jensen,
1996). For example, the method of Jensen (1996) for
estimating M yields values ranging from 0.05/yr (with
results from the von Bertalanffy model) to 0.23/yr (with
results from the Gompertz model). Similarly, theoretical
longevity estimates determined by the method of Fabens
(1965) are 115.5 years and 21.6 years from the von Ber-
talanffy model and the Gompertz model, respectively.
In general, our estimates of age and growth for fe-
male spinner sharks from the von Bertalanffy model
were similar to those reported by Allen and Wintner
(2002) for spinner sharks collected off South Africa.
Growth coefficients in their study were about 0.13/yr,
Lx was 250 cm FL, and observed longevity for females
was up to 19+ years. Branstetter (1987), in his study
on sharks collected in the Gulf of Mexico, reported an
observed longevity up to 11+ years (combined sexes) and
growth coefficients of about 0.21/yr. Because differences
in life history traits (e.g., growth rates, size and age
at maturity) between populations of blacktip and bull
sharks from South Africa and United States waters
have been proposed (Wintner and Cliff, 1995; Wintner
et al., 2002, respectively), results from our study for
spinner shark may be expected to be more similar to
those of Branstetter (1987) rather than those of Allen
and Wintner (2002). Although techniques (e.g., counting
winter bands on sagittal vertebral sections) in Brans-
tetter (1987) were similar to ours, the differences are
likely a result of low sample size in the earlier study.
The index of average percent error (IAPE) in aging
was at the higher end of the range of estimates pro-
vided in other studies that also used sagittal sections
for aging. Values have been reported as low as 3.0% for
the oceanic whitetip shark (Carcharhinus longimanus)
(Lessa et al., 1999), and up to 13.0% for the black-
tip shark (Carcharhinus limbatus) (Wintner and Cliff,
1995). Although IAPE indices are most commonly used
to evaluate precision among age determinations, IAPE
does not test for systematic differences and does not dis-
tinguish all sources of variation (Hoenig et al., 1995).
In addition, comparing IAPE values among studies may
not be valid unless the study species is the same and
from the same geographic area (Cailliet and Goldman
2004).
Although bands were readily discernible in most sam-
ples, the inexperience of one of the authors (reader 2)
in reading and counting vertebral bands likely led to
the higher IAPE and systematic bias. Generally, most
systematic bias is a shift to increasing or decreasing
counts with age (Morison et al. 1998), yet the bias in
this study was the result of reader 2 consistently over
aging sharks from the final agreed age regardless of the
band count of the sample. Percent agreement was simi-
lar for samples above 115 cm FL as it was for samples
below this size. Although a reference collection was
aged by reader 2 prior to beginning this study, finely
honed skills through experience are key elements in the
technique of aging.
The trend in marginal increment analysis indicated
that band formation occurs once a year during winter
months — a result common to most studies where rela-
tive marginal increment analysis is used for carcharhi-
nid sharks (e.g., Natanson et al., 1995; Carlson et al.,
1999; Carlson et al., 2003). However, high variance in
marginal increment analysis (MIR) within each month
resulted in months not being statistically different,
which is a widespread occurrence when using this meth-
od. Marginal increment analysis has been criticized as
one of the most abused methods for validation of band
formation (Campana, 2001). Problems with differentiat-
ing bands on the vertebral edge and application to older
age classes may provide misleading results (Campana,
Carlson and Baremore: Growth dynamics of Carcharhinus brevipmna
289
2001). Other methods have been used recently to report
yearly band formation in sharks, including oxytetra-
cycline marking (Simpfendorfer et al., 2002; Skomal
and Natanson, 2003; Driggers et al., 2004) and bomb
radiocarbon methods (Campana et al., 2002). However,
validation exists for relatively few elasmobranch species
(Cortes, 2000).
Two-phase growth models may be more appropriate
for describing the growth of sharks, especially those
that are longer lived. Soriano et al. (1992) developed a
biphasic growth model which they applied to the long-
lived Nile perch (Lates niloticus) to better describe their
change in growth from zooplanktivores as juveniles to
piscivores as adults. Growth by sharks could be regard-
ed as being found in two phases: a rapid juvenile growth
followed by a slower adult growth. From a bioenergetic
perspective, this would follow a change from energy
devoted to growth to energy devoted to reproduction.
The logistic model could be regarded as a two-phase
model and may help to describe this change. The shift
from juvenile to adult would correspond to the inflection
point (fu) of the curve, which approximates biological
age-at-maturity. In spinner sharks, age at maturity
was reported to be about 6-7 years for males and 7-8
years for females (Branstetter, 1987). This estimate of
age-at-maturity is similar to the inflection points from
our logistic model of 6.75 and 7.62 years for males and
females, respectively. Although each species should be
evaluated separately, future studies should investigate
the use of two-phase models to provide a more accurate
description of the growth of elasmobranchs.
There have been few other examples of fitting alter-
native growth models to size-at-age data when results
from the von Bertalanffy model were biologically in-
correct or when models did not fit the data well. The
present study represents the first attempt to dp so for a
species of shark. Comparison of age and growth models
by Mollet et al. (2002) and Neer and Cailliet (2001) for
two species of rays revealed that the Gompertz model
best described their respective data although all models
they tested fitted the data fairly well. For pelagic sting-
ray (Dasyatis violacea) the Gompertz model predicted a
more reasonable size-at-birth and growth rate than the
von Bertalanffy growth model (Mollet et al., 2002). Neer
and Cailliet (2001) reported a slightly better statistical
fit for the Pacific electric ray {Torpedo californica) when
using the Gompertz model. However, because the differ-
ence in model parameters was negligible, results were
reported only for the von Bertalanffy model.
The von Bertalanffy growth model is still the most
common model used to describe growth in fisheries
literature, despite criticism by Roff (1980) who recom-
mended its retirement. As pointed out by Roff (1980),
the choice of using another equation should be deter-
mined by the variables that are being investigated and
the results that are produced by the equation; for exam-
ple, if the results appear to be biologically unrealistic.
Our analysis of the growth of the spinner shark clearly
demonstrates the value of this approach. Use of the von
Bertalanffy growth model should continue because it
permits comparison of growth curves to information al-
ready published and in some cases adequately describes
the growth of a given organism. However, the variety of
statistical techniques and quality of each study make
comparisons of von Bertalanffy growth curves between
different populations difficult and results should be in-
terpreted with caution regardless of what growth model
is used (Roff, 1980).
Acknowledgments
We thank Enric Cortes, Pete Sheridan (NOAA Fisheries,
Panama City Laboratory), and Miguel Arraya (Universi-
dad Arturo Prat, Chile) for providing comments on ear-
lier versions of this manuscript. Ken Goldman (Jackson
State University) was especially helpful in discussion
on precision and bias in age estimation, Miguel Arraya
on the validity of the comparison of growth models, and
Henry Mollet (Monterey Bay Aquarium) with the Gomp-
ertz model. Many different laboratories and institutions
aided with the collection of vertebrae. George Burgess
and Matt Callahan (University of Florida) provided
samples from the directed shark longline fishery. Lisa
Natanson (NOAA Fisheries, Narragansett Laboratory)
obtained samples during their longline surveys from the
U.S. south Atlantic Ocean. Observers Armando de ron
Santiago, Carl Greene, Matt Rayl, Bill Habich, Mike
Farni, Jacques Hill, and Jeff Pulver collected samples
from the directed shark gillnet fishery. Mark Grace and
Lisa Jones (NOAA Fisheries, Pascagoula Laboratory)
provided samples from fishery-independent longline
surveys. We also thank Linda Lombardi, Lori Hale, and
numerous interns who assisted with the cleaning and
processing of vertebrae samples.
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Abstract— Data recovered from 11
popup satellite archival tags and 3
surgically implanted archival tags
were used to analyze the movement
patterns of juvenile northern bluefin
tuna (Thunnus thynnus orientalist in
the eastern Pacific. The light sen-
sors on archival and pop-up satellite-
transmitting archival tags (PSATs)
provide data on the time of sunrise
and sunset, allowing the calculation
of an approximate geographic position
of the animal. Light-based estimates
of longitude are relatively robust but
latitude estimates are prone to large
degrees of error, particularly near
the times of the equinoxes and when
the tag is at low latitudes. Estimat-
ing latitude remains a problem for
researchers using light-based geoloca-
tion algorithms and it has been sug-
gested that sea surface temperature
data from satellites may be a useful
tool for refining latitude estimates.
Tag data from bluefin tuna were sub-
jected to a newly developed algorithm,
called "PSAT Tracker," which auto-
matically matches sea surface tem-
perature data from the tags with sea
surface temperatures recorded by sat-
ellites. The results of this algorithm
compared favorably to the estimates
of latitude calculated with the light-
based algorithms and allowed for
estimation of fish positions during
times of the year when the light-
based algorithms failed. Three near
one-year tracks produced by PSAT
tracker showed that the fish range
from the California-Oregon border
to southern Baja California, Mexico,
and that the majority of time is spent
off the coast of central Baja Mexico.
A seasonal movement pattern was
evident; the fish spend winter and
spring off central Baja California, and
summer through fall is spent moving
northward to Oregon and returning
to Baja California.
Tracking Pacific bluefin tuna
(Thunnus thynnus orientalis)
in the northeastern Pacific with an
automated algorithm that estimates latitude by
matching sea-surface-temperature data from
satellites with temperature data from tags on fish
Michael L Domeier
Pfleger Institute ol Environmental Research
901 B Pier View Way
Oceanside, California 92054
E-mail address: Domeieng'cs com
Dale Kiefer
System Science Applications Inc.
POBox 1589
Pacific Palisades, California 90272
Nicole Nasby-Lucas
Adam Wagschal
Pfleger Institute of Environmental Research
901 B Pier View Way
Oceanside, California 92054
Frank O'Brien
System Science Applications Inc.
POBox 1589
Pacific Palisades, California 90272
Manuscript submitted 11 June 2004
to the Scientific Editor's Office.
Manuscript approved for publication
21 December 2004 by the Scientific Editor.
Fish. Bull. 103:292-306 (2005).
Current theories indicate the presence
of a single stock of northern Pacific
bluefin tuna (Thunnus thynnus orien-
talis) in the Pacific Ocean. Spawning
adults have been recorded only from
the western Pacific ( Yamanaka et al.,
1963; Yabe et al., 1966; Okiyama,
1974; Okiyama and Yamamoto, 1979;
Nishikawa et al., 1985) but resulting
offspring are known to either inhabit
the western Pacific or to travel to the
eastern Pacific (Sund et al., 1981; Bay-
liff, 1994; Itoh et al., 2003a) where
they remain for an undetermined
amount of time. Although it is believed
that only a small fraction of the popu-
lation migrates to the eastern Pacific,
these fish are the basis for a fishery
that occurs from May through Octo-
ber. A recent study has documented
the migration of an archival-tagged
juvenile northern Pacific bluefin tuna
from the western Pacific to the east-
ern Pacific in about two months, where
it remained for eight months before
being recaptured (Itoh, et al., 2003a).
Conventional tagging studies have
shown that Pacific bluefin tuna in
the eastern Pacific eventually return
to the western Pacific where they are
believed to remain as adults (Sund et
al., 1981; Bayliff, 1994). We provide
this cursory summary merely as an
introduction to our work, deferring
the known details of Pacific bluefin
biology to the excellent reviews that
have been previously published ( Bay-
liff, 1980. 1994; Sund et al., 1981).
Work presented in the present study
describes the use of electronic tags
(pop-up satellite-transmitting archi-
val tags and archival tags obtained
from fish) and a newly developed sea
surface temperature (SST) based geo-
Domeier et al.: Tracking Thunnus thynnus orientalis with the aid of an automated algorithm
293
location algorithm to further our understanding of blue-
fin tuna movements in the eastern Pacific.
The light sensors on archival and pop-up satellite
tags provide data on the time of sunrise and sunset,
allowing one to calculate the approximate geographic
position of an animal (Delong et al., 1992; Wilson et al.,
1992; Hill, 1994; Bowditch, 1995; Sobel, 1995; Welch
and Eveson, 1999; Hill and Braun, 2001; Metcalfe,
2001;Smith and Goodman;1 Gunn et al.2). The accu-
racy of the light-based geolocation estimates have been
studied under controlled conditions (tags tethered to
a moored buoy) and field conditions (tags attached to
fish at a known location). Locations from tethered tags
have been reported to be accurate to within ±0.2-0.9°
in longitude and ±0.6-4.4° in latitude (Welch and Eve-
son, 1999, 2001; Musyl et al., 2001). Tagged tuna have
provided light-based geolocation estimates within ±0.5°
of longitude and ±1.5-2.0° latitude (means) of known
locations (Schaefer and Fuller, 2002; Gunn et al.1).
Light-based estimates are not precise and comparing
studies that have examined the accuracy of this method
is complicated by differences in tag hardware and geo-
location algorithms used by different researchers. Other
physical and biological factors complicate the issue fur-
ther. Day length is not a good predictor of latitude dur-
ing the spring and fall equinox, therefore estimates of
latitude at times surrounding the equinox contain more
error than at other times of the year (Hill and Braun,
2001). Latitude estimates are also more prone to error
the closer the animal is to the equator (Hill and Braun,
2001). Additional errors can be introduced into esti-
mates of both latitude and longitude by the behavior of
the tagged animal (e.g., diving), bio-fouling of the tag,
cloud cover, and wave action (Metcalfe, 2001).
Poor resolution of latitude estimates continues to be
a problem for researchers using light-based geolocation
algorithms. Under ideal theoretical conditions the vari-
ability in latitude error cannot be less than 0.7° and the
expected variability in longitude will be a constant 0.32°
(Hill and Braun, 2001). Sibert et al. (2003) developed
an algorithm that applies a Kalman filter to light-based
geolocation estimates in an attempt to reduce the error
of these estimates. Although this approach smoothes
data, it does not incorporate external data (data not
collected by the tag) and therefore is still affected by
errors inherent in the use of light-based geolocation es-
1 Smith, P., and D. Goodman. 1986. Determining fish
movements from an "archival" tag: precision of geographi-
cal positions made from a time series of swimming, tem-
perature and depth. NOAA. Tech. Memo. NMFS-SWFC-60,
13 p. Southwest Fisheries Science Center, La Jolla, CA
92038.
2 Gunn, J. S„ T. W. Polacheck, T. L. O. Davis, M. Sherlock, and
A. Betlehem. 1994. The development and use of archival
tags for studying the migration, behavior and physiology of
southern bluefin tuna, with an assessment of the potential
for transfer of the technology to groundfish research. In
Proceedings of ICES mini-symposium on fish migration,
23 p. International Council for the Exploration of the Sea,
Palaegade 2-4, DK-1261 Copenhagen K. Denmark.
timates of latitude. It has been suggested that sea-sur-
face-temperature (SST) and bathymetry data be used
to refine light-based geolocation estimates (Block et al.,
2001). These techniques are particularly useful when
there is a north-to-south gradient of bathymetry or SST.
The use of bathymetry to refine latitude requires an as-
sumption that maximum diving depth is limited by the
bottom depth; certainly this assumption introduces a
new source of error. In addition, for animals that move
off the continental shelf, bathymetry would be useless.
The use of SST or bathymetry data to refine latitude
necessitates the arduous task of matching tag data with
another source of data.
It was our opinion that the accuracy of tracking ma-
rine animals could be improved through the develop-
ment of an algorithm that automatically resolved lati-
tude estimates by matching SST measurements from
the tag to those taken from satellites. Here we present
such an algorithm; one that was designed to operate
in a geographic information system (GIS) environment,
allowing for rapid analysis and display of archival and
PSAT tag data. We demonstrate the algorithm and its
product through the analyses of data we collected from
Pacific bluefin tuna tagged in the eastern Pacific.
Materials and methods
Tagging in the field
Pacific bluefin tuna were captured on rod and reel from
a recreational fishing vessel by using live bait and circle
hooks. Fishing took place 123 nmi southwest, 86 nmi
southwest, and 178 nmi south of San Diego in years
2000, 2001, and 2002, respectively. Fish were lifted into
the boat with a vinyl sling and then placed on a soft mat,
eyes were covered with a cloth, and the gills irrigated
with seawater. The fish were then measured (fork length
and girth), tagged, and immediately released. Sixteen
fish were tagged with Wildlife Computers Inc. (Redmond,
WA) pop-up satellite archival tags (PSATs), one fish was
tagged with a Microwave Telemetry Inc.! Columbia, MD)
PTT-100 PSAT, and seventeen fish were tagged with
Lotek Wireless Inc. (Newmarket, Ontario) LTD2310
nontransmitting archival tags. The two types of PSATs
either provided data once an hour (depth, water tempera-
ture, light level [Microwave Telemetry, Inc.]) or sum-
marized data that had been collected every two minutes
(Wildlife Computers, Inc.) — the difference being an arti-
fact of the two tag manufacturers. The Lotek archival
tags provided us with data every two minutes detailing
the swimming depth, water temperature, internal fish
temperature, and light level. Pressure sensor drift was
adjusted by the tag manufacturers' software for PSAT
tags and in the laboratory for the Lotek tags.
The PSAT tags were rigged with 300-lb monofilament
leaders and a nylon dart. In 2000 and 2001 the dart
was a "bluefin-type" provided by Eric Prince (NMFS-
SEFSC); in 2002 a Pfleger Institute of Environmental
Research (PIER) "umbrella" dart was used (Fig. 1).
294
Fishery Bulletin 103(2)
Figure 1
PIER umbrella dart used for external attachment of tags.
Each style of dart was inserted through the midline of
the fish at the base of the second dorsal fin according
to the method of Block et al. (1998).
Archival tags were surgically implanted either in the
dorsal musculature below the first dorsal fin (when fork
length was >110 cm) or into the peritoneal cavity (when
fork length was <110 cm). The dorsal musculature im-
plant was performed by making a 1-cm incision 3-5
cm below the first dorsal fin. A cold-sterilized trocar
(14 mm diameter) was then inserted into the muscle,
to a depth of 13-14 cm, within a plane parallel to the
pterygiophores but angled 45 degrees to the anterior.
The trocar was then removed and the tag was inserted
so that the light stalk was angled toward the tail. The
incision was then closed with a monocryl suture mate-
rial. This method was similar to that used by Musyl et
al. (2003). Interperitoneal implants were done according
to the method of Block et al. (1998).
PSAT Tracker algorithm and analysis system
We have developed an automated system, called the
PSAT Tracker Information System (PTIS), to improve
the accuracy and minimize the subjectivity and tedium
of matching data from different sources (tag and satel-
lite). It is an application of the Environmental Analysis
System (EASy) (System Science Applications, Redondo
Beach, CA) software that is specifically designed for
handling four-dimensional information (latitude, lon-
gitude, depth, and time). We describe the system in
terms of three processes; importing tag data and satel-
lite imagery, calculation of the optimal path of the tag,
and dynamic display of the path and associated tag
information.
Importing tag data and setting parameters
The PSAT tracker information system was designed
to support data formats of three tag manufacturers:
Wildlife Computers, Microwave Telemetry, and Lotek.
All three tag formats are imported into FIS and stored
in a universal relational database format for process-
ing. Key parameters used in the calculation of tracks
include time and position of tag deployment, time and
position of tag recovery, light-based estimates of lon-
gitude (provided by tag manufacturers), maximum
swimming speed of the tagged fish (estimated and
determined by the user), and a bracketed range of
latitude within which the program will search for SST
matches. Processing involves the temporal matching of
SST as recorded by the tag with that measured from
satellite imagery. It is important to note that the PTIS
user-defined latitude bracket is unrelated to the light-
based latitude estimates provided by the tag manufac-
turers; instead, it is simply a range set by the user to
include all possible movement of the animal during the
tag deployment. However, longitude estimates are tied
to the tag manufacturers' light-based estimates; the
user has the option of tying PTIS position estimates
directly to the light-based estimates or allowing the
algorithm to search a specified distance on either side
of the light-based estimate.
For this study the maximum fish velocity was set at
4 knots. This was meant to be an inclusive rather than
an exclusive value, broadening the range PSAT Track-
er could search for SST matches. SST matches were
also constrained to remain within ±20 nautical miles
(±0.33°) of the manufacturers' light-based estimates of
longitude, based upon the observance by Hill and Braun
Domeier et al.: Tracking Thunnus thynnus onentalis with the aid of an automated algorithm
295
Table 1
Resolution of sea-surface-temperature data from s
atellites and tags (ac
vanced ver\
high resolution radiometer [AVHRR1, moder-
ate resolution spectroradiometer IMODIS1, multichannel sea surface temperature
algorithm [MCSST],
Source
Accuracy (+C)
Spatial scale
kmi
Temporal scale
Availability
AVHRR pathfinder
0.3-0.5
9
Daily
1985-present
AVHRR pathfinder
0.3-0.5
9
8-day composite
1985-present
MODIS
0.3
4.6
Daily
Oct 2000-present
MODIS
0.3
4.6
8-day composite
Oct 2000-present
MCSST (Miami)
0.5-0.7
18
Weekly composite
1981-Feb 2001
MCSST (NAVOCEANO)
0.5-0.7
18
Weekly composite
Sep 2001-present
Wildlife computer tag
0.05
—
1-12/day
—
Microwave telemetry tag
0.17
—
60 minutes
—
Lotek 2300 tag
0.1
—
2 minutes
—
(2001) that light-based longitude estimates have a year
round constant error of ±0.32 degrees.
Satellite imagery, temperature sensors, and land mask
The PSAT Tracker code provides an interface to auto-
matically download, georeference, and display SST imag-
ery. As many as three different types of imagery can be
layered and prioritized to produce a collage of imagery
for processing and display. Higher priority layers are
searched first for SST matches before "drilling down"
to lower layers. The sources and types of available SST
data are numerous and have varied over the time frame
of this study; different sensors and algorithms produced
data of differing spatial and temporal resolution or accu-
racy (Table 1). To maximize the quality of the latitude
estimates produced by the PSAT Tracker algorithm, we
substituted better SST data as it became available. For
this study SST imagery was prioritized as follows: 1)
advanced very high resolution radiometer (AVHRR) or
moderate resolution spectroradiometer (MODIS) daily
data, 2) AVHRR or MODIS weekly data, and 3) multi-
channel sea surface temperature algorithm (MCSST)
weekly data. The MCSST algorithm is a weekly (or 8-
day) composite that is most helpful in analyzing regions
of frequent cloud cover; this algorithm was applied by the
University of Miami (Miami) from 1981 through Febru-
ary 2000 and has been applied by the Naval Oceano-
graphic Office (NAVOCEANO) since September 2001.
The MCSST algorithm provides a near complete picture
of SST data for the study area; although AVHRR and
MODIS data are higher resolution and more accurate.
The difference in the resolution and accuracy of tem-
perature sensors on the tags verses those on the satel-
lites (Table 1) are worth mentioning. The accuracy of
the satellite SST data, particularly for MCSST/NAV-
OCEANO. is the limiting factor when attempting to
match tag data to satellite data. The degree to which
the satellite data and tag data must match can be set
by the user in PSAT Tracker; for this study it was set
between the limit of MODIS and NAVOCEANO resolu-
tion (0.4°C).
There is a fourth layer that is superimposed upon the
imagery. This is a land mask that is used to eliminate
placing a tag on land and to insure that tags move
around land barriers rather than across them.
Computation of the track
A detailed mathematical description of the computation
for the best track would take more space than is avail-
able. Instead, we present a more general description of
the algorithm and its logic, consisting of the following
five steps that are summarized below and then subse-
quently described in detail.
1 Define the daily search area found within satellite
SST imagery.
2 Define appropriate tag data (termed selection set) to
match to satellite SST values found within the daily
search area.
3 Select candidate points within each daily search
area that provide the best match to the temperatures
found in the selection set. The cost of each candidate
point is largely determined by the difference between
the tag and satellite SST values.
4 Calculate the cost for all possible steps, called arcs,
between pairs of candidate points of adjacent daily
search areas. The cost of each step is a function of
the length of the arc that connects adjacent candidate
points (the greater the distance, the greater the cost)
and the cost of each individual candidate point (see
step 3).
5 Sum the costs of all tracks and identifying the track
with the lowest cost.
Step I: Defining the daily search area A daily search
area is defined by the tag manufacturers' light-based
solution for longitude, a user defined bracket for lati-
tude and the value entered for maximum swimming
296
Fishery Bulletin 103(2)
northern limit of habitat
search lines for
search area
t(1)
reference longitude
for search area t(1)
reference longitude
and parallel lines for
search area t(2)
reference longitude
and parallel lines for
search area t(3)
southern limit of habitat
3rd arc defining northern and
southern extent of search
area t(3)
Figure 2
Definition of terms used to describe the PSAT Tracker algorithm. A search area is a region in a satellite
thermal image where a search is conducted for pixels whose temperature values match those recorded by
the tag at that time and when it is at the surface. The search area consists of a reference longitude line,
defined by the daily calculation of latitude provided by the manufacturer's processed data record and par-
allel search lines that provide a hedge on this determination. The search area is uniquely defined by the
time at which this calculation was determined. The northern and southern bounds of the search area are
determined by either the habitat range or the maximum distance that the tagged fish can swim during
each time step. Those pixels underlying the reference and search line, whose temperature best match the
temperatures of the selection set of points from the tag, are chosen as candidate points. One candidate point
from each search area will eventually define the best track.
speed of the fish. The latitudinal bounds of the daily
search area are constrained in two ways, by the known
(or unknown) bounds of the fish's habitat and by its
maximum swimming speed. The northern and south-
ern bounds of the habitat are entered by the user, and
no areas are searched that are beyond these latitudes.
These values are meant to be inclusive and can be
determined from the literature or estimated by using
latitude values provided by light-based geolocation algo-
rithms. These bounds are set prior to processing and do
not change throughout the processing; in this study the
latitude search area was restricted to waters between
15 and 50 degrees north.
Each search area is centered on the light-based lon-
gitude estimate (termed the reference longitude). PSAT
Tracker does not search every pixel of SST data for
matches, but instead searches along parallel lines of
longitude on either side of, and including, the reference
longitude. These lines, termed search lines, are spaced
at equal distances from the reference longitude (Fig. 2).
The user establishes the extent to which PSAT Tracker
searches to the east and west of the reference longitude
by choosing the number of search lines as well as their
distance of separation. In this study four search lines
were drawn on either side of the reference longitude;
these parallels were drawn 5 nmi apart resulting in a 40
nmi wide daily search area. We refer to each search ac-
cording to the time at which the reference longitude was
determined, t(i) (where t is the time for which the refer-
ence longitude was determined and ; is the index for the
sequence of daily search areas in the time series).
The maximum swimming speed of the fish can also
constrain the latitudinal bounds of a daily search area.
The farthest a fish can swim in a given time interval is
simply the product of its maximum swimming speed and
the length of the time interval. Thus, all possible posi-
Domeier et al.: Tracking Thunnus thynnus onentalis with the aid of an automated algorithm
297
tions that a fish can occupy when swimming in a fixed
direction from the starting point of a track is the locus
of points forming a circle whose center is at the starting
point and whose radius is the product of its maximum
swimming speed and the length of the time interval.
Likewise, the farthest positions from which a fish can
swim in given direction and reach the end point of the
track is the locus of points forming a circle whose center
is at the end point and whose radius is the product of its
maximum swimming speed and the length of the time
interval. The intersection of loci originating from either
the start point or end point with a reference to longitude
defines the most northern and southern extent of the
search area for that reference longitude.
Because the distance of arcs whose center lies at the
start point increases with time, whereas the distance of
arcs whose center lies at the end point decreases with
time, the latitudinal range of the search area is usually
smallest at the start of the time series and at the end of
the time series and is usually largest midway through
the time series. The long time series obtained from
the recovered archival tags creates a situation where
the latitudinal extent of the search areas is largely
determined by the northern and southern bounds of
the habitat rather than by swimming speed. Swimming
speed does, however, constrain east-west movement on
a daily basis because the reference longitudes anchor
the search areas.
Step 2: Selection sets for tag data The second step
of processing involves selecting SST records (from the
tag data set) that are coincident in time with the daily
search area. The user can define the sea surface layer
by entering a maximum depth of this layer; for this
study the surface layer was defined as 0-1 m. The user
can also determine how many values from the selection
set should be used to search for SST matches. We chose
a selection set consisting of three individual values
for PSAT tags; however, because of the much higher
frequency of measurements from the archival tags, we
chose a selection set that consisted of a single average
SST value for each day. The temperatures found in the
selected set of points for a given daily search area would
be used to calculate the location of pixels within the
search area that the tag most likely visited.
Step 3: Choosing candidate points Selecting candidate
points from which a best track will be chosen begins by
assigning a temperature cost to pixels within the search
area. The temperature cost for a given pixel, j, with a
search area referenced by time, t{i), AT\J, Hi)], is simply
the absolute value of the difference in its temperature,
Tsatij, t(i)), and that of its closest match, k, from the
selected set of tag points, Ttag\k, Hi)]:
AT[j,t(i)} = \Tsat[j,tii)-Ttag[k,t(i)]]\.
The temperature cost, AT \j. Hi)], is an inherited trait
of a pixel and will be applied to all further calculations
of the best track(s). If the temperature cost of any pixel
examined in a search area exceeds the cutoff value
entered by the user, that pixel will be removed from
further consideration. Pixels will also be removed if
they lie over land.
Those pixels that remain are next subjected to an
evaluation to determine if they qualify as candidate
points. This evaluation is based upon the value of a cost
function that weighs both the pixel's temperature cost
described above, AT[j, t{i)], and the pixel's contribution
to spreading coverage over the search area:
Cost[jMi >] = AT[j,t(i)] + Spread Factor x AL[j,t( i >].
AL [j, Hi)] is the relative contribution a pixel makes to
providing even latitudinal distribution along the refer-
ence longitude and search lines of the daily search area;
the Spread Factor weights the relative importance of
temperature costs with the benefit of obtaining an even
distribution. Although the primary criterion for selecting
candidate points is how well tag SST matches satellite
imagery SST, we have found that this criterion alone can
cause all the selected candidate points to be bunched
together. Such aggregation will force the computed track
into small regions of the search area without regard
to the distribution of matching pixels in proceeding
or succeeding search areas. To avoid this problem the
Spread Factor function spreads candidate points in a
north-south direction thereby providing smoother and
more economical tracks. The degree to which the Spread
Factor function spreads candidate points is controlled by
the user by entering a weighted value. For this study we
chose an intermediate value (5000 out of a possible 9999)
and this value was constant for all evaluations.
The number of candidate points finally determined is
determined by the user. For this study, five candidate
points were identified for each search area. When the
user defines the number of points to be evaluated in the
search areas, pixels having the lowest cost are ranked
and selected accordingly.
Step 4: Enumerate and calculate the cost of arcs After
the candidate points have been chosen, the best track! s)
is computed by choosing a single candidate point from
each of the daily search areas in the time series. The
best track is selected from all possible tracks by choosing
the one of least cost. Thus, the solution is global rather
than serial. The computation begins by calculating the
cost of arcs between candidate points from adjacent
search areas, and ends by summing the cost of all the
arcs of a given track (Figs. 3 and 4).
The cost of an arc is a function of the temperature
match for the pair of candidate points that define the
arc, AT\j, t(i)\ and AT[k, t(i+D], as defined above. It also
depends upon the minimum swimming speed required
of the fish traveling between the two candidate points,
arc velocity min, where
arc velocity min
distance between candidate pixels
{t(i + l)-t(i))
298
Fishery Bulletin 103(2)
candidate point [j, t(i)]
with inherited
temperature cost
ATQ, t(i)]
enumerate all
possible Arcs between
consecutive search
areas
arc D.t(l) >[k.t(l+1>]
whose cost is a
function of distance
and temperature costs
candidate point [k,t(h
with inherited
temperature cost
AT|j,t(i+1)]
11]
End
Figure 3
Enumerating and costing arcs. An arc is defined as the arc between any two candidate points
of adjacent search areas. The cost of an arc depends upon the temperature cost, AT, of the two
candidate points of the arc. It is also depends upon the swimming speed required to travel
the distance of the arc.
The cost of the arc between candidate point j and can-
didate point k is
arccost({j,t(i)}->{k,Hi + l)}) = {AT(j,t(i)) + AT(k(t,i + l)) +
DistFactorl -
velocity
where velocity = the maximum sustained swimming
speed of the fish; and
DistFactor = a factor that scales the cost of swim-
ming at a given speed in relation to
the sum of the temperature costs of
the two candidate points.
Values for the DistFactor and Velocity are determined
by the user. The rationale for such cost is that the best
track should include an assessment of variations in
swimming velocity as well as the costs of temperature. If
swimming speed is judged to be an insignificant cost or
too difficult to quantify, the DistFactor can be set to 0. If
a land barrier lies between the pair of candidate points,
the distance to swim around the barrier is calculated and
included in the cost of the arc. In this study an interme-
diate value (5000 out of 9999) was assigned for the Dist-
Factor, and this value was constant for all evaluations.
Step 5: Calculating the best track Finally, the algorithm
calculates the sum of the arc costs for each track:
Cost of tract = £ g£, arccost({j,t(i)}- > {k,t(i + l)}).
The costs for all possible tracks are then ranked, and
the track(s) with the lowest cost(s) is then saved and
available for display (Fig. 4). The track is saved in a
table of the PSAT Tracker database; the table contains
records of the latitude, longitude, time, and surface
temperature of the candidate points that comprise the
track, as well as records of surface temperature from
the satellite imagery at regular intervals along the arcs
between candidate points. Depending on the length of
the time series, this process analyzes tens of thousands
to hundreds of thousands of tracks and thus is the most
time-consuming step of the algorithm.
Analyzing position data from PSAT Tracker
Location estimates provided by PSAT Tracker were
subjected to spatial analysis to describe the move-
Domeier et al.: Tracking Thunnus thynnus onentalis with the aid of an automated algorithm
299
End
Tstart > t(1), t{1) > t(2),
T(2) > t (3), t(3) > end
Figure 4
Diagram to show how the best track is calculated by summing the cost of arcs for
all possible paths and then choosing the track of least cost.
merit patterns and habitat use of Pacific bluefin tuna
in the eastern Pacific. Monthly data were combined
within each tag data set prior to performing utilization
distribution analyses with the Home Range Exten-
sion for ArcView (version. 1.1c, BlueSky Telemetry,
Aberfeldy, Scotland) that employs the fixed kernel
method (Rodgers and Carr, 1998). Results were dis-
played as volume contours displaying the main centers
of activity for each fish during a given time period.
Initial analyses allowed us to combine data so that
figures could be minimized. For the archival tag data,
consecutive months with similar spatial distribution
were combined and individual fish with very similar
tracks were combined. All data from fish that were
PSAT tagged were combined by month because of the
relatively sparse data compared with the data from
the archival tags. PSAT tag data provided a glimpse at
year-to-year variations in bluefin distribution (August
2000 through October 2002), whereas the archival tag
data were for a single year and allowed for a monthly
comparison within one year (August 2002 to Septem-
ber 2003).
The near daily position data provided through the
PSAT Tracker analyses allowed us to calculate the
swimming speed of each fish. This was done by simply
dividing the horizontal distance between consecutive
data records by the time between consecutive data re-
cords ( 1-4 days).
Results
Tag recoveries
Fifteen of the PSAT tags transmitted data after remain-
ing on the fish from 2 to 191 days (Table 2). Unfortu-
nately some of these tags did not transmit usable data.
Fourteen of them provided a pop-up location and eleven
of them transmitted enough data for some level of analy-
ses of behavioral and movement patterns. The Microwave
Telemetry PSAT tag provided an archival data set with
a one-hour sampling schedule. The Wildlife Computer
PSATs transmitted data summaries that included a
daily water column profile of temperature (obtained from
the deepest dive) and the percent time each fish spent
within predetermined temperature and depth bins.
Four archival tags were recovered after a period at
liberty of 16 hours to 385 days (Table 2). The 16-hour ar-
chival tag recovery was made from a recreational angler
very near the point of release; this tag was not used for
any analyses. The three tag recoveries made after 300
days came from a purse-seine vessel. Two of these three
recaptured fish spent several weeks in a grow-out pen
before the tags were discovered; the dates the fish were
in the pen were not used for any analyses. The light
stalks of tags 441 and 159 were damaged during recov-
ery. For these tags, the internal temperature and pres-
sure sensors were verified by Lotek data, but external
300
Fishery Bulletin 103(2)
temperature and light level sensors could not be checked.
For tag 233, none of the sensors could be verifed because
the tag had to be disassembled and destroyed by Lotek
personnel in order to recover the data.
Table 2
Details of tagged Pacific bluefin tuna (Thunnus thynnus
orientalist. WC=Wildlife Computer Tag, MT= Microwave
Telemetry Tag, Lot=Lotek Tag).
Fish
Tag date
Weight
(kg)
Time at
liberty (days)
4WC
13 August
2002
36
23
184 WC
13 August
2002
60
62
200 WC
13 August
2002
41
51
245 WC
2 August
2000
51
19
247 WC
2 August
2000
57
38
249 WC
2 August
2000
50
102
265 WC
2 August
2000
52
33
301 WC
2 August
2000
60
191
961 WC
3 August
2001
32
9
962 WC
3 August
2001
35
4
964 WC
3 August
2001
35
23
1041 WC
3 August
2001
26
2
1042 WC
2 August
2000
42
72
283 MT
13 August
2002
41
61
114 Lot
13 August
2002
52
16 (hours)
159 Lot
13 August
2002
52
375
233 Lot
14 August
2002
43
385
441 Lot
30 August
2002
12
323
50 -I
40-
30-
20-
T3
i io-
to
t^
III I '
I \ r-J
A
Fish 19203
Fish 19368
€ o-
o
z
-10-
!
!J
"Fish tracker latitude
-20-
!i
i'
_ . _
- Wildlife computer latitude
-30-
\
- Microwave telemetry latitude
4-Aug-00 c
28-Aug-OO
21-Sep-00
15-Oct-00
8-Nov-00
2-Dec-00
26-Dec-OO
19-Jan-01
20-Aug-02
13-Sep-02
7-Oct-02
Figure 5
PSAT Tracker SST-based latitude solutions vs. Wildlife Computers
and Microwave
Telemetry
light-based latitude estimates.
PSAT Tracker algorithm
The archival tags provided large data sets that allowed
for the comparison of the PSAT Tracker algorithm to
the manufacturer's light-based geolocation solution.
Because longitude estimates generated by PSAT Tracker
are constrained by the light-based estimates, these
values differed very little from the position estimates
from the various tag manufacturers. Although similar,
the PSAT Tracker latitude solutions were generally less
erratic than those produced from the three light-based
algorithms, particularly surrounding the times of the
equinoxes (Figs. 5 and 6). The spring and fall equinoxes
each produced approximately two months of unreliable
latitude estimates for light-based algorithms.
Pacific bluefin tuna habitat use
Horizontal movement Tagged bluefin tuna ranged as
far north as the California-Oregon border and nearly to
the tip of Baja California, Mexico, to the south. Although
this distance encompasses 2400 km of coastline, these
fish spent the majority of their time in the southern part
of the range, best illustrated by a home range analysis
of the combined approximately year-long tracks of the
three archival tagged bluefin (Fig. 7). Tagged off the
northern coast of Baja California, Mexico, these three
bluefin moved northward until November, followed by a
southward migration to south-central Baja California
where they spent the months of January through June
(Fig. 8). The two larger archival-tagged fish reached
the offshore waters of Oregon before turning south and
the smaller fish did not venture north of San Francisco,
California. The two larger fish spent much of the winter
and spring (January-June) in the coastal
bight between Punta Eugenia, Mexico, to
the north and Cabo San Lazaro, Mexico, to
the south, and the smaller fish had a more
dispersed spring range north of Punta Euge-
nia. In July all three fish began to move to
northern Baja, back into the general area
where they were originally tagged and where
they were subsequently recaptured (Fig. 8).
This general pattern of summer-fall move-
ment northward followed by a winter migra-
tion southward and a winter-spring holding
pattern off south-central Baja California was
supported by data from fish with PSATs in
years 2000 through 2002 (Fig. 9).
Although position data for the months of
January through June generally placed the
tagged bluefin off southern Baja, two of the
three fish tagged with archival tags under-
went rapid April excursions to the north be-
fore returning to the south (Fig. 10). Fish 159
traveled 2130 km, one way, before return-
ing by 1 May; fish 441 made a similar move
but did not go as far north (1285 km) and
stopped its southward return 480 km north
of its original starting point. The extreme
Domeier et al.: Tracking Thunnus thynnus onentalis with the aid of an automated algorithm
51)1
northern latitude estimates calculated
by PSAT Tracker placed fish 441 slightly
north of Point Conception, California,
and fish 159 near the California-Oregon
border before it returned to wintering
grounds off Baja California (Fig. 10).
This movement is corroborated by a
westerly trend in longitudes and a dra-
matic drop in SSTs. For fish 159, SST
dropped from 19. TC on 4 April 2003 to
12.4°C on 18 April 2003. Similarly, fish
441 experienced an SST drop from 19.5°
to 13.5°C between 1 and 18 April.
Data from the archival tags provided
near daily positions for each fish. The
longest time between successive fixes
was four days. The calculated swim-
ming speeds between successive posi-
tion fixes ranged from 0 to 14.7 knots
for all three fish combined. The mean
swimming speed for all three fish was
1.3 knots (±1.3 km.
Depth and temperature ranges Vertical
movement was similar to that reported
for other bluefin tuna (Block et al., 1997; Block, 2001;
Kitagawa et al., 2004). Detailed analyses of vertical
movement and temperature preferences and tolerances
are beyond the scope of this article and will be pre-
sented in a future publication. In general, dives were
most common during the day; maximum dive depths
ranged from 341 to 382 m. Fish with archival tags
spent nearly 70. 1% of the time near the surface (<20 m
deep). Ambient water temperatures ranged from 5.7°
to 25.0"C (mean=17.4°C). The internal temperature
offish tagged with archival tags ranged from 14.1° to
29.5 C (mean=21.8°C); average internal temperatures
of the fish were 4.4°C warmer than ambient waters
and at times were up to 19.2°C warmer.
Discussion
Although we used SST matching as the sole means
of estimating latitude for the fish tracks and spatial
analyses presented in our study, the extent of the
northward fall migration of juvenile Pacific bluefin
tuna in the eastern Pacific has been corroborated by
occasional commercial landings of Pacific bluefin tuna
in Oregon (McCrae3). Because Pacific bluefin tuna
are apparently capable of existing in the northern
part of the eastern Pacific range, even during the
colder months of the year, it is not clear what dictates
the movement pattern of these fish. It is reasonable
to speculate that the tuna are taking advantage of
seasonal ocean warming to exploit distant prey when
the physiological expense to maintain optimum body
50 -i
30 ■
^ W
■V*
***VjL-
/K
20 -
CD
■o
Fish 159
— — v
— ,
-m \xfsh&&*
S 10 -
CO
€ -30-
o
z
-50 -
Fish tracker latitude
-70 -
i i i
■
1
i i ■
1 '
CNJ CN CM
O O O
C\J C\J CO
o o o
CO
o
CO
o
CO CO CO
o o o
CO CO
o o
Aug
Sep
-Oct
Nov
Dec
Jan
CD
LL
ro
r-
-Apr
May
■Jun
1 1
CO CO 2
CD CD ^
CD
CO
CD ^ CD
T- CD
Figure 6
PSAT Tracker SST-b
ased latitude so
utions and Lotek light-based lati-
tude estimates.
3 McCrae, J. 2004. Personal commun.
Fish & Wildlife, Newport, OR 97365.
Oregon Dept.
Figure 7
Fixed kernel home range analysis illustrating relative
importance of the range of juvenile Pacific bluefin tuna
{Thunnus thynnus orientalist in the eastern Pacific; dis-
played are all points for fish 159, 233, and 441 and volume
contours of 95% (outer line) and 50% (inner line) for all
three fish combined. Isolated circle to the north is a 95%
contour.
302
Fishery Bulletin 103(2)
Oct-Nov
441 range
▲ deployment point
X recapture point
Figure 8
Grayscale contours of seasonal spatial use and movement
pattern for fish 159 and 233 combined, displaying "core areas"
of use represented by volumes of 10-50% . The smaller total
range of fish 441 is illustrated by the polygon.
temperature is less. Temperature and depth tolerances
and preferences indicated in our study are similar to
those of bluefin tuna studied in other parts of the world
(Carey and Teal, 1969; Carey and Lawson, 1973; Block
et al., 1997; Kitagawa et al., 2000, 2004; Block et al„
2001; Brill et al., 2002; Itoh et al., 2003b).
The migration of a fish with an archival tag from the
western Pacific to the eastern Pacific (Itoh et al., 2003a)
provides an interesting comparison to our data. This
individual, tagged off Japan, made the trans-Pacific
migration in about two months and then resided in
the eastern Pacific for about eight months before being
recaptured by a recreational angler. The fish arrived off
the coast of northern California in the month of Janu-
ary— a time when fish from our study were found to be
at the southern extreme of their eastern Pacific range.
By the month of March, the western Pacific migrant
had traveled to the winter-spring grounds where it
then seemed to behave in a pattern similar to that of
fish tagged for our study. Whether or not the Itoh et al.
(2003a) tagged fish illustrated a typical transition from
trans-Pacific migrant to eastern Pacific resident will
require more tag recoveries. It will be equally interest-
ing to see future descriptions, from archival-tag data,
of maturing Pacific bluefin tuna making the trip back
to the western Pacific.
Two of the Pacific bluefin tuna with archival tags
were captured and recaptured in very close proximity
in both space and time of year. The computed tracks
for these two fish, both relatively large for the eastern
Pacific, also showed that they kept close to each other
for most of the year. A smaller fish, tagged a month
later, underwent a similar north to south movement,
but did not range as far north, particularly, or south.
Given our extremely low sample sizes, very little can be
concluded, but the question is raised as to whether or
not Pacific bluefin tuna of different year classes have
distinct schools and migratory behaviors. It is also im-
portant to point out that the two larger fish were tagged
in the dorsal musculature, whereas the smaller fish was
tagged in the peritoneal cavity. The orientation of the
light stalk is different for these two methods, one point-
ing towards the surface and the other in the shadow of
the fish and pointing down. How this tag orientation
may influence the detection of light and subsequent
position estimates is unknown.
Two of our fish with archival made rapid northward
migrations into much colder water in the early spring.
This northward migration is similar to that made by
Itoh's fish in the early spring of 1998. Because these
movements occurred at a time when the light-based
latitude estimates prove unreliable, it would not have
Domeier et al.: Tracking Thunnus thynnus onentalis with the aid of an automated algorithm
303
~J August
September
7J October
~J November
December
~J January
Figure 9
Positions for eleven Pacific bluefin tuna {Thunnus thynnus orien-
talis) tagged with satellite pop-up tags from 2000, 2001, and 2002
showing the 100% minimum convex polygon for fish positions within
a given month.
been possible to be certain that this rapid excursion was
authentic without the aid of SST matching (as was also
done by Itoh et al. [2003a]).
The PSAT Tracker algorithm provided relatively quick
and automated geolocation estimates for data recovered
from three separate types of tags deployed on Pacific
bluefin tuna. Furthermore, the PSAT Tracker latitude
solutions compared favorably to the light-based latitude
estimates during non-equinox times of the year. The use
of SSTs to resolve latitude allowed for spatial analyses
of individual bluefin positions for every month of the
year, whereas a strictly light-based approach would not
provide reliable latitude position estimates for approxi-
mately 30% of a year-long track. PSAT Tracker also
results in a global, rather than serial track solution.
In essence this means that no single position estimate
is selected without regard to the influence this position
has on the overall track. A serial track is one that is
produced by selecting each position without regard to
the effect each selection has on the overall track. A se-
rial track is also heavily biased by the start point and
may weight the location estimates based upon the pre-
vious location estimate, allowing a single poor location
estimate to ruin the remainder of the location estimates
for the track.
It is instructive to compare our SST matching algo-
rithm to the Kalman filter-based algorithm developed
by Sibert et al. (2003). The Sibert et al. algorithm
depends solely upon light data collected by the tag to
estimate latitude and longitude, whereas the PSAT
Tracker algorithm depends upon the light field to pro-
vide an estimate of longitude and solely upon the sea
surface temperature to provide an estimate of lati-
tude. The initial estimates of both approaches are then
refined according to a goodness-of-fit criterion that
depends upon assumptions regarding the swimming
behavior of the tagged fish. In the case of the Sibert
et al.'s algorithm, the behavior of the fish is modeled
in terms of a biased random walk model that describes
the movement of the fish in terms of an advection-
diffusion equation; the advective term describes the
most probable displacement of the fish during a time
step and the diffusive term describes the distribution
of less likely displacements. The usefulness of the ran-
dom walk model is largely determined by the adequacy
of describing the distribution of swimming speed and
direction of the fish. The algorithm also includes for-
mulations of the dependence of the accuracy and pre-
cision of the estimates of latitude and longitude from
the tag upon other factors. For example, around the
equinox the weighting of the estimate of latitude from
the tag measurements is greatly reduced (specifically
an inverse cosine squared function of date.) The Sibert
et al. algorithm simply searches for a track that mini-
mizes discrepancies between the positions predicted
from random walk model (the transition equation) and
those predicted from the tag measurements (the mea-
surement equation).
304
Fishery Bulletin 103(2)
40.00
35.09)
-130.00 >k
-125i0 y^
30.00 \
-120.00
-115.00
25.00
<]
W%
Figure 10
Track showing northward excursions of fish 159 (track extending to 38°) and
441 (track extending to 34.5°) between 1 April and 10 May 2003. Displayed SST
imagery is a composite for the month of April showing a 7°C temperature gradient.
PSAT Tracker is similar to the Sibert et al. algorithm
in that it invokes a model of fish behavior; there is a
simple constraint on the maximum distance that a fish
can swim during a time step, and shorter tracks that
require lesser expenditures of energy by the fish are
favored. Like the Sibert et al. algorithm, the PSAT
Tracker also incorporates candidate points that are not
limited to the initial light-based estimate of longitude
but includes adjacent longitudes based upon the user's
assessment of the accuracy of the initial estimate. Fi-
nally, both the Sibert et al. and the PSAT Tracker al-
gorithms yield a solution that provides a best fit to the
time series of satellite (in the case of PSAT Tracker)
and tag measurements to the model of fish behavior.
Unfortunately, it is difficult to make a general assess-
ment of the accuracy of either approach. In the case of
the PSAT Tracker algorithm, the accuracy of the track
will decrease in the absence of a north-south tempera-
ture gradient. We have not found a means of quantita-
tively determining the accuracy of PSAT Tracker cal-
culations. However, the quality of the fit between pixel
values of temperature from imagery and tag values for
positions along the track is calculated as a x2 value. In
the case of the Sibert et al. algorithm, the accuracy of
the track will decrease during the period of the equinox
when the latitudinal errors of the light-based estimates
are extremely large. Our data indicate that this period
can be as long as two months surrounding each equinox
(skewed towards winter). At such times the estimates of
position derived by the Sibert et al. algorithm depend
largely on the random walk model of fish movement,
which provides only a generic description of movement.
Although the algorithm provides values for the mean
square errors of bias and randomness for the tag es-
timates of latitude and longitude, these values are not
true values for error of predicting location; rather they
represent of the discrepancy between the estimates of
position by the random walk model, the formulation
of the latitude estimation error, and the tag measure-
ments. Additionally, the Sibert et al. algorithm does not
exclude the possibility of placing a fish on land.
The PSAT Tracker worked well for this study because
of the strong north-to-south temperature gradient that is
presented in the northeastern Pacific. Studies conducted
in regions with poor temperature gradients will continue
to rely on light-based latitude estimates and approaches
like the Sibert et al. algorithm. Further development
of PSAT Tracker, or other SST-based geolocation al-
gorithms, should explore a means of using light-based
latitude positions in combination with SST matching
when light data are reliable, but excluding light-derived
latitude positions when they are unreliable.
Domeier et al.: Tracking Thunnus thynnus oriental* with the aid of an automated algorithm
305
Acknowledgments
This study was made possible through the support of
the George T. Pfleger Foundation and the Offield Family
Foundation. We thank those who helped us capture the
fish in our study: Tom Pfleger, Tom Fullam, Tom Roth-
erie, Greg Stutzer and Chugey Sepulveda. Archival tags
were recovered with the assistance of the Inter-American
Tropical Tuna Commission.
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307
Abstract— The gray snapper {Lutjanus
griseus) is a temperate and tropical
reef fish that is found along the Gulf
of Mexico and Atlantic coasts of the
southeastern United States. The rec-
reational fishery for gray snapper has
developed rapidly in south Louisiana
with the advent of harvest and sea-
sonal restrictions on the established
red snapper iL. campechanus) fishery.
We examined the age and growth of
gray snapper in Louisiana with the
use of cross-sectioned sagittae. A total
of 833 specimens, (441 males, 387
females, and 5 of unknown sex) were
opportunistically sampled from the
recreational fishery from August 1998
to August 2002. Males ranged in size
from 222 to 732 mm total length (TL)
and from 280 g to 5700 g total weight
(TW) and females ranged from 254 to
756 mm TL and from 340 g to 5800 g
TW. Both edge analysis and bomb
radiocarbon analyses were used to
validate otolith-based age estimates.
Ages were estimated for 718 individu-
als; both males and females ranged
from 1 to 28 years. The von Berta-
lanffy growth models derived from
TL at age were L, = 655.4ll-e[-°-23((|l|
for males, L, = 657.3{l-el-° 21l"l| for
females, and L , = 656.4)l-e[-° 22"l|l
for all specimens of known sex . Catch
curves were used to produce a total
mortality (Z) estimate of 0.17. Esti-
mates of M calculated with various
methods ranged from 0.15 to 0.50;
however we felt that M=0.15 was the
most appropriate estimate based on
our estimate of Z. Full recruitment to
the gray snapper recreational fishery
began at age 4, was completed by age
8, and there was no discernible peak
in the catch curve dome.
Age, growth, mortality, and
radiometric age validation of gray snapper
{Lutjanus griseus) from Louisiana
Andrew J. Fischer
Coastal Fisheries Institute
School of the Coast and Environment
Louisiana State University
Baton Rouge, Louisiana 70803-7503
E-mail address: afischeigilsu.edu
M. Scott Baker Jr.
North Carolina Sea Grant
UNC-W Center for Marine Science
5001 Masonboro Loop Rd
Wilmington, North Carolina 28409
Charles A. Wilson
Louisiana Sea Grant College Program
Louisiana State University
Baton Rouge, Louisiana 70803-7507
David L. Nieland
Coastal Fisheries Institute
School of the Coast and Environment
Louisiana State University
Baton Rouge, Louisiana 70803-7503
Manuscript submitted 19 September 2003
to the Scientific Editor's Office.
Manuscript approved for publication
20 November 2004 by the Scientific Editor.
Fish. Bull. 103:307-319 12005).
The gray snapper {Lutjanus griseus),
commonly referred to as the mangrove
snapper, is a temperate and tropical
reef species that is found along the
southeastern Atlantic coast of the
United States from North Carolina
to Bermuda, throughout the Gulf of
Mexico (GOM), and south to Brazil
(Johnson et al., 1994; Allman and
Grimes, 2002). Gray snapper are
fairly common along the Louisiana
coast and are usually associated
with complex structures such as oil
and gas platforms, artificial reefs
and other hard bottom substrates.
In 1991 restrictions were put on the
recreational red snapper (Lutjanus
campechanus) fishery; these restric-
tions coincided with a rapid expansion
of the gray snapper fishery in south
Louisiana. Recreational anglers now
typically target gray snapper once
they have reached their bag limit of
red snapper; thus peak gray snap-
per landings generally coincide with
the red snapper recreational season
(April-October). As a result, recre-
ational landings of gray snapper in
Louisiana have increased exponen-
tially from 3.25 metric tons (t) in 1983
to 175 t in 2002 (NMFS1). Currently
there is a 305 mm (12 inches) mini-
mum size and a recreational bag limit
of 10 fish/person/day for gray snapper
in the GOM.
Some background information is
available for gray snapper in the
southeastern United States, mainly
from south Florida. Scientists have
reported on early life history (Ruth-
1 NMFS (National Marine Fisheries
Service). 2003. Fisheries Statistics
and Economics Division. Unpubl.
data. Website: http://www.st.nmfs.
gov/pls/webpls/MF_ANNUAL_LAND-
INGS. RESULTS. [Accessed 25 August
2003.]
308
Fishery Bulletin 103(2)
erford et al., 1989; Domier et al.. 1997), population
dynamics (Rutherford et al., 1989), juvenile food hab-
its (Hettler, 1989), juvenile distribution (Chester and
Thayer, 1990), and reproduction (Domeier et al., 1997;
Allman and Grimes, 2002).
Few reports have been conducted on the age and
growth of gray snapper. Manooch and Matheson (1981)
used sectioned otoliths to age gray snappers from east-
ern Florida but did not validate their methods. Johnson
et al. (1994) also used sectioned otoliths to age fish
sampled from Fort Pierce, FL, to Grand Isle, LA, again
without validation of methods. Burton (2001) validated
the periodicity of opaque zone formation in gray snapper
from east coast Florida waters with the use of marginal
increment analysis of distal edge measurements. But
gray snapper have never been fully examined in the
northern GOM and comprehensive age, growth, and
mortality data from the thriving Louisiana recreational
fishery are virtually nonexistent.
The objectives of our study were to describe the age,
growth, and mortality of gray snapper from the Loui-
siana recreational fishery. We obtained age information
through examination of cross-sectioned sagittal otoliths,
validated our aging techniques with the use of bomb-
radiocarbon 14C and edge analyses, produced mortal-
ity estimates with standard procedures, and modeled
growth with the von Bertalanffy growth equation.
Methods and materials
Gray snapper were sampled from the Louisiana recre-
ational harvest from August 1998 to August 2002 by
personnel from the Louisiana State University Coastal
Fisheries Institute and the Louisiana Department of
Wildlife and Fisheries. Fish were opportunistically sam-
pled at charter boat facilities in Port Fourchon, LA, and
at spearfishing and hook and line fishing tournaments
in Grand Isle and New Orleans, LA. Morphometric
measurements (fork length [FL] and total length [TL]
in mm, total weight [TW] in g) were taken, sex was
determined by macroscopic examination of the gonads,
and both sagittae were removed, rinsed, and air dried,
weighed to the nearest 0.1 mg, and stored in coin enve-
lopes until processed. For specimens in which TL was
unavailable, TL was estimated from FL with the equa-
tion TL = 1.048(FL) + 8.35 (linear regression, df=275;
P<0.001; r2=0.98) calculated from specimens in which
both TL and FL were available.
In order to estimate age of gray snapper, a transverse
section (~1 mm thick) was taken containing the core
of the left sagittal otolith of each specimen. Sections
were made with a Hillquest model 800, thin-sectioning
machine equipped with a diamond embedded wafering
blade and precision grinder (Cowan et al., 1995). In in-
stances where the left otolith was unavailable, the right
was substituted. Examinations of otolith cross-sections
were made under a dissecting microscope with trans-
mitted light and polarized light filter from 20x to 64x.
Opaque zones were enumerated along the ventral side
of the sulcus acousticus from the core to the proximal
edge (Wilson and Nieland, 2001). Two readers (AJF
and MSB) performed opaque zone counts independently
without knowledge of capture date or morphometric
data. Otolith marginal edge condition was coded as
opaque or translucent by using the criteria described
by Beckman et al. (1989). Opaque zones were counted
a second time when initial counts differed. In instanc-
es where a consensus between readers could not be
reached, counts of the more experienced reader (AJF)
were used. Between-reader variation in opaque zone
counts was examined after the second readings of oto-
lith sections were completed. Differences in counts were
evaluated with the coefficient of variation (CV), index of
precision (D) (Chang, 1982), and average percent error
(APE) (Beamish and Fournier, 1981).
Ages of gray 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 365 ) +
{(.m-l)x30)+d,
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 of 1 July assigned
for all gray snapper to coincide with peak spawning
activity occurring in July (Domeier et al., 1997; Allman
and Grimes, 2002). Age in years was assigned by divid-
ing age (in days) by 365. Year of birth (YOB) was back
calculated by subtracting our otolith-based age esti-
mates from year of capture.
Validation of the periodicity of opaque zone forma-
tion in gray snapper otoliths was examined with two
approaches. An advanced and accurate method of age
validation uses a quantitative measurement of nuclear
bomb-produced radiocarbon (14C) that was accumulated
in carbon-containing hard parts of marine organisms
before, during, and after the atmospheric testing pe-
riod of nuclear weapons (1958-65) (Baker and Wilson,
2001). Elevated levels of 14C have been observed in
hermatypic corals (Druffel, 1980, 1989) and this time-
specific marker can be used to validate age estimates
derived from hard parts in marine fishes (Kalish, 1993;
Campana and Jones, 1998). Baker and Wilson (2001)
recently validated red snapper otolith section age esti-
mates using this technique with excellent results. This
same method was applied in our study to the otolith
cores of gray snapper hatched after the nuclear testing
periods.
Gray snapper hatched prior to 1973 were not avail-
able for our study, and thus the steepest portion of the
radiocarbon uptake curve could not be used to confirm
age estimates. Consequently, no coral reference data
for the general area were available after 1983. Because
red snapper otoliths have been previously validated
Fischer et al.: Age, growth, mortality, and radiometric age validation of Lut/anus griseus
309
with this same method (Baker and Wilson, 2001), we
anticipated that gray snapper radiocarbon values would
be roughly similar to red snapper values for a given
YOB.
To obtain the oldest portion of the otolith for radio-
carbon analysis, right otoliths of older gray snapper
with an estimated YOB after the period of atmospheric
testing (1973-95) were embedded in araldite epoxy
resin and thin sectioned (~1 mm in thickness) through
the core with an Isomet low-speed saw. The otolith core
region was isolated from the otolith section by using
the technique described in Baker and Wilson (2001).
Cores were rinsed in double-distilled de-ionized water,
allowed to air dry, weighed to the nearest 0.1 mg, and
submitted to the accelerator mass spectrometry (AMS)
facility in acid-washed 20-mL glass scintillation vials.
The mean sample weight submitted for analyses was
12.8 mg.
At the AMS facility, otolith cores underwent acid hy-
drolysis with 85% phosphoric acid to yield CO., which
was then made into graphite (pure C) by reduction at
high temperature under vacuum. The graphite was
pressed onto a target, loaded on the AMS unit and
analyzed for radiocarbon. Samples were also analyzed
for 13C to correct for natural and machine fractionation
effects. Radiocarbon values from individual otolith cores
were reported as A14C (mean ±SD), the adjusted devia-
tion from the radiocarbon activity of 19th century wood
(Stuiver and Polach, 1977).
The periodicity of opaque zone formation was also
examined with edge analysis. The marginal edge of
each otolith was examined and coded as
1 opaque zone forming on otolith margin;
4 translucent zone forming on margin up to 1/3 com-
plete;
5 translucent zone forming on margin 1/3 to 2/3 com-
plete;
6 translucent zone forming on margin 2/3 to fully
complete.
Percentages of otoliths with opaque margins were plotted
by month of capture (Beckman et al., 1989; Campana,
2001; Wilson and Nieland, 2001) for all months in which
specimens were available.
In order to examine the predictive capacity of otolith
weight (W0) to determine age in gray snapper, sex spe-
cific Wo-age relationships were fitted by using a power
function with least squares with the model: Age = aW0b.
A likelihood ratio test (Cerrato, 1990) was used to test
for differences between male and female models.
Male and female TW-TL relationships were indepen-
dently fitted with linear regression to the model W =
aTLh from log10-transformed data. Male and female re-
gression coefficients were compared with an ANCOVA.
Variability in age, TL, and TW-frequency distributions
of males and females were compared with Komolgorov-
Smirnov two-sample tests (Tate and Clelland, 1957;
Sokal and Rohlf, 1995). Growth of gray snapper was
modeled by using all specimens of known sex. Von Ber-
talanffy growth models of TL at age were fitted with
nonlinear regression by least squares (SAS 6.11, SAS
Institute, 1996, Cary, NO in the form:
TL,=LM
„l-*<nl
where / = age in years;
TL = TL at age t;
Lx = the theoretical maximum TL;
k = the growth coefficient.
and
Because of a lack of smaller individuals in our sample
population, no y-intercepts for t0 were specified and
models were forced through 0 (Szedlmayer and Shipp,
1994; Fischer et al., 2004) to better estimate juvenile
growth. One growth model was generated for all speci-
mens of known sex. Additional models were fitted inde-
pendently for males and females. Likelihood ratio tests
(Cerrato, 1990) were used to test for differences between
male and female models.
The instantaneous total mortality rate (Z) was esti-
mated from a catch curve (Nelson and Manooch, 1982;
Burton, 2001) assuming our collections represented the
actual age distribution of the population. These esti-
mates were made with the regression method of plotting
the logt, age frequency on age. We used the absolute
value of the slope of the linear descending right limb of
the curve after full recruitment to estimate Z.
Estimates of instantaneous natural mortality (M)
were computed with several methods. The first estimate
of M was based on Hoenig's (1983) longevity-mortality
relationship, where the mortality rate is based solely
on the oldest specimen encountered in the data set.
We also used Hoenig's (1983) relationship for natural
mortality with modifications for sample size. Natural
mortality was also computed with the method of Pauly
(1980) assuming a mean annual water temperature
of 25°C. Our mean annual water temperature esti-
mate was derived from the data buoys operated by the
National Oceanic and Atmospheric Administration's
National Oceanographic Data Buoy Center from 1995
to 2001. Finally, M was calculated with the Ralston
(1987) method, where the estimate of M is based solely
on a simple regression involving the Brody growth coef-
ficient (k). A significance level of 0.05 was used for all
statistical analyses.
Results
We sampled 833 gray snapper (441 males, 387 females,
and 5 individuals of unknown sex) from the recreational
fishery of Louisiana for morphometric data and otoliths.
The male:female ratio was 1:0.88; a x2 test indicated no
significant difference between the proportions of males
and females (/2=3.52> P=0.06). Male and female speci-
mens ranged from 222 to 732 mm TL and from 254 to
756 mm TL, respectively (Fig. 1A). Both sexes exhibited
multimodal distributions; males were represented in the
greatest numbers at 450 mm TL, compared to 400 mm
310
Fishery Bulletin 103(2)
J
I
■ Males
□ Females
ill
225 275 325 375 425 475 525 575 625 675 725
Total length (mm)
6 -i
5
4
B
■ Males
D Females
J
J
lllll lllllinl . .
200 800 1400 2000 2600 3200 3800 4400 5000 5600
Total weight (g)
Figure 1
Distributions of (A) total length in mm (n = 837) and (B) total weight
in g (/i = 832) for gray snapper (Lutjanus griseus) sampled from the
Louisiana 1998-2002 recreational harvest.
TL for females. A Komolgorov-Smirnov two-sample test
indicated no significant difference between male and
female TL frequencies (maximum difference=9.45). Male
and female TW ranged from 200 to 5700 g and 300
to 5800 g TW, respectively (Fig. IB). Both sexes also
displayed multimodal distributions in TW. A Komol-
gorov-Smirnov two-sample test indicated a significant
difference between sexes at 1600 g TW (maximum dif-
ference=9.67). A single predictive TL-TW regression was
generated for both males and females:
TW = 3. .31 x 10-5 (TL285)
(Fj 822=9,326.54; P<0.001; r2=0.92).
Significant differences were found between sexes in
TL-TW relationships (ANCOVA test of homogeneity of
slopes, F3 822=7.25; P=0.007; r2=0.92). Therefore, sepa-
rate models were fitted for each sex:
Males
2.04 x 10 -B(x2-93)
7588.29; P<0.001; r2
TW
(^l,436
Females = TW = 5.5 x 10-5(7/L277>
= 0.95)
Gray snapper otoliths are very similar in physical struc-
ture, although much smaller in actual size, to those of
the red snapper. Opaque zones are easily distinguishable
on the ventral side of the sulcus groove (Manooch and
Matheson, 1981; Johnson et al., 1994; Shipp2) (Fig. 2,
A and B).
Sagittae were collected from 721 gray snapper of
which 718 were aged. Readers were unable to resolve
opaque zones in three otolith sections because of poor
sectioning. Readers agreed on the ages of 568 indi-
viduals (78.8%) after initial counts and differed by one
opaque annulus for 154 specimens, two annuli for 18
specimens, and three annuli for 2 specimens. Readers
agreed on 709 ages (98.7%) after the second reading.
The average percent error (APE) was 0.5, coefficient of
variation (CV) was 0.00078, and index of percent (D)
was 0.0006.
cf,
385
= 3,089.16; P<0.001; r2=0.89>
2 Shipp, R. L. 1991. Investigations of life history parameters
of species of secondarily targeted reef fish and dolphin in
the northern Gulf of Mexico. Proc. Fourth Annu. MARFIN
Conf., San Antonio, TX, p 80-85. [Available from National
Marine Fisheries Service, State/Federal Liaison Office, 9721
Executive Center DR. N., St. Petersburg, FL 33702.1
Fischer et al.: Age, growth, mortality, and radiometric age validation of Lut/anus gnseus
311
Figure 2
(A) Transverse section of a gray snapper (Lutjanus griseus) otolith with
first opaque zone distant from the core, with 10 opaque zones and an edge
condition of 4 and (B) transverse section of a gray snapper otolith with first
opaque zone close to the core, with 8 opaque zones, and an edge condition
of 4. D indicates dorsal side and V indicates ventral side of otolith section.
Table 1
List of gray
otolith sepai
length. I.D.=
snapper {Lutjanus griseus) otoliths analyzed for stable carbon and bomb radiocarbon. "AMS wt
•ated from the otolith section and submitted for accelerator mass spectrometry (AMS) radiocarbon
= our identification number.
" is the
analysi
amount of
3;FL=fork
NOS-AMS
number
ID.
Date
caught
Otolith
section
age (yr)
Birth
date
Otolith
wt.
(mg)
AMS
wt.
(mg)
(%o)
AUC {'',,
Mean
±SD
OS-36337
320
2001
28
1973
639.1
9.9
-2.67
142.8
9.7
OS-36338
33
2000
25
1975
635.2
14.7
-2.55
126.2
6.7
OS-36339
5
2000
20
1980
536.7
15.0
-3.34
115.3
6.5
OS-36340
322
2001
16
1985
414.6
15.1
-5.27
113.5
11.9
OS-36341
316
2001
11
1990
306.5
9.8
-4.49
91.4
6.1
OS-36342
304
2001
6
1995
154.0
12.2
-5.73
74.5
5.9
The gray snapper (n = 6) used for the radiocarbon
age validation procedure ranged from 6 to 28 years
of estimated age and were collected during 2000 and
2001 (Table 1). Furthermore, YOB ranged from 1973
to 1995. Gray snapper radiocarbon values were plotted
along with red snapper radiocarbon values from the
northern Gulf of Mexico (Baker and Wilson, 2001) and
coral radiocarbon values from Bermuda (Druffel, 1989),
South Florida (Druffel, 1989), and Belize (Druffel, 1980)
(Fig. 3). Radiocarbon values of gray snapper cores were
312
Fishery Bulletin 103(2)
150 -
I
*°S»I »x ." 28yr a
100 -
o
a° a" f """U 25 yr ■
x • i J « 2°y m.
x5 • J I J 16yr "■
pyr.
i 50-
Q
X
° Bermuda
°°° x South Florida
x ° Belize
j ^o ° L eampeehanus
0 -
I ♦ L griseus
„« ■ Collection Date
-50 -
1950 1960 1970 1980 1990 2000 2010
Date of calcification (A.D.)
Figure 3
Plot of radiocarbon ( 14C ) values versus date of calcification for gray snapper
(Lutjanus griseus) (present study) and red snapper [Lutjanus eampeehanus)
(Baker and Wilson, 2001) from the northern Gulf of Mexico and from corals
off Bermuda ( Druffel, 1989 ), South Florida ( 1989 ), and Belize 1 Druffel, 1980 ).
Solid squares ■ indicate collection dates for the gray snapper samples
Oi=6) and the age listed are the estimated ages as read from the otolith
sections.
1 2
80 ■
Opaque
o
o" 40 •
60
20 J
\
\206
\n3 160 82 35 83
JFMAMJJASOND
Month
Figure 4
Marginal edge analysis of gray snapper (Lutjanus griseus) otoliths sampled
from the 1998-2002 Louisiana recreational harvest (n=718). Numbers above
data points indicate the number of otoliths analyzed for each month.
Fischer et al.: Age, growth, mortality, and radiometric age validation of Lut/anus gnseus
313
16 -
A
14 -
■ Males
12 -
□ Females
£. 10 -
"
Frequency
1
1
■
4 -
j~
li
1
2 -
j
H
1 ■"h-L_ rr
0 -
,i
1
1
ii
ilkJIki r* ru^^mn
~ r~ ii i i i i i i i i i i i i i i i i i i i i
1 3 5 7 9 11 13 15 17 19 21 23 25 27
Age (yrs)
25 -J
B
20 ■
£, 15 -
Percent
o
5 •
1
1
ill
0 -
.l-..llM
1
1..
1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000
Year of birth
Figure 5
i Al Age and (B) year of birth distributions for male in = 407 ) and
female (n = 307) gray snapper {Lutjanus griseus) sampled from the
1998-2002 Louisiana recreational harvest.
highest in 1973 and exhibited a steady decline to a low
in 1995.
The periodicity of opaque annulus formation in gray
snapper otoliths was further examined by plotting the
monthly percentages of otoliths with opaque margins
(Fig. 4). Although little data were available for the win-
ter months, one specimen sampled in January and two
specimens sampled in February 2001 each exhibited
opaque marginal otolith edges indicating that opaque
annulus formation occurs during the winter. Minimum
percentages of otoliths with opaque margins during
the months of April (22%) and May (8%) followed by
an absence of opaque margins during the months of
June through October indicate the cessation of opaque
annulus formation by early spring and the onset of
translucent annulus formation beginning in April and
continuing through November.
Male and female gray snapper ranged in age from 1
to 28 years (Fig. 5A). There was no significant differ-
ence in age distributions between males and females
(maximum difference=6.92 yr), but both sexes exhibited
variable multimodal distributions in age frequency.
Year of birth (YOB) frequency was also multimodal,
and the population was dominated by younger fish; 77%
of males and 80% of females were aged at 10 years or
younger (Fig. 5B).
Significant differences in slopes were detected when
plotting age-W0 relationships between sexes (ANCOVA
test of homogeneity of slopes, F3 353= 8.06; P=0.0005).
Therefore, predictive models of age-W0 were fitted sepa-
rately for males and females using a power function
with least squares as (Fig. 6)
Male age = 0.0278 (W0)106
(F2 204=3,956.29, P<0.001, r2=0.89).
Female age = 0.0460 (Wo)097
(F2 148=4,504.05, P<0.001, r2=0.90).
The single von Bertalanffy growth model to describe
gray snapper TL at age (Fig. 7) was
Lt = 656.4(1 -el-0-22inj|
<F2 714 = 32,217.6; P<0.0001; r2=0.72).
314
Fishery Bulletin 103(2)
30 -I
o o 0
X
o
25 •
* o * /?'
^r* X
X^r *
20 -
0 X y/% '
°Q> s+'
O * S* •
"
O q X ^r*
>^
XO ^Kv^T*
a> 15 -
O °^/^ »°
<
x xte/to db o
oo-xjgr ocr
o o ^jmQkio x
o ^kco o^fcStocxo *>*
10 -
o a»o dm *P °
octfcarcjto o Males
■ <&§§&§fco * Females
^^Sf^^ Power (Males)
5 -
£S|pP - - - Power (Females)
0 -
1 1 1 1 1 i i i
0 100 200 300 400 500 600 700 800
Otolith weight (mg)
Figure 6
Observed otolith weight (mg) at age for male (n=204) and female (n = 148) gray
snapper iLittjanus griseus) sampled from the 1998-2002 Louisiana recreational
harvests. Plotted lines are power functions fitted to the data.
800 -1
700 ■
X *
ox© qt x o *
8 I«X1 * £^ xl*o* * ° * *?°x
n n yn §, * 1 "i 5 jL-lj» V1
600 -
| 500 •
|? 400-
o
Z 300-
vm/m * x
qj x
200 -
o /
o Males
100 -
x Females
0
5 10 15 20 25 30
Age (yr)
Figure 7
Observed tota
length (mm) at age for male (n = 407) and female (n=307) gray snapper
{Lutjanus griseus) sampled from the 1998-2002 Louisiana recreational harvests.
Plotted lines are von Bertalanffy growth functions fitted to the data.
Fischer et al.: Age, growth, mortality, and radiometric age validation of Lut/anus gnseus
315
5 -
/\ A / A Gray snapper (n=732)
4 -
/ V V /\ Ages 5-16, Z=0. 17
QJ 3 -
n
E
c
J ^
5 2-
1 ■
\a a
VvJV^
0 4 8 12 16 20 24 28
Age (yr)
Figure 8
Catch curve for Louisiana gray snapper [Lutjanus griseus) (rc=742) sampled
from 1998 to 2002 Louisiana recreational harvests.
Table 2
Degrees of freedom (df), sum of squares (SS), mean square (MS), F value, and P values for
the full von Bertalanffy growth model lin which sexes were fitted independently) is compared
model (by fitting all specimens of known sex).
the likelihood ratio test by which
with the reduced von Bertalanffy
Model
df
SS
MS
F
P
Full
Reduced
4714
2714
1.9493 x
1.9489 x
108
10s
48,732,614
97,447,139
16,341
32,217.6
<0.0001
<0.0001
However, a likelihood ratio test indicated growth models
for males and females were significantly different from
one another <x2=494.77; df=2,714; P<0.001) (Table 2).
The resultant sex-specific von Bertalanffy growth models
were
Male L, = 655.411 -e1"0231"]]
(F2 407=19,732.9; P<0.001; r2=0.73)
Female L , = 657.311 - el-o.2i</»]}
(F2307=13,015.2; P<0.0001; r2 = 0.72).
Instantaneous total mortality (Z) was calculated with
catch curve analysis. Full recruitment to the gray snap-
per fishery began at age 4 and was completed by age 8
and there was no discernible peak in the catch curve
dome (Fig. 8). For the purposes of Z estimation, age 4
was used as the age of full recruitment to the fishery.
Z was estimated at 0.18 for all fish (age range: 5-28
years) and 0.17 for all fish when the age range was
truncated at 16 years. The age range was truncated
at 16 years because older age classes contained fewer
than 10 individuals.
Estimates for natural mortality (M) for gray snap-
per varied substantially and were dependent upon the
method used. Hoenig's (1983) longevity-mortality rela-
tionship produced the lowest estimate of 0.15. Hoenig's
(1983) relationship modified for sample size yielded
an estimate of 0.30. The regression method of Ralston
(1987) produced an estimate of 0.40. Finally, Pauly's
(1980) method using a mean annual water temperature
of 25°C and parameter estimates L, and k derived from
the von Bertalanffy growth equations produced the
highest estimate of 0.51.
Discussion
Validation of the periodicity of opaque zone formation
is critical when using otoliths to determine the ages of
fish (Beamish and McFarlane, 1983). The lack of data
during the winter months prevented us from making a
definitive statement on the timing of opaque zone forma-
tion based on edge analysis alone. However, we present
evidence that suggests that opaque zone formation may
316
Fishery Bulletin 103(2)
begin as early as December and proceed through May.
Opaque zone formation beginning in December through
spring has been shown to occur in the congeneric red
snapper (Render, 1995; Patterson et al., 2001; Wilson
and Nieland, 2001) as well as in a number of other tele-
osts in the northern GOM (Beckman et al., 1989, 1990,
1991; Thompson et al., 1999). Burton (2001) validated
the periodicity of opaque zone formation for gray snap-
per along the Atlantic coast but reported the period of
formation to occur during the summer months of June
and July.
The natural decay of radiocarbon in the world ocean
after the nuclear testing period is well documented
(Broecker et al., 1985) and close agreement between
gray snapper data and existing radiocarbon chronolo-
gies from the Gulf of Mexico, U.S. South Atlantic, and
Caribbean provided additional evidence that our otolith-
section-based age estimates of gray snapper were valid
(Fig. 3). The 14C values obtained from gray snapper
otolith cores formed after the period of atmospheric
testing of nuclear weapons were comparable to, if not
slightly less than, those values found in red snapper
from the northern Gulf of Mexico (GOM) (Baker and
Wilson, 2001).
Although published coral radiocarbon chronologies
are available for review and are made available in the
present study, we are most confident in comparing gray
snapper to the red snapper data for several reasons.
First and foremost, these two species were collected
from the same general area of the northern Gulf of
Mexico and thus in theory should have similar radio-
carbon chronologies (Broecker et al., 1985). Second,
although the coral samples would seem to be the best
possible items for comparison because of their known
age, stationary location, and most importantly because
multiple "birth dates" can be analyzed from one coral
head, the gray snapper and red snapper samples were
taken from different geographic areas and thus differ-
ent water bodies. No known coral radiocarbon chronolo-
gies exist for the northern Gulf of Mexico. Radiocarbon
chronologies have been shown to vary significantly in
the world ocean by latitude (Broecker et al., 1985) and
this trend in the reference corals can be seen in Fig-
ure 3, especially during the period of rapid radiocarbon
uptake (1958-75). Finally, all otolith samples (gray
snapper and red snapper) were analyzed for radiocarbon
by the same AMS facility by using identical laboratory
methods (Baker and Wilson, 2001). Delta 14C data from
the otoliths of gray snapper with presumed YOB back
to 1973 (the oldest fish in our data set) clearly reflected
the same pattern found in red snapper; high levels of
oceanic radiocarbon attributable to previous nuclear
testing followed by a slow but steady decline to a low
in 1995 (Fig. 3). The gray snapper curve is slightly
lower but parallel to the red snapper curve. Because
of the inherent variability associated with individual
fishes, it is inconceivable to think that the two species
of snapper would have curves that completely lie on top
of each other or on top of the coral chronologies for that
matter. Although the two species are very similar in
many regards, we can only speculate that differences
in juvenile life history patterns, habitat preferences,
water column chemistry, and possibly otolith formation
may account for the variation in radiocarbon chronolo-
gies. However, both the gray snapper and previously
validated red snapper chronologies exhibit the same
trend and indicate that our otolith-based age estimates
are accurate.
The majority of radiocarbon fisheries age validation
has produced otolith-based chronologies that resemble
those from nearby reference corals or other fish species
in the same general location (Campana, 2001). Cam-
pana and Jones (1998) observed extremely high and
erratic radiocarbon values for black drum (Pogonias
cromis) in the Chesapeake Bay. In that study, the ra-
diocarbon values resembled the intermediate of surface
oceanic (corals) and the much higher atmospheric values
(Campana and Jones, 1998). The reasons for the erratic
414C values remain unknown, but Campana and Jones
speculated that the estuarine dependency of the spe-
cies produced the variable activities of radiocarbon in
individual fish for a given YOB. This was not the case
with gray snapper, also a species that uses the shallow
estuarine environment during the first years of its life.
Because gray snapper is estuarine dependent, we fully
expected the gray snapper radiocarbon values to be
erratic and much higher than the reference corals. In
contrast, gray snapper radiocarbon values were strik-
ingly similar to, if not less than, red snapper and the
reference coral radiocarbon values at all comparable
YOBs (Fig. 3). Contrary to the opinions expressed by
Campana and Jones (1998), our limited data suggested
that estuarine dependency may have no effect on ob-
served radiocarbon values, at least for gray snapper.
Although opaque zones are distinct in gray snapper
otolith cross sections, the small size and apparent lon-
gevity of the species pose some challenges for age inter-
pretation. In older fish, opaque zones are formed more
closely together in the otolith, making accurate counts
and accurate interpretation of the otolith margin more
difficult. We observed considerable variability in the lo-
cation of the first opaque zone in gray snapper; the first
annulus was variously located somewhat distant from
the core to close to and continuous with the otolith core
(Fig. 2, A and B). Wilson and Nieland (2001) noted the
same pattern in red snapper otoliths suggesting that
this variability may be a function of the protracted red
snapper spawning season, which is similar to that of
gray snapper, and of the rapid growth rate during the
juvenile stage. This variability in first opaque zone posi-
tion accounted for the majority of disagreement between
readers in initial age estimates; there was only 76.5%
agreement. However, experience by both readers (AJF
and MSB) with red snapper otoliths produced consensus
of 98.8% after second readings.
Male and female gray snapper ranged in age from 1
to 28 years. Younger individuals composed the major
portion of the fishery; 90% of the catch was aged less
than 15 years. Maximum ages were greater than those
reported in previous studies. Johnson et al. (1994) re-
Fischer et al.: Age, growth, mortality, and radiometric age validation of Lut/anus gnseus
51/
ported maximum ages of 23 and 25 years for males
and females, respectively; the oldest fish in the study
was actually sampled from Grand Isle, LA. Burton
(2001) reported a non-sex-specific maximum age of 24
years. Sampling for both of these studies was focused in
Florida where there is higher fishing pressure on gray
snapper (Burton, 2001) and this fishing pressure may
explain the lesser maximum ages and paucity of older
individuals in their sample populations.
Gray snapper exhibit multimodal distributions in
age and YOB frequencies. Due to minimum size limits,
very few individuals were represented below age 3.
Age distributions exhibited an initial peak at 3 years,
when gray snapper are beginning to recruit to the rec-
reational fishery. Successive peaks in age-class abun-
dance in our data set occurred every two years. In an
examination of abundance by YOB a similar pattern
was observed; strong year classes were followed by di-
minished year classes. Similar patterns of variability in
year-class strength have been observed in black drum
(Pogonias chromis) and red drum (Scienops ocellatus)
in the northern GOM. Beckman et al. (1989) suggested
that year-class variability in these species might be
due to environmental factors during early life stages
or biological controls on the population. If this observed
consistent pattern is reflective of the gray snapper popu-
lation off Louisiana, we suggest that the variation in
year-class strength may be reflective of intra-species-
specific year-class competition of juveniles competing
for resources within the estuaries before recruiting to
the offshore fishery.
Researchers continually search for effective, cost-ef-
ficient ways to acquire fish age data. Body size has been
shown to be a poor value to use for estimating age in a
number offish species because of the considerable vari-
ability in size at age. Otolith growth has been shown
to continue with age, independent of somatic growth.
Otolith weight (W0) has been used as a predictive tool
to determine age in a number offish species (Temple-
man and Squires, 1956; Beamish, 1979; Wilson and
Dean, 1983; Secor et al., 1989; Beckman et al., 1991).
Although a strong relationship has been demonstrated
between W0 and age, especially for the younger age
classes, considerable variability exists in W0 at age in
older age classes. For example, the W0 of a 10-yr-old
male gray snapper can range from 180 mg to 357 mg
thus preventing a precise age estimate based on W0
alone. Although W(l data may provide general informa-
tion on overall age distribution patterns of a popula-
tion, we feel that annulus counts from otolith cross
sections provide the most accurate age estimates for
gray snapper.
Our overall (sexes combined) von Bertalanffy growth
model estimated a maximum theoretical length (Lj
of 656.4 mm TL. Although a likelihood ratio test indi-
cated a significant difference between male and female
models, this difference may be of limited biological
significance because male and female models appear
to be very similar. The presence of larger, older fish
in our sample population resulted in our overall model
coming to an asymptote at a smaller L, and having a
larger respective k than previously reported (Manooch
and Matheson, 1981; Johnson el al . 1994) Johnson
et al. (1994) predicted an Lr of 792.25 mm using the
regression method of Manooch and Matheson (1981)
to back calculate lengths at age. Johnson et al. (1994)
also obtained a much smaller estimate of ft at 0.08
compared with a k value of 0.22 predicted in our model.
A smaller estimate was not unexpected given the in-
verse correlation between Lx and k noted by Knight
(1968). Because of the minimum size limitations on
the recreational fishery, smaller (presumably younger)
individuals below 304 mm TL were almost absent in
our sample population. We chose to not specify a y-in-
tercept for t0 and to force our growth models through
zero in order to obtain more accurate estimates of k.
Forcing our models through zero also contributed to
the differences in growth parameters between our study
and those of Johnson et al. (1994). Like Johnson et al.
(1994), Burton (2001) also estimated growth param-
eters by fitting back-calculated lengths at age. Burton's
(2001) Lx estimates of 717 mm and 625 mm for north
and south Florida, respectively, are similar to those
found in our study. Burton's (2001) sample populations
consisted of a number of fish below 200 mm TL. These
smaller individuals had similar effects on his models
as that of forcing our models through zero. Burton's
estimates of k were 0.17 and 0.13 for north and south
Florida, respectively, compared with a /; of 0.22 for our
overall model.
We estimated total instantaneous mortality (Z) to
be 0.17 and full recruitment to the fishery at age 4.
We chose to use the truncated age range of 5-16 years
(versus 5-28 years) for Z estimation in order to have at
least 10 samples in each age category. Our estimation
of Z based on all age categories (5-28) was 0.18. Our
estimate of Z is at the low end of the range of values
reported by Johnson et al. (1994) (Z=0.17-0.26) for the
Gulf of Mexico. It should be noted, however, that John-
son et al. (1994) pooled fish from five distinct geographi-
cal locations. Of the 432 fish analyzed in their study,
69% came from Grand Isle, LA (n = 104) and Panama
City, FL (n = 193). The remaining 31% came from the
central and southern coasts of Florida. Perhaps John-
son et al.'s (1994) estimates of Z would be lower if only
the Louisiana samples were used. Our Z values, how-
ever, are much lower than those reported by Manooch
and Matheson (1981) (Z = 0.39-0.60) and Burton (2001)
(Z=0.34-0.95) for the east coast of Florida.
Our low estimate of Z for gray snapper in Louisiana
waters is clearly associated with the abundance of older,
larger individuals in the population. Unlike the catch
curves in previous studies that dealt with gray snapper
populations on the east coast of Florida (Manooch and
Matheson 1981; Burton 2001) and in the southeast in
general (Johnson et al. 1994), the mode of our catch
curve is not well defined. It is evident that gray snap-
per in the South Atlantic are heavily exploited (Burton,
2001), as evidenced from their age-frequency distribu-
tion and high estimates of Z.
318
Fishery Bulletin 103(2)
Estimates of M ranged from 0.15 to 0.51 and were
comparable to previous studies on gray snapper from
the southeastern United States. Johnson et al. (1994)
used the Pauly (1980) and Ralston (1987) methods to
estimate M to range from 0.12 to 0.32 for the west coast
of Florida, including Louisiana. Manooch and Matheson
(1981) used the Pauly (1980) relationship to calculate
M = 0.22. Burton (2001) used the same four methods
as in our study and found M to range from 0.18 to
0.43. It is well known that estimates of mortality are
highly variable and depend upon the parameters used
to calculate them. The purpose of providing various
estimates of M was to demonstrate to the reader the
variability in this important life history parameter
and to demonstrate how little we actually know about
it. Adopting our estimate of Z, we feel that the Hoenig
(1983) method (M=0.15) produced the most suitable
estimate of M for gray snapper in Louisiana waters
of the northern Gulf of Mexico. Based on the appar-
ent age-size structure of the stock, historical landings
data, and personal observation, all indications are that
this species is lightly fished in this study area. Hoenig
(1983) indicated that M should be roughly equivalent
to Z if the population is lightly exploited. Our estimate
of Z (0.17) was indeed roughly equivalent to M (0.15),
supporting our belief that fisheries mortality (F) is not
yet a significant threat to this fishery.
Gray snapper could become over-exploited if a large,
intensive fishery developed in the northern Gulf of
Mexico. Landings of gray snapper in Louisiana have
increased dramatically over the last few years, part-
ly because of the recent restrictions imposed on red
snapper in the Gulf of Mexico. Compared to the gray
snapper population structure in the South Atlantic,
especially off the coast of south Florida (Manooch and
Matheson, 1981; Burton, 2001), the Louisiana popula-
tion appears to be healthy. Long-term heavy fishing
pressure has probably affected the south Florida gray
snapper population (Burton, 2001). As a result, the
population structure of south Florida is dramatically
different from that of Louisiana. Our estimates of Z are
extremely low and indicate that fishing mortality (F) is
currently not a significant factor for the gray snapper
population in Louisiana waters. A low-intensity gray
snapper fishery could take most of the resource without
endangering future production.
Acknowledgments
Funding and assistance with sampling was provided by
the Louisiana Department of Wildlife and Fisheries. We
would also like to thank Josh Maier, Brett Blackmon,
and Candace Aiken for sampling efforts and otolith
processing as well as Brain Milan for providing juvenile
gray snapper samples. We thank Steve Tomeny, the boat
captains, and deck hands of Captain Steve Tomeny's
charters in Port Fourchon, LA, as well as all the recre-
ational fishermen that allowed us to sample their catch.
We wish to thank Ann P. McNichol of National Ocean
Sciences (Accelerator Mass Spectrometry facility at
the Woods Hole Oceanographic Institution) for otolith
radiocarbon analyses.
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1983. The potential use of sagittae for estimating the
age of Atlantic swordfish, Xiphias gladius. NOAA Tech.
Rep. NMFS 8:151-156.
Wilson, C. A., and D. L. Nieland.
2001. Age and growth of red snapper, Lutjanus
campechanus, from the Northern Gulf of Mexico off
Louisiana. Fish. Bull. 99:653-664.
320
Abstract— The objective of this study
was to investigate the spatial pat-
terns in green sea urchin (Strongylo-
centrotus droebachiensis) density off
the coast of Maine, using data from a
fishery-independent survey program,
to estimate the exploitable biomass of
this species. The dependence of sea
urchin variables on the environment,
the lack of stationarity, and the pres-
ence of discontinuities in the study
area made intrinsic geostatistics
inappropriate for the study; there-
fore, we used triangulated irregular
networks (TINs) to characterize the
large-scale patterns in sea urchin
density. The resulting density sur-
faces were modified to include only
areas of the appropriate substrate
type and depth zone, and were used
to calculate total biomass. Exploitable
biomass was estimated by using two
different sea urchin density threshold
values, which made different assump-
tions about the fishing industry. We
observed considerable spatial vari-
ability on both small and large scales,
including large-scale patterns in sea
urchin density related to depth and
fishing pressure. We conclude that
the TIN method provides a reasonable
spatial approach for generating bio-
mass estimates for a fishery unsuited
to geostatistics, but we suggest fur-
ther studies into uncertainty estima-
tion and the selection of threshold
density values.
Estimating exploitable stock biomass
for the Maine green sea urchin
(Strongylocentrotus droebachiensis)
fishery using a spatial statistics approach
Robert C. Grabowski
School of Marine Sciences
5741 Libby Hall
University of Maine
Orono, Maine 04469
Present address: Flat 6, Falmer House
16-17 Marylebone High St
London, W1U4NY, England
E-mail address grabowskirc6ig'yahoo com
Thomas Windholz
The GIS Training and Research Center
Idaho State University
Pocatello, Idaho 83209-8130
Yong Chen
School of Marine Sciences
5741 Libby Hall
University of Maine
Orono, Maine 04469
Manuscript submitted 27 January 2003
to the Scientific Editor's Office.
Manuscript approved for publication
21 December 2004 by the Scientific Editor.
Fish. Bull. 103:320-330 (2005).
The green sea urchin (Strongylocen-
trotus droebachiensis) is an impor-
tant resource of the fishing industry
in the State of Maine, where it cur-
rently ranks fourth by value. The com-
mercial fishing industry began in the
late 1980s as a result of expanding
foreign markets. Landings reached a
peak of more than 22,000 metric tons
(t) in 1993. However, declining stock
abundances have caused landings to
diminish over the last decade, and in
2001, less than 5,000 t were landed
(Chen and Hunter, 2003). Consider-
ing the economic importance of the
fishery and its persistent decline in
yield, it is essential that we establish
an accurate quantitative assessment
of the stock in order to develop an
effective management plan.
The Maine Department of Marine
Resources (DMR) has collected fish-
ery-dependent information since the
beginning of the state's commercial
fishery. This information, including
catch and size-composition data, has
formed the basis of most management
decisions in the fishery. The fishery is
currently managed through limited
entry, a restricted number of opportu-
nity days, and sea urchin size limits,
in which legal-size sea urchins have a
test diameter between 52 mm and 76
mm. The fishing grounds are divided
into two management areas based on
spatial and temporal variations in
spawning (Fig. 1), in which manage-
ment differs only by fishing seasons
(Vadas et al., 2002).
Chen and Hunter (2003) conducted
the first formal stock assessment for
the Maine green sea urchin in 2001.
Fishery-dependent data and sea ur-
chin life history parameters were
used to assess the population dy-
namics of the Maine urchin stock. A
length-based stock assessment model
was used with a Bayesian approach
to determine probabilistic estimates
of current stock biomass and exploi-
tation rate. The study estimated that
the current stock biomass was ex-
tremely low, about 10% of the virgin
biomass. Only fishery-dependent data
were available at the time the stock
assessment was conducted, but in
Grabowski et al.: Estimating stock biomass of Strongylocentrotus droebachiensis
321
«
-05 -60
9
,7
-
^
<■'■
P
-]
g
8
s
/ 6
7
3>
i) 25H 5(K) Mil
.'S
"^
-so W -75
-70 JS5 <0
\
5
\ 4 Management
area 2
3
2
N
1
v^
*" E
Management
V
s
area 1
0
20 40 60 80
100 Miles
Figure 1
Map of the Maine coastline, showing the two management areas and the nine study strata from the fishery-inde-
pendent survey program for green sea urchins (Stro/igylocentrotus droebachiensis).
2001 the DMR began an extensive fishery-independent
survey program. This program generates large, spa-
tially referenced, scientific data sets each year, which
can be incorporated into stock assessments by using
either fisheries population dynamics models or spatial
analysis techniques.
Spatial statistics, also known as spatial statistics or
geostatistics, encompasses a diverse group of techniques
that can be used to model the spatial variability of a
process, such as sea urchin density, to estimate the
value at unobserved locations (Bailey and Gatrell, 1995;
Petitgas, 2001). Spatial variability is routinely divided
into two categories: first- and second-order effects, or
similarly, large- and small-scale variability. Large-scale
variability is the variation in the mean value of the
process over the study area, whereas small-scale vari-
ability is the spatial dependence of the process, in other
words the similarity between neighboring sites (Bailey
and Gatrell, 1995).
Intrinsic second-order methods, along with kriging,
have become the most popular geostatistical tools and
are now commonly used to estimate exploited fish stock
biomass (e.g., Simard et al., 1992; Petitgas, 1993; Pelle-
tier and Parma, 1994; Maravelias et al., 1996; Lembo
et al., 1998; Maynou et al., 1998; Rivoirard et al., 2000;
Petitgas, 2001). Two assumptions must be met to use
intrinsic geostatistical methods: 1) independence be-
tween the variable and the region's geometry and 2)
stationarity (Petitgas, 1993; Warren, 1998; Rivoirard
et al., 2000). If these assumptions are violated, we can
attempt to modify the data to make them more appli-
cable or we must use other spatial analysis techniques
to estimate the spatial patterns.
Tessellation is a spatial analysis technique that in-
vestigates first-order, or large-scale, spatial variability
of a process (Ripley, 1981; Bailey and Gatrell, 1995).
Triangulated irregular networks (TINs), or Delaunay
triangulation, are the simplest and most common tes-
sellation technique, in which a three-dimensional sur-
face of contiguous, non-overlapping triangles is created
by linear interpolation of the variable. TINs are most
commonly used for visualization purposes but can be
used to estimate the biomass of a process (Simard et
al., 1992; Guan et al., 1999). They have received limited
use in fisheries stock assessment, however, because if a
stock exhibits stationarity, second-order methods tend
322
Fishery Bulletin 103(2)
to provide more precise biomass estimates, as well as
a quantification of their variances (Simard et al., 1992;
Bailey and Gatrell, 1995; Guan et al., 1999).
The objective of our study is to investigate the spatial
trends in green sea urchin density using spatial analy-
sis techniques to estimate stock biomass. In doing so,
we address the suitability of second-order methods to
analyze a fishery with a target species that is highly
spatially variable over a large, complex study area. We
compare biomass estimates from several techniques to
address the suitability of TINs for biomass estimation
in the green sea urchin fishery.
Materials and methods
Data collection and processing
Sea urchin density and size-frequency information were
obtained from the 2001 pilot study for the State's annual
fishery-independent survey. The Department of Marine
Resources conducted the survey in June and early July,
after the fishing season had ended. The survey was
restricted to rock and gravel habitats along the Maine
coast and we used two modes of data collection, divers
and video. In the first part of the study, divers sampled
144 sites according to a stratified random sampling
design. The design consisted of 16 sites in each of 9
survey strata, where the width of a survey stratum was
inversely proportional to the commercial landings in the
region. At each site, SCUBA divers randomly sampled
.30 quadrats (1 m2 each) along three parallel linear
transects set perpendicular to shore, for a total of 90
quadrats per site. The sampling intensity was divided
equally among three depth zones: 0-5 m, 5-10 m, and
10-15 m. At each site, size-frequency data were obtained
by randomly subsampling one quadrat in each depth
zone, in which test diameters were measured for all
individuals in the quadrat. An additional 148 sites were
sampled, in a 15-40 m depth zone, with a video camera
that recorded 10 quadrats (0.5 m2 each) at each site.
Because of the low sea urchin densities at these sites,
test diameters were measured for all recorded speci-
mens. Mean sea urchin density values were calculated
for each site (rc=292) and for each depth zone within a
site (« = 580). An analysis of variance (ANOVA) was used
to test if there were significant differences in mean sea
urchin density and test diameter among survey strata.
Five test diameter categories were created to more
accurately represent the wide range of individual sea
urchin weights. The categories were based on the state's
minimum and maximum size restrictions, allowing
us to separately estimate the biomass of sea urchins
that have not yet recruited to the fishery, sea urchins
within the fishery, and sea urchins that have escaped
the fishery. The minimum (50 mm) and maximum (80
mm) size limits for our study were set slightly wider
than the those of the state, because, according to the
fishery regulations, up to 10% of the catch can be il-
legal-size sea urchins. Size-frequency data from sub-
sampled quadrats were applied to the mean sea urchin
density for the specific depth zone and site, to generate
density values for each size category. Weight per sea
urchin was calculated from the mean length of the cat-
egory by using a length-weight relationship (Scheibling
et al., 1999).
Spatial interpolation
A sample semivariogram, often abridged to variogram,
was generated from mean sea urchin densities by site, to
examine the second-order spatial variation in the data
set. The sample variogram was calculated with the fol-
lowing equation (Bailey and Gatrell, 1995):
yUi)-
2n(h)
!(*,-*/,
(i)
SiS:,
where S, and S = sampling point pairs with (x,y) coor-
dinates;
n = the number of sample point pairs;
h - the distance between pairs; and
2 = mean urchin density for the sample.
Trends in the variogram provide insights into the viabil-
ity of second-order methods for the sea urchin data.
Representations of the large-scale trends in sea ur-
chin density were created by using Delaunay triangu-
lated irregular networks (TINs) (ArcView 3.2a, 3D and
Spatial Analyst Extensions, Redlands, CA). First, the
sample points were plotted by using sea urchin density
(/m2) as the z value. Second, each point was connected
to the three nearest sites by linear interpolation, form-
ing a continuous surface of nonoverlapping triangles
(Fig. 2) (Bailey and Gatrell, 1995; Guan et. al., 1999).
Thus, the z value of any location within a triangular
surface is based solely on the three nearest sites. TIN
surfaces were generated for 40 different scenarios, ac-
cording to the size category, depth zone, and manage-
ment area, which minimizes variability and allows us
to produce more realistic biomass estimates. Finally,
using a customized C++ program,1 we modified each
surface to include only areas of appropriate sea urchin
habitat. The green sea urchin is most commonly found
on rocky substrate in the shallow subtidal (Scheibling
and Hatcher, 2001), and, accordingly, the original sur-
vey program was limited to areas with predominately
rock or gravel substrata in areas less than 40 meters
deep. Therefore, we used a map of surficial geology to
identify areas of the correct substrate type (1:100,000
scale) (Kelley et al., 1997) and digital gridded bathym-
etry data to create a plot of 5-m isoline contours. The
bathymetry data source consisted of digital bathymetry
data sets from sources such as NOAA and the Naval
Oceanographic Office (15 arc second resolution) (Row-
orth and Signell, 2002).
1 The C++ code used in this study is available upon request
from the principal author (RCG).
Grabowski et al.: Estimating stock biomass of Strongylocentrotus droebachiensis
323
2H Kilometers
^
Urchin density
0-5
■ 5 - 10
| Id- 15
H 15
~\ No data
20 kiloaielere
Urchin density
I 10-5
1 5 - 111
■ I"- 15
^B 15 -
HNo data
5 10 15 20 Kilometer;
Urchin density
(5-10
| HI- 15
^B 15
J No data
4-
Urchin density
1 10-5
B 5- 1(1
| 10- 15
Hi l5
No data
Figure 2
Representations of the triangulated irregular networks (TINs), used to characterize the large-scale patterns in green sea
urchin [Strongylocentrotus droebachiensis) density (number of sea urchins/m2), for the 50-64 mm sea urchin size category in
the central portion of management area 2. Top left, 0-5 m depth zone; top right, 5-10 m depth zone; bottom left, 10-15 m depth
zone; bottom right, 15-40 m depth zone.
To determine total sea urchin biomass <6) for each sce-
nario, the volume beneath the modified TIN surface was
calculated, from Riemann sums, and multiplied by the
mean weight (w) according to the following equation:
»XW*.
(2)
where st
n
fis,)
= the spatial location (x,y) on an ASCII grid;
= the number of grids squares;
= the TIN surface and corresponds to a z value
for each grid cell; and
= the grid cell size, which was 1.72 hectares
for area 1 and 1.82 hectares for area 2.
Fishable biomass is defined as the biomass of all
legal-size sea urchins and is simply the subset of the
total biomass corresponding to legal-size sea urchins.
Exploitable biomass corresponds to the legal-size sea
urchins that are available to the fishery. Some areas
included in this study may not be subject to fishing
pressure because of geographic isolation or low sea
urchin densities. Because information on historical
fishing grounds is insufficient, exploitable biomass was
estimated by using a threshold density value. Only
areas with densities greater than the threshold were
included in the exploitable biomass estimates.
Two different types of threshold values were tested:
1) a threshold based on total sea urchin density and 2)
a threshold based on the density of legal-size sea ur-
chins. The threshold values make different assumptions
about the fishery: method 1 assumes that fishermen
target areas based on total sea urchin density, whereas
method 2 assumes that fishermen target areas based
on the density of legal-size sea urchins. Interviews
were conducted with state sea urchin biologists and
fishermen to determine an appropriate threshold value.
The reported threshold values, the minimum total sea
324
Fishery Bulletin 103(2)
urchin density that could attract fishermen, ranged
from 20-50 sea urchin/m2. For the first scenario, the
mean density from the range of recommended values,
35 sea urchin/m2, was selected. Therefore, the biomass
of legal-size sea urchins was calculated only in areas
where total sea urchin density was equal to or greater
than 35/m2. For the second scenario, we estimated that
commercial divers target areas that have greater than
10 legal-size sea urchins/m2.
Estimation of uncertainty and stock assessment
Because information on uncertainty cannot be directly
obtained from the TIN method, cross validation was
employed to approximate uncertainty in the estimation
process. Cross validation involves randomly removing
a site from a data set and predicting its value based
on the other data points using the TIN process (Bailey
and Gatrell, 1995). Residuals, or prediction errors, are
calculated between the predicted and true values at
the site. The process is repeated n times, resulting in
an observed set of n prediction errors, or residuals. The
frequency distribution and spatial distribution of residu-
als provide insights into the accuracy of the model; an
ideal model would have a mean residual value of 0 and
positive and negative residuals would be distributed
randomly over the study area.
Sea urchin biomass values were also calculated with
the arithmetic mean to provide comparisons with the
spatially derived estimates. For total biomass, mean sea
urchin densities by survey strata were multiplied by a
spatially derived area estimate of suitable sea urchin
habitat (<40 meters in depth) in the strata and the mean
sea urchin mass per strata. Fishable biomass was calcu-
lated the same way but sea urchin density values were
scaled by the proportion of legal-size sea urchins in the
stratum. Finally, exploitation rates, or the ratio of com-
mercial landings to the exploitable biomass estimates,
were calculated to facilitate comparison with the results
generated from the population dynamics stock assess-
ment and a recent study on biological reference points
(Chen and Hunter, 2003; Grabowski and Chen, 2004).
■
rable 1
Quadi
at density
counts
(/m2) for the green sea l
rchin
l Strongylocen trotu
s droebachiensis) by management area
and survey strata
Sample size, n,
is the number of
quad-
rats observed.
Area
Stratum
Density
SD
n
Min.
Max.
Mean
1
1
0
36
0.17
1.62
1706
2
0
130
2.57
10.63
1600
3
0
141
3.20
11.29
1580
2
4
0
180
4.20
14.13
1490
5
0
127
4.24
12.52
1580
6
0
147
10.06
17.59
1530
7
0
11.3
7.90
13.85
1498
8
0
113
13.50
20.38
1570
9
0
280
34.45
44.03
1540
Table 2
Sea urchin test
diameter (mm)
for gree
n sea urchins
( Strong
ylocentrotus droebachiensis) subsampled
in the
fishery
independent survey program.
Area
Stratum
Density
SD
n
Min
Max.
Mean
1
1
7
80
38.69
21,07
29
2
3
81
39,01
22,19
627
3
4
89
45.25
18,90
855
2
4
3
89
32,99
19,82
1148
5
3
77
29,25
17,56
1034
6
4
110
39,87
16,23
1734
7
5
92
47,23
16,07
1283
8
3
114
42,11
16,86
2567
9
3
114
28,84
12,90
5263
Results
Sea urchin density and size frequency, which were used
to calculate biomass, varied considerably along the coast
of Maine. Density (number of sea urchins/m2) differed
significantly among survey strata (P<0.05; ANOVA),
showing a general large-scale trend of increasing den-
sity from stratum 1 to 9 (Table 1). Density also varied
by depth; the sea urchin density in the 15-40 m depth
zone was 0.32 sea urchins/m2, significantly lower than
those of the three shallow (<15 m) depth zones (P<0.05, t-
test), which each had approximately 9.50 sea urchins/m2.
Sea urchin test diameter varied from 3 mm to 114 mm
(mean at 35.90 mm). Test diameter differed significantly
among survey strata (P<0.05; ANOVA), in which strata
4, 5, and 9 had the smallest size sea urchins, and strata
3 and 5 had the largest (Table 2). No meaningful trend
was evident in the sample variogram, which showed a
pure nugget effect (Fig. 3). This result indicates that the
sea urchin density data were too spatially variable to be
analyzed by intrinsic small-scale methods.
Total sea urchin biomass was estimated at approxi-
mately 250,000 metric tons (t), and legal-size sea
urchins accounted for 165,000 t (Fig. 4). Most of the
biomass was found in management area 2, which ac-
counted for over 75% and 80% of the total and fishable
biomass, respectively (Table 3). For both estimates, bio-
mass varied by depth, being highest in the 0-5 m depth
zone and lowest in the 15-40 m depth zone (Fig. 5).
The two methods used to estimate exploitable bio-
mass produced different biomass estimates with unique
Grabowski et al.: Estimating stock biomass of Strongylocentrotus droebachiensis
325
Table 3
A summary of 2001 biomass estimates
and 2000-2001 landings
in meti
ic
tons, for the Maine
green sea
urchin fishery. Biomass
estimates for the TIN
method and ari
thmetic mean were generated
in
th
is study, whereas the
popula
ion dynamics estimates
are from Chen and Hunter (2003). Area 1 consists of strata 1-3
and area 2
consists of strata 4
:>
When
possible, 95^ confidence
intervals are included.
in italics.
Area 1
Area 2
Total
TIN method
Total biomass
45,868
204,304
250,172
Fishable biomass
39,060
126,725
165,786
Exploitable biomass
Method 1
3645
5793
9438
Method 2
10.886
12.069
22,955
Arithmetic mean
Total biomass
47,933
(42,399-54,331)
290,954
(274,632-307,977)
338,887
(317.031-362,308)
Fishable biomass
24,241
(27.575-27.2S7)
90,185
(85,144-95.144)
114,426
(106.719-122.723)
Population dynamics
6550
(4041-9450)
8452'
(5866-11,701)
15,002
(10.307-21.151)
2000-2001 landings
2148
3213
5361
' 2000 value.
euu -
*
500-
IB
F
400-
»
E
CO
300-
200-
100-
0-
♦
•A— \
. * ♦ * . ♦
♦ ♦ ♦♦
-.«► * ♦ ♦ ♦/ ♦ ♦
50,000 100.000 150.000
h(m)
200.000
Figure 3
Sample variogram of mean green sea urchin (Stron-
gylocentrotus droebachiensis) density by site, showing
small-scale variability, gamma (y), with respect to
the distance between sample point pairs, /;.
spatial distributions. Exploitable biomass estimates for
method 2 were more than 2 times greater than those
for method 1 (Table 3). With method 1, legal-size sea
urchins were concentrated in the northeastern corner
of management area 2, but with method 2, they were
concentrated in the northeastern portion of area 1 and
the central portion of area 2 (Fig. 6). Exploitable sea
urchin biomass showed different patterns by manage-
ment area and depth than did total biomass and fish-
able biomass (Fig. 5). For example, management area
1 had a larger share of the total exploitable biomass,
39% or 47%, for methods 1 and 2, respectively, and
120,000 "I
(/)
c
o
100.000 -
o
80,000 "
E
60,000 "
O)
F
40,000 "
o
m
20,000 "
0 -
U\
■ Area 1
□ Area 2
u.
0-29
30^19 50-64 65-80
Diameter (mm)
81 +
Figure 4
Total biomass by green sea urchin (Strongylocentrotus droe-
bachiensis) test diameter according to management area. Sea
urchins between 50 and 80 mm were considered legal size
for this study, and the biomass within these limits, indicated
by the dashed lines, constitutes the fishable biomass.
this biomass was almost exclusively found in the 0-5 m
depth zone, accounting for 98% or 93%, respectively, of
the area's biomass.
TIN biomass estimates were similar to ones produced
with the arithmetic mean but were higher for total
biomass and lower for fishable biomass. Exploitation
rates for method 1 were estimated at 0.59 and 0.55
for management areas 1 and 2, respectively, and 0.20
and 0.27 for method 2, respectively. Exploitation rates
326
Fishery Bulletin 103(2)
30,000
25,000
20.000
15,000
10,000
5000
g 140,000
CO
120,000
■ total
□ fishable
□ exploitable
meth. 1
□ exploitable
meth. 2
0-5
5-10
10-15
15-40
■ total
□ fishable
□ exploitable
meth. 1
□ exploitable
meth. 2
0-5
5-10 10-15
Depth (m)
15-40
Figure 5
Total, fishable, and exploitable green sea urchin iStrongylocentrotus droe-
baclnensis) biomass estimates by depth zone. Top, area 1; bottom, area 2.
from the population dynamics modeling approach were
0.38 and 0.57 (2000) for management areas 1 and 2,
respectively.
Cross validation of sea urchin density surfaces yield-
ed a mean residual of 0.50 (median=0, standard de-
viation^.86, skewness=2.80, ra = 60) (Fig. 7). Residuals
were greatest in regions with the highest spatial vari-
ability, such as sites within depth zones 1 and 2 and in
the eastern survey strata.
Discussion
Spatial variability and distribution
The objective of this study was to investigate the spatial
variability in green sea urchin density to estimate the
biomass of the Maine stock. However, several factors
limited the choice of spatial statistical approaches that
could be used to assess the fishery. In particular, the
physical structure of the study area, the dependence of
sea urchin variables upon the environment and a high
degree of small-scale spatial uncertainty make small-
scale approaches inappropriate.
First, the study area was neither uniform nor con-
tinuous. Because the aim of the fishery-independent
survey program was to assess the whole population of
sea urchins in Maine, the study area had to span the
entire coastline. Consequently, the study area encom-
passed many features that create discontinuities in a
spatial model at varying, yet relatively small, spatial
scales. These features included the highly indented
coastline, the presence of several hundred islands and
the exclusion of regions because of environmental con-
straints. Second, green sea urchin variables were not
independent of the study area; rather, they were depen-
dent on several environmental, ecological, and anthro-
pogenic factors. In particular, depth, substrate type,
Grabowski et al.: Estimating stock biomass of Strongy/ocentrotus droebachiensis
327
-A
o"T"
-»'■;
Urchin densit\
■■ 0-10
■■
9 i.
No data
Figure 6
Final spatial representations of the density of exploitable green sea urchins (Strongylocentrotus droebachiensis). Top row, method
1: threshold was based on total sea urchin density. Bottom row, method 2: threshold was based on legal-size sea urchin den-
sity. Left column, eastern portion of management area 1; middle column, central portion of management area 2; right column,
northeastern corner of management area 2.
benthic algal presence, and the presence and level of
fishing or predatory activity all greatly affect urchin
density, growth rates, and size frequency (Vadas et
al., 1986; Scheibling and Hatcher, 2001). Mean sea
urchin density and size frequency were not constant
over the study area (Tables 1 and 2). Density exhib-
ited large-scale spatial trends along the coast, which
are related, at least, to depth and fishing activity. The
eastward increase in total sea urchin density along the
coast corresponded well with the historical patterns of
commercial sea urchin fishing in the State of Maine
(Table 1). The fishery began in the southwest, but as
sea urchin densities dropped in those regions, the fish-
ery steadily progressed northeastward along the coast.
Spatial patterns in density by depth (0-15 m vs. 15-40
m) may have been caused, in part, by the difference in
sampling techniques, yet the magnitude of the differ-
ences and support from ecological studies indicate that
there is a pattern. Finally, sea urchin densities varied
dramatically on small spatial scales — variations on
the order of one magnitude within the same habitat,
and sometimes only meters apart, are not uncommon
(Scheibling and Hatcher, 2001). This variability was
evident in the variogram analysis, which showed no
meaningful small-scale spatial structure and thus no
stationarity (Fig. 3).
We were interested in identifying a spatial statisti-
cal approach that would generate reasonable estimates
of stock biomass. The numerous discontinuities in the
study area, the dependence of variables on ecological
factors, and the high spatial variability indicated that
an intrinsic spatial statistical approach was not ap-
propriate for the investigation. Therefore, we needed
an approach that was geared towards the detection
and modeling of large-scale variability and that also
exhibited some robustness to discontinuities caused by
the indented coastline, islands, and habitat constraints.
We believe the TIN approach used in this study satisfies
these requirements, and, additionally, allows for vary-
ing levels of resolutions, with finer resolution in high
density sampling areas.
Biomass estimates
We calculated exploitable biomass in two different ways
because of the different assumptions they make about
the fishery. Method 1 assumes that fishermen target
areas based on total sea urchin density, whereas method
2 assumes that fishermen target areas based on the
density of legal-size sea urchins. The spatial distribu-
tions of legal-size sea urchin density, which were used
to calculate exploitable biomass, were distinctive and
showed little overlap between methods (Fig. 6). The
spatial distributions appear to reflect different aspects
of the sea urchin fishery. When the threshold was based
on total density (method 1), exploitable biomass was
328
Fishery Bulletin 103(2)
• «>
%°
e°
>%
jOCl
o o 0W
,o
Residuals
• -
o o
• +
Figure 7
Spatial distribution of residuals and frequency distribution, insert (median=0,
standard deviation = 1.86, skewness=2.80, n=60), from the cross-validation study
that addressed uncertainty in the TIN estimation process for estimating bio-
mass for the green sea urchin (Strongyloeentrotus droebachiensis) fishery.
concentrated in the eastern corner of management area
2, which is the most northeastern location on the coast
of Maine. This area has high total sea urchin densities,
but relatively low densities of legal-size adults, and is
an important location for the trawling industry. When
the threshold was based on the density of legal-size sea
urchins (method 2), however, exploitable biomass was
concentrated in the eastern portion of management area
1 and the central portion of area 2. These regions have
lower average sea urchin densities, but higher percent-
ages of legal-size adults, and are key fishing grounds for
the state's dive-based fishery.
Because the two methods reflected different aspects
of the fishery, it is not surprising that they produced
different estimates of exploitable biomass (Table 3).
Nevertheless, these estimates did not differ consider-
ably from those of the population dynamics model. The
spatial analysis estimates bordered the ones derived
from the population dynamics model; method-1 esti-
mates were smaller than those derived from the popula-
tion dynamics model whereas method-2 estimates were
larger. The biomass estimates were similar despite
the fact that they were derived from different models
(spatial analysis and population dynamics model) using
entirely different data sources (fishery-independent and
fishery-dependent).
The status of a fishery is often determined by com-
paring the current fishing mortality or stock biomass
with biological reference points (BRPs) (Hilborn and
Walters, 1992). The previous stock assessment study
estimated that the sea urchin stock biomass in Maine is
only about 10% of the virgin biomass, implying that the
fishery has been severely overfished. A preliminary in-
vestigation into BRPs recently estimated a BRP F0 l for
the urchin fishery, based on a yield per recruit analysis,
and concluded that estimates of the current exploitation
rate are much higher than the BRP, which means that
the fishery is being overfished (Grabowski and Chen,
2004). However, when we compare the TIN exploita-
tion rates with the preliminary mean BRP F0 ,, which
ranged from 0.37 to 0.43 depending upon uncertainty
levels, we get an unclear assessment of the stock status.
The fishery is being drastically overfished according
to method 1, but is healthy according to method 2. We
believe that the assessment generated by method 2 was
unrealistically optimistic, considering the results from
the stock assessment and the decade-long declining
trend in landings.
Uncertainty and further studies
The TIN method was an appropriate spatial statistical
approach for estimating biomass for the sea urchin fish-
ery; however, a disadvantage of this technique is that
there is no straightforward method to estimate the uncer-
tainty in the biomass estimates. Because the technique
does not incorporate a variance structure into the estima-
tion process, we could not directly estimate uncertainty.
Therefore, we used cross-validation to approximate the
uncertainty associated with the TIN method (Fig. 7).
We found that the mean residual did not equal zero,
indicating that there is a global bias in the TIN surfaces
and that biomass estimates were likely overestimated
(Simard et al., 1992). This bias was most likely caused
Grabowski et al .: Estimating stock biomass of Strongylocentrotus droebachiensis
329
by a combination of the underlying patterns in spatial
variability, the linear interpolation method employed in
TIN formation, and the effects of sample selection in the
cross-validation study. There are several possible ways
to reduce the bias in the estimation process, such as
incorporating a smoothing function or weighting based
on neighbors into the TIN model. This procedure would
not completely address uncertainty, however, because it
would only acknowledge uncertainty in the TIN estima-
tion process. To obtain confidence intervals for biomass
estimates, we needed to incorporate uncertainty in mean
density and in TIN estimation. We are currently inves-
tigating methods to estimate confidence intervals, such
as using a Monte Carlo simulation approach. A thorough
examination and quantification of uncertainty is beyond
the scope of this article.
In this study, we identified a basic approach for inves-
tigating spatial patterns, and estimating stock biomass
in situations where second-order methods are inappro-
priate. The TIN technique generated realistic biomass
estimates that are similar to those derived with other
approaches, but before we can recommend this tech-
nique for the green sea urchin fishery, several points
must be addressed. First, the two methods used to es-
timate exploitable biomass must be integrated because
they reflect different aspects of the fishery and result
in different stock assessments. Second, a process must
be established to estimate threshold levels because they
have a large control over exploitable biomass estimates.
Finally, a technique must be developed to estimate
uncertainty in biomass. We would also recommend fur-
ther investigations into tracking fishing pressure and
identifying its effects on the benthic ecosystem and the
spatial distribution of sea urchins.
Acknowledgments
We would like to thank the staff at the Maine Depart-
ment of Marine Resources for collecting and compiling
the sea urchin fishery data. We would especially like to
thank Margaret Hunter and Robert Russell from the
DMR, Kathryn Wisz, our laboratory assistant, Ryan
Weatherbee, for his help with the manuscript, and Oliv-
ier Mette, for his technical assistance. This project was
partially supported by grants from the Northeast Con-
sortium (UNH SUB 302-628), the Maine Department of
Marine Resources (G1102012), and the Sea Urchin Zone
Council to Y. Chen and a Maine Marine Science Fellow-
ship from the Marine Department of Marine Resources
and the University of Maine School of Marine Sciences
to R. Grabowski.
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331
Abstract— The abundance and dis-
tribution of California sea lions
iZalophus californianus) in central
and northern California was stud-
ied to allow future evaluation of
their impact on salmonids, the eco-
system, and fisheries. Abundance
at-sea was estimated by using the
strip transect method from a fixed-
wing aircraft with a belly viewing
port. Abundance on land was esti-
mated from 126-mm-format aerial
photographs of animals at haulouts
between Point Conception and the
California-Oregon border. The sum of
these two estimates represented total
abundance for central and northern
California. Both types of survey were
conducted in May-June 1998. Septem-
ber 1998, December 1998, and July
1999. A haulout survey was conducted
in July 1998. The greatest number
of sea lions occurred near Monterey
Bay and San Francisco Bay for all
surveys. Abundance was high in cen-
tral and northern California in 1998
when warm water from the 1997-98
El Nino affected the region and was
low in July 1999 when cold water
La Nina conditions were prevalent.
At-sea abundance estimates in cen-
tral and northern California ranged
from 12,232 to 40,161 animals, and
haulout abundance was 13,559 to
36,576 animals. Total abundance of
California sea lions in central and
northern California was estimated as
64,916 in May-June 1998, 75,673 in
September 1998, 56,775 in December
1998, and 25,791 in July 1999. The
proportion of total abundance to ani-
mals hauled-out for the four complete
surveys ranged from 1.77 to 2.13, and
the mean of 1.89 was used to estimate
a total abundance of 49,697 for July
1998. This multiplier may be appli-
cable in the future to estimate total
abundance of California sea lions
off central and northern California
if only the abundance of animals at
haulout sites is known.
Abundance and distribution of California sea lions
iZalophus californianus) in central and
northern California during 1998 and summer 1999
Mark S. Lowry
National Marine Fisheries Service
Southwest Fisheries Science Center
8604 La Jolla Shores Dr.
La Jolla. California 92037
E-mail address: mark.lowryia'noaa.gov
Karin A. Forney
National Marine Fisheries Service
Southwest Fisheries Science Center
110 Shaffer Road
Sanla Cruz, California 95060
Manuscript submitted 1 October 2002
to the Scientific Editor's Office.
Manuscript approved for publication
14 December 2004 by the Scientific Editor.
Fish. Bull. 103:331-343 (2005).
The California sea lion {Zalophus cali-
fornianus) is distributed from central
Mexico to British Columbia, Canada.
Four islands off southern California
(Santa Barbara, San Clemente, San
Nicolas, and San Miguel Islands) form
the reproductive center for the U.S.
population, although some pupping
occurs at various other haulout sites
in central California (Pierotti et al.,
1977; Keith et al., 1984). The number
of individuals off California varies
throughout the year because sea lions
from Mexico enter and leave Cali-
fornia waters and individuals from
California migrate southward into
Mexico or northward as far as Brit-
ish Columbia, Canada (Bartholomew,
1967; Bigg, 1988; and Huber, 1991).
In southern California, the abun-
dance of California sea lions peaks
during the summer breeding season
(Bartholomew, 1967; Odell, 1975). In
central and northern California, the
number of sea lions typically increases
in the autumn during the north-
ward migration, declines in winter,
increases in spring as sea lions move
to rookeries in southern California
and Mexico, and declines in summer
(Orr and Poulter, 1965; Mate, 1975;
Sullivan, 1980; and Griswold, 1985;
Bonnell et al.1).
Since the mid-1970s, the Califor-
nia sea lion population in the Unit-
ed States has expanded at an aver-
age of 5.0% per year and was most
recently estimated to be between
204,000 and 214,000 individuals in
1999 (Forney et al.2). This estimate
is roughly 2.7 times greater than
in 1981-83 (Bonnell et al.1). As the
U.S. sea lion population has grown,
concerns have arisen about potential
impacts on commercially harvested
fish stocks. California sea lions feed
on a variety of fish and cephalopods,
some of which are commercially im-
portant species, such as salmonids
(Oncorhynchus spp.). Pacific sardines
(Sardinops sagax), northern anchovy
(Engraulis mordax), Pacific mackerel
(Scomber japonicus), Pacific whiting
(Merluccius productus), rockfish (Se-
1 Bonnell, M. L., M. O. Pierson, and G.
D. Farrens. 1983. Pinnipeds and sea
otters of central and northern Califor-
nia, 1980-1983: status, abundance, and
distribution. Center for Marine Stud-
ies, Univ. California, Santa Cruz. OCS
Study MMS 84-0044, 220 p. Prepared
for Pacific OCS Region, Minerals Man-
agement Service, U.S. Department of
Interior, Camarillo, Calif. 93010, con-
tract no. 14-12-0001-29090.
2 Forney, K. A., J. Barlow, M. M. Muto,
M. Lowry, J. Baker, G. Cameron,
J. Mobley, C. Stinchcomb, and J. V.
Carretta. 2000. U.S. Pacific ma-
rine mammal stock assessments: 2000.
NOAATech. Memo.: NOAA-TM-NMFS-
SWFSC-300, 276 p. National Marine
Fisheries Service, Southwest Fisheries
Science Center, 8604 La Jolla Shores
Drive, La Jolla. CA 92037.
332
Fishery Bulletin 103(2)
bastes spp.), and market squid (Loligo opalescens) (Low-
ry et al., 1990. 1991; Lowry and Carretta, 1999; Weise,
2000). Effects on these resources have been estimated
for Monterey Bay only, where during the 1997-98 El
Nino sea lions consumed an estimated 269.1 to 804.7
metric tons (t) of salmon, 988.4 to 2206.8 t of sardine,
and 533.4 to 1827.4 t of rockfishes annually (Weise,
2000). Recently, salmon in central and northern Cali-
fornia have experienced population declines and some
stocks have been listed as threatened or endangered
under the U.S. Endangered Species Act. Although a
variety of factors are responsible for the decline (e.g.,
logging, dams, agriculture, fishing), some salmonid
populations are at such reduced levels that predation by
sea lions may negatively affect their recovery (NMFS3).
Sea lions also have been documented as interfering
with recreational fisheries by consuming bait and chum
and depredating hooked fish (Fluharty4).
Existing methods of population assessment have been
based on pup counts obtained at California sea lion
rookeries near the end of the breeding season and total
population has been estimated by extrapolating data
from a life history model (Barlow and Boveng, 1991;
Boveng5; Barlow et al.6 "; Forney et al.2). However, this
approach cannot be used outside of the breeding season
or in nonbreeding areas. Previous studies of California
sea lion abundance and distribution in central and
northern California during 1980-82 (Bonnell et al.1)
'NMFS (National Marine Fisheries Service). 1997. In-
vestigation of scientific information on the impacts of
California sea lions and Pacific harbor seals on salmonids
and on the coastal ecosystems of Washington, Oregon, and
California. NOAA Tech. Memo. NMFS-NWFSC-28, 172
p. Northwest Fisheries Science Center, 2527 Montlake Blvd.
E., Seattle, WA 98112-2097 and National Marine Fisher-
ies Service, Northwest Region, 7600 Sand Point Way N.E.,
Seattle, WA 98115-0070.
4 Fluharty, M. J. 1999. California sea lion interactions with
commercial passenger fishing vessel fisheries: a review of log
book data from 1994, 1995, and 1996. California Department
of Fish and Game Admin, report 99-2, 21 p. [Available from
California Department of Fish and Game, Marine Region,
San Diego Field Office, 4949 Viewridge Avenue, San Diego,
CA 92123.]
5 Boveng, P. 1988. Status of the California sea lion popula-
tion on the U. S. west coast. National Oceanographic and
Atmospheric Administration admin, report LJ-88-07, 26
p. Southwest Fisheries Science Center, 8604 La Jolla Shores
Drive, La Jolla, CA 92037.
6 Barlow, J., R. L. Brownell Jr., D. P. DeMaster, K. A. Forney,
M. S. Lowry, S. Osmek, T. J. Ragen, R. R. Reeves, and
R. J. Small. 1995. U.S. Pacific marine mammal stock
assessments. NOAA Tech. Memo. NMFS, NOAA-TM-NMFS-
SWFSC-219, 162 p. National Marine Fisheries Service,
Southwest Fisheries Science Center, 8604 La Jolla Shores
Drive, La Jolla, CA 92037.
7 Barlow, J., K. A. Forney, P. Scott Hill, R. L. Brownell Jr., J.
V. Carretta, D. P. DeMaster, F Julian, M. S. Lowry, T. Ragen,
R. and R. Reeves. 1997. U.S. Pacific marine mammal stock
assessments: 1996. NOAA Tech. Memo. NMFS, NOAA-
TM-NMFS-SWFSC-248, 223 p. National Marine Fisheries
Service, Southwest Fisheries Science Center, 8604 La Jolla
Shores Drive, La Jolla, CA 92037.
and 1995-96 (Beeson and Hanan8) included only ani-
mals on land; animals at sea were either not considered
or were included as a rough estimate. An assessment
approach was, therefore, needed to provide quantitative
estimates of California sea lion abundance in central
and northern California that included both animals at
sea and on land.
This study uses a combination of the strip-transect
method (to estimate at-sea abundance) and aerial pho-
tographic counts (to estimate abundance of sea lions
on land) in order to estimate the total abundance of
California sea lions in central and northern California.
Abundances were estimated separately for seven lati-
tudinal zones within central and northern California.
This study also describes distribution of sea lions by
age and sex class in central and northern California,
describes offshore distribution of sea lions, and intro-
duces a new multiplier that can be used to estimate the
total abundance of California sea lions at sea and on
land, when only an estimate of the number of animals
on land is available.
Methods
Survey dates and areas
Surveys were conducted during May-June, July, Septem-
ber, and December 1998, and July 1999. The May-June
survey occurred when salmonid smolts were migrating
out of rivers (NMFS3), the July survey when the United
States stock of California sea lions was expected to be
distributed mostly in California coastal waters, and the
September and December surveys when adult salmon
were migrating into rivers (NMFS3). The study area
encompassed the waters and shoreline of central and
northern California from Point Conception (34°26.8'N,
120°28.0'W) to the California-Oregon border (42°00.0'N,
124°12'W) within approximately sixty nautical miles of
the coast (Fig. 1).
Strip-transect surveys
A twin-engine, high-wing Partenavia PN68C- or PN68-
observer model aircraft was flown at an airspeed of 185
km/h during strip-transect and coastal haulout surveys.
Abundance of sea lions at sea was determined by using
the strip-transect method because previous aerial sur-
veys in central California indicated that densities of sea
lions would be too great in some areas to obtain reliable
measures of perpendicular distances for line-transect
density estimation. Previous aerial surveys using line
transect methods, conducted at 213 m altitude, indicated
a relatively flat detection function for sea lions between
Beeson, M. J., and D. A. Hanan. 1996. An evaluation of
pinniped-fishery interactions in California. Report to the
Pacific States Marine Fisheries Commission, 47 p. [Available
from Pacific States Marine Fisheries Commission, 205 SE
Spokane St., Suite 100, Portland, OR, 97202-6413.]
Lowry and Forney: Abundance and distribution of Zalophus californianus
333
42°
l l l l
i i i i i i i i i i i
\ Oregon
I \/
S California
41°
rV-Cape Mendocino
40
\ /
\ /
39°
\
\ i
rsi
38°
\
x / /M^San Francisco -
\ / K
\ / /I
37°
v' — /—^.Monterey -
36°
-
35°
N
\ / / (
A
\\_ 1 1
\T — \ — -_
\ 1 * 1 \
34°
i i i i i
Point Conception
127° 126° 125° 124° 123° 122° 121 120 11 9C
Longitude (°W)
Figure 1
Strip-transect lines (solid lines) within
the study area (dashed line I used for esti-
mating at-sea abundance of California sea
lions (Zalophus californianus) in central
and northern California.
approximately 85 meters left and right of the transect
line (Fig. 2; Carretta, personal commun.9). Therefore,
strip transect assumptions, that all individuals within
the observed strip are detected, were expected to be
valid within 85 meters left and right of the transect line.
In our study we lowered the altitude of the aircraft to
183 m to increase the detection probability for sea lions
in the water, especially in Beaufort 3-4 sea states. At
that altitude, the viewing area of a single observer view-
ing from the belly window extended from directly below
(90) to a declination angle of 65° on each side, resulting
in a total strip width of 170 m, or 85 m on each side of
the viewing window.
Transects followed predetermined lines that system-
atically zig-zagged the study area (Fig. 1). Surveys
were conducted in Beaufort sea states of 0-4. The lines
were flown from south to north to take advantage of
12 -
10 -
c
o
(J
a; 0.8 -
oS
■D
° 0.6 -
>,
.5
« 0.4 -
o
ct
0.2 -
00 01 0.2 0.3 0.4
Perpendicular distance (km)
Figure 2
Probability density function for California sea lion (Zalo-
phus californianus) sightings from an aircraft flying at an
altitude of 213 meters in Beaufort sea states 0-4. Figure
was provided by J. Carretta, National Marine Fisheries
Service, Southwest Fisheries Science Center, La Jolla,
CA. 92037.
9 Carretta, J. 1998. Personal commun. Southwest Fisher-
ies Science Center, NMFS, La Jolla, California, 92037.
sun angle and to minimize sun glare, except on a few
overcast days when southbound flights provided ample
visibility. Geographical positions were recorded at one-
minute intervals directly to a laptop computer by a se-
rial cable connected to the aircraft's global positioning
system (GPS). The following data were collected: num-
ber of California sea lions, GPS position, percentage of
cloud cover over the survey area, name of the observer
and data recorder, Beaufort sea state, transect num-
ber, and percentage of glare. Percentage of glare was
defined as the proportion of the viewing area in which
the observer could not see into the water because of
surface reflection caused by sun or cloud glare. During
the May-June survey we used a recorder, observer, and
a resting person — the resting person rotating with the
observer approximately every 30 minutes. During the
July, September, and December surveys, the resting
person was eliminated and the observer and recorder
rotated at approximately 30-minute intervals.
Abundance at sea
We used the nonparametric Kruskal-Wallis test for two-
way comparisons of the effects of glare and sea state on
California sea lion sighting rates. For these tests, each
transect segment with constant viewing conditions was
randomly assigned to one of five substrata, which served
as replicate samples for the tests. Viewing conditions
with significantly lower sighting rates were excluded
from the abundance analyses to reduce bias caused by
missed animals.
Two a posteriori geographic strata were created,
inshore (50,546 km2 total surface area) and offshore
334
Fishery Bulletin 103(2)
42
41° -
40
39c
38c
37c -
36°
35'
34c
Point Conception
J I I I I I I I I I I I I I L
N.
nA
WLg(O)
(1)
127° 126° 125° 124° 123° 122° 121° 120° 119°
Longitude (°W)
Figure 3
A posteriori stratification of study area
into "offshore" stratum and into seven
zones (A through G) within the "inshore"
stratum for estimating abundance of Cali-
fornia sea lions (Zalophus californianus)
from strip-transect data and haulout
count data.
(56,526 km2 total surface area), using transect intersect
points as the dividing line (Fig. 3). Differences between
the definition of haulout sites for the surveys in this
study and during previous surveys in 1980-82 and 1995
(Bonnell et al.1, and Beeson and Hanan8) made it neces-
sary to create additional zones within the inshore stra-
tum to allow comparisons of the three data sets. The
inshore stratum was thus divided into seven zones ("A"
through "G"), separated at the following latitudes: 1)
35°25'N; 2) 36°15'N; 3) 37°20'N; 4) 38°10'N; 5) 39°30'N;
and 6) 40°50'N (Fig. 3). The zones were separated where
gaps occurred in the distribution of haulout areas along
the coastline. Total area sizes for the seven zones were
the following: A: 7647 km2; B: 7206 km2; C: 8025 km2;
D: 6153 km2; E: 7790 km2, F: 6030 km2, and G: 7695
km2. At-sea abundance was obtained separately for
offshore and inshore strata, and for each zone within
the inshore stratum, by using a modified strip-transect
formula that included a correction, g(0), for diving ani-
mals that were not available to be seen:
where Nc = corrected total abundance (corrected for
animals below the surface);
n = number of individuals sighted within the
strip-transect;
A = total size of study area (in km2);
W = the strip width (in km);
L = distance surveyed (in km) calculated as the
sum of the great circle distances between
position fixes', and
g(0) = probability that a sea lion will be visible
at the surface within the strip viewed by
the observer as the aircraft passes over the
water.
Coefficients of variation (CV) and lognormal 95% con-
fidence limits of these abundance estimates were cal-
culated by using standard formulae (Buckland et al.,
1993).
Probability of missing submerged sea lions
We estimated the probability of seeing sea lions at the
surface, g(0), from dive data in Feldkamp et al. (1989)
derived from 14 foraging trips made by seven lactating
adult female California sea lions during late breeding-
season:
g<0) =
t+s + r
t+s+r+d
(2)
where t = average time (hours) spent at the surface
between dives within diving bouts by an adult
female sea lion;
s = average time (h) spent swimming near the
surface between diving bouts by an adult
female sea lion;
r = average time (h) spent resting at the surface
between diving bouts by an adult female sea
lion; and
d= average time (h) spent diving during diving
bouts by an adult female sea lion.
From seven female sea lions, Feldkamp et al. (1989)
calculated averages of 12.0 hours (no SD given) spent at
the surface between dives within diving bouts (t), 21.9
hours (SD = 9.5 hours) spent swimming near the surface
between diving bouts (s), 1.6 hours (SD = 1.6) spent rest-
ing at the surface between diving bouts (r), and 17.3
hours (SD = 6.7) spent diving during diving bouts (d). We
calculated the CV forg(0) from the standard deviations
of diving data. In using these data we assumed that
between dives, sea lions swam near the surface and at
a depth where they would be seen by an observer in
the aircraft and that sea lions were not visible to an
observer in the aircraft during dives. Dive data were
not available for other age and sex classes; therefore,
Lowry and Forney: Abundance and distribution of Zalophus californianus
335
it was assumed that the proportion of time spent at
or near the surface was similar for adult females and
other age and sex classes and did not vary significantly
within region, season, and year.
All counts were conducted by the first author, who is
an experienced counter with high intercount reliability
(Lowry, 1999). Geographical positions (latitude and
longitude) were assigned to each haulout site.
Photographic surveys
The aircraft was flown from north to south directly
over the coastline or slightly offshore at an altitude
of 183 to 213 m (typically 213 m) to locate sea lions
onshore. The low altitude ensured that California sea
lions could be detected on rocky substrates, aided in
identification of different pinniped species, and enabled
accurate counts from aerial photographs. All hauled-out
California sea lions onshore were photographed. At the
Farallon Islands, the aircraft was flown at an altitude
of 366 to 457 m (typically 396 m) to prevent disturbance
of nesting seabirds. Multiple passes were made over
large rocks or islands to ensure that the entire rock or
island was photographed. Surveys were made without
regard to tidal conditions at any time of day between
approximately two hours after sunrise and two hours
before sunset.
Sea lions were photographed with a 126-mm-format
KA-76 camera (Chicago Aerial Industries, Inc., Chi-
cago, IL) equipped with image motion compensation
(IMC) and operated at a cycle rate that achieved 67%
overlap between adjacent frames. The geographical
position of each photograph was recorded by linking
the camera (mounted vertically inside the belly of the
aircraft) to a computer and GPS unit. A 152-mm fo-
cal-length lens was used for low altitude photography
(i.e., 183-213 m) and a 305-mm focal-length lens was
used for higher altitude photography (i.e., 366-457 m).
Kodak Aerochrome MS Film 2448, a very fine-grained,
medium-speed, color transparency film, or Aerochrome
HS Film SO-359, a very fine-grained, high-speed, color
transparency film, was used. The camera was set at
an aperture of f/5.6 and a shutter speed between 1/400
and 1/2000 second.
Photographic counts
Sea lions were counted from photographs illuminated
with a light table by using a 7-30X zoom binocular
microscope. Counts were obtained for five age and sex
class categories: pups, juveniles, adult females or young
males of similar size, subadult males, and adult males.
Age and sex class distinctions were determined from
size and other external characteristics (e.g., hair color
on head, presence of sagittal crest, chest size, fore flip-
per width, snout shape, and body coloration). Animals of
each age and sex class were marked on a clear acetate
plastic overlay with different colored pens as each was
counted. Marks on the acetate were then compared and
verified with overlapping photographs. The acetate was
placed on another photograph at the exact position of the
coastline where the count ended previously and the count
was continued on the uncounted portion. One count was
made for each rock, island, or mainland haulout site.
Analysis of haulout data
Counts of sea lions made in this study were compared to
those obtained by earlier investigators in 1980-82 (Bon-
nell et al.1) and 1995-96 (Beeson and Hanan8) by using
nested ANOVAs and paired //-tests. The null hypothesis
of no difference in zonal counts was used to examine
differences in counts by zone, season, year, and survey.
The counts were 0.45 power transformed (with Systat
6.0 for Windows, SPSS Inc., Chicago, IL) because their
distribution was skewed toward zero.
Results
Sighting rates and g(Q)
No difference was found (P>0.05) for number of sight-
ings, total animals seen, and mean group size during
Beaufort sea state conditions 1 through 4. A sharp
decline in sighting rates was observed when sightings
were grouped into glare categories of 0-24% (rc=27.3
sightings/1000 km), 25-49% (n = 17.5 sightings/1000
km), 50-74% (ra=10.7 sightings/1000 km), and 75-100%
(?2 = 0 sightings/1000 km). Sighting rates were signifi-
cantly greater at 0-49% glare than at 50-100% glare
(P<0.001 for all surveys combined); therefore, only data
collected in 0-49% glare were used for at-sea abundance
estimation. With only data collected in 0-49% glare,
we used 48-76% of kilometers surveyed and 79-89%
of sightings.
The probability of sighting a sea lion at the surface,
g(0), was estimated as 0.67 (with a CV of g(0) = 0.12).
At-sea abundance
Strip-transect survey effort totaled 1272 km during
26-30 May 1998, 2856 km during 12-28 September
1998, 2993 km during 1-11 December 1998, and 1175 km
during 13-21 July 1999 (Fig. 4). No transect survey was
conducted in July 1998 because of persistent low clouds
and high winds. Transect distances in 0-49% glare
conditions are given in Table 1. Nearly all sightings
were within the inshore stratum, and most were within
20 nautical miles from the mainland coast (Fig. 5). Cor-
rected at-sea abundance estimates for sea lions in the
study area (Table 1) were 28,340 (May 1998), 40,161
(September 1998), and 24,720 animals (December 1998).
For July 1999, a corrected abundance estimate for the
inshore stratum in July 1999 was 11,492 animals (Table
1). From the total abundance estimated in the three
1998 surveys, the average proportion represented by
the offshore stratum was 0.073 (range: 0.000-0.204).
From this proportion, we estimated that there were
about 829 sea lions in the unsurveyed offshore stratum
336
Fishery Bulletin 103(2)
A
Oregon
r r
1 A
California
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A
41
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40
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B
a.
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39"
\ /
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37
36°
N / 1 G
3 5
.
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A
34°
\.y •©«-
B
\ Oregon
41
\\/\ California
40
.
*9v
39"
38°
.
%
37°
36°
A >;&
35°
-
34°
V' -oo>
127" 126° 125 124 123 122° 121 120° 119=
127° 126° 125 124 123 122= 121= 120= 119=
c
Oregon
d
California
A
\NC\
B
--
"
V '
\ C
\ /
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x /? E
-
V^Ca" "
F
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A
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41°
I N A
40
\ X" B
39°
\ j\C
38°
37°
36°
35=
34°
A V*^N
127" 126" 125= 124= 123" 122" 121" 120" 119"
127" 126" 125° 124° 123° 122° 121" 120° 119°
Longitude (°N)
Figure 4
California sea lions (Zalophus californianus) sightings (o) during strip-
transect surveys flown in Beaufort sea states 0-4 and 0-499£ glare
conditions (solid zig-zag linel. (A) 26-30 May 1998, (B) 12-28 September
1998, (C) 1-11 December 1998, and (D) 13-21 July 1999.
in July 1999, and this number was used to extrapolate
a total at-sea abundance estimate within the study area
of 12,232 sea lions. CVs of corrected estimates were 0.32
(May 1998), 0.26 (September 1998), 0.50 (December
1998), and 0.43 (July 1999; Table 1).
During the May-June 1998 survey, sea lions were
most abundant in the northern part of the study area
(Table 1). In September 1998, sea lions were most
abundant in the central part of the study area (zones
D and E). In December 1998 they were most abundant
in the southern portion of the study area (zones E
and F). During July 1999, sea lions were most abun-
dant in the south-central portion of the study area
(zone E ).
Lowry and Forney: Abundance and distribution of Zalophus califormanus
337
70
60
50
40
30
20
10
, Sightings V~\ % Km surveyed
17 sightings
612 km surveyed
tki
i
f-L-H
_
40
30
-20
10
0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80-69 90-99 100-109110-120
y 70
60 -
50
40
30
20
10
| % Sightings ^]% Km surveyed
40 sightings
2,181 km surveyed
40
-30
-20
-10
_n
0
70
60
50 i
40
30
20
10
0
B
70
60
50
40-
30
20
10
0
Sightings f~J % Km surveyed
67 sightings
1 ,796 km surveyed
\M
0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79
40
30
20
10
90-99 100-109110-120
D
, Sightings [~J % Km surveyed
18 sightings
888 km surveyed
_Q
t— =H h
-+-
40 2.
30
-20
10
0-9 '10-19 20-29 30-39 40-49 50-59 '60-69 70-79 '80-69 90-99 100-109110-120 ' ~ "0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 60-89 90-99 100-109110-120
Distance from shore (km)
Figure 5
Distances from shore for California sea lions (Zalophus californianus) sighted and kilometers from shore for California
sea lions that were surveyed during strip transect surveys in Beaufort sea state 0-4 and 0-49% glare conditions. (A)
26-30 May 1998, (B) 12-28 September 1998, (C) 1-11 December 1998, and (Di 13-21 July 1999.
Haulout abundance
In 1998 and 1999, aerial photographic surveys of sea
lion haulouts in central and northern California were
conducted during 31 May-8 June 1998, 7-18 July 1998,
11-20 September 1998, 14-16 December 1998, and 6-11
July 1999. For the July 1998 survey, low clouds pre-
vented aerial surveys of the coastline from Point Sal
(34°54.1'N, 120°40.0'W) to Point Conception (counts
from 1999 were used for these areas) and from the
Klamath River (41°32.5'N, 124°04.7'W) to Humboldt
Bay (40°45.4'N, 124°14.4'W). To estimate abundance
in the latter missed area, we obtained ground counts
from the mainland at all haulouts except Turtle Rocks
<41°08.0'N, 124°10.9'W) and Redding Rock (41°20.6'N,
124°10.5'W). In July 1999 a low cloud layer prevented
surveys of the coastline between Golden Gate Bridge
(37°51.1'N, 122 34.0'W) and just north of Ano Nuevo
Island (37°06'N, 122 20'W). This gap should have had
virtually no effect on the total counts, however, because
there is only one minor haulout in this region.
The number of sea lions hauled-out in the study area
(Table 2) were 36,576 (May 1998), 26,260 (includes
estimate, July 1998), 35,512 (September 1998), 32,055
(December 1998), and 13,559 (July 1999). There was
no significant difference in total number of sea lions
between the seven zones (P= 0.229) and between sea-
sons (P=0.179; Table 3). More sea lions were counted
in 1998-99 than during previous surveys in 1980-82
and 1995-96 (P<0.003 for both tests), but no difference
in counts was found between 1980-82 and 1995-96
surveys (P=0.232; Table 3).
In 1998, the greatest numbers of sea lions were found
in zone D and E (Table 2), corresponding to the San Fran-
cisco and Monterey Bay regions; most animals hauled out
at Ano Nuevo Island and South Farallon Islands. Juve-
niles and adult-females or young-males were the most
prevalent age and sex classes found in the study area in
1998 (Table 2). More adult males were counted during
the May-June 1998 survey than during other surveys. In
1998 the number of pups in the study area ranged from
22 (December 1998) to 149 (May- June 1998).
338
Fishery Bulletin 103(2)
Table 1
Abundance estimates for California sea
lions \Zalophus californianus) at sea from
sightings
dur
ng strip-transect surveys in the
central and northern California study area during three
surveys in
1998 and
one
survey in
1999, under 0-49% glare and Beau-
fort 0-4 sea state conditions. No survey
was conducted wi
thin the offshore stratum in July 1999.
'nsufficient kilometers were sur-
veyed for estimating at-
sea abundance.
CV(Ar>, and 95%
confidence limits for
strata noted v>
ith
a dash I — ). Corrected estimates
are based on g(0) calcu
ated from dive
studies on lactat
ing adult females du
ring
late breec
ing
-season (Feldkamp
et al„ 1989).
Corrected
Kilo
No. of
No. of
surveyed
CV
Abundance
Lower 95%
Upper 95%
Stratum
sightings
animals
(kml
(An
(A,.)
CL
CL
26-30 May 1998
Inshore: zone A
—
—
0
—
—
—
—
Inshore: zone B
5
6
96
—
3977
—
—
Inshore: zone C
—
—
19
—
—
—
—
Inshore: zone D
6
6
63
—
5156
—
—
Inshore: zone E
—
—
0
—
—
—
—
Inshore: zone F
4
4
118
—
1793
—
—
Inshore: zone G
—
—
6
—
—
—
—
Inshore: total
15
16
302
0.29
23,541
11,224
49,376
Offshore
2
3
310
1.01
4799
561
41,040
Inshore + offshore
17
19
612
0.32
28,340
15,237
52,713
12-28 September 1998
Inshore: zone A
1
1
121
—
556
—
—
Inshore: zone B
5
5
140
—
2256
—
—
Inshore: zone C
6
7
117
—
4235
—
—
Inshore: zone D
18
23
108
—
11,552
—
—
Inshore: zone E
16
25
146
—
11,752
—
—
Inshore: zone F
5
5
69
—
3852
—
—
Inshore: zone G
15
16
220
—
4919
—
—
Inshore: total
66
82
919
0.27
39,595
24,210
64,757
Offshore
1
1
877
1.1
566
82
3923
Inshore + offshore
67
83
1796
0.26
40,161
24,205
66.635
1-11 December 1998
Inshore: zone A
4
4
213
—
1262
—
—
Inshore: zone B
6
7
219
—
2026
—
—
Inshore: zone C
4
4
238
—
1185
—
—
Inshore: zone D
2
3
124
—
1303
—
—
Inshore: zone E
15
25
175
—
9773
—
—
Inshore: zone F
3
18
59
—
16,129
—
—
Inshore: zone G
6
6
175
—
2316
—
—
Inshore: total
40
67
1203
0.5
24,720
9333
65,479
Offshore
0
0
977
0
0
0
0
Inshore + offshore
40
67
2181
0.5
24,720
9726
62,831
13-21July 1999
Inshore: zone A
0
0
124
—
0
—
—
Inshore: zone B
0
0
174
—
0
—
—
Inshore: zone C
0
0
185
—
0
—
—
Inshore: zone D
—
—
0
—
—
—
—
Inshore: zone E
11
14
146
—
6573
—
—
Inshore: zone F
0
0
135
—
0
—
—
Inshore: zone G
7
9
128
—
4762
—
—
Inshore: total
18
23
888
0.5
11,492
4,358
30,304
Offshore (estimated)
0
0
23
0.9
829
183
3752
Inshore + offshore
18
23
911
0.43
12,232
5427
27,572
Lowry and Forney: Abundance and distribution of Zalophus califormanus
339
Table 2
Counts of California sea 1
ions (.Zalophus
californianus)
made from 126-mm-format
aerial color
photographs
~or five age- and
sex-class categories found
in seven zones
along the cent
ral and northern California
coast during
four surveys
in 1998 and one
survey in 1999.
Adult females
Subadult
Adult
Zone
Pups
Juveniles
or young males
males
males
Total
31 May-8 June 1998
A
0
299
1948
1554
528
4329
B
0
3195
1534
2371
911
8011
C
0
698
751
513
530
2492
D
11
3639
5821
1636
555
11,662
E
99
3481
2993
678
464
7715
F
5
186
380
93
52
716
G
34
684
886
32
15
1651
All
149
12,182
14,313
6877
3055
36,576
7-18 July 1998
A
0
358
206
148
22
734
B
(1
2382
116
162
62
2722
C
0
320
287
190
101
898
D
55
1918
7318
1283
290
10,864
E
54
2920
3226
564
178
6942
F
12
63
510
125
50
760
G
0
779
1362
92
30
3340'
All
121
8740
13,025
2564
733
26,260'
11-20 September 1998
A
0
73
1325
1548
559
4165
B
0
1136
351
938
173
2598
C
0
524
594
584
56
2028
D
18
1506
8453
1136
100
11,213
E
22
2122
8056
671
188
11,059
F
6
470
1440
78
24
2018
G
0
1224 '
1175
29
3
2431
All
46
7985
21,394
4984
1103
35,512
14-16 December 1998
A
0
27
105
162
123
663
B
0
193
1790
2950
429
5362
C
0
54
201
995
516
1766
D
1
765
10,310
632
97
11,805
E
12
1566
8035
311
103
10,027
F
9
307
903
84
15
1318
G
0
201
831
63
19
1114
All
22
3359
22,175
5197
1302
32,055
6-11 July 1999
A
0
111
167
5
4
287
B
0
6
6
1
1
14
C
0
0
0
1
0
1
D
3
193
970
109
91
1366
E
4
1226
5652
398
65
7345
F
0
270
578
90
14
952
G
0
919
2426
186
63
3594
All
7
2725
9799
790
238
13,559
1 Includes 1077 unknown age
- and sex-class sea lions that were estimated to have been missed
n zone G.
340
Fishery Bulletin 103(2)
Table 3
Results of four nested ANOVAs on haulout counts of California sea lions (Zalophus californianut
i found in
7 zones v.
ithin central
and northern California (refer to text and Fig.
3 for zone descriptions)
The tests
of ANOVA revealed differences between zones.
season, years, and surveys. 1980-82 sur
veys
were conducted by Bureau of Land Management (Bonnell et al.1) and 1995-96
surveys were conducted by the California
Department of Fish and Game (Beeson and Hanans)
Year was
nested within
survey,
season was nested within year, and zone was nested within season.
Source
Sum-of-squares
df
Mean-squa
re
F-ratio
P
1998-99 surveys
Season
1427.2
3
475.7
2.177
0.179
Zone (season)
9157.0
24
381.5
1.746
0.229
1998-99 surveys vs. summer and
autumn 1995 and winter 1996 surveys
Survey
1610.7
1
1610.7
11.449
0.003
Season (survey)
2019.4
5
403.9
2.871
0.037
Zone (season)
11,008.8
24
458.7
3.260
0.003
1998-99 surveys vs. 1980-82 surveys
Survey
1731.6
1
1731.6
21.224
<0.001
Year (survey)
2235.9
3
745.3
9.135
<0.001
Season (year)
3576.5
12
298.0
3.653
<0.001
Zone (season)
14,761.2
24
615.0
7.538
<0.001
1980-82 surveys vs. summer and
autumn 1995 and winter 1996 surveys
Survey
81.9
1
81.9
1.457
0.232
Year (survey)
649.0
3
216.3
3.849
0.013
Season (year)
3491.5
10
349.1
6.211
<0.001
Zone (season)
11,027.6
24
459.5
8.174
<0.001
In 1999, the majority of sea lions were found between
the San Francisco Bay area and Point Conception (zones
D through G). Zone E had the greatest number of sea
lions (Table 2); the majority of these animals hauled out
at Ano Nuevo Island. As in 1998, juveniles and adult-
females or young-males were the most prevalent age
and sex classes (Table 2). Only seven pups were counted
in the study area during July 1999. The number of sea
lions counted in 1999 was 52% of that counted in July
1998.
Total abundance
There was a significant correlation (r=0.468, P=0.024)
between at-sea abundance and haulout abundance within
zones. Total abundance of California sea lions in central
and northern California during 1998 was estimated
to be 64,916 in May-June, 75,673 in September, and
56,775 in December. Total abundance in July 1999 was
estimated at 25,791 individuals. The proportion of total
abundance to animals hauled-out was 1.77, 2.13, 1.77,
and 1.90, respectively, with a mean of 1.89 and a CV for
small samples (Sokal and Rohlf, 1995) of 0.09. Using the
mean multiplier of 1.89 on haulout counts obtained in
July 1998 (Table 2), when at-sea abundance could not
be estimated, we estimated total abundance as 49,697
(CV=0.09) animals for that period.
Discussion
This abundance study of California sea lions in central
and northern California successfully integrated two
methods: 1) strip transect surveys to estimate abun-
dance at sea; and 2) aerial photographic surveys to esti-
mate haulout abundance. TheglO) detection probability
derived from previously published dive data allowed esti-
mation of total abundance, including animals expected
to be underwater during at-sea strip transect surveys.
Previous surveys where transect methods similar to ours
were used in the Southern California Bight in 1975-78
and in central and northern California in 1980-83
(Bonnell and Ford, 1987; Bonnell et al.1- 10) did not have
information for deriving ^(0), and, therefore, densities of
sea lions at sea were underestimated in these studies.
California sea lions were abundant in central and
northern California during May through September
Bonnell, M. L., B. J. Le Boeuf, M. O. Pierson, D. H. Dett-
man, G. D. Farrens, C. B. Heath, R. F. Gantt, and D. J.
Larsen. 1980. Summary of marine mammal and seabird
surveys of the Southern California Bight area 1975-1978.
Vol. 3: Investigators reports, part 1 — pinnipeds of the South-
ern California Bight, 535 p. Univ. Calif, Santa Cruz, Calif.
95064. Final Report to the Bureau of Land Management,
under Contract AA550-CT7-367. [NTIS PB81-248-71.1
Lowry and Forney: Abundance and distribution of Zalophus califormanus
341
1998 when waters were warm because of the strong
1997-98 El Nino. Increased abundance of juveniles
and adult females were observed in this region during
previous El Nifios (Huber. 1991; Sydeman and Allen,
19991 and during our May-June, July, and September
1998 surveys. The increase in adult females in central
California in 1998 resulted in an increase in the num-
ber of pups counted at Ano Nuevo and South Farallon
Islands (106 pups in 1998 vs. 23 in 1997), and below
normal births at rookeries in southern California (Low-
ry, unpubl. data, Forney et al.2). In contrast to 1998,
during the summer of 1999 fewer sea lions were found
in central and northern California, especially north of
San Francisco (zones A, B, and C), and greater num-
bers were found at rookeries in southern California (M.
Lowry, unpubl. data) when waters were cold as a result
of the La Nina oceanographic condition that began in
October 1998 (Hay ward et al., 1999).
The abundance and distribution of California sea
lions were distinctly different between El Nino and
La Nina periods. During El Nino, sea lions were very
abundant in central and northern California, and were
distributed throughout the region. In contrast, during
summer 1999 (our only survey that year [La Nina|), sea
lions were less abundant than during summer 1998,
and they were distributed only south of the San Fran-
cisco Bay area. The abundance and distribution pattern
of summer 1999 is similar to the observed abundance
and distribution pattern described by earlier studies
(Chambers, 1979; Griswold, 1985; Weise, 2000; Bonnell
et al.1). During periods of elevated sea lion abundance
in central and northern California, such as those ob-
served during the 1998 El Nino, we would expect 1)
increased consumption of prey species because of more
sea lions feeding in the area, 2) increased pressure on
coastal fisheries resources because sea lions feed on
commercially valuable species (see Lowry et al., 1990,
1991; Lowry and Carretta, 1999; Weise, 2000), and 3)
increased interactions with commercial and sport fisher-
ies. The opposite would occur during periods of low sea
lion abundance during non-El Nino years. Greater abun-
dance of California sea lions in central and northern
California during the 1997-98 El Nino event, therefore,
would be expected to have a greater effect on salmonids
and other sea lion prey species, and on fisheries than
would occur during non-El Nino years.
Abundance of sea lions in central and northern Cali-
fornia during 1998 was greater in May- June (spring)
and September (fall) and less in July (summer) and
December (winter). This bimodal phenomenon, also ob-
served in the past (Sullivan, 1980; Bonnell et al.1), is
due to migrating subadult and adult male sea lions on
their way to (in fall) and from (in spring) Oregon (Mate,
1975), Washington, and British Columbia (Bigg, 1988).
However, these seasonal differences were not signifi-
cantly different, likely because of low power (only one
year of data), or because the animals behaved differ-
ently from other years. In fact, fewer subadult and adult
males were present at southern California rookeries
during the 1998 July census (near the end of breeding
season) than were present during 1997 and 1999 (M.
Lowry, unpubl. data). The large number of sea lions in
central and northern California during 1998 was the
result of a more numerous population (U.S. population
estimated at 204,000 to 214.000 in 1999) than existed
when previous surveys were conducted in 1980-82 and
1995-96 (U.S. population estimated at 76,000 in 1982
and at 167,000 to 188,000 in 1995) (Barlow et al.7; For-
ney2; Bonnell et al.1, and Beeson and Hanans>.
In central and northern California, California sea
lions have been sighted during aerial surveys (Carretta
and Forney"; present study) and tracked with satellite
tags (Melin and DeLong, 2000; Melin, 2002) up to 100
nautical miles from shore. However, our surveys indi-
cated that they forage predominantly within 20 nautical
miles from shore.
The strip transect method assumes that all animals
within a strip are sighted by the observer. Although we
found no difference in sighting rate between Beaufort
sea state scales 0-1, 2, 3, and 4, Carretta et al.12 found
during their 1998-99 line transect survey in waters
off San Clemente Island, California, that the effective
strip width of pinniped sightings at 213 m altitude
was slightly less in Beaufort sea states 3-4 (184 m on
each side) than in Beaufort sea states 0-2 (256 m on
each side). Their results suggest that if our analysis
suffered from reduced detection probability at high
sea states, then we may have underestimated at-sea
abundance of sea lions or increased the variance of at-
sea sea lion abundance. This potential negative effect
was minimized in our surveys by surveying at a lower
altitude (183 m) than the 213 m altitude surveyed by
Carretta et al.12
The g{0) correction derived from dive and foraging
studies of lactating adult-female California sea lions
during late breeding season (July-August) may be an
additional source of error in our at-sea abundance es-
timates. It may not be representative of nonlactating
adult females and other age- and sex-class sea lions,
and it may not be representative for all seasons or
different oceanographic cycles (e.g., El Nino and non-
El Nino). Dive data from various ages and sexes are
needed to test these assumptions, but existing dive data
from a single age+sex group provided a rough correc-
tion to account for animals underwater during at-sea
11 Carretta, J. V. and K. A. Forney. 1993. Report of two aerial
surveys for marine mammals in California coastal waters
utilizing a NOAA DeHavilland twin otter aircraft March
9-April 7, 1991 and February 8-April 6. 1992. NOAA
Tech. Memo. NMFS, NOAA-f M-NMFS-SWFSC-185, 77
p. National Marine Fisheries Service, Southwest Fisheries
Science Center, 8604 La Jolla Shores Drive, La Jolla, CA
92037.
12 Carretta. J. V., M. S. Lowry, C. E. Stinchcomb, M. S. Lynn,
and R. E. Cosgrove. 2000. Distribution and abundance of
marine mammals at San Clemente Island and surrounding
offshore waters: results from aerial and ground surveys in
1998 and 1999. National Oceanographic and Atmospheric
Administration admin, report LJ-00-02, 51 p. Southwest
Fisheries Science Center, 8604 La Jolla Shores Drive, La
Jolla, CA 92037.
342
Fishery Bulletin 103(2)
surveys. Seasonal differences may exist, but data in
Feldkamp et al., (1989, 1991) and Melin (2002) indicate
that these differences are negligible. Feldkamp et al.
(1991) showed differences in diving behavior during El
Nino and non-El Nino, but Melin (2002) did not find as
much difference in diving behavior during El Nino and
non-El Nino (with the exception of longer transit time
to foraging grounds during El Nino).
Error in age- and sex-class abundance estimates at
haulouts is also affected by subjectivity and inter-ob-
server differences in age and sex classification of sea
lions. Therefore, age- and sex-class counts provided
in these surveys, although conducted by a single ex-
perienced observer (M. Lowry), serve as approximate
indices of sea lion age- and sex-class distributions in
central and northern California. These indices will be
useful for future attempts to estimate consumption of
prey by sea lions along central and northern California,
given that nutritional requirements differ among age
and sex classes.
By estimating abundance of sea lions on land as
well as at-sea, we were able to derive a multiplier for
estimating total abundance from counts of animals
hauled out on land. This multiplier can be applied to
future land counts of California sea lions in central
and northern California to estimate total abundance,
as has been done for harbor seals in California, Or-
egon, and Washington (Huber et al., 2001; Barlow
et al.6; Forney et al.2). It may also be useful for es-
timating total abundance from counts of sea lions
hauled out in Oregon, Washington, and British Co-
lumbia because the age- and sex-class structure of sea
lions is similar to that found in central and northern
California. However, the multiplier should not be used
for smaller areas (such as the zones in the inshore
stratum) or for other species, because regional and
interspecies differences may exist. In particular, it
would not be appropriate for regions where sea lions
reproduce, such as in the Southern California Bight
(SCB) and in Mexico, because adult females that are
rearing pups may spend a different proportion of their
time at sea. For that reason, it would be judicious to
conduct concurrent offshore and haulout surveys in the
SCB and Mexico to derive a correction factor for each
geographical region of the sea lion's range. Multipliers
could also be derived for smaller areas (such as our
zones) by conducting suitably designed smaller-scale
at-sea surveys in conjunction with counts of animals
hauled out, or by using satellite or radio telemetry
tags to directly measure the relative times at sea and
on land.
The multiplier for deriving total abundance from
haulout counts provides researchers and resource man-
agers with an alternative method for estimating total
population abundance or abundance of a stock. Abun-
dance estimates derived with this new approach can
be compared to abundance estimates obtained with
more conventional methods (such as the life history
model), and may provide a means for estimating to-
tal abundance when life history data are unavailable.
The approach used in the present study may be par-
ticularly useful for estimating abundance at times and
places unrelated to breeding activities, or for periods
when breeding is disrupted, as with El Nino conditions.
Abundance estimates and distributional data provided
by these methods can be used to determine where and
when the greatest effects on salmon and other prey spe-
cies may occur. Diet studies at major hauling areas in
conjunction with abundance surveys to derive consump-
tion estimates are required to determine the effect of
California sea lions on salmon and other sea lion prey
species of the region.
Acknowledgments
This research was supported financially by the Office
of Protected Resources, National Marine Fisheries Ser-
vice. We greatly appreciate the assistance given by Jim
Gilpatrick, Charlie Stinchcomb, and, especially, Scott
Benson of Moss Landing Marine Laboratories during the
surveys. Jay Barlow provided guidance. Special thanks
to Morgan Lynn of the Southwest Fisheries Science
Center who kept the photographic equipment functioning
properly. Henry Orr of the Southwest Fisheries Science
Center helped with illustrations. Research within Gulf of
the Farallones National Marine Sanctuary and Monterey
Bay National Sanctuary was conducted under National
Marine Sanctuary Permit GFNMS/MBNMS-20-98. This
research was conducted under MMPA Research Permit
No. 774-1437. We greatly appreciated the reviews and
comments by Jay Barlow, Jeff Laake, Jim Harvey, and
three anonymous reviewers.
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344
Abstract— The narrow-barred Span-
ish mackerel (Seomberomorus com-
merson) is widespread throughout the
Indo-West Pacific region. This study
describes the reproductive biology of
S. commerson along the west coast
of Australia, where it is targeted for
food consumption and sports fishing.
Development of testes occurred at a
smaller body size than for ovaries,
and more than 90^ of males were
sexually mature by the minimum
legal length of 900 mm TL compared
to 50f7f of females. Females dominated
overall catches although sex ratios
within daily catches vary consider-
ably and females were rarely caught
when spawning. Seomberomorus
commerson are seasonally abundant
in coastal waters and most of the
commercial catch is taken prior to
the reproductive season. Spawning
occurs between about August and
November in the Kimberley region
and between October and January
in the Pilbara region. No spawning
activity was recorded in the more
southerly West Coast region, and only
in the north Kimberley region were
large numbers offish with spawning
gonads collected. Catches dropped to
a minimum when spawning began in
the Pilbara region, when fish became
less abundant in inshore waters and
inclement weather conditions limited
fishing on still productive offshore
reefs. Final maturation and ovulation
of oocytes took place within a 24-hour
period, and females spawned in the
afternoon-evening every three days.
A third of these spawning females
released batches of eggs on consecu-
tive days. Relationships between
length, weight, and batch fecundity
are presented.
Variability in spawning frequency and
reproductive development of the narrow-barred
Spanish mackerel (Seomberomorus commerson)
along the west coast of Australia
Michael C. Mackie
Paul D. Lewis
Daniel J. Gaughan
Stephen J. Newman
Western Australian Marine Research Laboratories
Department of Fisheries
Government of Western Australia
West Coast Drive
Waterman, Western Australia 6020. Australia
E-mail address (for M C Mackie) mmackietg'fish.wa. gov.au
Manuscript submitted 1 October 2002
to the Scientific Editor's Office.
Manuscript approved for publication
14 December 2004 by the Scientific Editor.
Fish. Bull. 103:344-354 (2005).
The narrow-barred Spanish mack-
erel (Seomberomorus commerson) is a
prized food fish targeted by fishermen
throughout its range in the Indo-West
Pacific region (Collette and Nauen,
1983). Reaching over 2.4 m in length
and 45 kg in weight, this pelagic spe-
cies is seasonally abundant in coastal
waters where it often schools in large
numbers. In Australian waters, the
commercial mackerel fishery targets
these schools using trolling methods,
and 2362 metric tons were caught in
2001-02 for domestic and overseas
markets (ABARE. 2003).
Seomberomorus commerson is also
a premier sport fishing species, tar-
geted by an increasing number of rec-
reational anglers throughout its broad
Australian distribution. The combined
commercial and recreation take of S.
commerson has put significant pres-
sure on stocks in Queensland (QLD)
waters, leading to a possible decline
in the spawning stock abundance
(McPherson and Williams, 2002).
The biology of S. commerson in these
waters has been well studied (e.g.,
Munro, 1942; McPherson, 1981, 1992,
1993). Biological information is also
available for S. commerson in wa-
ters of the Northern Territory (NT;
Buckworth1), where stocks are still
recovering from a prolonged period of
exploitation by foreign gill-net opera-
tors that ended in 1986. In contrast,
little is known about the stock status
and biology of S. commerson in West-
ern Australian (WA) waters, despite
the fact that catches are similar to
those taken in QLD and the NT, and
commercial fishermen have expressed
concern about increasing fishing pres-
sure on this species in WA. Recent
moves to overhaul management of the
mackerel fishery in WA (in which S.
commerson is the dominant species)
have further highlighted the need for
more information on the biology and
stock status of S. commerson along
the WA coast.
Research to enable a stock assess-
ment of S. co?7imerson in WA waters
was therefore commenced in 1999.
Description of reproductive biology
was a key focus of this study, since
this information is required for stock
assessment models and for manage-
ment controls such as minimum legal
lengths, which were previously set
with little knowledge of the biology of
S. commerson in WA. Information on
other reproductive parameters, such
as batch fecundity and spawning be-
havior, which are also required for
1 Buckworth, R. C. 1999. Age structure
of the commercial catch of Northern Ter-
ritory narrow-barred Spanish mackerel.
Final Report to the Fisheries Research
and Development Corporation (FRDC) on
project no. 1998/159. Fishery report 42,
27 p. Department of Business Indus-
try and Resource Development, Darwin,
Northern Territory, 0800, Australia.
Mackie et al.: Variability in reproductive development of Spanish mackerel (Scomberomorus commerson)
345
stock assessments, is unavailable or insufficiently
described in the literature for this species. The ob-
jective of our study was, therefore, to provide a com-
prehensive description of the reproductive biology of
S. commerson in Western Australian waters.
Material and methods
Collection and processing of samples
Scorn beromorus commerson were collected onboard
vessels operating from a number of locations along
the WA coast between 1998 and 2002 (Fig. 1). These
locations were pooled into three regions to reflect
differences in fishing methods within the mackerel
fishery (Kimberley — east of 120°E, Pilbara — north
of 23CS to the Kimberley border, and West Coast —
south of 23°S; Fig. 1). Scomberomorus commerson
are seasonally abundant in coastal waters although
low numbers are caught in the Pilbara region during
the "off-season." Samples were therefore collected
throughout the year from this region only.
Fresh S. commerson collected from commercial
and recreational fishermen were measured (total
length |TL] and fork length |FL] in mm) and, where
possible, weighed to 0.1 kg (whole weight |WW] and
clean weight (viscera and gonads removed]). Heads
were removed and measured from tip of the mouth
to firm edge of the operculum (mm), and weighed
with gills intact (±0.1 gm). Gonads were removed
from the fish within hours of capture, macroscopi-
cally staged (see below), weighed where possible (±0.01
g), and preserved in 10% formalin and seawater solution.
Frozen head and viscera obtained from commercial and
recreational fishermen were also measured and weighed
as above. The thawed gonads were macroscopically staged
by using a simplified staging system (see below) that is
used in less detailed reproductive analyses.
Preserved gonads were blotted dry with a paper towel
and weighed. A 4-mm slice from the mid-region was
processed by using standard histological techniques
and stained with Harris's haematoxylin and eosin for
microscopic examination. Full details of methods used
in the collection and analysis of S. commerson gonads
are provided in Mackie and Lewis.2
Biological analyses
Gonads were staged macroscopically and microscopi-
cally. Macroscopic staging employed five developmental
steps that were compatible with the microscopic staging
system (Mackie and Lewis2):
Pilbara
Kimberley
>y
'A Broome
Port Hedland
WESTERN
AUSTRALIA
West
Coast
•Geraldton
NORTHERN
TERRITORY
Figure 1
Sampling locations used in the study of the narrow-barred Spanish
mackerel {Scomberomorus commerson) reproductive biology.
Juvenile (J)
Females
stage 1
stages 2-3
stage 4
stage 5
Males
stage 1
stage 2
stage 3
stage 4
undifferentiated.
immature ("virgin
mature, resting;
reproductively developed;
spawning ("running, ripe
studies).
in other studies);
in other
- Mackie, M. C, and P. D. Lewis. 2001. Assessment of gonad
staging systems and other methods used in the study of the
reproductive biology of narrow-barred Spanish mackerel,
Scomberomorus commerson, in Western Australia. Fisheries
Research Report 136, 25 p. Department of Fisheries, Perth,
Western Australia 6020, Australia, http://www.fish.wa.gov.
au/res/broc/frr/frrl36/index.html. [Accessed January 15 2002.]
immature ("virgin" in other studies);
mature resting;
reproductively developed, ripe;
spawning ("running, ripe" in other
studies).
The microscopic staging system had more stages and
allowed a more detailed description of spawning:
Juvenile (J) undifferentiated.
Females
stage 1 immature ("virgin" in other studies);
stage la immature, developing;
stage 2 mature, resting;
stage 3 mature, developing;
stage 4 reproductively developed;
stage 5a prespawning;
stage 5b spawning ("running, ripe" in other
studies);
stage 5c postspawning;
stage 6 spent.
346
Fishery Bulletin 103(2)
Males
stage 1 immature ("virgin" in other studies);
stage la immature, developing;
stage 2 mature, resting;
stage 3 reproductively developed, ripe;
stage 4 spawning.
The immature, developing stage identified females that
were immature and unlikely to spawn but had ovaries
containing cortical alveoli stage oocytes (which other-
wise identified mature, developing females).
Division of the microscopic staging system for ovaries
into three spawning stages was based on the pres-
ence of migratory nucleus stage or hydrated oocytes
within the ovarian lamellae (stage 5a), the presence of
hydrated oocytes within the ovarian lumen (stage 5b),
and the presence of postovulatory follicles (POFs) in
the lamellae (stage 5c). In tropical fish species POFs
may remain up to 24 hours in the ovaries before being
resorbed (West, 1990), and there is evidence suggesting
this is the case for S. commerson in Queensland waters
(McPherson, 1993). In the present study POFs observed
in the ovaries of females were categorized as either
"new" or "old" based on their degree of degeneration
(Mackie and Lewis2).
Gonadosomatic indices (GSIs) were calculated by us-
ing ratios of gonad weight to whole body weight, head
weight, and head length. The latter two ratios were
used to assess the usefulness of head and viscera sam-
ples in future monitoring of S. commerson.
Scomberomorus commerson is a serial-spawning spe-
cies (Munro, 1942). Estimates of batch fecundity were
made for preserved prespawning (stage 5a) ovaries from
counts of hydrated oocytes within three samples taken
from the anterior, middle, and posterior region of one
lobe (each 130-200 mg). A section of each ovary was
also processed by using histological methods to confirm
suitability for estimation of fecundity. Some ovaries
were subsequently rejected for fecundity estimates be-
cause the most mature batch of oocytes had not fully
hydrated and were less easy to distinguish from earlier
stage oocytes. These ovaries tended to provide an over-
estimate of batch fecundity (Mackie et al.3).
The daily timing and frequency of spawning were
determined for females captured in the Kimberley re-
gion during September 1999 when 94% of ovaries were
retained for histological analysis (« = 344). Spawning
frequency was determined as the inverse of the spawn-
ing fraction (the number of ovaries with hydrated or
migratory nucleus stage (MNS) oocytes divided by the
total number of mature ovaries in the catch). These
data were compared with estimates made by using the
number of ovaries macroscopically identified as having
3 Mackie, M. C, D. J., Gaughan, and R. C. Buckworth.
2003. Stock assessment of narrow-barred Spanish mackerel
iScomberomorus commerson) in Western Australia. Final
report to the Fisheries Research and Development Corpora-
tion (FRDC) on project no. 1999/151, 242 p. Department
of Fisheries, Perth, Western Australia, 6020.
hydrated oocytes. Analyses of sex ratios were based on
data where the whole catch or a known random sample
of the catch was processed.
Results
The gonads of 5128 male, female, and juvenile S. com-
merson were macroscopically staged during this study.
Of these, 1624 were also processed with histological
techniques for more detailed analyses.
Biological analyses
Body lengths ranged from 58 to 1720 mm FL (62 to 1840
mm TL), and whole weights ranged from 0.0015 to 40.6
kg. Regression analyses incorporating step-wise reduc-
tion (using analysis of variance) of a fully parameterized
model indicated that differences in length and weight
relationships between regions and sex were minor com-
pared to measurement error. Thus, the simplest models
which adequately explain the pooled data were
Whole weight (kg) = 3.40e - 9 x FL (mm)3 12 (re=2842)
(SE of constants: a=2.78e-10, 6 = 0.01)
TL 'mm) = 42.74 + (1.06 x FL (mm))
(« = 1679, r2=0.996).
Overall sex ratios were biased towards females, with
the M:F ratio varying between 1:1.2 and 1:1.6 in the
three regions. However, there was considerable varia-
tion between samples, from a peak M:F ratio of 1:2.6
for samples obtained in the nonreproductive period, to
a male bias of 1.1:1 in pooled samples obtained during
the peak spawning period. This slight male bias during
the spawning period occurred in successive years; the
sex bias, however, was variable between daily samples.
Sex ratios also changed over from a male to female bias
with increasing size class, with a 1:1 ratio occurring at
about 1000-1050 mm FL.
Ovarian weight ranged from 2.00 to 1908.30 g and
testes from 0.84 to 840.10 g. Gonads of juvenile S. com-
merson were small and contained no recognizable germ
tissue. The smallest fish with differentiated gonads was
a 301-mm-FL male. The smallest female was 396 mm
FL. Two abnormally large juveniles (1170 and 1251
mm FL) were captured whose gonads had remained
unusually small and undifferentiated. Body lengths of
immature females (largest=1195 mm FL [13.8 kg WW])
overlapped substantially with those of mature females
(smallest=641 mm FL [2.3 kg WW]).
Estimates of the size at which 50% of females were
mature were calculated by using all available data as
well as data taken only during the reproductive season
(October to April). Data for each area were pooled to
provide sufficient samples (virtually all samples of im-
mature fish were obtained from the Pilbara region).
Both data sets provided similar estimates; 809 mm
FL, ±9.8 SE (898 mm TL) for all data, and 788 mm
Mackie et al.: Variability in reproductive development of Spanish mackerel (Scomberomorus commerson)
347
Females
150-,
400 600
1 1 1 r
000 1200 1400 1600
140-
Males
%^
. • ••.
120-
/•
•
100"
80 -
• /
/ •
* ■ *
I
60 -
i * 1 -•- — ■ ■ ■ ■
A •
. [\
,
40 -
20 "
■e ■ JPBe
/ i
/ i
fE^cnjrTkkf
lfTk__
I 1 1 1 1 1 1 1 1 1 —
100 200 300 400 500 600 700 800 900 1000
O
1 0 I
c
- 0 4
1200
1400
Length
Figure 2
Proportion of mature female and male S. commerson within samples.
The number offish within each length class is indicated by the verti-
cal bars and the left v-axis and the proportion of mature fish by the
black circles and the right y-axis. The length at which 50% of fish
within the samples were mature is indicated on the fitted maturity
curve (±95% CI). Lengths are fork length in mm. Note that data for
juvenile fish of undifferentiated sex are included in both graphs. The
dashed lines indicate the length at 50% mature (P=0.5).
FL (±14.5 SE) for data taken during the reproductive
period. The size at which 10% of females were mature
was 638 mm FL (±19.6 SE), with 90% mature by 981
mm FL (±7.2 SE) (Fig. 2A).
There was also considerable overlap between the
lengths of immature and mature males. The largest im-
mature male was 1140 mm FL (11.3 kg WW), whereas
the smallest mature male (stage 3) was 491 mm FL (1.0
kg WW). The size at which 10% of males were mature
was 465 mm FL (±24.9 SE), the size at which 50% of
males were mature was 628 mm FL (±13.8 SE) or 706
mm TL, and the size at which 90% were mature was
791 mm FL (±10.5 SE) (Fig. 2B).
Development of oocytes is asynchronous and all stag-
es of oocytes are present at the same time within re-
productively active ovaries. This reproductive feature,
along with the maturation of multiple batches of oocytes
(as evidenced by presence of both POFs and hydrated
or MNS oocytes in spawning ovaries), confirms that
female S. commerson are serial or partial spawners
(Hunter et al., 1985).
Relationships between batch fecundity and body
parameters were obtained from counts of hydrated
oocytes within prespawning (stage 5a) ovaries. Size
of females for which batch fecundity was determined
ranged from 857 to 1143 mm FL and from 5.3 to
348
Fishery Bulletin 103(2)
B Kimberley
Month
Resting (F 2 and 3)
Developing (F4)
Spawning (F5 a b)
Water temp
Figure 3
Annual cycle of Scombero?norus commerson reproduction within each
region, as indicated by macroscopically staged ovaries. Mid-month sea
surface temperatures are overlaid (solid line) and sample sizes are
shown above each column.
12.7 kg WW. Both relationships were explained with
power curves:
Batch fecundity
Batch fecundity
■■ 0.0011 x FL2896 (r2=0.441, n = 2l)
31087 x WW1™4 (r2=0.714, n = 19).
Annual reproductive cycle
Female S. commerson within the Pilbara region were non-
reproductive between March and June, during the down-
ward cycle of water temperatures (Figs. 3 and 4). As water
temperatures reached a minimum in July and August
(around 24°C), a small proportion of mature ovaries had
become reproductively developed (stage 4). The proportion
of developed ovaries during September (the start of the
upward cycle of water temperatures) varied noticeably
between years in the Pilbara region, from 18.5% to 79%
in 2001 and 2000, respectively. A small number of females
were also actively spawning when sampled during Sep-
tember 2000. Peak reproductive activity extended from
October to January, and spawning females were captured
during this period in 1999 and 2000 when the sea surface
temperature (SST) was rising from about 25.5° to 28.5°C.
By February, when SST peaked at approximately 30°C,
reproductive development was declining and the ovaries
of most females were spent or resting.
Mackie et al.: Variability in reproductive development of Spanish mackerel (Scomberomorus commerson)
349
A Pilbara
C West Coast
Month
r i
Resling (F 2) I I Developing (F3|
Pre-spawn (F5a) f7\\1 Post spawning (F5c)
Developed (F4)
Spenl(F6)
Water temp
Figure 4
Annual cycle of Scomberomorus commerson reproduction in Western
Australia for (A) Pilbara, (Bl Kimberley, and (Cl West Coast regions,
as indicated by histologically staged ovaries. Mid-month sea surface
temperatures are overlaid (solid line) and sample sizes are shown above
each column.
The annual reproductive cycle of ovaries in the
Kimberley region follows a similar pattern to that in
the Pilbara region (Figs. 3 and 4). However, because
30-50% of females captured in Kimberley waters dur-
ing September 1999 and 2000 were actively spawning,
it appears that S. commerson commence spawning at
least one month earlier in this region. About 60% of
females were also spawning when sampled during Oc-
tober 1999 and 2000, although only 35% were spawning
during this month in 2001. If spawning in the Kim-
berley region commenced in August and concluded in
November (same duration as in the Pilbara region), the
associated SST ranged from approximately 26.5-27°C
to 29-30°C (annual maximum approx 30-31cC; Figs.
3 and 4). Sampling of developed ovaries in March also
indicated that the reproductive period for S. commerson
in the Kimberley region may be more protracted than
in the Pilbara region.
In the West Coast region few reproductively devel-
oped ovaries and no spawning ovaries were obtained;
S. commerson are rarely captured in this region dur-
ing the peak spawning period observed in the northern
regions. The maximum sea surface temperature (SST)
in this region of around 28°C is above the lower tem-
perature range of spawning in the two northern regions.
Reproductively developed ovaries obtained from the
350
Fishery Bulletin 103(2)
A Pllbara (HL-97. WW-304. HW-232)
g
■u
£ 1
B Kimberley (HL-31 9. WW-443. HW-40)
I
I •
4 -
C West Coast (HL-304, WW-97, HW-232)
■
2 -
1 -
0 -
.4 ^.
• • • • * •
•*T-
•
Date
HL index
WW index
HW index
Figure 5
Annual cycle of gonad indices for Scomberomorus commerson in Western
Australia for (A) Pilbara, (B) Kimberley, and (Cl West Coast regions. Sample
sizes are given for each index, where HL = head length index, WW=whole
weight index, and HW=head weight index.
West Coast region were collected over a range of SSTs,
including when it was at a minimum (Figs. 3 and 4).
Gonadosomatic indices calculated from whole weight,
head weight, and head length exhibited similar patterns
and confirmed the spawning cycle determined from ex-
amination of ovaries (Fig. 5). The most complete data
set was for females from the Pilbara region. In this re-
gion indices were minimal between March and August
and increased considerably during September as ovaries
became reproductively developed. Peak indices occurred
in November 1999 and October 2000, coinciding with
peaks in the proportion of spawning (stage 5) ovaries
in the samples. The drop in gonad indices during De-
cember 1999 showed that the supplies of vitellogenic
oocytes within the ovaries were reduced by this time,
even though many females were still spawning (Fig. 4).
This drop continued until March when all the ovaries
in the samples were in the resting stage. Data for 2001
indicate that decreased GSIs during the reproductive
season were comparable to data from the previous two
Mackie et al.: Variability in reproductive development of Spanish mackerel (.Scomberomorus commerson)
351
Table 1
Ovarian development of Scomberomorus commerson sampled in the Kimberley region during the spawning season. POFs =
postovulatory follicles. Ovaries in prespawning. spawning, postspawning, and spent stages of development are indicated by 5a,
5b, 5c, and 6, respectively. Note that data for stage 5c includes only females that had spawned on the day of capture (i.e., exclud-
ing ovaries containing old POFs only). Data for "Old POFs" includes all ovaries containing old POFs as well as other evidence of
recent or imminent spawning.
Total
Year caught
Histological
analysis
Morning
Afternoon
Number
Total mature
Total 5a 5b 5c
Old Old
POFs Total 5a 5b 5c POFs
1999 344
325 306
171 59 0 0
70 135 1 1 23 51
2000 406
115 103
59 22 0 0
21 44 0 0 15 13
years. Data for the Kimberley and West Coast regions
were limited but concurred with gonad staging data
and also confirmed the low reproductive status of S.
commerson within the West Coast region.
Spawning
Evidence of spawning was found in 237 of the histologi-
cally processed ovaries. Thirty-eight percent (;? = 90) of
these were about to spawn when captured (stage 5a),
62% (n=147) had recently spawned (stage 5c), and one
was running, ripe (stage 5b). The ovaries of only two
macroscopically staged females were also running, ripe.
Most of these spawning fish (n=219) were captured in
the north Kimberley region (eighteen from the Pilbara
region). The most southern location from which a spawn-
ing female was obtained was Exmouth (one recently
spawned fish), and no females captured in the West
Coast or more southern regions showed histological (or
macroscopic) evidence of spawning.
Spawning females collected during 1999 and 2000
were either prespawning (stage 5a) and caught in the
morning, or had recently spawned (stage 5c) and were
caught in the afternoon (Table 1). The absence of hy-
drated oocytes in the afternoon and new POFs in the
morning showed that the entire cycle of oocyte matu-
ration, ovulation, and spawning is completed within
a 24-hour period. Because no new POFs were present
in ovaries sampled during the morning the transition
from new to old POFs occurs during the night, within
about 12 hours of spawning. The lack of evidence to
show that females spawned on more than two consecu-
tive days indicates that old POFs are unrecognizable
after 24 hours.
Spawning fraction was estimated by using data ob-
tained in the Kimberley region during September 1999
when 95% (n=344) of ovaries were examined by using
histological methods. Analyses were based on the num-
ber of prespawning (stage 5a) ovaries sampled during
the morning (usually between 0600-0900 h). Afternoon
samples (usually 1500-1800 h) were not used because
the number of spawning fish was likely to be under-
estimated because of the low catchability of running,
ripe (stage 5b) females. Thirty-five percent (n = 59) of
mature females in the morning samples were about to
spawn (stage 5a). Spawning frequency was therefore 2.9
days. Comparison of spawning fractions in samples of
at least ten females showed higher spawning fractions
(33-56%) for the Kimberley region compared with the
Pilbara region (4-28%).
Spawning fraction was also estimated for the morn-
ing samples as the proportion of macroscopically staged
mature ovaries that contained hydrated oocytes. Thirty-
one of the 180 mature females were identified as such,
providing an estimated spawning fraction of 17.2%, and
a spawning frequency of 5.8 days.
Thirty-six percent (n=54) of spawning females (stages
5, a-c) had spawned on two consecutive days. For exam-
ple, 39 ovaries contained oocytes in the MNS or hydrat-
ed stage of development (i.e., spawning was imminent
when fish were captured) and also contained old POFs.
Another 15 ovaries had both old and new POFs.
Discussion
Scomberomorus commerson has a gonochoristic life his-
tory in which the gonad differentiates into an ovary or
testis at around 300-400 mm FL. Males differentiate
and reach sexual maturity at a smaller body size than
females, as is the case with the congeneric species S.
maculatus and S. cavalla (Beamariage, 1973; Schmidt
et al., 1993). Consequently, more than 90% are sexually
mature by the time the minimum legal length of 900
mm TL is reached in the fishery. In contrast only 50%> of
females are mature at 898 mm TL. Although mortality
of released undersize fish may be high because of dif-
ficulties in removing fishing hooks, this size limit deters
fishermen from targeting small fish and relatively few
are captured (Mackie et al.3).
Biases in sex ratios have been observed in several
species of Scomberomorus (e.g. Trent et al., 1981; Sturm
352
Fishery Bulletin 103(2)
and Salter, 1990; Begg, 1998). In the case of S. com-
merson, females usually dominate size classes above
the MLL because they grow faster and reach a larger
maximum size (McPherson, 1992; Mackie et al.3). How-
ever, they are rarely caught when actively spawning,
despite observations by fishermen of leaping fish that
might indicate that they are still present on the fish-
ing grounds. Regional differences in fishing gear can
also affect catchability. The lighter monofilament and
reel outfits used in the Pilbara and West Coast regions
likely catch larger fish than the heavier rope and thick
monofilament hand-hauled rigs used by Kimberley fish-
ermen that do not allow the fish to be "played" (i.e. do
not allow the fish to swim) and may result in more
gear failure.
The spring-summer spawning pattern observed in
our study is similar to that of S. commerson along the
east coast of Australia (McPherson, 1981). Water tem-
perature may influence spawning in fish by affecting
gametogenesis, gonad atresia, and spawning behav-
ior (Lam, 1983). In WA waters S. commerson spawn
as water temperatures are rising and, as found in
Queensland, may compensate for latitudinal differences
in temperatures by spawning earlier in northern waters
(McPherson, 1981). No evidence of spawning activity
was found within the West Coast region although the
annual range of water temperatures overlap with those
in which spawning occurs farther north. Restricted
spawning by S. commerson on the east coast occurs at
similar latitudes to northern parts of the West Coast
region, and anecdotal evidence suggests that spawning
may be restricted in some years in this region.
During the spawning period the average female S.
commerson may spawn every three days and about one
third of fish spawn on consecutive days. Female fish
similarly spawn every 2-6 days and possibly on con-
secutive days in Queensland waters (McPherson, 1993).
Our study showed that estimates based on the fraction
of histologically staged prespawning (stage 5a) ova-
ries provided the best estimate of spawning frequency.
However, only samples taken during the morning can
be used for this analysis because of decreased catchabil-
ity of running, ripe females in the afternoon. In com-
parison, macroscopic staging of ovaries with hydrated
oocytes underestimated spawning frequency because
migratory nucleus oocytes (which comprised 54% of
histologically staged, prespawning [stage 5a] ovaries)
cannot be identified. It is also impossible to identify fish
that have spawned on more than one occasion with mac-
roscopic criteria, resulting in a further underestimate of
spawning activity (by 25% for S. commerson).
Maturation, ovulation, and spawning of oocytes by
female S. commerson was completed within a 24-h cycle
in the Kimberley region compared to 24-36 hours in
Queensland waters (McPherson, 1993). Maturation of
the oocytes is underway by sunrise and probably com-
pleted in all spawning ovaries by mid to late morning to
allow for ovulation prior to spawning in the afternoon.
Few samples were obtained at or after dusk because
fish are generally not catchable, indicating that a high
incidence of spawning at this time because only one
spawning fish was obtained during the study. Dusk
spawning is prominent among pelagic spawning species
that inhabit tropical reefs (Thresher, 1984). However,
spawning in the afternoon is less common and may be
linked to large tidal cycles and strong currents in the
north of WA, as indicated for the brown stripe snapper
(Lutjanus vitta) that also spawns in the afternoon in
the Pilbara region (Davis and West, 19931.
Batch fecundity of S. commerson has not previously
been recorded and such data are rare for other Scomb-
eromorus species. Fecundity estimates for S. commerson
from the Indian Peninsula (Devaraj, 1983) were not
comparable because those data appeared to be obtained
from counts of both vitellogenic and previtellogenic oo-
cytes. Although the current study provided fecundity
estimates only for females up to 13 kg whole weight, it
shows that S. commersorj is highly fecund (the highest
estimated batch fecundity of 1.2 million eggs was ob-
tained from an ovary that was less than half the weight
of the heaviest ovary sampled). This study highlighted
the need to histologically check that oocytes in the
spawning batch are fully hydrated because fecundity
may otherwise be over-estimated. Similarly, fecundity
will be under-estimated if ovulation has commenced.
The best time to collect gonad samples so that these
biases are minimized is during the mid to late after-
noon for this species.
Fishing activity is also regulated by the reproductive
cycle. About 3-6 months prior to the spawning sea-
son catches of S. commerson by commercial fishermen
increase as large numbers of smaller S. commerson
appear on offshore reefs sometime between March and
May, and soon after throughout the coastal waters of
WA (Mackie4). By the time reproductive development in
ovaries begins (approximately August and September
in the Kimberley and Pilbara regions, respectively)
catches have peaked or are declining. In the Pilbara
region commercial catches have dropped to a minimum
when spawning begins, as fish become less abundant
in inshore waters and inclement weather conditions
limit fishing on still productive offshore reefs. Because
S. commerson generally do not make substantial long-
shore movements (Buckworth et al.5), it is likely that
most spawning activity occurs at offshore locations in
this region (e.g., in mid to outer areas of the continen-
tal shelf), although anecdotal evidence indicates that
4 Mackie, M. C. 2001. Spanish mackerel stock status
report. In State of the fisheries report 1999/2000 (J. W.
Penn, W. J. Fletcher, and F. Head, eds.), p. 71-75. Depart-
ment of Fisheries, Perth, Western Australia, 6020. http://
www.fish.wa.gov.au/sof/1999/comm/nc/commnc26.html.
Accessed 10/2/2001.
6 Buckworth, R. C, S. J. Newman, J. R. Ovenden, R. J. G.
Lester, and G. R. McPherson. 2004. In prep. The stock
structure of northern and western Australian Spanish mack-
erel. Final report to the Fisheries Research and Development
Corporation (FRDC) on project no. 1998/159. Department
of Business Industry and Resource Development, Darwin,
Northern Territory, 0800, Australia.
Mackie et al.: Variability in reproductive development of Spanish mackerel (Scomberomorus commerson)
353
large, more solitary individuals may spawn in inshore
waters.
Catches of S. commerson peak and decline rapidly
along the Kimberley coast during the main spawning
period because of declining fish abundance and weather
conditions. As in the Pilbara region, few S. commerson
are caught at this time in southern or midsections of
the Kimberley coast. Fishermen must therefore under-
take extensive trips north to the remaining productive
grounds located between 12.5° and 15°S latitude where
the majority of S. commerson spawning activity was
encountered in the present study. Although it is pos-
sible that S. commerson in other areas of the Kimberley
region may move offshore to spawn, it is also possible
that some move northward, mixing and spawning with
otherwise temporally and spatially discrete northern
populations, in a similar manner to S. cavalla in U.S.
waters (Broughton et al., 2002).
Monitoring of the WA fishery for S. commerson is
likely to be based on the collection of head and gonad
samples because limited funding and large distances
will restrict future research trips. Onboard storage of
filleted frames for research purposes is also prohibited
by the large body size of S. commerson. In contrast, the
head of this species is relatively small and easy to store,
and as shown in the present study, provides a general
measure of reproductive activity through calculation of
head-to-gonad ratios. These ratios can also be supple-
mented by staging the gonads by using the macroscopic
staging system developed for this species (Mackie and
Lewis2). Head length can also be used to estimate body
length of S. commerson (Mackie et al.3) and the otoliths
contained in the head can be used to determine age.
Although data gathered by such means is less accu-
rate than that obtained from whole, fresh samples, it
presents the best option for gathering ongoing data in
sufficient quantities for meaningful analyses.
Acknowledgments
The authors thank the numerous commercial and rec-
reational fishermen who assisted in the collection of
samples and provided invaluable advice. The assistance
of Department of Fisheries staff and volunteers on field
trips is also appreciated. We also thank Rod Lenanton,
Rick Fletcher, and Peter Stephenson for reviewing the
manuscript, and to the Fisheries Research and Develop-
ment Corporation for funding Project 1999/151, of which
this study formed a part.
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Spanish mackerel, Scomberomorus commersoni (Lace-
pede) with preliminary notes on the spawning of that
species. Proc. Royal Soc. Qld. 54:33-48.
Schmidt, D. J., M. R. Collins, and D. M. Wyanski.
1993. Age, growth, maturity and spawning of Spanish
mackerel, Scomberomorus maculatus (Mitchell), from the
Atlantic coast of the southeastern United States. Fish.
Bull. 91:526-533.
354
Fishery Bulletin 103(2)
Sturm, M. G. deL., and P. Salter.
1990. Age, growth and reproduction of the king mack-
erel, Scomberomorus eavalla (Cuvier), in Trinidad
waters. Fish. Bull. 88:361-370.
Thresher, R. G.
1984. Reproduction in reef fishes. 391 p. T.F.H. Pub-
lications Pty Ltd., Neptune City. NJ.
Trent, L„ R. O. Williams, R. G. Taylor, C. H. Saloman. and
C. S. Manooch.
1981. Size and sex ratio of king mackerel, Scomberomorus
eavalla, in the southeastern United States. NOAA
Tech. Memo. NMFS-SEFC 62:1-59.
West, G.
1990. Methods of assessing ovarian development in fishes:
areview. Aust. J. Mar. Freshw. Res. 41:192-222.
355
Abstract— Recent research demon-
strated significantly lower growth
and survival of Bristol Bay sockeye
salmon (Oncorhynchus nerka) during
odd-numbered years of their second
or third years at sea (1975, 1977,
etc.). a trend that was opposite that
of Asian pink salmon (O. gorbuscha)
abundance. Here we evaluated sea-
sonal growth trends of Kvichak and
Egegik river sockeye salmon (Bristol
Bay stocks) during even- and odd-
numbered years at sea by measur-
ing scale circuli increments within
each growth zone of each major
salmon age group between 1955 and
2000. First year scale growth was
not significantly different between
odd- and even-numbered years, but
peak growth of age-2. smolts was sig-
nificantly higher than age-1. smolts.
Total second and third year scale
growth of salmon was significantly
lower during odd- than during even-
numbered years. However, reduced
scale growth in odd-numbered years
began after peak growth in spring
and continued through summer and
fall even though most pink salmon
had left the high seas by late July
(10-18% growth reduction in odd vs.
even years). The alternating odd and
even year growth pattern was consis-
tent before and after the 1977 ocean
regime shift. During 1977-2000,
when salmon abundance was rela-
tively great, sockeye salmon growth
was high during specific seasons com-
pared with that during 1955-1976,
that is to say. immediately after entry
to Bristol Bay, after peak growth in
the first year, during the middle of the
second growing season, and during
spring of the third season. Growth
after the spring peak in the third
year at sea was relatively low during
1977-2000. We hypothesize that high
consumption rates of prey by pink
salmon during spring through mid-
July of odd-numbered years, coupled
with declining zooplankton biomass
during summer and potentially cyclic
abundances of squid and other prey,
contributed to reduced prey availabil-
ity and therefore reduced growth of
Bristol Bay sockeye salmon during
late spring through fall of odd-num-
bered years.
Manuscript submitted 7 April 2004
to the Scientific Editor's Office.
Manuscript approved for publication
14 December 2004 by the Scientific Editor.
Fish. Bull. 103:355-370 (2005).
Seasonal marine growth of Bristol Bay
sockeye salmon (Oncorhynchus nerka)
in relation to competition with Asian pink salmon
(O. gorbuscha) and the 1977 ocean regime shift
Gregory T. Ruggerone
Natural Resources Consultants, Inc.
1900 West Nlckerson Street. Suite 207
Seattle, Washington 98(19
E-mail address GRuggeronein'nrccorp.com
Ed Farley
National Marine Fisheries Service
11305 Glacier Highway
Juneau, Alaska 99801
Jennifer Nielsen
Biological Resources Division
U.S. Geological Survey
Anchorage, Alaska 99503
Peter Hagen
Alaska Dept. of Fish and Game
P.O. Box 25526
Juneau, Alaska 99802-5526
Competition among Pacific salmon
{Oncorhynchus spp.) for food resources
in the North Pacific Ocean and Bering
Sea is a potentially important mech-
anism affecting salmon growth and
population dynamics. Reduced growth
at sea may lead to delayed matura-
tion (Rogers, 1987), lower reproductive
potential (Groot and Margolis, 1991),
or greater risk of predation (Juanes,
1994).
Density-dependent growth in the
ocean has been observed among sock-
eye (O. nerka), pink (O. gorbuscha),
and chum salmon (O. keta), which are
the most abundant species among Pa-
cific salmon (Rogers1; Eggers et al.2).
Density-dependent growth may occur
during early marine life (Peterman,
1984) or during the homeward mi-
gration period when the potential for
high growth rate (Ishida et al., 1998)
may be influenced by high concen-
trations of salmon (Rogers and Rug-
gerone, 1993).
Since the early 1970s, salmon
abundance in the North Pacific Ocean
has increased, whereas body size for
many populations of all salmon spe-
cies has declined (Bigler et al., 1996).
However, greater abundance of adult
sockeye salmon returning to Bristol
Bay, Alaska, was associated with in-
creased growth during the first and
second years at sea, followed by rela-
tively low growth during the third
year at sea, and greater adult size at
a given abundance (Ruggerone et al..
1 Rogers, D. E. 2001. Estimates of
annual salmon runs from the North
Pacific, 1951-2001. Report SAFS-UW-
0115. 11 p. School of Aquatic Sciences,
Univ. Washington, Seattle, WA.
2 Eggers, D. M, J. Irvine, M. Fukawaki,
and V. Karpenko. 2003. Catch trends
and status of North Pacific salmon. Doc.
no. 723, 34 p. North Pacific Anadromous
Fisheries Commission (NPAFC), 889
Pender Street, Vancouver, Canada.
356
Fishery Bulletin 103(2)
2002). Increased growth of Bristol Bay sockeye salmon
during the first two years at sea was associated with
greater adult returns, but high abundance apparently
led to increased competition and reduced growth during
the third year.
The potential for competition for food between Asian
pink salmon and Bristol Bay sockeye salmon stocks is
great in the North Pacific Ocean and Bering Sea. Tro-
phic level, diet, and feeding behavior of pink salmon
overlap significantly with sockeye salmon (Welch and
Parsons, 1993; Davis et al., 2000; Kaeriyama et al.,
2004). Asian pink salmon are highly abundant, averag-
ing approximately 162 million adults in odd-numbered
years and 104 million adults in even-numbered years,
1955 to 2000 (Rogers1). Bristol Bay sockeye salmon and
Asian pink salmon overlap in the central North Pacific
Ocean and the Bering Sea. Greatest overlap is with
pink salmon from the eastern Kamchatka Peninsula
and Sakhalin Island (French et al., 1976; Takagi et al.,
1981; Myers et al.3), which are especially abundant, as
shown by average harvests of 79,000 metric tons (t) in
odd-numbered years and 33,000 t in even-numbered
years, 1955-99 (Sinyakov, 1998; Anonymous4).
Evidence for competition between Asian pink and
Bristol Bay sockeye salmon was provided in a recent in-
vestigation by Ruggerone et al. (2003). During 1955-97,
annual sockeye salmon scale growth during the second
and third years at sea was significantly reduced during
odd- compared to even-numbered years. Adult sockeye
salmon length was relatively low when sockeye salmon
overlapped with abundant odd-year pink salmon during
the year prior to homeward migration. Furthermore,
smolt-to-adult survival of Bristol Bay sockeye salmon
was significantly lower when they encountered odd-year
pink salmon during the second year at sea. However,
Bristol Bay sockeye salmon encountered relatively few
pink salmon during their first year at sea and no com-
petition effect was observed during this early marine
period.
In our study we examined the seasonal growth of
Bristol Bay sockeye salmon scales in an effort to deter-
mine the approximate timing and duration of reduced
growth during odd-numbered years at sea that was
observed by Ruggerone et al. (2003). Scale circuli in-
crements and annuli are correlated with salmon body
size (Clutter and Whitesel, 1956; Fukuwaka and Kaeri-
yama, 1997; Fukuwaka, 1998). We compared seasonal
scale growth before and after 1977 to examine seasonal
growth trends associated with the twofold increase in
Bristol Bay sockeye salmon abundance and the 1977
:) Myers, K. W., K. Y. Aydin, R. V. Walker, S. Fowler, and M. L.
Dahlberg. 1996. Known ocean ranges of stocks of Pacific
salmon and steelhead as shown by tagging experiments,
1956-1995. Report FRI-UW-9614, 159 p. School of Aquatic
and Fishery Sciences, Univ. Washington, Seattle, WA
4 Anonymous. 2002. Biostatistical information on salmon
catches, escapement, outmigrants number, and enhancement
production in Russia in 2001. Doc. no. 646, 14 p. NPAFC,
889 Pender Street, Vancouver, Canada.
ocean regime shift (Rogers, 1984; Beamish and Bouil-
lon, 1993; Rogers1). We also examined the hypothesis
that seasonal growth during the second growing sea-
son was dependent on previous marine growth (Aydin,
2000). These hypotheses were tested by using scales
from Kvichak River and Egegik River sockeye salmon,
which averaged approximately 16 million fish per year
or approximately 57% of the annual sockeye salmon run
to Bristol Bay, 1955-2000.
Methods
For our study, we used scales from four age groups of
Kvichak River sockeye salmon and three age groups of
Egegik River sockeye salmon collected from the late
1950s through 2000 (Fig. 1). Adult salmon scales were
obtained from the Alaska Department of Fish and Game
(ADFG) archive in Anchorage, Alaska, and from the
School of Aquatic and Fishery Sciences, University of
Washington. Scales have been collected annually for
measuring and quantifying age composition for manage-
ment of the fisheries in Alaska. We selected scales from
salmon sampled in the Kvichak and Egegik rivers rather
than in the ocean fisheries to reduce the possibility of
mixed stocks in the scale collection. Scale collections
from the Kvichak River began in 1955, whereas collec-
tions from Egegik River began in 1960. Major freshwater
and ocean age groups from Kvichak (ages 1.2, 1.3, 2.2,
2.3) and Egegik (ages 1.3, 2.2, 2.3) sockeye salmon were
measured. Age was designated by European notation,
i.e. the number of winters spent in freshwater before
going to sea (1 winter=age-l. or two winters = age-2.)
followed by the number of winters spent at sea (two
winters = age-.2 or 3 winters = age-.3.l. Nearly all Bristol
Bay sockeye salmon mature after spending two or three
winters at sea.
Scales were selected for measurement in this study
only when 1) we agreed with the age determination
previously made by ADFG, 2) the scale shape indi-
cated that the scale was removed from the "preferred
area" (Koo. 1962), and 3) circuli and annuli were clearly
defined and not affected by scale regeneration or sig-
nificant resorption along the measurement axis. We
measured up to 50 scales per year, representing equal
numbers of male and female salmon from each age
group within each stock.
Scale measurements followed procedures described
by Davis et al. (1990) and Hagen et al.5 After select-
ing a scale for measurement, the scale was scanned
from a microfiche reader and its image was stored as a
high resolution digital file. High resolution (3352x4425
pixels) allowed the entire scale to be viewed and pro-
vided enough pixels to be seen between narrow circuli
5 Hagen, P. T., D. S. Oxman, and B. A. Agler. 2001. Devel-
oping and deploying a high resolution imaging approach for
scale analysis. Doc. 567, 11 p. North Pacific Anadromous
Fish Commision, 889 Pender Street, Vancouver, Canada.
Ruggerone et al.: Seasonal growth of Oncorhynchus nerka in relation to competition with O. gorbuscha
357
Figure 1
Map of Bristol Bay, Alaska, and the location of the Kvichak and Egegik river systems.
to ensure accurate measurements of circuli spacing.
The digital image was loaded in Optimas 6.5 (Media
Cybernetics, Inc., Silver Spring, MD) image processing
software to collect measurement data with a customized
program. The scale image was displayed on a digital
LCD flat panel tablet. The scale measurement axis was
determined by a perpendicular line drawn from a line
intersecting each end of the first saltwater annulus.
Distance (mm) between circuli was measured within
each growth zone (i.e., from the scale focus to the outer
edge of the first freshwater (FW1) annulus, between the
first and second freshwater (FW2) annuli, within the
spring plus (FWPL) growth zone, within each annual
saltwater (SW1. SW2, SW3) growth zone, and from the
last ocean annulus to the edge of the scale (i.e., the
saltwater plus [SWPL] growth zone).
Data analysis
Mean scale circuli increments (distance between adjacent
circuli pairs) of each age group and stock were calculated
for each year when 10 or more scales were available.
Typically, 40 to 50 scales of each age group and stock
were measured in a given year. To facilitate evaluation
of trends between odd- and even-numbered years at sea,
scale circuli measurements were described in terms of
the odd- or even-numbered year when the salmon entered
the ocean. Thus, a salmon smolt entering the Bering Sea
during an even-numbered year interacted with abundant
odd-year Asian pink salmon during its second growing
season (SW2) and less abundant even-year pink salmon
during its third year, if it remained at sea. The number
of circuli pairs considered in our analysis differed by
growth zone, ranging from 22 circuli (SW1) to 20 cir-
culi (SW2) to 15 circuli (SW3) in order to represent the
majority of salmon. Analyses of seasonal scale growth
trends were based on the mean of annual mean scale
circuli increments, percentage change in scale circuli
increments during odd- versus even-numbered years, and
percentage change in odd- and even-year growth during
periods before and after the 1977 ocean regime shift. A
two-sample t-test was used to test for differences between
odd- and even-numbered year scale growth at each cir-
culi pair. Correlation was used to determine whether an
individual's growth during the second growing season
was related to previous growth at sea.
Results
First year (SW1) growth of ocean age-3 sockeye salmon
Kvichak and Egegik river sockeye salmon scale growth
(distance between adjacent circuli) increased rapidly
358
Fishery Bulletin 103(2)
Odd year smolts
Even year smolts
Circuli pair
Figure 2
Average seasonal scale growth for Kvichak and Egegik ocean age-3 sockeye
salmon (Oncorhynchus nerka) that entered the ocean as smolts during odd
( ) and even ( ) numbered years, 1952-2000. Growth of salmon
spending one (age 1.3) and two years (age 2.3) in freshwater are shown
separately. Circuli pair ordering restarts at the beginning of each new
growing season (SW1, SW2, SW3, SWPL). 95f7r confidence intervals (CIs)
are shown at each measurement.
after the fish entered Bristol Bay during May and early
June, reaching peak growth near the fifth circuli (Fig. 2).
Thereafter, growth declined steadily to a minimum at
the first ocean annulus (circuli 18-22).
Peak scale growth of age-2. smolts was significantly
greater compared with that of age-1. smolts for both
Kvichak (df=79, i=5.757, P<0.001) and Egegik salm-
on (df=73, £=4.667, P<0.001). During the first eight
circuli, age-2. smolts averaged 6.5% greater growth
than age-1. smolts. Thereafter (circuli 11-20), growth
of age-2. smolts declined more rapidly and averaged
2.3% (Kvichak) to 6.1% (Egegik) less than growth of
age-1. smolts.
Within the SW1 growth period, no statistically sig-
nificant difference in circuli growth was detected be-
tween smolts entering the ocean during odd- and even-
numbered years (P>0.05). However, there was a trend
for greater growth among even-year smolts in some
Ruggerone et al.: Seasonal growth of Oncorhynchus nerka in relation to competition with O. gorbuscha
359
Pre-1977
Post 1976
Circuli pair
Figure 3
Percent change in scale growth of ocean age-3 sockeye salmon (O. nerka)
entering the ocean during even-numbered years compared to odd-numbered
years. Growth patterns represent ocean developmental periods prior to 1977
( ) and after 1976 t ). Even-year smolts encountered odd-year
pink salmon (O. gorbuscha) during their second year at sea (SW2), but they
encountered even-year pink salmon during their third year at sea (SW3).
Age 1.3 = 1 year in freshwater and 3 years in saltwater; age 2.3= 2 years
in freshwater and 3 years in saltwater.
portions of SW1. including the annulus (circuli 18-22)
and immediately after peak growth (circuli 7 to 13)
(Figs. 2 and 3).
SW1 growth of both even- and odd-year smolts tended
to be greater after the 1977 climate shift than prior
to this period, except for the last few circuli (Fig. 4).
The greatest difference in growth between these two
periods occurred immediately after entry into Bristol
Bay (circuli 1-3) and during the last part of the SW1
growth period (circuli 13-19). This bimodal pattern of
growth between the two periods was somewhat con-
sistent among both stocks and freshwater age groups.
However, Kvichak age 2.3 salmon experienced especially
high early marine growth that was 17% greater, on
average, after 1976. Following peak scale growth in
spring, Egegik age 1.3 sockeye salmon experienced a
360
Fishery Bulletin 103(2)
Odd year smolts
Even year smolts
Circuli pair
Figure 4
Percent change in scale growth of ocean age-3 sockeye salmon (O. nerka)
entering the ocean during 1977-97 from those entering the ocean during
1952-76. Growth patterns represent smolts entering the ocean during
odd- ( ) and even-numbered years ( ). Even-year smolts encoun-
ter odd-year pink salmon (O. gorbuseha) during their second year at sea
(SW2), but they encountered even-year pink salmon during the their third
year at sea (SW3).
15% increase in growth after 1976. In contrast, growth
near the winter annulus (circuli 20-22) was up to 5%
lower after the 1977 climate shift.
Second year (SW2) growth of ocean
age-3 sockeye salmon
At the beginning of the second growing season (SW2),
when Bristol Bay sockeye salmon are farthest south
in the North Pacific Ocean (French et al., 1976), scale
growth of both stocks and age groups increased rapidly,
but the rate of increase was 59% less than that of SW1
and 377, less than SW3 growth (Fig. 2). Peak growth
occurred near circuli 5 or 6 and it averaged 15% lower
than that of SW1 growth.
During their second year at sea, even-year sockeye
smolts inhabited the North Pacific and Bering Sea when
Asian pink salmon were abundant in offshore waters
Ruggerone et al.: Seasonal growth of Oncorhynchus nerka in relation to competition with O. gorbuscha
361
Table 1
Summary
of two sample /-tests
for
evaluating the circu
i number at which sockeye scale
growth began
to differ between odd-
versus even-numbered years of the
second
and third seasons at sea. Between-year differences in circuli growth were greater after
the circuit
num
ser shown in this
table.
No
consistent patt
ern of difference;;
between odd- and even-numbe
'ed years was observed
during the first
season at sea. Age '
1.2
' is a fish that has
spent one year in
fresh water and two years in ss
It water. SW2=2 years
in saltwater.
Age
Ocean period
Stock
Circuli no.
df
/-value
P (two tailed I
1.2
SW2
Kvichak
Cll
43
2.412
0.020
2.2
SW2
Kvichak
Cll
44
3.283
0.002
2.2
SW2
Egegik
Cll
39
3.434
0.001
1.3
SW2
Kvichak
C12
42
3.068
0.004
SW3
Kvichak
C8
42
3.126
0.003
1.3
SW2
Egegik
Cll
38
2.140
0.038
SW3
Egegik
C7
38
2.527
0.016
2.3
SW2
Kvichak
Cll
43
2.711
0.010
SW3
Kvichak
C8
43
2.384
0.022
2.3
SW2
Egegik
Cll
39
3.061
0.004
SW3
Egegik
C7
39
2.728
0.010
(i.e., during odd-numbered years). Initial scale growth
prior to the SW2 peak in spring was the same between
odd- and even-numbered years, although there was a ten-
dency for greater growth following the SW1 annulus of
even-year smolts (Fig. 3). Immediately after peak growth
near circuli 11, scale growth of even-year smolts became
significantly less than that of odd-year smolts (Table 1).
The growth differential continued through the end of the
SW2 growing season and it reached a maximum reduc-
tion of -10% to -18% near circuli 14 to 18 (Fig. 3). This
pattern was consistent before and after the 1977 climate
shift and among each stock and age group. The reduced
growth of even-year smolts during SW2 corresponded
with high abundance of pink salmon in the central North
Pacific Ocean during odd-numbered years.
Scale growth during SW2 of both odd- and even-year
smolts tended to be greater after the 1977 climate shift
(Fig. 4), a period when abundance of Bristol Bay sock-
eye salmon and Asian pink salmon was great. This pat-
tern was consistent among both age groups of Kvichak
and Egegik River sockeye salmon. Greatest growth dif-
ferential between the two periods (up to 10%) occurred
just after peak growth (circuli 5 to 15), a pattern that
differed markedly from both SW1 and SW3. In contrast
to the relatively large increase in growth shown in
the central portion of SW2 after 1977, growth at the
beginning of SW2 was similar during both periods and
growth at the end of SW2 was relatively low after the
climate shift.
Third year (SW3) growth of ocean age-3 sockeye salmon
Scale growth at the beginning of the third year at sea
increased rapidly, peaked near circuli 5-6, then declined
steadily through the year (Fig. 2). Peak growth during
SW3 was intermediate to the relatively high peak
growth during SW1 and relatively low peak growth
during SW2.
During their third year at sea, even-year sockeye
smolts inhabited the North Pacific and Bering Sea when
relatively few Asian pink salmon were in offshore wa-
ters (i.e., even-numbered years). Prior to peak growth,
SW3 growth of even-year smolts was similar or below
that of odd-year smolts (Fig. 3), a pattern that contin-
ued from the previous season. Immediately following the
peak, growth of even-year smolts significantly increased
in relation to odd-year smolts (Table 1), and growth re-
mained relatively high throughout the remaining season
(Fig. 2). Growth of even-year smolts was approximately
5% to 15% greater than that of odd-year smolts from
circuli 8 to the annulus (Fig. 3). Differences in growth
during even- versus odd-numbered years tended to be
greater after 1976 when both pink and sockeye salmon
were relatively abundant.
Peak SW3 scale growth was up to 10% greater after
the mid-1970 regime shift during both odd- and even-
numbered years (Fig. 4). However, after the peak grow-
ing season, scale growth was typically lower after 1976.
The relatively low growth after 1976 was especially
pronounced among odd-year smolts that inhabited the
ocean during odd-numbered years when Asian pink
salmon were abundant in offshore waters. Scale growth
of odd-year smolts during SW3 was as much as 10%
lower than that prior to 1977.
Scale growth during both SW3 and SW2 were signifi-
cantly reduced during odd-numbered years at sea (Table
1). However, SW3 scale growth during odd- versus even-
years diverged immediately after the peak, whereas
362
Fishery Bulletin 103(2)
Odd year smolts
Even year smolts
~i i i i i i i i i i r
7 10131619 22 3 6 9 121518 1 4
Circuli pair
Figure 5
Seasonal scale growth of Kvichak and Egegik ocean age-
2 sockeye salmon (O. nerka) that entered the ocean as
smolts during odd- ( ) and even- ( ) numbered
years, 1952-2000. Growth of salmon spending one (age
1.2) and two years (age 2.2) in freshwater are shown
separately. Circuli pair ordering restarts at the begin-
ning of each new growing season (SW1, SW2, SWPLl.
95% CIs are shown at each measurement. Age 1.2 = 1
year in freshwater and 2 years in saltwater.
Pre-1977
Post
1976
o-
SW1 (even yt)
SW2 (odd yr)
SWPL
5 "
0 -
-< ,-,/^V\<y0'
.--;v"\
,-,
si"-^ ,_' V
^v\ ,
/^
5-
\\
(
o-
Kvichak 2.2
o
1
J
I I I I I
I
1 1
J/\\ r
Kvichak 1.2
i i i i i i i
i i i i i i
r t
o-
5 -
o -
5-
0-
5-
Egegik 2.2
i i i i i i i
i i i i i 'i '
1 4 7 10 13 16 19 22 3 6 9 12 15 18 1 4
Circuli pair
Figure 6
Percent change in scale growth between ocean age-2
sockeye salmon (O. nerka) entering the ocean during
even years and those entering during odd-numbered
years. Growth patterns represent ocean rearing periods
prior to 1977 ( ) and after 1976 ( ). Even-year
smolts encountered odd-year pink salmon (O. gorbuscha I
during the second year at sea (SW2).
growth during SW2 diverged two or three circuli af-
ter the peak (Fig. 2). Late season growth of even-year
smolts during SW3 was greater than late season growth
during SW1 and SW2, whereas growth of odd-year
smolts during SW3 was intermediate to SW1 and SW2
growth. These relatively large, older fish experienced a
longer growing season, especially during even-numbered
years, when few pink salmon were present.
Growth during homeward migration (SWPL) of ocean
age-3 sockeye salmon
The peak return of sockeye salmon to Bristol Bay occurs
near 3 July. Scale growth during the homeward migra-
tion peaked at circuli 3 and 4, then declined (Fig. 2).
Peak growth was less than that of SW1, but greater
than SW2 and SW3 growth. No growth difference was
detected between odd- and even-year migrants during
the period of homeward migration. Spring growth after
1976 was 5-10% greater than that during the earlier
time period (Fig. 4).
First year ocean (SW1) growth of ocean
age-2 sockeye salmon
Scale growth patterns of ocean age-2 Kvichak and
Egegik sockeye salmon were remarkably similar to that
of ocean age-3 sockeye, especially among those having
the same freshwater age (Fig. 5 1. Sockeye salmon that
had spent two winters in freshwater had significantly
greater SW1 peak growth compared with those spending
one winter in freshwater (Kvichak stock: df=85, ^=6.772,
P<0.001). Growth of age-2. smolts during the first eight
circuli averaged 9% higher compared to age-1. smolts.
However, as with ocean age-3 salmon, postpeak growth
of age-2 smolts averaged 3.5% less than that of age-1.
Ruggerone et al.: Seasonal growth of Oncorhynchus nerka in relation to competition with O. gorbuscha
363
smolts. Growth of even- and odd-year smolts during
the first growing season was not significantly different
but even-year smolts tended to have somewhat greater
growth immediately following peak growth (circuli 7-13)
and at the end of the growing season (circuli 19-22)
(Fig. 6).
SW1 growth was markedly greater after 1976 when
salmon abundance was relatively high compared with
the growth during 1952-1976 (Fig. 7). Greater growth
during the recent time period was most pronounced
immediately after entry to Bristol Bay and after peak
growth (circuli 13-18), but it was relatively low at the
end of the growing season (circuli 20-22). These pat-
terns were generally consistent between odd- and even-
year smolt years.
r (SW2) growth of ocean age-2 sockeye
Second yea
salmon
SW2 scale growth patterns of ocean age-2 sockeye
salmon were similar to SW2 patterns of ocean age-3
sockeye salmon. Scale growth of odd- and even-year
smolts was similar until scale growth of even-year smolts
significantly declined approximately three circuli after
peak growth (Fig. 5, Table 1). Lower growth of even-year
smolts continued to the end of the growing season. Scale
growth of even-year migrants during their second year
at sea was approximately 107c to 15% less than that of
odd-year migrants (Fig. 6). Low growth of even-year
migrants was associated with odd-numbered years at
sea — a trend that was observed among SW2 and SW3
growth periods of ocean age-3 sockeye salmon.
Scale growth during SW2 was greater after 1976 when
salmon abundance was relatively high compared with
the growth before 1977, especially during the middle of
the growing season (Fig. 7). However, after 1976, growth
near the end of the growing season (circuli 17-20) tend-
ed to be below average. These patterns were consistent
among the two stocks and three age groups.
Late season growth of ocean age-2 sockeye salmon
during the second year at sea differed from that of
ocean age-3 sockeye salmon (Figs. 2 and 5). Growth
after circuli 8 of SW2 was significantly greater among
ocean age-2 compared with ocean age-3 sockeye salm-
on (df=283, £=12.81, P<0.001), averaging 11% greater
growth.
Growth during homeward migration (SWPL) of ocean
age-2 sockeye salmon
Scale growth of ocean age-2 sockeye salmon during the
homeward migration peaked at circuli 4, then declined.
Prior to peak growth, even-year migrants experienced
approximately 57c less growth than odd-year migrants,
a pattern that was similar prior to and after the climate
shift (Fig. 6). Low initial growth during SWPL appeared
to be a continuation of relatively low growth during
SW2. No difference in peak growth between odd- and
even-years was apparent. Growth tended to be higher
after the mid-1970s (Fig. 7).
Odd year smolts
Even year smolls
SW1
SW2
SWPL
-
"At-.-y^/vN,
rCX
^
5-
-
\S
J
0-
Kvichak 2.2
i i i i i i i
1 1 1 1 1 1
1 1
10 13 16 19 22
Circuli pair
Figure 7
Percent change in ocean age-2 sockeye salmon (O. nerka)
scale growth entering ocean during 1977 to 1998 com-
pared with 1952-1976. Growth patterns represent smolts
entering ocean during odd- I ) and even-numbered
years ( ). Even-year smolts encountered odd-year
pink salmon (O. gorbuscha) during the second year at
sea (SW2).
Relationship between early marine and late SW2
scale growth
We examined correlations between early marine scale
(SW1 growth through the first eight circuli of SW2) and
late SW2 growth (circuli 11 to annulus), corresponding
with periods before and after the divergent scale growth
pattern observed between odd- and even-numbered years.
Negative correlations between early marine and late SW2
scale growth were observed among each stock and age
group, before and after the 1977 regime shift, and among
fish inhabiting the ocean during odd- or even-numbered
years (Table 2). Only one of the 28 correlations (Egegik
age-2. 2, early period, odd SW2 year) was statistically
insignificant. Thus, individual sockeye salmon that expe-
rienced somewhat low growth during early marine life
tended to have somewhat high growth during later por-
tions of their second year at sea, regardless of whether
they competed with pink salmon. The strength of the
364
Fishery Bulletin 103(2)
Table 2
Correlation between early marine scale grow
th (SW1 through SW2,
circuli 1-8) and SW2 scale growth
after growth difference
in odd and even numbered years (SW2. circu
i 11 to annulus). Measurements based
on individual fish (;
). Correlation coefficient
and statistical significance are
shown for each age group and stock during early
pre-1977) and recent (post-1976)
periods for
odd- and even-numbered years
at sea. SW2 =
I years in saltwater.
Age Stock
Period
SW2 year
r
n
F-value
P-value
1.2 Kvichak
Early
Even
-0.11
408
5.18
<0.025
Early
Odd
-0.20
429
18.20
<0.001
Recent
Even
-0.22
550
27.84
<0.001
Recent
Odd
-0.24
596
36.07
<0.001
2.2 Kvichak
Early
Even
-0.14
592
12.17
<0.001
Early
Odd
-0.14
523
10.16
<0.002
Recent
Even
-0.31
549
56.23
<0.001
Recent
Odd
-0.17
568
16.78
<0.001
2.2 Egegik
Early
Even
-0.14
428
8.61
<0.004
Early
Odd
-0.06
441
1.33
0.249
Recent
Even
-0.14
551
10.21
<0.002
Recent
Odd
-0.09
599
4.81
<0.030
1.3 Kvichak
Early
Even
-0.15
270
6.53
<0.020
Early
Odd
-0.15
333
7.50
<0.010
Recent
Even
-0.35
517
71.18
<0.001
Recent
Odd
-0.20
504
21.89
<0.001
1.3 Egigik
Early
Even
-0.15
191
4.32
<0.040
Early
Odd
-0.22
210
10.51
<0.002
Recent
Even
-0.23
453
24.67
<0.001
Recent
Odd
-0.27
479
38.60
<0.001
2.3 Kvichak
Early
Even
-0.15
347
7.78
<0.010
Early
Odd
-0.16
376
10.12
<0.002
Recent
Even
-0.24
438
25.86
<0.001
Recent
Odd
-0.18
407
13.38
<0.001
2.3 Egegik
Early
Even
-0.16
460
12.35
<0.001
Early
Odd
-0.23
416
23.94
<0.001
Recent
Even
-0.18
546
17.94
<0.001
Recent
Odd
-0.17
543
16.11
<0.001
correlations was low, but the consistent pattern among
stocks, age groups, and time periods indicates that the
negative correlations were not spurious.
Discussion
Previous research documented reduced annual scale
growth of Nushagak Bay (Bristol Bay) sockeye salmon
during odd-numbered years of their second and third
years at sea (Ruggerone et al., 2003). The primary find-
ing of our investigation was that salmon scale growth
reduction during odd-numbered years did not occur
throughout the second and third years at sea. During the
second year at sea, scale growth reduction began three
to five circuli after peak scale growth. During the third
year at sea, scale growth reduction began immediately
after peak growth. This finding was consistent among all
age groups of both Kvichak and Egegik sockeye salmon
prior to and after the mid-1970s regime shift that led to
greater sockeye salmon abundance. Comparison of sea-
sonal scale growth patterns before and after the regime
shift indicated that the recent period of high sockeye
salmon abundance was associated with relatively high
growth 1) immediately after entry to Bristol Bay, 2) after
peak scale growth during the first growing season, 3)
during the middle of the second growing season, and 4)
during the third spring but followed by below average
growth during the remaining summer and fall.
Timing of peak scale growth and differences in
scale growth between odd- and even-numbered years
The approximate time period of peak scale growth can
be estimated from previous studies of salmon circuli for-
mation at sea and timing of peak prey production. Bilton
Ruggerone et al.: Seasonal growth of Oncorhynchus nerka in relation to competition with O. gorbuscha
365
and Ludwig (1966) reported that sockeye salmon in the
Gulf of Alaska tended to form annuli during December
and January, whereas salmon sampled farther west in
the relatively cold waters below the Aleutian Islands
appeared to form annuli during March (Birman, 1960).
For example, sockeye salmon collected from the east-
ern range of Bristol Bay sockeye salmon in the Gulf of
Alaska (e.g., 152-160°W) averaged 1.2 circuli beyond
the winter annulus during January and 3.6 circuli in
April. We observed peak circuli growth of Kvichak and
Egegik sockeye salmon to occur near circuli 5 to 6 (all
ages), indicating that peak scale growth occurred from
approximately early May to mid-June. This finding is
consistent with scale growth in the year of homeward
migration when Bristol Bay sockeye salmon averaged
approximately 1 to 2 circuli after peak circuli growth
before reaching Bristol Bay. on average, during the first
week in July. The estimated date of peak scale growth
is also consistent with observations of peak biomass
of zooplankton in the Gulf of Alaska and Bering Sea,
which typically occurs during May or June (Brodeur et
al., 1996; Coyle et al., 1996; Mackas et al., 1998; Mackas
and Tsuda, 1999). However, Ishida et al. (1998) reported
that salmon growth was greatest between June and July,
a period apparently later than peak scale growth and
peak zooplankton biomass. Furthermore, scale growth
may lag behind body growth (Bilton, 1975). Based on
these observations, the observed divergence in scale
growth between odd- and even-numbered years likely
began after zooplankton biomass declined and during a
period of high potential body growth of salmon.
Differences in SW2 scale growth between odd- and
even-numbered years at sea began three to five circuli
after peak growth, rather than immediately after the
peak as shown among fish during their third year at
sea (SW3). Because younger salmon begin circuli for-
mation earlier in winter than do older salmon (Bilton
and Ludwig, 1966; Martinson and Helle, 2000), it is
likely that the differences in time of SW2 scale growth
was only slightly later than that scale growth during
SW3. The reason for the somewhat later differences
between odd and even years of younger sockeye salmon
might relate to the degree of diet overlap with pink
salmon. In the central North Pacific Ocean and Ber-
ing Sea, pink salmon in their second growing season
have greater diet overlap with larger sockeye salmon
(Davis, 2003), such as sockeye salmon in their third
season at sea. Thus, competition for prey may be great-
est between pink salmon and the larger, older sockeye
salmon, leading to earlier growth differences between
the SW3 than the SW2 growth period. Alternatively,
this pattern may reflect differences in the distribution
of age-2 and age-3 sockeye salmon: age-3 salmon maybe
distributed farther west where overlap with Asian pink
salmon is greater.
that affect the degree of competition. Little or no overlap
occurs between these stocks during the first growing
season (SW1) and there are typically small numbers
of pink salmon originating from Bristol Bay (Rogers1).
Little sampling has occurred during winter (Myers6),
but data collected during fall and spring indicate that
some overlap between Asian pink salmon and Bristol
Bay sockeye begins in the central North Pacific Ocean
during winter (French et al., 1976; Takagi et al., 1981;
Myers et al.3). The degree of overlap likely increases
into spring when both species reach their southernmost
distribution, which is somewhat farther south for pink
salmon. As the temperature begins to increase, both
species migrate northwest — pink salmon leading the
migration. Both species enter the Bering Sea but many
Bristol Bay salmon and some Asian pink salmon remain
in the North Pacific Ocean. In June, some Asian pink
salmon leave the high seas for coastal areas, whereas
others remain offshore through July (Myers et al.3; Azu-
maya and Ishida, 2000). During odd-numbered years,
pink salmon are more broadly distributed on the high
seas and catch per effort in the Bering Sea remains high
through at least mid-July (up to 400 fish per 30 tans
(1.5 km) of gill net) compared with that during even-
numbered years (Azumaya and Ishida, 2000). Catch
per effort of pink salmon during July is somewhat lower
in the central North Pacific Ocean. Most pink salmon
in the Bering Sea likely originate from the eastern
Kamchatka Peninsula, which supports a major Asian
population that is dominated by odd-year pink salmon.
Thus, the period of overlap between Asian pink salmon
and Bristol Bay sockeye salmon is from approximately
winter through July and greatest overlap likely occurs
during late spring through at least mid-July.
The relatively slow growth of sockeye salmon scales
during odd-numbered years at sea began in the period
of overlap with pink salmon and continued for months
after pink salmon left the high seas. This finding in-
dicates that prey availability was reduced for months
after most pink salmon left the high seas. Sugimoto and
Tadokoro (1997) examined zooplankton biomass dur-
ing June and July, 1950-81 and concluded that Asian
pink salmon caused the observed alternating pattern of
zooplankton biomass in the central North Pacific Ocean
and the eastern Bering Sea. Shiomoto et al. (1997) ex-
amined macrozooplankton biomass in the central North
Pacific Ocean during 1985-94 and also concluded that
Asian pink salmon, especially those from the eastern
Kamchatka Peninsula, reduced the biomass of macro-
zooplankton. Shiomoto et al. (1997) noted that lower
zooplankton biomass was still apparent in the central
North Pacific Ocean after many pink salmon had mi-
grated into the Bering Sea. These findings support the
hypothesis that predation by pink salmon altered zoo-
plankton biomass from spring through at least July.
Interactions with pink salmon and prey
Spatial and temporal overlap between Asian pink salmon
and Bristol Bay sockeye salmon are important factors
6 Myers, K. 1996. Survey on overwintering salmonids in
the North Pacific Ocean: Kaiyo Maru, 5 January-29 Janu-
ary 1996. Report FRI-U W-9607, 54 p. Univ. Washington,
Seattle, WA.
366
Fishery Bulletin 103(2)
Timing of peak zooplankton biomass occurs later in
the year in northern regions, but zooplankton biomass
typically declines during summer and fall (Batten et al..
2003). Declining zooplankton biomass in epipelagic wa-
ters is related, in part, to the ontogenetic migration to
deep waters of some major zooplankton species, such as
Neocalanus spp. (Mackas and Tsuda, 1999). Declining
zooplankton biomass during summer likely enhanced
the effect of competition exerted by pink salmon during
odd-numbered years. July through at least September
is a period of high potential salmon growth (Ishida et
al., 1998); therefore sockeye salmon may be especially
influenced by prey reduction during this period. During
early spring, when scale growth of sockeye salmon was
great and did not differ between odd- and even-num-
bered years, prey availability was apparently sufficient
to minimize the effects of competition. Walker et al.
(1998) reported that density-dependent growth of Asian
pink salmon occurred after late June — a finding that is
consistent with our study.
The transition from foraging on zooplankton to for-
aging on squid for both pink and sockeye salmon may
also contribute to the alternating-year pattern of sock-
eye salmon growth. Aydin (2000) suggested that pink
and sockeye salmon may begin to feed intensively on
micronekton squid after reaching sufficient size dur-
ing their second growing season. Pink salmon report-
edly begin feeding on squid during spring, whereas
sockeye salmon may not begin to feed on squid until
summer because sockeye salmon are smaller. During
odd-numbered years, pink salmon may have reduced
the availability of squid to sockeye salmon and influ-
enced the observed differences in scale growth after
spring. In support of this hypothesis, sampling of sock-
eye and pink salmon during a recent 10-year period in
the Bering Sea (June and July) indicated a 58% reduc-
tion among sockeye salmon and 32% reduction among
pink salmon in the weight of squid consumed during
odd- compared to even-numbered years (Davis, 2003).
Few annual estimates of squid abundance are available,
but Sobolevsky (1996) estimated that epipelagic squid
biomass in the western Bering Sea was approximately
five times greater in an even-year (1990) than in an
odd-year (1989). Population dynamics and life history
of squid are not well known (Nesis, 1997; Brodeur et
al., 1999), but their apparent one- or two-year life his-
tory, in conjunction with predation by pink salmon, may
lead to an alternating-year pattern of squid abundance
that re-enforces the alternating-year pattern of sockeye
salmon growth.
Ruggerone et al. (2003) reported that Bristol Bay
sockeye salmon that inhabited the ocean in odd-num-
bered years of their second year at sea experienced
lower smolt-to-adult survival compared with sockeye
salmon that were present during even-numbered years.
Lower survival was believed to be related to competi-
tion with Asian pink salmon. Our findings suggest that
this mortality was likely related to reduced growth
during late spring through fall, rather than during
the first winter. We hypothesize that reduced sockeye
salmon growth during the second year at sea led to
lower energy reserves and to greater mortality during
the second winter, but predation on smaller salmon may
also be an important factor (Nagasawa, 1998). Bioener-
getic modeling of salmon by Aydin (2000) indicated the
greatest difference between the need for prey and prey
availability is during winter. Nagasawa (2000) reported
exceptionally low prey availability and corresponding
low lipid content for salmon in the North Pacific Ocean
during winter. Ishida et al. (1998) examined salmon
on the high seas and determined that condition factor
of all salmon species was lowest during late winter.
Beamish and Mahnken (2001) provided evidence that
relatively low growth of salmon during summer and
fall can lead to significant growth-related mortality
during the first winter at sea. Growth-related mortal-
ity appears to occur among Bristol Bay sockeye salmon
in response to competition with pink salmon, but this
competition-related mortality primarily occurs during
the second winter at sea.
Bristol Bay sockeye salmon are broadly distributed
across the North Pacific Ocean and Bering Sea. They
occur in several oceanographic regions in which domi-
nant prey may vary (e.g., the Bering Sea (euphausiids,
squid, fish], subarctic current [squid], ridge domain
(small zooplankton], the Alaska stream [small zoo-
plankton, squid, fish], and the coastal domain [fish,
euphausiids]) (Pearcy et al., 1988; Aydin, 2000). The
alternating-year pattern of scale growth was persistent
among adult Kvichak and Egegik sockeye salmon of all
age groups returning to Bristol Bay even though many
of these fish likely inhabited different ocean habitats.
Thus, the observed scale growth pattern is either highly
persistent in most of these ocean habitats or it is es-
pecially important in certain key regions inhabited by
Bristol Bay sockeye salmon.
Salmon growth in relation to the regime shift
of the mid-1970s
Several studies indicate that a significant change in the
species assemblage of the North Pacific Ocean began
near 1977 and concurrent with a dramatic shift in
physical oceanic regimes (Francis et al., 1998; Anderson
and Piatt, 1999). Pacific salmon abundance, including
Bristol Bay sockeye salmon, more than doubled after
this period (Rogers1). Zooplankton and squid biomass
have appeared to increase substantially, especially in
coastal regions, since the mid-1970s (Brodeur and Ware,
1992; Brodeur et al., 1996). Furthermore, Mackas et al.
(1998) reported that the period of maximum zooplank-
ton biomass shifted one or two months earlier after
the mid-1970s. In comparison, seasonal scale growth
of Kvichak and Egegik sockeye salmon during the first
and second years at sea tended to be high after the
regime shift. This pattern was also observed in annual
scale measurements of sockeye salmon (Ruggerone et
al., 2002). Spring scale growth of sockeye salmon after
the regime shift was relatively high immediately after
entry of sockeye salmon into Bristol Bay and during
Ruggerone et al.: Seasonal growth of Oncorhynchus nerka in relation to competition with O. gorbuscha
367
their third year at sea, but spring growth was relatively
low during the second year. Growth during the second
year was relatively high during summer, a pattern that
was different from SW1 and SW3 growth. Seasonal
scale growth patterns of sockeye salmon indicate that
the response of salmon to the 1977 ocean regime shift
varied with age and season but that the greater growth
during early marine life was associated with greater
adult returns. The shift in seasonal growth patterns
of sockeye salmon likely reflected their opportunis-
tic forging behavior and the changes in prey species
abundances caused by climate change (Kaeriyama et
al, 2004).
Greater growth of sockeye salmon when they initially
entered the Bering Sea after the 1977 ocean regime
shift may reflect differences in seaward migration pat-
terns. Prior to the 1977 regime shift, juvenile sockeye
salmon were observed in a narrow band that extended
from the shore along the Alaska Peninsula to as far as
50 km offshore (Straty, 1981; Hartt and Dell, 1986).
However, recent survey results indicate that juvenile
sockeye salmon are broadly distributed in the eastern
Bering Sea from the Alaska Peninsula to north of 58°N
and that the highest catch rates occur beyond 50 km
offshore (Farley et al.7). Zooplankton are more abundant
in offshore, deeper waters of Bristol Bay than within
near shore waters (Straty, 1981; Napp et al., 2002),
indicating that the recent northerly seaward migration
patterns of juvenile sockeye salmon may place them in
areas of higher prey densities and lead to higher early
marine growth rates.
Sockeye salmon scale growth during the third year
of growth (SW3) was relatively low after 1977, indicat-
ing that density-dependent growth was most apparent
during this late life stage when mortality is likely rela-
tively low (Ruggerone et al., 2002). Our study indicated
the reduced SW3 growth after the 1977 regime shift
occurred after peak spring growth, indicating that in-
terspecific competition was most apparent during sum-
mer and fall. During the spring homeward migration
(SWPL) period, scale growth was above average after
1977. Age-specific size of adult sockeye salmon return-
ing to Bristol Bay was density dependent, but size at a
given density was greater after 1977 (Rogers and Rug-
gerone, 1993; Ruggerone et al., 2003).
7 Farley, E. V., Jr., R. E. Haight, C. M. Guthrie, and J. E.
Pohl. 2000. Eastern Bering Sea (Bristol Bay) coastal
research on juvenile salmon, August 2000. Doc. 499, 18 p.
North Pacific Anadromous Fish Commission, 889 Pender
Street, Vancouver, Canada.
Farley, E.V., Jr., CM. Guthrie, S. Katakura, and M.
Koval. 2001. Eastern Bering Sea (Bristol Bay) coastal
research on juvenile salmon, August 2001. Doc. 560, 19 p.
NPAFC, 889 Pender Street, Vancouver, Canada.
Farley, E.V, Jr., B.W. Wing, A. Middleton, J. Pohl, L. Hulbert,
M. Trudel, J. Moss, T. Hamilton, E. Parks, C. Lagoudakis, and
D. McCallum. 2002. Eastern Bering Sea (BASIS) Coastal
Research (August-2002) on Juvenile Salmon. Doc. 678, 27
p. NPAFC, 889 Pender Street, Vancouver, Canada.
Salmon survival and scale growth
Biologists have suggested that rapid growth early in
life can lead to greater growth in subsequent periods
because larger animals have a greater variety of prey
and prey size available to them (Pearcy et al., 1999).
Aydin (2000) hypothesized that rapidly growing salmon
in their first year at sea would more quickly reach a
threshold size for feeding on abundant, energy-rich
micronekton squid, leading to even greater growth in
their second year. However, comparison of early marine
scale growth (SW1 through SW2, circuli 8) with late
season SW2 growth of individual Kvichak and Egegik
sockeye salmon indicated a negative rather than positive
relationship. Individual salmon having relatively great
early marine scale growth tended to experience reduced
scale growth during the later portion of their second year
when sockeye salmon reach the size needed to readily
consume larger prey such as squid. This finding reflects
the growth of sockeye salmon survivors and not those
that died at sea. Thus, we interpret this counterintui-
tive finding as an indication that slow growing sockeye
salmon during late SW2 survived primarily when their
early marine growth was relatively high. Salmon that
experienced both low early marine growth and low SW2
growth apparently did not survive and were not repre-
sented in the scale collection. These observations do not
necessarily reject the hypothesis that high early marine
growth leads to high subsequent growth. In fact, other
analyses of sockeye scales indicate spring growth is
positively correlated with fall growth within a given
year (G. Ruggerone, unpubl. data).
Effect of freshwater age on seasonal scale growth
Scale growth during the first year at sea was differ-
ent among salmon spending one versus two winters in
freshwater. Early SW1 scale growth of sockeye salmon
spending two winters in freshwater (age-2.) was sig-
nificantly greater than that of salmon spending only
one winter in freshwater. This trend might reflect dif-
ferences in migration timing or size (or both) of age-2
versus age-1 smolts. Age-2 smolts are approximately
17 mm longer than age-1 smolts and most age-2 smolts
enter marine waters before age-1 smolts (Crawford and
West8). After peak growth in spring, scale growth of age-
1. smolts exceeded that of age-2. smolts. The different
early marine growth patterns of age-1. and age-2. smolts
did not appear to significantly affect the size of the fish
at the end of the growing season. For example, during
1958-72, age-2. 1 sockeye salmon sampled immediately
south of the Aleutian Islands were 25 mm longer than
age-1. 1 sockeye salmon (French et al., 1976). The size
difference between age-2. and age-1. smolts declined to
8 mm during the second growing season.
; Crawford, D. L., and F. W. West. 2001. Bristol Bay sock-
eye salmon smolt studies for 2000. Reg. Info. Rept. 2A01-
12, 164 p. Alaska Dept. Fish Game, 333 Raspberry Road,
Anchorage, AK.
368
Fishery Bulletin 103(2)
Difference in growth by ocean age
Barber and Walker (1988) reported that peak SW2 scale
growth for Bristol Bay sockeye salmon (Ugashik stock)
was less than peak growth during SW1 and SW3. They
suggested that this trend reflected lower prey availability
for sockeye salmon in the North Pacific Ocean than in the
Bering Sea (Mackas and Tsuda, 1999). But Bristol Bay
sockeye salmon also develop in the Bering Sea during
their second growing season (French et al., 1976; Myers
et al.3). Kvichak and Egegik sockeye salmon scales,
1955-2000, exhibited relatively low growth throughout
SW2 year compared to SW1 and SW3 years. We suggest
that low SW2 growth may also be related to the inabil-
ity of sockeye salmon to efficiently capture large prey
(Aydin, 2000) and to a lower bioenergetic efficiency when
consuming smaller prey. Salmon in their third year at
sea may experience greater prey availability and capture
efficiency because they are larger.
Late season growth of ocean age-2 sockeye salmon
during SW2 was significantly greater than that of ocean
age-3 sockeye salmon. This finding indicates that the
greater size-at-age of ocean age-2 sockeye salmon com-
pared to ocean age-3 sockeye salmon at the end of the
second growing season (French et al., 1976) may be
largely related to increased growth during the later
portion of the second growing season at sea.
Conclusions
Seasonal scale growth patterns of Kvichak and Egegik
sockeye salmon exhibited significant differences in SW2
and SW3 scale growth during odd- versus even-num-
bered years. Differences in scale growth did not begin
until after peak scale growth and difference began
somewhat later for younger SW2 sockeye salmon. The
persistence of this pattern over the past 45 years may
be caused by pink salmon, especially those from eastern
Kamchatka that are highly abundant during odd-num-
bered years. During odd-numbered years, pink salmon
reduced prey abundance prior to migrating to coastal
areas in June and July (Shiomoto et al., 1997; Sugimoto
and Tadokoro, 1997). This prey reduction, coupled with
declining abundance and ontogenetic vertical migra-
tions of some zooplankton (Mackas and Tsuda, 1999),
appears to have influenced (reduced) growth of sockeye
salmon from early summer through fall of odd-numbered
years. We hypothesize that the alternating odd- and
even-year growth pattern of sockeye salmon may be re-
enforced by the one- or two-year life cycle of prey, such
as squid, whose abundance may be out-of-phase with
the two-year cycle of pink salmon. These data, coupled
with previous findings of reduced smolt-to-adult sur-
vival of sockeye salmon that interacted with odd-year
pink salmon during the second year at sea (Ruggerone
et al., 2003), indicate that reduced growth of salmon
during the second year at sea can lead to measurable
salmon mortality. Sockeye mortality associated with
pink salmon likely occurs during winter when demand
for prey by salmon exceeds the low availability of prey
(Aydin, 2000), but it may also occur in response to size-
selective predation. Our study indicates that salmon
growth and survival are influenced by complex food web
interactions, which are likely to significantly shift under
various scenarios of climate change that affect tempera-
ture, C02, and phytoplankton community structure of
the Bering Sea (Hare et al.9).
Acknowledgments
We appreciate the efforts of biologists and technicians
of the Alaska Department of Fish and Game who col-
lected salmon scales and associated data, and B. Agler
and D. Oxman who helped compile the data. S. Good-
man assisted with graphics. The manuscript benefited
from comments provided by N. Davis, G. Duker, and two
anonymous reviewers. This study was funded by the
Global Change Program, Biological Resources Division,
U.S. Geological Survey.
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371
Abstract— Distribution of eggs and
larvae and feeding and growth of
larvae of Japanese Spanish mack-
erel iScomberomorus niphonius) were
investigated in relation to their prey
in the Sea of Hiuchi, the Seto Inland
Sea. Japan, in 1995 and 1996. The
abundance of S. niphonius eggs and
larvae peaked in late May, corre-
sponding with that of clupeid larvae,
the major prey organisms of S. nipho-
nius larvae. The eggs were abundant
in the northwestern waters and the
larvae were abundant in the south-
ern waters in late May in both years,
indicating a southward drift during
egg and yolksac stages by residual
flow in the central part of the Sea of
Hiuchi. Abundance of clupeid larvae
in southern waters, where S. nipho-
nius larvae were abundant, may indi-
cate a spawning strategy on the part
of first-feeding S. niphonius larvae
to encounter the spatial and tem-
poral peak in ichthyoplankton prey
abundance in the Seto Inland Sea.
Abundance of the clupeid larvae was
higher in 1995 than in 1996. Feed-
ing incidence (percentage of stomachs
with food; 85.3% in 1995 and 67.7%
in 19961 and mean growth rate esti-
mated from otolith daily increments
(1.05 mm/d in 1995 and 0.85 mm/d
in 1996) of S. niphonius larvae in
late May were significantly higher
in 1995. Young-of-the-year S. nipho-
nius abundance and catch per unit of
fishing effort of 1-year-old S. nipho-
nius in the Sea of Hiuchi was higher
in 1995, indicating a more successful
recruitment in this year. Spatial and
temporal correspondence with high
ichthyoplankton prey concentration
was considered one of the important
determinants for the feeding success,
growth, and survival of S. niphonius
larvae.
Distribution, feeding condition,
and growth of Japanese Spanish mackerel
iScomberomorus niphonius) larvae
in the Seto Inland Sea
Jun Shoji
Masaru Tanaka
Laboratory of Estuanne Ecology
Field Science Education and Research Center
Kyoto University
Kita-shirakawa, Sakyo, Kyoto 606-8502, Japan
E-mail address (for J Sho|i): shogG'kais.kyoto-uaC-ip
Manuscript submitted 12 February 2004
to the Scientific Editor's Office.
Manuscript approved for publication
28 December 2004 by the Scientific Editor.
Fish. Bull. 103:371-379 12005).
Scombrid fishes are considered to have
adopted a survival strategy charac-
terized by fast growth and the abil-
ity to consume large prey at an early
age (Hunter, 1981). Their larvae have
morphological features such as large
eyes and mouths, with which piscivory
and fast growth can be achieved in
early life stages. Among scombrids,
extremely early piscivory and fast
growth have been observed in the
early life stages of Spanish mackerels
iScomberomorus fishes). Fish larvae
were dominant in stomachs of Scomb-
eromorus larvae in three regions: 1) S.
semifasciatus, S. queenslandicus, and
S. commerson, in Australian waters
(Jenkins et al., 1984), 2) Spanish
mackerel (S. maculatus) and king
mackerel (S. cavalla) in the south-
eastern United States (Finucane et
al., 1990), and 3) Japanese Spanish
mackerel (S. niphonius) in the Seto
Inland Sea, Japan (Shoji et al., 1997).
Larval growth rate was reported to
be approximately 1.0 mm/d in king
and Spanish mackerels (DeVries et
al., 1990; Peters and Schmidt, 1997)
and S. niphonius (Shoji et al., 2001).
Tanaka et al. (1996) demonstrated
precocious development of an adult-
type digestive system (with a func-
tional stomach and pyloric caecum)
occurred in first feeding S. niphonius
larvae. They suggested that Scomb-
eromorus fish have adopted a special-
ized feeding strategy, namely piscivory
and fast growth from the time of first
feeding, which reduces the duration of
the larval stage, the period of great-
est vulnerability to predation ( Houde,
1987).
Ichthyoplankton prey seem to be
indispensable for growth and survival
during larval period of Scorn beromorus
fish. Under laboratory conditions, Fu-
kunaga et al. (1982) reported that S.
niphonius larvae preferred fish larvae
to invertebrate plankton prey (roti-
fer and Artemia nauplii). Shoji and
Tanaka (2001) demonstrated that S.
niphonius larvae began to cannibal-
ize siblings when they were supplied
with only invertebrate plankton prey.
Scomberomorus larvae would need to
exert greater searching effort and to
swim fast to capture ichthyoplank-
ton prey because they are larger and
much less abundant in water than
invertebrate plankton prey (Sheldon
et al., 1972). Scomberomorus larvae
with a high swimming performance
have been shown to have high levels
of larval mortality due to starvation.
Margulies (1993) demonstrated by
histological analysis that Pacific sier-
ra (S. sierra) larvae could not survive
beyond 48 hours without feeding in
the Panama Bight. Shoji et al. (2002)
observed that the point-of-no-return
for S. niphonius larvae was one day
after first feeding in laboratory ex-
periments. Scomberomorus niphonius
larvae fed after 1- or 2-days starva-
tion showed significantly retarded
growth during the following period
372
Fishery Bulletin 103(2)
of adequate feeding compared to fish that had been fed
from the time of first feeding. These observations sug-
gest that ichthyoplankton prey availability can strongly
influence growth and survival of S. niphonius larvae.
Scomberomorus niphonius is distributed in the coastal
waters of Japan and supports important commercial
fisheries in the Seto Inland Sea. The total catch ex-
ceeded 6000 metric tons (t) in the middle 1980s but
decreased to less than 1000 t in the late 1990s in the
Seto Inland Sea. Spawning migration of S. niphonius
into the Seto Inland Sea occurs in May (Kishida and
Aida, 1989) and the larvae are distributed in May and
June in the Sea of Hiuchi, the central Seto Inland Sea
(Kishida, 1988). In order to ensure that catches remain
at stable levels and to establish more efficient fisheries
management, it is necessary to accumulate biological
information to elucidate the recruitment process of the
species.
The objective of the present study is 1) to investigate
spatial and temporal distribution of S. niphonius larvae
and their prey and 2) to compare feeding conditions and
growth of S. niphonius larvae for two consecutive years
with contrasting levels of recruitment. 1995 and 1996,
in the Seto Inland Sea, Japan. The catch-per-unit-of-
fishing-effort (CPUE: no. offish/boat/day) of 1-year-old
S. niphonius (Fig. 1) fished by drift gill net in May, the
major fishing season for the species, at the Kawarazu
Fisherman's Association (Fig. 2) has been used as a
recruitment index in the Sea of Hiuchi (Kishida, 1991).
The CPUE fluctuated tenfold in the 1990s (Ehime Pre-
fecture Chuyo Fisheries Experimental Station Toyo
Branch1) and indicated recruitment in 1995 was more
successful. Egg, larval, and larval prey distributions,
larval feeding incidence and growth, and young-of-the-
year (YOY) fish abundance were investigated in 1995
and 1996 in the Sea of Hiuchi.
Materials and methods
Ichthyoplankton sampling
Three research cruises were carried out in 1995 (11-16
April, 24-28 May, and 20-23 June) and in 1996 (10-13
May, 27-30 May, and 18-21 June) in the Sea of Hiuchi
(Fig. 2). Ichthyoplankton sampling and hydrographic
survey were conducted from the RV Shirafuji (138 t) of
the National Research Institute of Fisheries and Envi-
ronment of Inland Sea (NRIFEIS). Double oblique tows
from the surface to 5 m above the bottom were made
by using a bongo net (0.7-m diameter, 0.315-mm mesh)
at 80 stations during the cruises in 1995 and at 50
stations in 1996. Average depth of the Sea of Hiuchi is
approximately 17.8 m (Montani, 1996). Scomberomorus
1990
1992 1994 1996
Year class
Figure 1
Catch per unit of fishing effort
(CPUE: no. offish/boat/day) of 1-
year-old Scomberomorus niphonius
in the 1990-99 year classes at the
Kawarazu Fisherman's Association
in the central Seto Inland Sea. Data
were obtained from drift gill-net
catches in May. the major fishing
season for S. niphonius.
1 Ehime Prefecture Chuyo Fisheries Experimental Station Toyo
Branch. 2000. Unpubl. data. Kawarazu, Toyo, Ehime
799-1303, Japan.
niphonius larvae were quickly sorted from the samples
and were preserved in 95% ethanol. Other ichthyoplank-
ton were fixed in 10% formalin seawater for sorting in
the laboratory. Flow meters were mounted in the mouth
of the net to determine the filtered volume. Each tow
followed a salinity-temperature-depth sensor cast to
measure the water temperature and salinity profiles at
each station.
YOY fish abundance
YOY S. niphonius have been reported to occur in the
southern part of the Sea of Hiuchi from late June to
early July (Watanabe, 1994). To detect a potential dif-
ference in S. niphonius recruitment abundance between
1995 and 1996, YOY fish abundance was assessed in the
southern part of the Sea of Hiuchi. YOY S. niphonius
were collected from catches by a seine fishery in the
southern part of the Sea of Hiuchi (Fig. 2). The seine
fishery primarily targets young and adult Japanese
anchovy iEngraulis japonicus). The codend of the net
has a 2-mm mesh aperture and was towed by two boats
for about 1 hour at a ship velocity of 3 to 4 knots. Two
to 10 kg of the catch by the seine fishery was sampled
weekly (five times each year) from mid June to late July
in 1995 and 1996. YOY abundance was expressed as the
number of S. niphonius per 10 kg of the catch.
Laboratory procedures
Larval SL was measured to the nearest 0.1 mm, and
stomach contents were identified under a dissecting
microscope. After removal of S. niphonius larvae, the
bongo-net samples were processed to estimate concentra-
tions (no./lOO m2) of S. niphonius eggs. Larvae of two
Sho|i and Tanaka: Feeding and growth of Scomberomorus niphomus
373
Japan N
Sea -+-
O Pacific
V Ocean
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20°
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• ©
•
• •
• •
•
•
© ■
•
•
. . .
• •
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•
•
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•
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34°N"
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133°E
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40°
i
Figure 2
Map of the Sea of Hiuchi, central Seto Inland Sea, showing the
sampling stations where ichthyoplankton were collected with a bongo
net during the three cruises in 1995 Iclosed small circles) and in
1996 (large open circles). Catch data for 1-year-old S. niphonius were
obtained at Kawarazu Fisherman's Association (asterisk). Young-
of-the-year Japanese Spanish mackerel were collected by the seine
fishery in the southern waters indicated by the shaded area.
clupeid species, gizzard shad (Konosirus punctatus) and
Japanese sardine iSardinops melanostictus), that were
the major prey organisms of the post-first-feeding S.
niphonius larvae (see "Results" section) were counted
to estimate prey concentrations.
Scomberomorus niphonius larvae were aged by count-
ing daily increments on otoliths. Right-side sagittal oto-
liths were removed under a dissecting microscope and
the number of increments on the otolith were counted
using an image-analysis system (ARP, version 4.21,
Ratoc System Engineering Co., Ltd., Tokyo, Japan) con-
nected to a compound light microscope at 400 to 1000 x
magnification. Daily increments begin to be deposited
on the sagittal otoliths of S. niphonius larvae at first
feeding (Shoji and Tanaka, 2004). Scomberomorus ni-
phonius larvae initiate feeding on day 5 under 19.0°C
(Shoji et al., 2001). Larval age was therefore estimated
by adding five to the increment count because the water
temperature in the southern part of the Sea of Hiuchi
where S. niphonius larvae were abundant ranged be-
tween 18° and 20°C (see "Results" section) in late May.
Data from cruises in late May only (the second cruise
in both years) were included in the feeding and growth
analyses because no S. niphonius larvae were collected
during the first cruise and too few were collected during
the third cruise in both years.
Results
Physical environment
The surface water temperature was higher in the south-
eastern area and lower in the northwestern area in all
cruises. Mean surface temperatures (±SD) were 12.3°
(±0.4), 18.6° (±1.2), and 20.5° (±0.6)°C in 11-16 April,
24-28 May, and 20-23 June, 1995, and were 14.3° (±0.6),
19.0° (±1.3), and 19.4° (±1.0)°C in 10-13 May, 27-30
May, and 18-21 June 1996, respectively (Fig. 3). Salinity
ranged between 32.5 and 34.3 ppt and was lower in the
southeastern area in all cruises. In late May, during the
seasonal peak in abundance of S. niphonius larvae, the
mean surface temperature was slightly higher in 1996
although there was no significant difference between the
two years (ANOVA: F=3.14, P=0.08).
Scomberomorus niphonius eggs and larvae
A total of 1018 eggs and 272 larvae of S. niphonius were
collected during the cruises. No eggs and larvae of S.
niphonius were collected during the first cruise in both
years. The egg and larval abundance peaked in late May
and decreased thereafter in both years (Fig. 4, A and B).
The eggs were abundant in the northwestern waters in
374
Fishery Bulletin 103(2)
late May where the surface temperature was between
17° and 19°C (Fig. 5). The larvae were abundant in the
middle to southern waters, where the surface tempera-
ture was between 18° and 20°C in late May (Fig. 6).
There was no significant difference in egg and larval
abundance in late May between the two years ( ANOVA:
F=0.03, P=0.87 for eggs; F=0.02, P=0.89 for larvae).
Clupeid larvae
Of the 107,252 larvae collected throughout the cruises,
clupeid larvae were most dominant, accounting for 57.2%
in number. Gizzard shad and Japanese sardine larvae
accounted for 76.4% and 23.6% of clupeid larvae, respec-
tively. A seasonal change in abundance of clupeid larvae
and a peak in abundance in late May in both years
were evident (Fig. 4C). Maximum abundance (no./m2)
was more than 400 in late May in 1995 in the southern
waters and there was no station where the abundance
exceeded 300/m2 in 1996 (Fig. 7). The difference in
abundance of clupeid larvae in late May between the two
years was significant (ANOVA: F=8.12, P=0.005).
Feeding
Clupeid larvae (gizzard shad, Japanese sardine, and
unidentified clupeid larvae) were the most dominant
items in the stomachs of S. niphonius larvae (Table 1).
Feeding incidence (percentage of stomachs with food)
was significantly higher in 1995 than in 1996 (chi square
test; df=l, chi-square=8.538, P=0.0035).
Growth
Age of S. niphonius larvae collected in late May in 1995
and 1996 was estimated to be between 5 and 14 days
Figure 3
Contour plots of the surface water temperature (°C) of the Sea of Hiuchi during the three
cruises in 1995 and 1996.
Shop and Tanaka: Feeding and growth of Scomberomorus niphonius
375
after hatching. Relationships between larval age (A) and
SL (L. mm) were best described by a linear regression
for each year (Fig. 8):
1995: L = 1.05A-1.39
1996: L = 0.85A-0.15
(ra=102, r2 = 0.87, P<0.0001)
1,7 = 93, r2=0.80, P<0.0001).
The slope of the equation for 1995 was significantly
higher than that for 1996 (ANCOVA; df=l, F=11.01,
P=0.001).
YOY S. niphonius abundance
YOY S. niphonius (14.6-122.8 mm in TL) were collected
by the seine fishery in the Sea of Hiuchi from late June
through late July in 1995 and 1996. Mean (±SE) abun-
dance of YOY S. niphonius in 1995 (7.7 [±2.1] individu-
als/m2) was significantly higher than that in 1996 (0.6
[±0.4] individuals/m2; Mann-Whitney [/-test; P=0.006,
Fig. 9).
Discussion
Spawning strategy
Abundance of S. niphonius eggs and larvae peaked
in late May in 1995 and 1996. A similar pattern was
observed in the abundance of clupeid larvae, indicating
that spawning of S. niphonius was synchronized with
4
3
A
• 1995
j 01996
2
/ /-
0
*y d ■*
r B
individuals
o
en
" ^
o
^"/ x_
1 0
150
.-^ t/ ' %
c
100
/ J2j\
50
" /^\
m ilk
0
April May June
Figure 4
Seasonal change in abundance (no./
m2) of S. niphonius eggs (A), larvae
(B) and clupeid prey larvae (Cl in
the Sea of Hiuchi in 1995 and 1996.
Bars indicate standard error.
24-28
1995
18
>2C
V
SJ»?
.c
4
w-
\y
Y.
■
*
*
■1
June \
20-23 <
1995
IZ
0.5 1
1.5
llm2
I
■ MM
S
^
•
\y
9
•
m>
June \
18-21 <
1996
•
0.5
1 1.5 /m2
! I ■
Figure 5
Horizontal distribution of S. niphonius eggs in the Sea of Hiuchi in 1995 and 1996.
376
Fishery Bulletin 103(2)
$$&■:■■:■:■■
w
_.:::
May \ •
24-28 \
^y^ 1 2 3
4/m2
1995 ^yv
HUM
Figure 6
Horizontal distribution of S. niphonius larvae in the Sea of Hiuchi in 1995 and 1996.
that of clupeid fishes in the central Seto Inland Sea.
Piscivorous fishes tend to spawn earlier than other fishes
in freshwater ecosystems so that they attain sufficient
size to enable consumption of other young fishes by
the onset of piscivory (Keast, 1985). Because S. nipho-
nius larvae are piscivorous from the first feeding stage,
spawning that is synchronized with the seasonal peak
in abundance of clupeid larvae would be advantageous
for survival of S. niphonius larvae.
Larvae of S. niphonius were abundant in the southern
part of the Sea of Hiuchi in late May 1995 and 1996
while eggs were abundant in the northwestern waters
during the same season. This difference in horizontal
distribution patterns of eggs and larvae seems to be as-
sociated with the drift by a residual flow (current) from
northern to southern waters. In the central part of the
Sea of Hiuchi, a residual flow in the middle (5-15 m)
layers proceeds southward at a speed of about 5 cm/s
(=4.32 km/d; Yanagi et al., 1995). Yolksac larvae of S.
niphonius are abundant in the 5- to 10-m layers in the
Sea of Hiuchi (Kishida, 1988) and do not exhibit diel
vertical migration (Shoji et al., 1999). The horizontal
distance between the stations with the highest egg and
larval abundance in late May was approximately 15
km in 1995 and 20 km in 1996. Given that the yolksac
stage is five days for mackerel larvae under 19°C (Shoji
et al., 2001), drift distance while larvae are entrained
in the southward residual flow during the yolksac stage
would be estimated to be approximately 20 km. The
estimate for the drift distance during the yolksac stage
Table 1
Feeding incidence (percentage of stomachs with prey) and
stomach contents of S. niphonius larvae collected in late
May of 1995 and 1996 in the Sea of Hiuchi.
No. of larvae examined
No. of larvae feeding
Feeding incidence {.% )
Size range (SL, mm)
Stomach contents
Sardinops melanostictus
Konosirus punctatus
Unidentified clupeids
Engra ulis japon icus
Unidentified Clupeiformes
Mugiliidae
Gobiidae
Total
1995
1996
102
93
87
63
85.3
67.7
4.2-13.8
4.5-14.2
4
2
21
14
19
11
2
4
34
22
3
2
13
9
96
64
approximates the horizontal distance between the sta-
tions of egg and larval highest abundance. It is there-
fore plausible that the larvae were transported by the
southward residual flow to the southern part of the Sea
Sho|i and Tanaka: Feeding and growth of Scomberomorus niphonius
377
^p&'^'
C
£7
<A^M>. . . .
•^S
AJrii^. • • •
^rAf* .^ .
Mav "BBB „
<& . .J
24-28 I V^a^1^~~^-
10Q. V .^ 100 200 3C
)0 400 /m2
^ ^ I I ■
June
20-23
1995
12 /m2
Figure 7
Horizontal distribution of clupeid larvae in the Sea of Hiuehi during the three cruises in 1995
and in 1996.
of Hiuehi where clupeid larva concentration was high
in late May. We suggest that spawning of S. niphonius
in the northern part of the Sea of Hiuehi would enable
their first-feeding larvae to meet high prey abundance
in the southern part.
Significance of high ichthyoplankton prey
Water temperature and prey concentration would be
possible factors that can influence growth rates of S.
niphonius larvae. In aquaria, the mean absolute growth
rate of S. niphonius larvae fluctuated between 0.87 and
1.28 mm/d depending on temperature between 18.2° and
22.6°C (Fukunaga et al., 1982; Shoji et al., 2001). In
the present study, the mean surface temperature of the
Sea of Hiuehi in late May was slightly higher in 1996,
although the difference was not significant.
The higher abundance of clupeid larvae in 1995 would
better explain the higher larval growth rate in 1995.
The mean larval growth rate in late May 1995, 1.05
mm/d, approximates those reported in aquaria at the
same temperature (1.03 mm/d at 20.8°C; Fukunaga et
al., 1982) where S. niphonius larvae were provided with
an excess of prey, indicating that the prey concentration
in late May 1995 met larval requirements. It is likely
that the lower growth rate in late May 1996 resulted
from lower prey concentration. This conclusion is sup-
ported by results of the stomach content analysis: the
larval feeding incidence was significantly lower in May
1996. We conclude that clupeid larvae concentration
had a significant effect on growth of the S. niphonius
larvae.
In the Sea of Hiuehi, clupeid larvae abundance greatly
increased from April to May. We suggest that the prey
378
Fishery Bulletin 103(2)
20
15
1995
L=1 .05-4-1.39
n=102 r2=0.87
1996
L=0.65A-0 .15
n=93 r2=0.80
i i
12
16
A (d)
Figure 8
Relationships between standard length
(L, mm) and otolith-estimated age (A, d)
of S. niphonius larvae collected during
the cruises in late May of 1995 and 1996
in the Sea of Hiuchi.
10
2 8
o
S e
to
1 4
i 2
0
1995 1996
Year
Figure 9
Mean (SE) young-of-the-year S. niphonius abun-
dance collected by the seine fishery in 1995 and
1996 in the Sea of Hiuchi. Asterisk indicates a
significant difference between the years (Mann-
Whitney I/- test, P<0.01).
availability for S. niphonius larvae fluctuated depending
for the most part on seasonal change in abundance of
gizzard shad larvae that were dominant in the Sea of
Hiuchi. The difference in clupeid larval abundance in
late May between 1995 and 1996 may be explained by
between-year difference in gizzard shad spawning stock
biomass. The total catch of gizzard shad in the south-
ern Sea of Hiuchi (coastal waters of Ehime Prefecture)
in 1995 (372 t) was higher than that in 1996 (217 t:
Ehime Prefecture Agriculture, Forestry and Fisheries
Statistics Association, 1998).
Implications for recruitment
Variability in larval growth rate can influence survival
during the larval period by affecting the length of the
early life stages because total mortality is positively cor-
related with the length of these early life stages (Houde,
1987). Campana (1996) demonstrated a significant corre-
lation between growth to the end of the pelagic juvenile
stage (90 d) and the year-class strength of Atlantic cod
on the Georges Bank and suggested that the adult cohort
strength could be predicted from growth during early life
stages. In the present study, egg and larval S. niphopius
abundance during their peak-occurrence period did not
differ between 1995 and 1996, whereas YOY and 1-year-
old S. niphonius were more abundant in 1995. These
results indicate more successful recruitment and higher
larval growth rate in 1995 although there are no data
available for years other than 1995 and 1996. Larvae of
S. niphonius initiate feeding at 5.59 mm SL at 18.5°C
(Shoji et al., 2002). Given the mean larval growth rate
in 1995 (1.05 mm/d) and 1996 (0.88 mm/d), the critical
period (from first feeding to the onset of schooling at the
early juvenile stage, 19.6 mm SL; Masuda et al., 2003)
is estimated as 13.3 days in 1995 and 16.5 days in 1996.
For S. niphonius, even a slight increase in larval stage
duration due to retarded growth can greatly reduce
larval survival because the larval daily mortality coeffi-
cient is expected to be extremely high (>0.6: Grimes and
Kingsford, 1996). The lower recruitment of S. niphonius
in 1996 may be partly explained by the prolonged larval
period (3.2 d) which could have led to lower survival
(1/6.82, assuming the daily mortality coefficient is 0.6)
during the larval period of that year.
Acknowledgments
We thank M. Fukuda, N. Suzuki, N. Kohno, and the crew
of RV Shirafuji of NRIFEIS and staff of Asagi-Suisan
Co. Ltd. for their assistance with field sampling. We also
thank T. Maehara and N. Murata, Ehime Prefecture
Chuyo Fisheries Experimental Station Toyo Branch,
and Y. Maki, Kawarazu Fisherman's Association, for
their help in collecting young-of-the-year Japanese Span-
ish mackerel and data on the catch of 1-year-old fish.
Two anonymous reviewers and M. Takahashi, National
Research Institute of Fisheries Science, provided valu-
able comments on the manuscript.
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1996. Year-class strength and growth rate in young
Atlantic cod Gadus morhua. Mar. Ecol. Prog. Ser. 135:
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380
Abstract— We consider estimation of
mortality rates and growth param-
eters from length-frequency data of a
fish stock and derive the underlying
length distribution of the population
and the catch when there is individual
variability in the von Bertalanffy
growth parameter L„. The model is
flexible enough to accommodate 1) any
recruitment pattern as a function of
both time and length, 2) length-spe-
cific selectivity, and 3) varying fish-
ing effort over time. The maximum
likelihood method gives consistent
estimates, provided the underlying
distribution for individual variation in
growth is correctly specified. Simula-
tion results indicate that our method
is reasonably robust to violations
in the assumptions. The method is
applied to tiger prawn data (Penaeus
semisulcatus) to obtain estimates of
natural and fishing mortality.
Maximum likelihood estimation of
mortality and growth with individual variability
from multiple length-frequency data
You-Gan Wang
CSIRO Mathematical and Information Sciences
65 Brockway Road
Floreat Park
Western Australia 6014, Australia
E-mail address. You-Gan Wangig'csiro.au
Nick Ellis
CSIRO Marine Research
P.O.Box 120
Cleveland, Queensland 4163, Australia
Manuscript submitted 5 March 2004
to the Scientific Editor's Office.
Manuscript approved for publication
9 November 2004 by the Scientific Editor.
Fish. Bull. 103:380-391 (20051.
Estimation of growth and mortality
is fundamental in fisheries because
stock assessment and management
rely on these population parameters.
Length-frequency-based methods
become important when aging tech-
niques are either not possible or very
expensive. Existing methods such
as that of Beverton and Holt (1956)
assume that recruitment is continu-
ous and constant throughout the year,
which leads to a population with an
exponentially distributed age struc-
ture. Existing modifications to Bever-
ton and Holt's method comprise some
simple recruitment patterns or distri-
butions (Ssentongo and Larkin 1973;
Ebert 1980; Hoenig 1987; Wetherall
et al. 1987). As pointed out by Vetter
(1988), the existing methods for esti-
mating mortality in the literature
have strong limitations and disadvan-
tages. In particular, they require the
following assumptions:
1) each individual follows the same
von Bertalanffy growth curve;
2) the recruitment is either con-
tinuous and constant through-
out the year (as in Beverton and
Holt [1956] and Wetherall et al.
[1987]) or is a pulse function (as
in Hoenig [1987]);
3) the total instantaneous mortality
rate, z, is constant.
As pointed out by Sainsbury (1980),
it is more realistic to allow individual
variability in growth. For example,
using tag-recapture data, Wang et al.
(1995) found substantial individual
variability for the tiger prawn species
P. semisulcatus.
Estimation of mortality relies on
the distribution of the lengths, which
is determined by the age distribution,
mortality rates, and the individual
variability in growth rates. If individ-
ual variability in growth is ignored,
an inappropriate length distribution
will be generated, leading to biases
in parameter estimates. It is also
biologically interesting to quantify
the individual variability in growth,
which has important implications in
fisheries management. Although it is
well understood that variability leads
to increased uncertainty in estimates,
it is less well recognized (among the
fisheries community) that variability
can also lead to bias. Wang and Ellis
(1998) analyzed the effect of ignoring
individual variability in a simplified
context of constant recruitment and a
single length-frequency record. They
found that, in the presence of indi-
vidual variability, existing methods
gave positively biased parameter es-
timates. More details about the back-
ground can be found in Ebert (1973),
Askland (1994), and Wang and Ellis
Wang and Ellis: Maximum likelihood estimate of mortality and growth from multiple length-frequency data
381
(1998). See DeLong et al. (2001) for alternative ap-
proaches to length-frequency data where individual
variability is taken into account.
In our study, we develop a new framework for analyz-
ing length-frequency data. In particular, we incorporate
1) individual variability in growth parameters; and 2)
an arbitrary recruitment function. The model is flexible
enough to incorporate various sizes at recruitment and
a fishing selectivity function. However, we did not use
these aspects in the analysis of tiger prawn data. Some
analytical expressions are derived for these generaliza-
tions. A maximum likelihood approach is developed for
estimation of mortality and growth parameters. Sepa-
ration of fishing mortality from natural mortality is
possible only when there is substantial contrast in the
effort pattern. We also require a known recruitment
pattern, and sampling times are spread out so that
the length-frequency data will contain information on
growth and mortality. Simulation studies are carried
out to determine the performance of the method. The
simulated data are generated from the recruitment pat-
tern of the brown tiger prawn iPenaeus esculentus) in
the northern prawn fishery of Australia. Finally we ap-
ply the maximum likelihood method to length-frequency
data from grooved tiger prawn data (P. semisulcatus) in
the northern prawn fishery of Australia.
where /',(/IL , =.v, L0=s) is the conditional probability
density function of L at time t when Lx is known to be
x and the size at recruitment is s. Note the lower limit
of the inner integral is / because L t cannot be less than
an individual's length.
Let the age (again, relative to t0) at recruitment of an
individual be A0. From Equation 1, we have age a at
length / is a = -k~1\og(l-l/L_j ) and hence the conditional
distribution, ft(l/Lx=x, Ln = s), which may be written
as ft(l\x, s) for brevity, can be expressed by using the
conditional distribution of age \\tia\Ly=x, A0=an) (see
Wang et al.. 1995), as
ft(l\x,s)-
k( x-1)
h, (-/?"' log(l-//.v)|.r,a0).
(3)
We now generalize assumptions 2 and 3 by introduc-
ing the intensity function of recruitment, r(t ), and the
total instantaneous mortality, z(t), which are arbitrary
functions of time t. The total mortality would depend on
time through the fishing mortality component F, where
zit)=M+Fit) and M is the constant natural mortality.
The age distribution satisfies
h,(a ILM=.v,A0-a0)~exp|-J z(t - a + y)dy\r(t - a + a0). (4)
Materials and methods
The model
We assume that the growth of individuals follow a von
Bertalanffy curve so that the length at age a (relative
to some origin t0) is given by
L(a) = LJl
-e-ha).
(1)
In this study, age is always defined to be relative to t0,
i.e. t0 is absorbed into a for the purpose of identifiability.
We will consider estimation of (k, lx) only because t0 is
not estimable from length-frequency data with aging
data. Note that this does not mean t0 is assumed to be
0. To provide a general treatment we relax each of the
assumptions mentioned in the introduction. First we
relax assumption 1 by letting the maximum length, L ,,
vary within the population. We denote the density func-
tion of L , as p(x), which has a mean of I r and a variance
of a2. It is possible that recruits to the fishery have a
range of sizes. To allow for this range we let the size
at recruitment, L0, be a random variable with density
function u(s). In practice, one may be able to use infor-
mation from other studies (such as subadult abundance)
to arrive at an approximate parametric form for u(s).
If ft(l) is the probability density function of L at time
t, then
ft(.l) = J"j"p(x\L0=s)ft(l\L„=x,LQ = s)u(s)dxds, (2)
This equation states that the density of individuals of
age a is proportional to the intensity of recruitment at
the time when these individuals were recruited, namely
t-a+a0, multiplied by a reduction factor due to mortality
over the intervening period. We therefore have
ht(a\x,s) = ht(a\L„=x,Ao=-k~1log(.l-s/x))
=exp(-|
(5)
-k "Mogll-s/.rl
zit-a + y )dy \r(t- a- k 1 log(l-s/x)
and Equation 3 becomes (after substituting for a and
shifting the dummy variable y)
x-l
exp
-j:
fta\x,s)
-M^fy)dy
t-k'Hog
x-s\) (6l
Let us consider the case of fixed recruitment length,
i.e., L0=l0, and define a parameter vector, p, consisting
of th, /x, s), and other parameters quantifying mortality
and catchability. Equation 2 then reduces to a single
integral over x,
fl(l\/5)ocj°°p(x)exp
-LMS)^4("r'log(^))£'
(7)
382
Fishery Bulletin 103(2)
A more convenient form for computation arises after
changing the integration variable from the asymptotic
length x to time since recruitment, t-a+a0,
'-*Sf3
(8)
The expression (Eq. 7) then becomes
ftil\p)^j°°p(x(T))exp(-f' ^z(y)dy)r(t-T) ^- (9)
In the special case of constant recruitment, i.e., r(t)=l,
and constant mortality, z(.t)=z, f,U\p) becomes indepen-
dent of time as first obtained by Powell (1979).
Maximum likelihood estimation
Let p,,(/3) be the expected proportion of individuals in
the ith length class (/,_j, /) on the j,h occasion, where
j=l, 2, • •• , N; and let n:] be the corresponding observed
numbers. The value of Pj.ifi) can be obtained from the
density function ft(l;P) given by Equation 2. Thus
P,/Py-
(10)
in which fAl;P) is the (unnormalized) density function on
the yth occasion. Under a multinomial model, estimation
of the parameter vector fi relies on the procedure
maximize £ nlt log Py(.fi) with respect to ft. (11)
The sum is the log-likelihood function up to a constant
independent of the parameters. The probability, p , can
be approximated as fj(.li+i/2^ifj^i+V2^> wnich is the nor-
malized value of the density function for thejth occasion
at the midpoint of the ;'th length class.
If sampling effort is known and expected catch is as-
sumed to be a known function of effort and population
abundance, the log-likelihood function in Equation 11
can be easily modified to incorporate effort informa-
tion. For example, if the total number of individuals on
each occasion, ni=I.i=nll, is assumed to follow a Poisson
model with overdispersion parameter v, the log-likeli-
hood function becomes
sampling effort, <p is the total abundance index over all
occasions; andp is the expected proportion of individu-
als on the./"1 occasion (i.e., the relative abundance), so
that (pp is the expected catch per unit of effort. In this
case we can obtain the maximum likelihood estimate of
<p as 2yi-/2.-ej7.-. The probability, p}, can be approximated
as EjjWj+i^V^ ,/J(/,+i/2>- Here v is introduced to allow for
overdispersion in the Poisson model. It plays a weighting
role for the two terms in Equation 12, and the second
summation can be regarded as auxiliary information.
If?;, is assumed to follow a Poisson distribution exactly,
we have v=l.
In our simulation and tiger prawn studies we specify
a case of fixed, known recruitment length, /0, and fM;P)
is obtained from Equation 7 or 9. For definiteness we
set the constant of proportionality implicit in these
equations to one.
The integrals in Equations 7 and 9 present some
subtleties for their evaluation, so that some details
of the numerical implementation might be of inter-
est. For the simulation study we used Equation 7.
The integral was performed on an /-dependent grid
of 41 and 81 quantiles of the Lx distribution p(x) and
then improved upon by using the Richardson extrap-
olation. Note that there is an apparent singularity
at x = l. However, by decomposing the mortality into
a mean and deviation term, z(y)=z +z(y)— z , we find
that the factor involving mortality is proportional to
(x-lYlk. Hence the integrand is proportional to (x-lYlk,
and, because zlk— 1>— 1, the singularity is integrable
(i.e., the integral is finite). We used a quadrature scheme
designed for integrands of the form (x— lrf(x)£>— 1, to
perform the integral in the neighborhood of x = l.
For the tiger-prawn study we used Equation 9. The
integral was performed on uniform grids of 41 and 81
points over the interval tE(0,1.5) years and, as before,
was improved by using the Richardson extrapolation.
We used our knowledge that tiger prawns live for about
18 months to determine the upper limit of integration.
Note that despite appearances, this integral contains no
singularity because 3c(t)-><* as t-»0), and therefore the
factor p(x(T))/(l-e_,'T)^0. The effort integral within the
integrand was computed by linear interpolation between
cumulative totals of the weekly effort.
The prototype implementation of our maximum like-
lihood method was written in S-plus software (Lucent
Technologies) by using the optimizer "nlminb." However,
to improve the performance for a large number of simu-
lations, the program was recoded in C by using Powell's
optimization routine with numerical derivatives (Press
et al., 1992). The C code and some relevant reports are
available on request.
5X-]ogpj,(j8) + vX{n,logA,(0)-A//»}, (12)
where A(/3) is the expected total number in the sample
on the j-th occasion and depends on effort. One way to
model this dependence is A/(/3) = 0p/(/3)e/, where ef is the
Results
Simulation studies
We simulated length-frequency data based on the
recruitment pattern of tiger prawns P. esculentus in
Wang and Ellis: Maximum likelihood estimate of mortality and growth from multiple length-frequency data
383
1.0
1.0
/T^^v ! ! !
„ 0.8
1 \ 1 Eflort •
0.8
(0
E
I 0.6
/ i \ ill.
Norma
CO
d
Q>
/ I \ ! !
N
<D
^ 0.4
/ \ Recruitment 1 '
0.4 |
|
O
/ ' "^^"\ • '
a
z 0.2
J ^L
0.2
0.0
""■""""' ! ! """] ■
0.0
Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
Month
Figure 1
The empirical recruitment pattern (solid line) of the tiger prawn Penaeus esculetus in the northern
prawn fishery of Australia and the fishing effort pattern (dashed line).
the northern prawn fishery of Australia. This pattern
has been derived from experimental trawls in which
the number of individuals in the lowest length class
are counted (Wang and Die, 1996). We assume the
recruitment and effort patterns are the same in each
year (Fig. 1). The effort pattern (dashed line) consists of
two constant-fishing periods: 15 May to 15 June, and 1
August to 1 December. The unit of effort, E, depends on
the unit of catchability, q, because the fishing mortality
F=qE must have unit vr1: therefore we let £=1 during
the fishing season. Note that the proportion of the year
that is fished is JE(t)dt=5/12.
The growth component of our models has ^ = 40 mm
and k=3yr~1; the instantaneous natural mortality is
M=2yr~l\ and the instantaneous fishing mortality, F,
during the fishing season is 4yr_1 (i.e., c/ = 4, because in
our units, F=q). The resulting annual mortality, Z=fz{t)
dt=M+qJE(t)dt=2+4x5/l2=ll/3. The values for mortal-
ity come from Somers and Wang (1996). We assume that
all recruits have length 19.5 mm. The L( distribution
is normal (standard deviation 4 mm) but is truncated
at 19.5 mm. The truncated normal distribution at l0 is
simply a conditional normal distribution conditional on
being greater than l0.
We generate twelve length-frequency data sets, one
for the beginning of each month. We choose a monthly
time interval because the data from our case study in
the next section were sampled at roughly monthly in-
tervals. In addtion, because the recruitment pattern is
periodic it is sufficient to analyze one year of data.
We obtain each monthly length-frequency data set
by taking a sample of size 1000 from the theoretical
length distribution ft(l) given by Equation 6, which
depends on the recruitment pattern, the effort pattern,
and the distribution of L^. That is, for each of the 12
time points /, we evaluate numerically the right-hand
side of Equation 6 over a set of finely spaced / values
(i.e., every 0.25 mm), aggregate the ft(l) to 1-mm inter-
vals and finally normalize the function by dividing by
the sum of ftil). This results in an array of probabilities
for an individual's length in each 1-mm interval. It is
then straightforward to sample from the corresponding
multinomial distribution.
We then obtain parameter estimates from the twelve
months of simulated data. The process is repeated 100
times to provide a reasonable estimate of the sampling
variance of the parameters. In practice, (k, IJ) can of-
ten be estimated from a different study. We therefore
consider two models. In model 1, we assume all five
parameters are unknown, and, in model 2, we assume
that lm and k are known and we estimate M, F, and a.
It is also common practice (e.g., Sullivan, 1992) to as-
sume that M is known and to estimate the remaining
parameters; this is the case in our model 3.
The results are summarized in Table 1. All the pa-
rameters are quite well estimated, even for model 1.
Estimates of both natural mortality and fishing mor-
tality are quite reliable when growth parameters are
assumed known. There is also a modest reduction in the
standard deviation when (k, Zx) are assumed known.
We have also tested for robustness by performing
the estimation process on data generated from a log-
normal distribution. The results are shown in Table 1.
For model 1 the estimates of M and F have a larger
and opposite bias, whereas the absolute bias for Z is
somewhat smaller. Model 2 improves the estimates
dramatically, despite the fact that an incorrect dis-
tribution (the truncated normal) is being used in the
model. Note that the variation in the estimates of total
annual mortality, Z, is somewhat less than that for F
and M; this is because F and M are highly negatively
correlated (typically 94%). In model 3 the estimate of
384
Fishery Bulletin 103(2)
Table 1
Mean parameter estimates and standard deviations (in parentheses) for
simulated tiger prawn (Pe/
aeus eseulentu
s ) data. The
model assumes an underlying truncated normal L_x distribution. The data are generated from two u
nderlyingLx d
istributions:
the truncated normal and the lognormal. With model 1 al
parameters are unassumed to be unknown; with model 2 ik, l^) are
assumed to be known; with model 3 M is assumed to be known.
Model k
'.
(7
Z
M
F
Underlying truncated normal distribution
True 3
40
4
3.67
2
4
1 2.99(0.05)
40.00(0.19)
4.02(0.08)
3.65(0.05)
1.98(0.15)
3.99(0.34)
2 3
40
4.01 (0.07)
3.65(0.04)
2.001.11)
3.95(0.28)
3 2.99(0.05)
40.02(0.15)
4.01(0.07)
3.65(0.05)
2
3.95(0.12)
Underlying lognormal distribution
True 3
40
4
3.67
2
4
1 3.02(0.07)
39.53(0.22)
4.28(0.08)
3.53(0.05)
1.51(0.16)
4.84(0.35)
2 3
40
4.14(0.07)
3.62(0.04)
1.93(0.11)
4.05(0.28)
3 2.96(0.06)
39.92(0.17)
4.16(0.07)
3.57(0.05)
2
3.76(0.11)
F is negatively biased, but once again the standard
deviation is reduced.
Application to tiger prawns (P. semisulcatus)
The data for this application consist of a six-year
sequence of experimental length-frequency data from
the trawling region around Albatross Bay in the east-
ern Gulf of Carpentaria, Australia. The data consist of
catches of tiger prawns from 11 mm to 59 mm (carapace
length) for each of 69 times ranging from March 1986 to
March 1992. The catches from several stations covering
the trawling region at each time (over a few consecutive
days) are aggregated. Sampling was done roughly every
lunar month.
We use the catch data for the smaller size classes to
obtain two types of recruitment patterns: the aperiodic
pattern and the quasiperiodic pattern. The aperiodic
pattern is constructed by summing over all individuals
with length 21 mm or less for each occasion. The result-
ing sequence of plotted time points is then joined up by
straight lines. The quasiperiodic pattern is generated
from the aperiodic pattern by averaging corresponding
points across years to give a single annual pattern. The
pattern for all six years is generated from the annual
pattern by applying, for each biological year, a scale
factor that is found by averaging the catch over all size
classes within the year. The start of the biological year
is defined as the time when the annual pattern reaches
its minimum (see Fig. 2).
The effort pattern comes from commercial log books
collected from fishermen for the period from 1986 to
1992 in the area. Effort is measured in boat-days (see
Fig. 2). There is substantial contrast in the effort both
within years (due to seasonal closures) and across
years. This contrast may allow us to separate fishing
mortality from natural mortality.
The instantaneous fishing mortality Fit) is assumed
to be qE(t). The mean total mortality Z=M+q E , where
E is the mean effort over the study period. Given the
results of the simulation study, we expect the parameter
Z may be more reliably estimated than either M or q,
whose estimates are negatively correlated.
We further assume that the L y distribution is a trun-
cated normal distribution. This choice is based on the
shape of the observed length distribution from July to
September, the period when this distribution should
approximate the asymptotic length distribution. The
truncated normal distributions are then reparameter-
ized in terms of the mean lx, and variance a\ of this
underlying normal distribution. It is more convenient to
use these parameters than the mean la and variance
a2 of the truncated normal distribution. Note that l^
is always larger than la and a is always less than a*.
However, in this application the two sets of parameters
are nearly interchangeable because over the range of
estimated values Zx exceeds lx* by at most 0.5 mm and
o, exceeds a by at most 0.6 mm (see Table 2).
We define a recruit to be an individual with length l0,
which can be chosen at discretion. We examine a range
of candidate values of /,, between 19.5 mm and 27.5 mm,
to find out which values provide the most suitable defi-
nition of recruitment for this data set, i.e., that which
leads to the least violation of model assumptions.
In our application the recruitment pattern was de-
rived from size classes 21 mm or less. If we use this
pattern at say 23.5 mm then we need to shift the pat-
tern slightly to later times. It is not apparent to what
degree we should shift the pattern; therefore we shall
estimate the degree of shift. We call this parameter
the lag. We expect the lag to increase with Z0. Also note
that the derived recruitment pattern is an average over
different size classes and hence it is an average over
different times. The absolute timing of the pattern is
Wang and Ellis: Maximum likelihood estimate of mortality and growth from multiple length-frequency data
385
A Female recruitment
cc 0 0-1
300-
250-
200-
150-
100-
50-
r
1986
1987
1988
1 989
1990
1991
D Male recruitment
1986
1987
1989
1990
1991
C Commercial fishing effort
_aJL
\
jK
1986
1987
1989
1990
1991
Date
Figure 2
(A) Quasiperiodic Isolid line) and aperiodic (dashed line) recruitment patterns for female tiger
prawns (Penaeus esculetus) in the study area; (B) quasiperiodic and aperiodic recruitment pat-
terns for female tiger prawns in the study area; (C) the weekly fishing effort pattern in the
study area.
therefore uncertain and so the lag parameter adopts the
role of estimating this uncertainty.
We do have sampling effort information, so that it
would be reasonable to consider incorporating into the
likelihood the Poisson term for the total catch as men-
tioned in section 3. Information on total catch per oc-
casion would improve estimates of mortality. However,
preliminary analysis found that there was a mismatch
of the expected total catch with the observed total
catch. Therefore, it appears to be unrealistic to assume
that the catch is proportional to the sampling effort.
In the subsequent data analysis we use the form of the
log-likelihood in Equation 11, which uses the shape of
the observed distribution and takes the total catch as
given.
We have estimated all the parameters k, lat, a,, M,
q, and the lag simultaneously (model 1). To achieve
a better understanding of the data, we also estimate
parameters for a range of fixed values of M (model 3).
This is common practice in the fisheries literature (e.g.
Sullivan, 1992). Estimates of q for corresponding values
of M can be useful in some contexts where the outcome
of an analysis is insensitive to the joint pairs (M, q)
(Somers and Wang, 1996). Taking the rough values
of Somers and Wang (1996) and Wang and Die (1996)
as a guide, we choose the values M=l, 2, and 3yr~1.
The utility of considering a range of values of M ap-
plies equally to considering a range of values for {k,
IJ. Somers and Kirkwood (1991), Wang et al. (1995)
and Wang (1998) have all reported estimates of ik, l^)
for this species, and we would like to incorporate this
information. However, it is well known that estimates
of the growth parameters are strongly correlated. We
therefore considered a range of feasible pairs (k. I , I,
and estimated the remaining parameters under model
2. The fixed values we used were, for males, (2, 39.3),
(3, 37.7), and (4, 36.1), and for females, (2, 53.1), (3,
47.4), and (4, 41.7). These values were obtained by a
386
Fishery Bulletin 103(2)
Table 2
Parameter estimates for tiger prawn
tPenaeus semisulcatus)
data. FKi) is
the estimated fishing
mortality in 1989. coi
(M,
FS9) is
the jackknifed correlation between M
and F89. The last column is the objective value per unit of effort.
With model 1
all
jaram-
eters are assumed to be unknown; with model 2 ik, I
. ) are assumed to be known
with model 3 M is assumed to be known.
Model
M
^89
Z
k
1,
CT*
cor(M, F89)
-21og
Males: quasiperiodic recruitment
1
4.1
2.3
5.2
9.3
33.4
4.5
-0.82
72.96
2
2.9
0.3
3.1
2
39.3
5.1
-0.78
74.43
2
3.7
0.6
3.9
3
37.7
4.3
-0.35
73.99
2
3.4
2.1
4.4
4
36.1
4.3
-0.25
73.60
3
1
2.2
2.0
5.3
32.3
4.8
—
73.05
3
2
1.9
2.9
6.7
32.5
4.8
—
73.03
3
3
0.0
3.0
7.6
32.3
4.8
—
73.15
Males: aperiodic recruitment
1
1.3
1.6
2.0
5.0
32.6
4.8
-0.67
72.91
2
2.8
0.4
3.0
2
39.3
5.8
-0.79
74.65
2
3.7
0.1
3.7
3
37.7
4.7
-0.81
74.31
2
3.5
0.5
3.7
4
36.1
4.5
-0.64
73.84
3
1
1.8
1.8
4.9
32.4
4.8
—
72.93
3
2
1.0
2.5
5.9
32.5
4.8
—
72.93
3
3
0.0
3.0
7.0
32.5
4.8
—
73.01
Females: quasiperiodic recruitment
1
4.2
1.7
5.0
5.6
42.2
7.1
-0.65
86.83
2
3.9
0.3
4.1
2
53.1
8.3
-0.83
87.94
2
4.0
0.7
4.3
3
47.4
6.9
-0.66
87.31
2
2.7
1.3
3.3
4
41.7
7.7
-0.71
86.91
3
1
2.6
2.2
4.1
38.8
8.3
—
87.10
3
2
1.8
2.8
4.4
39.9
7.9
—
86.92
3
3
1.6
3.7
5.1
40.7
7.5
—
86.87
Females: aperiodic recruitment
1
2.6
0.9
3.0
4.9
39.2
8.2
-0.67
86.90
2
3.9
0.1
4.0
2
53.1
13.5
-0.80
88.43
2
4.3
0.1
4.4
3
47.4
9.7
-0.70
87.88
2
3.0
0.8
3.4
4
41.7
8.1
-0.71
87.04
3
1
2.1
2.0
3.6
39.3
8.4
—
87.07
3
2
0.8
2.4
2.8
41.5
8.5
—
86.94
3
3
0.6
3.3
5.0
39.4
8.1
—
86.91
simple linear fit to the estimates in the three papers
mentioned above.
The estimates of M from model 1 appear more rea-
sonable for the aperiodic recruitment pattern. The cor-
relations between M and FR9 (the fishing mortality in
1989) are not as strong as in the simulation example.
This is encouraging and indicates that there may be
enough contrast in the effort pattern to separate fishing
mortality from natural mortality.
The estimates of lr, and a, for model 3 are not sensi-
tive to M. However /; and M are quite strongly related.
In the case of constant recruitment r(t) and mortality
z(t)=Z, it is well known that k and Z are perfectly cor-
related, and only their ratio Zlk is able to be estimated.
The separation of M and k therefore relies on there be-
ing adequate contrast in recruitment and effort.
For model 2 there is little difference between the two
recruitment models. The estimates of M show moderate
dependence on (k, I J, but without trend. These esti-
mates are generally somewhat higher than we expect
from prior studies. But for the natural mortality rate,
this is the first time we have obtained estimates of M,
which is larger than what we have assumed in previous
stock assessments, around 2.3 per year (Wang and Die,
1996). Estimates of Fm are too variable to be relied up-
on. All models agree reasonably on the a, parameter.
Our model assumes recruitment at a fixed length,
l0, which has to be chosen. In Figure 3 the parameter
estimates for fixed (k, l^J are plotted against lQ for the
quasiperiodic recruitment model. Parameter estimates
are consistent for given l0 provided that all model as-
sumptions are satisfied. However, when l0 is too small
Wang and Ellis: Maximum likelihood estimate of mortality and growth from multiple length-frequency data
387
Males
Females
N
24 26 20 22 24
Recruitment length (mm)
Figure 3
Parameter estimates against recruitment length l0 for real tiger prawn
{Pcnaeus esculetus) data using quasiperiodic recruitment under model 2.
The mean annual total mortality Z is equal to M+0.46F89, where Fg9 is
the fishing mortality in 1989.
or too large, there is bound to be a violation of those
assumptions, leading to high sensitivity of the estimates
to changes in /0. Therefore, we say the most reasonable
value for l0 is that for which the estimates are most
slowly varying in the immediate neighborhood of Zn.
On the basis of at, M and Z for males, /0=23.5 would
be a reasonable choice. We exclude q from consider-
ation because its standard deviation is comparable to
its magnitude (see Table 2). In addition we exclude
the lag because we expect it to increase approximately
monotonically with l0, as indeed it does. There is no
clear choice for females; therefore we choose /0=23.5,
the same as for males. This choice is consistent with
the consideration that l0 should be somewhere between
20 mm and 30 mm, but in the lower half of the range
so that more data can be included in the estimation
(because lengths must exceed /0I.
Also shown in Table 2 are jackknife estimates of
the standard deviations. The jackknifing is done by
dropping the length-frequency record from each occa-
sion in turn and re-estimating the parameters. From
the over-all estimate 6 and the jackknife estimate 0,
from dropping the itb occasion we obtain a pseudovalue
0-(n-l)6Jn, where in our case n=69. The jackknifed
standard deviation is simply the standard deviation of
these pseudovalues. We also show the jackknifed corre-
lation between M and q, which is simply the correlation
between the corresponding pseudovalues. In most cases
there is a large negative correlation.
The fishing mortality in 1989 (the year of peak ef-
fort), F89, is simply proportional to q with constant
of proportionality 2865, the number of boat-days of
effort in that year. The mean total annual mortality
Z is M+0.46Fg9 because the mean annual effort was
388
Fishery Bulletin 103(2)
1320 boat-days. The mostly high negative correlations
between M and F89 (equivalently, q) may explain why Z
tends to have a smaller standard deviation than either
M or F89. The results of Figure 3 can be regarded as a
sensitivity study on the effect of changing /0. The pur-
pose of this sensitivity study is not to estimate l0 but
rather to check that the model assumptions have not
been violated for the given l0.
The results are fairly similar for the two recruitment
models although there are differences: the quasiperi-
odic recruitment model gives larger Fm estimates and
smaller a* estimates. Our method assumes that the
recruitment pattern is known without error; therefore
the preferred recruitment pattern should be the one
with less error. Let us suppose that the true recruit-
ment pattern consists of a periodic pattern with random
variation both within years and between years. If the
within-year variation is sufficiently large in comparison
with the between-year variation, then the quasiperiodic
pattern should be used. On the other hand, if the be-
tween-year variation is large, then the aperiodic pattern
is preferred. Based on the objective values (-21og) in
Table 2, model 2 with quasiperiodic recruitment pat-
tern and fixed k at 4yr_1 appears to be the best model
for both males and females.
Figure 4 shows the 40 length-frequency records for
females with the largest total catch. Overlaid is the ex-
pected catch (given the total catch) from the model with
ik, lv.) fixed at (3, 47.4) for quasiperiodic recruitment
(solid line) and for aperiodic recruitment (dashed line).
Because the integral for the expected length distribu-
tion is singular in the neighbourhood of l0, the first few
size classes are omitted from the estimation; only data
with length above l0+2 are used in the estimation. The
fit is quite reasonable for most records. It is interest-
ing to compare the performance of the two recruitment
models. In early 1988, when recruitment occurred later
than usual (see Fig. 2), the aperiodic model tracks the
data more closely than the quasiperiodic model, espe-
cially in March. On the other hand, the quasiperiodic
model fits better in October 1990, whereas the aperiodic
model predicts higher abundance of small females be-
cause of a recuitment "blip" in September, which was
perhaps due to sampling variation.
Discussion
Methods such as McDonald and Pitcher's (1979),
ELEFAN (Pauly et al., 1981), and Sparre's (1987) oper-
ate on multiple length-frequency data and attempt to
identify cohorts in the frequency pattern. Essentially
they estimate the growth parameters by tracing cohorts
in time; then they estimate mortality by measuring the
evolution in abundance of a cohort. For mortality esti-
mation these methods need catch-per-unit-of-effort data.
Sparre's method bears some similarity to ours because
it attempts to fit the length distribution of a cohort to
a normal distribution whose variance is a parameter to
be estimated. Our method does not require separation
of cohorts because samples are assumed to come from a
length distribution which may be multimodal. Another
advantage of our method is that it is not necessary to
have information about sampling effort and thus may
greatly reduce the complexity of sampling. However, our
approach needs a known recruitment pattern.
In our application, recruitment was assumed to occur
at a fixed length, /0, which had to be chosen. We used
prior information to constrain l0 to lie somewhere be-
tween 20 mm and 30 mm. We then found the sensitivity
of the estimates to changes in l0 and chose a value that
reduced this sensitivity. This choice could be further
refined if more accurate constraints were available from
other sources. Alternatively, Wang and Somers (1996),
who also used /(l to account for continuous recruitment
in estimating growth parameters, have provided guide-
lines for choosing /0.
Deriso and Parma (1988) and Sullivan et al. (1990)
reported methods based on stochastic growth. Sullivan
(1992) also applied the Kalman filter approach for es-
timating population parameters. Their models differ
from ours in the way random variation is incorporated
in the growth model. In their models the length incre-
ment from one time step to the next follows a distribu-
tion whose mean is given by a fixed growth model. As
Wang and Thomas (1995) have demonstrated, this is
equivalent to assuming that the growth rate changes
randomly from time to time. In our model each indi-
vidual follows a deterministic growth curve whose Lx
parameter is chosen from a random distribution. An
individual with larger than average growth at one time
step will have above-average growth at subsequent time
steps. Perhaps further modeling effort could be directed
into combining these approaches.
DeLong et al. (2001) have reported a method for es-
timating density-dependent natural mortality and the
growth rate from length-frequency data for juvenile
winter flounder not subject to fishing mortality. Other
growth parameters (Lx and the variability of k) were
fixed by using information from other sources. Because
their data were recorded in the latter half of the year,
when recruitment was nearly complete, recruitment
was not a complicated issue. In contrast, we had the
challenge of a species that recruits all year round. The
degree of fit in DeLong et al.'s Figure 5 is comparable
to that in our Figure 4.
Our methods are based on distributional assumptions
that must be tested for robustness, because, in practice,
the /x distribution of real prawn populations will not
equal any of our mathematical distributions. We have
found that, even for our ideal model, akin to any other
existing model, biases occur for moderate to large co-
efficients of variation when violation of distributional
assumptions occurs.
Our model is motivated by the trawl data from the
tiger prawn fishery and relies on 1) known recruitment
pattern, 2) contrast in commercial fishing effort for
estimation of M and F simultaneously, and 3) contrast
in sampling times. Requirement 3 is to spread sam-
pling effort so that growth and mortality information
Wang and Ellis: Maximum likelihood estimate of mortality and growth from multiple length-frequency data
389
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Fishery Bulletin 103(2)
are in the data. We fitted a variety of different models.
The objective function -21og( likelihood) values in Table
2 should be used only as guidelines and should not
drive the analysis or be used for model selection. Tiger
prawns are subject to very high total mortality and
hence are short-lived species. Our method is also ap-
plicable to longer-lived species. However, for application
to other fisheries, some modification of the model may
be necessary to incorporate relevant information in the
model. Simulation studies may have to be carried out
to see how reliable the modified version is for param-
eter estimation because many factors, such as growth
rate and commercial effort patterns, will determine if
parameter estimates can be found or how reliable they
are if they can be found.
We aim to obtain growth and mortality parameter
estimates simultaneously. However, this may be too
ambitious, especially for short-lived species unless
other information can be incorporated to assist esti-
mation. For instance, Ebert (1973) found estimation
of even two parameters (natural and fishing mortal-
ity) unreliable and had to assume one of them. This
is perhaps why natural mortality is assumed to be
known in traditional cohort analysis. Also Askland's
method (1994), one of the most recent cohort-analysis
methods, requires a known M. Nevertheless, in prac-
tice, ik, l.,) may be estimated from different types of
data. The results based on model 2 (assuming {k, l^)
are known) indicate that both M and F can then be
estimated more reliably when there is substantial
contrast in the effort pattern. Another assumption
is that catchability does not change over time. This
may not be necessarily true when new technology is
introduced into the fishery (Bishop et al., 2000). The
assumption that growth parameters are known greatly
reduces the complexity of estimating the remaining
unknown parameters and improves the performance
of the proposed methods.
We have chosen to allow only lm to be random because,
unlike tag-recapture data, the length-frequency data do
not have multiple measures from each individual. Each
individual is measured only once. Therefore, it might be
problematic to allow random K and correlation between
K and L^. Such an attempt using length-frequency
data may lead to misleading conclusions because the
conclusion will be model-driven instead of data-driven.
Parameter estimates obtained by fixing M as a constant
are deemed more reliable.
We provided a framework for length-frequency da-
ta analysis that incorporates continuous recruitment,
selectivity, and time-dependent fishing mortality. We
have also provided guidelines for how to compute the
likelihood function, which depends on rather delicate
integrals. Such a model would be very useful for many
fisheries because such unified models are not available
in the literature. Our work provides a sensible case
study. Application of our method may require incorpora-
tion of specific information in a fishery. We believe our
model, which generalizes the traditional model and is
somewhat complicated, has provided us with some use-
ful results for future stock assessment and evaluation
of management strategies.
Acknowledgments
This research project was partly supported by the Fisher-
ies Research and Development Corporation of Australia.
We gratefully acknowledge the helpful suggestions and
comments of David Die, Andre Punt, Neil Loneragan,
and two anonymous referees.
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392
Abstract— Fisheries often target indi-
viduals based on size. Size-selective
fishing can create selection differen-
tials on life-history traits and, when
those traits have a genetic basis, may
cause evolution. The evolution of life-
history traits affects potential yield
and sustainability of fishing, and it is
therefore an issue for fishery manage-
ment. Yet fishery managers usually
disregard the possibility of evolution,
because little guidance is available to
predict evolutionary consequences of
management strategies. We attempt,
to provide some generic guidance. We
develop an individual-based model of
a population with overlapping genera-
tions and continuous reproduction.
We simulate model populations under
size-selective fishing to generate and
quantify selection differentials on
growth. The analysis comprises a
variety of common life-history and
fishery characteristics: variability
in growth, correlation between von
Bertalanffy growth parameters (K
andL,.), maturity rate, natural mor-
tality rate (M), M/K ratio, duration
of spawning season, fishing mortality
rate (F), maximum size limit, slope of
selectivity curve, age at 50% selectiv-
ity, and duration of fishing season.
We found that each characteristic
affected the magnitude of selection
differentials. The most vulnerable
stocks were those with a short spawn-
ing or fishing season. Under almost
all life-history and fishery character-
istics examined, selection differentials
created by realistic fishing mortality
rates are considerable.
Effects of fishing on growth traits:
a simulation analysis
Erik H. Williams
Kyle W. Shertzer
Center for Coastal Fisheries and Habitat Research
101 Pivers Island Road
Beaufort, North Carolina 28516
E-mail address EnkWilliams@noaa.gov
Manscript submitted 16 April 2004
to the Scientific Editor's Office.
Manuscript approved for publication
20 December 2004 by the Scientific Editor.
Fish. Bull. 103:392-403 (20051.
Fishing is typically size selective.
It almost always targets the larger
individuals of a population and can
thus shift the spawning stock towards
smaller, slower-growing individuals. If
somatic growth has some genetic basis,
size-selective fishing may cause evolu-
tion toward a smaller size-at-age.
Changes in somatic growth are
well documented in field data, and
several studies implicate fishing
(Ricker, 1981; Harris and McGovern,
1997; Haugen and Vollestad, 2001;
Sinclair et al., 2002). However, with
typical field data, it is difficult to rule
out other explanations. Changes in
growth could result from fluctuations
in population density or the environ-
ment. Furthermore, they may not be
evolutionary, but instead expressions
of phenotypic variability. Because of
such possibilities, the idea that fish-
ing can cause evolution has often
been accepted because of compelling
theoretical arguments, rather than
on empirical support. However, the
laboratory experiments of Conover
and Munch (2002) demonstrated that
size selection can cause evolution of
growth traits. More and more, fish-
ing-induced evolution is considered
not just possible, but prevalent (Law,
2000; Stockwell et al., 20031.
The evolution of growth traits, de-
spite wide acknowledgement of the
potential for evolution of these traits,
is usually a low priority in fishery
management. However, it raises at
least four management concerns.
First, any reduction in growth rate
or maximum size can decrease rec-
reational and economic value (Miller
and Kapuscinski, 1994). Second, size
selection could reduce genetic vari-
ability (Falconer and Mackay, 1996).
unpredictably altering correlated
traits and population fitness. Third,
evolution may not easily be reversed,
even with after-the-fact management.
Fourth, the evolution of growth and
other life-history traits can modify
population dynamics (Bronikowski et
al., 2002; Shertzer and Ellner, 2002)
and therefore potential yield (Edley
and Law, 1988; Heino 1998). Evolu-
tion in fishes can be rapid (Reznick et
al., 1997; Hendry et al., 2000; Quinn
et al., 2001), so that evolutionary,
population, and fishery dynamics oc-
cur on similar time-scales (Sinervo
et al., 2000; Shertzer et al., 2002;
Yoshida et al., 2003). These dynam-
ics imply that evolution matters for
fishery management on the time-scale
of years or decades.
For fishing to cause evolution, two
conditions must be met. There must
be a selection differential on a pheno-
typic trait and a genetic basis must
exist for the trait's expression (i.e.,
the trait must be heritable). Selec-
tion differential is defined as the dif-
ference in the mean phenotypic trait
value of parents before and after se-
lection (e.g., size-selective fishing).
Stokes and Law (2000) argued that,
under exploitation levels in many of
today's fisheries, "selection differ-
entials on body size should be sub-
stantial and measurable." Even so,
attempts to estimate selection differ-
entials of actual fish stocks have been
rare (but see Law and Rowell, 1993;
Miller and Kapuscinski, 1994). This
lack of estimates is surprising, given
that the data needed are often avail-
able, as noted by Law (2001).
The second necessary condition, her-
itability, is defined as the proportion
of phenotypic variability in offspring
Williams and Shertzer: Effects of fishing on growth traits: a simulation analysis
393
that is due to the genotypes of the parents. It
can range from zero to one, with a higher value
potentially speeding the evolutionary response
to selection. Field estimates of heritability in
fish size are uncommon because in nature it is
difficult (although not impossible; McAllister
et al., 1992) to separate genetic and environ-
mental effects on phenotypes. Almost all esti-
mates come from laboratory experiments (e.g.,
Hadley et al., 1991; Conover and Munch, 2002;
Vandeputte et al., 2002), mostly on populations
from aquaculture breeding programs (e.g., Gje-
drem, 1983; Jarayabhand and Thavornyutikarn,
1995; Henryon et al., 2002). One might expect
laboratory experiments to over-estimate natural
heritabilities, because experiments tend to re-
duce environmental effects on total phenotypic
variance, but estimates from the laboratory
have been similar to those from the field (Wei-
gensberg and Roff, 1996). The laboratory exper-
iments indicate that heritabilities in fish growth
traits may vary widely among populations but Repeat
are high enough to allow rapid evolution, given over
a large enough selection differential. time
Models of evolutionary response to selec- steps (t)
tive harvest have usually taken one of two for one
approaches: quantitative genetics (e.g., Law, year
1991; Ratner and Lande, 2001) or life-history
optimization (e.g., Blythe and Stokes, 1999). In
the present study, we take a different approach.
Rather than attempt to predict evolution ex-
plicitly, we focus on selection differentials, a
necessary (but not sufficient) condition for an
evolutionary response.
We use simulation analyses to compute selec-
tion differentials caused by fishing. The simula-
tion model is one common in fisheries. It con-
sists of an age-structured population following
von Bertalanffy growth, with fishing and repro-
duction modeled as continuous processes.
Our goal is to compare selection differentials
across a variety of life-history and fishery char-
acteristics. We quantify selection differentials
on growth parameters and body size. If growth
traits are heritable, those life-history and fish-
ery characteristics with the largest selection
differentials are most likely to generate an evo-
lutionary response. Armed with such knowl-
edge, fishery managers can weigh potential evolutionary
effects when choosing a fishing strategy.
Draw uniform random number to determine cohort of
individual; probabilities based on stable age structure
Draw bivanate normal random numbers to determine
values of growth parameters L , K
Draw uniform random number to determine spawning
time step
Unfished population
Fished population
Draw uniform random number to determine
mortality
Alive?
Alive?
t = spawning
time step7
: = spawning
time step?
Draw uniform random
number to determine if
spawning occurred
Draw uniform random
number to determine
if spawning occurred
Store growth
parameters
Store growth
parameters
Figure 1
Flow diagram of the individual-based model. 250,000 individu-
als were initialized and then duplicated; one copy entered an
unfished population, the other entered a fished population. Both
populations were simulated for a single year with monthly time
steps. Selection differentials on the growth parameters were
computed as the difference between mean trait values of the
unfished and fished parents.
Materials and methods
To compute selection differentials caused by size-selective
fishing we used an individual-based model (Fig. 1). To
initialize the model, 250,000 individual phenotypes were
generated. Each was assigned a set of life-history param-
eters and then duplicated. One copy entered an unfished
population that experienced only natural mortality; the
other copy entered a fished population that experienced
both natural and fishing mortality. Growth, survival, and
reproductive success of individuals were simulated with
monthly time steps for a single year. At the end of the
simulation, selection differentials on growth parameters
were computed as the percent change between the mean
values of spawners in the two populations.
Model structure
The model comprised three basic life-history functions:
growth, survival, and reproduction. For each individual.
394
Fishery Bulletin 103(2)
size was assumed a function of age (a) and followed the
von Bertalanffy model,
Ha)
LJl-e-^-V],
(1)
where /(a)=the length-at-age of an individual;
Lr = the theoretical maximum length;
K =the growth rate, and
t0 =the theoretical age when size would have
been zero.
In our study, each individual's age and size were updated
at each monthly time step.
Survival was computed differently for the two popula-
tions. In the unfished population, individuals survived
with a probability depending only on the natural mor-
tality rate (M/yr). In the fished population, individuals
survived with a probability depending on both the natu-
ral mortality rate and the size-specific fishing mortality
rate. Size selectivity [s(/)] by the fishery increased with
length according to the logistic equation
s(l)-
1 + e
■Psu-l,)
(2)
where /3S = the slope of the selectivity curve; and
Ls = the length at 50% selectivity.
The function s(l) describes the proportion of the fully-
selected fishing mortality rate IF) experienced by indi-
viduals of length /. The size-specific fishing mortality
rate, therefore, is s(l)F per year. Fishing was applied
over a fishing season of duration DF.
The probability of reproduction was assumed equal to
the probability of maturity [m(a)\. In the model, matu-
rity increases with age and is independent of length. Al-
though maturity likely relates to length through bioen-
ergetics, the relationship was not modeled here because
it is, in general, poorly understood. Like selectivity (Eq.
2), m(a) was modeled by a logistic equation, but with a
slope parameter, )3m, and age at 50% maturity, Am.
In nature, values of life-history parameters K and Am
are related to a stock's natural mortality rate. A higher
natural mortality rate reduces the expected lifespan
and consequently tends to be associated with a higher
growth rate (K) and a younger age at maturity (Am).
In the simulation, K and Am were related to natural
mortality by life-history invariants (detailed later).
Life-history invariants have a strong theoretical and
empirical basis (Roff, 1984; Beverton, 1992; Charnov,
1993) and have been valuable in other fishery applica-
tions (Mangel, 1996; Charnov and Skuladottir, 2000;
Frisk et al., 2001; Williams and Shertzer, 2003).
Simulation
To initialize the simulation, individuals were assigned
at random to a cohort. The number of cohorts was deter-
mined as the age at which approximately 1% of the
population would be expected to remain under natural
mortality [-ln(0.01)/M, rounded to the nearest integer].
Probabilities of cohort membership decayed exponen-
tially with age according to M; the probability of the
oldest cohort was adjusted to include the remaining
fraction offish (i.e., a plus group). The probabilities were
scaled to sum to one, and a uniform random number was
drawn to determine an individual's cohort.
Next, individuals were assigned parameter values for
von Bertalanffy growth. The value of t0 was fixed at 0.5
yr. Values of Lx and K were chosen uniquely for each in-
dividual. Following Xiao (1994), Lx and if were assumed
to follow a bivariate normal distribution with standard
deviations aL and aA-, respectively, and correlation p.
Finally, individuals were assigned a time step (month)
within the year to attempt spawning. The time step
was chosen from months distributed uniformly over a
spawning season of duration, Z)s.
Once assigned parameter values, each individual was
duplicated. One copy entered the unfished population,
the other the fished population. The populations were
simulated in parallel over a single model year.
The simulation iterated each individual through
monthly time steps. At each step, the simulation com-
puted growth and checked for survival and reproduc-
tion. In the unfished population, the monthly probability
of survival was exp(-M/12). In the fished population,
the monthly probability of survival during the fishing
season depended on natural mortality and on the size-
specific fishing mortality. For simplicity, we assumed
size within a month was fixed so that that the prob-
ability of survival was exp[(-M/12-s(/0)F)/DF], where l0
was an individual's size at the beginning of the month.
Outside the fishing season, only natural mortality ap-
plied. To check for survival, a uniform random number
was drawn and compared to the survival probability
appropriate for the population.
Each individual surviving to its assigned spawning
time had the opportunity to reproduce. In that case, a
uniform random number was drawn and compared to
the probability of reproduction. If reproduction was suc-
cessful, the individual's growth parameters went into a
pool of parents used to compute selection differentials.
Growth parameters Lx and K jointly determine size-
at-age, and it is on these parameters that we describe
selection differentials. At the end of the simulation year,
we computed a selection differential on each growth
parameter as the percent difference between mean trait
values (Lr or K) of the unfished and fished parents.
Based on the differences in Lx and K, we also computed
upper and lower bounds of selection differentials on
size-at-age. The bounds occur where age approaches t0
or oc. Because each population consisted of the same set
of individuals at the beginning of the year, any differ-
ence in growth traits between parents at the end of the
year could be attributed solely to fishing.
Base model and variations
We began with a base model built on parameter values
chosen or computed to represent common life-history and
Williams and Shertzer: Effects of fishing on growth traits: a simulation analysis
395
Table 1
Parameter
values used in the base model. Formulas for the growth
rate (A'l and the age at 50% matu
-ity (A„
) are life-history
invar
lant relationships from Charnov ( 1993 ) and Beverton ( 1992 )
, respectively. The formula forLq is
the
length
it age Am accord-
ing to
von
Bertalanffy growth. A value of °° for slope parameters
corresponds to
a knife-edge curve.
Parameter
Description
Formula
Value
M
Natural mortality rate (per year)
Fixed
0.2
F
Fishing mortality rate (per year)
Fixed
Oto 10
£»
Mean asymptotic size in growth function
Fixed
1000
K
Mean growth rate in growth function
M/1.65
0.12
t0
Location parameter in growth function
Fixed
-0.5
cvL
Coefficient of variation in hr
Fixed
20%
cvA.
Coefficient of variation in A'
Fixed
20%
p
Correlation between L, and K
Fixed
0
ft
Slope of the size selectivity curve
Fixed
00
ft,
Slope of the maturity curve
Fixed
■x.
K
Age at 50% maturity
log[(3 A + M)/M]
IK
8.55
k
Length at 50% selectivity
L.[l-exp(-X[Am
-to
')]
666
Ds
Duration of spawning season (yr)
Fixed
1
DF
Duration of fishing season (yr)
Fixed
1
fishery characteristics (Table 1). We then conducted a
variety of sensitivity analyses.
In the base model, the natural mortality rate (M) was
set at 0.2/yr, a value common for many fish species.
Sensitivity analyses used M = 0.1, 0.4, or 0.8. The value
of M affects the values of A', Am, and Ls, according to
the life-history invariant relationships (Table 1). The
relationship between M and K is often referred to as the
M/K ratio. Charnov (1993) suggested a central value for
fishes of M/A"=1.65, which we used in the base model.
Beverton (1992) examined the M/K ratio for fishes and
found a range of 0.5 to 2.5. We used this range in our
sensitivity analyses to examine the effect of the M/K
ratio on selection differentials (Table 2).
The base model treated Lx and K as independent
variables (p=0. Table 1). Often these parameters are
correlated. A meta-analysis by He and Stewart (2001)
of 235 fish populations indicated a correlation value of
-0.28. The negative correlation could be expected from
a trade-off between growth rate (represented by A'l
and maximum size (represented by Lx), as has been
suggested in studies of bioenergetics (Stearns, 1992;
Hutchings, 1993; Mangel, 1996). Our sensitivity analy-
ses considered negative values of correlation that range
from -0.25 to -1.
With the base model, selectivity and maturity were
assumed to be "knife-edge," a functional form often used
in fisheries for convenience. Also, in the base model the
size at 50% selectivity (Ls) was assumed to occur at an
age equal to the age at 50% maturity (Am). Although
these fishery characteristics are common, selectivity
and maturity may not be knife-edge or coincide. In
sensitivity analyses, we examined different shapes of
selectivity and maturity curves (Fig. 2). We also ex-
amined the affect of shifting the age at 50% selectivity
from -2 to 2, in relation to the base case. This shift
corresponds to a range in Ls values from 574 to 738.
For simplicity, we held F constant for these sensitivity
analyses, implying constant effort but resulting in dif-
ferent amounts of removals.
Under logistic selectivity, the oldest, largest fish
receive the highest rate of exploitation. Yet often the
largest fish are unavailable to a fishery because of mi-
gration patterns or regulations (e.g., a maximum size
limit). Thus our sensitivity analyses included a cap on
susceptible sizes. The cap was set at 70, 80, or 907c of
Using the base model, we examined the effects of an-
nual fishing mortality rate over values that range from
F=0 to F=10/yr, which is 0 to 50 times the natural mor-
tality rate. Fishing mortality was applied continuously
throughout the year (i.e., DF=1). In sensitivity analyses,
we examined shorter fishing seasons ranging from one
to six months. The F was still an annual rate but was
applied over fewer months and adjusted so that the
number of fish removed was the same as when DF=1.
For seasons shorter than a full year, fishing was as-
sumed to occur at the beginning of the year.
Like the fishing season, the duration of the spawn-
ing season was a full year in the base model (Ds=l).
396
Fishery Bulletin 103(2)
Table 2
Percent selection differential on the von Bertalanffy growth coefficient (A") at fishing mortality = 0.8/yr. Columns correspond to
the levels of the coefficient of variation (CV=0%, 10%, 20%) in A' and in the asymptotic length (L„). Any combination with 0% CV
in A is not presented because it results in zero selection differential. The first row corresponds to the base model and subsequent
rows correspond to changes in the base model: correlation between L , and K(p), slope of maturity curve (ft,), natural mortality
(M), M/K ratio, duration of annual spawning season (Ds), maximum size limit (Lu), slope of selectivity curve (/} ), change in age
at 50% selectivity (A J in relation to the base case, and duration of annual fishing season lDF).
Parameter values
L„:0%CV
L/. 10%CV
L,_
: 20%CV
L„
: 0%CV
LX:W%CV
L„: 20%CV
A: 10% CV
A: 10%CV
A
10%CV
A:
20% CV
A:20%CV
A: 20%CV
Base
0.7
0.5
0.3
2.1
1.7
1.2
P = -1
0.7
-0.7
-1.3
2.1
0.2
-2.3
p = -0.75
0.7
-0.3
-0.8
2.1
0.8
-0.9
p = -0.5
0.7
0.0
-0.4
2.1
1.1
0.1
p=-0.25
0.7
0.3
0.0
2.1
1.4
0.6
Pm = 0.25
0.2
0.2
0.1
0.7
0.7
0.6
ft, = 0.5
0.3
0.3
0.2
1.1
1.1
0.9
l\„ = 1
0.5
0.4
0.3
1.7
1.4
1.1
M = 0.1
0.4
0.4
0.3
1.6
1.5
1.2
M = 0.4
0.7
0.4
0.3
2.0
1.5
1.0
M = 0.8
0.6
0.3
0.2
1.6
1.1
0.7
M/A=0.5
0.6
0.3
0.1
1.9
1.0
0.6
M/K= 1
0.4
0.3
0.2
1.5
1.3
0.8
M/A=2
0.5
0.4
0.3
1.9
1.6
1.2
M/A=2.5
0.8
0.6
0.4
2.4
2.1
1.5
Ds= 1/12
1.6
1.0
0.6
4.5
3.6
2.3
Ds=3/12
1.4
0.9
0.5
4.1
3.3
2.2
Ds = 6/12
1.1
0.8
0.5
3.3
2.7
1.8
L„ = 700
0.0
0.0
0.0
-0.1
-0.1
0.0
Lu = 800
0.2
0.0
0.0
0.3
0.2
0.0
Lu = 900
0.4
0.2
0.1
1.1
0.8
0.3
ft = 0.01
0.3
0.2
0.2
1.1
1.0
0.8
ft = 0.05
0.6
0.4
0.3
1.9
1.6
1.2
ft = 0.1
0.6
0.5
0.3
2.0
1.7
1.2
As = -2
0.1
0.2
0.2
1.1
1.2
1.0
A, = -1
0.4
0.4
0.3
1.7
1.6
1.1
A, = l
0.6
0.5
0.3
2.1
1.7
1.2
As = 2
0.5
0.4
0.3
1.9
1.6
1.1
£>F= 1/12
1.5
1.0
0.6
4.3
3.5
2.3
DF = 3/12
1.3
0.9
0.6
3.9
3.1
2.1
£>,, = 6/12
1.2
0.7
0.5
3.3
2.6
1.8
In sensitivity analyses, the spawning season ranged
from one to six months and was assumed to occur at
the end of the year.
A selection differential cannot exist without phe-
notypic variation. The base model assumed a coeffi-
cient of variation (CV) of 20% in both L^ and K. For
sensitivity analyses, combinations of 09c , 10%, and
20% CV in Lx and K were examined for the influ-
ence of growth variability on selection differentials
of L and K.
Results
Changes in growth parameters L, and K affect size-at-
age jointly, resulting in non-uniform selection differ-
entials across ages (Fig. 3). The selection differentials
on size are bounded by the differentials at the extreme
ages, t0 and ». At the youngest age, the selection dif-
ferential on size is limited by the sum of the selection
differentials on L r and K plus their product. (At age t0,
the selection differential on size is undefined.) As age
Williams and Shertzer: Effects of fishing on growth traits: a simulation analysis
397
10
0.8
06
0 4
0.2
0.0'
10
Age
o
1.0-
B
—7y —
if
, - '
08-
I
0.6-
•
0.4-
/
0.2-
i
i
o.o-
j i
200 400 600 800
Length
1000
Figure 2
Effect of the slope parameter on (A) the prob-
ability of maturity and (B) the probability of
selection. (A) Maturity slope parameter /3m = 0.25
(light dash), /i„, = 0.5 (light solid!, ft,, = 1.0 (heavy
dash), and Pm=°° (heavy solid). (B) Selectivity
slope parameter /3S = 0.01 (light dash). /3S = 0.05
(light solid), /3S = 0.1 (heavy dashl, and /3S = ^
(heavv solid).
increases, the selection differential on size increases
or decreases monotonically toward an asymptote, the
selection differential on Lx. Thus selection differentials
on size across all ages are bounded by those at L _, + K
+ Lx K and Lx. The selection differential on the small-
est fish (age approaching t0) is an upper bound when
the selection differential on K is positive, and a lower
bound when negative. These properties are important
for interpreting how selection differentials on size-at-age
correspond to differentials on Lx and K.
Using the base model, we computed selection differen-
tials on Lx and K as functions of fishing mortality, over
the range F=Q to F=10/yr. The selection differentials
increased with F nonlinearly, resulting in a concave
relationship (Fig. 4). However for F<2.0, the relation-
ship is nearly linear.
The alternative models also revealed linear relation-
ships between selection differentials and F, for F<2.0
(figures not shown). In addition, those relationships
have a zero intercept (by definition, no fishing, no selec-
tion differential). Because the relationships are (nearly)
linear and have a common intercept, the rank of selec-
1000
800
£ 600
400
200
~i 1 1 r~
5 10 15 20
B
o -
Ni
8 -
■-.
6 -
*•-._
V.
4 -
**
~
2 -
"* ..
0 -
I I I I I
0 5 10 15 20
Age
Figure 3
Hypothetical changes in
length, given changes in
growth parameters. (Ai
Growth trajectories in the
base model (solid), a 59c de-
crease in growth parameter
K (dash), a 5r/r decrease in
growth parameter L ^ (dot),
and bc/< decrease in both
parameters (dash-dot). (B)
The corresponding reductions
in length are relative to the
base model.
tion differentials among models does not change across
values of F. A model that bears the highest selection dif-
ferential at F=0.2 does so at F=2.0. We therefore present
results of sensitivity analyses for a single value of F
(F=0.8/yr), with the understanding that for other values
of F (up to 2.0), magnitudes of selection differentials can
be inferred and ranks among models are maintained.
Increased variation in Lx and K tended to increase
the selection differentials, and interaction between the
two growth parameters (Tables 2 and 3). Selection dif-
ferentials on Lx were generally larger than those on K.
In the base model, the largest selection differential on
each growth parameter occurred when variation in the
focal parameter was highest and variation in the other
parameter was zero. The selection differentials on size-
at-age were largest when variation in both parameters
was highest (20% CV for both Lx and K).
398
Fishery Bulletin 103(2)
Life-history parameters
The correlation (p) between L A and K was assumed to
be zero in the base model and negative in sensitivity
analyses. The effect of correlation depended on variation
in the growth parameters. When the CV was zero for
either parameter, correlation had no effect on selection
differentials (Tables 2 and 3). When the CV was posi-
tive for both, a negative correlation decreased selection
differentials in relation to those from the base model
(Tables 2 and 3). For decreased values of the correlation
coefficient (i.e., stronger negative correlation), the per-
cent selection differentials on K decreased, whereas the
percent selection differentials on Lx either decreased or
remained constant. The percent selection differentials on
the size near age t0 ranged from 3.7% to -0.1% for values
of p from 0 to -1. The percent selection differentials on
Lx remained relatively constant, ranging from 2.1% to
2.5%, with the highest at p=0 (Fig. 5).
Knife-edge maturity (/3m = oc) resulted in larger selec-
tion differentials than did other maturity curves (Tables
2 and 3 1. As the slope of the maturity curve became more
gradual, the selection differentials decreased. For /3m
values greater than 1, the selection differentials on size
were similar to those of the knife-edge case (Fig. 5).
The effect of M on selection differentials was relative-
ly small (Tables 2 and 3). Changes in M from 0.1 to 0.8
led to small changes in selection differentials (Fig. 5).
The largest selection differentials tended to occur near
intermediate values of M (Tables 2 and 3, Fig. 5). This
nonlinear response in the selection differentials is not
surprising because changes in M affected the values of
K, Am, and maximum age nonlinearly (Table 1).
Changes in the M/K ratio did not reveal a clear trend
(Tables 2 and 3, Fig. 5). As with M, the M/K ratio af-
fects other parameters; therefore changes in M/K could
be expected to produce a nonlinear response in the
selection differentials. The percent selection differen-
tial on Lx was lowest at an intermediate value of Ml
K-2 (Table 3). The percent selection differentials on K
showed no consistent trend (Table 2). For M/K values
from 0.5 to 2.5, the selection differentials on size across
ages ranged from 2.3% to 4.0% (Fig. 5).
Decreases in the spawning season duration (Z)s)
caused a near linear increase in the selection differen-
tials (Tables 2 and 3, Fig. 5). A compressed spawning
duration of one month resulted in a range of 5.0% to
7.4% selection differential on size across ages (Fig. 5).
Of all the life-history parameters examined in this
analysis, spawning duration had the greatest effect.
Fishery parameters
A limit (Lu) on sizes susceptible to the fishery decreased
the selection differentials (Tables 2 and 3, Fig. 5). The
percent selection differential at all ages was zero for
Lu = 800 and -0.1% for Lu = 700 (Fig. 5). In these analy-
ses, F was held constant. Consequently, smaller values
of Lu correspond to fewer fish removed. An alternative
approach would have been to maintain constant catch
0 2 4 6
Fishing motality (per year)
Figure 4
Selection differentials on growth parameters
(A) K and (B) Lml computed as functions of
fishing mortality. Parameter values are the
same as those in the base model.
by increasing F, which would have led to selection dif-
ferentials larger than those in Tables 2 and 3.
Knife-edge selectivity (jis = x) caused larger selec-
tion differentials than did selectivity curves with more
gradual slopes (Tables 2 and 3). For )3S greater than
0.1, the selection differential rapidly converged to that
of the knife-edge case (Fig. 5). As with Lu, F was held
constant across /3S sensitivity analyses.
A change in the ages of fishery selectivity had little
effect on selection differentials (Tables 2 and 3, Fig.
5). When selectivity was set to a larger age or size, the
selection differential decreased slightly. In this case,
selectivity was occurring after maturity, allowing more
fish to reproduce before reaching sizes selected by the
fishery. However if harvest had been held constant in-
stead of F, the selection differentials would have been
larger. When selectivity was set to a smaller age or size,
the selection differential decreased slightly or remained
constant. This result is due to a reduction in the time
exposed to differential fishing mortality. Differential
fishing mortality occurs only on the sizes where se-
lectivity is less than one; otherwise fishing mortality
is constant for all individuals. Under von Bertalanffy
growth, younger fish grow more quickly. A decrease
in the age or size of selectivity shifts the fishing pres-
sure to ages with quicker growth, reducing the time
Williams and Shertzer: Effects of fishing on growth traits: a simulation analysis
399
Table 3
Percent selection differential on the von Bertal
anffy
asymptotic length (Lr ) at fishing mortality =
).8/yr. Columns correspond to
the levels of the coefficient of variation (CV=09i
,10%
,20%
) inL, and
in the gro
»vth coefficient (K).
Any combination with 0% CV
in t, is not presented because
it results in zero
selection differential.
The first row corresponds
to the base mo
del and subsequent
rows correspond to changes in
the base model:
correlation between L
, and Kip
. slope of maturity
curve (ft,
, natural mortality
(M),M/K ratio
duration of annual spawning season
(Ds),
maximum
size limit CL ), slope of selectivity curve
(ft), change in age
at 50% selectivity (As) in relation to the base case, and duration of annual fishing season (DF).
Parameter values
L„:0%CV
L„: 10%CV
L,
: 20%CV
L„
: 0%>CV
L
j:io%cv
L,:20%CV
K: 10%CV
K: 10%CV
K
10%CV
K:
20% CV
K
20%CV
K. 20%CV
Base
1.0
2.7
0.9
2.7
0.8
2.5
P = -1
1.0
2.8
0.7
2.7
-0.1
2.3
p = -0.75
1.0
2.7
0.7
2.6
0.2
2.2
p= -0.5
1.0
2.8
0.8
2.7
0.4
2.3
p = -0.25
1.0
2.8
0.9
2.7
0.6
2.4
Pm = °'25
0.3
1.2
0.3
1.1
0.3
1.1
ft, = 0-5
0.5
1.8
0.5
1.8
0.5
1.7
ft,= l
0.8
2.4
0.7
2.4
0.7
2.2
M = 0.1
0.8
2.6
0.7
2.5
0.7
2.4
M = 0.4
1.0
2.8
1.0
2.7
0.8
2.6
M = 0.8
1.0
2.6
1.0
2.6
0.8
2.4
MIK = 0.5
1.4
3.2
1.4
3.2
1.3
3.1
MIK= 1
0.9
2.7
0.9
2.7
0.8
2.5
MIK =2
0.9
2.5
0.8
2.5
0.7
2.3
M/X = 2.5
1.1
2.8
1.0
2.7
0.8
2.5
Ds= 1/12
2.2
5.6
2.0
5.5
1.7
5.0
Ds = 3/12
2.0
5.1
1.8
5.0
1.5
4.6
Ds = 6/12
1.6
4.4
1.5
4.3
1.3
3.9
Lu = 700
-0.1
-0.1
-0.1
-0.1
-0.1
-0.1
L„ = 800
0.0
-0.1
0.0
-0.1
-0.1
-0.1
Lu = 900
0.3
0.5
0.2
0.5
0.1
0.4
ft = 0.01
0.5
1.9
0.5
1.9
0.5
1.8
ft = 0.05
0.9
2.7
0.9
2.6
0.8
2.5
ft = O-1
1.0
2.7
0.9
2.7
0.8
2.5
As = -2
0.4
2.1
0.4
2.1
0.4
2.1
As = -1
0.7
2.5
0.7
2.5
0.7
2.4
A8=l
1.0
2.8
1.0
2.7
0.9
2.5
A, = 2
1.0
2.7
0.9
2.6
0.8
2.4
DF= 1/12
2.2
5.5
2.0
5.3
1.6
4.8
£>f = 3/12
1.9
4.9
1.7
4.8
1.5
4.4
DF = 6/12
1.6
4.2
1.5
4.1
1.2
3.7
individuals experience differential fishing pressure and
therefore the potential for selection differentials. If har-
vest had been held constant instead of F, the selection
differentials would have been larger.
The fishing season duration (DF) affected selection
differentials in ways similar to the spawning season
duration (Tables 2 and 3, Fig. 5). A fishing season of
one month resulted in an upper bound of selection dif-
ferentials that ranged from 4.8% to 7.3% over all ages
(Fig. 5). Of all the fishery parameters examined in this
analysis, a concentrated fishing season resulted in the
largest selection differentials.
Discussion
The individual-based simulation approach used here
simplifies computation of selection differentials and
400
Fishery Bulletin 103(2)
A
B
c
6-
6-
6-
4-
2-
O o- -^ Q^-O • 2.
o
o ■ -//— 4"
O
o-» 0— _____
— o
0-
rT 0-
0-
.0 -0.6 -0.2 0 2 4 6 °° 0.1 0.3 0.5 0.7
P An M
D E F
6-
O
I 4'
cu
j5 2-
6-
--o--- •-.Q---0 2_
^O 6-
°- -ex \.
-O.^ \. 4-
"*• 2-
•
D
0-
0-
0-
„ n— 8'
15 1.0 1.5 2.0 2.5 02 0.4 0.6 0.8 1.0 700 800 900 1000
M/K Ds Lu
G H I
0
6-
6-
6-
o
4-
oo— —H— • 4"
o_o— — °— o 4"
o---o---»---o---o 2.
2-
q»-- -•//--•„
O 2-
- -•
0-
0-
0-
0.0 02 0.4 0.6 0.8 °° -2 -1 0 1 2 02 0.4 0.6 0.8 1.0
A ^s DF
Figure 5
Upper and lower bounds of selection differentials on size across all ages. Solid line
represents selection differential on the size near age f0; dashed line represents selec-
tion differential on Ly. (A) correlation between L, and K (p); (B) slope of maturity
curve (/3m); (C) natural mortality (M); ID) MIK ratio; (E) duration of annual spawn-
ing season (Ds); (F) maximum size limit (Lu); (Gl slope of selectivity curve (j3s); (H)
change in age at 50* selectivity (As) relative to the base case, and (I) duration of
annual fishing season (DF). In all panels, CV's in K and L x are 20%. Filled circles
refer to the base model.
isolates the cause — fishing. Yet with any simulation
analysis, one must interpret results in light of model
assumptions. With our model maturity was assumed to
be a function of age, and the computation of selection dif-
ferentials were consequently focused to those on growth
traits and size. If maturity were considered a function
of size, it too would have been subject to a selection
differential. Changes in size or age at maturity have
been considered in other studies (Stokes and Blythe,
1993; Haugen and Vollestad, 2001; Olsen et al., 2004)
and are likely connected to growth parameters through
bioenergetic constraints.
A central assumption is that somatic growth follows
the von Bertalanffy model. That model was chosen be-
cause of its successful track record (Chen et al., 1992;
Quinn and Deriso, 1999). Life-history characteristics
other than growth are assumed to follow life-history
invariant relationships. The invariants constrain bio-
logical parameters to values that represent an "average
stock." Of course, no stock is truly average, and there-
fore our sensitivity analyses incorporate considerable
deviation from life-history invariants.
In our simulation, the largest selection differentials
occurred when the spawning or fishing seasons were
Williams and Shertzer: Effects of fishing on growth traits: a simulation analysis
401
compressed. We modeled fishing seasons at the begin-
ning of the year and spawning seasons at the end of
the year, and in a single-year simulation, the annual
timing of the fishing and spawning seasons will affect
selection differentials. For example, if the one-month
fishing season had been modeled at the end of the year,
the selection differential would be smaller because of
the 11 months of spawning prior to fishing mortality.
Over multiple years, however, the annual timing of the
fishing and spawning seasons is less important than
their duration and overlap.
Our model simulated selection differentials at the
onset of a fishery. As a fishery progresses, selection
differentials should decrease as life-history parameters
shift in the direction of selection. A multiyear simula-
tion of evolution would require knowledge or assump-
tions about heritability and trait distributions, both of
which are likely to be dynamic. Even so, a short-term
simulation, where selection differentials and heritabil-
ity are assumed to be static, may be an informative
approximation.
We simulated evolution of the base-model population,
assuming a static heritability of 0.2 and selection differ-
entials of 2.5% for Lv and 1.2% for K (values from Tables
2 and 3 with 20% CV's in both parameters). Two simu-
lations were conducted with different values for fishing
mortality. With F = AM, five years of evolution led to a
9.0% decrease in the capacity of spawning biomass. With
F = M, five years led to a 2.3% decrease.
With real fishery data it is often impossible to docu-
ment conclusively that fishing causes a genetic change
in growth. Any such change may be hard to measure,
fall within the range of statistical variability due to
sampling, or be masked by strong year classes. Selec-
tion for reduced growth may be compensated by den-
sity-dependent effects (for example, lower abundance
leaving more resources for survivors to allocate towards
growth). Even when a change can be demonstrated,
fishing is just one potential explanation. Alternative
explanations include environmentally driven evolution
and reaction norms (i.e., phenotypic expressions of a
genotype-environment interaction).
Nonetheless, size-selective fishing is widespread and
often accompanies changes in somatic growth rates
(Ricker, 1981; Harris and McGovern, 1997; Haugen and
Vollestad, 2001; Sinclair et al., 2002). Until recently,
the question was whether fishing can cause changes in
growth that are evolutionary, and the answer was "yes
. . . probably." The laboratory experiments of Conover
and Munch (2002) removed any doubt. However, those
experiments represented an extreme fishery in terms
of its potential to inflict a selection differential: high
F compressed in time (90% of population removed in
one day), knife-edge selectivity, non-overlapping gen-
erations, and a population where all individuals are
susceptible.
The goal of our study was to shed light on selection
differentials created by fishing under realistic ranges of
life-history and fishery characteristics. Understanding
how life-history characteristics affect selection differen-
tials is important for identifying which stocks are most
susceptible to evolution of growth traits. For example,
susceptibility increases with compression of the spawn-
ing season. Fish species with compressed spawning
seasons, such as many anadromous species, may be at
higher risk of evolution from size-selective fisheries.
Understanding how fishery patterns affect selec-
tion differentials has direct management implications
because it is the fishery parameters that can be con-
trolled. For example, our results indicate that size-selec-
tive fisheries compressed in time are apt to cause high
selection differentials. Managers should avoid "derby"
style harvests, such as the annual Pacific herring sac-
roe fisheries, which are completed in only a few days.
Other management strategies could reduce selection
differentials, such as slot limits, reduction in the slope
of selectivity curves, and partial selectivity after the
age at maturity. However, because no size-selective
fishing pattern can preclude some directional selection
on growth, management by area closures may be the
best option for avoiding fishery-induced evolution of
growth traits.
As fishing technology improves, so does the ability
to fully and rapidly exploit fish populations, and thus
increase the potential for evolutionary responses. Still,
when overfishing depletes a stock, low abundance is
usually the paramount concern. With appropriate man-
agement, stock abundance may recover, but pre-fishing
growth capacity may recover more slowly or not at all
if genetic variation is lost. Given plausible heritabili-
ties of growth traits, this analysis shows that under a
wide variety of life-history and fishery characteristics,
selection differentials are large enough to allow for
rapid evolution.
Acknowledgments
We thank R. Munoz, M. Prager, and D. Vaughan for
comments on the manuscript. This work was supported
by the National Marine Fisheries Service through its
Southeast Fisheries Science Center.
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404
Preliminary evidence of increased
spawning aggregations of mutton snapper
(Lutjanus analis) at Riley's Hump
two years after establishment of the
Tortugas South Ecological Reserve
Michael L. Burton
Kenneth J. Brennan
Roldan C. Munoz
Richard. O. Parker Jr.
Center for Coastal Fisheries and Habitat Research
National Marine Fisheries Service
National Oceanic and Atmospheric Administration
101 Pivers Island Rd
Beaufort. North Carolina 28516-9722
E-mail address Michael.BurtoniSnoaa.gov
In this note we describe the re-for-
mation of a spawning aggregation of
mutton snapper {Lutjanus analis). A
review of four consecutive years of
survey data indicates that the aggre-
gation may be increasing in size.
Mutton snapper are distributed in
the temperate and tropical waters of
the western Atlantic Ocean from Flor-
ida to southeastern Brazil (Burton,
2002). Juveniles and subadults are
found in a variety of habitats such
as vegetated sand bottoms, bays, and
mangrove estuaries (Allen, 1985).
Adults are found offshore on coral
reefs and other complex hardbottom
habitat. They are solitary and wary
fish, rarely found in groups or schools
except during spawning aggrega-
tions (Domeier et al., 1996). Spawn-
ing occurs from May through July at
Riley's Hump (Domeier et al., 1996)
and peaks in June, as indicated by
gonadosomatic indices (M. Burton,
unpubl. data). Mutton snapper are
highly prized by Florida fishermen
for their size and fighting ability, and
the majority of landings occur from
Cape Canaveral, , through the Flor-
ida Keys, including the Dry Tortugas
(Burton, 2002).
Reports of spawning aggregations
of tropical reef fishes are abundant
in the fisheries literature. Most docu-
mented aggregations of commercially
important fishes are attributed to
members of the grouper family, Ser-
ranidae, including observations of
spawning Nassau grouper iEpineph-
elus striatus), red hind (E. guttatus),
and tiger grouper {Mycteroperca ti-
gris) in the Caribbean (see review in
Domeier and Colin, 1997, and refer-
ences therein). Eklund et al. (2000)
observed black grouper (M. bonaci)
aggregating during their spawning
season just outside no-take zones
along the Florida Keys reef tract.
Samoilys and Squire (1994) and
Samoilys (1997) documented spawn-
ing aggregations of coral trout (Plec-
tropomus leopardus) from the Great
Barrier Reef, and Johannes (1988)
described the aggregating behavior
of squaretail coralgrouper (P. areola-
tus) from the Solomon Islands. Most
recently, Sala et al. (2003) observed
aggregating behavior in two species
of serranids — the sawtail grouper
(M. prionura) and the leopard grou-
per (M. rosacea) from the Gulf of
California.
There are fewer descriptions of
spawning aggregations of the com-
mercially important snappers (Lut-
janidae) in the literature. Wicklund
(1969) described spawning behavior
of lane snapper {Lutjanus synagris)
from southeast Florida, Carter and
Perrine (1994) described a spawning
aggregation of dog snapper (L. jocu)
from Belize, and Sala et al. (2003)
described spawning behavior in two
lutjanids from the Gulf of California
(yellow snapper, L. argentiventris; Pa-
cific dog snapper, L. novemfasciatus).
Mutton snapper (L. analis) are per-
haps the best known snapper to form
spawning aggregations. Craig (1966)
observed concentrated commercial
fishing on an apparent "spawning
run" of mutton snapper in August at
Long Cay, Belize. Domeier and Colin
(1997) described an aggregation of
L. analis in the Turks and Caicos
Islands in April 1992, and Domeier
et al (1996) identified a spawning ag-
gregation at Riley's Hump.
Because of their predictable nature
with respect to location and time,
spawning aggregations become ex-
tremely vulnerable to heavy exploi-
tation once discovered by fishermen.
The majority of annual catches of
Nassau grouper in some areas comes
from annual spawning aggregations
(Colin, 1992; Aguilar-Perera and
Aguilar-Davila, 1996), whereas other
aggregations have been completely
extirpated (Olsen and LaPlace, 1978;
Sadovy and Eklund, 1999; Heyman,
2003). Russ (1991) observed that
uncontrolled fishing on spawning
aggregations could lead to recruit-
ment overfishing. During a May 1991
survey of Riley's Hump, a site of a
known mutton snapper spawning ag-
gregation in the Dry Tortugas, Flor-
ida, Domeier and Colin (1997) noted
that fish were more scattered and far
less abundant than they were at the
Turks and Caicos site. The authors
suggested that this difference was at-
tributable to heavy commercial fish-
ing pressure at Riley's Hump during
the several years prior to 1991.
Although recent literature indi-
cates that fishing pressure on Riley's
Hump has been intensive for several
years prior to 1991 (Domeier and
Colin, 1997), anecdotal information
indicates otherwise. According to a
commercial hook-and-line fisherman
who fished on Riley's Hump from
1978 through 2001, the first known
Mansucript submitted 20 December 2003
to the Scientific Editor's Office.
Manuscript approved for publication
29 December 2004 by the Scientific Editor.
Fish. Bull. 103:404-410 (2005).
NOTE Burton et al.: Spawning aggregations of Lut/anus analis at Riley's Hump
405
instance of commercial fishing on this area occurred in
1968 by a fisherman named Riley.1 However, the naviga-
tion device in common use in 1968 was LORAN (long
range navigation) A; thus, the likelihood of a fisherman
finding the exact spot where he fished previously was
much less likely than with today's global positioning
system (GPS) receivers. Large-scale commercial fishing
of Riley's Hump began in 1976, with the introduction of
the improved LORAN C navigation system.
Commercial fishermen began fishing the area with
longline gear in 1979, and fish traps were introduced
there in 1984. This was the period of the most intensive
fishing; longliners harvested between 10 and 21 metric
tons per trip and fish trappers typically landed an aver-
age of 11.5 metric tons (Gladding1). It is necessary to
rely on knowledgeable fishermen for anecdotal data such
as this because the National Marine Fisheries Service
(NMFS) did not separate out individual species in their
data sets prior to 1986, instead consolidating all snap-
pers into an unclassified snapper category. After 1986,
landings from the Dry Tortugas were included with
the rest of the Florida Keys in a Monroe County total;
therefore it is virtually impossible to obtain an exact
magnitude of the landings from the Dry Tortugas for
this time frame without information from knowledge-
able fishermen who were involved in the fishery at the
time. In addition to the commercial effort, a small fleet
of headboats ran multiday fishing trips to Riley's Hump
and other areas in the Dry Tortugas (Dixon2).
Fishermen began to realize declining catches in the
mid-1980s and brought this to the attention of the fish-
ery management councils. The Gulf of Mexico Fishery
Management Council (GMFMC) enacted a spawning-
season closure in 1992, prohibiting fishing on Riley's
Hump in May and June (Gulf of Mexico Fishery Man-
agement Council, 1992). An analysis of pre- and postclo-
sure commercial landing data revealed that, as a result
of the closure, there was a shift in effort to the months
on either side of the period of closure, and landings
during the two-month closure decreased in only one of
the months while annual landings increased (Burton,
1997). After further urging by fishermen and an effort
by the Tortugas Working Group (a group of stakehold-
ers appointed by the Florida Keys National Marine
Sanctuary [FKNMS] Advisory Council), the Tortugas
South Ecological Reserve (TSER) was created in July
2001 specifically to protect the spawning aggregation
and habitat of mutton snapper. Current regulations pro-
hibit all uses of the reserve, except continuous transit
through the reserve, for any vessels without a FKNMS
research permit. The authors initiated data collection
on Riley's Hump in July 2001 to document the effect of
the newly designated ecological reserve on abundance
of snappers and groupers.
1 Gladding, P. 2003. Personal commun. 27A 12th Avenue,
Stock Island, FL 33040.
2 Dixon, R. 2003. Personal commun. CCFHR, NMFS,
NOAA, 101 Pivers Island Rd., Beaufort, NC 28516-9722.
Materials and Methods
Study area
Riley's Hump is a carbonate bank of Holocene origin
located 20 km southwest of the Dry Tortugas National
Park (DTNP) island of Garden Key (Ft. Jefferson). Riley's
Hump sits in the northeast corner of the TSER within
the FKNMS (Fig. 1). The area has a predominantly
low-relief hardbottom and patchy hard coral and scat-
tered gorgonian sponge-soft coral communities. Rising
to within 30 m of the surface, Riley's Hump covers an
area of approximately 10 km2. Habitat mapping efforts
by Franklin et al. (2000), who used a nine-tier habi-
tat classification scheme, and visual observations from
SCUBA dives revealed that Riley's Hump consisted
mostly of areas of rocky outcropping and some patchy
hard bottom in sand. More detailed multibeam mapping
showed that the top of the bank is relatively flat and has
an escarpment on the south side of the bank dropping
from 30 m to well over 50 m deep (Fig. 2) (Mallinson
et al., 2003).
Sampling
Initial sampling stations were selected in 2001 by divid-
ing the top of Riley's Hump into a grid consisting of
0.40-km2 sections and by conducting a census with the
ship's depth sounder in order to identify (within as many
grids as possible) reef habitat that could be reached by
dives. Ten initial stations were selected according to this
procedure. Five more stations were added in 2002 at the
recommendation of our vessel captain, Peter Gladding
(Fig. 2). Two-man dive teams conducted several 30-m
visual census strip transects (Brock, 1954) at each sta-
tion during the summer months of each year, enumerat-
ing all species of snappers and groupers observed.
Results
We summarize our observations of mutton snapper abun-
dance and behavior on Riley's Hump in Table 1, along
with the observation's relation in time to the lunar cal-
endar. The initial sighting of an unusually large group
of mutton snapper occurred on 17 July 2001. A group
of 10 fish was observed by the senior author at station
2 (Fig. 2). The fish were swimming 0.5-1 m apart in
a group approximately 1.5 m above the seafloor. The
next year, on 27 May 2002, we observed a larger group
of approximately 75-100 mutton snapper on the same
site, station 2 (Fig. 2). These fish were exhibiting simi-
lar behavior to that observed the preceding year. The
group remained schooled while the dive team completed
one 30-m visual transect and then slowly dispersed as
the divers returned to the aggregation location. On 15
June 2003, a team of divers discovered an aggregation
of over 200 individual mutton snapper at station 12
(Fig 2). The fish repeatedly swam up to the diver doing
the census transects and then slowly turned and swam
406
Fishery Bulletin 103(2)
*foj
~^i
N
+
(Enlarged below)
0
30 60 Miles
^Mp
<***^
0 "
Loggerhead Key /■
Middle Key
Garden Key
Bush Key
Riley's Hump
South Tortugas Ecological Reserve
12 Miles
Figure 1
Location of Riley's Hump, Tortugas South Ecological Reserve, Florida
Keys National Marine Sanctuary.
away. The aggregation was spread out over a wide area,
was not as dense as in the previous two sightings, and
exhibited the milling behavior similar to that described
by Thresher (1984) for several other species of lutjanids.
This aggregation remained at the site throughout the
entire 20-minute census dive. Later that day, divers
recording their observations at nearby station 2 reported
a group of approximately 100 mutton snapper. These fish
were more widely dispersed and maintained a distance
of 3-5 m from divers. Finally, on 4 July 2004, the senior
author and another diver encountered a large school
of approximately 300 mutton snapper at station 12,
exhibiting behavior similar to that observed during the
preceding year.
Discussion
We believe that the large groups of fish encountered at
station 12 in June 2003 and again in July 2004 were
spawning aggregations based on their behavior and
on the timing and location of the aggregation. First,
behavior of the snappers themselves was not typical
of nonspawning individuals. Although Humann (1997)
described them as being very curious, mutton snapper
are typically described as solitary animals (Domeier
and Colin, 1997), cautious of divers, and not allowing
close approach. Many large reef fishes exhibit simi-
lar solitary behavior, such as Nassau grouper (Smith,
1972) and black grouper (Eklund et al., 2000). The
NOTE Burton et al.: Spawning aggregations of Lut/anus analts at Riley's Hump
407
24*32'
24'31'
24-3CT
24*29'
-83*08'
■aarg'
-83*06;
-25-
-30-
-35-
-40-
-83-05'
Figure 2
Multibeam bathymetric image of the top of Riley's Hump showing locations of visual census
stations (white circles! and mutton snapper aggregation sightings (stations 2 and 12).
Bathymetric image was provided courtesy of D. Naar and B. Donahue, Univ. S. Florida,
from Mallinson et al., 2003.
Table 1
Observations on mutton snapper (Lutjanus analis) on Riley's Hump and their behavior as noted by the authors.
Date and station
Numbers observed
Behavior
Moon phase
28 May-1 June 1999
31 July-3 Aug 2000
Solitary L. analis observed
on 3 of 11 dives
Solitary L. analis observed
on 5 of 6 dives
17 Jul 2001
Station 2
10
27 May 2002
Station 2
75-100
15 June 2003
Station 2
75-100
Station 12
200+
4 July 2004
Station 12
300
Slowly swimming, diver avoidance
Slowly swimming, diver avoidance
Swimming in a tightly packed group,
1.5 m off bottom
Swimming in tightly packed group,
1.5 m off bottom
Widely dispersed, diver avoidance
Widespread aggregation,
actively swimming, did not avoid divers
Widespread aggregation,
actively swimming, did not avoid divers
Full moon May 30
New moon July 30
3 days before
new moon
1 day after
full moon
1 day after
full moon
2 days after
full moon
408
Fishery Bulletin 103(2)
senior author completed over 115 dives on Riley's Hump
from 1995 through 2004, and the typical mutton snap-
per sighting during dives made outside the spawning
season (February, 5 dives; August, 5 dives; October, 7
dives) was a single fish. In these instances, the closest
approach allowed by the fish was 3 m, and when an
attempt was made to approach, the fish would swim
away, maintaining separation. The only exceptions to
this behavior were the four sightings in which groups
of fish were apparently unconcerned with the presence
of divers (Table 1). Johannes (1981) described a condi-
tion he termed "spawning stupor" in P. areolatus from
Palau. He took this term from the Palauan fishermen's
description of the fish as "stupid." We do not believe
that "stupid" in this context means unaware, but more
closely approximates Johannes et al.'s (1999) modified
description of spawning stupor as more of a lack of
concern about divers. Mutton snapper in the spawning
aggregation we observed seemed aware of our presence
because they approached and retreated from the divers
many times. Domeier and Colin (1997) asserted that
spawning or courtship behavior is easily broken off by
a diver's close approach or SCUBA exhalation, although
Johannes et al. (1999) offered evidence showing that this
is not always the case. We conducted our dive operations
primarily in the day and thus did not witness spawning,
which is thought to occur at dusk or later (Domeier and
Colin, 1997). Courtship behavior has not been described
for mutton snapper except by Domeier and Colin (1997)
who observed that fish in the Turks and Caicos aggrega-
tion "milled in a dense school from the bottom to within
a few meters of the surface." The mutton snapper we
observed exhibited this milling behavior and did not
change it because of our presence.
Consistent timing of spawning with respect to a spe-
cific lunar phase has long been thought to be a char-
acteristic of many spawning aggregations. Johannes
(1978) noted that the majority of fishes with known
lunar-associated spawning rhythms spawned near the
full or new moon. However, the published literature
does not provide strong support for a correlation be-
tween spawning of most lutjanid species and any single
lunar phase. The lane snapper aggregation observed by
Wicklund (1969) occurred just after the new moon but
has not been corroborated since this single observa-
tion. Spawning of dog snapper in Belize was variable,
however, occurring three days after the new moon on
Cay Glory (Carter and Perrine, 1994) and just after the
full moon on English Cay (Domeier and Colin, 1997).
Spawning peaks for gray snapper off Key West, Florida,
were also variable, occurring on the new and full moons
of June-August, although the strongest spawning peak
was associated with the last quarter moon of August,
half way between the new and full moons (Domeier et
al., 1996). Back-calculated spawning dates of gray snap-
per collected in ichthyoplankton samples near Beaufort
Inlet, North Carolina, have indicated that spawning
takes place primarily at the time of the new moon and
secondarily at the time of the full moon (Tzeng et al.,
2003).
Evidence of mutton snapper spawning tends to sup-
port the argument that the species spawns during a
full moon, in contrast to the examples of other lutjanids
above. Mutton snapper aggregations off Gladden Spit,
Belize, peaked during the April and May full moons
and were heavily exploited by fishermen (Heyman et
al., 2001). Domeier and Colin's (1997) observation of a
mutton snapper aggregation off West Caicos occurred
on the April 1992 full moon, and Domeier collected
specimens with hydrated oocytes from the Riley's Hump
location within one day of the full moon in May 1991
(Domeier and Colin, 1997). Our observation of a small
group of about 10 mutton snapper at Riley's Hump in
July 2001 occurred three days before the new moon.
Our observations of groups of approximately 100, 200,
and 300 fish, however, occurred one day after the full
moons of May 2002 and June 2003, and two days after
the full moon of July 2004, respectively. In contrast,
the back-calculated spawning dates of mutton snapper
collected in icthyoplankton samples near Beaufort Inlet,
NC, indicated that spawning occurred from two days
after the full moon to three days before the new moon
and that peak spawning occurred between the full moon
and last quarter moon phase (Hare3). These data are
not inconsistent, however, with our observations of fish
beginning to aggregate on or around the full moon for
spawning. Our sightings of such large groups of mutton
snapper around the full moon indicate activity associ-
ated with a spawning aggregation.
Finally, many species of reef fishes consistently aggre-
gate to spawn at specific locations at regular intervals
(e.g., daily, annually). The two main hypotheses as to
why reef fishes do this are to offer increased chances
of 1) immediate survival of eggs and larvae, and 2) en-
trapment of larvae in favorable currents for transport
to suitable nursery habitat (Johannes, 1978; Lobel,
1978; Gladstone, 1994), although the former hypothesis
currently has more support (Hensley et al., 1994; Peter-
son and Warner, 2002). Without invoking the hypothesis
of local adaptation to the aggregation sites on Riley's
Hump, several studies have indicated that the physical
oceanography of the region is favorable for transporting
larvae spawned at Riley's Hump up the Florida Keys
reef tract (Lee et al., 1994; Lee and Williams, 1999)
and even as far north as Vero Beach, Florida (Domeier,
2004), presumably to suitable habitat. We believe that
the specific location on Riley's Hump where we observed
aggregations supports our conclusion that these were
spawning aggregations.
In describing lutjanid behavior Thresher (1984)
said, "A key feature of reproduction ... is an extensive
spawning migration to select areas along the outer
reef." Observations in the literature of reef fish spawn-
ing aggregations occurring on the outer reef edge, on
seaward extensions or promontories, near the shelf-edge
3 Hare, J. 2002. Personal commun. Center for Coastal
Fisheries and Habitat Research, National Ocean Service,
NOAA, 101 Pivers Island Rd., Beaufort, NC 28516-9722.
NOTE Burton et al.: Spawning aggregations of Lutjanus analis at Riley's Hump
409
break, on the reef slope or near drop-offs are numer-
ous (Randall and Randall, 1963; Smith, 1972; Munro,
1974; Colin, 1992; Shapiro et al., 1993; Sadovy et al.,
1994a. 1994b; Samoilys and Squire, 1994; Sala et al.,
2003, and others). Heyman (2003) described a single
promontory on a Belize reef that harbored spawning
aggregations of 26 different species throughout the
year. The mutton snapper aggregation from West Caicos
(Domeier and Colin, 1997) occurred on a reef near a
drop-off into deep water. The south end of Riley's Hump
drops quickly from 35 m to well over 50 m. The two
sites where we have observed unusually large numbers
of mutton snapper are in the vicinity of this drop-off.
Station 2, where we observed aggregations of various
sizes in all four years, is approximately 300 m inshore
of the edge, whereas station 12, where we observed the
largest aggregation in June 2003 and July 2004, is
within 150 m of the edge (Fig. 2).
We conclude from behavior, timing, and location that
we are observing spawning aggregations of mutton
snapper beginning to re-form on Riley's Hump follow-
ing more than two decades of intensive exploitation.
Although the numbers we observed are not close to
anecdotal descriptions of the numbers of fish caught
during the height of the commercial fishery at this
location, it is encouraging to note that we have seen
an increasing number of fish for each successive year
that we have surveyed these stations. It is too early to
say definitively whether the fish are actually becoming
more abundant, but preliminary indications are that
one effect of the TSER has been to increase numbers
of mutton snapper. Current research plans include con-
tinued annual monitoring of transects and increased
exploration for additional spawning sites, as well as an
expansion of our surveys to the last quarter and new-
moon phases in order to continue to try to document the
exact timing of spawning.
Acknowledgments
We gratefully acknowledge and dedicate this paper to
Peter Gladding, master of the FV Alexis M, for his superb
boat handling skills and knowledge of Riley's Hump; Peter
recently lost his battle with cancer and we will greatly
miss his guidance and company on our trips. We acknowl-
edge the contributions of Richard Stoker, first mate of
the Alexis M for his repeated suggestions and help that
improved our research efforts; Don Field, Don Demaria,
Bill Gordon, and Ian Workman for their assistance at
various times with diving efforts; Lisa Wood for her
help with the figures; Jon Hare, Erik Williams, Michael
Prager, and three anonymous reviewers for constructive
reviews of the manuscript that greatly improved it.
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411
Feeding habits of European hake
(Merluccius merluccius)
in the central Mediterranean Sea
Paolo Carpentieri
Francesco Colloca
Department of Animal and Human Biology
University "La Sapienza"
Viale dell'Umversita 32
00185 Rome, Italy
E-mail address (for P. Carpentieri) paolo.carpentieri@uniromal it
Massimiliano Cardinale
Institute of Marine Research
National Board of Fisheries
P.O. Box 4
45 332, Lysekil, Sweden
Andrea Belluscio
Giandomenico D. Ardizzone
Department of Animal and Human Biology
University "La Sapienza"
Viale dell'Universita 32
00185 Rome, Italy
European hake (Merluccius merluc-
cius) is an important predator of
deeper shelf-upper slope Mediterra-
nean communities. It is a nectoben-
thic species distributed over a wide
depth range (20-1000 m) throughout
the Mediterranean Sea and the north
east Atlantic region (Fisher et al.,
1987). Notwithstanding the ecologi-
cal and economic importance (Oliver
and Massuti, 1995) of hake in the
Mediterranean, many aspects of its
biology (e.g., recruitment and repro-
duction), due to multiple spawning
(Sarano, 1986) and the current state
of exploitation, are poorly understood
(Arneri and Morales-Nin, 2000).
Recent studies on hake feeding
habits in the Mediterranean (Papa-
costantinou and Caragitsou, 1987;
Bouaziz et al., 1990; Oliver and Mas-
suti, 1995) have focused on 0-3 age
groups using data from trawl catch-
es (Recasens et al., 1998; Colloca et
al., 2000). For this reason, trophic
habits of older individuals (Bozzano
et al., 1997) and possible ontogen-
esis-related diet changes are almost
unknown. Therefore, in this study
we combined samples from trawl and
gillnet fisheries collected in the same
fishing ground (Colloca et al., 2000)
to address these issues.
Materials and methods
The study area is located off the cen-
tral western coasts of Italy, cover-
ing 13,404 km2 between 20 and 700
meters depth (outer boundaries: lati-
tude 40°52'64, longitude 13°23T3; lat-
itude 42°20'30, longitude 11°16'32).
Monthly size-stratified samples
were obtained from spring 1997 to
winter 1998 both from bottom-trawls,
gillnet commercial-vessels, and from
commercial landings. Trawlers catch
mainly 0-2 year-old juveniles; they
rarely capture adults (Aldebert et al.,
1993; Abella et al., 1997; Ardizzone
and Corsi, 1997). The gillnet fishery
exploits mainly adults of the species
(>25 cm TL).
Caught fish were kept on ice,
subsequently frozen to prevent di-
gestion of their stomach contents,
taken to the laboratory, measured
(total length: TL) to the nearest
1 mm, and weighed to the nearest
0.01 g. Sex and maturity stage were
also recorded. Maturity state was
determined by macroscopic analysis
of the gonads by using the maturity
scale for partial spawners (Holden
and Raitt, 1974).
Stomachs were removed and their
contents weighed to the nearest
0.001 g. Prey items were identified
and sorted into taxonomic groups to
the species level whenever possible.
When the state of digestion was
more advanced, prey were checked
and grouped into unidentified fish,
cephalopods, or crustaceans. The de-
gree of digestion of the prey was not
considered in the analysis. Empty
stomachs and those with partially
everted or unidentified contents were
excluded from the total sample.
With the exception of the largest
individuals (grouped into two het-
erogeneous length classes), all re-
maining hakes in the sample were
grouped into 5-cm length classes.
The study of size-related diet varia-
tions was based on these groups. The
contribution of each food item to the
diet of these fish length groups was
evaluated by using the index of rela-
tive importance (IRI, Pinkas et al.,
1971) as modified by Hacunda (1981):
IRI= F{N + W).
This index, expressed as
IRI%=IRI
- IIRI .
100,
incorporates the percentage by num-
ber (N%), wet weight (W7<), and fre-
quency of occurrence (F% ) (Hyslop,
1980). Hierarchical cluster analysis
and nonmetric multidimensional scal-
ing (NMDS), based on Bray-Curtis
similarity and on the IRI%, were
used for classification and ordination
of hake size classes (Clarke and War-
wick, 1994).
Manuscript submitted 27 April 2003
to the Scientific Editor's Office.
Manuscript approved for publication
13 December 2004.
Fish. Bull. 103:411-416(2005).
412
Fishery Bulletin 103(2)
Results
A total of 2761 hakes between 5 and 90 cm TL were
collected (Table 1). The total number of prey was about
1700, divided into 46 different species. Cluster and
NMDS analysis (stress = 0.02) based on the IRI allowed
the identification of four groups below 50% similarity
that were separated along a size gradient (Fig. 1).
Euphausiids iNictiphan.es couchi, IRI=76%) and my-
sids (Lophogaster typicus, IRI=22%) dominated the diet
of group A (hake between 5 and 10.9 cm TL), and deca-
pods were the secondary prey.
£ 40 ■
M 80
100
VI III IV V IX VII VIII
Hake size classes
Stress: 0.02
Group A
(<11 cm) II
Group B (11 to15.9cm)
Group C (16 to 35.9 cm)
Figure 1
Dendrogram and NMDS (nonmetric multidimensional scaling)
plot, based on IRI% values, of the nine hake (Merluccius merluc-
eius) size classes using group-average clustering from Bray-Curtis
similarity on diet data. (A) The four groups defined at arbitrary
similarity level of 50% are indicated (dotted line); (B) NMDS
showing the ordination of hake into four size classes with similar
diets (the details of each size class are explained in the text).
Group B (hake from 11 to 15.9 cm TL) showed a more
heterogeneous diet characterized by a high occurrence
of euphausiids but also with a considerable number of
decapods (IRI=18%). Decapods were represented by a
wide variety of species, such as Chlorotocus crassicor-
nis, Alpheus glaber, Plesionika heterocarpus, Pasiphaea
sivado, and Solenocera membranacea. Pisces and mysids
showed lower percentages (IRI=15% and 4%, respec-
tively). Sepiolidae (IRI = 0.9%), Sepietta oweniana and
Alloteuthis media, dominated among cephalopods.
The data suggest a gradual change towards a fully
piscivorous diet (Fig. 2) which begins around 16 cm TL
and is completed when sexual maturity is at-
tained (TL = 32 cm for males and TL = 38.5 cm
for females; Colloca et al., 2002).
The importance of teleosts strongly increased
in group C (hake from 16 to 35.9 cm TL), where
they accounted for 91% of hake diet. The main
prey were Clupeiformes (IRI=61 %), Sardina
pilchardus and Engraulis encrasicolus. Fish
(IRI = 96%) represented almost the entire diet
of group D (>36 cm TL). In this group a shift
towards Centracanthidae (Spicara flexuosa,
Centracanthus cirrus) and a simultaneous de-
cline in consumption of Clupeiformes was ob-
served. Among decapods (IRI=4%), two species
occurred most frequently: Processa spp. and S.
membranacea. Euphausiids, mysids, and cepha-
lopods were absent in the diet of hakes larger
than 36 cm TL.
Cannibalism of hake juveniles also accounted
for some of the diet and increased with predator
size. In hake between 36 and 40 cm TL cannibal-
ism represented 12% of IRI, reaching the highest
values (IRI = 17%) among larger individuals (TL
>51 cm).
Discussion
Hake is a top predator that occupies different
trophic levels during its ontogenetic develop-
ment. Hake size classes are differentiated along
food niche dimensions according to different prey
sizes or different prey taxa. Hake diet shifted
from euphausiids, consumed by the smaller
hakes (<16 cm TL), to fishes consumed by larger
hakes. Before the transition to the complete
icthyophagous phase, hake showed more gener-
alized feeding habits where decapods, benthic
(Gobiidae, Callionymus spp., Arnoglossus spp.)
and nectonic fish (S. pilchardus, E. encrasicolus)
dominated the diet, and cephalopods had a lower
incidence. Specific size-related differences in
prey spectrum seem to be associated with dif-
ferent spatial distributions or genetic needs (or
with both) (Flamigni, 1984; Jukic and Arneri,
1984; Velasco and Olaso, 1998).
The patterns observed in the present study
indicated a strong partitioning among hake
NOTE Carpentien et al.: Feeding habits of Merlucaus mer/uccius in the central Mediterranean Sea
413
Table 1
Number of hakes and values of IRI (index of relative importance) (% ) for the
nine size
classes. The four groups identified from the
cluster analysis are indicated.
Size group
A
B
C
D
I
II
III
IV
V
VI
VII VIII
IX
Length (cm)
5.0-10.9
11.0-15.9
16.0-20.9
21.0-25.9
26.0-30.9
31.0-35.9
36.0-40.9 41.0-50.9
51.0-90.0
Number of hakes
202
430
564
454
555
224
139 107
75
Stomach contents
93
215
239
173
170
78
45 35
26
Prey
Cephalopoda
Alloteuthis media
0.22
0.02
0.01
Septet ta oweniana
0.02
0.02
0.01
Unid. Sepiolidae
0.35
0.30
0.03
Unid. Cephalopoda
0.42
0.10
0.01
0.02
Crustacea
Alpheus glaber
0.02
0.33
0.05
0.22
0.05
0.81 1.54
Aristeidae
0.01
0.02
Aristeus antennatus
0.02
Chlorotocus crassieornis
1.61
1.83
1.09
1.10
0.48
Crangonidae
0.01
0.01
Pandalidae
0.03
0.01
Parapenaeus longirostris
0.01
Pasiphaea multidentata
0.02
0.01
Pasiphaea sivado
0.20
0.04
0.05
0.02
0.05
0.33
Plesionika heteroearpus
0.11
0.01
Plesionika sp.
0.62
0.07
0.01
0.04
0.05
Pontocaris lacazei
0.01
0.02
0.01
0.20
Pontophdus spinosus
0.01
0.01
0.03
0.05
0.20
Processa sp.
0.25
0.06
0.06
0.15
1.77
0.83 1.54
Solenoeera membranaca
0.04
0.02
0.05
0.34
0.58
3.27 3.53
Squilla sp.
0.05
Unid. Decapoda
3.05
19.91
6.19
2.84
2.73
1.45
1.58
1.32
Lophogaster typieus
28.77
4.34
0.16
0.01
Nictiphanes couchi
54.10
31.83
0.37
Unid. Euphasiacea
13.99
3.43
0.11
Unid. Isopoda
0.07
0.02
0.01
Pisces
Argentina sphyraena
0.08
0.41
1.06
4.04 3.29
2.34
Arnoglossus laterna
0.01
0.01
Arnoglossus sp.
0.01
0.01
0.01
Callionymus sp.
0.01
0.01
0.01
0.06
Centracanthidae
0.03
0.11
2.60
2.43 11.23
53.97
Centracanthus cirrus
1.93
26.54 4.62
3.80
Clorophthalmus agassizi
0.01
Conger conger
0.34 0.85
Echiodon dentatus
0.05
Engraulis encrasicolus
1.95
11.61
1.28
4.45
9.91
0.87 1.27
1.86
Gadiculus argenteus
0.08
0.65
0.31 0.58
Gobiidae
0.04
0.02
0.01
0.01
0.05
Gobius quadrimaculatus
0.02
0.02
0.01
Lepidotrigla dieuzedei
0.01
0.01
0.78
Lesuerigobius friesii
0.01
0.02
0.03
Merluccius merluccius
0.07
0.18
12.00 4.10
17.95
continued
414
Fishery Bulletin 103(2)
Table 1 (continued)
Size group
A
B
C
D
I
II
III
IV
V
VI
VII
VIII
IX
Pisces (continued)
Mullus barbatus
0.12
0.44
0.49
Myctophidae
0.30
0.28
0.03
0.15
Nettastoma melanurum
0.02
0.01
0.01
Sar'dina pilchardus
0.05
45.23
72.55
46.19
62.0
5.20
12.77
10.31
Sphyraena sphyraena
0.60
4.98
Spicara flexuosa
0.02
0.10
1.33
12.63
21.83
0.01
Spicara sp.
0.37
4.57
0.54
1.69
Trachurus trachurus
0.09
0.13
1.60
1.93
Trisopterus m. capelanus
0.02
0.01
0.01
0.05
Unid. Osteichthyes
0.04
34.19
33.14
21.61
43.44
15.01
23.09
22.90
4.25
Raja sp.
0.50
size classes. Two main thresholds associated with
ontogenesis-related diet changes have been identi-
fied. The first one was observed around 16 cm TL
and corresponded to a significant change in depth
distribution. The second, around 36 cm TL, cor-
responded to the attainment of sexual maturity
(Colloca et al., 2002).
Although hakes are demersal fishes, they feed
typically upon fast-moving pelagic prey that are
ambushed in the water column (Alheit and Pitcher,
1995). There is evidence that hakes feed in mid-wa-
ter or near the surface at night, undertaking daily
vertical migrations (Hickling, 1927; Papacostanti-
nou and Caragitsou, 1987; Orsi-Relini et al., 1989)
which are more frequent for juveniles. Small hakes
feed daily on small Euphausiacea (Nictiphanes cou-
chi). This school-forming planktonic crustacean
carries out vertical migrations at night (Casanova,
1970; Franqueville, 1971; Vallet and Dauvin, 2001).
They rise to near the surface at night to feed on
phytoplankton and sink during daylight between 50
and 800 m depth (Buchholz et al., 1995). Juveniles
of M. merluccius may follow such migrations, moving
from near the bottom, 100-200 m depth, to midwater at
night (Froglia 1973; Papaconstantinou and Caragitsou,
1987; Orsi-Relini et al., 1989). Nocturnal vertical mi-
gration behavior has been described for gadoids such as
hake and cod and is considered responsible for the re-
duction of trawl catches of these fish at night (Beamish,
1966; Bowman and Bowman, 1980).
Considerable diet changes have been observed after
the first year of life (>16 cm TL) when juveniles move
from nursery areas on the shelf-break and upper slope
to the middle shelf (Andaloro et al., 1985; Ardizzone
and Corsi, 1997). The data indicate that such migration
is induced by a change in trophic requirements. In this
size class, diet changed to fish prey (Clupeiformes), and
the importance of the small epiplanktonic crustaceans
100 -.
*oo o°
£ g 75-
o°o
o o o
Porportion of fish
in hake stomachs
en o
r, °°
o °
o
o °
0
10 20 30 40 50 60
Hake length (cm)
Figure 2
70 80
90
Proportion
{%) of fish prey occurring in the
diet of hake
{Merluccius
merluccius) during its growth.
(Euphausiacea) strongly decreased. Clupeiforms S. pil-
chardus and E. encrasicolus are distributed largely on
the continental coastal shelf forming schools usually
deeper than 25 m (Fisher et al., 1987).
The size-depth distribution pattern of hake was con-
firmed by experimental trawl surveys carried out in
the Mediterranean (Relini and Piccinetti, 1996; Relini
et al., 1999). Juveniles (modal length of 10 cm TL) are
found mostly between 100 and 200 m depth. Intermedi-
ate hakes reach the highest abundance mainly on the
shelf (<100 m). Large hakes (>36 cm) are found in a
wide depth range but concentrate on the shelf break
during the spawning period (Recasens et al., 1998; Col-
loca et al., 2000; Alvarez et al., 2001).
Growth induces a continuous qualitative and quanti-
tative change in diet that is reflected in the increasing
NOTE Carpentieri et al.: Feeding habits of Merlucaus merluccius in the central Mediterranean Sea
415
mean weight of prey and decreasing mean number of
prey items per stomach. The shift towards large fish
prey (i.e., Centracanthidae) usually occurs slightly be-
fore maturity — the life history stage with much higher
energetic demands due to gonad development (Ross,
1978). A similar pattern was observed for Atlantic cod
(Gadus morhua) where sexual maturation and spawn-
ing are also associated with an ontogenetic change in
diet (Paz et al., 1993). Thus, increased energy demands
related to sexual requirements, gonad development, and
breeding activity appear to be the critical factors driv-
ing the changes in feeding strategy of M. merluccius.
In large hakes (>36 cm), cannibalism played an
important role and should be carefully considered in
stock-recruitment analyses. Studies carried out in the
Mediterranean (Macpherson, 1977; Bozzano et al., 1997)
and in the Atlantic (Guichet, 1995; Link and Garrison,
2002) showed that cannibalism has some importance
for hake. In silver hake (M. bilinearis), cannibalism
notably increased with ontogeny (Link and Garrison,
2002). In the large cape hakes, M. capensis, hake is
the dominant food item (50% of the diet) for individu-
als larger than 60 cm (Roel and Macpherson, 1988).
Conversely, a low cannibalism rate was observed for
M. paradoxus in the same area (Payne et al., 1987).
This could be a response to the greater accessibility
of conspecifics compared to other species. As Payne et
al. (1987) pointed out, small hake are not found in the
vicinity of adults of the species. This is supported by
the observed size segregation by depth, which is more
pronounced in M. paradoxus than in M. capensis (Gor-
doa and Duarte, 1991). Density-dependent cannibalism
may be an important source of natural mortality that
can stabilize fish populations (Smith and Reay, 1991),
and for M. capensis, cannibalism has even been consid-
ered the main cause of natural mortality (Lleonart et
al., 1985; Payne and Punt, 1985).
Our results on the trophic ecology of hake are of pri-
mary importance for future management of fish assem-
blages where this species plays an important predatory
role. Multispecies management requires quantitative
data on fish diet to elucidate the relationships between
species and, consequently, to forecast temporal biomass
fluctuations, under specific fishing regimes, in an inte-
grated manner.
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417
Biology of queen snapper
(Etelis oculatus: Lutjanidae) in the Caribbean
Bertrand Gobert
Institut de Recherche pour
le Developpement (IRD)
Technopole Brest-lroise
BP 70
29280 Plouzane, France
E-mail address: gobertra) ird.fr
Alain Guillou
Institut Francais de Recherche
pour I'Exploitation de la Mer (Ifremer)
Boulevard Jean Monnet
BP 171
34203 Sete Cedex, France
Peter Murray
Organization of Eastern Caribbean States
(OECS)
Environment and Sustainable
Development Unit
The Morne
POBox 1383
Castries, Saint Lucia
Patrick Berthou
Institut Francais de Recherche
pour I'Exploitation de la Mer (Ifremer)
BP 70
29280 Plouzane, France
Maria D. Oqueli Turcios
38, rue Desaix
75015 Paris, France
Ester Lopez
Departement Halieutique
Ecole Nationale Supeneure Agronomique de
Rennes
65, rue de Saint-Bneuc
CS 84215
35042 Rennes Cedex, France
Pascal Lorance
Jerdme Huet
Institut Francais de Recherche pour
I'Exploitation de la Mer (Ifremer)
BP 70
29280 Plouzane, France
Nicolas Diaz
Boyer
97129 Lamentin
Guadeloupe, French West Indies
Paul Gervain
Rue Authe 2
Petit Pans
97100 Basse Terre
Guadeloupe, French West Indies
tation of the queen snapper is poorly
documented, and very few detailed
catch statistics are available; in all
cases, the amounts landed in each
country are small (probably not ex-
ceeding a few tens of tons per year),
but the potential production of these
resources has never been estimated.
Owing to the depth of its habitat
and to the relatively small economic
importance of the fisheries for queen
snapper on the local scale, very little
is known about the biology of E. ocu-
latus. It is generally cited in species
checklists or in general descriptions
of deepwater fisheries. Very few stud-
ies actually have focused on the spe-
cies itself (Murray, 1989; Murray and
Charles, 1991; Murray et al., 1992;
Murray and Moore, 1992; Murray
and Neilson, 2002).
The objective of this study is to
present new information about the
biology of E. oculatus, obtained from
fishing experiments undertaken since
the 1980s in the French West Indies
(Martinique, Guadeloupe, Saint-
Barthelemy, and the French part of
Saint-Martin), Dominica and Saint-
Lucia, and from a study conducted
in the late 1990s on the artisanal
and semi-industrial fisheries off the
Caribbean coast of Honduras.
Material and methods
Areas studied
The data were collected from various
research projects (Fig. 1 and Table 1):
The queen snapper (Etelis oculatus)
is among the deepest dwelling spe-
cies of the family Lutjanidae, and the
only Atlantic species of Etelis. Its dis-
tribution covers the tropical western
Atlantic Ocean, from North Carolina
to the eastern tip of Brazil, at depths
of 130 to 450 m (Allen, 1985).
Although it reaches a large size
and presents no risk of ciguatoxicity
(Lorance1), the species is exploited by
only a few fisheries in the Caribbean.
Most often it is only a minor part of
the catch of line fisheries that focus
on the whole community of deep snap-
pers, or on more abundant species
such as vermilion snapper (Rhom-
boplites aurorubens) or silk snapper
(Lutjanus vivanus) (e.g., in Venezu-
ela: Mendoza and Larez, 1996). In
a few cases, however, E. oculatus is
specifically sought by fishermen; for
example, in Saint-Lucia within a tra-
ditional fishery operating during the
months when migratory pelagics are
not fished (Murray et al, 1992), or in
Bermuda where it has been caught
irregularly (pulse fishery) since the
ban on potfishing (Luckhurst, 1996).
Commercial exploitation is only be-
ginning in the French West Indies,
but is much more developed in Barba-
dos (Prescod et al., 1996) and Puerto
Rico (Matos-Caraballo, 2000). Exploi-
1 Lorance, P. 1988. La ciguatoxicite des
poissons sur les bancs de Saint-Barthe-
lemy. Saint-Martin et Anguilla. Doc.
Sci. Pole Caraibe 15, 31 p. [Available
from Ifremer, Pointe Fort, 97231 Le
Robert, France.]
Manuscript submitted 16 September 2003
to the Scientific Editor's Office.
Manuscript approved for publication
20 October 2004 by the Scientific Editor.
Fish. Bull. 103:417-425 (20051.
418
Fishery Bulletin 103(2)
Figure 1
Study area and locations sampled for queen snapper {Etelis oeulatus) by Caribbean fisheries
1982-2001.
1) On the French parts of the wide shelf shared by St-
Martin, St Barthemely, and Anguilla (abbreviated
as SMSBA shelf in the text), exploratory fishing
experiments were conducted to assess the fishing
potential and the risk of ciguatoxicity (Lorance2).
The deep slopes of the bank (200-300 m) were fished
in 1986-87, using bottom longlines, trammel nets,
and secondarily bottom gill nets.
2) In Martinique, exploratory fishing experiments were
conducted in 1986-87 on various parts of the shelf
slope (100-300 m), and some observations were
made in 1982 and 1988-91, mainly with gill nets
and trammel nets (Guillou3).
3) In Saint-Lucia, observations were made in 1987 on
the commercial fishery, and fishing experiments
were conducted in 1992 with longlines (Guillou4).
4) In Dominica, fishing experiments were conducted in
1992 with longlines and gill nets.
5) In Guadeloupe, experiments were conducted in 2001
with gill nets in the range 200-400 m (Diaz et al.,
in press); some small Etelis were also caught with
10-mm-mesh traps used for a survey of deep crus-
tacean resources.
6 1 In the Bay Islands, off the Caribbean coast of Hondu-
ras, a fisheries survey was conducted in 1999-2000
as part of a coastal zone management project (Ber-
thou et al.5). This artisanal fishery uses mainly han-
dlines to catch snappers and groupers on the shelf,
but a fraction of the fishing effort is directed towards
the deepwater snappers on the shelf slopes.
7) In Honduras, the landings of the semi-industrial
fishing fleet based in Roatan (Bay Islands) were
studied, through catch statistics of the export firms
and by sampling in the collecting centers (de Rodel-
lec6). These fleets target snappers and groupers over
the entire Caribbean shelf of Honduras, and fish
with handlines.
2 Lorance, P. 1989. Ressources demersales et descriptions des
pecheries des bancs de St-Martin et St Barthelemy. Rapp.
Int. Dir. Ressources Vivantes Ifremer, DRV-89.039-RH/Mar-
tinique, 75 p. [Available from Ifremer, Pointe Fort, 97231
Le Robert, France.]
3 Guillou, A. 1989. Ressources demersales du talus insu-
laire de la Martinique. Rapp. int. Dir. Ressources Vivantes
Ifremer DRV-89.037-RH/Martinique, 121 p. [Available from
Ifremer, Pointe Fort, 97231 Le Robert, France.]
4 Guillou A., A. Lagin, and P. Murray. 1996. Observations
realisees sur la biologie et la peche du «gros yeux« Etelis
oeulatus Val. aux Petites Antilles de 1982 a 1992. Doc. Sci.
Pole Caraibe 33, 137 p. [Available from Ifremer, Pointe
Fort, 97231 Le Robert, France.]
5 Berthou P., M. D. Oqueli, E. Lopez, B. Gobert, C. Macabiau,
and P. Lespagnol. 2001. Diagnostico de la pesca artesanal
de la Islas de la Bahia, Honduras. Proyecto Manejo Ambi-
ental de las Islas de la Bahia (PMAIB), Informe Tecnico
PES-06, vol 1, 194 p. [Available from PMAIB, Roatan,
Islas de la Bahia, Honduras.]
6 de Rodellec, A. 2001. Les debarquements de poissons
destines a l'exportation dans l'ile d'Utila (lies de la Bahia,
Honduras). Unpubl. report, IRD-Brest, 51 p. [Available
from IRD, BP 70, 29280 Plouzane, France.]
NOTE Gobert et al.: Biology of Etelis oculatus in the Caribbean
419
Table 1
Summary of sample sizes and depth ranges of queen snapper {Etelis oculatus) by area
mercial fishing operations ( SMSBA=Saint Martin-Saint Barthelemy-Anguilla).
and fishing gear, in
exploratory or corn-
Area
Trammel nets
(exploratory)
Gill nets
(exploratory
Lines
(exploratory)
Lines
(commercial)
Depth range
(ml
Martinique
300
209
6
140-300
SMSBA shelf
249
406
230-430
Saint-Lucia
34
394
210-290
Dominica
191
20
180-300
Guadeloupe
Bay Islands
Honduran shelf
1133
794
3948
195-410
unknown
unknown
Fishing gears used
In all islands but Guadeloupe, gill nets had mesh sizes
of 65 mm (knot to knot) and a stretched height of 6.4 m.
In Guadeloupe, mesh was 60 mm and height was 4 m;
in addition, the nets were given more slack than in
Martinique to increase their efficiency, and thus caught
a wider size range offish.
Trammel nets had mesh sizes of 40 mm (knot to knot)
on the central panel and 200 mm on the outer panels,
and were 2 m high. All nets (trammel nets and gill
nets) were set overnight (15 to 20 hours of fishing time)
in units of 200 or 300 m.
Three types of longlines were used in the fishing ex-
periments. Vertical longlines were derived from those
used by fishermen in the Lesser Antilles and had about
20 hooks on 40 cm-long secondary lines. Pole longlines
were adapted from a technique used in Florida and
Puerto-Rico: poles about 2 m long are fastened to the
main line lying on the bottom, each having 12 to 25
hooks on very short secondary lines (20 to 30 cm). Re-
inforced longlines are horizontal longlines whose main
line is heavier, in order to fish on very rough grounds.
All longlines were hauled after 30 to 45 minutes fish-
ing. For the analysis, no distinction was made between
samples of these three types of longlines. Various kinds
of longlines are used in the small-scale queen snap-
per fishery in Saint-Lucia. Handlines used in the ar-
tisanal and semi-industrial Hondurian fisheries are
either mono- or multifilament, and bear one or several
hooks. No detailed observations were made on the size
of hooks or on the bait used in the commercial queen
snapper fisheries.
1987) could be done reliably in the field for adults and
juveniles, but had to be confirmed under the microscope
for the smallest individuals (less than 10 cm). Fish
length was the only information recordable from profes-
sional landings (St-Lucia, Honduras); fishing experi-
ments yielded more detailed data, by order of decreasing
frequency: length (fork length FL, total length TL, or
both; unless specified, all lengths mentioned in the
text are fork lengths), weight, and sexual stage, and
occasionally a few additional observations (such as
unusual number or length of fin rays). Sexual stages
were identified by using the macroscopic scale defined
by Barnabe (1973) and were coded as follows: 1 (imma-
ture, without identifiable sex), 2 (immature, of identifi-
able sex), 3 (mature), 4 (prespawning), 5 (spawning),
6 (postspawning), and 7 (resting). Depth was recorded
only in the fishing experiments; for gillnet and tram-
mel-net stations, it was measured at each end of the net,
and the depth used in the analysis was the average of
these two values.
Length-frequency analysis
In most cases, length-frequency analysis was strongly
hindered by gear selectivity and sample sizes. We
attempted to estimate L, and ZIK with the method
of Wetherall et al. (1987) applied to the sample of the
semi-industrial Hondurian fishery. All other samples
were unsuitable for length-frequency analysis because
of severe violations of one or several assumptions, prin-
cipally regarding constant catchability above the full
selection length, which was obviously not the case for
the three gears used in the fishing experiments.
Data collected
None of these studies was specifically designed for
the study of E. oculatus, and therefore the nature and
amount of available information (sampling coverage
though time, space, and depth) for this species were
variable. Species identification (Allen, 1985; Anderson,
Results
Depth distribution
During the fishing experiments, E. oculatus of market-
able size (i.e., larger than about 20 cm) were caught
420
Fishery Bulletin 103(2)
between 140 and 430 m. In Martinique, the
trammel nets were set between 100 and 300 m
but did not catch any E. oculatus in the shal-
lowest part of this range. In Guadeloupe, gill
nets were set down to 410 m, but the deepest
catch of queen snapper was 340 m. No E.
oculatus were caught in shallower (<80 m)
fishing experiments with any of the gears
used (traps, gill nets, trammel nets, and long-
lines) on the SMSBA shelf. According to some
local fishermen, however, queen snappers can
be caught from about 100 m down to 550 m
(Lorance2).
Depth-size relationship
i
u
c
/u ■
60 -
50 -
A
D
•
A
A
•
•...■•■
■A ..a.
* *■ ■ A
A
A
o
CO
40 -
30 -
A
■
■
6 ■ -
A
>
<
?0 -
100
150
200
250 300
Depth (m)
350
400
450
No clear relationship between depth and aver-
age size offish was found in the fishing experi-
ments (Fig. 2). This is not unexpected given
the selectivity of some gears (gill nets) and
the small sample sizes in most depth strata
outside the main fishing range (250-300 m);
70% of the 456 fish caught by longlines were in the 290
m depth stratum, and five or fewer fish were caught in
most of the other strata.
A different picture emerges from the analysis of the
professional fisheries of Honduras. Multivariate analy-
sis (principal component analysis followed by hierar-
chical classification) applied to the landings by species
revealed the two different categories of fish caught by
the two types of semi-industrial vessels operating from
Roatan (de Rodellec6), the shelf-operating fleet and the
slope-operating fleet. The first category of fish were
dominated by shallow species such as Ocyurus chrys-
urus (59.8%), Lutjanus analis (7.8%), and several grunts
(Haemulidae), whereas E. oculatus accounted for only
2.2%. On the other hand, the second category comprised
mainly deep snappers: L. vivanus (39.6%), E. oculatus
(22.4%), R. aurorubens (6.9%) or L. buccanella (1.9%).
The two divisions of the fleet independently exploit the
continental shelf and the deep slope. Although actual
depth of fishing operations is unknown, the shelf-oper-
ating fleet probably catches E. oculatus in the deepest
part of its working area (i.e., at the shallowest part of
the species' bathy metric range), whereas the slope-op-
erating fleet exploits the main habitat of the deepwater
snappers. The size structures of Etelis catches (Fig. 3, A
and B) strongly indicate that only the fish up to 45-50
cm live on the shelf or its edge, whereas individuals of
all sizes, and particularly the largest ones, inhabit the
shelf slope.
A similar observation was made for the island of
Roatan, where the artisanal fleet is the least developed
of the archipelago: fishermen using small (<6 m) and
often (57%) nonpowered canoes fish quite close to the
shore and catch a large diversity of coastal reef fishes,
a large proportion of which are juveniles. Etelis oculatus
is rarely caught by these small-scale fishermen but is
so only as individuals smaller than 50 cm, sometimes
as small as 16 cm (Fig. 3C).
Figure 2
Average fork length of queen snapper {Etelis oculatus) by depth (m)
strata in the fishing experiments with gill nets (circles), trammel
nets (squares), and lines (triangles). Sample sizes are indicated
by size of the symbols: empty symbol (rc<10), filled symbol by
increasing size (/i = ll-20, 21-50, 51-100. >100).
Habitat of early juveniles
Some observations were made on very small (smaller
than 10 cm) individuals of E. oculatus. Off Guadeloupe,
a few of them were entangled in gill nets at 300 m depth
(Fig. 3D); on the same island, previous exploratory fish-
ing operations with small-mesh traps caught six juve-
niles ranging from 5.5 to 7 cm FL at 490 m depth; off
Dominica, one small individual (8.5 cm TL) was found
in the stomach of a predator caught at a depth greater
than 200 m (see below). In spite of the general tendency
of increasing size with depth found for the larger indi-
viduals, these observations show that the habitat of
early postsettlement juveniles is not restricted to the
shallowest part of the species depth range.
Morphometric relationships
The main morphometric relations were computed from
the fish sampled in commercial or scientific fishing
operations in the Lesser Antilles (Martinique, Saint-
Lucia, SMSBA shelf). Because the differences between
relations for males and females were insignificant, only
global equations are given (Table 2).
Maximum size and weight
The largest individual caught was 90 cm FL in the
Lesser Antilles (Guadeloupe) and 86 cm in Honduras,
and the maximum weight recorded was 6280 g, in the
Lesser Antilles; fish were not weighed individually in
Honduras.
Sex-related length differences
When sex was recorded, the largest fish were always
female, and no male was found above 70 cm. The differ-
ence between size-structure of male and female catches
NOTE Gobert et al.: Biology of Etelis oculatus in the Caribbean
421
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90
6 i
5
4 -
3
2 -
1
0
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90
FL (cm)
Figure 3
Length-frequency distributions for queen snapper {.Etelis
oculatus) catches. (A) Semi-industrial deepwater Hon-
durian line fishery (rc=3415). (B) Semi-industrial shal-
low-water Hondurian line fishery (n=387). (C) Artisanal
line fishery of Roatan (Honduras) (ra=52). (D) Gillnet
exploratory fishing in Guadeloupe (rc=779). (E) Trammel-
net exploratory fishing in all areas: males (h=231). (F)
Trammel-net exploratory fishing in all areas: females
(n=227).
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90
FL (cm)
Figure 3 (continued)
was particulary clear for trammel nets (Fig. 3, E and
F): the mode corresponding to fish gilled in the small-
mesh central panel had similar characteristics for both
sexes (range 25-45 cm and peak at 36 cm), as opposed
to the diffuse mode for fish >45 or 50 cm (predominantly
females) entangled in the large-mesh outer panels. With
many fewer fish («=23 for both sexes), the longline sam-
ples showed a similar difference between sizes of males
(maximum 55 cm, mean 43.8 cm) and females (maximum
71 cm, mean 51.8 cm). In Guadeloupe, the sex offish was
not determined, but the existence of two modes in the
overall size structure of gillnet catches (Fig. 3D) could
possibly be related to this sex-related length difference.
Growth and mortality
The data collected in the various surveys did not
allow any reliable analysis of the growth of E. ocula-
tus. Because growth may be different for males and
females, the length-frequency distributions of the large
samples (where sex was not determined) from Honduras
could not be processed rigorously to estimate life-history
population parameters. However, in order to provide
preliminary information on such a little known species,
the regression method of Wetherall et al. (1987) was used
in the modified version of FiSAT (Gayanilo et al., 1996)
to estimate Lx and Z/K. With a satisfactory fit of the
regression line (r=0.986), the estimates were L, = 90.57
cm and Z/K = 3.73. For the reason mentioned above
(together with other weaknesses related to possible
violations of the hypotheses underlying the regression
422
Fishery Bulletin 103(2)
Table 2
Morph
jmetric relationships established for
queen snapper
tEtelis oeulatus).
Parameters
Equation
Sample size
r
FL(cm)-TL(cm)
TL = 2.7458 + 1.1644 x FL
842
0.987
TL (cm) - FL (cm)
FL = -1.0028 + 0.8368 x TL
842
0.987
FL(cm)-Wlg)
W = 0.02748 x FL28348
499
0.990
TL(cm)-W(g)
W = 0.03006 x FL2 a"?
487
0.990
method), these estimates have to be seen only as indica-
tions that the asymptotic length of E. oeulatus is quite
large and that the Hondurian population is moderately
exploited (if M = 2K, as suggested by Ralston (1987) for
snappers, then ZIK = 3.73 and E = F/Z = 0.46).
Reproduction
Macroscopic observations of gonads were recorded for
309 fish whose sex could be identified (118 males and
191 females); all stages of the reproductive cycle were
observed, but only 20 individuals were in the prespawn-
ing to postspawning stages, and a single one was found
to be in the process of spawning.
The smallest fish with developing gonads was 36 cm
for females and 29 cm for males (Fig. 4). Although
only part of the length range of males was adequately
sampled (100 out of the 118 fish were smaller than 44
cm I, it appears that the progressive build-up of the
reproductive male population occurs between about 30
cm and 45 cm. The picture is clearer for females, whose
sample size was larger and more evenly spread over
the length range: above 54 cm, all females were found
to be in a reproductive cycle. The maturing process
therefore occurs at clearly lower sizes for males (30-45
cm) than for females (35-55 cm). Females in advanced
reproductive stages (postspawning and resting stages)
were observed across the length range, including the
smallest adult sizes, those below 45 cm (Fig. 4).
A full analysis of the seasonality of reproduction is
not possible because data were collected in only seven
months, out of which only four (May, June, November,
and December) yielded samples large enough for the
analysis (21 to 72 females per month). No females were
found to be spawning, but most of the pre- and post-
spawning stages (14 out of 17) were observed in Novem-
ber and December, and half of maturing females were
fished during the last quarter of the year (Fig. 5). How-
ever, 74% of females at sexual rest (resting stage) were
caught in May and June. Additional pieces of informa-
tion confirm this pattern: the only spawning individual,
a male, was observed in November (Dominica); females
gonads in advanced stage of vitellogenesis were observed
in September (Guadeloupe); no mature individual was
found in Honduras in April-June. These observations
show that an active spawning period occurs at the end
of the year (even if all fish caught at this period were
not close to the spawning phase), as opposed to late
spring which is a period of sexual inactivity.
Such limited results leave open the overall interpre-
tation of the annual reproductive cycle of E. oeulatus.
In particular, according to the fishermen working on
the SMSBA shelf, the species could have an extended
spawning season, lasting from November to April or
May.
Predators and prey
No systematic observations were made on the trophic
relationships of E. oeulatus, but a few occasional record-
ings were made of its predators and prey. The only record
of a predator was that of a beardfish {Polymixia lowei:
Polymixiidae) measuring 40 cm TL containing a very
small queen snapper (8.5 cm TL) and which was caught
deeper than 200 m. This is the first record of such a food
item for this beryciform fish whose diet had so far been
reported to comprise cephalopods (Cervigon, 1991). The
stomachs of E. oeulatus that could be observed were most
often empty; on a few occasions, unidentified squids were
the only items present. This was the case for three fish
(58 to 62 cm) caught at 430 m depth.
Discussion
Etelis oeulatus was found on the upper part of the con-
tinental and insular slopes, from about 150 to 450 m;
this observed range confirms previous indications (Allen,
1985), but the bathymetric distribution of the species
could possibly extend beyond the maximum depth fished
in these surveys. The presence of E. oeulatus in shal-
lower waters of the shelf seems possible, according to a
statement that juveniles can be found in less than 30 m
(Appeldoorn et al., 1987) and to the reported catch of one
fish (size not recorded) at 59 m depth by a trawl survey
off southeastern United States (Cuellar et al., 1996).
However the present data, other fishery-independent
surveys focusing on snappers (i.e., Marcano et al., 1996,
down to 128 m), and most studies on Caribbean coastal
fisheries strongly indicate that the species is very rare
on the shelf itself.
Within the observed depth range, there is a ten-
dency for the largest fish to be found in the deeper
areas, as observed in the closely related Pacific species
NOTE Gobert et al.: Biology of Etelis oculatus in the Caribbean
423
E. carbunculus and E. coruscans (Brouard and
Grandperrin"), other deepwater lutjanids (Board-
man and Weiler, 1980; Cuellar et al., 1996), and
many reef fish species. The maximum size recorded
for large samples (90 cm FL) is much greater than
the 60 cm TL indicated by Allen (1985) but is con-
sistent with other field observations, such as 94 cm
TL in Saint-Lucia (Murray, 1989) or 100 cm TL in
Venezuela (Cervigon, 1991).
No reliable growth estimate could be obtained be-
cause males and females showed very different size
structures, and the only data suitable for length-fre-
quency analysis were data for which the sexes had
not been determined.
Important differences were found between sexes in
terms of size structure and maturation size. Male E.
oculatus attain a smaller length than females, and
are much rarer above 45 cm. Sex-ratios skewed in
favor of females in large size classes were observed
in the most complete studies of snapper populations
(Grimes, 1987), including Pacific deepwater snap-
pers (Brouard and Grandperrin7), and probably re-
sult from a difference in growth and mortality be-
tween the sexes; in Cuba, for instance, females of
most snapper species have been found to grow faster
than males (Claro and Garcia-Arteaga, 2001). In
the present study, sex-specific growth and mortality
estimates were not available, but our interpretation
seems likely because other possible causes could be
ruled out, such as selectivity of nets (morphometric
relationships are identical for both sexes) and fish be-
havior in relation to fishing gear (differences between
sexes, however, were observed in trammel nets and
lines whose catch mechanism is completely different).
Different habitat preferences, which can lead to sex-
related size structures in reef species (Garcia-Cagide
et al., 2001), seem unlikely in our study because the
deep slopes have fewer habitat gradients than the
shallower reef environments and because no relation
was found between depth and sex-ratio. A similar
difference between males and females was found for
reproductive size. Male snappers generally mature at
a slightly smaller size than females, but sex does not
appear as a significant factor of variation for relative
length at first reproduction, as opposed to depth or
continental or insular habitat (Grimes, 1987).
In the Lesser Antilles, E. oculatus spawns at the end
of the year and has a period of sexual rest during from
late spring through early summer. These results are
not sufficient to establish the entire annual reproduc-
tive pattern, and even these partial findings cannot be
applied to other parts of the Caribbean because snap-
per populations of continental and insular shelves gen-
erally show different seasonal patterns of reproduction
(Grimes, 1987). This indication of a spawning period
for E. oculatus in the cold season contrasts with the two
eteline species (Aprion virescens and E. coruscans) stud-
ied in Hawaii, which have a protracted spawning period
extending through the summer (May or June through
October or November) (Everson et al., 1989).
26 30 34 38 42 46 50 54 58 62 66 70 74
100%
80%
60°
40%
20%
0%
B
~3i
26 30 34 38 42 46 50 54 58 62 66 70 74
FL (cm)
Figure 4
Proportion of sexual stages by 2-cm length classes for
(A) female (n=191) and (B) male (/; = 118 ) queen snapper
iEtelis oculatus): immature fish (gray), maturing fish
(large squares), prespawning (horizontal bars), spawn-
ing (oblique bars), postspawning (vertical bars), sexual
rest (black). Empty areas indicate the absence of data for
the length class.
□ April
sexual rest
postspawning
spawning
prespawning
maturation
immature
as
HMay
111
sss mil
sssssss:
DJune
B August
■ September
□ October
U November
U December
iim
(
Distribution o
latus) by mont
) 20 40 60 80 100 %
Figure 5
"sexual stages of queen snapper (Etelis ocu-
h.
Brouard, F., and R. Grandperrin. 1985. Les poissons pro-
fonds de la pente recifale externe a Vanuatu. South Pacific
Commission, r7<"me conference technique regionale des peches,
Noumea (Nouvelle Caledonie) 5-9 August 1985. SPC/Fish-
eries 17/WP.12 , 131 p. [Available from SPC, BP D5, 98848
Noumea Cedex, New-Caledonia, France.]
424
Fishery Bulletin 103(2)
The data collected in these studies did not allow the
analysis of the aggregation pattern of E. oculatus. In
the Pacific, E. coruscans was found to form feeding ag-
gregations near underwater promontories and these ag-
gregations had important consequences for catchability
(Ralston et al., 1986). For the deeper living alfonsinos
(Beryx spp.) and orange roughy (Hoplostethus atlanti-
cus), fisheries have shown their ability to quickly fish
down aggregations once they are discovered (Lorance
and Dupouy, 2001). Added to "K-selected" life-history
strategies (high longevity, slow growth, late reproduc-
tion) and irregular recruitment, this aggregating behav-
ior reinforces the vulnerability of deepwater species to
overfishing (Koslow et al., 2000).
Recently gained knowledge about the exploitation of
seamount and deep bank fish resources (Clark, 2001)
cannot be applied directly to E. oculatus and the other
slope-dwelling snappers which, although they are the
deepest dwelling species of the family, are much closer
in terms of demographic strategy to their shallow rela-
tives (longevity 10-20 years; Manooch, 1987) than to
these truly deep species (longevity 50 to more than 100
years; Koslow et al., 2000). However, less extreme life
history traits do not protect deep snappers against over-
fishing, as shown by the example of E. coruscans and
E. carbunculus in Hawaii (Simonds, 1995). The limited
fishery data available on E. oculatus in the Caribbean
do not seem to show evidence of a similar situation so
far, but the stocks are being increasingly fished without
much scientific basis (i.e., catch statistics) for manage-
ment (Mahon, 1990; FAO, 1993). Regulation measures
continue to be defined (Diaz et al., in press), but so far
they are based only on conservative rules of thumb
because of a lack of reliable biological information. To
address this lack of information, future research on E.
oculatus therefore should address, in particular, sex-
specific growth, reproductive biology, and fine-scale
distribution patterns.
Acknowledgments
The data presented here were collected and processed
with the help of many people; the authors particularly
wish to thank E. Burgos, T. and J. Chapelle, R Galera,
J. Grelot, A. Lagin, P. Lespagnol, L. Reynal, J. Robin,
B. Seret, and the Chief Fisheries Officers of Dominica
and Saint-Lucia.
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Ralston, S., R. M. Gooding, and G. M. Ludwig.
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fishing) at Johnston atoll. Fish. Bull. 84:141-155.
Simonds, K.
1995. Federal state cooperation in managing deepwater
bottom fish in Hawaii. South Pacific Commission work-
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ies, Noumea (New Caledonia), 26 Jun-7 Jul 1995. South
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426
Courtship and spawning behaviors of
carangid species in Belize
Rachel T. Graham
Wildlife Conservation Society
P.O. Box 37
Punta Gorda, Belize
E-mail address: rgraham@wcs.org
Daniel W. Castellanos
Monkey River Village
Toledo District, Belize
Many species of reef fish aggre-
gate seasonally in large numbers
to spawn at predictable times and
sites (Johannes, 1978; Sadovy, 1996;
Domeier and Colin, 1997). Although
spawning behavior has been observed
for many reef fish in the wild (Wick-
lund, 1969; Smith, 1972; Johannes,
1978; Sadovy et al., 1994; Aguilar
Perera and Aguilar Davila, 1996),
few records exist of observations on
the courtship or natural spawning for
the commercially important family
Carangidae (jacks) (von Westernha-
gen, 1974; Johannes, 1981; Sala et
al., 2003). In this study, we present
the first observations on the natural
spawning behavior of the economi-
cally-valuable permit (Trachinotus
falcatus) (Linnaeus, 1758) from the
full to new moon period at reef prom-
ontories in Belize, with notes on the
spawning of the yellow jack (Caran-
goides bartholomaei) (Cuvier, 1833),
and the courtship of five other caran-
gid species.
Permit belong to the family Ca-
rangidae and are broadly distrib-
uted in the western Atlantic Ocean
from Massachusetts to southeastern
Brazil, including the Caribbean Sea
and Gulf of Mexico (Smith, 1997).
Considered an inshore pelagic species
(Valdez Munoz and Mochek, 2001)
that spawns offshore, permit utilize a
range of habitats that include coastal
mangroves and seagrass beds, reef
flats, and fore-reef areas during their
life-cycle (Crabtree et al., 2002). Per-
mit are reported to feed during the
day and may show similar feeding
characteristics to the closely related
T. carolinus that displays a clear cir-
cadian rhythm entrained to the light
phase during its feeding period (Heil-
man and Spieler, 1999). According to
otolith analysis of fish caught in Flor-
ida, permit live to at least 23 years
and reach a maximum published fork
length of 110 cm and a weight of 23
kg (Crabtree et al., 2002). 12 Permit
are gonochoristic and Crabtree et al.
(2002) recorded 50% sexual matu-
rity for females at 547 mm FL or 3.1
years and males at 486 mm FL and
2.3 years. Permit exhibit a protract-
ed spawning season from March to
September in Cuba ( Garcia- Cagide et
al., 2001) and from March to July in
Florida (Crabtree et al., 2002). High
gonadosomatic indices recorded for
March and maturation of oocytes
noted in late June- July (Crabtree et
al., 2002) support the observations by
Garcia-Cagide et al. (2001) that per-
mit are batch spawners and have an
asynchronous cycle of vitellogenesis.
Spawning cued by the full moon has
been recorded in many species of reef
and inshore fish (Johannes, 1978,
1981; Moyer et al., 1983; Crabtree,
1995; Hoque et al., 1999). Macro-
scopic gonadal analysis and observa-
tions on the timing of courtship and
spawning in several carangid species
in the wild (Johannes, 1981; Sala
et al., 2003), coupled with gonadal
sampling observations on the cap-
tive spawning behavior of the related
bluefin trevally (Caranx melampygus)
(Moriwake et al., 2001), further indi-
cate that permit and other carangids
display circa lunar periodicity when
spawning naturally.
Permit represent a valuable re-
source for recreational fishermen
throughout their range. In Florida,
recreational fisheries land more than
100,000 fish per year, but declines in
landings from 1991 to date prompted
regulation (Crabtree et al., 2002) and
a move towards catch-and-release of
fish. As such, Belize is rapidly be-
coming known as a world-class fly-
fishing location due to its abundance
of permit. The fishery is highly lucra-
tive; flynshers pay up to US$500 per
day in Belize to catch and release a
permit. This niche tourism industry
has also become an economic alter-
native for local fishermen (Heyman
and Graham3). Consequently, infor-
mation on the timing and behavior of
reproduction of permit can underpin
conservation efforts that focus on a
vulnerable stage in their life cycle.
1 The IGFA (International Game Fishing
Association) notes a record length for
permit of 122 cm FL. 2001. Database
of IGFA angling records until 2001.
IGFA, Dania Beach, Florida, 33004.
2 The United Nations notes a maximum
weight of 36 kg for a permit. (Cervigon,
F., R. Cipriani, W. Fischer, L. Garib-
aldi, M. Hendrickx, A.J. Lemus, R.
Marquez, J. M. Poutiers, G. Robaina
and B. Rodriguez. 1992. Fichas FAO
de identificacidn de especies para los
fines de la pesca. Guia de campo de las
especies comerciales marinas y de aquas
salobres de la costa septentrional de Sur
America, 513 p. FAO. Rome.
3 Heyman W. D., and R. T. Graham.
2000. The voice of the fishermen of
Southern Belize, 44 p. TIDE (Toledo
Institute for Environment and Devel-
opment), P.O. Box 150, Punta Gorda,
Belize.
Manuscript submitted 9 December 2003
to the Scientific Editor's Office.
Manuscript approved for publication
9 November 2004 by the Scientific Editor.
Fish. Bull. 103:426-432 (2005).
NOTE Graham and Castellanos: Courtship and spawning behaviors of carangid species in Belize
427
Materials and methods
Turneffe Elbow (17°09'N, 87°54'W) and Gladden Spit
(16°35'N, 88°00'W) are two sites located on the Belize
Barrier Reef that were monitored for abundance and
behavior of many species of spawning reef fish between
1999 and 2002. Both sites are promontories with a slop-
ing reef shelf that drops off steeply at a depth of 35-45
m to over 1000 m into the southern tip of the Cayman
Trench. According to the spawning aggregation criteria
developed by Domeier and Colin (1997), Turneffe Elbow
and Gladden Spit attract, respectively, an estimated 13
and 27 species of reef fish that aggregate seasonally to
spawn (Graham, 2003).
We logged over 270 hours of underwater monitoring
of reef fish spawning aggregations at Turneffe Elbow
and Gladden Spit, primarily from the full-moon to the
new-moon from March to July from 2000 through 2002.
Additional dives took place variously over the course of
3-5 days during the same lunar period from 1999 to
2002. Most dives for monitoring spawning aggregations
took place between 0830 and 1100 hours, at midday,
and between 1600 to 1730 hours of each diving day.
Dives began 150-250 m north of both spawning aggre-
gation sites and proceeded to the south along the reef
platform edge. Dive depth usually began at about 30 m
and decreased to 15 m as the dive progressed because
of SCUBA decompression constraints. Dives normally
lasted between 35 and 50 minutes. Horizontal and ver-
tical visibility rarely dropped below 20-25 m.
Results and discussion
During 10 dive surveys (15 diving hours) at Turneffe
Elbow, we observed a large school of 250 to 500 permit
aggregating on the reef promontory (Table 1). The
aggregated fish slowly swam into the south current
along the south-facing sloping fore-reef shelf at 5-15 m
depth and the steep drop-off located at -30-35 m.
The school streamed down to the spur and groove for-
mations at about 20 m depth on the reef shelf and rose
up into the upper water column again. Permit were
loosely grouped and displayed little fear of divers, a
behavior commonly observed among a range of other
fish species that aggregate to spawn (Graham, 2003).
Several individuals displayed a dark patch located above
and behind the pectoral fin on both flanks. Permit dis-
played this same behavior coloration change during
each encounter.
On 22 August 2000, 7 days after the full moon, at
-1730 (41 minutes before sunset at 1811 hours local
time) we conducted our standard north to south fish
census dive at a depth of -20-30 m along the fore-reef
drop off. During all dives horizontal and vertical visibil-
ity was at least 20 m and often over 40 m. We observed
a school of -300 permit descend from 5-15 m depth
above the fore-reef drop-off to 25 m directly on the shelf
edge. At -1745 hours (26 min before sunset) within-
group activity increased as permit schooled densely on
the edge of the reef drop-off. At -1750 hours, a subgroup
of eight permit left the dense school and ascended in
the water column to -18 m depth. The lead individual
initiating the ascent was -100 cm FL and was pursued
by seven fish ranging from -55 to 75 cm FL. The pursu-
ing fish nuzzled the larger fish's vent as it rose in the
water column. All fish displayed a dark flank patch
behind their pectoral fins. The lead permit then ceased
its ascent at -15 m, tilted its head down slightly and
convulsed rapidly, releasing a puff of gametes. Pursu-
ing permit tried to position their vents as closely as
possible to the lead individual's while releasing their
gametes. The resulting gamete cloud was less than 50
cm in diameter and dispersed within seconds (Fig. 1).
Following gamete release, all fish descended quickly to
the main school still located -25 m below. Within mo-
ments this behavior was repeated and observed in two
smaller groups of permit before all observations ceased
because of a lack of light.
At Gladden Spit, we observed slightly different permit
spawning behavior. On 7 April 2002 (10 days after the
full moon), the aggregation remained in a restricted
area -100 m north of where we previously witnessed
the spawning of several species of fish and -30 m east
of where we have also observed groupers Epinephelus
striatus, Mycteroperca tigris, M. venenosa, and M. bonaci
aggregate to spawn (Graham, 2003). Ambient water
temperature was 27.7°C as measured by a temperature
logger (Onset Corp. Tidbit data logger) moored at the
spawning site at 30 m depth.
At least 300 permit — many of them large individuals
(-70-90 cm FL)— schooled densely into a ball at -1700
hours (66 minutes before sunset local time) near the
reef shelf drop-off at a depth of -40-48 m. Subgroups
comprised five to nine fish, and the lead fish was much
larger than the pursuers. Subgroups rapidly rose up on
the periphery of the school, spawned at the apex of the
aggregation, and descended towards the bottom of the
school again. Spawning was more frenetic than that
observed at Turneffe Elbow. Permit subgroups behaved
in the same manner as that observed at Turneffe dur-
ing spawning, and all spawning individuals displayed a
large dark flank patch behind the pectoral fins.
Based on our observations of courtship and spawn-
ing behavior, our estimate of spawning season for per-
mit in Belize may stretch from February to the end of
October, beyond the period of March to September as
suggested by Garcia-Cagide et al. (2001) and Crabtree
et al. (2002). Permit may also reach larger sizes than
published by Crabtree et al. (2002); we estimated the
largest individual permit observed at Turneffe Elbow
in Belize to be -120 cm FL, which may indicate that
permit exceed a lifespan of 23 years.
We could not determine if the lead permit was fe-
male and the pursuing permit were males because no
individuals were caught for gonadal analysis. However,
carangids are gonochoristic and it is highly likely that
the lead fish in the spawning rush was female. Garcia-
Cagide et al. (2001) noted that spawning females are
often larger than mature males in several species of
428
Fishery Bulletin 103(2)
Figure 1
Subgroup of eight permit [Trachinotus falcatus) immediately following spawning at Truneffe
Elbow, Belize. The subgroup detached itself from the main aggregation to spawn in midwater
at -15 m. The larger fish led the ascent to 15 m; all fish in the subgroup hovered at that
depth, released gametes, and returned to the main school at a depth of -25 m. The arrow
indicates the dark patch behind the pectoral fin that each fish sports during spawning.
reef fish. This is also supported by our observations
of gonochoristic spawners such as the cubera snapper
(Lutjanus cyanopterus) and the dog snapper (L. jocu)
that display a pattern of group, broadcast spawning
where larger females are swollen with roe and lead the
subgroup spawning ascents (Graham, 2003).
Group spawning behavior in the yellow jack (C. bar-
tholomaei) closely resembled that of permit. We recorded
yellow jacks schooling at Gladden Spit on only two occa-
sions (Table 1). On 7 April 2002, we observed that the
yellow jacks spawned at -1705 hours (61 minutes before
sunset local time) at Gladden Spit, less than 50 m south
of the school of spawning permit. The jacks schooled
densely at -40-45 m and subgroups of 5 to 8 fish de-
tached themselves from within the school, ascending
rapidly to -35 m, releasing gametes at the apex, and
descending into the school again. Observations ceased
shortly thereafter because of depth constraints and
decreasing light.
Not all species of carangids are group spawners. Pair
spawning has been observed in species such as C. igno-
bilis and Alectis indicus in the Pacific (von Westernha-
gen, 1974) and C. sexfasciatus in the Gulf of California
(Sala et al., 2003). We have also observed on numerous
occasions pair courtship in crevalle jack (C. hippos),
horse-eye jack (C. latus), and bar jack (Carangoides
ruber) in schools exceeding 1000 fish, in rainbow run-
ner iElagatis bipinnulata) in schools of up to -300 fish,
and occasionally greater amberjack (Seriola dumerili)
in schools numbering -120 individuals, primarily fol-
lowing during the full-moon and waning moon periods
between February and October (Table 1). These five
species displayed extended pair courtship within and
outside a large aggregation of conspecific fish as they
swam along the edge of the reef drop-off. All courting
pairs observed showed similar behavior. The chasing
fish nuzzled the gonopore of the lead fish (whose head
and upper body half had turned black but whose fins
were lighter, Fig. 2, A and B) during prolonged chases,
often swimming close to and at a perpendicular angle to
the lead fish. Seriola dumerili also displayed dichroma-
tism; the pursuing fish turned a vivid electric blue and
exhibited a scrawled pattern on its upper flanks, simi-
lar to that displayed by the scrawled filefish {Aluterus
senptus). Occasionally, 1-10 individuals that did not
display coloration changes followed the courting pairs.
These five species may also pair spawn because their
courtship behavior parallels that of C. sexfasciatus,
observed by Sala et al. (2003) to spawn in pairs from
the full moon to waning crescent periods from July to
September. However, we did not observe any release of
gametes during all pair courtship behavior.
NOTE Graham and Castellanos: Courtship and spawning behaviors of carangid species in Belize
429
Figure 2
Pair courtship behavior in the horse-eye jack (Caranx latus) at Gladden Spit, Belize. The
pursuing fish often swims slightly behind the lead and their flanks touch. The lead fish (A)
remains silver colored, and the pursuing fish (Bl takes on a very dark coloration around
the head and upper flank during courtship.
Conclusions
Our observations confirm that permit spawn offshore
at reef promontories that support other reef fish spawn-
ing aggregations. Permit demonstrate group broadcast
spawning behavior and spawning events take place
close to sunset. Further observations indicate that other
species of carangids, such as yellow jack are also group
broadcast spawners, occupying the same spatiotemporal
spawning niche as permit. If observed courtship behav-
430
Fishery Bulletin 103(2)
Table 1
Timing and lunar phase of observati
Belize from April 1999 to July 2002.
C = courting and color change; Spaw
ans on the schooling, courtship, and spawning of seven carangids at two reef promontories in
fm = full moon; dafm = days after full moon; dbfm = days before full moon. Sch = schooling;
n = spawning observed.
Date
Dive
start time
Moon phase
Location
Species
Behavior
2 Apr
1999
12:04
2 dafm
Gladden
Yellow jack
Sch
3 Apr
1999
10:25
3 dafm
Gladden
Crevalle
Sch
5 Apr
1999
16:40
5 dafm
Gladden
Crevalle, horse-eye, rainbow runner
Sch
2 May
1999
16:50
2 dafm
Gladden
Bar jack, crevalle
Sch
5 May
1999
5:40
5 dafm
Gladden
Horse-eye, crevalle
Sch, C
30 May
1999
12:45
fm
Gladden
Amberjack, bar jack
Sch, C
3 Jun
1999
9:10
4 dafm
Gladden
Horse-eye, bar jack
Sch
4 Jun
1999
15:30
5 dafm
Gladden
Crevalle
Sch
30 Jun
1999
12:00
2 dafm
Gladden
Bar jack, horse-eye
Sch
27 Sep
1999
16:30
2 dafm
Gladden
Crevalle, amberjack
Sch, C
28 Sep
1999
10:50
3 dafm
Gladden
Crevalle, bar jack, horse-eye
Sch
16:30
3 dafm
Gladden
Horse-eye, amberjack
Sch, C
24 Mar
2000
17:15
4 dafm
Gladden
Horse-eye
Sch, C
17 Apr
2000
16:25
1 dbfm
Gladden
Horse-eye, crevalle
Sch, C
18 Apr
2000
16:25
fm
Gladden
Bar jack, rainbow runner
Sch
19 Apr
2000
17:10
1 dafm
Gladden
Horse-eye
Sch, C
20 May
2000
17:00
2 dafm
Gladden
Crevalle
Sch, C
23 May
2000
16:45
5 dafm
Gladden
Amberjack
Sch, C
24 May
2000
16:21
6 dafm
Gladden
Bar jack
Sch
25 May
2000
-16:30
7 dafm
Gladden
Crevalle
Sch
26 May
2000
16:00
8 dafm
Gladden
Horse-eye, crevalle
Sch, C
23 Jun
2000
17:30
7 dafm
Gladden
Bar jack
Sch, C
18 Aug
2000
15:36
3 dafm
Gladden
Bar jack
Sch
15:36
3 dafm
Gladden
Horse-eye, rainbow runner
Sch, C
19 Aug
2000
-12:00
4 dafm
Gladden
Bar jack, crevalle
Sch
20 Aug
2000
15:00
5 dafm
Turneffe
Horse-eye
C
15:00
5 dafm
Turneffe
Permit
Sch
20 Aug
2000
17:00
5 dafm
Turneffe
Permit
Sch, C
17:00
5 dafm
Turneffe
Amberjack, bar jack
Sch, C
21 Aug
2000
15:00
6 dafm
Turneffe
Crevalle, horse-eye
Sch, C
15:00
6 dafm
Turneffe
Permit
Sch
22 Aug
2000
17:30
7 dafm
Turneffe
Horse-eye
C
17:30
7 dafm
Turneffe
Permit
Spawn
14 Oct
2000
17:30
1 dafm
Gladden
Horse-eye, crevalle
C
15 Oct
2000
17:30
2 dafm
Gladden
Rainbow runner
C
17 Oct
2000
16:30
4 dafm
Turneffe
Horse-eye, crevalle
C
16:30
4 dafm
Turneffe
Permit, amberjack
Sch
18 Oct
2000
16:30
5 dafm
Turneffe
Horse-eye, crevalle, amberjack, permit
C
13 Dec
2000
16:30
2 dafm
Gladden
Horse-eye
Sch
9 Apr
2001
16:00
1 dafm
Gladden
Horse-eye
C
8 May
2001
11:15
1 dafm
Gladden
Crevalle
c
9 May
2001
-10:30
2 dafm
Gladden
Crevalle
Sch
7 Jun
2001
17:00
1 dafm
Gladden
Crevalle, bar jack, horse-eye
Sch
continued
NOTE Graham and Castellanos: Courtship and spawning behaviors of carangid species in Belize
431
Table 1 (continued)
Dive
Date
start time
Moon phase
Location
Species
Behavior
8 Jun
2001
17:00
2 dafm
Gladden
Amberjack, crevalle
horse-eye
Sch, C
9Jun
2001
11:00
3 dafm
Gladden
Crevalle, horse-eye
Sch
10 Jun
2001
17:50
4 dafm
Gladden
Crevalle, horse-eye
Sch, C
3 Oct
2001
-17:00
1 dafm
Turneffe
Horse-eye
C
6 Feb
2002
16:00
9 dafm
Turneffe
Horse-eye, permit
Sch
7 Feb
2002
8:30
10 dafm
Turneffe
Horse-eye, permit
C
16:30
10 dafm
Gladden
Horse-eye, crevalle.
bar jack
Sch
28 Mar
2002
16:48
fm
Gladden
Crevalle, permit
Sch
16:48
fm
Gladden
Horse-eye
C
29 Mar
2002
16:30
1 dafm
Gladden
Crevalle, bar jack, horse-eye
Sch
30 Mar
2002
16:45
2 dafm
Gladden
Crevalle, horse-eye
Sch
31 Mar
2002
16:40
3 dafm
Gladden
Horse-eye
Sch
1 Apr
2002
16:35
4 dafm
Gladden
Bar jack, horse-eye
Sch
3 Apr
2002
9:40
5 dafm
Gladden
Bar jack, horse-eye
Sch
7 Apr
2002
10:30
9 dafm
Gladden
Bar jack
Sch
16:30
9 dafm
Gladden
Permit, yellow jack
Spawn
16:30
9 dafm
Gladden
Bar jack
Sch
6 May
2002
9:40
9 dafm
Gladden
Horse
Sch
27 May
2002
12:18
1 dafm
Gladden
Horse-eye
C
30 May
2002
11:07
4 dafm
Gladden
Horse-eye
Sch
31 May
2002
16:20
5 dafm
Gladden
Crevalle
Sch
1 Jun
2002
16:15
6 dafm
Gladden
Bar jack, rainbow runner
Sch
2 Jun
2002
16:15
7 dafm
Gladden
Bar jack, horse-eye
Sch
29 Jun
2002
12:00
5 dafm
Turneffe
Permit, horse-eye
Sch
1 Jul
2002
15:00
7 dafm
Gladden
Bar jack, crevalle, horse-eye
Sch
ior is included, the spawning season for permit and
horse-eye jacks is protracted from February through
October, and the five other carangid species described
in the present study spawned within this period. Pro-
tection of permit stocks throughout their life cycle, and
particularly during their spawning season, underpins
the associated rapidly growing and economically lucra-
tive flyfishing tourism. Future directions of study should
include a study of permit movement patterns between
feeding and spawning grounds and mortality rates of
catch-and-release fishing.
Acknowledgments
We would like to thank two anonymous reviewers who
provided helpful suggestions for the improvement of this
paper. The fieldwork and observations were supported
by grants from the UK Darwin Initiative and the UK's
Natural Environment Research Council. We worked
under permits provided by the Belize Department of
Fisheries.
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433
Comparison of two approaches for
estimating natural mortality based on longevity*
David A. Hewitt
John M. Hoenig
Virginia Institute of Marine Science
The College of William and Mary
P.O. Box 1346
Gloucester Point, Virginia 23062
E-mail address (for D A Hewitt) dhewittiq'vimsedu
Vetter (1988) noted that her review
of the estimation of the instanta-
neous natural mortality rate (M)
was initiated by a discussion among
colleagues that identified M as the
single most important but least
well-estimated parameter in fishery
models. Although much has been
accomplished in the intervening
years, M remains one of the most
difficult parameters to estimate in
fishery stock assessments. A number
of novel approaches using tagging
and telemetry data provide promise
for making reliable direct estimates
of M for a given stock (Hearn et al.,
1998; Frusher and Hoenig, 2001;
Hightower et al., 2001; Latour et al.,
2003; Pollock et al., 2004). However,
such methods are often impracticable
and fishery scientists must approxi-
mate M by using estimates made
for other stocks of the same or simi-
lar species or by predicting M from
features of the species' life history
(Beverton and Holt, 1959; Beverton,
1963; Alverson and Carney, 1975;
Pauly, 1980; Hoenig, 1983; Peterson
and Wroblewski, 1984; Roff, 1984;
Gunderson and Dygert, 1988; Chen
and Watanabe, 1989; Charnov, 1993;
Jensen, 1996; Lorenzen, 1996).
We are concerned with two ap-
proaches for predicting M based
solely on the longevity of the mem-
bers of a stock — an approach that
can be used when data are not
available to make direct estimates
of the parameter. One is a linear re-
gression model (Hoenig, 1983) and
the other is a simple rule-of-thumb
approach. Hoenig (1983) found that
M was inversely correlated with lon-
gevity across a wide variety of taxa
and recommended use of the follow-
ing predictive equation relating the
maximum age observed in the stock
Umax) to M:
ln(M) = 1.44-0.982xln(?max).
(1)
The rule-of-thumb approach consists
of determining the value of M such
that 100(P)% of the animals in the
stock survive to the age tmax; thus,
M-
-ln(P>
(2)
The challenge in this approach is
determining an appropriate value for
the proportion P.
The rule-of-thumb approach has
the potential to be used widely be-
cause it is presented in Quinn and
Deriso (1999) and stock assessment
manuals of the Food and Agriculture
Organization of the United Nations
(FAO; Sparre and Venema, 1998;
Cadima, 2003). The approach has re-
cently been used extensively, in the
specific form M~3/tmax, in work relat-
ed to stock assessments for blue crab
(Callinectes sapiclus). In this note,
we 1) show that the regression model
and the rule-of-thumb approach can
be compared directly; 2) illustrate
the difference in the estimates of M
generated by the two approaches; 3)
discuss the origins and current use
of the rule-of-thumb approach; and 4)
recommend that the regression model
be used instead of the rule-of-thumb
approach.
Methods
With the rule-of-thumb approach, the
fraction of a population that survives
to a given age is used to estimate
M. This approach is equivalent to a
quantile estimator (Bury, 1975). Sup-
pose the fraction surviving to age / is
described by the negative exponential
function
~-zt
(3)
where Z is the total instantaneous
mortality rate. The quantile estima-
tor is of the form
-ZrP
(4)
where rp is the age at which 100(P)%
of the population remains. In the case
where P = 0.05, the estimator, based
on data from a sample of the popula-
tion, is
0.05 =
(5)
where 595 of the animals in the sample
are older than age t005.
To estimate M, an empirical ap-
proach is usually taken where f0 05
is replaced with tmax:
0.05:
-»,
(6)
where tma!i is either the oldest age
observed in the stock or the oldest
age found in the literature for the spe-
cies of interest. When age composition
data are used from an exploited stock.
Equation 6 will provide an estimate
of M only if fishing mortality is rea-
sonably close to zero iM=*Z) or if there
is a refuge where older animals can
accumulate. If exploitation affects all
* Contribution 2637 of the Virginia Insti-
tute of Marine Science, The College of
William and Mary, Gloucester Point,
VA 23062.
Manuscript submitted 25 March 2004
to the Scientific Editor's Office.
Manuscript approved for publication
12 October 2004 by the Scientific Editor.
Fish. Bull. 103:433-437(2005).
434
Fishery Bulletin 103(2)
0 025 -
/ \
- 8
"0
\
Absolute differenc
RE-RT
o o o
o o o
o Ul o
/ — ■ —
/
srcent difference
(RE-RT)/RE
CD T
/
- 2
0.005 -
1
• Percent
0.000 -
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 96 100
max
Figure 1
The absolute and percent difference between estimates of M from the regres-
sion estimator (RE) and the approximate rule of thumb, 4.22/rmax (RTl.
animals in the stock, Equation 6 is unlikely to provide
a reliable estimate of M.
The rule of thumb for approximating M follows di-
rectly from Equation 6:
-ln(0.05) = M xtn
M =
2.996
(7)
Most importantly, note that the use of 0.05 or any other
proportion in the equations is arbitrary because we have
no reason to believe that tmax pertains to any particular
quantile.
We show in the present study that this arbitrary rule
of thumb for approximating M is unnecessary, as an
empirical method (Hoenig, 1983) provides an analogous
estimate based on a substantial data set. Equation 1 is
based on the same model as that in Equation 3 and was
developed from a regression of In (AD on ln(<max) from
data on 134 stocks of 79 species of fish, mollusks, and
cetaceans. It can be shown to be of the same form as
the rule-of-thumb approach as follows:
InlM) _ 1.44-0.982xln(«max)
M = -
.0.982xln<(l
4.22
(8)
(t )
utnax '
4.22
0 982
Results
We substituted 1.0 for 0.982 in Equation 8 to allow the
development of a simple, approximate rule of thumb for
direct comparison with 3/tmax. As a result, this rule of
thumb strictly applies only to the case where tm3X = 1.
Estimates from the regression estimator in Equation
1 are always greater than estimates from Equation 8
for £max>l, although the difference is usually small
(Fig. 1).
Estimates from the regression estimator are typically
40-50% greater than estimates from 3/tmax (Fig. 2).
For example, if a maximum age of eight years is used
for blue crab in Chesapeake Bay (Rugolo et al., 1998),
3/tmax gives an estimate for M of 0.375/yr and the re-
gression estimator gives 0.548/yr.
Perhaps the most significant result is the finding that
rearrangement of the regression model yields an esti-
mate of an appropriate value for P in Equation 2. The
value of 4.22 in Equation 8 approximately corresponds
to -ln( 0.015), indicating that the average longevity for
stocks in the data set used by Hoenig (1983) is the age
at which about 1.57c of the stock remains alive (versus
5% in 3/tmax).
Discussion
Development of the rule-of-thumb approach
The rule-of-thumb approach appears to have arisen inde-
pendently in four different places. Cadima (2003) sup-
ported the approach by citing the early work of Tanaka
(1960). Sparre and Venema (1998) based their presen-
NOTE Hewitt and Hoenig: Estimating natural mortality from longevity
435
0) LU
Absolute
Percent
i ■ i ■ i ■ : F^=
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 96 100
max
Figure 2
The absolute and percent difference between estimates of M from the
regression estimator (RE) and 3/imM (3M).
tation on the work of Alagaraja (1984), who provided
the mathematics of a method that Sekharan (1975)
used without description. Interestingly, Shepherd and
Breen (1992) rearranged Equation 3 to obtain the rule of
thumb based on the results of Hoenig (1983). This latter
presentation is provided in Quinn and Deriso (1999). In
all of these cases, the proportion of animals surviving
to £max is assumed to be some arbitrarily small value,
typically 1% or 5%.
The development and use of the specific form 3/tmax
in blue crab work occurred altogether separately. Its
use began with an assessment for the Chesapeake Bay
stock, in which Rugolo et al. (1998) used an estimate
of M based on "the ICES [International Council for the
Exploration of the Sea] convention; that is, 5% survivor-
ship at maximum age following negative exponential de-
pletion." The approach is more explicitly denned in their
original document (Rugolo et al.1) as M = (3/maximum
age). The report also states that "this convention ... is
widely used for many east coast finfish stocks (NMFS
[National Marine Fisheries Service]/NEFSC [Northeast
Fisheries Science Center], ASMFC [Atlantic States Ma-
rine Fisheries Commission])." Following its introduction
by Rugolo et al. (Rugolo et al.1; Rugolo et al., 1998), the
3/£max approach has been used in nearly all blue crab
Rugolo, L., K. Knotts, A. Lange, V. Crecco, M. Terceiro, C.
Bonzek, C. Stagg, R. O'Reilly, and D. Vaughan. 1997. Stock
assessment of Chesapeake Bay blue crab (Callinectes sapi-
dus), 267 p. Report of the Technical Subcommittee of the
Chesapeake Bay Stock Assessment Committee of the National
Marine Fisheries Service, NOAA (National Oceanic and
Atmospheric Administration). NOAA Chesapeake Bay Office,
410 Severn Avenue, Suite 107, Annapolis, MD 21403.
stock assessment work conducted on the east coast of
the United States (Miller and Houde2; Miller, 2001;
Murphy et al.3; Helser et al., 2002; Kahn4).
The references used by Rugolo et al. (1998) in support
of what they termed the "ICES convention" (Antho-
ny5; Vetter, 1988) do not mention the 3/tmax approach.
Rather than advocating a method for determining M,
Anthony5 called for standardization of the range of ages
to include in the calculation of yield-per-recruit for a
stock; this range of ages was termed the stock's "fish-
able life span." He proposed that the fishable life span
should be defined such that the oldest age would be that
2 Miller, T. J., and E. D. Houde. 1999. Blue crab target
setting, 167 p. Final report to the Living Resources Sub-
committee of the Chesapeake Bay Program. University
of Maryland Center for Environmental Science (UMCES)
Technical Series No. TS-177-99. Chesapeake Bay Program,
U.S. EPA (Environmental Protection Agency), 410 Severn
Avenue, Annapolis, MD 21403.
3 Murphy, M. D., C. A. Meyer, and A. L. McMillen-
Jackson. 2001. A stock assessment for blue crab, Ca Uinectes
sapidus, in Florida waters, 56 p. FMRI (Florida Marine
Research Institute) Inhouse Report Series IHR 2001-008.
Florida Fish and Wildlife Conservation Commission, FMRI.
100 Eighth Avenue SE, St. Petersburg, FL 33701.
4 Kahn, D. M. 2003. Stock assessment of Delaware Bay
blue crab (Callinectes sapidus) for 2003, 52 p. Delaware
Department of Natural Resources and Environmental Control.
Division of Fish and Wildlife, P.O. Box 330, Little Creek.
DE 19961.
5 Anthony, V. C. 1982. The calculation of F0-1: a plea for
standardization, 16 p. Northwest Atlantic Fisheries Organi-
zation ( NAFO ) Serial Document N557, SCR 82/VI/64. NAFO
Secretariat, P.O. Box 638, Dartmouth, Nova Scotia B2Y 3Y9,
Canada.
436
Fishery Bulletin 103(2)
at which 59c or less of the initial recruits survived. The
use of Anthony's standard to approximate M makes the
assumption that the fishable life span of an exploited
stock is the same as the longevity of the members of
the stock in an unexploited condition. It is unlikely
that this assumption will be met unless the fishery is
at an early stage in its development because fishing
may alter the age structure of the stock (Hilborn and
Walters, 1992). We note that although a limited num-
ber of scientists involved with ICES have used 3/tmax
in a general way, the method has not been adopted as
a convention within ICES (O'Brien6). Furthermore, we
did not find evidence that the approach is currently in
common use in stock assessments on the east coast of
the United States, with the exception of those for blue
crab. Nonetheless, the rule-of-thumb approach certainly
has the potential to be used widely, given its repeated
presentation in fishery literature and its accumulated
momentum in blue crab work.
Recommendations
The power of empirical relationships for predicting natu-
ral mortality can be rather limited (Vetter, 1988; Pas-
cual and Iribarne, 1993), and the uncertainty associated
with parameter estimates should be taken into account
whenever possible (Patterson et al., 2001). Further-
more, methods for directly estimating M are likely to be
preferable to making predictions based on life history
features. Nonetheless, such estimates may be needed
when available data are inadequate for making a direct
estimate. Given the results of our comparison, we recom-
mend that the regression estimator be used instead of
the rule-of-thumb approach when longevity is used to
predict M. The regression estimator is based on a least
squares fit to an extensive data set and thus matches
experience better than a rule-of-thumb approach based
on an arbitrary constant.
We recommend that use of the 3/tmax rule of thumb
be abandoned, despite it being entrenched in blue crab
literature. For a species like blue crab, for which tmax is
less than 10 years, the differences in the estimates of M
from the regression estimator and 3/tmax are not trivial
(-45%). Although the regression estimator was based
on data for fish, mollusks, and cetaceans (Hoenig, 1983)
and may not be applicable to other exploited taxa, such
as crustaceans, the model had a good fit to the data
across widely disparate taxa. Finally, estimates of M for
blue crab based on longevity are controversial because
of continued difficulty in determining an appropriate
'max- In *"ne aDsence of data to directly estimate M for
this species, we suggest that the most prudent course
O'Brien, C. M. 2004. Personal commun. Chair of ICES
Working Group on Methods of Fish Stock Assessments and
ICES Resource Management Committee. CEFAS (Centre for
Environment, Fisheries and Aquaculture Science) Lowestoft
Laboratory, Pakefield Road, Lowestoft, Suffolk NR33 0HT,
England.
of action is a review and comparison of other methods
for predicting M.
Acknowledgments
We thank Doug Vaughan for helping investigate the
use of the rule-of-thumb approach, and Russell Burke,
Romuald Lipcius, Jacques van Montfrans, and three
anonymous reviewers for helpful comments on the manu-
script. D.A.H. gratefully acknowledges the support of
the Willard A. Van Engel (WAVE) Fellowship for Crus-
tacean Research. This work was supported by fund-
ing from the NOAA Chesapeake Bay Office, award no.
NA03NMF4570376.
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438
Effects of current speed and turbidity
on stationary light-trap catches of
larval and juvenile fishes
David C. Lindquist
Richard F. Shaw
Coastal Fisheries Institute
School of the Coast and Environment
Louisiana State University
Baton Rouge, Louisiana 70803
E-mail address (for D C Lindquist): dlindqlig1 lsu.edu
Light traps are one of a number
of different gears used to sample
pelagic larval and juvenile fishes. In
contrast to conventional towed nets,
light traps primarily collect larger
size classes, including settlement-size
larvae (Choat et al., 1993; Hickford
and Schiel, 1999; Hernandez and
Shaw, 2003), and, therefore, have
become important tools for discern-
ing recruitment dynamics (Sponau-
gle and Cowen, 1996; Wilson, 2001).
The relative ease with which multiple
synoptic light trap samples can be
taken means that larval distribu-
tion patterns can be mapped with
greater spatial resolution (Doherty,
1987). Light traps are also useful
for sampling shallow or structurally
complex habitats where towed nets
are ineffective or prohibited (Gregory
and Powles, 1985; Brogan, 1994; Her-
nandez and Shaw, 2003).
As with any sampling gear, there
are concerns about light trap sam-
pling biases and efficiency. Light
traps are taxon-selective because
they target fishes that are photoposi-
tive and able to swim to and enter
the trap (Thorrold, 1992; Choat et al.
1993; Hernandez and Shaw, 2003),
and size-selective because both pho-
totactic behavior and swimming abil-
ities change during ontogeny (Stea-
rns et al., 1994; Fisher et al., 2000).
LTnlike conventional towed nets, it is
difficult, if not impossible, to quan-
tify the volume of water sampled by
light traps. This is largely due to ex-
ternal, environmental factors such as
lunar phases, current speed or water
clarity, which may have a large im-
pact on catch rates (Doherty, 1987;
Meekan et al, 2000).
Few studies have attempted to ad-
dress the effects of environmental
factors on light trap performance.
Catches have been found to be lower
during full moons as compared to new
moons, either because of the greater
ambient illumination interfering with
light trap efficiency (Gregory and Pow-
les, 1985; Hickford and Schiel, 1999)
or because of higher abundances of
presettlement fish during the darker
lunar phases (Johannes, 1978; Rob-
ertson et al., 1988). Thorrold (1992)
showed that catches were greater for
light traps drifting with the current
as compared to traps anchored in the
current flow. Anderson et al. (2002)
found that anchored light traps were
less efficient at a high-current sam-
pling site as compared with a low-
current sampling site. The latter two
studies, however, did not provide any
information on catch rates with varia-
tion in current speed. The purpose of
this study was to assess the relation-
ships between catch rates from sta-
tionary (anchored or tethered) light
traps at offshore petroleum platforms
and concurrent measurements of cur-
rent speed and turbidity.
Materials and methods
Study sites
Larval and juvenile fishes were col-
lected at five oil and gas platforms
(platforms) in the north-central
Gulf of Mexico. These platforms
included: Mobil's Green Canyon 18
(27°56'37"N, 91°0'45"W; sampled from
July 1995- June 1996); Mobil's Grand
Isle 94B (28°30'57"N, 90°07'23"W;
April-August 1996); Exxon's
South Timbalier 54G (28°50'01"N,
90°25'00"W; April-September 1997);
Santa Fe-Snyder's Main Pass 259A
(29C19'32"N, 88°01'12"W; May-
September 1999); and Murphy
Oil's Viosca Knoll 203 (29°46'53"N,
88°19'59"W; May-October 2000). All
platforms had similar underwater
structural complexity, and had well-
developed biofouling communities
when sampled.
Sampling procedures
Sampling procedures have been
described in detail elsewhere (Her-
nandez and Shaw, 2003) and will be
briefly described here. Fish collec-
tions were made by using a modified
quatrefoil light trap with a Brinkman
Starfire II halogen light (250,000 can-
dlepower) powered through an umbili-
cal by a 12-volt marine battery. Light
traps were deployed in surface waters
within the platform structure along
a stainless-steel guidewire (within-
platform light trap), and tethered and
floated in surface waters to a distance
of 20 m from the down-current side of
the platform (off-platform light trap).
Light traps were deployed with their
lights off, fished with lights on for
10-15 min, and retrieved with lights
off.
Sampling was undertaken general-
ly twice monthly coincident with new
and full moon phases. During each
trip, light traps were fished during
four to six sets per night, starting
at least one hour after sunset and
ending at least one hour before sun-
rise, over two to three consecutive
nights. Each sample set consisted of
a within-platform light trap collec-
Manuscript submitted 4 February 2004
to the Scientific Editor's Office.
Manuscript approved for publication
1 December 2004 by the Scientific Editor.
Fish. Bull. 103:438-444 (2005).
NOTE Lmdquist and Shaw: Effects of current speed and turbidity on catches of larval and juvenile fishes 439
140 -
•
1 120-
° 100 -
sh per
00
o
•
•
• •
& 60 -
LU
g 40-
§ 2°-
2
•• • I
• • ...% •
0 i 1" ~' r" T — — — i ™— n 1 i i • - i
0 10 20 30 40 50 60 70 80 90
Mean water current speed (cm/sec)
Figure 1
Mean total CPUE per sampling set (from within- and off-platform
light traps) in relation to the mean current speed per sampling set.
Data from all platforms were combined. Line calculated from the
regression equation: loglfl(y+l) = -0.013.V + 1.302, r2 = 0.23.
tion and an off-platform light trap collection in random
order. During sampling, turbidity (Nephelometric tur-
bidity unit: NTU) was measured every 5 sec by using
a Hydrolab DataSonde3 suspended in surface waters
within the platform structure. Current speed and direc-
tion were measured every 10 min with an InterOcean
S4 Current Meter suspended 1-2 m below the surface
on the up-current side of the platform. Because the
platform structure undoubtedly reduced current speeds
(Forristall, 1996), current data taken from this location
should be considered as relative estimates for the light
trap collections.
Samples were preserved in 10% buffered formalin and
transferred to ethanol within 12 hours. Fish were enu-
merated and identified to the lowest possible taxonomic
level. Preflexion larvae were measured to notochord
length, and postflexion and juvenile fish were measured
to standard length. Data from light trap catches were
standardized to a catch per unit of effort (CPUE) of
number of fish per 10 minutes.
Data analyses
We assumed that there were no inter-location differences
in the relationship between light trap CPUE and current
speed or turbidity; therefore, data from all platforms
for the months May to September were combined. The
relationship between total light trap CPUE and current
speed or turbidity was analyzed by using regression
analysis. Current speed and turbidity were analyzed
separately, rather than in a multiple regression analysis,
because there was a limited number of sampling sets
where we had data for light trap CPUE, current speed
and turbidity together (n = 60, or 31% and 37% of the
available turbidity and current data, respectively). There
were no significant differences in the regression coef-
ficients of CPUE vs. current speed or turbidity between
within- and off-platform light traps (P>0.15); therefore,
the CPUEs from both light traps were averaged for each
sampling set. Mean total CPUEs were log-transformed
(log10(.y+l)) and analyzed with the mean current speed
or turbidity from each respective sampling set. Mean
CPUEs were also calculated for the dominant families
collected; however, regression analyses could not be
performed because variances remained heterogeneous
after transformation.
To investigate how fish size (i.e., locomotive ability)
influenced light trap catches with increasing current
speed, length-frequency distributions of all fishes col-
lected at different current speed intervals (0-9, 10-19,
20-29, 30-39, 40-49 and >49 cm/sec) were compared by
using Kolmogorov-Smirnov tests (a=0.05). The length-
frequency figures were subdivided by three ecological
groupings: clupeiforms (Clupeidae and Engraulidae);
demersal taxa (predominantly Synodontidae and Blen-
niidae); and scombrids and carangids, to further assess
whether any changes in the size of fish collected over
the current intervals were due to a particular group.
All statistics were performed with SAS version 6.12
(SAS Institute, Cary, NO.
Results
Current speed
Mean total CPUEs generally decreased with increasing
current speed (Fig. 1). At current speeds s30 cm/sec,
light trap catches were highly variable (CPUEs ranged
from 0 to 138 fish per 10 min); however, CPUEs >20
fish per 10 min occurred only at these lower speeds.
Although there were fewer samples at speeds >30 cm/sec,
440
Fishery Bulletin 103(2)
50
45
25
20
15
10
5
0
- 75
Clupeidae
E
70
< >
*-
^S -,
(i)
C
20 -
CO
—
15 -
111
)
Q_
1(1 -
O
to
5 -
a)
i
n -
]•
Synodontidae
• • • . " »
90-
80.
50
40
30 -
20
10
0
Engraulidae
• • • •
0 -|
.
Carangld
ae
8-
6 -
•
•
4 -
•
«
•
2 -
i-i.
•
0 -
■ — f
i i
s •
-•-•n — • — i —
* •• i
25 n
20
15
10
5
0
Scombridae
*%•_-. 1*
*^-
+■
-T-
0 10 20 30 40 50 60 70 80 90 0 10 20 30 40 50 60 70 80 90
Mean water current speed (cm/sec)
Figure 2
Mean CPUE per sampling set (from within- and off-platform light traps) in relation to the mean cur-
rent speed per sampling set for each of the dominant families collected. Data from all platforms were
combined. Note changes in the scale of the .y-axis.
CPUEs were mostly <5 fish per 10 min at these speeds.
There was a significant linear relationship between log-
transformed mean total CPUE data and mean current
speed (log10(y+l) = -0.013.T + 1.302, r2=0.23; F=49.61,
P<0.0001).
Each of the dominant families collected by light traps
showed a similar pattern of highest mean CPUEs at
current speeds <30 cm/sec and relatively low mean
CPUEs at higher current speeds (Fig. 2). Clupeidae,
Engraulidae, and Blenniidae showed a slight trend of
highest CPUEs at intermediate current speeds (10-30
cm/sec), whereas the other families generally had high-
est CPUEs at the lowest speeds (<10 cm/sec). Synodon-
tidae and Blenniidae were rarely collected at current
speeds >40 cm/sec, and small numbers of Clupeidae,
Engraulidae, Carangidae, and Scombridae were col-
lected at speeds up to 80 cm/sec.
As current speeds increased, light trap collections
became limited to smaller size classes offish (Fig. 3).
For the first three current intervals, i.e., 0-9, 10-19,
and 20-29 cm/sec, a broad range of sizes were collected
and the distributions had median lengths of 15-19
mm. However, beginning at the fourth current interval,
30-39 cm/sec, the size distributions shifted toward an
increasingly greater proportion of the catch <10 mm
in length. This trend was most pronounced at the two
highest current intervals, 40-49 and >49 cm/sec, both
of which had distributions with median lengths of 5
mm. The size distributions from the two highest cur-
rent intervals were the only distributions that were not
NOTE Lindquist and Shaw: Effects of current speed and turbidity on catches of larval and |uvenile fishes
441
0.15
0 1 -
0.05
0
0.15
o
£ 01
3
O"
0)
0.15
I I Clupeiforms
H Demersal taxa
Current = 0-9 cm/sec
0.15
n = 1994 median=15
0.1
m
1 5 10 15 20 25 30 35 40+
Current=10-19 cm/sec
n = 1009 median=19
tf+^fl
15 10 15 20 25 30 35 40+
Current = 20-29 cm/sec
n = 1499 median=16
10 15 20 25 30 35 40+
005 -
Scombnds and carangids
Current=30-39 cm/sec
n=206 median =12
Jl ol^fllrMltorlH.Fffir^n.n
1 5 10 15 20 25 30 35 40+
0.1
t
0.15 -1 l-
Current=40-49 cm/sec
n=78 median = 5
0 1 - -
-,
0.05 -"
0
-=-Tn,,lfl =
"iii
15 10 15 20 25 30 35 40+
0.15 -,
0.1
0.05
0
1
Current = >49 cm/sec
n=92 median = 5
nmTwHininn.Him n , ■ ■ ■ H
1
10 15 20 25 30 35 40+
Length (mm)
Figure 3
Size distributions of fishes collected by light traps from all platforms at different current speed intervals.
The total number offish collected [n) and the median length (mm) over each interval are included. Size
distributions are further subdivided by three general ecological groupings: clupeiforms (Clupeidae and
Engraulidae), demersal taxa (i.e., more substrate-oriented fishes such as synodontids and blenniids), and
scombrids and carangids.
significantly different from each other (P=0.11). The
decrease in the frequency of fishes larger than 10 mm
at the higher current intervals was not limited to any
particular ecological grouping, i.e., pelagic fishes such
as clupeiforms, scombrids, and carangids were as rare
as demersal taxa.
Turbidity
Mean total CPUEs generally decreased with increasing
turbidity (Fig. 4). Highest catches (CPUEs >50 fish per
10 min) predominantly occurred at turbidities below
1.0 NTU, whereas at higher turbidities catches were
generally lower. There was a significant linear relation-
ship between log-transformed mean total CPUE data
and mean turbidity (log10(y+l) = -0.25.v + 1.48, r2=0.08;
F=11.86, P=0.0007).
The majority of the dominant families showed a simi-
lar pattern of highest mean CPUEs at turbidities <1.0
NTU, and relatively low mean CPUEs at higher turbidi-
ties (Fig. 5). Clupeidae, however, showed a pattern of
high CPUEs at turbidities <0.5 NTU and between 1.0
and 2.0 NTU.
Discussion
Light trap catches of larval and juvenile fishes appeared
to be negatively affected by increasing current speeds at
platforms. This was expected because stronger currents
may interfere with a fish's ability to swim to and enter
a light trap (Doherty, 1987; Thorrold, 1992; Anderson
et al., 2002). Doherty (1987) predicted that, for station-
ary (anchored or tethered) light traps, catches should
increase initially with current speed as more water
is sampled, but then decrease as current speed inter-
feres with catchability. Although mean total CPUEs
clearly decreased with increasing current speed, they
442
Fishery Bulletin 103(2)
350 -
| 300 -
o
>- 250 -
•
•
•
s. : •
sz 200 - • *
in
W 150 - . *
o ioo- l:'tm ,
S t M I t - . . ^* • • •
11*1-1 1.' I.J'Jl'1,' . -t*
0 H
(
112 3
Mean water turbidity (NTU)
Figure 4
Mean total CPUE per sampling set (from within- and off-platform
light traps) in relation to the mean turbidity per sampling set. Data
from all platforms were combined. The line was calculated from the
regression equation: log1(1(y+l) = -0.25.r + 1.48, r- = 0.08. Included in
the analysis, but not shown in the plot, were three points from 583
to 878 CPUE between 0.2 to 0.5 NTU.
did not appear to peak at some intermediate current
level. These results, however, represented the total
catch of all fishes, and the relationship between cur-
rent speed and light trap catches may be more taxon
specific (Doherty, 1987). When analyzed at the family
level, a bell-shaped relationship may have occurred for
Clupeidae, Engraulidae, and Blenniidae; however, the
pattern was indistinct and there was generally little
difference among families.
The lack of any strong differences in the relationship
between light trap CPUEs and current speed among
the dominant families was unexpected, considering
the potential differences in swimming abilities. Be-
cause larvae and juveniles of demersal fishes are gener-
ally believed to have lower swimming speeds (Blaxter,
1986), it was anticipated that catches of synodontids
and blenniids would have been more negatively affected
by increasing current speed than relatively stronger-
swimming pelagic taxa (e.g., scombrids and carangids).
Perhaps larvae of demersal taxa have greater swim-
ming capabilities than previously considered, as has
been recently found for certain settlement-stage larval
reef fishes (sustained swimming speeds of 20-60 cm/
sec; Stobutzki and Bellwood, 1994; Leis and Carson-Ew-
art, 1997). However, despite possible strong swimming
abilities, few larval and juvenile demersal or pelagic
fishes were collected at current speeds >40 cm/sec, and
of these the majority were preflexion larvae that were
undoubtedly passively entrained in the light trap. It is
possible that the larvae and juveniles of taxa collected
at platforms were unable to maintain the metabolic
power required to swim against the stronger currents
over extended distances from the light trap (Fisher and
Bellwood, 2002).
Currents may have interfered with the functioning of
the light traps. Assuming that larval and juvenile fishes
were able to swim against the stronger currents, their
ingress into the light trap may have been impeded by
turbulence created by the current flow around the trap.
If turbulence occurred after some critical current speed,
then this may explain the lower CPUEs beginning at
around 30 cm/sec observed for each of the dominant
families.
Higher turbidity also appeared to have a negative ef-
fect on light trap catches at platforms. Light trap catch
efficiency should be greatly impaired by highly turbid
waters because greater light attenuation would reduce
the effective sampling radius of the trap. In addition,
the phototactic response of larval and juvenile fishes
may be lower at lower light intensities (Gehrke, 1994;
Stearns et al., 1994). However, it is uncertain whether
the relatively small range of turbidities (0.1-2.6 NTU)
sampled during this study would result in a significant
decrease in light trap catch efficiency, particularly given
the intensity of the light source used (250,000 candle-
power). The observed patterns may have been a reflec-
tion of intrusions of turbid coastal and Mississippi River
plume water at the platforms, during which light trap
catches comprised large numbers of coastal clupeids and
relatively few other taxa (Fig. 5).
Although they were treated separately for the purpos-
es of this study, the effects of current speed and turbid-
ity also may have been interrelated. A positive relation-
ship between turbidity and current speed was found for
a limited data set where both variables were available
(r-=0.28, P<0.0001). It is unlikely that this relationship
was caused by the resuspension of benthic sediments,
given the water depth at the platforms (20-230 m), but
NOTE Lindquist and Shaw: Effects of current speed and turbidity on catches of larval and juvenile fishes
443
140 n
120
100 -
80
60
40
20 -
0
z>
Q.
o
Clupeidae
* i • tf ••*•» _••••■ ••
~ 60
c
0 50
1 40
I 30
20
10 -
Synodontidae
• • •
5
4
3
2 -
1 -
0
Carangidae
200
150
100
50
80
70
60
50
40
30
20
10
0
Engraulidae
• ! • • i • •
irfl I. »■!■.'.
iifci
mi * qt
Blenniidae
t
»i*tm—*»t — ■ *}•+
30
25
20
15
10 -
5
0
Scombndae
t • • ■ i
* : • , • ; i •
jgfej Hi i. y.t.iJ.l%.\ ■•!»;.
0 1 2 3 0 1 2 3
Mean water turbidity(NTU)
Figure 5
Mean CPUE per sampling set (from within- and off-platform light traps) in relation to the mean turbidity
per sampling set for each of the dominant families collected. Data from all platforms were combined. Note
changes in the scale of the y-axis. Not shown in the Engraulidae plot were three points from 551 to 606
CPUE between 0.2 and 0.5 NTU.
particles may have been flushed from the platforms and
their associated biofouling communities by currents.
In a comparison of light trap catches between adjacent
beach and rocky shore habitats, Hickford and Schiel
(1999) attributed lower catches at the beach to lower
water clarity caused by sediment resuspension by wave
action. Therefore, high current speeds at platforms may
have indirectly affected light trap catch efficiency by
reducing water clarity.
Results from this study have clear implications for
future studies with light traps. At platforms, light trap
CPUEs began to decline noticeably at current speeds
of 30 cm/sec, and by 40 cm/sec catches of active swim-
ming larval stages (i.e., all but preflexion stages) were
rare. This finding suggests that, for comparison studies.
estimates of relative abundance from light traps may be
biased where there is considerable variation in current
flow (Doherty, 1987; Anderson et al., 2002). Drifting
traps may be used to avoid the confounding effect of
differential water flow (Thorrold, 1992); however such
a deployment method may not be applicable when habi-
tats of interest are fixed (e.g., platforms, coral reefs).
In such cases, the best course may be to not consider
light trap samples at high current speeds (240 cm/sec).
For turbidity, study results were not as clear; however,
temporal or spatial variation in turbidity also would
undoubtedly bias light trap results. Short of using light
traps at times or locations of similar water clarity, an
adjustable light source may be incorporated into light
trap design so that equivalent light intensities, and
444
Fishery Bulletin 103(2)
therefore sampling fields, can be maintained across a
variety of water conditions. The alternative would be
to standardize the volumes of water sampled by light
traps; however, considering the suite of external factors
that affect light trap efficiency, such attempts may be
fruitless (Meekan et al., 2000).
Acknowledgments
We would like to thank A. Scarborough-Bull, C. Wilson,
D. Stanley, J. Ditty, F. Hernandez Jr., J. Cope, J. Plun-
ket, T. Farooqi, and all of those who assisted in the field
and laboratory for their assistance and efforts during
this research. We also thank Exxon USA, Inc., Mobil
USA Exploration and Production, Inc., Santa Fe-Snyder
Oil Corp., and Murphy Oil Corp. for access to their oil
and gas platforms and logistical support, the crews of
GC 18, GI 94B, ST 54G, MP 259A and VK 203 for their
assistance and hospitality, and two anonymous review-
ers for their helpful comments on this manuscript. This
research was funded by the Minerals Management Ser-
vice-Louisiana State University-Coastal Marine Insti-
tute (contract no. 14-35-0001-30660-19961).
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Carr, and J. M. Shenker.
2002. Current velocity and catch efficiency in sampling
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100:404-413.
Blaxter. J. H. S.
1986. Development of sense organs and behaviour of tele-
ost larvae with special reference to feeding and predator
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Brogan. M. W.
1994. Distribution and retention of larval fishes near
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Choat, J. H., P. J. Doherty, B. A. Kerrigan, and J. M. Leis.
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Doherty, P. J.
1987. Light-traps: selective but useful devices for quan-
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Fisher, R., and D. R. Bellwood.
2002. The influence of swimming speed on sus-
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Fisher, R., D. R. Bellwood, and S. D. Job.
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Forristall, G. Z.
1996. Measurements of current blockage by the Bullwinkle
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1994. Influence of light intensity and wavelength on
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effectiveness of light traps. J. Fish Biol. 44:741-751.
Gregory, R. S., and P. M. Powles.
1985. Chronology, distribution, and sizes of larval
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Hernandez, F J., Jr., and R. F. Shaw.
2003. Comparison of plankton net and light trap meth-
odologies for sampling larval and juvenile fishes at
offshore petroleum platforms and a coastal jetty off
Louisiana. In Fisheries, reefs and offshore develop-
ment (D. R. Stanley and A. Scarborough-Bull, eds.), p.
15-38. Am. Fish. Soc. Symp. 36.
Hickford, M. J. H., and D. R. Schiel.
1999. Evaluation of the performance of light traps for
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Ecol. Prog. Ser. 186:293-302.
Johannes. R. E.
1978. Reproductive strategies of coastal marine fishes
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Leis, J. M., and B. M. Carson-Ewart.
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Meekan, M. G., P. J. Doherty, and L. White Jr.
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Sponaugle, S., and R. K. Cowen.
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Stobutzki, I. C, and D. R. Bellwood.
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445
Can a change in the spawning pattern of
Argentine hake (Merluccius hubbsi)
affect its recruitment?*
recruitment of this stock in different
years between 1988 and 2001.
Materials and methods
Gustavo J. Macchi
Conseio Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
Rivadavia 1917
1033 Buenos Aires. Argentina
Present address: Instituto Nacional de Investigacion y Desarrollo Pesquero (INIDEP)
Paseo Victoria Ocampo N° 1. CC. 175
Mar del Plata, 7600, Argentina
E-mail address gmacchnaHnidepeduar
Marcelo Pajaro
Adrian Madirolas
Instituto Nacional de Investigacion y Desarrollo Pesquero (INIDEP)
Paseo Victoria Ocampo N° 1 CC. 175
Mar del Plata, 7600, Argentina
Argentine hake (Merluccius hubbsi)
inhabit waters of the Southwest
Atlantic Ocean between 22° and 55°S,
at depths ranging from 50 to 500 m
(Cousseau and Perrota, 1998). This
species has historically been among
the more abundant fish resources in
the Argentine Sea, where its biomass
has ranged between one and two
million metric tons annually since
1986 (Aubone et al., 2000). In this
area, there are two identified fish-
ing stocks, limited by the 41°S paral-
lel. The southern group (Patagonian
stock) is the more important with an
abundance of about 85% of the total
biomass estimated for this species in
1999 (Aubone et al., 2000). During
the late 1990s, the spawning biomass
of both stocks and their recruitment
indices declined drastically, both of
which were attributed to an increase
in exploitation (Aubone et al., 2000).
The Patagonian stock of Argentine
hake spawns from November through
March and peak spawning occurs in
January (Macchi et al., 2004). This
species is a batch spawner and has
indeterminate annual fecundity,
which is to say that unyolked oocytes
continuously mature and are spawned
throughout the reproductive season
(Macchi and Pajaro, 2003). Thus, to
estimate total fecundity, it is neces-
sary to determinate the number of
eggs released at one spawning (batch
fecundity) and to estimate the num-
ber of batches spawned in a repro-
ductive season (spawning frequency).
Macchi et al. (2004) estimated these
parameters for the southern stock of
M. hubbsi. They analyzed total egg
production during the reproductive
season and determined that the size
composition of the spawning fraction
influences the reproductive potential
of the stock.
Reproductive activity of the Pata-
gonian hake historically has taken
place mainly in coastal waters off the
Chubut province at depths near 50
m, in the area known as Isla Escon-
dida (43°30-44°S) (Ciechomski et al.,
1983). Since 1997-98, a movement of
reproductive hake to deeper waters
and a decrease in fish density have
been observed (Ehrlich et al.1). These
changes, mainly in the location of the
spawning area, may have affected
the reproductive potential of this spe-
cies, reducing the survival of eggs
and larvae. If so, we would expect a
negative effect on the number of juve-
niles recruited after this period.
In this note, we hypothesize that a
change in spawning site for Patago-
nian hake can affect species recruit-
ment. We studied temporal changes
in the location and density of spawn-
ing aggregations, egg production, and
Samples of M. hubbsi were collected
from the area where the Patagonian
stock is known to reproduce during
four acoustic surveys in December
1988, 1993, 1996, and 2000 and
during six trawl cruises carried out
in January between the years 1996
and 2001.
Acoustic surveys covered the Isla
Escondida area between 43° and
45°S (Fig. 1). A SIMRAD EK400/QD
echointegrator was used for the 1988
survey and a SIMRAD EK500 echo-
sounder and BI500 postprocessing
program were employed for subse-
quent surveys. To avoid possible bi-
ases due to the presence of fish in the
near-bottom, acoustic transects were
carried out at night when hake as-
sume a more pelagic behavior. Trawl
catches were carried out during the
day, when fish are concentrated close
to the bottom, and immediately af-
ter each acoustic transect. Because
trawls were intentionally biased to
those areas of higher fish density,
their positions were different be-
tween 1988 and 2000. Nevertheless,
the study area, transect design, and
sampling effort were similar for all
cruises covering the main spawning
shoals.
In January, information was col-
lected from trawl surveys to assess
the Patagonian stock of juvenile
hake between 1996 and 2001. These
cruises covered a wide area between
43° and 47°S that included a section
' Contribution 1357 from the Instituto
Nacional de Investigacion y Desarrollo
Pesquero, Mar del Plata, Argentina.
Ehrlich, M. D., P. Martos, A. Madirolas,
and R. P. Sanchez. 2000. Causes of
spawning pattern variability of anchovy
and hake on the Patagonian shelf. ICES
CM 2000/N:06.
Manuscript submitted 2 July 200.3
to the Scientific Editor's Office.
Manuscript approved for publication
20 December 2004 by the Scientific Editor.
Fish. Bull. 103:445-452 (2005).
446
Fishery Bulletin 103(2)
62
Longitude °W
Figure 1
Distribution and density (sA) of Argentine hake iMerluccius hubbsi) estimated from acoustic
surveys carried out during December (1988, 1993, 1996, and 2000) in the Isla Escondida area.
The size of the symbols is proportional to the percentage of spawning females (with hydrated
oocytes). Vertical shaded scale represents scattering coefficient values (sA), where 7.14 sA
units = 1 t/nautical mile2.
of the main spawning ground of hake. Thus, to ana-
lyze spawning individuals we used only data from 33
fish stations located offshore within the spawning area
between 43°30' and 46°S (Fig. 2). Trawl station sites
were the same during all cruises. In January of 1996
and 2001 additional information from catches obtained
inshore near Isla Escondida was analyzed (Fig. 2).
Argentine hake were collected with a bottom net with
a mouth width of about 20 m, a height of about 4 m,
and with 20-mm mesh at the inner cover of the codend.
Total length (TL) in cm, total weight (TW) in g, and
sex were recorded for each fish sampled; for females a
subsample was randomly selected from different trawl
stations (Table 1) and the maturity stage was deter-
mined for each individual. A macroscopic maturity key
of five stages designed for biological studies was em-
ployed: 1) immature; 2) developing and partially spent;
3) spawning (gravid and running); 4) spent; and 5)
resting (Macchi and Pajaro, 2003). This scale was vali-
dated by the histological analysis of ovaries collected
during December 2000 and January 2001 (Macchi et al.,
2004). Females were classified as reproductively active
or inactive, according to the presence of yolked oocytes
and atresia stages following the criteria of Hunter et al.
(1992). When we consider the codes used in the visual
assessment of maturity, stages 2 and 3 corresponded
to active females, which were capable of spawning at
the time of capture or in the near future (Hunter et
al., 1992).
Abundance of active females was estimated from data
collected during each survey. Information obtained from
sampling the trawl catch was expanded to obtain esti-
mates of the number of individuals per length class, fol-
lowing the method described by Macchi et al. (2004).
During December, information from acoustic surveys
was used to assign a different weight to each trawl
station, based on the relative density and size of the
school targeted by the trawl. The transect segment
that contained a given trawl was determined and the
average value of the water column scattering coefficient
NOTE Macchi et al.: Effect of the spawning pattern of Merlucaus hubbsi on recruitment
447
68
67 66
1?
43-
44
45
4fr
1996
Argentina
63
62
- 1 — i — i — i — i — i — | — i — i — i — i — i — | — i — i — i — i — r
67 66 65
64 63 62
62 68
Longitude "W
; 2001
i i.i
i
-42
43
Argentina
/
o
44
> o .
4-
45
/ ■ .
i \'\ i 1 1 1 1 i i i i i
^46
67
66
65
64
63
62
Figure 2
Distribution and density of Argentine hake iMerluccius hubbsi) estimated from trawl surveys carried out
during January (1996-2001) in the offshore area. The size of the symbols is proportional to the percentage
of spawning females (with hydrated oocytes). The square shows the Isla Escondida area. Vertical shaded
scale represent biomass in t/nautical mile2.
(sA) was calculated and weighed by the corresponding
number of acoustic observations.
The number of active females for each survey was
estimated by multiplying the number of hake within
each length class by the proportion of females and the
proportion of active females for that length class ob-
tained for that survey (Marshall et al., 1998). The sum
of values estimated across the size range was an index
of the number of reproductive females in the sampled
area during that survey.
Egg production of the Patagonian hake in Decem-
ber during the period 1988-2000 and in January from
1996 to 2001 was based on estimates of three variables:
the abundance of active females per length class, the
448
Fishery Bulletin 103(2)
Table 1
Number of Argentine
hake (Merluccius hubbsi) s
ampled during
research surveys carrie
d out
in the
north Patagonian area in
December and January, bet
ween 1988 and 2001.
Number of
Number of females
Period
Number of trawls
ndividuals sampled
subsampled
December
1988
18
9527
2054
1993
6
2156
1060
1996
9
1563
690
2000
12
4390
708
January
1996
38
17,715
1509
1997
33
12,687
842
1998
33
15,804
1092
1999
33
14,987
817
2000
33
14,389
958
2001
37
17,944
856
batch-fecundity-size relationship, and spawning fre-
quency. The batch fecundity-total-length relationship
and the spawning frequency values used for December
(1988-2000) and for January (1996-2001) were those
estimated in December 2000 and January 2001, re-
spectively (Macchi et al., 2004). We assumed that these
values were applicable to all previous years, because in
general, annual differences of these variables were not
significant for hake females of the same length range
(Macchi et al., 2004).
Egg production by length for each month was esti-
mated by multiplying the number of active females in
each length class by the batch fecundity corresponding
to that length class and by the number of spawnings es-
timated for each month. The sum of the egg production
values estimated across the size range was the total
number of eggs produced in the sampled area during
each month (December or January) in different years.
To analyze the relationship between egg production
and recruitment, estimates of the relative abundance at
age 1 (number of individuals per trawl hour) of Argen-
tine hake were used as a recruitment index. These data
were obtained from samples to assess hake juveniles
collected from the whole area covered during the cruises
carried out in January 1997-2001. In 2002, this index
was estimated with samples collected in the same area,
but in a different month (March) (GEM, unpubl. data2).
The number of age-1 individuals in year t+1 was the
recruitment index corresponding to the year t.
Results
(with hydrated oocytes) in the Isla Escondida area during
December 1988, 1993, 1996, and 2000. A decline in hake
abundance from 1988 to 2000 was observed — in particu-
lar, a drastic decrease in 2000, when the mean density
value (14.6 t/nautical mile2) was thirty times less than
that estimated in 1988 (469.2 t/nautical mile2). During
December 1988-96, spawning females were mainly
located in the northern area (between 43° and 44°S)
inshore at depths lower than 50 m. In 2000 reproduc-
tive activity was concentrated at the same latitude as
in previous years, but offshore (Fig. 1).
In January 1996 the highest densities of M. hubbsi
and the spawning females of this species were located
in the Isla Escondida area (Fig. 2). Between 1997 and
2000 we did not obtain data from this zone, but the
increase in the proportion of spawning hake in deep
waters observed since 1998 indicates a spatial change
in the reproductive area. During January 2000 and
2001, in addition to the increase of reproductive females
offshore, the abundance of hake was higher than that
estimated previously for the same area (Fig. 2). In Jan-
uary 2001, trawl stations located near Isla Escondida
showed very low values of hake density, in contrast to
that observed offshore. This contrast could be attributed
to the movement of individuals from the traditional
spawning area near the coast to deeper water.
Egg production
Egg production estimated for December in the Isla
Escondida area showed a considerable decrease from
1988 to 2000 (Fig. 3). The number of eggs produced
Abundance of hake and location of spawning females
Figure 1 shows the acoustic densities estimated for
Argentine hake and the distribution of spawning females
- GEM (Grupo de Evaluacibn Merluza). 2002. Evaluacion
del estado del recurso merluza (Merluccius hubbsi) al sur de
41° S, ano 2002. Unpubl report. INIDEP, CC. 175, Mar
del Plata (7600), Argentina.
NOTE Macchi et al.: Effect of the spawning pattern of Merlucaus hubbsi on recruitment
449
1600
2 1200
800
400 -
XZL
2000
1600
1200
800
400
1988
1993
1996
2000
Figure 3
Egg production of Argentine hake (Merluccius. hubbsi)
estimated for December (1988. 1993, 1996, and 2000)
in the Isla Escondida area (bars), and production by
unit-weight of reproductively active female (line) for
the same month.
per unit of weight (kg of active females) declined from
1988 to 1996, and to a value of around 1700 eggs/kg in
the last year (Fig. 3). During December 2000, however,
relative egg production increased to 2000 eggs/kg, which
can be attributed to the effect of a higher proportion of
larger females in reproductive activity. In fact, when
the percentage of eggs produced by length class was
analyzed, the distribution obtained for December 2000
was different from that for 1988, 1993, and 1996 (Fig. 4).
During the earlier years, production mainly depended on
young females (<50 cm TL), whereas in December 2000
most of the eggs produced (about 70%) where spawned
by females larger than 50 cm TL.
Egg production estimated for the offshore area in Jan-
uary increased from 1996 to 2001 (Fig. 5), in contrast to
that observed during December in shallow water near
Isla Escondida. The number of eggs produced per unit
of weight of active females was similar in 1996 and
1997 (about 1600 eggs/kg), but increased in 1998-2001
to about 1800 eggs/kg. This increase was similar to
that observed for December 2000, which was attributed
to the higher proportion of larger females within the
spawning fraction of hake. In fact, percentage-distribu-
tion of eggs produced by length class showed a change
beginning in 1998 (Fig. 6). In 1996 and 1997, 70% of
the eggs were produced by young females (<50 cm TL),
but subsequent production of old females increased to
60% in 1998-99 and to 70% in 2000-01.
40 -
^^1988
o
a -»— 1993
! 3°-
/V n^
// T4
T3
t 20-
\
if \
| 10-
al
// \^^\
0)
JJ \bs=53£liS^~X
20 30 40 50 60 70 80 90 100
Total length (cm)
Figure 4
Relative egg production {%) by length class estimated
for Argentine hake (Merluccius hubbsi) from December
1988, 1993, 1996, and 2000.
800 -
- 2000 7
o
700 -
j** '
o
S~ 600 -
o
~ 500 -
o
" 400 -
ion per kg of
o o
o o
CD CM
2 300-
D3
■ 800 £
<
S 200 -
CD*
-400 |
100 -
n
CD
n O
1996 1997 1998 1999 2000 2001
Years
Figure 5
Egg production of Argentine hake [Merluecius hubbsi)
estimated for January (1996-2001) in the offshore area
(bars), and production by unit-weight of reproductively
active female (line) for the same month.
from the offshore area was used; thus, the number of
eggs estimated was a fraction of that produced by all
spawning females in January. However, the increase in
egg production observed offshore for the parental stock
in 2000 and 2001 was coincident with higher values of
age-1 recruitment estimated one year later during 2001
and 2002, respectively (Table 2).
Recruitment
Relative abundance data for hake at age 1 (year t+1)
in the north Patagonian area were contrasted with the
egg production obtained in January from the previous
year (t). To estimate egg production, only information
Discussion
The spatial pattern of M. hubbsi spawning aggrega-
tions inshore and offshore of the north Patagonian area
between 1988 and 2001 has changed since 1998. This
450
Fishery Bulletin 103(2)
Table 2
Egg production estimates for Argentine hake (Merluccius
hubbsi) for January cruises 1 1996-2001 ) taken offshore of
the north Patagonian area, and indices of abundance at
age 1 corresponding to these annual classes.
Year
Egg production
(1012)
Index of age-1 hakes
(individuals per trawl hour)
1996
116.625
1997
81.774
347
1998
270. 512
438
1999
228.020
133
2000
627.484
250
2001
572.485
1367
2002
2444
change was characterized by a decrease in density on
shoals and a movement of spawning females to deeper
water, withand a more scattered distribution than in the
early 1990s. Our results confirm previous observations
reported by Ehrlich et al.1, who analyzed ichtyoplankton
samples collected from 1973 to 1999, in the traditional
spawning area of Isla Escondida. These authors did not
observe significant environmental anomalies that might
have affected the spawning of hake and associated the
change with the high levels in fishing exploitation in the
1990s. These shifts in the pattern of reproduction led to
the following question: "How does the movement of the
center of spawning affect the recruitment of Patagonian
hake?" — given that different environmental conditions
could be present in the new spawning area.
Our analyses show that the abundance of active fe-
males offshore of the north Patagonian area increased
from 1998 to 2001, coinciding with a significant de-
crease in hake biomass in the shallow waters of Isla
Escondida. During these years, demographic changes
in the offshore area were characterized by an increase
of larger females (>50 cm TL) compared to previous
years. The increase in proportion of older individuals
in spawning condition may result in a greater contribu-
tion to egg production because of the higher fecundity
produced by larger females (Mairteinsdottir and Thora-
rinsson, 1998). In fact, egg production estimated for the
offshore Patagonian hake during January showed an in-
crease since 1998, with the highest values in 2000 and
2001 (400% more than those estimated in 1996-97). A
high proportion (70%) of these eggs were spawned by
females larger than 50 cm TL (s5-year old, Otero et al.,
1986), whereas in January 1996 and 1997 eggs were
mainly produced by young females.
Because of the displacement of active females to deep
water, the offshore north Patagonian area from 43°30'
to 45°S and between 50 m and 100 m depths was con-
sidered an important section of the spawning ground for
Patagonian hake after 1998. The comparison between
the January 1996 and 2001 surveys, in which inshore
1996
1997
1998
-1999
-2000
-2001
40 50 60 70 80
Total length (cm)
90
100
Figure 6
Relative egg production (%) by length class estimated
for Argentine hake (Merluccius hubbsi) in January from
1996 to 2001.
and offshore samples of the north Patagonian area were
collected, demonstrated this change. In January 1996,
spawning of Patagonian hake was concentrated inshore
(Isla Escondida), whereas in January 2001 reproduction
of this stock took place mainly offshore (Fig. 2). For
this reason, the offshore egg production value obtained
after 1998 was considered a representative index of the
spawning area.
Relative abundance of hake at age 1 (number of indi-
viduals/hour) in the north-Patagonian area, showed a
decline from 1996 to 2000 and an increase in 2001 and
2002, reaching the highest values of the study period. The
recruitment index obtained for 2002 (2444 individuals/h)
was about twice that estimated for 2001 (1367 individu-
als/h). According to Santos et al.,3 it is possible that this
value has been overestimated, because it was determined
3 Santos, B. A., E. B. Louge, and R. Castrucci. 2003. Estu-
dio de las variaciones conjuntas de la temperatura y de la
salinidad del area de cria de la merluza con los indices de
abundancia de los grupos de edad 0. 1 y 2. (enero 1995-enero
2002). Tech. Rep. 10/03. 6 p. INIDEP, CC.
Plata (7600), Argentina.
175. Mar del
NOTE Macchi et al.: Effect of the spawning pattern of Merluccius hubbsi on recruitment
451
from samples collected two months later (March) than
those during 1996-2001. These authors suggested that
the spatial distribution or catchability of juvenile hake
could have changed from January to March, resulting in
a greater abundance index during 2002.
The higher recruitment levels observed for Patago-
nian hake during 2001 and 2002 were coincident with
higher indices of egg production estimated offshore in
January during the two previous years (2000 and 2001).
Therefore, in principle we concluded that the change in
spatial location of spawners in the Patagonian stock did
not appear to negatively affect the recruitment of this
species. The next question to be answered is: "Why were
recruitment indices in the early 2000s higher than in
previous years?"
Several authors have analyzed the spawner-recruit
relationship in different species and have concluded
that recruitment is often positively correlated with
spawner biomass estimated from virtual population
analysis (VPA) (Myers and Barrowman, 1996). In the
case of Patagonian hake, the increase in abundance at
age 1 observed in 2001 and 2002 was not associated
with higher values of the VPA-based spawner biomass
in previous years (GEM, unpubl. data2). Thus, envi-
ronmental and ecological factors affecting prerecruit
mortality should be considered, mainly in association
with a no-fishing area implemented in 1997. Moreover,
the demographic composition and the nutritional state
of spawning females (maternal effect) are other factors
that have been related to recruitment levels (Trippel et
al., 1997; Kjesbu et al., 1998; Cardinale and Arrhenius,
2000).
Analysis of hydrographic characteristics from the
north-Patagonian waters in the 1980s and 1990s indi-
cated that the Patagonian shelf, including the Isla Es-
condida area, is a relatively stable environment (Erhlich
et al.2). On the other hand, analysis of temperature
and salinity data collected from 1995 to 2002 in the
nursery area of the Patagonian stock (San Jorge Gulf),
showed that higher values of salinity and temperature
during the time of hatching were associated with higher
indices of abundance at age 1, one year later (Santos
et al.3).
The high proportion of larger females in the offshore
area mainly in 2000 and 2001 may have affected the
quality as well as the quantity of hake progeny. In gen-
eral, older females produce larger eggs and larger lar-
vae with higher rates of survival, in combination with
more egg batches over a longer spawning season (Kjesbu
et al., 1996; Trippel, 1998). Previous reports showed
that M. hubbsi older than 5-years have a longer spawn-
ing season (Macchi et al., 2004) and produce heavier
eggs than young females do (Pajaro et al.4). Thus, an
increase in the proportion of older spawning females in
4 Pajaro, M, E. Louge, G. J. Macchi, N. Radovani, and L.
Rivas. 2002. Calidad de los ovocitos de la poblacion
patagonica de merluza {Merluccius hubbsi) durante la epoca
de puesta estival. Tech. Rep. 55/02, 13 p. INIDEP, CC.
175, Mar del Plata (7600), Argentina.
the stock may result in improved recruitment, as has
been reported for other species (Mairteinsdottir and
Thorarinsson, 1998).
The fishing regulation for Patagonian hake imple-
mented in the late 1990s mainly affected bottom trawl-
ers and the factory freezer fleet, which applied greater
fishing effort in the north Patagonian area during the
1990s. It is possible that this decline in harvesting
pressure by trawlers on Patagonian hake after 1997 in-
fluenced the reproductive success of this species. Stress
can have a negative impact on fish reproduction (Camp-
bell et al, 1994; Clearwater and Pankhurst, 1997). The
potential effects of trawl avoidance can affect the repro-
ductive physiology and behavior during spawning, which
could lead to the production of fewer viable juveniles
(Morgan et al., 1999).
Finally, other factors, such as predation and feeding
conditions within the new spawning ground of Patago-
nian hake, can affect survival of the early life stages.
In addition, future studies should include a comparison
between the inshore and offshore waters of the north-
Patagonian area with respect to the abundance of jel-
lyfish (i.e., Medusae and Ctenophora), which are known
to be major predators of fish eggs and larvae (Bailey,
1984; Fancett, 1988).
Acknowledgments
We thank Jorge Hansen for assistance with the method
used to estimate fish abundance. We would also like to
thank Hector Cordo for reading and making suggestions
to improve the manuscript.
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453
Feeding habits of the dwarf weakfish
(Cynoscion nannus) off the coasts
of Jalisco and Colima, Mexico
Alma R. Raymundo-Huizar
Centro Universitano de la Costa, Departamento de Ciencias
Universidad de Guadalaiara
Av. Universidad 203
Puerto Vallarta, Jalisco, CP 48280 Mexico
Horacio Perez-Espana
Centro de Ecologia y Pesquerias
Universidad Veracruzana
Dr, Castelazo s/n. Xalapa
Veracruz, CP 91 190 Mexico
Maite Mascaro
Laboratono de Ecologia y Conducta
Unidad Academica Sisal
Universidad Nacional Autonoma de Mexico
Sisal, Yucatan, CP 97355 Mexico
Xavier Chiappa-Carrara
Unidad de Investigacion en Ecologia Marina, FES-Z
Mexico, DF, CP 09230 Mexico
Present address: Unidad Academica Sisal
Universidad Nacional Autonoma de Mexico
Sisal, Yucatan, CP 97355 Mexico
E-mail address (for X. Chiappa-Carrara, contact author) chiappaig'servidor unam mx
Sciaenids from the Pacific coast of
Mexico are used as a second-class
fish species for human consumption
(Aguilar-Palomino et al., 1996). The
dwarf weakfish (Cynoscion nannus)
(Castro-Aguirre and Arvizu-Mar-
tinez, 1976) is often caught as bycatch
in the shrimp fishery but, because
of its small size (<27 cm TL, total
length), it is not considered a valuable
resource. This species can be found
in great numbers in waters between
100 and 812 m (Allen and Robert-
son, 1994; Fischer et al., 1995) asso-
ciated with the soft-bottom regions
off the coast of Jalisco and Colima
(Gonzalez-Sanson et al., 1997).
Previous studies of the trophic bi-
ology of the Sciaenidae (Chao and
Musik, 1977; Campos and Corrales,
1986; Chao, 1995; Pelaez-Rodriguez,
1996; Cruz-Escalona. 1998; Lucena
et al., 2000) have shown that they
feed on a variety of small fish and
benthic invertebrates (Allen and Rob-
ertson, 1994). However, there are few
studies concerning the feeding habits
of C. nannus, and its dietary prefer-
ences are not known. Considering its
abundance, C. nannus must play an
important role in the trophic rela-
tionships of soft-bottom ecosystems
in this region.
Most studies describing the feeding
habits of fish have used the normal-
ized version of the breadth niche in-
dex proposed by Levins (1968). This
index is based both on the number of
food resources and on the proportion
of prey used by a species. The appro-
priate distribution function for this
index ensures sample independence
among prey found in any particular
stomach. Distribution functions based
either on the number or the relative
biomass or volume of dietary items do
not ensure such independence, given
that all items found in any particular
stomach are statistically associated
(Hurlbert, 1984). Therefore, neither
the number nor the relative biomass
or volume of dietary items should be
used to calculate the Levins index.
The only distribution function that
ensures statistical independence is
that which is based on the proportion
of stomachs in which a certain food
resource is found (Krebs, 1999).
Considering the ecological impor-
tance of studying the feeding habits
of this abundant fish species, we ex-
amined trophic breadth variations
(temporally and ontogenetically) of
C. nannus. When attempting to cor-
rectly apply the Levins index, we
used the distribution function of prey
that ensures statistical independence
among sampling units.
Materials and methods
The sampling area was located in
the central region of the continental
shelf off the Pacific coast of Mexico,
where the mouth of the river Cuitz-
mala, in Punta Farallon, Jalisco
(19°22'N, 105°01'W), is the northern
limit, and Cuyutlan, Colima (18:55'N,
104°08'W), is the southern limit. Sam-
ples of C. nannus were collected on a
monthly basis from January to Decem-
ber 1996 (except February, August,
and September) on the research vessel
BIP V, equipped with a trawl net with
a pair of codends. Sampling was car-
ried out over seven transects perpen-
dicular to the coast, each comprising
four bathymetric strata: 20, 40, 60,
and 80 m mean depth.
Fish were individually identified,
measured (TL, ±1 mm), and the total
weight of each fish was recorded to
the nearest 0.1 g. The stomachs of
individual fish were dissected and
preserved in 10% neutralized forma-
lin. Stomach contents were analyzed
Manuscript submitted 16 May 2003
to the Scientific Editor's Office.
Manuscript approved for publication
20 December 2004 by the Scientific Editor.
Fish. Bull. 103:453-460 (2005 1.
454
Fishery Bulletin 103(2)
with a stereoscopic microscope and dietary items were
identified to the lowest taxonomic level possible by using
specialized keys. Garth (1958), Rodriguez de la Cruz
(1987), Hendrickx and Salgado-Barragan (1991), and
Hendrickx (1996), were consulted for crustacean iden-
tification, whereas Jordan and Evermann (1896-1900),
Castro-Aguirre (1978), Allen and Robertson (1994),
Thomson et al. (2000), and FAO guides were used for
fish identification (Fischer et al., 1995).
Both the number of individuals and weight of each
dietary category were quantified, and mean proportions
in terms of number (%7VV ) and biomass C7rWj ) were cal-
culated according to Tirasin and Jorgensen (1999):
IX
%X, =
j=i
■xlOO,
where X = the number or weight of each taxa i in the
jth stomach; and
k = the number of dietary components found in
all stomachs analyzed, /;,.
The percent frequency of occurrence of each component
was also obtained (c7cF). Finally, the index of relative
importance for each dietary category was calculated
(IRI, Pinkas et al., 1971; Rosecchi and Nouaze, 1987):
IRI, =(%Ni+%Pi)x%Fi.
Relative importance index values were expressed as
a percentage of the total items analyzed (Cortes, 1997)
and results were graphically represented as a rectangle
of base %F and height 7c N + 7cW.
Variance analysis was applied on transformed W'=
sin_1(VW)l gravimetric proportions of the dietary
components (Zar, 1999) to evaluate both monthly and
ontogenetic variations in the feeding habits of C. nan-
nus. The number [q,=l+3.322(Log]0n)] and width of size
classes (w=RTL/q) were considered for analysis, where ;;
is the sample size and RTL=TLmRX-TLmm.
For the analysis of trophic niche breadth, the nor-
malized version of the index proposed by Levins (1968)
was used. This index combines both the number of prey
resources used (k) (i.e., the trophic spectrum) and the
relative frequency with which each prey resource is
consumed (J). This represents the distribution function
of prey proportions in diet (Hespenheide 1975; Hurlbert,
1978):
(n, \
Ba-
k-1
Because the ensemble of prey found in any given
stomach does not constitute independent samples (Hurl-
bert, 1984), pf was calculated as the proportion of indi-
vidual fish (iV*) that consumed a certain food resource
in relation to the number of resources used by the total
number of fish:
N
YTn sothatI^ = 1-
Ba values range between 0 and 1. Zero values indi-
cate that fish feed on only one prey type, representing
the minimum diet breadth and high feeding special-
ization. Unity values, on the other hand, indicate that
the species consumed all k food resources in the same
proportion (p; = l/&), representing no selection among
prey types and the widest possible trophic niche (Gibson
and Ezzi, 1987; Labropoulou and Eleftheriou, 1997). Ba
values were calculated on the basis of matrix resources
(Colwell and Futuyma, 1971) both for each month and
for each size class. The percentage similarity measure
(/?) between size classes q' and q" (Renkonen, 1938;
Schoener, 1970; Hurlbert, 1978) was calculated as
V-=l"2
H\pJq--p,A
where p is the proportion of individual fish in each size
class that consumed a certain food resource, calculated
over the total number of stomachs per size class.
Confidence intervals (CI95%) of Ba were obtained by
means of the bootstrap method (Mueller and Altenberg,
1985; Efron and Tibshirani, 1986) by considering two
thousand resamplings of the data (Hamilton, 1991).
Results
The 311 Cynoscion nannus examined ranged from 7.5
to 20.6 cm TL. Food was found in 287 (92%, rang-
ing from 85% to 98% among size classes) stomachs.
The trophic spectrum of C. nannus is composed of 29
dietary items (Table 1), which were classified into four
general categories: penaeid shrimp, fish, stomatopods.
and cephalopods.
Penaeid shrimp constituted the principal dietary cat-
egory of C. nannus (A^ = 82.5%, Wf = 35.4%; Fj=43.9%,
77?/j = 74.6%; Fig. 1), of which juvenile stages were the
most frequent (Ff=23.4%). Fish were the second most
important category (7Vf = 6.5%, Wf = 36.5%, Fv = 37.7%,
7ff/j = 14.5% ), followed by stomatopods of the Squilla
genus (iV—5.8%, W==8.6%, FI=25.5%, 7/^ = 6.6%). The
cephalopod Loliopsis diomedae was the last category in
order of importance (JV==1.0%, Wf = 12.4%, 7^ = 4.2%,
IRI; = 1.87c).
Overall, significant differences in diet were found
between individuals of different size classes (F=1.03;
P<0.05). Values of the percentage similarity of diet (i?)
between size classes were, in general, <50% (Table 2).
R -values were relatively high only among size classes 2
NOTE Raymundo-Huizar et al.: Feeding habits of Cynoscton nannus
455
Table 1
Composition of the trophic spectrum of Cynoscion nannus
(7.5 cm 5
TL s20.6 cm; n
=287) from the coast of Jalisco
and Colima
(mean percentage by weight [g; %W], frequency of occurrence [%F'_
, number [%N],
and index of relative importance [%/ft/| of
prey).
Dietary categories
7c W
9cF
%N
%IRI
Cephalopods
Loliopsis diomedae
12.4
4.2
1.0
1.8
Remains
0.1
0.4
0.1
0.0
Stomatopods
Squilla sp.
5.9
19.7
4.0
6.4
S. panamensis
1.5
1.7
0.8
0.1
S. hancocki
0.5
1.7
0.4
0.0
S. mantoidea
0.7
2.5
0.7
0.1
Penaeid shrimps
Solenoeera sp.
7.6
10.9
4.3
4.2
S. florea
2.2
1.3
0.6
0.1
S. mutator
3.8
2.9
4.6
0.8
Traehypenaeus brevisuturae
3.5
5.4
2.3
1.0
Juvenile shrimps
18.2
23.4
70.8
68.4
Other crustaceans
Carideans
1.3
4.2
0.9
0.3
Panulirus sp. larvae
0.1
0.4
0.1
0.0
Other crustacean larvae
0.1
0.4
0.3
0.0
Euphausiids
0.5
1.3
2.3
0.1
Microcrustaceans
0.2
0.4
0.1
0.0
Unidentified remains
4.2
13.8
—
1.9
Fish
Cynoscion nannus
2.1
0.8
0.4
0.1
Cherublemma emmelas
1.3
1.7
1.0
0.1
Polydactylus opercularis
1.6
1.3
0.4
0.1
Ophidium sp.
0.7
0.4
0.8
0.0
Monolene sp.
0.9
0.4
0.1
0.0
Symphurus sp.
0.1
0.4
0.1
0.0
Bregmaceros bathymaster
1.6
2.5
0.7
0.2
Anguilliformes
1.2
2.1
0.5
0.1
Leptocephalus larvae
8.9
4.2
1.1
1.4
Other fish larvae
1.4
1.7
1.0
0.1
Unidentified remains
16.6
22.2
0.3
12.3
Anelids
Polychaeta
0.62
1.26
0.38
0.0
Table 2
Percentage similarity
values iR) of the diet between size
classes (cm, TL) of Cyn
oscion nannus
(ra=287) from the coast of Jalisco
and Colima.
Size class (cm)
7.0-8.9
9.0-10.9
11.0-12.9
13.0-14.9
15.0-16.9 17.0-18.9
Size class (cm)
9.0-10.9
37.0
11.0-12.9
44.2
54.2
13.0-14.9
33.5
65.1
51.1
15.0-16.9
31.0
47.6
51.4
64.1
17.0-18.9
12.5
31.6
39.6
38.0
40.4
19.0-20.9
29.3
45.8
44.3
47.9
40.1 21.6
456
Fishery Bulletin 103(2)
100-
80-
% Weight
o o
1
3
20-
0-
20-
5
— W-^
2
II I
4 6
1 40-
E
% 60-
80-
0 20 40 60 80 100 120 140 160
Cumulative frequency of occurence (%)
Figure 1
Graphical representation of the percentage values of the index of relative
importance (IRI) of the main dietary components found in the stomachs
of Cynoscion nannus (n=287). 1: penaeid shrimps; 2: stomatopods;
3: fish; 4: crustacean remains; 5: cephalopods; 6; other crustaceans.
1 oo-
n=22
n=45
n=53
n=59
n=36
n=37
n
= 35
0.75-
i
i
(
»
0.50-
<
i
I
i
i
i
0.25"
4
>
i
»
.«»■
„c/
.c
<*■
J^
Size class (cm)
Figure 2
Ontogenetic variations of the diet diversity index (B<7±CI9Vi )
of Cynoscion nannus (n is the number of stomachs contain-
ing food).
through 5 (51.1%-65.1%). The trophic spectrum of
the smallest C. nannus (7 cm sTL slO.9 cm, n = 67)
was composed by crustaceans (W^ = 68%), mostly
carideans and stomatopods (W^ = 2Q9c). The diet
of intermediate individuals (11 cm sTL sl6.9 cm;
/; =148 ) was composed by penaeid shrimp, fish, and
stomatopods. Only fish of the size classes grouped
in this range showed percentages of diet similarity
>50%. Among C. nannus between 17 and 18.9 cm
TL (« = 37), the value of consumed fish biomass at-
tained 69%, whereas that of penaeid shrimp reached
20%. Only among the larger individuals (19 cm sTL
s20.9 cm; n = 35) did cephalopods attain high gravi-
metric values (W^=457() followed by penaeid shrimp
(W£=38%).
Values of trophic niche breadth for each size class
indicated ontogenetic variation in the diet (Fig. 2).
The smallest individuals fed on a smaller number
of prey species and showed a trend towards higher
trophic specialization. Larger individuals, however,
had a wider trophic spectrum and fed on a greater
number of different prey species.
Temporal variations in the dietary composition
of C. nannus were significant (F=3.58; P<0.05).
During the first months of the year, C. nannus
consumed a higher percentage offish ( WJ = 37.2'7f ),
NOTE Raymundo-Huizar et al.: Feeding habits of Cynoscion nannus
457
1.00-
n = 20
n- 25
II
075-
II
n= 39
n=34
n -
35
n -
24
n=24
iS 0.50-
II
n= 58
"
, , n = 28
0.25-
"
uuu"l i i i I I I I I I I I
Month
Figure 3
Monthly mean values of the diet diversity index [Ba± CI95,; 1 of
Cynoscion nannus. The overall mean value of the index (Bo; )
and its confidence intervals (CI95%; ....) are shown in is the number
of stomachs containing food).
whereas towards the end of the year, penaeid shrimp
were eaten in higher proportions (Wf = 50.6%). During
May, stomatopods and carideans were found with higher
biomass values than during the rest of the year lW^
= 68.2% and 20%, respectively). Cephalopods were found
in most months with biomass values ranging from 4%
to 34% of consumed biomass.
The mean value of diet diversity was 0.41 (±0.18
CIg5<7t). Although the number of dietary categories for
C. nannus that were identified was high (29 prey types),
there were a few items with significant importance.
Monthly variations in Ba ranged from 0.1 to 0.8 (Fig.
3). During most of the period analyzed, Ba values were
not significantly different from each other as shown by
the lack of overlap between CI95,-. The only exceptions
were January and April, when CI95% was above the
mean Ba ±CI95Q value, and October when ClS59 was
below the mean Ba.
Discussion
Cynoscion nannus is a carnivorous fish that feeds on
at least 29 different prey types. Although cannibal-
istic behavior has been reported for several fish spe-
cies in a variety of habitats and life-history strategies
(Smith and Reay, 1991), C. nannus as a prey type was
found in only 0.8% (two individuals >15.0 cm TL) of all
stomachs analyzed. According to the IRI values, crus-
taceans— specifically juvenile shrimp and stomatopods
of the genus Squilla — appear to be the most important
items in the diet. The type of substrate can influence
the feeding habits of these fish. For example, Minello
and Zimmerman (1984) observed that under experimen-
tal conditions, the feeding preferences of C. nebulosus
(16 cm^TL<;21 cm) for Farfantepenaeus aztecus varied
depending on the substrate. These authors suggested
that substrate characteristics determine the burrow-
ing capacity of F. aztecus and thus predator avoidance.
In the study area, juvenile shrimp and stomatopods
of the genus Squilla can be abundantly found in soft-
bottom habitats (Gonzalez-Sanson et al., 1997). Both
the cephalopod iLoliopsis diomedae) and the fish spe-
cies found in the stomach contents of C. nannus are
pelagic or demersal species, indicating that the feeding
activities of C. nannus are not exclusively limited to the
benthos, and that this species can forage throughout
the water column. Results in the present study provide
evidence that fish feeding at different water depths have
access to a broader variety of prey types. This has been
shown both for other Sciaenidae (Chao and Musik, 1977;
Campos and Corrales, 1986; Chao, 1995; Pelaez-Rodri-
guez, 1996; Cruz-Escalona, 1998), and other species of
demersal fish (Lucena et al., 2000).
458
Fishery Bulletin 103(2)
It should be noted that graphic representations of the
IRI values are more accurate in describing the diet of
fish species (Cortes, 1997). Our results (Fig. 1) demon-
strate that the three indices representing the relative
importance of each food item highlight the influence
that the percentages of occurrence, by number and by
weight, have on the overall IRI values.
The temporal analysis of the tropic spectrum of C.
nannus showed that during October, November, and
December this species fed mainly on penaeid shrimps.
Fish prey were abundant in stomachs collected only
during March, April, June, and November. Stomato-
pods were present all year round, but only abundant
during May. Low Ba values in October were due to the
prevailing consumption of Solenocera spp. Monthly dif-
ferences in the diet of C. nannus were most probably in
accordance with the seasonal variations in prey species
abundance, which in turn determined their availability.
Lucena et al. (2000) found that temporal variations
in the diet of C. guatucupa from southern Brazil are
related to seasonal production cycles of prey, mainly
fish and crustaceans, thus supporting the view that
sciaenids can generally be considered opportunistic
species.
Results of this study showed ontogenetic variations
in the trophic spectrum of C. nannus. The smallest
individuals (7 cm <rTL <;10.9 cm) feed mainly on sto-
matopods, whereas larger individuals (all cm TL), con-
sume less stomatopods and more penaeid shrimp and
fish. Merriner (1975) also found ontogenetic variations
in the diet of C. regalis, where the smallest individu-
als (age group "0") fed on crustaceans and small fish.
The relative importance of shrimp, however, decreased
as C. regalis increased in size, and individuals of age
group "2" generally consumed different species of clu-
peids, depending on the local abundance of each prey
species. The measure of percentage similarity among
size classes (Table 2) shows that C. nannus share a
limited number of resources. Only fish belonging to
intermediate lengths feed on the same prey types in
percentages greater than 50% for the total number of
food resources used.
Ontogenetic changes in the diet of C. nannus ob-
served in the present study are due to differences in
diet composition and proportions of consumed prey.
These results suggest that food types are ingested un-
equally as fish grow and that morphological and physi-
ological changes take place. As fish grow, the size of
their mouth increases proportionally, their swimming
capacity is modified, and their energetic requirements
vary. Thus, larger fish have different feeding require-
ments than smaller ones and will attempt to satisfy
them by consuming a larger variety of prey types. As C.
nannus grow, Ba values increase and the trophic spec-
trum of the species grows wider (Fig. 2). Our results
indicate that there is a pattern of differential use of
food resources throughout the different size classes of
C. nannus, and suggest a possible ecological strategy to
reduce intraspecific competition for food in the popula-
tion (Schoener, 1974; Werner, 1979).
The increasing variety of food resources used as
predators increase in size is a common pattern among
marine organisms, including invertebrates (Rangeley
and Thomas, 1987; Mascaro and Seed, 2001). These
ontogenetic variations in food preferences can be ex-
plained by changes in foraging behavior where preda-
tors of certain size classes actively select their prey
(Jubb et al., 1983; Allan et al., 1987). Alternatively,
they can be the result of passive mechanisms that do
not involve individual decisions associated with age or
life stages, such as differences in the predator's mouth
structures, changes in movement velocity of both prey
and predator, and spatial or temporal variations in
habitat as predators increase in size (Hughes, 1979;
Rodrigues et al., 1987).
To show that Ba values are affected by the type of
prey distribution function used, we calculated the mean
diet diversity index using 1) the proportion of the num-
ber of prey (N; Ba = 0.03), 2) the percent frequency of
occurrence of prey (F; Ba = 0.16), and 3) the proportion
of prey biomass (W; Ba = 0.32). The values obtained
were then compared to those calculated by considering
the proportion of individuals (2V*; Ba = 0.41) that use a
certain food resource for the total number of stomachs
analyzed. Ba values calculated by using N, F, and W are
markedly lower than the Ba value obtained by using
N*. These differences serve to underline the importance
of complying strictly with the property of statistic inde-
pendence of sampling units when the feeding habits of
a species are being studied.
Given the numerical importance of C. nannus as part
of demersal assemblages, observations on the trophic
spectrum of this and other species can help to generate
a conceptual model of the trophic webs and dynamics of
the feeding relations among communities found on the
continental shelf of Jalisco and Colima. an area that
has received little attention in the past.
Acknowledgments
J. Arciniega, R. Garcia de Quevedo, and V. Landa-Jaime
kindly verified the taxonomic status of prey. We also
thank L. E. Hidalgo-Arcos for his technical support and
S. Bowers who edited the text.
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461
Using bone measurements to estimate the
original sizes of bluefish (Pomatomus saltatrix)
from digested remains
Anthony D. Wood
Box 200
Graduate School of Oceanography
University of Rhode Island Bay Campus
South Ferry Rd.
Narragansett, Rhode Island 02882
E-mail address: awoodigigso un edu
The ability to estimate the original
size of an ingested prey item is an
important step in understanding the
community and population structure
of piscivorous predators (Scharf et al.,
1998). More specifically, knowledge
of original prey size is essential for
deriving important biological infor-
mation, such as predator consumption
rates, biomass of the prey consumed,
and selectivity of a predator towards
a specific size class of prey (Hansel et
al., 1988; Scharf et al., 1997; Radke
et al., 2000). To accurately assess
the overall "top-down" pressure a
predator may exert on prey commu-
nity structure, prey size is crucial.
However, such information is often
difficult to collect in the field (Trippel
and Beamish, 1987). Stomach-con-
tent analyses are the most common
methods for examining the diets of
piscivorous fish, but the prey items
found are often thoroughly digested
and sometimes unidentifiable. As a
result, obtaining a direct measure-
ment of prey items is frequently
impossible.
Because of the problems of recon-
structing original prey size directly
from prey remains, numerous meth-
ods involving correlations between
measurements of specific morphologi-
cal features of the prey and prey size
(length) have been devised. External
body measures such as eye diameter,
and caudal peduncle depth (Crane et.
al., 1987; Serafy et. al., 1996; Scharf,
et. al., 1997), as well as numerous in-
ternal measures such as pharyngeal
arch length (Fickling and Lee, 1981;
Mclntyre and Ward, 1986; Radke et.
al., 2000), vertebral diameter (Pikhu
and Pikhu, 1970; Feltham and Mar-
quiss, 1989), and a variety of skeletal
bones (Newsome, 1977; Hansel et. al.,
1988; Scharf et. al., 1998) have been
used to generate models for predict-
ing original prey size.
The bluefish (Pomatomus salta-
trix) is a voracious piscivore and is
among the top predatory fish species
in the western North Atlantic Ocean
(Buckel et. al., 1999). Bluefish are an
important fish both commercially and
recreationally, and over the past two
decades stocks off the eastern coast
of the United States have experi-
enced a dramatic decline. From 1978
through 1996, the commercial land-
ings and spawning stock biomass of
bluefish declined by over 60'~A (Fahay
et. al.1). A variety of mechanisms
have been proposed to explain this
dramatic decline, including intense
predation by large apex predators.
It is known that bluefish act as an
important prey species for a num-
ber of apex predators in the North
Atlantic, most notably the shortfin
mako (Isurus oxyrinchus). Stillwell
and Kohler (1982) sampled 399 ma-
kos from 1972-79 and found that
bluefish made up 85% of the diet by
volume. The mako diet has recently
been reviewed and it appears that
the incidence of bluefish in the diet
has increased (assume 1 mL = l g for
flesh) to 94% of their diet by weight
(Wood et al.2). Bluefish have also
been found to be important in the di-
et of bluefin tuna (Thunnus thynnus)
(Chase, 2002), swordfish (Xiphias
gladius) (Stillwell and Kolhler, 1985),
blue shark (Prionace glauca) (Kohler,
1989), and the thresher shark (Alo-
pias vulpinis) (Kohler3).
The motivation for this study came
from field sampling shortfin mako
(Isurus oxyrinchus) stomach contents
where it was observed that bluefish
jaw bones and various other skull
bones were often intact, even if the
rest of the prey fish was digested.
To generate accurate estimates of
the original prey size a series of pre-
dictive equations was generated by
regressing bluefish skull bone mea-
surements with the fork length (FL)
and total length (TL) of the fish. Five
skull bones were chosen to obtain
measurements for the relationships:
the dentary, maxilla, premaxilla,
opercle, and cleithrum (Fig. 1). These
five bones were chosen because they
are strong bones (with the exception
of the opercle), covered by extensive
musculature, and assumed to be re-
silient to digestion.
Materials and methods
During June-September of 2000 and
2001, bluefish were collected by rod
and reel and by otter trawl in Narra-
gansett Bay, RI, and at bluefish fish-
ing tournaments along the northeast
coast of the United States from Ocean
1 Fahay. M. P.. P. L. Berrien, D. L. John-
son, and W. W. Morse. 1999. Essential
fish habitat source document: Bluefish,
Pomatomus saltatrix, life history and
habitat characteristics. NOAA Tech.
Memo. NMFS-NE-144, 68 p. U.S.
Department of Commerce, NOAA,
NMFS-NEFSC. Woods Hole, MA.
2 Wood, A. D., B. Wetherbee, N. E. Kohler.
F. Juanes and C. Wilga. 2004. In
prep. Predator prey interaction between
the shortfin mako (Isurus oxyrinchus)
and bluefish (Pomatomus saltatrix).
3 Kohler, N. E. 2001. Personal commun.
NMFS Narragansett lab, 28 Tarzwell
Drive, Narragansett, RI 02882.
Manuscript submitted 4 February 2004
to the Scientific Editor's Office.
Manuscript approved for publication
21 December 2004 by the Scientific Editor.
Fish. Bull. 103:461-466 (2005).
462
Fishery Bulletin 103(2)
D
OPL
PMXL
E
MXL
DN
D8L
| — | = 10 mm
Figure 1
Diagrams of the five bluefish iPomatomus saltatrix) skull bones
used in this study: (A) premaxilla; (B) maxilla; (C) dentary; (D)
opercle; and (E) cleithrum. Bones came from a 701-mm (FL) fish
and are drawn to scale with respect to each other. The scale bar
represents 10 mm. Measurements for each bone were taken along
the longest axis and were given the following abbreviations: PMXL
(premaxilla length), MXL (maxilla length), DN (dentary length),
DBL (dentary body length), OPL (opercle length), CL (cleithrum
length).
City, MD, north to Bayshore, NY. Upon retrieval, the
fork length (FL) and total length (TL) of each fish were
measured to the closest mm. The heads of the bluefish
were then removed by cutting approximately 5 cm behind
the pectoral girdle, and all heads were immediately
placed on ice. Samples were returned to the laboratory
and kept in a cool room on ice until the selected bones
could be extracted and measured (within 24 hours).
Bones were extracted by immersing the bluefish heads
in boiling water for a short period of time (between 30
and 180 seconds, depending on the size of the fish and
on the amount of musculature around the bones). The
dentary, maxilla, premaxilla, opercle, and cleithrum
were dissected from the left side of each fish and mea-
sured to the nearest 0.1 mm by using 0-150 mm dial
calipers. Measurements were taken linearly along the
longest axis of each bone and the following abbrevia-
tions were used to indicate lengths: DBL (dentary body
length), DN (dentary length), OPL (opercle length), CL
(cleithrum length), MXL (maxilla length), and PMXL
(premaxilla length) (Fig. 1). In cases where left bones
were damaged, or it was determined that an accurate
measurement could not be retrieved, right-side bones
were measured in place of the damaged bones.
Least squares regression analyses, which reveal the
relationship of each of the bone measurements to FL
and TL, were then conducted to generate predictive
equations. The strength of each of the correlations was
judged by both the r2 values and by calculating the
mean percent prediction error for each model, where the
percent prediction error for a model (Sharf et. al., 1997)
is calculated by the following equation:
NOTE Wood: Using bone measurements to estimate the size of Pomatomus saltatnx 463
§ ^ V '
CD
FL= 1827 x DBL- 22 A6 ^f §"
FL= 10.97 x DN- 11.27 -^m
o
o -
CO
>^ o
^^
o
o -
co
^^
III I I 1 1 1 [ 1 1 1
5 15 25 35 45 55 5 15 25 35 45 55 65 75 85
Dentary body length (mm) Dentary length (mm)
t o -
E °>
FL= 10.19 x OSL- 16.51 ^f S~
FL = 6.38 xCt- 20.87 -^
length
600
iiS** ^ ~
•V«
Fork
300
I
^^ I-
^^
1 I I I I I I I I
k i I I I I I I
5 1 5 25 35 45 55 65 75 85 0 20 40 60 80 1 00 120 1 40
Opercle length (mm) Cleithrum length (mm)
o O /
CD
FL= 10.48 x MXL- 1593 -^ §"
FL = 11.11 x PMXL- 12.99 -S*
O
o -
CD
*•* o -
O
o -
CO
_^f^ CO
Jf£*>
I I I I I I I I I I I I I I I I I 1
5 15 25 35 45 55 65 75 85 5 15 25 35 45 55 65 75 85
Maxilla length (mm) Premaxilla length (mm)
Figure 2
Fork length (mm) in relation to six skull bone measurements (mm) in bluefish (Poma-
tomus saltatrix). Resulting linear regression models and trendlines are shown.
( Observed - Predicted)
(Predicted)
xlOO.
To determine if any one bone or set of bones provided the
best predictor equation, comprehensive models involving
sets of bones were fitted in a stepwise linear algorithm
by using the Akaike information criterion (AIC) as the
criterion for model selection. Models were generated in
both a forwards and backwards manner in order to con-
firm that the same model was returned in all cases.
Results
Fork length (FL) and total length (TL) measurements
were taken from 58 bluefish ranging from 110 mm to 900
mm FL. The resulting regression equations correlating
skull bone measurements to FL (Fig. 2) were highly
significant (P=0.005 for the dentary correlation and
P<0.001 for the rest of the models). The r2 values for the
FL predictive equations ranged from 0.988 to 0.997, and
the mean percent predictive errors ranged from -0.03
to 1.19 (Table 1). Similarly, all of the resulting models
correlating the bone measurements to total length (Fig.
3) were highly significant (P<0.001, r'2 values ranging
from 0.987 to 0.996, and mean percent predictive errors
ranging from -0.11 to 1.07 [Table 1]).
Bones were ranked from best predictor to worst pre-
dictor for both the FL and TL models by using the
Akaike information criterion (AIC). In both cases the
premaxilla was ranked the best predictor bone, followed
by the maxilla, the opercle, the dentary, the cleithrum,
and finally dentary body length. The bone measure-
ments included in the stepwise multiple regression mod-
el for predicting fork length were PMXL, OPL, and DN
(Table 2). In the best predictor model for total length,
PMXL, OPL, DN and CL were included (Table 2).
464
Fishery Bulletin 103(2)
Table 1
Resulting predictive equations of fork and total length in relation to several skull bone measures with corresopnding
coefficient
of determination (r2) and P-values, and
mean percent predictive errors
OPE) for each model.
Bone
Fork length
r2
P-value
%PE
Dentary body length (DBLl
FL = 18.27<DBL>- 22.46
0.988
<0.001
0.54
Dentary (DN)
FL = 10.97(£W)- 11.27
0.996
0.005
-0.03
OperclelOPL)
FL = 10.19(OPL)- 16.51
0.997
<0.001
0.28
Cleithrum(CL)
FL = 6.38(CLl- 20.87
0.993
<0.001
1.19
Maxilla (MXL)
FL= 10.48 (MXL)- 15.93
0.997
<0.001
0.31
Premaxilla(PMXL)
FL = ll.ll(PMA'L) - 12.99
0.997
<0.001
0.26
Bone
Total length
r2
P-value
%PE
Dentary body length (DBL)
TL = 20. 20(DSL) - 27.69
0.987
<0.001
0.46
Dentary (DN)
TL= 12.130W) - 15.42
0.996
<0.001
-0.11
OperclelOPL)
TL= 11.27IOPD- 21.13
0.996
<0.001
0.15
Cleithrum(CL)
TL = 7.05ICD- 26.13
0.994
<0.001
1.07
Maxilla (MXL)
TL= 11.59(MA'L)- 20.43
0.996
<0.001
0.19
Premaxilla(PMXL)
TL= 12.28(PMXLl- 17.20
0.996
<0.001
0.14
Table 2
Independent variables included in the stepwise linear regression models used to estimate original bluefish fork length and total
length.
Variables included in
forward stepwise regression model
Variables included in
backward stepwise regression model
Fork length
Total length
PMXL, OPL, DN
PMXL, OPL, DN, CL
PMXL, OPL, DN
PMXL, OPL, DN, CL
Discussion
This study revealed that measurements of five skull
bones can be used as accurate predictors of original
fork length and total length of bluefish. Although the
methods of other studies were incorporated in this study,
the information is the first of its kind for bluefish and
may serve as a tool for the future study of this species
in the North Atlantic.
In recent years there has been growing concern over
the stability of the bluefish stock and an increased ef-
fort to gather information on the possible mechanisms
affecting bluefish abundance and distribution in the
western North Atlantic.4 One of the proposed mecha-
In 1997 Rutgers University and the NMFS organized a work-
shop to study the factors that could be contributing to the
depressed state of the bluefish stock. A similar concern was
expressed by Congress at this time, and the Rutgers and
NMFS workshop led to a request for proposals for bluefish-
related research in 1998, 1999, and 2000.
nisms that could be adversely influencing the recovery
of bluefish is top-down pressure by a number of apex
predators in the North Atlantic. Although indiscrimi-
nant predation on bluefish may not be a significant
pressure on the stock, size selective predation can dra-
matically alter the structure of the prey community
(Mclntyre and Ward, 1986; Trippel and Beamish, 1987;
Sharf et. al., 1997).
In order to study the consumption rates of key preda-
tors in an ecosystem it is necessary to gather informa-
tion on the sizes of the prey being consumed (Elliot and
Persson, 1978; Sharf et. al., 1998). However, it is often
difficult to estimate the original size of a prey item
from stomach content data because of the complications
caused by digestion. Erosion of the prey bones from
digestive juices can lead to measurement error or bias
when prey sizes are back-calculated from digested parts
(Sharf et al., 1998). Although bias from digestion is a
concern that should be addressed in studies, internal
bones and hard parts of fishes have been shown to be
excellent predictors of original prey size (Trippel and
NOTE Wood: Using bone measurements to estimate the size of Pomatomus saltatnx
465
TL = 20.20 x DBL - 27.69 ^f*
71 = 12.13 xDW- 15.42 ^/^
o
m -
r-
•Z" m -
^^
o
o -
IT!
s^1* §"
y^
o
Lfi —
C\J
**• o
^^
■ 1 1 I 1 1 1 1 1 1 1 1
5 15 25 35 45 55 5 15 25 35 45 55 65 75 85 95
Dentary body length (mm) Dentary length (mm)
TL = 11.27 x OPL- 21 13 ^^
TL = 7.05 x CL - 26 1 3 ^^
Fork length (mm
250 500 750
250 500 750
l l l
^S^
I I I I I I I I
5 15 25 35 45 55 65 75 85 95 20 40 60 80 100 120 140 160
Opercle length (mm) Cleithrum length (mm)
-i
71= 11 59* MXL- 20 43 .^ H
TL= 12.28 x PMXL- 17.20 ^^
o
in -
vrf»'»
y0^
o
o -
IT)
r*^**^ § -
JiS^^
o
in -
CVJ
^^ l~
^^
II 1 1 1 1 1 1 1 1 1 1
5 15 25 35 45 55 65 75 85 5 15 25 35 45 55 65 75 85
Maxilla length (mm) Premaxilla length (mm)
Figure 3
Total length (mm) in relation to six skull bone measurements (mm) in bluefish (Poma-
tomus saltatrix). Resulting linear regression models and trendlines are shown.
Beamish, 1987; Hansel, 1988, Sharf et al., 1998). In
addition, the bones used in the present study are strong
bones (with the exception of the opercle), that are liable
to resist digestive erosion.
All the relationships generated in the present study
yielded very accurate predictions of original prey size,
but the jaw bones are of special interest. Bluefish can
be classified as predators that exhibit a biting behavior
during predation. Fish that show this type of predation
behavior have very heavy, robust jaw bones (Norton,
1995). The jaw bones (maxilla, premaxilla, and dentary)
of bluefish are both easily identifiable and likely resis-
tant to digestion, and when combined with the adequacy
with which original size can be determined from these
bones (based on AIC rankings and %PE), they are the
best option for researchers interested in back-calculat-
ing original bluefish sizes.
The results of this study provide a means to fur-
ther analyze the stomach contents of bluefish preda-
tors beyond identifying, and quantifying prey items.
The usefulness of this type of data has been shown
repeatedly for a number of species (Mclntyre and Ward,
1986; Feltham and Marquiss, 1989; Serafy et. al., 1996;
Sharf et. al., 1997; Sharf et. al., 1998). The ability to
back-calculate the original size of a prey leads to the
enhancement of diet studies and allows for more accu-
rate estimates of predator consumption rates. The lack
of this kind of data and correlations for many key prey
species in the Atlantic and elsewhere is surprising.
Acknowledgments
Funding for this study was provided by the Bluefish-
Striped Bass Dynamics Research Program at Rutgers
University in cooperation with the National Marine
Fisheries Service (grant NA97FE0363). I am indebted
to the numerous fishing tournament directors, as well
as the fishermen at the tournaments for allowing me to
collect many of the bluefish needed for this study. I am
466
Fishery Bulletin 103(2)
also especially grateful to Abby McLean for her help
with the exhausting task of measuring bones. Finally,
I wish to thank Francis Juanes for encouraging me to
pursue and publish this study and Jeremy Collie and
two anonymous reviewers for comments that helped to
improve this manuscript.
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I < r.m/FBNMFMT PPTWTINr. flFFTrF- 0Cti\c. — 7Q1-110 / Q77Zf, Bo
ciitoH
$mt^hj<£&*®mt£}}
U.S. Department
of Commerce
Volume 103
Number 3
July 2005
Fishery
Bulletin
U.S. Department
of Commerce
Carlos M. Gutierrez
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
<^T0Fe%
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Volume 103
Number 3
July 2005
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 iNOAAl 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
469-488
489-500
501-515
516-523
524-535
536-543
544-552
553-558
559
Articles
Marina Biotog""
Woods Hole Oeanographic *'
L'b
jyt * d 2005
Dressel, Sherri C, and Brenda L. Norcross
Using poststratification to improve abundance estimates from
multispecies surveys: a study of |uvenile flatfishes
Francis, Malcolm P., and Clinton Duffy
Length at maturity in three pelagic sharks (Lamna nasus,
Isurus oxyrinchus, and Pnonace glauca) from New Zealand
Fritz, Lowell W., and Eric S. Brown
Survey- and fishery-derived estimates of Pacific cod
(Gadus macrocephalus) biomass: implications for strategies
to reduce interactions between groundfish fisheries and
Steller sea lions (Eumetopias jubatus)
Greig, Thomas W., M. Katherine Moore, Cheryl M. Woodley,
and Joseph M. Quattro
Mitochondrial gene sequences useful for species identification
of western North Atlantic Ocean sharks
Hawkins, Sharon L., Jonathan Heifetz,
Christine M. Kondzela, John E. Pohl, Richard L. Wilmot,
Oleg N. Katugin, and Vladimir N. Tuponogov
Genetic variation of rougheye rockfish (Sebastes aleutianus)
and shortraker rockfish (5. borealis) inferred from allozymes
Sulikowski, James A., Jeff Kneebone, Scott Elzey, Joe Jurek,
Patrick D. Danley, W. Huntting Howell, and Paul C. W. Tsang
The reproductive cycle of the thorny skate (Amblyra/a radiata)
in the western Gulf of Maine
Notes
Fey, Dariusz P., Gretchen E. Bath Martin, James A. Morris,
and Jonathan Hare
Effect of type of otolith and preparation technique on age
estimation of larval and |uvenile spot (Leiostomus xanthurus)
Piner, Kevin R., Melissa A. Haltuch, and John R. Wallace
Preliminary use of oxygen stable isotopes and the 1983 El
Niiio to assess the accuracy of aging black rockfish (Sebastes
melanops)
Subscription form
469
Abstract— Population assessments
seldom incorporate habitat informa-
tion or use previously observed dis-
tributions of fish density. Because
habitat affects the spatial distribution
offish density and overall abundance,
the use of habitat information and
previous estimates offish density can
produce more precise and less biased
population estimates. In this study,
we describe how poststratification can
be applied as an unbiased estimator
to data sets that were collected under
a probability sampling design, typi-
cal of many multispecies trawl sur-
veys. With data from a multispecies
survey of juvenile flatfish, we show
how poststratification can be applied
to a data set that was not collected
under a probability sampling design,
where both the precision and the bias
are unknown. For each of four spe-
cies, three estimates of total abun-
dance were compared: 1) unstratified;
2) poststratified by habitat; and 3)
poststratified by habitat and fish den-
sity (high fish density and low fish
density) in nearby years. Poststrati-
fication by habitat gave more precise
and (or) less design-biased estimates
than an unstratified estimator for all
species in all years. Poststratification
by habitat and fish density produced
the most precise and representative
estimates when the sample size in the
high fish-density and low fish-density
strata were sufficient (in this study,
Ha20 in the high fish-density stratum,
na9 in the low fish-density stratum).
Because of the complexities of statis-
tically testing the annual stratified
data, we compared three indices of
abundance for determining statisti-
cally significant changes in annual
abundance. Each of the indices closely
approximated the annual differences
of the poststratified estimates. Selec-
tion of the most appropriate index was
dependent upon the species' density
distribution within habitat and the
sample size in the different habitat
areas. The methods used in this study
are particularly useful for estimating
individual species abundance from
multispecies surveys and for retro-
spective studies.
Manuscript submitted 28 December 2001
to the Scientific Editor's Office.
Manuscript approved for publication
31 March 2005 by the Scientific Editor.
Fish. Bull. 103:469-488 (2005).
Using poststratification to improve
abundance estimates from multispecies surveys:
a study of juvenile flatfishes
Sherri C. Dressel
Brenda L. Norcross
Institute of Marine Science
School of Fisheries and Ocean Sciences
University of Alaska Fairbanks
245 O'Neill Building
Fairbanks, Alaska 99775-7220
Present Address (for S C Dressel): Alaska Department of Fish and Game
Commercial Fisheries Division
802 3rd Street
P.O. Box 240020
Douglas, Alaska 99824-0020
E-mail address (for S C. Dressel): shern_dressel(S)fishgame. state. ak. us
Scientists must be able to assess popu-
lation abundance with a high degree
of confidence to achieve the goals of
fishery management (Quinn, 1985).
To do this, survey designs and esti-
mation methods that minimize the
variance in estimates of abundance
are needed. Recently, the National
Research Council (NRC, 2000) rec-
ommended incorporating habitat
information and commercial fisher-
ies data in population assessments.
Both of these data may result in lower
variances in estimates of abundance.
Habitat type and habitat quality
are becoming more widely recognized
as primary determinants for the dis-
tribution and survival of marine fish
species (Murawski and Finn, 1988;
Gadomski and Caddell, 1991; Reichert
and van der Veer, 1991; Norcross et
al., 1999). Until recently, however,
few studies have been directed to-
ward defining fish habitat or using
habitat associations to help decrease
the variability in abundance estima-
tion (Scott, 1995). In response to the
growing recognition of the importance
of habitat, the Magnuson-Stevens
Fishery Conservation and Manage-
ment Act was amended in 1996 (Pub-
lic Law 104-297) so that the National
Marine Fisheries Service (NMFS) and
regional fishery management councils
must describe and identify essential
fish habitat (EFH) for managed spe-
cies. Similarly, a recent report from
the NRC calls for methods that link
environmental data to stock assess-
ments (NRC, 2000).
Poststratification can be used in a
number of different ways to address
the NRC recommendations. Although
poststratification is not a new statisti-
cal method, it is one that is not com-
monly used for estimating ground-
fish population abundance and can
be used to meet these newly defined
challenges. In contrast to a stratified
sampling design, poststratification
is a method that allocates samples
to strata after they have been col-
lected. As a result, habitat data col-
lected during a survey can be used
for stratification. When poststratifi-
cation is applied to data that have
been collected under a simple random
sampling design, the poststratifica-
tion estimator is unbiased and may
produce more precise estimates than
those from a simple random sampling
estimator. Poststratified estimates
will be nearly as precise as strati-
fied sampling with proportional al-
location, in which the sample sizes
in each stratum are proportional to
stratum sizes, if stratum sample sizes
are large (rc>20) and errors in esti-
mates of strata areas are negligible
(Cochran, 1977; Pollock et al., 1994;
470
Fishery Bulletin 103(3)
Scheaffer et al., 1996). If poststratification is applied to
data from a multispecies survey, 1) abundance data for
each species can be poststratified with different habitat
variables or 2) abundance data for every species can
be poststratified with the same variables, but different
stratum boundaries can be used for each species.
Many large-scale multispecies groundfish surveys are
conducted by using a stratified random sampling design
(Azarovitz, 1981; Halliday and Koeller, 1981; Pitt et
al., 1981; Martin1; Weinberg et al.2). Depth, distance
from or along shore, latitude, distance along depth
contours, or broad geographic features (such as bays,
capes, banks, gullies, and slopes) are used as stratum
boundaries in trawl surveys because they have been
shown to be related to species distributions. These fac-
tors are fixed spatially, allowing samples to be allocated
to strata prior to sampling. The same boundaries are
used for all species, and boundaries generally remain
the same over years.
When conducting a multispecies survey with a strati-
fied random sampling design, optimal stratification for
one species may not be optimal for others (Koeller, 1981;
NRC, 2000). Because the placement of strata boundar-
ies is critical for precise stratified estimates (Cochran,
1977), use of a stratified sampling design for a multispe-
cies survey may result in only small gains in precision
for some or all species. Poststratification is possible for
data that have been collected under a stratified design.
It can be used to stratify data more finely for individual
species. Under stratified random sampling, a simple
random sample is taken in each stratum. Thus, data
within each stratum can be poststratified separately
with additional variables and the abundance estimates
from each of the strata can be summed. The resultant
estimator is unbiased and likely will be more precise
than that of the original stratified design if sample
sizes in poststratified strata are large enough.
Often, researchers need to estimate abundance from
data sets that were not recorded under a probability
sampling design (a design in which randomness is built
into the survey design, such as simple random sampling
or stratified random sampling). Finances and logistics,
for example, may make it impossible to collect data
under a probability sampling design, researchers may
want to estimate species abundance from commercial
fisheries or other nonsurvey data, or previously collected
data sets that were not recorded under a probability
1 Martin, M. H. 1997. Data report: 1996 Gulf of Alaska
bottom trawl survey. NOAA Tech. Memo. NMFS-AFSC-
82, 235 p. National Technical Information Service, U.S.
Department of Commerce, 5285 Port Royal Road, Springfield,
Virginia 22161.
2 Weinberg, K. L., M. E. Wilkins, R. R. Lauth, and P. A. Ray-
more jr. 1994. The 1989 Pacific west coast bottom trawl
survey of groundfish resources: Estimates of distribution,
abundance, and length and age composition. NOAA Tech.
Memo. NMFS-AFSC-33, 168 p., plus appendices. National
Technical Information Service, U.S. Department of Com-
merce, 5285 Port Royal Road, Springfield, Virginia 22161.
sampling design may be used for retrospective studies.
In this article, we refer to data collection without a
probability sampling design as "haphazard sampling."
The use of haphazardly collected data for estimating
abundance is undesirable because they cannot be eval-
uated by the theorems of probability theory (Krebs,
1989). Although undesirable, it is often necessary to
analyze haphazardly collected data and effective meth-
ods are needed to do so.
Poststratification can be applied to data that were
not collected with a probability sampling design. When
poststratification is applied to data not collected under
a probability sampling design, the poststratification es-
timator, a design-based estimator, may be biased. When
analyzing such data, it is important both to maximize
the precision and to minimize the bias. Poststratifica-
tion has been applied to nonprobability samples in other
studies to increase the precision (Hall and Boyer, 1988)
and decrease the bias of estimators (Buckland and An-
ganuzzi, 1988; Hall and Boyer, 1988; Anganuzzi and
Buckland, 1989).
Poststratification can be useful, but has some draw-
backs. With poststratification, sample sizes within
strata are random variables — which are an additional
source of variability over that of a stratified sampling
variance estimator (Thompson, 1992; Scheaffer et al.,
1996). The variance of a poststratified estimator can
be estimated by using standard stratified sampling
variance equations and by incorporating an additional
approximate term to account for the random sample
sizes present with poststratification (Scheaffer et al.,
1996). Alternatively, the variance of a poststratified
estimator can be estimated by conditioning on samples
sizes and by applying the standard stratified sampling
variance equation (Thompson, 1992). For accurate post-
stratification estimates, the proportion of total possible
samples in each stratum (for this study the propor-
tion of the total survey area included in each stratum)
must be known or approximated closely enough that
the error in the approximation is negligible (Cochran,
1977). Error in estimates of stratum sizes causes bias
in poststratified estimates of abundance. Because error
in the estimation of stratum size is unaccounted for in
the estimated variance of poststratified estimates, the
estimated variances may be underestimates of the true
error (Cochran, 1977).
This study had two goals. The first goal was to evalu-
ate the benefits and drawbacks of using poststratifica-
tion to incorporate habitat and fish-density information
into estimates of abundance from multispecies survey
data that were not collected under a probability sam-
pling design. To achieve this goal, this study compared
three estimates of total abundance and variance (un-
stratified, poststratified by habitat, poststratified by
habitat and estimates of fish density in neighboring
years) for each of four species. The comparison was
made to determine whether poststratification of hap-
hazardly sampled data with habitat and fish-density
information increases the precision and helps account
for possible bias in abundance estimates.
Dressel and Norcross: Using poststrafication to improve abundance estimates from multispecies surveys
471
Because this study is an observational study
with haphazard sampling, the precision and
bias cannot be directly assessed. Instead, we
estimated and compared the precision by using
unstratified and poststratified estimators. We
qualitatively estimated the relative amount of
design bias (i.e., how representative the esti-
mates are) with the use of habitat. In previ-
ous studies (Norcross et al., 1995; 1997; 1999),
depth and sediment were identified as habitat
characteristics closely associated with the dis-
tribution of the four species in this study. From
depth, sediment, and fish abundance data col-
lected in this study we were able to identify
ranges of habitat characteristics associated
with areas of high, low, and no fish density.
By estimating the proportion of area (km2) in
the study area characterized by the ranges of
depth and sediment, it was possible to estimate
the proportion of the survey area with high,
low, and no fish density. Because samples in
our study were not randomly allocated, the
probability of selection was not equal among all
samples in the survey area. The resulting num-
bers of samples taken in areas of high, low, and
no fish density were not in proportion to the
size (km2) of those areas as it would have been
with repeated simple random sampling. There-
fore, by comparing the relative size of high, low
and no fish-density areas in the survey area
with the relative number of samples in those
areas, we made qualitative estimates of the design bias
associated with the estimators. Although an assessment
of the relative amount of design bias made in this way is
only an approximation, it is helpful when using haphaz-
ardly collected data in order to provide some indication
of the amount of design bias based on the disproportion
of samples in an area to the size of that area.
Because of the complexities of statistically testing the
annual stratified data, the second goal of our study was
to develop indices of abundance that closely approximat-
ed the annual differences of poststratified estimates and
that could easily be tested for statistically significant
changes between years. To achieve the second objective,
three indices of annual relative abundance were con-
structed and compared with respect to their estimated
relative precision and design bias: one from all sites in
the survey area, one from all sites within the species'
habitat, and one from all sites within an area of high
fish density within the species' habitat.
The data for this study were obtained from six years
of juvenile groundfish surveys conducted in Kalsin Bay
and Middle Bay, Kodiak Island, Alaska. The four spe-
cies studied were age-0 rock sole (Lepidopsetta spp.),
age-1 yellowfin sole (Pleuronectes asper), age-0 Pacific
halibut (Hippoglossus stenolepis), and age-0 flathead
sole (Hippoglossoides elassodon). The survey data were
collected during the six-year survey under three dif-
ferent survey designs, none of which were strictly ran-
domized, but each involved some degree of haphazard
Study area
Alaska.
Figure 1
(in black) in Middle and Kalsin Bays, Kodiak Island,
sampling due to weather, sediment structure, and other
logistical restrictions for beam trawling in small bays
off the Gulf of Alaska (Norcross et al.3). Although many
trawl survey data sets to which these methods could be
applied are collected under a probability sampling de-
sign where the estimator is unbiased, the haphazardly
collected data set used in our study was chosen to show
how poststratification can be applied when both the pre-
cision and the bias of the estimator are unknown.
Methods
Sampling
Middle and Kalsin Bays are part of Chiniak Bay, 10 nmi
south of the town of Kodiak, Alaska. The total size of
the study area, 87 km2, included the combined areas of
both bays and the areas directly outside the mouths of
the bays (Fig. 1). Middle Bay is 8 km long and has depths
of 50 m at the mouth of the bay and an area of 21 km2.
Kalsin Bay is 8 km long, has depths greater than 100 m
3 Norcross, B. L., B. A. Holladay, A. A. Abookire, and S. C.
Dressel. 1998. Defining habitats for juvenile groundfishes
in Southcentral Alaska with emphasis on flatfishes. Vol. I,
Final Study Report, OCS Study MMS 97-0046, 131 p. Coastal
Marine Institute, Univ. Alaska Fairbanks, Fairbanks, AK
99775.
472
Fishery Bulletin 103(3)
N 57.70
~ N 57.65
M 52.55
W 152.50
W 152.45
W 152 35
W 152.30
Longitude
Figure 2
Kalsin and Middle Bay sample sites (1991-96) and bathymetry. Fixed (sampled every year)
sites are noted.
at the mouth of the bay, and encompasses an area of
34 km2. Rocky cliffs and islands surround the mouths
of the bays, and rocks in the sediment made several
areas untrawlable (Fig. 2). Although trawling was not
conducted in these areas, depth and sediment data were
collected. In this analysis, untrawlable areas were still
considered possible flatfish habitat and were included in
the measurements of the size of the total study area.
Annual cruises were conducted in Middle and Kalsin
Bays for two weeks in August from 1991 to 1996. Ju-
venile flatfish were collected by using 3.05 and 3.66 m
plumb-staff beam trawls (Gunderson and Ellis, 1986).
Trawl nets were made of 7-mm square net mesh and had
a 4-mm codend liner that retained flatfish as small as 11
mm. Sampling methods were consistent for all six years
(Norcross et al., 1995; Norcross et al.3). Collections at
each sample site included a tow of 10 minutes or less, a
vertical CTD (conductivity, temperature and depth) cast,
and a sediment grab (0.06-m3 Ponar grab). The sampling
area of each tow was determined by the width of the
beam trawl, which was 0.74 of the beam length (Gunder-
son and Ellis, 1986), and distance towed was based on
global positioning system (GPS) coordinates. Fish were
identified to the lowest possible taxon and measured
to the nearest millimeter total length. At the time of
collections, all rock sole were identified as Pleuronectes
bilineatus. Following Orr and Matarese's (2000) revision
of the genus, we refer to these fishes as Lepidopsetta
spp. in this article because both species, L. bilineata and
L. polyxystra, were identified in the study area during
1996 sampling. Fish ages were determined by length-
frequency analysis. Fish catch-per-unit-of-effort (CPUE)
values were standardized to a 1000-m2 tow area.
Sampling designs varied from year to year (Norcross
et al.3). Extensive exploratory sampling was conducted
from 1991 through 1994 to describe juvenile flatfish
distributions in relation to habitat characteristics (Nor-
cross et al., 1995; 1997). The goal in these years was to
sample over the widest range of areas and habitat char-
acteristics possible within the depth, sediment, weather,
and logistical constraints. In 1995 and 1996, sampling
was stratified by depth and percent sand in sediment.
The sample allocation and the number of strata differed
in 1995 and 1996 (Norcross et al.3). Because of logisti-
cal constraints, samples were not randomly allocated
within each stratum. Within these sampling designs,
nine fixed sites were chosen, each with different depth
and sediment combinations and with high abundances
of one of the four species. Each of the nine fixed sites
was sampled at least once in each of the six years. For
this study, survey data in each year were treated as
unstratified samples that were not collected under a
probability sampling design.
Analysis
Poststratification Habitat preferences of juvenile fiat-
fishes, as defined by depth and sediment variables, have
been identified as affecting the distribution and abun-
dance of juvenile flatfish around Kodiak Island (Norcross
et al., 1995; 1997; 1999; Mueter and Norcross, 1999) and
elsewhere (Pearcy, 1978; Tanda, 1990; Burke et al., 1991;
Rogers, 1992; Walsh, 1992). Four areas were defined for
use in estimating total and relative abundance: habitat,
nonhabitat, high fish-density (HFD) and low fish-density
(LFD) areas. Percent sand was used as a continuous vari-
able of sediment type. Suitable habitat (habitat area) was
defined for each species as ranges of depth and percent
sand in which the species was caught during one or more
Dressel and Norcross: Using poststrafication to improve abundance estimates from multispecies surveys
473
of the six sampling years. Unsuitable habitat (nonhabitat
area) was denned for each species as ranges of depth
and percent sand in which the species was never caught.
Within the habitat area, the area of high fish density for
each year was defined as ranges of depth and percent
sand associated with CPUEs in the 75th-100th percentile
of nonzero catches in the five other years. The area of low
fish density was defined as the remaining habitat area
not incorporated in the HFD area.
In order for the poststratification method to estimate
abundance accurately (high precision and low bias), the
size of each stratum must be known or closely approxi-
mated (Cochran, 1977; Scheaffer et al., 1996). When
using habitat variables to determine stratum sizes, the
accuracy of stratum sizes defined by the boundaries is
heavily dependent upon the number and distribution
of habitat variable measurements. For our study, 243
depth and percent sand measurements collected over
the six years at trawl locations were used to determine
stratum boundaries. The ranges of depth and percent
sand that defined the four areas for each species were
contoured over the study area by using a minimum
curvature algorithm (Surfer, 1995). The size of each
stratum in relation to the size of the entire study area
was then visually estimated to the nearest square ki-
lometer. Although not used in our study, a digital rep-
resentation of the size of each stratum and the size of
the study area is recommended to produce more precise
estimates.
To assess the advantages and disadvantages of using
poststratification to estimate abundance, three esti-
mates of total abundance were calculated and compared
for each species in each year. An unstratified estimate
of total abundance was calculated from samples across
the entire survey area, with no differentiation with
regard to habitat. The unstratified estimate of total
abundance was calculated with the standard simple
random sampling equation
The estimate poststratified by habitat was calculated
as
isl=lN,yr
where fs, = the estimated population total;
L = the number of strata (here L=2, habitat and
nonhabitat);
N: = the total number of possible samples in stra-
tum ; (samples were standardized to 1000 m2,
therefore iV, x 1000 m2=stratum size); and
yi = the mean CPUE in stratum i.
A third estimate, poststratified by habitat and fish
density, was calculated with the same poststratification
estimator with L = 3. This poststratification estimator
used the HFD area of that year as one stratum, the
LFD area of that year as the second stratum, and the
nonhabitat area as the third. An approximate variance
estimator (Scheaffer et al., 1996),
VPGM
, N(N-n)^N, 2
£IB>-
was used to estimate the variance of each poststratifica-
tion estimator,
where V = the estimated poststratified variance of ist,
the estimated population total;
N = the total number of possible samples in the
survey area;
n = the total number of samples taken;
Nt = the total number of possible samples in
stratum i; and
s;2 = the sample variance in stratum i.
i = Ny,
where i = the estimated population total;
N = the total number of possible samples in the
survey area; and
y = the mean CPUE of all sites sampled in a
year.
The estimated variance for the unstratified estimator
was calculated as
The first term of the variance equation is the variance of
a stratified sample mean under proportional allocation.
The second term shows the amount of increase in vari-
ance expected from post- rather than prestratification
(Scheaffer et al., 1996).
Relative efficiency statistics were calculated for pair-
wise comparisons of the precision of the unstratified
and the two poststratified estimates. Pairwise com-
parisons of the estimates were made for each species in
each year. Relative efficiency was calculated as
V(i) = N
2 s
2\
m
R.E.
Va
where V(f ) = the estimated variance of the population
total estimate;
N = the total number of possible samples in the
survey area;
n = the total number of samples taken; and
s2 = the sample variance.
where V^ represents the variance of an unstratified
estimate or a stratified sample with fewer strata than
the estimate of variance represented by VB.
The variance of an estimate is directly affected by the
sample size (Zar, 1996). In our study, three total abun-
dance estimates and their respective variances were
474
Fishery Bulletin 103(3)
calculated and compared for each of the 24 species-
year combinations. One of the three total abundance
estimates was most precise for each of the species-year
combinations. For each species-year combination, the
habitat stratum sample size (used in the estimate post-
stratified by habitat), the HFD stratum sample size,
and the LFD stratum sample size (both used in the
estimate poststratified by habitat and fish density) were
plotted in relation to the total abundance estimator that
was most precise in order to investigate the influence of
sample size on the relative precision of the three total
abundance estimators.
Indices of abundance Three indices were constructed
for each species in each year to determine interannual
variations in relative abundance (mean CPUE): an all-
site index, a habitat index, and a HFD index. For each
species and year, the all-site index was the mean CPUE
from all sites sampled. The habitat index was the mean
CPUE from all sites sampled within the species' habitat
area. The HFD index was the mean CPUE from all sites
sampled within the species' HFD area.
CPUE values were not normally distributed and
therefore the Kruskal-Wallis nonparametric analysis
of variance test was used to test the three indices for
each species' differences in mean CPUE among years.
For species that showed significant differences (o=0.05),
a Tukey HSD (honestly significant difference) multiple
comparison test for unequal sample sizes was conducted
to determine which years differed (a=0.05). The Tukey
multiple comparison test was used because it is robust
with respect to departures from population normality
and homogeneity of variance (Keselman, 1976). The
results for the three indices for each species were com-
pared to see how the differences in estimating abun-
dance with the three indices affected conclusions of
significant differences in abundance between years.
Numerous sources of bias can affect estimators of
abundance from survey data. The poststratification
estimator and other design-based estimators may be
biased when applied to data that were not collected
under a probability sampling design, as done in the
present study. For a qualitative estimate of possible
design bias in the estimates, the annual proportion of
sample sites in each stratum (habitat, nonhabitat, HFD,
and LFD strata) were compared with the proportion of
area (km2) in that stratum. First, we compared the size
of the habitat area, in relation to the size of the total
survey area, with the number of samples taken in the
habitat area, in relation to the number taken in the
total survey area.
number of samples taken in the HFD area, in relation
to the number taken in the total habitat area.
Size of the HFD area
Size of the habitat area
Number of samples taken
in the habitat area
Size of the total survey area Number of samples taken
in the total survey area
Second, we compared the size of the HFD area, in
relation to the size of the total habitat areas, with the
Number of samples taken
in the HFD area
Size of the habitat area Number of samples taken
in the habitat area
Recognizing that the distribution of individuals var-
ied within and across strata, two measures were used
to better understand the distribution of each species in
each year. The proportion of zero catches (e.g., a "zero
catch" for rock sole indicates a tow in which no rock sole
were caught) and the mean CPUE of nonzero catches
were calculated for each species in each year over four
areas: the total survey area, the habitat area, the HFD
area, and the LFD area.
Results
Fish CPUE statistics were calculated for a total of 244
quantitative tows over the six sampling years (Fig. 2)
in habitats ranging from 1 to 111 m depth and from 0%
to 99% sand. Based on compiled data from all six years,
the habitat area for rock sole was defined by 1-84 m
depth and 2-99% sand; for yellowfin sole, by 2-43 m
depth and 24-99% sand; for Pacific halibut, by 2-27 m
depth and 2-99% sand; and for flathead sole, by 12-87 m
depth and 8-97%. sand (Fig. 3). The HFD area, defined
by depth and percent sand, was determined for each of
the four species in each of the six years (Table 1, Fig. 3).
Although the range of depth and the range of percent
sand were determined independently in each year, they
remained quite constant for each species over the six
sampling years.
The size of habitat area in relation to total area
ranged across species from 0.62 to 0.92 and, for each
species, the proportion of habitat sites to total sites
varied among years (Table 2). The proportion of sample
sites in habitat to sample sites in the total survey area
ranged from 0.88 to 1.00 for rock sole, 0.60 to 0.87
for yellowfin sole, 0.52 to 0.93 for Pacific halibut, and
0.29 to 0.67 for flathead sole. The relative number of
samples taken in each species' habitat area exceeded
the relative size of their habitat area (i.e., a positive
disproportion of samples in habitat), except for rock
sole in 1991 and 1994, yellowfin sole in 1993 and 1994,
Pacific halibut in 1993 and 1994, and all years for
flathead sole. On average, rock sole had a 5% positive
disproportion of samples in its habitat area, yellowfin
sole and Pacific halibut had an 11% positive dispropor-
tion of samples in their habitat area, and flathead sole
had a 15% negative disproportion of samples in its
habitat area.
The size of the HFD area in relation to habitat area,
and the number of sites sampled in the HFD area in
relation to the number sampled in the entire habitat
area, varied over the six sampling years for each of the
four species (Table 2). On average over the six years,
Dressel and Norcross: Using poststrafication to improve abundance estimates from multispecies surveys
475
Q.
CD
a
1.'
40 ..:
/
A
AA*
AA*A A
A
A*- • *
.....
A
*
■
Rock sole
zero catch
A nonzero catch
habitat area
Q. 60
CD
Q
Percent sand in substrate
VL^yzt&m
• •-
, I high fish-density
Yellowfin sole
zero catch
A nonzero catch
Percent sand in substrate
0.
2
■**"■
A..
*•■
Iff*
5^
Q- 60
Q
so
•
I
•
•
; habitat area
! i high fish-density
Pacific halibut
zero catch
A nonzero catch
I habitat area
i | high fish-density
Percent sand in substrate
& 60
Q
I- - -A-AI A
!*** A
-•"I*" : i Flathead sole
i
A*A
. A
A*
A .
A*A i A
A-*- -A-A_>
A'
' A \
zero catch
A nonzero catch
[ I habitat area
J ' high fish-density
Percent sand in substrate
Figure 3
Summary of 1991-96 tows, in relation to depth and percent sand.
Tows are divided into zero and nonzero catches for each species. The
dotted line separates the depth and percent sand characteristics of
habitat and nonhabitat areas. The dashed line separates the depth
and percent sand characteristics of high and low fish-density areas
within the habitat area.
rock sole had a 10% negative disproportion of samples
in the HFD area, Pacific halibut had a 3% negative
disproportion of samples in the HFD area, and flathead
sole had a 28% negative disproportion of samples in the
HFD area. For yellowfin sole, the average distribution
of samples between the high and low fish-density areas
was in direct proportion to the size of the areas, i.e.,
there was no disproportion of samples.
Two measures were used to characterize the distribu-
tion of a species within their habitat: the proportion of
zero catches and the mean of nonzero catches in high
and low fish-density areas. As expected, for all species
the average proportion of zero catches over all sites
was greater than the proportion of zero catches in the
habitat or HFD areas (Table 3). For rock sole, yellowfin
sole, and flathead sole, the average proportion of zero
476
Fishery Bulletin 103(3)
Table 1
Characteristics defining 1991
-96 high fish-den
?ity areas for each
species of flatf
sh. Ranges of depth and percent
sand, defining
the high fish-density (HFD) area,
and the associated spat
al coverage within the bay (km2).
Each
year's HFD area was deter-
mined as the range of depth
and
percent sand
associated
with the 75lh-100th
percentile of
nonzero catch from the other five
years.
Species
Year
Depth
(m)
Percent sand in
sediment
Size (km2)
minimum
maximum
minimum
maximum
Rock sole
1991
3.0
27.3
31.5
99.2
52
iLepidopsetta spp. )
1992
3.0
36.0
20.2
99.2
56
1993
3.0
27.3
31.5
99.2
52
1994
3.0
27.3
31.5
98.8
52
1995
3.0
27.3
31.5
99.2
52
1996
3.0
25.0
47.8
99.2
46
average
3.0
28.3
32.4
99.2
52
Yellowfin sole
1991
1.7
23.0
40.5
98.6
33
iPleuronectes asper)
1992
2.3
25.0
24.2
86.7
29
1993
2.3
25.0
24.2
86.7
29
1994
2.3
25.0
24.2
86.7
29
1995
2.3
25.0
24.2
86.7
29
1996
2.3
25.0
24.2
86.7
29
average
2.2
24.7
26.9
88.7
30
Pacific halibut
1991
2.5
25.0
52.3
99.3
39
l Hippoglossus stenolepis )
1992
2.3
27.0
52.3
99.3
41
1993
2.3
27.0
52.3
99.3
41
1994
2.3
27.0
52.3
99.3
41
1995
2.0
27.0
64.6
99.3
33
1996
2.3
25.5
52.3
98.4
37
average
2.3
26.4
54.4
99.1
39
Flathead sole
1991
19.8
87.0
17.4
89.1
42
(Hippoglossoides elassodon )
1992
25.5
87.0
10.7
89.1
38
1993
19.8
87.0
8.4
70.7
34
1994
19.8
67.5
10.7
89.1
40
1995
19.8
87.0
17.4
89.1
42
1996
19.8
64.0
17.4
89.1
39
average
20.8
79.9
13.7
86.0
39
catches in the LFD area was higher than in the HFD
area. For Pacific halibut, the average proportion of zero
catches remained approximately constant across the
entire habitat area. The relative mean nonzero catch
between the LFD and HFD areas varied across species,
ranging from 37% to 82% (Table 4).
In each of the 24 species-year combinations, three esti-
mates of population abundance were compared, except for
flathead sole in 1992 when no samples were taken in the
flathead sole HFD area (Fig. 4). In every case in which
the proportion of habitat stratum-size sites to total study
area sites exceeded the proportion of habitat stratum
size to total study area size (Table 2), the unstratified
estimate was greater than the estimate poststratified by
habitat (Fig. 4). In every case that the proportion of habi-
tat stratum sites to total study area sites was less than
the proportion of habitat stratum size to total study area,
the unstratified estimate was less than the estimate
poststratified by habitat. Similarly, in every case that
the proportion of HFD stratum sites to habitat stratum
sites exceeded the proportion of HFD stratum size to
habitat stratum size (Table 2), the estimate poststratified
by habitat was greater than the estimate poststratified
by habitat and fish density (Fig. 4). In all but two cases
in which the proportion of HFD stratum sites to habitat
stratum sites was less than the proportion of HFD stra-
tum size to habitat stratum size, the estimate poststrati-
fied by habitat was less than the estimate poststratified
by habitat and fish density. The two exceptions were for
Pacific halibut in 1991 and 1996, where the difference
between poststratified estimates was small. In 1991, the
estimate poststratified by habitat was 2.9% (8116 fish)
greater than the estimate poststratified by habitat and
fish density; in 1996, it was 0.56% (4905 fish greater).
Dressel and Norcross: Using poststrafication to improve abundance estimates from multispeaes surveys
477
Table 2
A comparison of the relative nt
mber of sample site
i and relative
size ( km2 ) of the habitat area
high fish-density ( HFD ) area, and
total study area. Comparisons
include the size of the habitat area versus the size of the study
area,
the number of sites
sampled
in the habitat area versus the number sampled in
the total study area, the size
of the HFD
area versus
;he size of the habitat
area, and the number of sites e
amplec
in the HFD
area versus
he nu
mber sampled in the habitat area.
Habitat sites/Total sites
Year
ha
size/ total stuuy sizeiiuii-j
Species
All years
1991 1992
1993
1994
1995
1996
average
Rock sole (Lepidopsetta spp. )
0.92
0.92 1.00
1.00
0.88
1.00
1.00
0.97
Yellowfin sole (Pleuroneetes asper)
0.66
0.78 0.87
0.63
0.60
0.80
0.80
0.75
Pacific halibut (Hippoglossus stenolep
s)
0.62
0.73 0.93
0.58
0.52
0.80
0.80
0.73
Flathead sole (Hippoglossoides elassodon )
0.67
0.43 0.29
0.67
0.56
0.60
0.60
0.52
High fish-density size/Habitat size
(km2)
High fish-density sites/Habitat sites
Species
Year
Year
1991
1992
1993
1994 1995
1996
average
1991 1992
1993
1994
1995
1996
average
Rock sole
0.65
0.70
0.65
0.65 0.65
0.58
0.65
0.64 0.73
0.42
0.45
0.55
0.50
0.55
(Lepidopsetta spp.)
Yellowfin sole
0.58
0.51
0.51
0.51 0.51
0.51
0.52
0.76 0.46
0.47
0.40
0.50
0.50
0.52
(Pleuroneetes asper)
Pacific halibut
0.72
0.76
0.76
0.76 0.61
0.69
0.72
0.69 0.86
0.79
0.62
0.63
0.54
0.69
(Hippoglossus stenolepis )
Flathead sole
0.72
0.66
0.59
0.69 0.72
0.67
0.68
0.52 0.00
0.50
0.43
0.50
0.44
0.40
(Hippoglossoides elassodon )
Calculations of relative efficiency among the three to-
tal abundance estimators showed increases in estimated
precision with stratification (Table 5). In most cases (18
out of 24), the estimate poststratified by habitat was
more precise (corresponding to a lower standard error
in Fig. 5) than the unstratified estimate. Of the 16 (of
23) cases in which the precision of both poststratified
estimates were greater than that of the unstratified
estimate, in half the estimate poststratified by both
habitat and density was more precise than the estima-
tor poststratified by habitat alone.
Sample sizes across the survey area and in each sub-
area (habitat, high fish-density, and low fish-density
areas) (Table 6) strongly influenced the precision of es-
timates. Habitat sample sizes for all species-year combi-
nations ranged from 4 to 45 (proportion of samples tak-
en in habitat ranged from 0.286 to 1.000); HFD sample
sizes ranged from 0 to 29 (proportion of samples taken
in the HFD area ranged from 0.0 to 0.8); and LFD
sample sizes ranged from 4 to 16 (proportion of samples
taken in the LFD area ranged from 0.125 to 0.583).
Although the number of samples in both the high and
low fish-density areas (Fig. 6, A and B) likely affected
estimates poststratified by habitat and fish density, the
number of samples in the HFD area appears to have
had the primary influence on the precision of estimates.
The species-year combinations for which the unstrati-
fied estimate was the most precise occurred when habi-
tat sample sizes ranged from 4 to 22 (Fig. 7) and HFD
stratum samples sizes ranged from 6 to 11 (Fig. 6A).
The species-year combinations for which the estimate
poststratified by habitat was the most precise occurred
when habitat sample sizes ranged from 12 to 30 (Fig. 7)
and when sample sizes in the HFD stratum ranged
from 6 to 15 (Fig. 6A). The species-year combinations
for which the estimate poststratified by habitat and fish
density was most precise occurred when habitat sample
sizes ranged from 15 to 45 (Fig. 7) and HFD stratum
sample sizes ranged from 10 to 29 (Fig. 6A). Estimates
poststratified by habitat and fish density were the most
precise for all three cases in which the HFD stratum
sample size was greater than 20 (corresponding to LFD
stratum sample sizes ranging from 9 to 16) (Fig. 6, A
and B). Both of the poststratified estimates were more
precise than the unstratified estimate when habitat
stratum sample sizes were greater or equal to 24 (Fig.
7) and when HFD stratum sizes were greater or equal
to 12 (Fig. 6A).
Statistically significant changes in annual abundance
varied among indices and species. There were signifi-
cant changes in annual mean CPUE in all indices for
rock sole and Pacific halibut, in two indices for yellowfin
sole and in no indices for flathead sole (Table 7). Rock
sole abundance was significantly greater in 1992 than
all other years except 1996. Individual indices indicated
that rock sole 1996 abundance was greater than that
478
Fishery Bulletin 103(3)
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of 1992 and 1993. Tukey post hoc tests on the yellowfin
sole all-site and habitat indices showed that 1991 yel-
lowfin abundance was greater than that of 1994. All
three indices showed that Pacific halibut abundance
was greater in 1995 than in 1991 and 1993. Individual
indices also indicated that Pacific halibut abundance
was greater in 1995 than in 1992, 1994, and 1996.
Discussion
The Chiniak Bay multispecies survey was designed
to estimate the abundance of four species with equal
emphasis. Because the distribution of species varied
greatly throughout the bay, what might have been an
optimal stratification for individual species was com-
promised to develop a stratification scheme that was as
effective as possible for all target species. Because we do
not believe sampling was optimal for any one of the spe-
cies, a poststratification method of analysis was investi-
gated to increase the precision of abundance estimates
for each species individually and to account for possible
bias due to the uneven and nonrandom distribution of
sampling sites over space and time.
The need for stratification and the concern about
the distribution of sampling sites arise because of the
varying distributions of species in the study region.
Knowledge of the spatial distributions of species is im-
portant when estimating abundance from trawl surveys.
A random distribution of individuals is often taken as
a starting point for defining spatial distributions in
ecology (Taylor et al.. 1978). It is also a primary as-
sumption for many survey sampling designs and analy-
sis measures. The assumption of randomly distributed
individuals often is not appropriate, however, because
the concentration of fish varies over time and space in
relation to environmental factors (Murawski and Finn,
1988; Gadomski and Caddell, 1991; Reichert and van
der Veer, 1991; Norcross et al., 1999). If habitat (Fiedler
and Reilly, 1994; Reilly and Fiedler, 1994) and related
spatial population density distributions (Buckland and
Anganuzzi, 1988) are not accounted for when calculat-
ing abundance estimates, precision can decrease and
results can be seriously biased. Inaccurate results can
have strong management repercussions.
In situations such as that of the present study, where
the sample does not properly represent the population,
poststratification is appropriate (Scheaffer et al., 1996).
By comparing poststratified and unstratified estimates
of abundance, we found that in every species-year com-
bination for which the three estimates of abundance dif-
fered (Fig. 3), the poststratified estimates reduced the
effect of the disproportion of samples allocated between
habitat and nonhabitat areas and between high and low
fish-density areas. For instance, in 1992, a dispropor-
tionately large number of samples were taken in Pacific
halibut habitat (Table 2). We suspect, therefore, that
the unstratified estimate of abundance was an overes-
timate of true population abundance. The disproportion-
ately large number of samples taken in Pacific halibut
Dressel and Norcross: Using poststrafication to improve abundance estimates from multispecies surveys
479
20,000,000
15,000,000
10,000,000
5,000,000 -
0
2,000,000 •
1,500,000 ■
1 ,000,000 ■
500,000 -|
0
Rock sole
DUnstratified
■ PoststraWied(H)
■ Poststratified(D)
1991 1992 1993 1994 1995 1996
Yellowfin sole
fra^foffi
D Unstratified
■ Poststratified(H)
IPoststratitied(D)
2,500,000
2,000,000
1 .500,000
1 ,000,000
500,000
0
1991 1992 1993 1994 1995 1996
Pacific halibut
D Unstratified
■ Poststratitied(H)
■ Poststratitied(D)
1991 1992 1993 1994 1995 1996
2,500.000 -I
Flathead sole
2.000.000 •
-■
-■
1.500,000 •
1 .000.000 ■
ffirf\
jM ttI
500,000 -
0 -
u
i a -
DUnstratified
■ Poststratified(H)
■ Poststratitied(D)
1991 1992 1993 1994
Year
1995 1996
Figure 4
Three estimates of total abundance and standard error. Estimates
are unstratified, poststratified by habitat (poststratified [H]), and
poststratified by habitat and fish density (poststratified [£>]).
habitat was adjusted by poststratifying by habitat. The
estimate poststratified by habitat was less than the
unstratified estimate of abundance, as we suspect the
true abundance was. Poststratification by habitat and
neighboring years' halibut density adjusted not only for
the disproportionately large number of samples in the
habitat area but also for the disproportionately large
number of samples in the HFD area (Table 2). The es-
timate poststratified by habitat and halibut density was
less than both the estimate poststratified by habitat
and the unstratified estimate, as we suspect was the
case for the true Pacific halibut abundance.
In 1992, the number of samples in yellowfin sole
habitat was disproportionately large, but the number
of samples in the HFD area was disproportionately
small (Table 2). In this case, we suspect the unstrati-
fied estimate of abundance was an overestimate of true
abundance because of the overabundance of samples
in the habitat area. We also believe, however, that it
was not a very large overestimate because of the dis-
proportionately small number of samples in the HFD
area. Poststratifying by habitat adjusted for the dis-
proportionately large number of samples in the habitat
area and produced an estimate that was less than the
unstratified estimate. Poststratifying by habitat and
fish density adjusted for both the disproportionately
large number of samples in the habitat area and the
disproportionately small number of samples in the HFD
480
Fishery Bulletin 103(3)
Table 4
The mean catch per unit of effort (CPUE) of nonzero catches in
the habitat, high fish-density (HFD), and low fish-density (LFD)
areas and the proportion of the mean CPUE of nonzero catches
in LFD and habitat areas
in relation to those i
n the HFD area.
Species
Pacific halibut
Flathead sole
Rock sole
Yellowfin sole
( Hippoglossu s
( Hippoglossoides
(Lepidopsetta spp.)
iPleuroneetes asper)
stenolepis)
el as sod on )
Habitat nonzero mean 85.3
15.6
16.8
16.0
HFD nonzero mean 105.4
20.7
17.9
20.6
LFD nonzero mean 52.2
7.6
14.7
9.5
Habitat mean/concentration mean 0.81
0.75
0.94
0.78
LFD mean/HFD mean 0.50
0.37
0.82
0.46
Table 5
L'nstratified total abun
mates poststratified by
dance estimates (£/), total abundance estimates poststratified by habitat (H), and total abundance esti-
habitat and fish density (D) are compared by using annual relative efficiency statistics.
Species
Relative efficiency
comparison
Year
1991
1992
1993
1994
1995
1996
Rock sole
HtoU
1.076
1.081
1.084
0.985
1.083
1.084
iLepidopsetta spp.)
DtoH
1.129
1.496
0.865
0.834
1.089
0.999
DtoU
1.214
1.618
0.937
0.821
1.179
1.084
conclusion
D>H>U
D>H>U
H>U>D
U>H>D
D>H>U
H>D>U
Yellowfin sole
HtoU
1.318
1.317
0.988
0.922
1.266
1.324
iPleuronectes asper)
DtoH
1.111
0.969
0.890
0.715
0.936
0.967
DtoU
1.465
1.277
0.880
0.659
1.186
1.280
conclusion
D>H>U
H>D>U
U>H>D
U>H>D
H>D>U
H>D>U
Pacific halibut
HtoU
1.272
1.521
1.007
1.369
1.607
1.440
[Hippoglossus stenolepi
s) DtoH
1.029
0.936
0.996
0.792
1.340
0.949
DtoU
1.309
1.424
1.003
1.084
2.155
1.366
conclusion
D>H>U
H>D>U
H>D>U
H>D>U
D>H>U
H>D>U
Flathead sole
HtoU
0.726
0.449
1.075
0.973
1.025
1.056
[Hippoglossoides elassodon ) D to H
0.786
—
0.976
0.705
0.746
0.992
DtoU
0.571
—
1.049
0.686
0.765
1.047
conclusion
U>H>D
U>H
H>D>U
U>H>D
H>U>D
H>D>U
area. As a result, the estimate poststratified by habitat
and fish density was greater than the estimate post-
stratified by habitat, but lower than the unstratified
estimate. According to our results, it is unlikely that
the estimates poststratified by habitat and fish density
were the most representative estimates of abundance
because poststratification adjusted for the disproportion-
ate distribution of samples between areas.
Another reason to poststratify the data is to increase
the precision of abundance estimates. Poststratified
estimates in our study were generally more precise
than unstratified estimates, given sufficient sample
sizes (Table 5). Poststratification by habitat character-
istics increased the precision of abundance estimates
in three-quarters of all species-year combinations. This
finding indicates a close link between habitat type and
fish abundance and agrees with poststratification re-
sults in other studies (Pollock et al., 1994; Reilly and
Fiedler, 1994). Estimates poststratified by both habitat
and fish density were also generally more precise than
Dressel and Norcross: Using poststrafication to improve abundance estimates from multispecies surveys
481
Rock sole
□ Unstratified
■ Poststratified(H)
■ Poststratitied(D)
1991 1992 1993 1994 1995 1996
Yellowfin sole
D Unstratified
■ Poststratilled(H)
■ Poststratified(D)
1991 1992 1993 1994 1995 1996
Pacific halibut
D Unstratified
■ Poststratified(H)
■ Poststratified(D)
1991 1992 1993 1994 1995 1996
Flathead sole
1991 1992 1993 1994 1995 1996
Year
Figure 5
Three standard error estimates of annual total abundance. Standard
error estimates are for the unstratified, poststratified by habitat
(poststratified [H]), and poststratified by habitat and fish density
(poststratified [D]) estimates.
unstratified estimates but were not consistently more
precise than the estimates poststratified by habitat
alone. The six cases in which estimates poststratified
by habitat and fish density were the most precise show
that some species have strong density gradients within
habitat areas and that the incorporation of fish density
information from neighboring years can be beneficial for
increasing precision. Being able to predict the distribu-
tion of fish density in one year from that of neighboring
years indicates annual consistency in species distribu-
tion in relation to habitat characteristics.
The present study indicates that when estimating
abundance from haphazardly sampled data, the estima-
tor poststratified by habitat is superior to the unstrati-
fied estimator regardless of sample size. The estimate
poststratified by habitat was more precise than the un-
stratified estimate in 18 of the total 24 species-year
combinations. These 18 species-year combinations oc-
curred across nearly the full range of habitat stratum
sample sizes, from 12 to 45. The six cases in which the
estimate poststratified by habitat was less precise than
the unstratified estimate were affected by the propor-
482
Fishery Bulletin 103(3)
35 -i
0)
A
N
<D 30-
aa
Q.
E
s 2S-
A
E
i 20-
to
>> 15-
A
c
A
JA
<D
A A AA
-D 10 -
AAA
_C
AAAA
U)
AA
i! 5-
O)
I
0 T ■ 1 1 1
Unstratified Poststratified (H) Poslslratilied (D)
18 ■
B
aj
N 16 -
A
c/i
A
"5. 14 -
A
E
CO
w 12 -
A A
E
A A
1 1°-
A A
A AA
CO
>. 8-
AA AA
to
A
oj 6
A A
■a
A
■g 4-
A A
**—
A
O 2
A
_l
0 T 1 1 1 '
Unstratified Poststratified (H) Poststratified (D)
Most precise estimate of total abundance
Figure 6
High and low fish-density stratum sample size in relation to the most
precise estimate of total abundance. The (A) high fish-density and
IB) low fish-density stratum sample size for each species-year com-
bination is plotted in relation to the most precise estimate of total
abundance — the unstratified estimate, the estimate poststratified by
habitat (poststratified [H]), or the estimate poststratified by habitat
and fish density (poststratified [D]).
tion of samples in unsuitable habitat. As a measure of
variability, the magnitude of the variance is dependent
on the magnitude of the data (Zar, 1996). Thus, the
variances of trawl catches decrease as the observed
means decrease (Taylor, 1953). A lower variance, there-
fore, does not necessarily indicate a better estimator,
but instead may reflect lower population abundance. In
the six cases in this study where the variance of the
unstratified estimate was less than the variance of the
estimate poststratified by habitat, the unstratified abun-
dance estimate was less than the abundance estimate
poststratified by habitat. The low unstratified abundance
estimates in these six cases were the result of a dis-
proportionately large number of samples in nonhabitat
areas in relation to the size of the nonhabitat areas.
Therefore, although the unstratified estimate was more
precise, it was also likely to be an underestimate of the
true abundance. Thus, we suggest that the estimate
poststratified by habitat is the most desirable estimator
in these situations, despite the decrease in precision in
relation to the unstratified estimator.
In many cases, small sample size was likely the rea-
son that the estimates poststratified by habitat and fish
density were not the most precise of the three estimates.
Poststratification produces precise estimates when the
overall sample size and the sample size in each stratum
are large (Scheaffer et al., 1996). In our study, the esti-
mator poststratified by habitat and fish density was the
most precise estimator of the three when sample size
in the HFD stratum was 20 or greater and the sample
size in the LFD stratum was 9 or greater. The number
of samples in the HFD stratum appears to have had a
larger influence on the precision of estimates stratified
by habitat and fish density than the number of samples
Dressel and Norcross: Using poststrafication to improve abundance estimates from multispecies surveys
483
su -
45 ■
A
40-
A
35 ■
A
30-
A
25-
AAA
20 ■
i
A
A
is-
t
AA
i
le-
s'
0-
A
f ,. . ,
Unstratified Poststratified (H) Poststratified (D)
Most precise estimate of total abundance
Figure 7
The habitat stratum sample size for each species-year combination is plotted
in relation to the most precise estimate of total abundance — the unstrati-
fied estimate, the estimate poststratified by habitat (poststratified [H]), or
the estimate poststratified by habitat and fish density (poststratified [D]).
Table 6
Annual number of tows made across all strata
in habitat and
nonhabitat strata, and in
the high and low fish-density strata
within the habitat stratum.
Species
Stratum
Year
1991
1992
1993
1994
1995
1996
Rock sole
all
49
15
24
25
20
30
iLepidopsetta spp.)
habitat and nonhabitat
45 and 4
15 and 0
24 and 0
22 and 3
20 and 0
30 and 0
high fish density and
29 and 16
11 and 4
10 and 14
10 and 12
11 and 9
15 and 15
low fish density
Yellowfin sole
all
49
15
24
25
20
30
iPleuronectes
habitat and nonhabitat
38 and 11
13 and 2
15 and 9
15 and 10
16 and 4
24 and 6
asper )
high fish density and
low fish density
29 and 9
6 and 7
7 and 8
6 and 9
8 and 8
12 and 12
Pacific halibut
all
49
15
24
25
20
30
I Hippoglossus
habitat and non-habitat
36 and 13
14 and 1
14 and 10
13 and 12
16 and 4
24 and 6
stenolepis)
high fish density and
low fish density
25 and 11
12 and 2
11 and 3
8 and 5
10 and 6
13 and 11
Flathead sole
all
49
14
24
25
20
30
(Hippoglossoides
habitat and non-habitat
21 and 28
4 and 10
16 and 8
Wand 11
12 and 8
18 and 12
elassodon )
high fish density and
low fish density
11 and 10
0and4
8 and 8
6 and 8
6 and 6
8 and 10
in the LFD stratum (Fig. 6, A and B). This study sup-
ports the conclusion of Scheaffer et al. (1996) but also
indicates that the sample size in the HFD stratum may
have a larger influence on the precision of the resultant
estimate.
As concluded in other studies (Fiedler and Reilly,
1994; Pollock et al., 1994; Reilly and Fiedler, 1994;
Bernard et al., 1998), we found that poststratification
can provide increased precision and decreased bias for
estimates. Small stratum sample sizes, however, can
make it impossible to detect heterogeneity among strata
and fail to give increased precision (Powell et al., 1995;
Friedland et al., 1999). The wide range of sample sizes
among strata across species-year combinations exempli-
484
Fishery Bulletin 103(3)
Table 7
Kruskal-Wallis test statistics for differences in annual relative abundance and, for significant Krust
corresponding significant Tukey post hoc pairwise differences. Statistics were calculated for the all-sitf
density indices.
al-Wallis statistics, the
, habitat, and high fish-
Species Index
Kruskal-Wall
('^indicates statistically signi
is
ficant difference)
Tukey post hoc
significant differences
Rock sole All-site
P=0.0003*
1992>1991(P<0.0006)
(Lepidopsetta spp. )
1992>1993(P<0.0001)
1992>1994(P<0.0009)
1992>1995(P<0.0124)
1996>1993(P<0.0301)
Habitat
P=0.0008*
1992>1991(P<0.0012)
1992>1993(P<0.0001)
1992>1994(P<0.0022)
1992>1995(P<0.0149)
1996>1993(P<0.0351)
High fish density
P=0.0035*
1992>1991 (P<0.0005)
1992>1993(P<0.0003)
1992>1994(P<0.0127)
1992>1995(P<0.0206)
1996>1992 (P<0.0145)
Yellowfin sole All-site
P= 0.0033*
1991>1994(P<0.0096)
{Pleuronectes asper) Habitat
P= 0.0022*
1991>1994lP<0.0374)
High fish density
P=0.1240
Pacific halibut All-site
P= 0.001*
1995>1991(P<0.0013)
tHippoglossus stenolepis)
1995>1993(P<0.0012)
1995>1994(P<0.0359)
Habitat
P=0.0004*
1995>1991(P<0.0018)
1995>1993(P<0.0077)
High fish density
P=0.0002*
1995>1991(P<0.0002)
1995>1992(P<0.0127)
1995>1993(P<0.0004)
1995>1996(P<0.0249)
Flathead sole All-site
P=0.1955
(Hippoglossoides elassodon) Habitat
P=0.2950
High fish density
P=0.5151
fies an important drawback to using the poststratifica-
tion method. Because strata criteria are unknown when
sampling, it is not possible to insure that there will be
sufficient samples in each poststratified stratum. When
resulting sample sizes in some strata are small, post-
stratification may be ineffective at increasing precision.
If the resulting sample size in one or more strata is one,
the poststratification variance will be inestimable. If
the resulting sample size in one or more strata is zero,
poststratification may not be possible.
Because sample size is a limiting factor for increased
precision with poststratification, there are strong impli-
cations for survey design. Many multispecies surveys
are conducted by using a stratified random sampling de-
sign. There are two ways to apply poststratification to a
stratified survey. First, for an unbiased estimator, each
stratum of the stratified survey can be poststratified
individually (Cochran, 1977). For the poststratification
estimator to have increased precision beyond that of
stratified random sampling, each of the original strata
must have a large number of samples to allow suffi-
cient samples in each poststratified stratum. Therefore,
investigators who intend to poststratify data within a
stratified random survey for unbiased estimates need
to construct large strata with many samples in the
original sampling design. Second, if poststratification
is applied to data that were not collected under a prob-
ability sampling design, the estimator may be more
precise, but may be biased. For the analysis of data
that were not collected under a probability sampling
Dressel and Norcross: Using poststrafication to improve abundance estimates from multispecies surveys
485
design, developing an index of relative abundance from
all samples, or samples in the habitat or HFD areas,
is an easy and effective way to estimate statistically
significant changes in abundance among years. To de-
termine which tows should be included in an index to
effectively approximate the variations in the annual
total abundance estimates, it is helpful to compare the
size of the habitat area over years and to study the dis-
tribution of species density within the habitat area. The
goal of creating an index should be to include the most
information possible, while avoiding undue influence
from the haphazard distribution of sample sites.
If the total study area is the same in each year, the
choice of whether to use the all-site index should depend
on whether the size of the habitat area is constant over
the compared years. In this study, the defined habitat
area for each species was the same over the six years
compared. Therefore, for an index of relative abundance,
the habitat index retained all necessary information
and reduced possible bias due to the disproportionate
distribution of haphazard samples between habitat and
nonhabitat areas. When a temporally dependent strati-
fication variable, such as temperature, is used to define
the placement of stratum boundaries, however, the size
of the habitat area may vary between years. If the an-
nual size of the habitat area varies, some common size
would need to be chosen for the relative index to ap-
proximate the annual changes in the total abundance
estimates. The all-site index could be used for this
purpose, but the index will be affected by any dispro-
portionate distribution of samples between habitat and
nonhabitat areas. Another possible way to do this would
be to include all tows from the habitat area each year,
plus as many zero catches from the nonhabitat area
necessary to be proportional to the annual size of the
nonhabitat area. Such an approach would not depend
on actual tows in nonhabitat area but would depend on
the estimated size of the habitat and nonhabitat areas
and the sample size in the habitat area.
If the size of habitat area is the same in each year,
the choice of whether to use the habitat index should
depend on whether the distribution of species density
is constant throughout the habitat area. If a species'
density distribution is approximately constant across
the habitat area, a haphazard distribution of sample
sites should have little influence. Constructing an index
from all habitat tows may then be desired to retain the
largest sample size and the most information possible.
Alternatively, if a species has a strong density gradient
within its habitat area, a disproportionate distribution
of sites in relation to the size of high and low fish-den-
sity areas may provide an unrepresentative estimate of
abundance from the habitat index. In this case, if a suf-
ficient number of samples are taken in the HFD area,
constructing an index from samples within the species'
HFD area alone may provide an effective index while
minimizing the effect of a disproportional distribution
of haphazard samples within the habitat area.
A comparison of the number of zero catches and the
mean nonzero catch between the high and low fish-
density areas provides information about the density
distribution of species within a habitat area. The pro-
portion of zero catches of rock sole, yellowfin sole, and
flathead sole and the mean nonzero catch between high
and low fish-density areas indicated density gradients
within the habitat areas. Unlike these three species,
the proportion of Pacific halibut zero catches was ap-
proximately the same in the HFD area as across the
entire habitat area and the difference in mean nonzero
catch between low and high fish-density areas was only
approximately half that of the other species. Therefore,
it appears that the Pacific halibut density distribution
across the defined habitat area varied little compared
with the other three species.
In this study, we suggest that the habitat index was
the most appropriate for all four species. For each spe-
cies in our study, the size of the habitat area remained
the same across all six years. Thus, the habitat index
eliminated the influence of disproportionately allocated
samples in habitat and nonhabitat areas. For Pacific
halibut, the relatively homogenous distribution of abun-
dance across the habitat area indicates that the effect
of disproportionate samples between high and low fish-
density areas is small and that samples across the
entire habitat area are helpful in describing annual
differences in abundance. For rock sole, yellowfin sole,
and flathead sole, the difference in the proportion of
zero catches and nonzero mean abundance between the
high and low fish-density areas was considerable. As a
result, differences in annual abundance suggested by
the habitat index may be affected by the inconsistent
disproportion of samples between high and low fish-den-
sity areas over years. Although it would be preferable to
use the HFD index in these cases, annual sample sizes
in the HFD area were so small that we recommend the
habitat index instead. Recognizing that the habitat
index will not account for the annual disproportion of
samples between the high and low fish-density areas,
we used the comparison of the size and the number of
samples taken in high and low fish-density areas to flag
differences in annual index abundance estimates that
might be over- or underestimates. If this method is ap-
plied in a management context, the levels of the factors
describing the density distribution of the species (i.e.,
difference in the percent of zero catches and the percent
difference in mean nonzero catch between years) can be
set as criteria and kept constant over years to elimi-
nate subjectivity between years or between species. For
example, if the percent of zero catches in high and low
fish-density regions differ by 40% and the mean nonzero
catch in the HFD area is 30% greater than that in the
LFD area, the HFD index should be used. Otherwise,
the habitat index should be used.
For many surveys, identifying habitat and fish-density
areas for poststratification and index construction is pos-
sible with currently available information. The estima-
tion methods used in the present study can be applied
to any survey for which abundance and environmental
measurements are available for each sampled site and
the environmental measurements are related to species
486
Fishery Bulletin 103(3)
abundance in a consistent way. For example, the NMFS
Bering Sea trawl survey includes measurements of depth
and surface and bottom temperatures at all trawl sites
(Goddard and Walters4) that could be used for post-
stratification. Similarly, the Pacific West Coast trawl
survey includes measurements of surface and bottom
temperature and salinity at all stations (Lauth et al.5)
that could be used. Poststratification allows for use of a
wide range of stratification variables, including tempo-
rally dependent variables that are not available before
sampling is complete, e.g., temperature and salinity.
For surveys where habitat information is not collected
at trawl sites, habitat information from other sources
can be paired with fish distribution information after
collections have been made. For instance, when habitat
information is available, but has not been collected at
each site, spatial statistics can be used to krige the
habitat information over the study area and to predict
the specific habitat data value at the sampling sites. If
there is a consistent relationship between species abun-
dance and the habitat variable, the catch and habitat
data paired at sample sites can then be used to identify
areas of suitable habitat and areas of high fish density
within suitable habitat. How well habitat and HFD
areas are estimated will depend on the number and
distribution of habitat measurements, the contouring
algorithms used, and the estimates of areas within
contours. Even if species are not distributed in direct
response to particular environmental characteristics,
the characteristics may serve as proxies for effects that
are more difficult to measure (Perry and Smith, 1994).
Once habitat and HFD areas are identified, poststrati-
fication can be conducted for total abundance estimates,
and statistically significant changes between years can
be assessed with an index of relative abundance. These
methods could yield more accurate estimates of abun-
dance for use by managers. The goal of most sampling
plans is to provide statistical estimates with the small-
est possible confidence limits at the lowest cost (Krebs,
1989). Thus, being able to use data collected indepen-
dently of a survey should be appealing.
The NRC (2000) recommends using data from com-
mercial or sportfishing vessels in scientific assessments
of abundance. A primary difficulty in using commercial
fisheries data for scientific estimates of abundance is
that the data do not represent random samples of the
fish population. As a result, commercial fisheries data
4 Goddard, P., and G. Walters. 1998. 1995 bottom trawl
survey of the eastern Bering Sea continental shelf. AFSC
Processed Report 98-08, 170 p. Resource Assessment and
Conservation Engineering Division, Alaska Fisheries Science
Center, NMFS, NOAA, 7600 Sand Point Way N.E., Seattle,
Washington, 98115.
5 Lauth, R. R., M. E. Wilkins, and P.A. Raymore Jr. 1997. Re-
sults of trawl surveys of groundfish resources of the West
Coast upper continental slope from 1989 to 1993. NOAA
Tech. Memo. NMFS-AFSC-79, 342 p. National Technical
Information Service, U.S. Department of Commerce, 5285
Port Royal Road, Springfield, Virginia 22161.
present a biased perspective of the population that may
change over time and may not correlate well with ac-
tual fish abundance (NRC, 2000). Although commercial
fishery-dependent data may provide biased estimates of
abundance, fishery-dependent data also provide large
sample sizes and a wide range of information not avail-
able from other sources. For example, commercial and
sportfishing data often provide broader geographic and
temporal coverage. Poststratification of haphazard data
from commercial and sportfishing sources may be one
way to reduce inherent bias and provide useable scien-
tific information. For instance, Buckland and Anganuzzi
(1988) described how data collected on commercial tuna
fishing vessels can be used to estimate dolphin abun-
dance when survey data are not sufficient. The data
collection sites were not randomly selected. Instead,
the sampling sites were directly related to dolphin
sightings, because dolphins and tuna schools are often
closely associated. As a result, areas of high dolphin
density corresponded with areas of high fishing effort.
Poststratification was used to decrease the bias result-
ing from nonrandom distribution of both search effort
and dolphin schools. A second example is a retrospec-
tive study that combined survey and commercial fishing
data. In this study (Halliday8), 1958-60 poststratified
survey data were used to develop a relationship between
the survey abundance of the 1954-1959 year classes
and their abundance estimates from commercial fishery
data. This relationship was then used, along with 1969
survey data, to predict the size of the 1966-68 year
classes. The same process was used to predict the size
of later year classes with later years of survey data.
Poststratification also facilitates the use of a single
data set for multiple objectives. Collecting data is costly
and many data sets are collected and analyzed for a
single objective and then not used again. Although it
is preferable to use data for multiple objectives, it can
be difficult to meet statistical assumptions when the
data are re-used for a different purpose. For example,
a multispecies survey may be stratified according to the
distribution of one or more of the most commercially
valuable species collected. An example is the stratifica-
tion of Pacific west coast bottom trawl surveys in 1980,
1983, and 1986, which were focused to improve the
precision of canary and yellowtail rockfish abundance
estimates (Weinberg et al.2). If the stratification used
was not effective for decreasing the variance of abun-
dance estimates for other species, treating the data as
if they were haphazardly collected, recognizing that
the estimator may be biased, and poststratifying the
data by habitat variables that are closely related to the
6 Halliday, R. G. 1970. 4T-V-W haddock: recruitment
and stock abundance in 1970-72. ICNAF Res. Doc
70/75, 12 p. Approved for citation by Tissa Amaratunga,
Deputy Executive Secretary, Northwest Atlantic Fisher-
ies Organization. [Available from the Secretariat Library,
Northwest Atlantic Fisheries Organization, 2 Morris Drive,
Burnside Industrial Park, Dartmouth, Nova Scotia, Canada,
B3B 1K8.]
Dressel and Norcross: Using poststrafication to improve abundance estimates from multispecies surveys
487
distribution of the other species may be a beneficial way
to make multiple uses of the data. Although the post-
stratified estimator may be biased, poststratification
may provide large gains in precision and a decrease
in bias in relation to an unstratified estimator. Large
increases in precision may be worth the acceptance of
some bias.
Multispecies surveys are often not optimal for es-
timating the abundance of individual species but are
often necessary because of limited time and financial
resources. As a result, researchers need to explore al-
ternative sampling and analysis designs to increase
the precision of individual species abundance estimates
(NRC, 2000). Poststratification is a method that can be
applied to any number of species by using a wide range
of habitat and other variables that can be stratified.
Because of the dramatic increase in habitat information
that is likely to be collected in response to the expanded
emphasis in the Magnuson-Stevens Act (NRC, 2000)
and because of the adaptability of poststratification for
handling a multitude of types of data sets, the method
of poststratification may provide increased usefulness
for scientific researchers.
Acknowledgments
We thank Eric Munk and National Marine Fisheries
Service Kodiak Laboratory for the vessel and field assis-
tance from 1993 to 1996 and Bruce Short for field assis-
tance in 1991 and 1992. Additionally, we thank Brenda
Holladay, Franz Mueter, Brad Allen, Ed Roberts, and
Cindy VanDamm, who helped with the fieldwork for this
project, and Franz Mueter, Michael Simpkins, Robert
Foy, and Amy Blanchard for constructive advice. For
critical review of this article, we thank Milo Adkison,
Alison Banks, Allison Barns, Cathy Coon, Judy Ham-
ilton, Sue Hills, Heather Patterson, Andy Seitz, Dana
Thomas, Albert Tyler, and other anonymous review-
ers. This project was funded by Saltonstall-Kennedy
NOAA (contracts number NA16FD021601, NA26FD0156,
NA47FD0351), Minerals Management Service through
the University of Alaska Coastal Marine Institute (task
order numbers 11983, 12041, 18445), and the Rasmuson
Fisheries Research Council.
Literature cited
Anganuzzi, A. A. and S. T. Buckland.
1989. Reducing bias in trends in dolphin abundance,
estimated from tuna vessel data. Rep. Int. Whal.
Comm. 39:323-334.
Azarovitz, T. R.
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489
Abstract— Reproductive data col-
lected from porbeagle, shortfin mako.
and blue sharks caught around New
Zealand were used to estimate the
median length at maturity. Data
on clasper development, presence or
absence of spermatophores or sper-
matozeugmata, uterus width, and
pregnancy were collected by observers
aboard tuna longline vessels. Direct
maturity estimates were made for
smaller numbers of sharks sampled
at recreational fishing competitions.
Some data sets were sparse, par-
ticularly over the vital maturation
length range, but the availability
of multiple indicators of maturity
made it possible to develop estimates
for both sexes of all three species.
Porbeagle shark males matured at
140-150 cm fork length and females at
about 170-180 cm. New Zealand por-
beagles therefore mature at shorter
lengths than they do in the North
Atlantic Ocean. Shortfin mako males
matured at 180-185 cm and females
at 275-285 cm. Blue shark males
matured at about 190-195 cm and
females at 170-190 cm: however these
estimates were hampered by small
sample sizes, difficulty obtaining rep-
resentative samples from a popula-
tion segregated by sex and maturity
stage, and maturation that occurred
over a wide length range. It is not yet
clear whether regional differences in
median maturity exist for shortfin
mako and blue sharks.
Length at maturity in three pelagic sharks
(Lamna nasus, Isurus oxyrinchus, and
Prionace glauca) from New Zealand
Malcolm P. Francis
National Institute of Water and Atmospheric Research
301 Evans Bay Parade
Greta Point
Wellington, New Zealand
E-mail address m francisifi'niwa co nz
Clinton Duffy
Department of Conservation
Private Bay 68908
Auckland, New Zealand
Manuscript submitted 20 April 2004 to
the Scientific Editor's Office.
Manuscript approved for publication
30 March 2005 by the Scientific Editor.
Fish. Bull. 103:489-500 (2005).
The attainment of sexual maturity in
sharks is a major developmental mile-
stone which has a large impact on their
distribution, behavior, and biology.
Immature sharks often associate with
each other regardless of sex, but after
maturity sexual segregation is the
norm. Mature males and females may
come together only to mate, resulting
in movements that may range from
small-scale aggregation of dispersed
individuals to long-range migra-
tions over thousands of kilometers.
The process of maturation, and the
subsequent need to channel energy
into reproduction, affect the growth
rate of at least some shark species.
Immature male and female porbea-
gles grow at the same rate, and the
growth rate of both sexes slows at
maturity; however females mature at
a greater age than males and there-
fore their period of fast immature
growth lasts longer and they grow
larger than males (Natanson et al.,
2002).
The maximum reproductive lifes-
pan of a shark species is the time
elapsed between the age at maturity
and the maximum age. In conjunction
with the duration of the reproductive
cycle, the reproductive lifespan deter-
mines the maximum number of litters
a female shark can produce in her
lifetime. Population modeling indi-
cates that shark species that mature
at a young age have a greater capac-
ity to recover from exploitation than
sharks that mature later (Smith et
al., 1998). Thus age at maturity is a
crucial factor influencing the produc-
tivity of a species.
Age at maturity can be estimated
directly from paired age-and-matu-
rity estimates taken from the same
shark, but often such data are not
available, or are too few to provide
precise estimates. Consequently it is
often necessary to estimate age at
maturity indirectly from length at
maturity and a growth curve.
In the present study we estimate
the length at maturity for three spe-
cies of large pelagic sharks in New
Zealand waters: porbeagle (Lamna
nasus (Bonnaterre, 1788)), shortfin
mako (Isurus oxyrinchus Rafinesque,
1810), and blue (Prionace glauca
(Linnaeus, 1758)) sharks. These spe-
cies are commonly caught by tuna
longliners fishing around New Zea-
land (Francis et al., 2001). Longline
fishing effort declined from a high
of over 25 million hooks per year
in the early 1980s, to a low of 2—4
million hooks in 1995-98, largely
because of a reduction in the number
of foreign licensed vessels (Francis
et al., 2001). Since then, the do-
mestic longline fleet has expanded,
and fishing effort exceeded 10 mil-
lion hooks in 2001-02 (Ayers et al.,
2004). Because of concern over the
sustainability of the catches of both
target and nontarget species in this
fishery, the New Zealand Ministry
490
Fishery Bulletin 103(3)
of Fisheries introduced individual trans-
ferable quotas for a number of pelagic
species, including the three sharks, in
October 2004.
Despite the panglobal distributions of
porbeagle, shortfin mako, and blue sharks,
and their importance in the catches of
pelagic longline fisheries worldwide, com-
paratively little effort has been devoted to
estimating their length (or age) at matu-
rity. In the northwest Atlantic Ocean, the
length at maturity of male and female por-
beagles has been well determined (Jensen
et al., 2002), but preliminary data from
the southwest Pacific Ocean indicate that
females mature at a much smaller length
there (Francis and Stevens, 2000). Mol-
let et al. (2000) found significant differ-
ences in the length at maturity of female
shortfin makos between the Northern and
Southern hemispheres; however there is
little information on the length at matu-
rity of male makos (Stevens, 1983). Blue
sharks have been studied in a number
of regions worldwide (Pratt, 1979; Ste-
vens, 1984; Hazin et al., 1994; Nakano,
1994; Castro and Mejuto, 1995), but size
and sex segregation have made it difficult
to obtain representative samples of both
sexes from which to determine length at
maturity.
In the southwest Pacific Ocean, esti-
mates of length at maturity are lacking or
uncertain for at least one sex of all three
species. Although all species make long
distance movements, and presumably have
wide-ranging stocks, the interhemispheric
differences in length at maturity reported
for female porbeagles and shortfin makos
indicate that it is not safe to transfer esti-
mates from one region to another. The aim
of the present study is to develop region-
specific estimates of length at maturity
for male and female porbeagle, blue and shortfin mako
sharks, and to determine whether this parameter var-
ies globally. These results will contribute to efforts to
determine the productivity and stock status of pelagic
sharks in New Zealand waters.
i — i — TTri — i — i — i — i — i — i — i — i — i — i — i — r
;
D
Norfolk/^
Island M
■3
Figure 1
Start-of-set positions of tuna longline sets during which observers
sampled porbeagle [Lamna nasus), shortfin mako (Isurus oxyrin-
chus), and blue [Prionace glauca) sharks. Also shown are the North
Island ports where sharks landed during fishing competitions were
sampled.
Fisheries observers aboard commercial tuna longline
vessels (Fig. 1). Sharks obtained from fishing competi-
tions provided the opportunity to measure a wide range
of reproductive parameters on relatively small samples,
whereas sharks observed on tuna longline vessels pro-
vided large samples but limited reproductive data.
Materials and methods
Sharks obtained from fishing competitions
Data sources
Reproductive data were collected from two main sources.
The first consisted of sharks sampled by the authors at
recreational fishing competitions, or occasionally sharks
retained by commercial fisheries or research vessels. The
second source consisted of data and occasionally embryos
and female reproductive tracts collected by Ministry of
Competition sharks consisted mainly of makos and
blue sharks sampled at fishing competitions around the
North Island (Fig. 1). Most sharks were sampled from
the Hawke Bay competition held annually in February
or March from the port of Napier. Other significant
competitions were sampled at Castlepoint, Raglan, and
New Plymouth. All except two of the competition sharks
were collected in summer (January-March) and samples
Francis and Duffy Length at maturity in three pelagic sharks
491
spanned the period from 1986 to 2004. In the early
years, only data on length, sex, weight, and maturity
were collected. In later years, detailed reproductive data
were also collected. The following length measurements
were made as point-to-point straight line distances to
the whole centimeter below actual length:
Total length (TLnat): tip of snout to a perpendicular
dropped from the tip of tail to
the midline (with the tail in
the natural position);
Total length (TLflex): tip of snout to tip of tail (with
the tail flexed towards the
midline to provide maximum
extension);
Fork length (FL): tip of snout to fork in the
tail;
Precaudal length (PCL): tip of snout to the upper pre-
caudal pit (mako and por-
beagle sharks) or the origin
of the upper caudal lobe (blue
sharks).
Total weight was measured on accurate scales provided
at the fishing competitions, on research vessels, or in
commercial fish processing sheds.
In males, inner clasper length was measured between
the anterior margin of the cloaca and the posterior clasp-
er tip, and expressed as a percentage of fork length:
Clasper length index (CLI) = 100 (clasper length I FL).
The degree of clasper calcification and development
was determined and included an assessment of whether
the terminal cartilages could be splayed open, whether
a spur was present and erupted, and whether the en-
tire clasper could be rotated. In some males sampled
in later years, the degree of development of the testes,
epididymis, and ampulla at the posterior end of the
epididymis was also recorded, and occasionally testes
were weighed and measured (following dissection from
the epigonal organ if necessary). The presence or ab-
sence of spermatophores or spermatozeugmata in the
ampulla epididymis was noted. (Spermatophores are
masses of encapsulated sperm, and they are found in
porbeagle and mako sharks; spermatozeugmata are
unencapsulated masses of naked sperm that are found
in blue sharks [Pratt and Tanaka, 1994]).
In females, the reproductive system was examined,
and in later years a number of measurements were
taken. Uterus width was measured near the middle of
the body cavity and expressed as a percentage of fork
length:
Uterine width index (UWI) = 100 (uterus width/FL).
sured after dissection (if necessary) from the epigonal
organ. Any contents of the uteri were noted; embryos
were measured and sex was determined. The presence
or absence of a hymen (cloacal membrane occluding the
vaginal opening) was recorded.
For both males and females, a direct assessment of
maturity (hereafter called direct maturity) was made
by using all the available reproductive data. A three-
stage classification scheme was used: immature, ma-
turing, and mature. Mature sharks were defined as
those in which the reproductive system was judged to
be fully functional and capable of delivering reproduc-
tive products. For analysis purposes, maturing sharks
were grouped with immature sharks.
Sharks sampled by observers
Observers sampled tuna longline sets from around the
New Zealand region (Fig. 1). Data from blue and mako
sharks were obtained throughout the sampled area, but
porbeagles came mainly from the southwestern South
Island. Most sharks were sampled in autumn-winter
(April-July) over the period 2001-2003. The "standard"
length measurement for sharks was FL, but frequently
observers also recorded TLnat or PCL.
Observers were provided with instructions and pho-
tographs indicating the reproductive data they needed
to collect, but they were not provided with any practi-
cal training. The main data they collected were the
following: inner clasper lengths, presence or absence of
spermatophores or spermatozeugmata in the ampulla
epididymis (for males); uterus width, maximum ovum
diameter, and whether the shark was pregnant or not
(for females).
Examination of observer pregnancy records for blue
sharks indicated numerous probable errors: uterus
widths from sharks scored as pregnant were frequently
less than 18 mm, which seems implausible considering
that ova are ovulated at about 18 mm, and pregnant
sharks are unlikely to have such small uteri (Pratt,
1979; Natanson1). This problem was apparent for sev-
eral observers, some of whom were very experienced
(although they had no previous experience examining
shark reproductive systems). We suspect that they may
have scored some female blue sharks as pregnant if the
ovary contained large yolky ova (this problem did not
occur for mako and porbeagle sharks, which have much
smaller ovarian ova). We therefore used observer blue
shark pregnancy records only if they were supported by
appropriate comments on the data sheet (e.g., mention
of embryos or ovulated eggs in uteri), or if the observers
retained embryos or intact uteri for us to examine.
Observers did not assess direct maturity; therefore
we were unable to derive direct maturity ogives for
observer sharks.
The maximum diameter of ova, where they were suf-
ficiently developed to be visible in the ovary, was re-
corded, and the diameter of the oviducal gland was
measured. Ovarian dimensions and weight were mea-
1 Natanson, L. 2004. Unpubl. data. National Marine Fish-
eries Service, 28 Tarzwell Drive, Narragansett, Rhode Island
02882-1152.
492
Fishery Bulletin 103(3)
Table 1
Regression equations used to convert shark length
size. Measurement method acronyms are denned in
and CTL = curved total length (both measured over
s reported in the literature,
the "Materials and methods'
the curve of the body).
r2=the coefficient of determination; « = sample
section, except that CFL = curved fork length
Species
Regression equation
r-
n
Data range (cm)
Source
Porbeagle
FL = -6.943 + 0.893 TLna,
0.997
103
61-181 FL
This study
FL = 0.90 + 0.95 CFL
0.997
172
83-253 FL
S. Campana'
Mako
CFL = -1.7101 + 0.9286 CTL
0.997
199
65-338 CFL
Kohler et al., 1995
FL = 0.973 + 0.968 CFL
0.999
30
113-287 FL
This study
FL = 0.766 + 1.100 PCL
0.997
999
61-346 FL
This study
FL = 0.821 + 0.911 TLnat
0.993
399
70-346 FL
This study
Blue
FL = -0.90 + 0.98 CFL
0.99
789
123-286 FL
S. Campana'
FL = -1.615 + 0.838 TLmt
0.990
273
50-270 FL
This study
FL = 0.745+ 1.092 PCL
0.998
12,657
34-326 FL
This study
' Refers to footnote 2 in the general text.
Data analysis
For each shark species and sex, we were interested in
determining the length at which 50% of the individuals
in a population reached full sexual maturity. That length
is the median length at maturity, hereafter referred to
as "median maturity."
Many shark species show abrupt transitions in the
sizes of reproductive organs near length at maturity.
To locate such transitions in clasper length, we fitted
"split" linear regressions to CLI data plotted against
FL. Split regressions consist of two simple linear re-
gressions fitted to different nonoverlapping data ranges
that meet at a point called the breakpoint (Kovac et al.,
1999). A split regression has the form
CLI = f(FL
CLI = g(FL
-p) + h for FL < p
p) + h for FL a p,
where f and g are slope parameters for the two limbs
of the regression, and h andp are they-axis and .r-axis
coordinates of the breakpoint, respectively. The param-
eters f, g, h, and p were estimated by least squares by
using the curve fitting routine in the Sigmaplot sta-
tistical and graphing package (Sigmaplot, vers. 9.01,
Systat Software Inc., Richmond, CA). The length at the
breakpoint was corrected for downward rounding of FL
by adding 0.5 cm.
Maturity ogives were fitted to the direct maturity
data separately by sex by using probit analysis (Pear-
son and Hartley, 1962). The analyses were performed
on individual FL measurements, but we also calcu-
lated the proportions of mature individuals in 10-cm
length classes to illustrate the trends. Probit analysis
assumes that the length at which a randomly selected
fish reaches maturity is normally distributed. Two pa-
rameters, the mean and standard deviation of the nor-
mal distribution, were fitted. Each maturity ogive is
the cumulative distribution function for the associated
normal distribution. The probit function was fitted by
maximum likelihood, and 95% confidence limits were
estimated by the bootstrap method. The mean of the
normal distribution is an estimate of the median ma-
turity, and it was corrected for downward rounding of
FL by adding 0.5 cm.
All shark length measurements provided in the pres-
ent study are FL, unless otherwise stated. For com-
parison with our results, we converted measurements
from the literature to FL where necessary using the
regression equations in Table 1. Literature reports of
total length were assumed to be TLnat unless otherwise
stated. Scientists working on sharks in the northeast-
ern United States, and eastern Canada have typically
measured lengths over the curve of the body rather
than as straight line distances (Natanson1; Campana2;
Pratt3), notwithstanding some published statements to
the contrary (Pratt, 1979; Kohler et al., 1995).
Results
Porbeagle shark
In male porbeagles, CLI showed two strong inflection
points: the first at about 110 cm, and the second, esti-
2 Campana, S. E. 2004. Personal commun. Bedford Insti-
tute of Oceanography, P.O. Box 1006, Dartmouth, Nova Scotia,
Canada B2Y 4A2.
3 Pratt, H. L. 2004. Personal commun. Mote Marine
Laboratory, 24244 Overseas Highway, Summerland Key,
FL 33042.
Francis and Duffy Length at maturity in three pelagic sharks
493
mated by split linear regression fitted to
sharks longer than 110 cm, at 142.7 cm
(95% confidence interval (CI) 140.7-144.7
cm) (Fig. 2). Thus rapid elongation of the
claspers began at about 110 cm and was
completed by 143 cm. Spermatophores
first appeared in the posterior reproduc-
tive tract at 135 cm and by about 152 cm
50% of males contained spermatophores.
The percentage of sharks with spermato-
phores peaked at 165 cm (82% of males)
and then declined to about 50% , although
sample sizes were small in the longer
length groups (Table 2).
In females, UWI began increasing
at a length of about 145 cm, but many
larger, nonpregnant sharks showed no
expansion of the uteri (Fig. 3). Three
females with UWI of about 4-5% were
postpartum, and two with UWI about
11% and one with UWI of about 4% were
pregnant. Pregnant females measured
167-202 cm (mean 184 cm, n = 55). Of
19 females longer than 175 cm that were
scored by observers for pregnancy, 10
(53%) were pregnant, two (11%) were
postpartum, and seven (37%) were rest-
ing (or possibly immature).
Apart from a 185-cm pregnant fe-
male, all whole porbeagles examined
by us were immature; therefore no at-
tempt was made to estimate maturity
directly.
Shortfin mako shark
20 -i
15-
10
♦ Claspers • embryos (n=6)
° Claspers - free living (n=322)
Claspers (split regression)
Spermatophores present
%,
100
80 t/>
60
40 ^
80 100 120
Fork length (cm)
140 160 180 200
Figure 2
Maturation of male porbeagle sharks iLainna nasus): variation in
clasper development and presence of spermatophores in the reproduc-
tive tract.
12-
10-
6-
I I Pregnant females (n=55)
o Uterus width index (n=63)
CLI showed two strong inflection points
in male makos; the first at about 140 cm
and the second (estimated by split linear
regression) at 185.1 cm (CI 182.5-187.7
cm) (Fig. 4). The smallest male with
spermatophores was 136 cm, but this
measurement was an outlier and may
have been an error; the next smallest was
156 cm. Fifty percent of males contained
spermatophores by 178 cm, and 100% by
about 235 cm. Sample sizes were reason-
able over the transition range but small
above 230 cm (Table 2).
Male makos examined by us showed
little overlap in length between immature and ma-
ture sharks (Fig. 4), but sample sizes were small in
all length classes (Table 2). The smallest mature male
was 182 cm and the largest immature male was 183 cm
long. The median maturity estimated by probit analysis
was 182.9 cm (CI 180.7-185.1 cm) (Fig. 4).
In females, UWI began increasing at a length of about
275 cm, and all larger sharks had expanded uteri (Fig. 5).
Only one pregnant female mako has been recorded from
New Zealand waters, and it was 290 cm FL (Duffy and
<&
Qtfffooo o°q£8 ^"l&pfT
6C
- 12
10
- 6
-2
0 25 50 75 100 125 150 175 200 225
Fork length (cm)
Figure 3
Maturation of female porbeagle sharks lLamna nasus): variation in uterus
width index, and length-frequency distribution of pregnant females.
Francis, 2001); no uterus width measurement was avail-
able for that shark. The remaining makos over 275 cm
were either postpartum or resting. The maximum ovum
diameter began increasing in sharks longer than 250
cm (in shorter sharks, ova were barely visible or were
invisible) (Fig. 6). The diameter of the oviducal gland
increased abruptly between 250 and 270 cm, but ovary
dimensions showed no abrupt change in size (Fig. 6).
Median maturity was estimated directly from a sam-
ple of 88 females (Table 3). The smallest mature female
494
Fishery Bulletin 103(3)
Table 2
Sample sizes by 10-cm length class for the assessment of maturity in male
porbeagle, mako, and blue sharks.
Porbeagle shark
Shortfin mako shark
Blue shark
Direct
Direct
Length class
midpoint (cm) Spermatophores
Spermatophores
maturity
Spermatozeugmata maturity
45 0
0
0
0 1
55 0
0
0
0 3
65 0
0
0
0 2
75 2
0
0
0 0
85 15
0
1
1 0
95 4
0
0
2 1
105 0
3
1
2 0
115 2
3
3
0 0
125 8
3
0
1 0
135 23
4
8
1 0
145 28
4
11
3 1
155 30
9
4
6 5
165 17
10
6
13 3
175 18
19
3
4 6
185 6
16
7
20 4
195 4
15
1
21 6
205 1
27
1
18 6
215 0
19
4
15 4
225 0
14
1
12 1
235 0
8
0
20 8
245 0
5
1
26 2
255 0
3
0
19 1
265 0
0
0
11 1
275 0
1
0
6 2
285 0
0
0
2 0
295 0
0
0
1 1
Total 158
163
52
204 58
Table 3
Sample sizes by 10-cm length class for the assessment of maturity in female mako and blue sharks.
Shortfin mako shark
Blue shark
Length class
Shortfin mako shark
Blue shark
Length class
Direct
Direct
Direct
Direct
midpoint (cm)
maturity
0
maturity
midpoint (cm)
maturity
maturity
55
6
215
10
2
65
0
3
225
10
0
75
0
1
235
6
0
85
0
2
245
9
0
95
0
0
255
4
0
105
0
0
265
3
0
115
2
0
275
1
0
125
2
0
285
2
0
135
2
0
295
3
0
145
10
1
305
1
0
155
6
1
315
0
0
165
3
0
325
3
0
175
1
3
335
2
0
185
3
5
345
1
0
195
0
0
Total
88
26
205
4
2
Francis and Duffy Length at maturity in three pelagic sharks
495
was 274 cm and the longest immature
female was 300 cm. Median maturity
was estimated by probit analysis to be
280.1 cm (CI 267.5-292.9 cm), but sam-
ple sizes were very small over the tran-
sitional range (Fig 5). The nonoverlap
of the CIs between males and females
showed that median maturity differs
significantly between the sexes.
Blue shark
The relationship between CLI and FL
was essentially linear in blue sharks,
and no apparent inflections were evident
(Fig. 7). The smallest male with sperma-
tozeugmata was 164 cm; 50% of males
contained spermatozeugmata by 194 cm,
and 100% by about 260 cm.
Samples of male blue sharks examined
by us were small (Table 2). Maturation
occurred over a wide length range: the
smallest mature male was 157 cm and
the largest immature male was 237 cm
long. The direct estimate of median
maturity was correspondingly variable
(192.1 cm, CI 178.1-206.3 cm) (Fig. 7).
The UWI increased abruptly above
about 170 cm in some sharks, all of
which were pregnant (Fig. 8). Other non-
pregnant sharks up to about 220 cm FL,
which were presumably subadults, had
UWIs less than 2%. Pregnant females
ranged from 166 to 252 cm (mean 203
cm) (Fig. 8).
Only 26 females were available for di-
rect maturity estimation (Table 3). The
smallest recorded mature female was
142 cm, but this seems exceptional; the
next smallest was 172 cm. The longest
immature female was 185 cm. The num-
ber of sharks in the maturation length
range was inadequate for determining
median maturity (Table 3), although we
have shown the probit analysis ogive in
Figure 8.
Discussion
20-i
- 100
♦ Claspers - embryos (n=3)
o Claspers - tree living (n=236)
° ,._. ^ \ 1
^
Claspers (split regression)
Spermatophores present
o
M8 o
-80
co
"O
Ti <r>
o
• Percentage mature (direct)
o ^
oH 'to
o
>
3 3
Clasper length index
Percentage mature (titled curve)
cP'q
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.i<5
£><DI
°$ J
• o/
;oo /
%
&> /
0 20 40 60 80 100 120 140 160 180 200 220 240 260 280
Fork length (cm)
Figure 4
Maturation of male shortfin mako sharks Usurits oxyrinchus):
van
ation
in clasper development, presence of spermatophores in the
reproduc-
tive tract, and direct maturity estimation determined from
a su
ite of
maturity indicators.
8-
• •
•
- 2
- 100
i i Pregnant females (n=1 )
o Uterus width index (n=79)
°l °
5" 6-
C""
X
CD
"D
C
£ 4-
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c/)
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CD
5 2-
• Percentage mature (direct)
Percentage mature (fitted curve)
c
<t>
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CD
Percentage mature (%)
D O O O
/ ^
o
(
o
o
;
<gS 0°S&&>8&>0 %aggg5^ °
-0
0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375
Fork length (cm)
Figure 5
Maturation of female shortfin mako sharks (Isurus oxyrinchus):
varia-
tion in uterus width index, and direct maturity estimation from
a suite
of maturity indicators. The only pregnant female recorded from New
Zealand waters is also indicated.
Maturity estimates
To be sexually mature, a male shark must be able to
produce viable sperm and have the means to deliver
them to a female. Similarly, females must be able to
produce viable eggs and nourish the developing embryos
through to parturition. An assessment of the degree
of development of all parts of the reproductive system
and the presence or absence of reproductive products
is the best way to determine sexual maturity. We used
this approach to score the maturity status of individual
sharks and thereby derive direct median maturity esti-
mates. However, the sample sizes available for this
approach were sometimes small, and confidence limits
ranged from unrealistically low (because of lack of over-
lap of immature and mature sharks) to high; therefore it
was not possible to rely entirely on these estimates.
We supplemented our direct maturity estimates with
measurements or assessments (made by observers) of
some key components and products of the reproductive
496
Fishery Bulletin 103(3)
system. The presence or absence of spermatophores or
spermatozeugmata is a good indicator of the ability of
a male to produce viable sperm, but it is not infallible:
such structures sometimes lack viable sperm (Pratt
and Tanaka, 1994). Furthermore, male reproductive
products may not be present year-round: blue sharks
appear to have a seasonal cycle of spermatozeugmata
production in the western central Atlantic (Hazin et
al., 1994), although Pratt (1979) found no evidence of a
cycle in the western North Atlantic. Thus the presence
of spermatophores and spermatozeugmata does not
90-
■
-10
80 -
■ Ovary thickness (n=47)
A Oviducal gland diameter (n=38)
5
| 70-
o Maximum ovum diameter (n=50)
o
-8 0)
X
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E B 60-
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3
S« 50-
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m m
3
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>, O)
A O A A
L" 3
ra ra 30 -
A AO
> o
;»
O O
> 20-
O
. -r-8
o °
"2 1
10-
rf A***-*
o
o
0 25 50 75 100 125 150 175 200 225 250
275 300 325 350 375
Fork length (cm)
Figure 6
Maturation of female shortfin mako sharks (Jsurus oxyrinchus): relation-
ship between fork length and ovary thickness, oviducal gland diameter,
and maximum ovum diameter.
Clasper length (%)
en o oi
i i 1
• jAf *
Spermatozeugmata present (%)
Percentage mature (%)
o
o o o o o
^ CO CD ''t OJ C
o Claspers - free-living (n=286)
Spermatozeugmata present
• Percentage mature (direct)
Percentage mature (fitted curve)
o ft
^sF®t o? o ° °
c% cSfc ° •
u -i
(
Matui
develc
and d
) 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 3J
Fork length (cm)
Figure 7
ation of male blue sharks (Prionace glauca): variation i
pment, presence of spermatozeugmata in the reproduct
trect maturity estimation from a suite of maturity indii
0
n clasper
ive tract,
;ators.
necessarily confirm reproductive viability, and their
absence does not confirm immaturity. Similarly, fully
calcified claspers that can be rotated, splayed open,
and possess an anchoring mechanism may confer an
ability to mate, but they do not necessarily confirm an
ability to deliver viable products; however the lack of
fully developed claspers presumably does prevent suc-
cessful copulation.
In the present study, either the length at which
clasper development was completed in half the male
population, or the length at which 50% of males pos-
sessed spermatophores or spermatozeug-
mata, whichever was higher, provided
an estimate of the lower bound of the
median maturity. The actual median
maturity may be higher than this es-
timate if some males had reproductive
products that lacked viable sperm, or if
some other feature of the reproductive
system (e.g., the siphon system) was in-
sufficiently developed to enable delivery
of sperm to the female.
An analogous argument applies to fe-
male sharks. Full development of the
uterus and oviducal gland, and produc-
tion of vitellogenic ovarian ova, are all
required for successful reproduction.
Expansion of the uterus, as measured
here by UWI, may not be a sufficient
condition by itself. Thus the length at
which half the female population had
expanded uteri places a lower bound on
the median maturity.
The smallest length at which females
were pregnant, and the length-frequency
distributions of pregnant females, are
not by themselves good indicators of me-
dian maturity. A better indicator would
be the length at which half the females
in a population first become pregnant,
but this is impossible to determine. Fur-
thermore, pregnancy estimates could be
confounded by unrepresentative sam-
pling of a population that may be seg-
regated by reproductive status and by
nonparticipation of some females during
breeding because they are "resting" be-
tween pregnancies. Nevertheless, preg-
nancy absolutely confirms maturity;
therefore it is a useful adjunct to other
measures of maturity.
The presence or absence of a hymen
has been used in some studies to indi-
cate maturity. However it should not be
used for that purpose because adolescent
(premature) mating occurs in at least
some species of sharks, including blue
sharks (Pratt, 1979). Furthermore, the
absence of a hymen may not even be a
good indicator of mating: we observed
Francis and Duffy Length at maturity in three pelagic sharks
497
Pregnant females (n=40)
Uterus width index (n=650)
Percentage mature (direct)
Percentage mature (fitted curve)
■8 _Q -08
125 150 175 200
Fork length (cm)
Figure 8
Maturation of female blue sharks iPrionace glauca): variation in uterus
width index, direct maturity estimation from a suite of maturity indicators,
and length-frequency distribution of pregnant females are shown.
Table 4
Summary of length at maturity indicators in porbeagle, shortfin mako, and blue sharks, and estimates of median length at
maturity. Table entries are fork lengths in centimeters. Direct maturity estimates were derived by examination of a suite of
maturity indicators. Italics indicate estimates based on small sample sizes over the maturation length range. " — " indicates that
an estimate was not possible.
Sex
Maturity indicator
Porbeagle shark
Shortfin mako shark
Blue shark
Males
Females
50% with spermatophores
Rapid clasper elongation complete
Direct maturity estimate
Median length at maturity
Rapid expansion of uterus begins
First females pregnant
Direct maturity estimate
Median length at maturity
152
143
140-150
145
167
170-180
178
194
185
—
183
192
180-185
190-195
275
170
i
166
280
—
275-285
170-190
Only one pregnant female (290 cm FL) has been recorded from New Zealand.
some female shortfin makos in which the membrane
was very thin and partially perforated, but had clearly
not been damaged by copulation. We believe that the
hymen disintegrates naturally with growth in makos;
the same possibility was proposed for blue sharks by
Pratt (1979).
Using a combination of our direct maturity estimates,
and other indicators of maturity based on larger sam-
ples of sharks, we generated overall estimates of me-
dian maturity for both sexes of the three pelagic sharks
(Table 4).
Porbeagle shark
In male porbeagles, the length at which 50% of sharks
had spermatophores (152 cm) was longer than the length
at which clasper elongation was complete (143 cm)
(Table 4). However the percentage of males having sper-
matophores did not reach 100% in the longer length
groups (Fig. 2), indicating that some mature males were
reproductively inactive. This finding is consistent with
reports from the western North Atlantic that male por-
beagles have a seasonal cycle of spermatophore produc-
tion, with a minimum in winter-spring (Jensen et al.,
2002). If some mature males lacked spermatophores, the
length at which 50% of males had spermatophores in our
study was probably greater than the median maturity.
The lack of a direct maturity estimate limits our ability
to estimate the median maturity, but it is likely in the
range 140-150 cm.
Similarly, we have no direct estimate of female por-
beagle maturity. There was a considerable gap between
498
Fishery Bulletin 103(3)
the length at which rapid expansion of the uterus be-
gan (145 cm) and the length of the smallest pregnant
female (167 cm). UWI values less than 2% occurred for
females up to about 185 cm (Fig. 3), but this does not
mean that a high proportion of females in this length
group had narrow uteri; uterus width measurements
were not available for most of our pregnant females and
therefore large UWI values are underrepresented in
Figure 3. Most pregnant females were 170-200 cm long.
We estimate that median maturity in females is about
170-180 cm, but this estimate requires confirmation.
It is essentially the same as that provided by Francis
and Stevens (2000) for New Zealand and Australian
porbeagles (their New Zealand data were a smaller
subset of the data used in the present study).
Although our estimates of median maturity for both
males and females are uncertain, it is clear that por-
beagles from New Zealand mature at considerably
smaller lengths than they do in the North Atlantic.
In the western North Atlantic, males mature at about
166 cm and females at 208 cm (Jensen et al., 2002).
Data from the eastern North Atlantic (Gauld, 1989;
Ellis and Shackley, 1995) are insufficient to estimate
length at maturity, but the pregnant females reported
by Gauld (1989) were considerably longer (199-248 cm)
than those from New Zealand.
Porbeagles from the North Atlantic also grow larger
than those from New Zealand: in the North Atlantic,
sharks longer than 200 cm are common (Gauld, 1989;
Campana et al., 2001), whereas around New Zealand
and Australia they are very rare (Francis et al., 2001;
Stevens and Wayte4). Differences in length at maturity
between the North Atlantic and New Zealand and the
proportion of sharks in the longer length classes indi-
cate the existence of separate populations in the two
regions — a conclusion that is supported by the disjunct
distribution of porbeagles in the Northern and Southern
Hemispheres (Compagno, 2001).
Shortfin mako shark
Our direct maturity estimate for male makos (183 cm)
was based on a small sample size, and the small overlap
between the lengths of immature and mature sharks
is implausible. However, the lengths at which clasper
development was completed, and at which 50% of males
had spermatophores, were similar to the direct estimate
(Table 4). Median maturity for males is therefore about
180-185 cm.
Our direct maturity estimate for female makos
(280 cm) was based on few sharks over the matura-
tion length range but was consistent with the length
at which rapid uterus expansion began (275 cm). Our
best estimate of median maturity in females is 275-
285 cm.
Stevens (1983) used the degree of clasper calcifica-
tion and an inflection in clasper length to estimate the
length at maturity of males from New South Wales
as 176 cm. In South Africa, males were estimated to
mature at 177-188 cm (Cliff et al., 1990), but very few
immature sharks were available. Our estimate of me-
dian maturity in New Zealand males (180-185 cm) is
therefore similar to those from elsewhere.
Mollet et al. (2000) reported lengths at maturity for
female makos of 298 cm total length in the Northern
Hemisphere and 273 cm total length in the Southern
Hemisphere. However, some of the 25 cm difference was
due to Northern Hemisphere measurements having been
taken over the curve of the body and Southern Hemi-
sphere measurements having been taken in a straight
line. Using appropriate conversion regressions, their
Northern Hemisphere median maturity is equivalent
to 267 cm FL, and their Southern Hemisphere median
maturity is equivalent to 248 cm FL. When Mollet et
al.'s Southern Hemisphere data are analysed separately
for two subregions, South Africa and Australia, the
estimated lengths at maturity are 244 cm (n = 50) and
254 cm (n = 32) respectively (Mollet5). The former is con-
sistent with Cliff et al.'s (1990) estimate of 243 cm for
South Africa, and the latter is consistent with Stevens's
(1983) estimate of 255 cm for eastern Australia (both
those estimates were made from subsets of the data
used by Mollet et al. [2000]).
Our estimate of median maturity in New Zealand
females (275-285 cm) is substantially higher than Mol-
let's5 estimate for Australia (254 cm). Because tagged
makos have moved between New Zealand and eastern
Australia in both directions (Chan, 2001; Hartill and
Davies, 2001; Holdsworth and Saul, 2003), we think it
is unlikely that the difference is due to the presence
of distinct populations in the two regions. We suspect
that the difference is a result of possible length estima-
tion errors (some of the Australian shark lengths were
calculated from recorded weights, with a length-weight
regression [Stevens, 1983; Mollet et al., 2000]), and
the result of small sample sizes over the length range
at maturation. For our direct maturity estimate, we
had only 19 New Zealand sharks over the length range
240-290 cm, and Mollet5 had 15 sharks.
Interestingly, our estimate of median maturity in New
Zealand females is also greater than Mollet et al.'s (2000)
estimate for the western North Atlantic, thus removing
the reported between-hemisphere difference. We believe
that larger, accurately measured samples of female ma-
kos are required before definitive statements can be
made about length at maturity in the various regions.
Blue shark
In male blue sharks from New Zealand, CLI lacked an
inflection near the length of maturity — a feature that
4 Stevens, J. D., and S. E. Wayte. 1999. A review of Aus-
tralia's pelagic shark resources. FRDC Proj. Rep. 98/107,
64 p. [Available from CSIRO Marine Research, PO Box
1538, Hobart, Tasmania 7001, Australia.]
5 Mollet, H. 2004. Personal commun. Moss Landing Marine
Laboratories, 8272 Moss Landing Road, Moss Landing, CA
95039.
Francis and Duffy: Length at maturity in three pelagic sharks
499
has also been reported elsewhere (Pratt, 1979; Hazin et
al., 1994). Thus clasper length was not useful in estimat-
ing length at maturity. Our direct maturity estimate
was similar to the length at which 50% of sharks had
spermatozeugmata and indicated that median maturity
occurs at about 190-195 cm (Table 4).
In females, maturation occurred over a wide length
range, as reported elsewhere (Hazin et al., 1994). Taking
into account the length distributions of pregnant females
and females with low UWI values (Fig. 8), we believe
median maturity is likely in the range 170-190 cm.
In other blue shark studies, estimation of the length
at maturity has also been hindered by small sample
sizes, or even a complete absence of immature or mature
sharks. In the western North Atlantic, males mature at
about 178 cm, and females at around the same length,
although few mature females have been available (Pratt,
1979). In the Gulf of Guinea, Atlantic Ocean, 50% of
females were pregnant at 180 cm (Castro and Mejuto,
1995). In Australian studies, a lack of immature sharks
made it impossible to estimate maturity adequately (Ste-
vens, 1984; Stevens and McLoughlin. 1991). In the North
Pacific Ocean, 50% of males had spermatozeugmata at
166 cm and 50% of females were pregnant at 174 cm
(Nakano, 1994). Thus worldwide estimates of maturity
in blue sharks are similar to ours from New Zealand,
except perhaps for a smaller length at maturity of males
in the North Pacific. Unlike females in most species of
sharks, female blue sharks do not appear to mature at
a length greater than that for mature males.
Acknowledgments
We thank the Ministry of Fisheries for funding this
study under research project TUN2002/01, and provid-
ing access to data collected by observers. Lynda Griggs
(NIWA) assisted with data extracts and interpretation,
and Chris Francis (NIWA) carried out the probit analy-
ses. Lisa Natanson, Wes Pratt, Steve Campana, and
Henry Mollet kindly provided unpublished data and
advice on their interpretation.
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tion and survey. J. Morph. 219:297-308.
Smith, S. E., D. W. Au, and C. Show.
1998. Intrinsic rebound potentials of 26 species of Pacific
sharks. Mar. Freshw. Res. 49:663-678.
Stevens, J. D.
1983. Observations on reproduction in the shortfin mako
Isurus oxyrinehus. Copeia 1983:126-130.
1984. Biological observations on sharks caught by sport
fishermen off New South Wales. Aust. J. Mar. Freshw.
Res. 35:573-590.
Stevens, J. D., and K. J. McLoughlin.
1991. Distribution, size and sex composition, repro-
ductive biology and diet of sharks from Northern
Australia. Aust. J. Mar. Freshw. Res. 42:151-199.
501
Abstract — Survey- and fishery-
derived biomass estimates have
indicated that the harvest indices
for Pacific cod iGadus macrocepha-
lus) within a portion of Steller sea
lion (Eumetopias jubatus) critical
habitat in February and March 2001
were five to 16 times greater than
the annual rate for the entire Bering
Sea-Aleutian Islands stock. A bottom
trawl survey yielded a cod biomass
estimate of 49,032 metric tons (t) for
the entire area surveyed, of which
less than half (23,329 t) was located
within the area used primarily by
the commercial fishery, which caught
11,631 t of Pacific cod. Leslie deple-
tion analyses of fishery data yielded
biomass estimates of approximately
14,500 t (95% confidence intervals of
approximately 9,000-25,000 t), which
are within the 95f>r confidence inter-
val on the fished area survey estimate
(12,846-33,812 t). These data indicate
that Leslie analyses may be useful
in estimating local fish biomass and
harvest indices for certain marine
fisheries that are well constrained
spatially and relatively short in dura-
tion (weeks). In addition, fishery
effects on prey availability within
the time and space scales relevant
to foraging sea lions may be much
greater than the effects indicated by
annual harvest rates estimated from
stock assessments averaged across the
range of the target species.
Survey- and fishery-derived estimates of
Pacific cod (Gadus macrocephalus) biomass:
implications for strategies to reduce interactions
between groundfish fisheries and Steller sea lions
(Eumetopias jubatus)
Lowell W. Fritz
National Marine Mammal Laboratory
Alaska Fisheries Science Center
National Marine Fisheries Service
7600 Sand Point Way NE
Seattle, Washington 98115
E-mail address lowell.fntz@noaa gov
Eric S. Brown
Resource Assessment and Conservation Engineering
Alaska Fisheries Science Center
National Marine Fisheries Service
7600 Sand Point Way NE
Seattle, Washington 98115
Manuscript submitted 20 May 2004 to
the Scientific Editor's Office.
Manuscript approved for publication
23 March 2005 by the Scientific Editor.
Fish. Bull. 103:501-515 (20051.
For the past 30 years, the Steller sea
lion (Eumetopias jubatus) popula-
tion in western Alaska has declined
(Braham et al., 1980; Sease and Gud-
mundson1). The species was listed as
threatened under the U.S. Endangered
Species Act (ESA) in 1990 after evi-
dence of a major decline in abundance
in the core of its range from the Kenai
Peninsula in south-central Alaska to
Kiska Island in the western Aleutian
Islands (Braham et al., 1980; Merrick
et al., 1987). After the decline was
first observed in the eastern Aleutian
Islands in the early 1970s (Braham
et al., 1980), it spread eastward to
Prince William Sound and west-
ward through Russia during the next
decade (Merrick et al., 1987; Loughlin
et al., 1992). From the early 1970s
to 1990, counts of adult and juvenile
Steller sea lions declined by over 70%,
but annual rates of decline were most
severe between 1985 and 1989 (-15%/
yr; Loughlin et al., 1992). During the
1990s, the decline slowed to approxi-
mately -5%/yr and may have tempo-
rarily abated in many areas by 2002
(Sease and Gudmundson1).
Understanding the causes for the
decline and lack of recovery in the
Steller sea lion population has large-
ly eluded scientists and managers.
despite the millions of dollars spent
on scientific research (Ferrero and
Fritz2) and numerous reviews by aca-
demic (Alaska Sea Grant3; DeMaster
and Atkinson4; NRC, 1996; 2003) and
governmental panels (Kruse et al.5;
NMFS6'7'8-9). Although recent reviews
1 Sease, J. L., and C. J. Gudmundson.
2002. Aerial and land-based surveys
of Steller sea lions (Eumetopias jubatus)
from the western stock in Alaska, June
and July 2001 and 2002. NOAA Tech.
Memo. NMFS-AFSC-131, 45 p. Alaska
Fisheries Science Center, 7600 Sand
Point Way NE, Seattle WA 98115.
2 Ferrero, R. C. and L. W. Fritz. 2002.
Steller sea lion research coordination:
a brief history and summary of recent
progress. NOAA Tech. Memo. NMFS-
AFSC-129, 34 p. Alaska Fisheries Sci-
ence Center, 7600 Sand Point Way NE,
Seattle WA 98115.
3 Alaska Sea Grant. 1993. Is it food?:
Addressing marine mammal and sea-
bird declines. Workshop summary
rep. AK-SG-93-01, 59 p. Univ. Alaska
Fairbanks, Alaska Sea Grant College
Program, Fairbanks AK 99775.
4 DeMaster, D., and S. Atkinson, (eds.l.
2002. Steller sea lion decline: Is it food?
II. Workshop summary, rep. AK-SG-
02-02, 80 p. Univ. Alaska Fairbanks,
Alaska Sea Grant College Program,
Fairbanks AK 99775.
5. 6. 7, 8, 9 gee nexf page.
502
Fishery Bulletin 103(3)
(Kruse et al.5; DeMaster and Atkinson4; NRC, 2003)
concluded that "top-down" forces, such as predation or
illegal shooting, are greater threats to recovery of the
Steller sea lion population, they could not eliminate
"bottom-up" factors from consideration. NRC (2003)
suggested that NMFS conduct an adaptive manage-
ment experiment to determine the magnitude of one
such "bottom-up" force, nutritional stress resulting from
competition with fisheries for prey (NMFS67-89; NRC.
2003). The North Pacific is home to some of the largest
fisheries in the world, particularly those for groundfish
such as Pacific cod (Gadus macrocephalus) and walleye
pollock (Theragra chalcogramma). Steller sea lions eat
a wide variety offish and cephalopods, including Pacific
cod, walleye pollock, Atka mackerel (Pleurogrammus
monopterygius), arrowtooth flounder (Atherestes sto-
rnias), salmon (Oncorhynehus spp.), herring (Clupea pal-
lasi), capelin (Mallotus villosus), eulachon (Thaleichthys
pacificus), sand lance {Ammodytes hexapterus), squid,
and octopus (Sinclair and Zeppelin, 2002). A large pro-
portion of their diet, however, is composed of semide-
mersal or pelagic schooling fish, particularly fish in
spawning migrations or aggregations nearshore. These
same species are often targeted at the same time and
in the same areas by groundfish fisheries, particularly
those fisheries that use trawl gear. Concerns about the
potential of fisheries to create localized depletions of
prey in important sea lion foraging habitats have led to
controversial groundfish fishery restrictions throughout
most of Alaska (NMFS8-9).
5 Kruse, G. H., M. Crow, E. E. Krygier, D. S. Lloyd, K. W.
Pitcher, L. D. Rea, M. Ridgway, R. J. Small, J. Stinson and
K.M.Wynne. 2001. A review of proposed fishery manage-
ment actions and the decline of Steller sea lions lEumetopias
jubatus) in Alaska: a report by the Alaska Steller sea lion
restoration team. Regional information report 5J01-04,
106 p. Alaska Dep. Fish and Game, P.O. Box 25526. Juneau
AK 99802.
H NMFS (National Marine Fisheries Service). 1998. En-
dangered Species Act Section 7 Consultation on an Atka
mackerel fishery under the BSAI groundfish FMP between
1999 and 2002; authorization of a walleye pollock fishery
under the BSAI FMP between 1999 and 2002; and under the
GOA FMP between 1999 and 2002, 189 p. NMFS Protected
Resources Division, Alaska Region, P.O. Box 21668, Juneau,
AK 99802.
7 NMFS. 2000. Endangered Species Act. Section 7: Con-
sultation, biological opinion and incidental take statement
on the authorization of the Bering Sea-Aleutian Islands and
Gulf of Alaska groundfish fisheries based on the Fishery
Management Plans, 352 p. NMFS Protected Resources Divi-
sion, Alaska Region, P.O. Box 21668, Juneau. AK 99802.
8 NMFS. 2001. Endangered Species Act. Section 7: Con-
sultation, biological opinion and incidental take statement
on the authorization of the Bering Sea-Aleutian Islands and
Gulf of Alaska groundfish fisheries based on the Fishery
Management Plans as modified by Amendments 61 and 70,
206 p. NMFS Protected Resources Division, Alaska Region,
P.O. Box 21668, Juneau, AK 99802.
9 NMFS. 2003. Supplement to the Endangered Species Act.
Section 7: Consultation, biological opinion and incidental
take statement of October 2001, 179 p. NMFS Protected
Resources Division, Alaska Region, P.O. Box 21668, Juneau,
AK 99802.
Assessment models and fisheries harvest strategies
have determined the overall fishing mortality rate that
can be allowed for the stock and the amount of biomass
that can be removed. In practice, however, catches are
not uniformly distributed across the range of the as-
sessed stock nor are they distributed equally through-
out the year. Although there is evidence that the Atka
mackerel trawl fishery has created localized depletions
of its target species (NMFS6 Lowe and Fritz, 1997;
NRC, 2003), this finding has not been generally applied
to fisheries for other sea lion prey. Trawl fisheries in
the Aleutian Islands may have, in certain instances,
reduced local abundances of Atka mackerel by as much
as 90% (Lowe and Fritz, 1997). Atka mackerel and its
fishery have characteristics that permitted analysis of
fishery data in this way. The species does not possess
a swim bladder and thus makes a poor acoustic target.
As a consequence, the Atka mackerel fishery does not
target on an acoustic signal, but instead trawls in ar-
eas where the species is known to congregate. Through
the analysis of time series of catch and effort statis-
tics from local fisheries with Leslie's equation (Ricker,
1975; Hilborn and Walters, 1992; Gunderson, 1993),
estimates of the initial abundance of Atka mackerel
(prefishery) and its catchability (proportion of the stock
caught with one unit of effort) were made within the
context of certain assumptions, which included the
following: 1) the population being fished is closed, or
alternatively that immigration and growth are equal
to emigration plus natural mortality, 2) catchability
over the course of the fishery remains constant, and
3) changes in catch per unit of effort (CPUE) are di-
rectly related to changes in fish density. These assump-
tions may be met for marine species if the area fished
is well defined (e.g., is surrounded by habitat that is
unsuitable for the species), the duration of the fishing
season is relatively short, or the species is relatively
sedentary (Polovina, 1986; Ralston, 1986; Joll and
Penn, 1990; Miller and Mohn, 1993). Although they
indicate that fisheries have created local depletions
of Atka mackerel, these models are difficult to apply
to other North Pacific fisheries because of a lack of
fishery-independent estimates of biomass and by cir-
cumstances unique to the Atka mackerel fishery (e.g.,
the fishery trawls in areas where the species is known
to congregate rather than uses acoustic signal, Atka
mackerel are patchily distributed, and patches are
separated by areas with low fish density).
To obtain information on the winter distribution of
groundfish in areas used by foraging Steller sea lions
and groundfish fisheries, the Alaska Fisheries Science
Center of the National Marine Fisheries Service con-
ducted a bottom trawl survey for groundfish in the
southeastern Bering Sea north of Unimak Island in
February-March 2001 (Fig. 1). This area is important
to the Pacific cod fishery in winter because cod ag-
gregate in this area to spawn (Shimada and Kimura,
1994). It is also recognized as an important foraging
area for Steller sea lions because it is designated as
critical habitat under the ESA (NMFS7-8).
Fritz and Brown: Interactions between the Pacific cod fishery and Steller sea lions
503
Figure 1
The four areas (high and low sampling-effort survey areas, the area east of the survey area, and
the area south of the survey area) in the southeastern Bering Sea that were surveyed in February-
March 2001 for groundfish with a bottom trawl and used for analysis of Pacific cod iGadus mac-
rocephalus) fishery data. Steller sea lion {Eumetopias jubatus) critical habitat is also shown.
In this article, estimates of Pacific cod biomass from
Leslie depletion analyses of fishery data are compared
with those derived from a bottom trawl survey con-
ducted in the same area at the same time. These two
methods are independent because they use completely
different data to estimate the same parameter, Pacific
cod biomass. If they yield similar results, they would
support each other in the estimate of local area cod bio-
mass and support the use of Leslie depletion analyses
of data from relatively short and spatially well-defined
fisheries operations for making such estimates. Fur-
thermore, these comparisons increase our understand-
ing of the potential local effects of a fishery in areas
important for sea lion foraging and permit compari-
son with the results of assessments of the Pacific cod
stock in the entire eastern Bering Sea (Thompson and
Dorn, 2002). In this instance, if the change in Pacific
cod abundance attributable to the fisheries north of
Unimak Island is not greater than what would have
occurred if catch were evenly distributed throughout
the year and across the range of the stock, then it
could be argued that no localized depletion occurred.
However, if the local change in abundance is greater
than expected, does this constitute a localized deple-
tion of the species? The answer ultimately depends on
the extent to which the fishery negatively affects the
target species (e.g., by reducing recruitment) or, as
in our case, by reducing the foraging success of sea
lions, which, in turn, could lead to reduced survival or
reproductive rates. Although we do not know what the
threshold levels of change in local prey densities are
for foraging Steller sea lions, it is first necessary to
determine the level of change in local abundance that
may be attributable to fisheries.
There are several aspects of Pacific cod life history
in the eastern Bering Sea that make it difficult to use
fishery data and the Leslie depletion method to estimate
local area biomass. The most important may be that the
population in the area fished may not be closed over
the time period analyzed. Pacific cod spawn north of
Unimak Island in late winter but apparently arrive in
groups and, after spawning, leave the area and spread
out on the eastern Bering Sea shelf to feed during the
remainder of the year (Shimada and Kimura, 1994;
Thompson and Dorn, 2002). Seasonal emigration from
and immigration into spawning areas in critical habi-
tat, modeled with a combination of fishery and survey
data by NMFS scientists10 (Fig. 2), provide a baseline
111 NMFS. 2000. Estimation of monthly Pacific cod biomass
inside Steller sea lion critical habitat. In Biological opinion
questions, NMFS-AKC analytical team. Unpubl. manuscript,
112 p. Alaska Fisheries Science Center, 7600 Sand Point
Way NE, Seattle WA 98115.
504
Fishery Bulletin 103(3)
1 o
09
08
07
06
05
04
03
02
0 1
0.0
Feb Mar Apr May Jun
Aug Sep Oct Nov Dec
Figure 2
Proportion of maximum (in February) biomass of Pacific cod iGadus
macrocephalus) within Steller sea lion (Eumetopias jubatus) critical
habitat in the eastern Bering Sea by month (see Footnote 10 in the
general text).
against which possible changes related to local fisheries
can be compared. The model results indicate that the
highest biomass in critical habitat (largely on the shelf
north of Unimak Island) occurs in February, declines to
about 10% of the peak in June, and then slowly rebuilds
through the summer and fall. Changes in the behavior
of Pacific cod immediately prior to or after spawning,
such as the formation of dense aggregations or the tem-
porary cessation of feeding, would affect catchability by
both trawl and fixed gears. However, abrupt changes in
catchability due to the formation of aggregations should
be evident within the time series of catch and effort
data, and changes in feeding habits would not affect
the catchability by trawl gear.
Methods
Bottom trawl survey
Stations sampled during the bottom trawl survey were
selected by using a stratified random scheme. Two strata
were defined: one with a high and another with a low
degree of sampling effort, based on the expected distri-
bution and abundance of Pacific cod from fishery infor-
mation. In the nearshore or high sampling-effort stratum
(7765 km2), 38 stations were sampled, whereas 19 sta-
tions were sampled in the larger (12,112 km'2), offshore
low sampling-effort stratum (Fig. 1). All survey tows
were conducted during daylight hours from 16 Febru-
ary to 1 March 2001 aboard the FV Northwest Explorer
and the FV Ocean Harvester. The 49-m FV Northwest
Explorer was equipped with two 1800-hp engines, and
the 33-m FV Ocean Harvester had a single 1250-hp
engine. Both vessels were house-forward trawlers that
had stern ramps, multiple net storage reels, and paired
hydraulic trawl winches with 1280-2190 m of 2.54-cm
diameter steel cable. Each vessel carried a full comple-
ment of navigation and fishing electronics, including
global positioning systems (GPS), video position plotters,
radars, and depth sounders.
A Poly-Nor'eastern high-opening bottom trawl rigged
with roller gear was used to sample the groundfish
community at each selected location. The trawl net
was constructed of 12.7-cm stretched-mesh polyethylene
web and had a 3.2-cm stretched-mesh nylon liner in
the codend. Accessory gear for the Nor'eastern trawl
included three 54.9 m, 1.6 cm diameter galvanized wire
rope bridles, and 1.8 x 2.7 m steel V-doors weighing ap-
proximately 850 kg each.
Biomass (S) estimates for each stratum surveyed
were computed by multiplying the average CPUE (in
units of kg/km2) for all hauls (n) in a stratum by its
area (A). Haul CPUE was calculated as the weight of
cod caught (kg) divided by the area swept (a), which
was the length of the tow multiplied by the average net
width determined by sonic mensuration equipment:
kg
■xA.
B
Confidence bounds on stratum biomass estimates were
computed from the standard deviation of the haul
CPUEs. For haul CPUEs we assumed a catchability11
of 1 for Pacific cod (all cod within the area swept by
Note that catchability within the survey biomass estima-
tion procedure has a different literal definition than in the
Leslie equation.
Fritz and Brown: Interactions between the Pacific cod fishery and Steller sea lions
505
Bottom Trawl Survey - Pacific cod
WGTCPUE
o Cod CPUE=0
° Cod CPUE < Mean
* Mean < Cod CPUE < Mean + 2 SDs
• Mean + 2 SDs < Cod CPUE < Mean + 4 SDs
#Cod CPUE > Mean + 4 SDs
Figure 3
Catch per unit of effort (CPUE=kg/km2l of Pacific cod {Gadus macrocephalus) during the February-
March 2001 bottom trawl survey of the southeastern Bering Sea. "Wgtcpue" refers to the CPUE of
Pacific cod from individual hauls (Table 2). Area shading is the same as that in Figure 1.
the net are captured) and that it is constant over the
course of the survey. This assumption is also made in the
Leslie analyses of fishery data. In addition, each haul is
assumed to be a random, normally distributed estimate
of the density of cod within the stratum. Therefore, the
average of the haul CPUEs of cod was assumed to be an
unbiased estimate of the true density of cod, allowing
linear extrapolation from the CPUE within the area
swept to a biomass estimate for each stratum.
Analysis of fishery data
Fishery observers record a wide variety of information
about each haul taken by a fishing vessel, including
retrieval location, depth, date and time of catch, and
total catch weight (all referred to hereafter as "haul
data"). In addition, the catch of a randomly chosen subset
of hauls was sampled to determine the species composi-
tion of the haul and the length distribution of the target
species (see Nelson et al. 1981 and NMFS12 for observer
sampling methods). Observer data were queried for any
12 NMFS. 1996. Manual for biologists aboard domestic
groundfish vessels, 431 p. U.S. Dep. Commer., NOAA.
NMFS, Alaska Fisheries Science Center, 7600 Sand Point
Way, NE, Seattle, WA 98115.
hauls with any gear in which Pacific cod were caught in
the eastern Bering Sea and Aleutian Islands region in
2001. The geographic distribution of the observed Pacific
cod catch was used to estimate the distribution of the
actual catch of Pacific cod from January-April 2001
in four areas of the southeastern Bering Sea (Fig. 1):
the high and low sampling-effort areas surveyed in
February-March 2001, and two areas outside of the
area surveyed — one to the east, and one to the south.
To account for Pacific cod catches in both unsampled
hauls and on unobserved vessels, the observed catch
of cod was multiplied by the ratio of total-to-observed
catch by processing sector and gear type (Table 1). For
this procedure, the catch of the unobserved portion of
the fleet is assumed to be similar to the observed por-
tion. Ratios of total-to-observed catch by sector and gear
ranged from 1.02 to 33.94, but for the majority of the
catch, the ratios were less than 2 (Table 1).
A simple Leslie analysis of fishery catch and effort
data was conducted on data collected by observers on-
board vessels targeting groundfish. For the basic Les-
lie model (Ricker, 1975; Hilborn and Walters, 1992;
Gunderson, 1993) a deterministic linear relationship
between CPUE and cumulative catch is assumed:
Ct
■■qB0-qKt,
506
Fishery Bulletin 103(3)
Table 1
Observed and total estimate
5 of total catches of Pacific cod
by processor
and gear type
in the Be
ring Sea-Aleutians
Island region in 2001, and the ratio o
f Total h- Observed
catches. CP=
=catcher processor; CV=catcher vessel
Catches
Processor type
Gear
and ratio
CP
CV
Other
Trawl
Total (t)
29,398
21,354
734
Observed ( t )
19,316
8590
720
Ratio
1.52
2.49
1.02
Hook and
Total (t)
96,238
637
11,331
line
Observed (t)
52,920
19
11,109
Ratio
1.82
33.94
1.12
Pot
Total (t)
16,506
478
Observed (t)
4741
469
Ratio
3.48
1.02
directly related to vessel length. With increasing vessel
length, horsepower would increase as would the vessel's
ability to use larger nets. Vessel length (a surrogate vari-
able for horsepower) could be a significant covariate in
the relationship between CPUE and cumulative catch.
Results
Bottom trawl survey
Mean CPUE (kg/km2) of Pacific cod in the smaller HSE
survey stratum was almost three times higher than
in the larger LSE stratum, resulting in mean biomass
estimates of 31,312 t and 17,720 t of Pacific cod, respec-
tively (Table 2 and Fig. 3). The highest recorded CPUE
of cod was recorded for a haul on the northeast side of
Unimak Pass (Fig. 3). Hauls with CPUEs above the
mean were distributed throughout the HSE stratum in
depths less than 200 m. Only one of the 18 hauls in the
LSE stratum had a CPUE larger than the mean. For the
HSE stratum, the 95% confidence interval on the mean
biomass estimate was 19.284-43,339 t.
where C, = catch in time period t;
ft = effort in t;
q = catchability;11
B0 = underlying (or initial) biomass; and
Kt = cumulative catch through /.
Current catch, effort, and cumulative catch are required
by the model, whereas catchability and initial biomass
are estimated from it. The catch and effort time series
used in these analyses were 1) daily aggregates of
observed cod catch in metric tons (t) and effort by ves-
sels targeting cod by area (i.e., the high sampling-effort
[HSE] area, the low sampling-effort area [LSE], the
area east [AE] and the area south [AS] of the survey
area), and 2) daily cumulative catch of cod by area for
all vessels. CPUE metrics were defined for each gear: 1)
trawl as the catch of cod (t) per hour of observed trawl-
ing per day; 2) pot as the catch of cod (t) per 20 pots
observed per day; and 3) hook and line as the catch of
cod (t) per 1000 hooks observed per day. These metrics
were chosen so that the CPUE for each gear would be in
approximately the same range to permit being plotted
together on the same axis. Changing the unit-of-effort
definition (number of pots or hooks fished, for instance)
has no effect on the significance of the results. Hauls for
which cod was the target species were defined as those
in which the catch of cod was at least 20% of the total
groundfish catch; target levels of 40% and 60% were also
explored for trawl fisheries. Catch and effort from these
hauls alone, in which cod was the target species, were
used for CPUE calculations, whereas cumulative catch
was derived from the total catch of cod from all vessels
regardless of their target species.
The relationship between trawl vessel length and
CPUE was investigated but was not included in the
Leslie analyses. It was expected that CPUE would be
Fishery data
Total catch of Pacific cod Approximately 30,500 t of
Pacific cod were caught in the four areas of the south-
eastern Bering Sea from 1 January to 30 April 2001
(Table 3 and Fig. 4). Almost 60% of this total catch was
collected in the HSE survey stratum, whereas 25% and
12% of the total catch were collected in the AE and AS
of the survey area, respectively; only 4% was collected
in the LSE survey stratum. Based on the distribution of
the observed catch of cod by gear, approximately half of
the total catch was collected by trawls, a third by hook
and line (=longline), and 14% by pots.
The distribution of cod catch by area primarily re-
flects the distribution of the fishery targeting Pacific cod
(Fig. 4). Of the 5813 t of cod that was observed caught
by the cod trawl fleet (with at least 20% of each haul
composed of cod), 86% was caught in the HSE stratum
in over 4600 hours of observed trawling. Most of the
remainder (13% or 781 t) was caught east (AE) of the
survey area, primarily between the HSE stratum and
the 20 nautical mile (nmi) radius trawl exclusion zone
encompassing sea lion critical habitat around Sea Lion
Rocks and Amak Island (Figs. 1 and 4). There was little
trawl effort targeting Pacific cod in the LSE stratum
(only 10 observed hours of trawling) or south (17 hours
observed) of the survey area. The cod pot fleet worked
primarily south of the survey area (57% of their catch)
and in the HSE stratum (31%) in areas where conflicts
with trawl gear would be minimized. The cod longline
fleet worked in both the HSE stratum and to the east
of the survey area, and had only trace amounts of catch
in the other areas (Table 3).
Percentage of Pacific cod in the haul The distribution
of the percentage of cod in the total catch of each haul
Fritz and Brown: Interactions between the Pacific cod fishery and Steller sea lions
507
0 25 50 Kilometers
I i I
Figure 4
Locations of groundfish fishery catches of Pacific cod tGadus macrocephalus) in the south-
eastern Bering Sea, January-April 2001. The cod target fishery is separated by gear type
(trawl = at least 20% of the haul by weight was cod). "All catches of cod" refers to bycatch in
trawl fisheries targeting other species. Area shading is the same as that seen in Figure 1.
Table 2
Results (catch and biomass of Pacific cod
and haul data from the bottom trawl survey of the southeastern Bering Sea con-
ducted in February-March 2001
Low and high sampling-effort strata
are
shown in Figure 1. (CPUE =
=catch
per unit of effort;
CI=confidence interval).
Survey stratum
Low sampling effort
High sampling effort
Total
Number of hauls
19
38
57
Number of hauls with cod
19
37
56
Mean CPUE (kg cod/km2)
1463
4032
3176
Range in CPUE
65-12,681
0-21,299
0-21,299
Standard deviation of CPUE
2776
4676
4292
Area of stratum (km2)
12,112
7765
19,877
Area of stratum sampled (km2)
0.472
0.927
1.399
% of stratum area sampled
0.004%
0.012%
0.007Q
Biomass (t I
17,720
31,312
49.032
95% CI on biomass (t)
1513-33,928
19,284-43,339
20,796-77,267
indicates that the vast majority of the fleet using pots
or longline gear were targeting Pacific cod. The total
catch of 350 of 351 observed hauls of pots and 777 of
797 observed hauls of longlines was composed of at least
60% cod (Table 4). Therefore, use of a 20% threshold to
identify the cod fleet for the longline and pot vessels was
unnecessary. For the trawl fleet, however, more than
half the observed hauls had less than 10% cod, and
508
Fishery Bulletin 103(3)
63% had less than 20% cod. These trawl vessels were
targeting fish species other than Pacific cod, such as rock
sole, and caught some cod (as bycatch) in the process.
The distribution of hauls that had greater than 20%
cod (by 10% bins) was relatively flat, varying only from
4% to 7% between bins and having no clear threshold
or breakpoint. Use of a low threshold proportion of cod
(such as 20%) would likely include some hauls in which
Table 3
Catch and effort statistics for Pacific cod fisheries in the southeastern Bering sea by strata (Fig. 1) in January-April 2001.
Statistics include total catch estimates (in metric tons (t); all gear and fisheries), observed catch by all fisheries (by gear type),
and observed catch and effort by fisheries targeting Pacific cod (by gear type). Three levels of Pacific cod catches from trawl gear
are listed and are based on the minimum proportion of cod in each haul.
Strata
East of
sampling area
High sampling
effort
Low sampling
effort
South of
sampling area Total
Catch
Total catch
Observed catch — all fisheries
Trawl
Pot
Longline
Total
Observed catch — Pacific cod fisheries
Trawl (20% cod in each haul)
Trawl (40% cod in each haul)
Trawl (60% cod in each haul)
Pot
Longline
Effort
Trawl (hours; 20% cod in each haul)
Trawl (hours; 40% cod in each haul)
Traw] (hours; 60% cod in each haul)
Pot (number of pots)
Longline (no. of hooks)
7691
17,875
1,200
3724
30,491
1628
5737
324
32
7720
85
655
152
1198
2091
2493
2001
45
116
4654
4205
8393
521
1345
14,465
781
4993
4119
3364
7
32
5813
85
655
152
1198
2090
2493
2001
45
116
4654
677
4644
3768
2903
10
17
5348
1857
10,130
1119
14,816
27,922
220,051
3,265.606
88,880
165,585
7,740,122
Table 4
Frequency distribution of the percentage
of cod in
each haul by gear for the
groundfish fi
shery in
the four areas of the eastern
Bering Sea (Fig.
1) in January-Apri
2001
%cod
Trawl
Longline
Pot
No. of hauls
% of total
No. of hauls
% of total
No. of hauls
% of total
<10%
1810
52
0
0
0
0
10-20%
371
11
1
0
0
0
20-30%
237
7
2
0
1
0
30-40%
169
5
1
0
0
0
40-50%
126
4
5
1
0
0
50-60%
126
4
11
1
0
0
60-70%
151
4
40
5
2
1
70-80%
166
5
120
15
4
1
80-90%
181
5
334
42
37
11
90-100%
161
5
283
36
307
87
Total
3498
797
351
Fritz and Brown: Interactions between the Pacific cod fishery and Steller sea lions
509
other species were targeted. On the other hand, the use
of a high threshold (such as 60%) might exclude hauls
where Pacific cod was the target species. Therefore, a
range of trawl target definitions from 20% to 60% was
used. The cod trawl fleet distribution shown in Figure
4 was defined by the 20% threshold. If the 40% or 60%
thresholds are used, most of the cod trawl effort shown
in the HSE area remains, whereas some of the effort in
the eastern portions of the AE of the survey area is not
coded as the effort of a cod-target fishery.
Distribution of Pacific cod catch Cod catches accu-
mulated differently in the three primary areas fished
(Fig. 5). In the HSE area, cod catches rose steadily from
1 January through early April, and totaled approxi-
mately 13,000 t. There was a brief increase in the rate
of cod catch in mid-April, but by approximately 20 April,
the cod fishery in the HSE area had essentially finished
with a catch total of 17,875 t. In the AE of the survey
area, cod catches accumulated steadily from 1 Janu-
ary through 2 March, and totaled 6340 t. There was a
brief increase in catch rates for 6 days from 25 through
30 March, after which the cod fishery in the AE of the
survey area was finished with a catch total of 7691 1. In
the AS of the survey area, there was little cod fishing
effort prior to 22 February, and it lasted only through
27 March, by which time almost 3500 t had been caught;
catches through 30 April from the AS of the survey area
totaled 3724 t. There was very little cod fishery effort
in the LSE area (Table 3), and only 1200 t of cod were
caught (principally as bycatch in other fisheries) through
30 April 2001.
The longline fleet began fishing for Pacific cod in both
the HSE area and AE of the survey area on 1 January
(Fig. 5). In the HSE area, daily average longline CPUE
(t cod per 1000 hooks per day) remained relatively low
and steady, ranging from 0.3-0.7 through January. The
longline fleet left the HSE area for approximately two
weeks, resuming effort again on 13 February and con-
tinuing through 6 March. Longline CPUEs were gener-
ally higher in late February than they were in January,
ranging from approximately 0.7 to 1.2. The longline
fleet again returned to the HSE area on 19-24 March,
but daily average CPUEs were <0.5. There was sporadic
longline fishing for cod in the HSE area through April,
and CPUEs ranged from 0.3 to 1.0. In the AE of the
survey area, the longline fleet fished continuously from
1 January through 2 March, and daily average CPUE
declined from a range of 0.7-1.0 on 1-7 January to a
range of 0.3-0.5 on 24 February-2 March.
The trawl fishery for cod began on 20 January in both
the HSE area and AE of the survey area (Fig. 5). In the
HSE area, trawl CPUE (t cod per hour trawled per day)
increased from a range of 0.7-1.4 on 20-27 January to a
range of 1.3-2.5 on 6-15 February. From 16 February-
1 March, trawl CPUEs were slightly lower, ranging from
0.8 to 2.0, after which they declined further, ranging
only from 0.5 to 1.3 from 2-24 March. On 26 March,
the average CPUE increased substantially to over 12
but quickly declined to less than 1.0 by 1 April. This
was followed by another short-lived increase in CPUE
on 11 April, after which daily average CPUEs remained
below 1.0 through April. In the AE of the survey area,
CPUEs were highly variable (between 0.4 and 2.3) and
there was little observable trend between 20 January
and early March. On 25 March, however, average CPUE
increased to over 4 and ranged between 0.4 and 3.9
through 2 April, after which there was only sporadic
effort and daily average CPUEs were less than 1.
The pot fishery for cod began on 22 February south
of the survey area and on 24 February in the HSE area
(Fig. 5). In the AS of the survey, pot CPUE (t cod per
20 pots per day) decreased from a range of 0.3-1.0 from
22 February-1 March, to a range of 0.2-0.5 on 8-17
March. However, on 18 March, pot CPUE increased
to 1.1, and remained between 0.5 and 0.8 through 22
March, after which it quickly declined to very low lev-
els. In the HSE area, pot CPUE ranged between 0.7 and
1.7 from 24 February to 23 March. However, on 24-25
March, CPUE was greater than 2. Pot cod fishing oc-
curred on only three more days through the end of April
in the HSE area: on 27 March, 6 April, and 12 April.
Although daily average CPUEs on the last two days
were the highest recorded in the pot fishery in 2001,
observed catches on these days totaled only 4 and 5 t
of cod, respectively.
Leslie depletion analyses Leslie depletion analyses
were conducted on four sets of Pacific cod fishery data
collected in the HSE area and on two sets of data col-
lected in the AE of the survey area (Table 5). In the
HSE area, longline fishery data collected prior to 13
February and trawl fishery data collected prior to 6
February were excluded from the analyses because
CPUE data indicated that fish were immigrating
into the area in January in preparation for spawning
(Fig. 5). It is unlikely that the increase in CPUE was
due to a change in catchability because the increase
was evident whether bait was used (pots and longlines)
or not (trawls). Data indicating an increase in the
abundance of cod north of Unimak Island in January
and a peak in February were in agreement with a
generalized model of cod abundance in Steller sea lion
critical habitat in the eastern Bering Sea (Fig. 2) and
seasonal cod movements from tagging data (Shimada
and Kimura, 1994). The time series was truncated at
24 March because of the evidence within the fisheries
data (increase in CPUE) that another group of cod had
immigrated to the HSE area and AE of the survey
area in late March or that catchability had increased
substantially (Fig. 5). In addition, daily average CPUEs
from hauls that had at least 20%, 40%, and 60% Pacific
cod by weight were regressed against cumulative catch
to see what effect the target definition might have on
the regression results.
All Leslie regressions with longline or trawl fish-
ery data from the HSE area were highly significant
(P<0.000001; Table 5 and Fig. 6). Coefficients of de-
termination (r2) for the longline and the trawl-20%
data were both greater than 0.6. Regression coefficients
510
Fishery Bulletin 103(3)
A High sampling-effort area
1-Jan-01 16-Jan-01 31-Jan-01 15-Feb-01 2-Mar-01 17-Mar-01 1-Apr-01 16-Apr-01 1-May-01
1-Jan-01 16-Jan-01 31-Jan-01 15-Feb-01 2-Mar-01 17-Mar-01 1-Apr-01 16-Apr-01 1-May-01
' C South of survey area
35
0.0
1-Jan-01
x2KJ^5cJ^bfe.
4.000
3,500
3.000
2.500
2.000
1,500
1.000
500
16-Jan-01 31-Jan-01 15-Feb-01 2-Mar-01 17-Mar-01 1-Apr-01 16-Apr-01 1-May-01
Figure 5
Daily average catch per unit effort (CPUE on left y-axis) for the observed Pacific cod (Gadus
macrocephalus) fishery by gear (see legend for units) and area (Fig. 1) from 1 January-30 April
2001 in the southeastern Bering Sea. Estimated cumulative catch (t) of cod by all gear types
by area is also shown (right y-axis).
(slopes) in all cases were negative and significantly
different from zero. Collectively, these results strongly
indicate that cod fishery CPUE was negatively corre-
lated with cumulative catch. Initial biomass estimates
(B0) from the four regressions were similar and ranged
between 14,119 and 14,806 t, with 95% confidence in-
tervals ranging from approximately 9000 to 25,000 t.
Use of different fishery catch levels (20%, 40%, 60%
cod in each haul) had little effect on the initial biomass
estimate but changed the estimate of q, which increased
directly with the threshold proportion of cod in each
haul (Table 5 and Fig. 7).
Fritz and Brown: Interactions between the Pacific cod fishery and Steller sea lions
511
Table 5
Results of Leslie depletion analyses on cod trawl and longline fishery data collected in the (Ai high sampling-
effort (HSE) survey-
area and (B) east of the
survey area • Fig. 2). Dates
when data were collected
are listed, along with the regression parameters
(q = slope and y-intercept=
=QB„
and
statistics (P=probability that slope is not sig
nificant
y different from 0, r=
Pearson correlation
coefficient, and 95% con
idence interval (CI) on S„)
Fo
r the trawl fishery in the HSE
area, three different levels catch for the
target fishery were used
20',
. 40c
, or60% of the total
catch per haul was cod
I. Cumu
ative catches in each
area are defined as
the catch from 1 January through
he end of the per
iod
analyzed.
A High sampling-effort
survey area
Gear
Longline
Trawl 20%
Trawl 40%
Trawl 60%
13 Feb-24 Mar
6 Feb-24 Mar
6 Feb-24 Mar
6 Feb-24 Mar
Cumulative catch (t)
11,631
11,631
11,631
11,631
B0(t)
14,251
14,806
14.119
14,410
95%CIonB0(t)
9608-22,195
10,549-21,570
9526-21,942
8989-24,860
9
0.000115
0.000172
0.000207
0.000212
v-intercept
1.6395
2.5442
2.9246
3.0573
P
<0.000001
<0.000001
<0.000001
<0.000001
No. of days (n)
27
47
46
46
r2
0.712
0.635
0.577
0.479
B East of survey area
Gear
Longline
Trawl 20%
1 Jan-2 Mar
20 Jan-21 Mar
Cumulative catch (t)
6340
6837
B0(t)
14,671
95%CIonB0(t)
10,934-20,936
<?
0.000053
v-intercept
0.7707
P
<0.000001
0.65
No. of days (n)
61
49
r2
0.515
0.004
Although a portion of the AE of the sampling area is
also critical habitat, the majority of it is not. Cod are
thought to move from the areas east and south of the
survey area to aggregate within critical habitat, partic-
ularly north of Unimak Island, for spawning (Shimada
and Kimura, 1994; Thompson and Dorn, 2002). Leslie
analyses were conducted on longline data collected from
1 January to 2 March in the AE of the survey area, and
on trawl data collected from 20 January to 21 March.
The longline data yielded a highly significant nega-
tive relationship between CPUE and cumulative catch
(P<0.000001), whereas the trawl data did not <P=0.65;
Table 5 and Fig. 6).
Trawl fishery CPUE in the HSE area was not cor-
related with daily average vessel length for the pe-
riod 20 January-30 April 2001 (P=0.16; r2 = 0.02; Fig.
8). The data from the analysis period 6 February-24
March are highlighted in Figure 8. Although there
was a significant linear relationship between vessel
length and CPUE for this shorter period (P=0.004),
the correlation coefficient was low (r2 = 0.16), indicat-
ing that daily average CPUE and vessel length were
poorly correlated.
Discussion
The bottom trawl survey point estimate of cod biomass
in the HSE area (31,312 t) is approximately twice the
values derived from analyses of fishery data (approxi-
mately 14,500 t). This is in part because the fishery
worked almost exclusively within the eastern two-thirds
of the HSE area. Restratifying the HSE survey yields
biomass estimates of 23,329 t for the eastern two-thirds
used by the fishery and 7983 t for the western portion.
The fishery-derived biomass estimates for the eastern
portion of the HSE survey area are within the 957c con-
fidence bounds on the survey estimate (12,846-33,812 t).
512
Fishery Bulletin 103(3)
In addition, the survey biomass estimate for the eastern
two-thirds of the HSE area is within or close to the
upper 95% confidence bounds of the Leslie analyses of
trawl and longline Pacific cod fishery data (Table 5).
One possible explanation for the lower fishery-derived
estimates in the eastern portion of the HSE area is that
emigration of fish after spawning contributed to the low
CPUEs observed near the end of the fishery time series.
If this emigration occurred, however, it went largely
undetected in the neighboring areas. Emigration over
the course of the fishery would decrease CPUEs fast-
er than what would be attributable to fisheries alone,
which would, in turn, decrease the estimate of initial
biomass.
A
High
sampling-effort area
A
A
AA
. A A
\. **
A .
2.5 ■
2.0 -
A Trawl fishery data
Trawl regression
□ Longline fishery data
Longline regression
1.5 •
10 -
0 5 -
n n -
A^S^.
A
I
A A
^^ A
D
111
a.
o
5.000
10,000
2.5
2.0
1.5
1.0
0.5
0.0
B East of survey area
B East of
Survey Area
A
A
A A
D □
*F? A
-^
CD '
2.500 5.000
Cumulative cod catch (t)
Figure 6
Daily average catch per unit of effort (CPUE) of Pacific cod (Gadus
macrocephalus) by the observed Pacific cod fishery by gear type plot-
ted against the estimated cumulative catch of cod by the groundfish
fishery in the high sampling-effort area (A) and in the area east
of the survey area (B; Fig. 1). For the trawl fishery (at least 20%
of the haul catch was cod). CPUE = t/h; for the longline fishery,
CPUE = t/1000 hooks. Lines are shown for those regressions whose
slope was significantly different from 0 (P<0.05; Table 5).
Plots of fishery CPUEs of Pacific cod were very simi-
lar for all gears used in each area. This finding indi-
cates that these time series are useful as indices of
relative cod abundance. Similarly, inferences can be
made through analyses of fishery CPUE data regard-
ing fish movement from area to area (or lack thereof)
to a possible cause in the observed declines in CPUE
(or local abundance). For instance, the lack of fish-
ery CPUE increases in areas to the north, east, and
south of the HSE survey area in March indicates that
emigration was not a significant factor in the CPUE
decline observed in both the longline and trawl fishery
CPUE data from early February through 24 March. In
fact, in the AE of the survey area through 2 March,
longline CPUE declined, indicating that ei-
ther fish left this area (to the north) or were
reduced in abundance by fishing and were
not replenished. Although the time series
from the AS of the survey area is short,
there is no indication that cod moved there
in early March. There is also no evidence
that cod moved north to the LSE survey
area because the longline or pot fleets tar-
geting cod did not move there, nor did the
proportion of cod in trawl hauls increase
(otherwise they would have been labeled
as a cod-target fishery). It is possible that
cod emigrating from the HSE area were so
dispersed or their catchabilities were much
lower than those for residents in other ar-
eas that their presence went undetected,
but there is no evidence to suggest that ei-
ther of these were any more likely than the
more simple assumption that changes in
CPUE within the fished area represented
real changes in local abundance even after
accounting for some level of emigration. If
cod immigration exceeded emigration for the
HSE area during early March as CPUEs
were declining, then fishery-derived esti-
mates of initial biomass calculated in our
study are biased high.
Pot fishery CPUE data in the AS of the
sampling area and in the HSE area indicated
that there was an influx of Pacific cod from
the south in mid-March. This was evident
from the increase in pot fishery CPUE on
18 March in the AS of the survey area and
beginning on 24 March in the HSE area.
Cod may have moved into nearshore sections
of the HSE area where they would be more
vulnerable to pot gear than to trawlers. How-
ever, on 25-26 March, trawl CPUE on the
border of the HSE area and the AE of the
survey area increased substantially, indicat-
ing that these fish had moved offshore to
areas worked by trawlers, or that they be-
came highly aggregated (perhaps just prior to
spawning). The late-March "pulse" of Pacific
cod biomass was probably smaller than the
15,000
7,500
Fritz and Brown: Interactions between the Pacific cod fishery and Steller sea lions
513
3.5 -
* 20% dala
3.0 -
* x
a 40% data
2.5 -
LU
Am
— — 40% regression
x 60% data
lv 2.0 -
O
13 15-
o ' -J
O
1.0 -
0.5 -
^•*»C?.* Six
- - - - 60% regression
u T^X x ' ^* w
a «$ HSa^x
0.0 ' ' '
0 5,000 10,000 15,000
Cumulative cod catch (t)
Figure 7
Catch per unit of effort (CPUE; t/h) of Pacific cod {Gadus macrocepkalus)
by the cod trawl fishery in the high sampling-effort area plotted against
cumulative catch of cod in the same area by all groundfish fisheries. Three
different levels of the cod fishery catch are used (20%, 409c. or 60% cod
in each haul).
30 -I
2.5 -
in 20"
0.
O 1.5 -
TD
O
° 1.0-
0.5 -
♦ 20 Jan -30 Apr
D 6 Feb - 24 Mar
a
a » fea a
ffl . . . *@m * ®
.ra®B I / *>B b
♦ ♦ ♦ ♦
o.o -
6
Daily a\
(CPUE;
fishery ]
April 2C
0 80 100 120 140 160 180 200
Average vessel length (feet)
Figure 8
'erage Pacific cod {Gadus macroeephalus) catch per unit of effort
t/h) plotted against daily average vessel length for the trawl cod
n the high sampling-effort area in two time periods: 20 January-30
01, and 6 February-24 March 2001.
initial influx that peaked in early February because it
sustained the fishery for only 1-2 weeks, and resulted
in cod catches of only approximately 7500 t from all
four areas.
In the stock assessment for Pacific cod in the eastern
Bering Sea and Aleutian Islands (BSAI; Thompson and
Dorn, 2002), the estimate of age 3+ biomass in 2001
was approximately 1.284 million t, whereas the female
spawning biomass was approximately 359,000 t. Dou-
bling the latter to account for male spawner biomass,
the survey and fishery data discussed in the present
study indicate that only 4% of the adult spawning and
3% of the age 3+ biomass was in the HSE area, and
only about 1% and 4%, respectively, in the entire area
surveyed. The area north of Unimak Island is thought
to be one of the principal spawning grounds for Pacific
cod in the eastern Bering Sea (Shimada and Kimura,
1994; Thompson and Dorn, 2002). The results reported
in the present study may indicate that either 1) this is
not one of the principal spawning grounds for Pacific
cod in the eastern Bering Sea and most spawning oc-
curs elsewhere, 2) the stock assessment estimates are
too high, or 3) Pacific cod aggregated in the area after
the survey occurred.
Biomass estimates from the assessment are approxi-
mately twice those derived directly from bottom trawl
514
Fishery Bulletin 103(3)
lil
D.
U
i.u -
0.9 -
0.8 -
0.7 ■
0.6 ■
0.5 -
0.4 -
0.3 ■
n ? -
^""WCI . +-+
• +
' . +
. ++
>
en
No fishing model
© Fishing model
+ Longhne fishery index
• Trawl fishery index
■■■■%
•+
\
1/15/2001
1/29/2001
2/12/2001
2/26/2001
3/12/2001
3/26/2001
Figure 9
Comparison of relative abundance of Pacific cod (Gadus maerocephalus) in
portions of Steller sea lion lEumetopias jubatus) critical habitat from 15 Janu-
ary-24 March 2001 based on 1) no fishing model: the proportion of the maxi-
mum biomass (on 15 February) in critical habitat each day; 2) the fishing
model: subtracting catch per day from 15 January-24 March 2001 in high
and low sampling-effort areas from the no fishing model (total of 12,800 t); 3)
longline fishery catch-per-unit-of-effort (CPUE) index of abundance from the
high sampling-effort area, 13 February to 24 March (assigned a value of 1 on
13 February); and 4) trawl fishery (20% threshold) CPUE index of abundance
from the high sampling-effort area, 6 February to 24 March (assigned a value
of 1 on 6 February).
surveys of the entire Bering Sea shelf conducted in
summer (Thompson and Dorn, 2002). This difference
stems from highly domed-shaped selectivity-at-length
schedules for the summer surveys and most fishery
catches of cod (Thompson and Dorn, 2002). As a conse-
quence, the model "assumes" that fewer cod are caught
in proportion to their actual abundance at lengths
greater than 45 cm for the survey catch and 80 cm
for the fishery catch. However, it is unclear how large
cod avoid capture during surveys or by longline, pot,
and trawl fishery gear as implied by the dome-shaped
selectivity-at-length schedules.
A seasonal model of Pacific cod movement patterns
into and out of Steller sea lion critical habitat (Fig. 2)
indicates that relative Pacific cod biomass inside criti-
cal habitat is highest in February, then drops 13% in
March and 44% by April. If these values are assigned
to the middle of each month and daily values are ex-
trapolated linearly, the relative change from 15 Febru-
ary through 24 March is 23% (Fig. 9). Fishery indices
of abundance in the HSE area in January and Febru-
ary are consistent with this seasonal pattern, with
both trawl and longline CPUEs increasing from Janu-
ary to February. According to Figure 2 and the 2001
age 3+ biomass estimate (Thompson and Dorn, 2002),
catches through 24 March within the entire survey area
(12,806 t) represented only 1% of the BSAI stock and
should have reduced the relative biomass of cod within
critical habitat by only an additional 2%. Thus, the
total reduction in relative cod biomass within critical
habitat from mid-February through late March after
accounting for fishing and emigration should have been
25% (Fig. 9). Longline and trawl fishery CPUE data
in the HSE area provide an independent estimate of
relative cod biomass. Both indices indicate that the re-
duction in relative cod biomass within the HSE survey
area through 24 March was 71-46% greater than that
predicted by the model.
Catches and biomass estimates of Pacific cod for dif-
ferent time periods and areas can be used to compute
harvest indices (catch divided by observed biomass).
For instance, the harvest index within the entire sur-
vey area (based on the catch from 1 January through
24 March and the survey biomass estimate) was 26%
(12,806 or-=-49,032). If the focus is narrowed to only the
HSE survey area through 24 March, the harvest index
was 37% (11,631 or^-31,312). However, both the fish and
the fishery were concentrated within the HSE area. The
eastern two-thirds of the HSE survey area had survey
and fishery-derived biomass estimates of 23,418 t and
-14,500 t, respectively. With the area of fishery effort
more precisely defined, local harvest indices increase
even further, ranging from 50% (11,631 or-23,329) to
80% (11,631 or-r 14,500).
Fritz and Brown: Interactions between the Pacific cod fishery and Steller sea lions
515
The annual harvest rate of BSAI cod in 2001 was es-
timated to be approximately 11% (Thompson and Dorn,
2002). The total catch of cod in the BSAI through 24
March represented only 44% of the total catch of Pa-
cific cod in 2001. Therefore, the harvest rate through
24 March should only have been 44% of 11%, or about
5%. The local harvest indices estimated in the present
study, which ranged from 26% to 80%, were five to 16
times greater than that on the BSAI Pacific cod stock
as a whole in 2001. Much of the area used by the fish-
ery is designated as critical habitat for the endangered
Steller sea lion, primarily because of the prey resources
available within it. In addition, the fisheries occurred
in the winter and early spring, when sea lions are most
likely to consume Pacific cod (Sinclair and Zeppelin,
2002). It is not known how or if cod fishery catches
in this area affect Steller sea lion foraging success.
One objective of the Pacific cod fishery management
regulations is to minimize the competitive interactions
between locally intense fisheries and Steller sea lions.
The suite of groundfish fishery regulations enacted in
2001 and 2002 work together to avoid adverse modifica-
tion of critical habitat under the ESA. However, based
on the observations during 2001 discussed in the pres-
ent study, regulations for the eastern Bering Sea Pacific
cod fishery should be reviewed to ensure that they meet
these management objectives.
Acknowledgments
We thank D. DeMaster, G. Duker, B. Fadely, J. Lee, T
Loughlin, S. Lowe, S. Moore, and especially M. Sigler for
their reviews of early versions of the manuscript. We also
give heartfelt thanks to the captains and crews of the
FV Northwest Explorer and FV Ocean Harvester, AFSC
personnel (E. Acuna, T Buckley, W. Floering, L. Haaga,
R. Harrison, E. Jorgensen, G. Lang, D. Nebanzahl, D.
Nichol, and K. Smith) who conducted the bottom trawl
survey in February-March 2001, and the numerous
fishery observers working onboard commercial vessels
at that time.
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516
Abstract— Molecular-based approach-
es for shark species identification have
been driven largely by issues specific
to the fishery. In an effort to estab-
lish a more comprehensive identifica-
tion data set, we investigated DNA
sequence variation of a 1.4-kb region
from the mitochondrial genome cover-
ing partial sequences from the 12S
rDNA. 16S rDNA, and the complete
valine tRNA from 35 shark species
from the Atlantic fishery. Generally,
within-species variability was low in
relation to interspecific divergence
because species haloptypes formed
monophyletic groups. Phylogenetic
analyses resolved ordinal relation-
ships among Carcharhiniformes and
Lamniformes, and revealed support
for the families Sphyrnidae and Tri-
akidae (within Carcharhiniformes)
and Lamnidae and Alopidae (within
Lamniformes). The combination of
limited intraspecific variability and
sufficient between-species divergence
indicates that this locus is suitable
for species identification.
Mitochondrial gene sequences useful for species
identification of western North Atlantic Ocean sharks
Thomas W. Greig
M. Katherine Moore
Cheryl M. Woodley
National Ocean Service
National Center for Coastal Ocean Science
Center for Coastal Environmental Health and Biomolecular Research at Charleston
219 Fort Johnson Road
Charleston, South Carolina 29412-9110
E-mail address (for T W. Greig) Thomas Greig (ginoaa gov
Joseph M. Quattro
Department of Biological Sciences
School of the Environment
University of South Carolina
Columbia, South Carolina 29208
Manuscript submitted 22 June 2004
to the Scientific Editor's Office.
Manuscript approved for publication
28 March 2005 by the Scientific Editor.
Fish. Bull. 103:516-523 (2005).
Seventy-three species of sharks inhabit
the United States territorial waters
of the Atlantic Ocean, Gulf of Mexico,
and Caribbean Sea (Compagno,
1984a, 1984b). All but one (spiny
dogfish, Squalus acanthias, managed
separately) are managed under the
current Fisheries Management Plan
(FMP) for highly migratory species
(NMFS1). Thirty-three species are of
lesser commercial importance and are
relegated to the "deepwater and other"
species management group, and 19
species cannot be landed commercially
or recreationally ("prohibited species"
group). The remaining 20 species are
of interest to the commercial shark
fishery and are categorized as large
coastal species (LCS), small coastal
species (SCS), and pelagic species
management units in the current
FMP. Although these management
units are practical, it is clear that
species respond uniquely to exploita-
tion and therefore should be managed
on a species-by-species basis (Castro
et al., 1999; NMFS2). Species-level
management is widely recommended
(e.g., FAO Marine Resource Service,
2000) but is complicated by the pau-
city of species-specific fisheries data,
stemming, in part, from an inability
to accurately identify species.
Many commercially important spe-
cies (e.g., within Carcharhiniformes)
are difficult to identify whole, and
this task is more daunting if indi-
viduals are processed (head, entrails,
and fins are removed); unfortunately,
at-sea processing is widespread in the
industry (Castro3). Although current
U.S. legislation prohibits the practice
of "finning" (where fins are retained
and carcasses are discarded at sea).
1 NMFS (National Marine Fisheries Ser-
vice). 2003. Final amendment 1 to the
fishery management plan for Atlantic
tunas, swordfish and sharks, 599 p. Of-
fice of Sustainable Fisheries, Highly
Migratory Species Management Division,
NMFS, NOAA, 1315 East West Highway,
SSMC3, Silver Spring, MD 20910.
2 NMFS (National Marine Fisheries Ser-
vice). 2001. Final United States na-
tional plan of action for the conservation
and management for sharks, 90 p. Of-
fice of Sustainable Fisheries, Highly
Migratory Species Management Division,
NMFS, NOAA, 1315 East West Highway,
SSMC3, Silver Spring, MD 20910.
3 Castro, J. I 1993. A field guide to
the sharks commonly caught in com-
mercial fisheries of the southeastern
United States. NOAA Tech. Memo.
NMFS-SEFSC-338, 47 p. Southeast
Fisheries Science Center, NMFS, NOAA,
75 Virginia Beach Dr., Miami, FL
33149.
Greig et al.: Gene sequences useful for identification of western North Atlantic shark species
517
the landing of fins is allowed where carcasses and fins
are off-loaded at the same time in a no more than 1:20
(fin-to-carcass) weight ratio. However, serious problems
can arise in matching off-loaded fins to processed car-
casses. In and of itself, the landing of shark fins can
be lucrative; fins accounted for more than 50% of the
total Atlantic shark fishery value in 2002 (NMFS4).
Because preferences exist for fins from certain species,
exvessel prices for specific types of fin vary consider-
ably (e.g., Weber and Fordham, 1997). It is perhaps not
surprising that augmenting the fin-to-carcass ratio with
spoiled meat or "finning" target species out of season
(and subsequently attributing the fins to fish that are
allowed to be caught during the season) might not be
uncommon (Vannuccini, 1999). Clearly, these possibili-
ties lead to the challenge of matching collected fins to
processed carcasses. Therefore, accurate and reliable
species identification methods are paramount for law
enforcement and sound species management.
Molecular species identification research on sharks
has been driven largely by resolution of specific prob-
lems associated with the fishery. For example, Heist
and Gold (1999) used mtDNA sequence data to develop
restriction fragment assays that differentiate 11 species
of carcharhiniform sharks commonly encountered in the
LCS fishery. Similarly, Pank et al. (2001) used multiplex
PCR to differentiate two morphologically similar shark
species (Carcharhinus obscurus and C. plumbeus) — an
approach that was expanded by Shivji et al. (2001) to
include five additional species (with some overlap of
species included by Heist and Gold 1999). Both ap-
proaches are relatively rapid, inexpensive, and easily
implemented; however, they appear most applicable
when the number of species investigated is limited. In
sum, of the thirty-nine species of sharks that are not in
the "deepwater and other" management group, molecu-
lar species identification assays have been developed for
fifteen species (9 LCS, 3 pelagic, and 3 in the prohibited
species management groups) (Heist and Gold, 1999;
Pank et al., 2001; Shivji et al., 2001), leaving 24 species
without molecular methods for identification.
Some investigators have instead turned to DNA se-
quence analysis to resolve issues of species identification
(Takeyama et al., 2001; Akimoto et al., 2002; Jerome
et al., 2003). This approach is exemplified best by the
recent development of computer interfaces that allow
access to and analysis of large DNA databases (DNA
Surveillance, Ross et al., 2003; ARB, Ludwig et al.,
2004). Simply put, these databases circumvent the te-
dious process of scanning large taxonomically diverse
DNA repositories (e.g., GenBank) by allowing the user
to access (DNA Surveillance) or maintain (ARB) taxo-
nomically restricted sets of reference sequences. Users
4 NMFS (National Marine Fisheries Service). 2003. Stock
assessment and fishery evaluation report for Atlantic highly
migratory species (SAFE), 274 p. Office of Sustainable
Fisheries, Highly Migratory Species Management Division,
NMFS, NOAA, 1315 East'West Highway, SSMC3. Silver
Spring, MD 20910.
can submit "unknown" sequences to compare against
specified sequence subsets; subsequent analyses are
returned as genetic distances (between unknown and
reference sequences) and include a phylogenetic hy-
pothesis.
The power of this approach lies in the ease with
which reference sequences can be added to the data-
base, in the "quality-control" that can be exerted over
subsequent additions to the reference sequences, and in
the ease with which geographic variation within species
can be included. The success of this approach, however,
hinges on the information contained in the gene in the
reference database. The inception of this approach, as
applied to commercially important sharks, requires
a sufficiently informative set of reference sequences
against which searches can be made. The aforemen-
tioned molecular approaches (RFLP, multiplex PCR)
include a diversity of gene regions (mitochondrial DNA,
nuclear ITS); thus no comprehensive data set exists
for commercially landed Atlantic shark species. Fortu-
nately, recent work with a 2.4-kb fragment of the mi-
tochondrial genome (spanning 12S rDNA to 16s rDNA)
to examine the phylogenetic relationships among shark
orders has shown that this region may be useful in re-
solving relationships at this taxonomic level (Douady et
al., 2003). Unfortunately, sampling within orders was
limited, and it is thus unknown whether this region
contains sufficient phylogenetic signal at lower taxo-
nomic levels.
We present here mtDNA sequence data of a smaller
fragment of the same region containing partial se-
quence information for the mitochondrial 12S rDNA,
16S rDNA, and the complete valine tRNA from 35 shark
species (including all 20 commercially exploited species,
12 of 19 prohibited species, the spiny dogfish, and two
species of Mustelus). We suggest that a suitable locus
for species-identification purposes will permit identifica-
tion of unequivocally distinct species (i.e., large genetic
differentiation between species compared to within spe-
cies) and offer the potential for meaningful phylogenetic
comparisons (important when "query" animals are ab-
sent or not adequately represented in a molecular data-
base). Keeping in mind issues of species identification
and fisheries management, we examine this mtDNA
region for patterns of genetic variability and assess its
utility in phylogenetic reconstruction. We then discuss
the use of this region for the underpinnings of a vali-
dated reference DNA database suitable for forensic and
fisheries management applications.
Methods
Sample collection
Voucher Atlantic Ocean shark samples (muscle, fin, or
blood) were obtained from the CCEHBR Marine Foren-
sics archive in Charleston, SC (Table 1). Samples were
accompanied by species certification and chain-of-cus-
tody forms. Muscle and fin samples were either frozen at
518
Fishery Bulletin 103(3)
Table 1
Scientific and common names of samples, number of individuals sampled (n), species codes, and Genbank accession numbers.
Taxonomy follows Campagno (1984. 2001). Species codes correspond to a representative individual in the National Ocean Service
Marine Forensics Program (CCEHBR. Charleston, SO tissue archive with that particular haplotype (except for Heterodontus
franeisei Hfral).
Order
Family and species
Common name
Code ( ;i)
Accession
Carcharhiniformes
Lamniformes
Carcharhinidae
Carcharhinus acronotus
Blacknose
Cacr003(3)
AY830721
C. altimus
Bignose
Calt001(2)
AY830722
C. brevipinna
Spinner
Cbre001(3)
AY830723
C. falciformis
Silky
Cfal003(l)
AY830725
Cfal006(l)
AY830726
C. isodon
Finetooth
Ciso004(l)
AY830727
CisoOlO(l)
AY830728
Ciso015(l)
AY830729
C. leucas
Bull
Cleu003(3)
AY830730
C. limbatus
Blacktip
Clim004(l)
AY830731
Clim006(2)
AY830732
C. longimanus
Oceanic whitetip
ClonOOO(l)
AY830736
Clon002(l)
AY830733
Clon005(l)
AY830734
Clon006(l)
AY830735
C. obscurus
Dusky
CobsOOO(l)
AY830737
Cobs001(3)
AY830738
C. perezi
Caribbean reef
Cper001(2)
AY830739
Cper002(2)
AY830740
C. porosus
Smalltail
CporOOKl)
AY830743
C. plumbeus
Sandbar
Cplu004(2)
AY830741
Cplu023(l)
AY830742
C. signatus
Night
Csig002(l)
AY830744
Galeocerdo cuvier
Tiger
Gcuv003(3)
AY830746
Negaprion brevirostris
Lemon
Nbre005(l)
AY830756
Prionace glauca
Blue
Pgla004(l)
AY830760
Pgla0020(l)
AY830761
Pgla0022(l)
AY830762
Rhizoprionodon terraenovae
Sharpnose
Rter001(2)
AY830763
Rter026(ll
AY830764
Sphyrnidae
Sphyrna lewini
Scalloped hammerhead
Slew003(2)
AY830768
S. mokarran
Great hammerhead
Smok003(3)
AY830769
S. tiburo
Bonnethead
Stib016(2)
AY830770
Stib018(l)
AY830771
S. zygaena
Smooth hammerhead
Szyg681(6)
AY830772
Triakidae
Mustelus eanis
Smooth dogfish
Mcan003(3)
AY830754
M. norrisi
Florida smoothhound
Mnor001(2)
AY830755
Alopiidae
Alopias superciliosus
Bigeye thresher
AsupOOKll
AY830718
Asup006(l)
AY830719
A. vulpinus
Thresher
Avul002(l)
AY830720
Lamnidae
Careharodon carcharias
White
Ccar002(3)
AY830724
Isurus oxyrinchus
Shortfin mako
Ioxy005(l)
AY830747
Ioxy032(l)
AY830748
Ioxy051(l)
AY830749
I. paucus
Longfin mako
Ipau002(2)
AY830750
lpau005(l)
AY830751
Lamna nasus
Porbeagle
Lnas001(2)
AY830752
Lnas003(l)
AY830753
continued
Greig et al.: Gene sequences useful for identification of western North Atlantic shark species
519
Table 1 (continued)
Order
Family and species
Common name
Code i n I
Accession
Odontaspididae
Carcharius taunts
Sand tiger
Otau004(ll
Otau005(l)
Otau007(l)
AY830757
AY830758
AY830759
Orectolobiformes
Ginglymostomatidae
Ginglymostoma cirratum
Nurse
Gcir001(2)
AY830745
Hexanchiformes
Hexanchidae
Hexanchus vitulus
Bigeye sixgill
Hvitlll)
AY830716
Heptranchias perlo
Sevengill
Hperl(l)
AY830715
Squaliformes
Squalidae
Squalus acanthias
Spiny dogfish
Saca002(l)
Saca003(2)
AY830765
AY830766
Squatiniformes
Squatinidae
Squatina dumeril
Atlantic angel
Sdum001(3)
AY830767
Heterodontiformes
Heterodontidae
Heterodon tus fra n cisci
Horn shark
Hfra(l)
NC003137
-80°C, dried, or stored in 70% EtOH. Blood was stored at
room temperature in sodium dodecyl sulfate-urea (SDS-
urea: 1% SDS, 8M urea, 240 mM Na2HP04, ImM EDTA
pH 6.8). Total nucleic acids were extracted from frozen,
dried, and EtOH-preserved samples by using DNeasy
Tissue Kits and following manufacturer's recommenda-
tions (Qiagen, Valencia, CA). DNA was isolated from
blood in SDS-urea according to White and Densmore
(1992; protocol 11). Extracted DNA was visualized by
electrophoresis in a 1% agarose gel stained with 0.4
ng/mL of ethidium bromide in lx Tris-borate-EDTA
(TBE: 89 mM Tris-borate, 2 mM Na2EDTA, pH 8). A
1-kb DNA ladder (Promega, Madison. WD was used as
a size standard.
Amplification and sequencing
Primers 12SA-5' and 16SA-3' (Palumbi, 1996) were used
to amplify an approximately 1400-bp region spanning
the 3' end of the 12s rDNA, the valine tRNA, and the
5' end of the 16s rDNA region of mitochondrial DNA
(mtDNA). Samples were amplified in 50 uL reactions
containing -50 ng of template DNA, 20 mM Tris-HCl
pH 8.4, 50 mM KC1, 0.2 mM each dNTP, 2 mM MgCl2,
20 mM each primer, and 2.5 units Taq DNA polymerase
(Gibco BRL, Rockville, MD). Thermal cycling consisted of
an initial denaturation at 94°C for 1.5 minutes, followed
by 30 cycles of 40 seconds at 94°C, 40 seconds at 52°C,
and 50 seconds at 72°C, and a final extension step of 15
minutes at 72°C. Negative controls (no template) were
included in each set of reactions. PCR products were
gel-purified as described in Rosel and Block (1996) and
20-50 ng were used as template for ABI Big Dye Ter-
minator (v. 1.0, Applied Biosystems, Foster City, CA)
cycle sequencing reactions. Sequence was obtained with
amplification primers 12SA-5', 16SA-3' and two addi-
tional internal sequencing primers. Sequencing reaction
products were precipitated with ethanol, washed accord-
ing to sequencing kit instructions, dried in a Savant
Speedvac Plus, and resuspended in 4 j<L of loading dye
(5:1 Hi-Di formamide:dextran blue). Fragments were
analyzed on an Applied Biosystems 377 automated DNA
sequencer.
Sequence analysis and alignment
Sequences were edited with SEQUENCHER (vers. 3.0;
Gene Codes Corp., Detroit, MI). We included three
additional sequences from GenBank: horn shark
(Heterodontus francisci, NC003137) to represent the
family Heterodontidae, thorny skate (Raja radiata,
AF106038), rabbit fish (Chimaera monstrosa, AJ310140),
and the Atlantic guitarfish {Rhhiobatis lentiginosus,
AY830717 — this study) to serve as outgroups for phy-
logenetic analyses. Sequences were aligned by using a
linear hidden Markov model (HMM) as implemented
in SAM (Sequence Alignment and Modeling System;
Hughey and Krogh, 1996; Karplus et al., 1998) with
default settings. The alignment file is available from
the senior author.
Phylogenetic hypotheses were constructed by using
the maximum parsimony (MP) and neighbor-joining
(NJ) algorithms implemented in PAUP 4.0bl0 (Sinauer
Associates, Sunderland, MA). NJ analyses employed a
variety of pairwise distance measures, but the distance
measure used had little or no effect on the recovered
topologies. Phylogenies recovered with MP with equally
weighted characters were generally concordant with
those recovered by NJ, particularly when bootstrap
consensus trees were compared. For ease of interpre-
tation, we report NJ analyses using p-distances as a
metric. Bootstrapping (Felsenstein, 1985) was used to
estimate the reliability of NJ reconstructions (1000
pseudoreplicates).
520
Fishery Bulletin 103(3)
Results
Sequence variation and divergence
An approximately 1.4-kb gene region was amplified
and sequenced from 93 samples representing 35 shark
species. Fifty-seven of the 93 individuals had unique
haplotypes (Table 1, Fig. 1). An alignment of these hap-
lotypes with several outgroups with the SAM algorithm
resulted in a 1510 position consensus alignment after the
introduction of gaps. Of these 1510 aligned positions, 717
positions were variable and 543 were parsimony informa-
tive. Transition outweighed transversion substitutions
by a factor of 4.27. Considering only phylogenetically
informative sites within the ingroup, we found that
nucleotide composition did not differ significantly among
haplotypes (A: 35.9%, C: 21.9%, G: 16.9%, T: 25.3%;
X2=175.6, P=0.39).
Phylogenetic analysis
Unweighted parsimony analysis produced 24 equally
parsimonious trees of length 2733 (CI=0.39, RI=0.74)
that differed primarily in the relationships among haplo-
types within species (not shown). Neighbor-joining anal-
yses produced nearly identical topologies regardless of
the distance metric used. When differences were noted,
they often involved trivial placements of individual vari-
ants within species or the placement of branches that
were poorly supported by bootstrap analyses regard-
less of the reconstruction method employed. For this
reason, we present phylogenetic hypotheses generated
by neighbor-joining, using p-distances as a surrogate
for all analyses.
Most clades containing multiple haplotypes within
species were highly supported by bootstrap analyses. Of
16 species represented by more than a single sequence,
15 were recovered as monophyletic groups in 100% of
1000 bootstrap replicates (Fig. 1). Sequence divergence
within species was generally trivial compared to among-
species divergences. For example, sequence divergence
among haplotypes within species of Carcharhinus dif-
fered by approximately two orders of magnitude from
that among species within the genus (average p-dis-
tance of 0.05% and 4.16%, respectively). The exception
involved haplotypes observed within C. plumbeus that
were supported as monophyletic by fewer than 70%
of 1000 bootstrap replicates in MP and NJ analyses.
Interestingly, a sister group relationship between C.
plumbeus and C. altimus was highly supported by boot-
strapping, and average sequence divergence within spe-
cies (0.14%) was only about one-third of that observed
between these two (0.43%).
Some higher order relationships were recovered with
high bootstrap support. Notably the Carcharhiniformes
were strongly supported as monophyletic, as were the
families Sphyrnidae and Triakidae. The family Car-
charhinidae was poorly supported as monophyletic, al-
though a group that included Negaprion, Prionace, and
all Carcharhinus was observed in a large number of
bootstrap replicates. Carcharhinus was paraphyletic in
the NJ topology, and Negaprion was nested within the
genus, but this relationship received little support from
bootstrapping. The Lamniformes were monophyletic
and strongly supported by bootstrapping. Within this
order, only the family Lamnidae received strong sup-
port, whereas support for a monophyletic Alopidae was
moderate. The order Hexanchiformes was recovered as
a monophyletic group; however bootstrap support for
this grouping was low.
Discussion
Our goal was to assess whether the 12s-16s region of
the shark mitochondrial genome contained sufficient
genetic variation and phylogenetic signal to be useful
in species identification. Of the 35 species examined,
6 species were each represented by a single individual,
and 16 of the remaining 29 species contained variants
at the mtDNA locus examined. Importantly, all within-
species variants formed strongly supported monophyletic
groups concordant with morphologically based species
descriptions. Intraspecific variability was low in rela-
tion to interspecific divergence at this locus and in no
instance was a paraphyletic relationship between spe-
cies observed. The combination of limited intraspecific
variability combined with sufficient between-species
divergence indicates that this locus is suitable for spe-
cies identification.
Two exceptions to this generalization of low within
versus large between-species differentiation exist in our
phylogenetic hypothesis — one involving the sister spe-
cies pair C. plumbeus and C. altimus. In an alignment
of mitochondrial sequences from these species, only 5
or 7 transition substitutions were observed across ap-
proximately 1.4 kb of sequence data. Interestingly, Heist
and Gold (1999) included these two taxa in their cyto-
chrome^ RFLP analysis, and again, Atlantic samples
of C. plumbeus and C. altimus differed by only a single
transition in 395 basepairs (0.25%), and there were
more substitutions observed between Atlantic and Pa-
cific C. plumbeus than between Atlantic samples of C.
plumbeus and C. altimus (Table 2 in Heist and Gold
1999). The next most closely related pair of taxa in
our phylogenetic hypothesis comprised two other Car-
charhiniforms. C. longimanus and C. obscurus, a taxon
pair differing by approximately 1.44% sequence diver-
gence, compared with an average of 0.06% within taxon
diversity. These two taxa were considered by Shivji et
al. (2001) while developing a multiplex PCR assay for
six commercially important pelagic species. Specifically,
assays developed to diagnose C. obscurus could not
discriminate between C. obscurus and C. longimanus,
two closely related species in our phylogenies. The C.
plumbeus and C. altimus species pair was not consid-
ered by Shivji et al. (2001); thus no comparison to the
Heist and Gold (1999) cytochrome-6 sequence/RFLP or
the 12s-16s data set presented in our study was pos-
sible. We are currently analyzing additional samples,
Greig et al.: Gene sequences useful for identification of western North Atlantic shark species
521
100
73
97
99
100
Hperl (1)
_ Hvitl (1)
73
100
83
100
Saca002(1)
Saca003 (2)
SdumOOl (3)
Hfran (1)
100 Asup001 (1)
I Asup006(1)
Avul002(1)
Ccar002 (3)
100
100
79
LnasOOl (2)
Lnas003(1)
j- Ioxy005(1)
[L Ioxy051 (1)
100
Ioxy032(1)
-r
100
Otau004 (1)
Otau007 (1)
Otau005 (1)
Ipau002 (2)
Ipau005(1)
100
98
100
100
100
Cacr003 (3)
Ciso004(1)
Ciso010(1)
Ciso015(1)
CbreOOl (3)
Cleu003(3)
- CporOOl (1)
100 r- CaltOOl (2)
Cplu004 (2)
Cplu023(1)
— Nbre005(1)
■Q
-i
100
Cfal003(1)
Cfal006(1)
88
100
97
93
100
100
100
C
99
100
83r
. Clim004(1)
1 Clim006 (2)
Clon002(1)
Clon005 (1)
ClonOOO(1)
Clon006(1)
CobsOOO(1)
"I CobsOOl (3)
100 , CperOOl (2)
~^ Cper002 (2)
— Csig002(1)
r Pgla004(1)
_rl Pgla022(1)
L Pgla020(1)
RterOOl (2)
Rter026(1)
— Gcuv003(3)
Slew003(2)
100 Stib016(2)
I Stib018(1)
Smok003 (3)
100
Mcan003 (3)
MnorOO! (2)
Szyg681 (6)
GcirOOl (2)
0.01 substitutions/site
Figure 1
Neighbor-joining tree showing relationship of observed 12s-16s haplotypes among 36 species of shark. Codes are defined
in Table 1 and numbers in parentheses indicate the number of individuals found with the indicated haplotype. Bootstrap
support is indicated as numbers immediately above the relevant node (only values greater than 70% are shown). The
phylogeny was rooted with several outgroup taxa (Heterodontus francisci (NC003137), Raja radiala (AF106038), Chunaera
monstrosa (AJ310140), and Rhinobatis lentiginosus (AY830717)).
522
Fishery Bulletin 103(3)
including a more comprehensive geographical survey
of these four species to confirm that the genetic differ-
ences observed are diagnostic. However, it is clear that
DNA sequence-based approaches appear more powerful
in discriminating closely related species pairs and less
likely to produce false positives than other DNA-based
assays.
Although it was not our intent to conduct an ex-
haustive analysis of higher-order relationships among
western North Atlantic shark species, some interesting
results nonetheless deserve mention. First, the orders
Carcharhiniformes and Lamniformes were strongly
supported as monophyletic, as were the families Sphy-
rnidae, Triakidae, and Lamnidae that were included
in the study. The order Hexanchiformes was likewise
monophyletic, but bootstrap support for this grouping
was low. The family Carcharhinidae was poorly sup-
ported as monophyletic, which is consistent with previ-
ous studies (Nalyor, 1992; Nelson, 1994; Musick et al.,
2004). Interestingly, our phylogenetic hypotheses place
the family Triakidae basal to all other families within
the Carcharhiniformes, following Compagno (1988),
but this position was not strongly supported and is
predicated on limited sampling of Carcharhiniform
familes (only four of eight were included in our analy-
sis). Clearly this gene region contains some phylogenet-
ically useful information regarding shark relationships,
confined principally to higher-level groupings.
We are careful in judging the utility of a locus for
species identification on the basis of phylogenetic sig-
nal alone. Clearly, rapidly evolving molecular mark-
ers are valuable tools for species identification but
might not be appropriate for reconstructing phylo-
genetic relationships at certain scales. Conversely,
those regions containing sufficient signal to generate
reasonable phylogenetic reconstructions (i.e., general
concordance with accepted phylogenetic relationships
based on other independent characters) must be useful
(and appropriate) markers for species identification.
Further, these regions are amenable to the addition
of uncharacterized species and the inclusion of in-
traspecific diversity (e.g., diverged mtDNA lineages
within species). Importantly, however, DNA sequence-
based approaches offer the potential to assign at least
some level of taxonomic characterization to unknown
or unrepresented samples. Although the use of DNA
sequencing has historically been viewed as cost pro-
hibitive, the genomic revolution over recent years has
spawned cost-effective sequencing services, making
routine sequencing of samples for species identification
not only practical but optimal.
The size of the amplification product in the present
study might place limitations on the application of this
method to the poor-quality tissue and DNA often en-
countered in forensic studies. It has been our experience
that the primers used in our study consistently have
generated strong amplification products with DNA iso-
lated from a variety of tissue types, including dried tis-
sue and fins; however, we have yet to explore the range
of amplifications possible using tissues more commonly
encountered in forensic cases. To circumvent potential
problems with large amplifications on degraded DNA
samples, we have constructed a preliminary, search-
able DNA-sequence database using the FASTA program
(Univ. Virginia, Charlottesville, VA; Pearson, 1999)
and the 12s-16s sequences presented in the present
study. Our preliminary analyses indicate that all spe-
cies examined in the study can be uniquely identified
from approximately 400 bp of sequence generated by
the 12SA-5' primer. We are examining the limitations
of sequence length in combination with the search ac-
curacy of this informative fragment.
We are mindful of the restriction placed on these
analyses due to limited within-taxon sampling (par-
ticularly within-family) and of the incomplete represen-
tation (notably the Pristophoriformes) of all orders of
sharks and are aware that the phylogenetic affinities
presented in this study could change with the addition
of characters and taxa. These caveats notwithstand-
ing, we believe that a taxonomically restricted DNA
sequence database offers certain advantages over per-
haps more rapid RFLP or multiplex PCR assays. DNA
databases 1) can be "curated" (additions and access to
the database can be selective) and distributed as an
alignment suitable for further subsequent statistical
or phylogenetic manipulation; 2) can be easily amended
to include additional taxa, genetic variation within
species, and additional gene loci more appropriate at
various taxonomic scales; 3) allow for unequivocal as-
signment (subject to limits of discrimination of those
loci included) of species identification while making
available the raw data necessary for the development
of more rapid assays (RFLP/Multiplex PCR) for select
taxa (note that the opposite is not necessarily true);
and, 4) facilitate the identification of those taxa not
currently represented in the database through phylo-
genetic analysis.
In summary, we have found that the sequence of
the 12S-16S region of the mtDNA that we examined
contains ample information for discriminating between
the shark species studied and shows promise for the
placement of species not yet examined within the cor-
rect phylogenetic group (family). We are continuing
to examine geographic variation within and among
species and to assay genetic variability at nuclear loci
in an effort to resolve potential introgression and (or)
hybridization events. As information is added to our
database, either in the form of additional species or
loci, our species identification method will become more
robust.
Acknowledgments
Much of this work derived directly from forensic case
work conducted by Ann Colbert for the National Marine
Fisheries Service. Robert Chapman provided primer
sets and guidance. Laura Webster conducted initial sur-
veys of shark mtDNA variability and assisted in sample
acquisition. Shannon Leonard and David Carter assisted
Greig et al.: Gene sequences useful for identification of western North Atlantic shark species
523
in DNA sequencing. The authors thank Trey Knott,
Ron Lundstrum, Laura Webster and two anonymous
reviewers for their critical review of this manuscript.
This project was funded partially by grants from the
Cooperative Institute for Fisheries Molecular Biology
(FISHTEC; NOAA/NMFS (RT/F-D) and SC SeaGrant
(R/MT-5) to JMQ.
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524
Abstract— Rougheye rockfish (Sebas-
tes aleutianus) and shortraker rock-
fish [Sebastes borealis) were collected
from the Washington coast, the Gulf
of Alaska, the southern Bering Sea,
and the eastern Kamchatka coast of
Russia (areas encompassing most of
their geographic distribution) for pop-
ulation genetic analyses. Using starch
gel electrophoresis, we analyzed 1027
rougheye rockfish and 615 shortraker
rockfish for variation at 29 protein-
coding loci. No genetic heterogeneity
was found among shortraker rock-
fish throughout the sampled regions,
although shortraker in the Aleutian
Islands region, captured at deeper
depths, were found to be significantly
smaller in size than the shortraker
caught in shallower waters from
Southeast Alaska. Genetic analysis
of the rougheye rockfish revealed
two evolutionary lineages that exist
in sympatry with little or no gene
flow between them. When analyzed
as two distinct species, neither lin-
eage exhibited heterogeneity among
regions. Sebastes aleutianus seems to
inhabit waters throughout the Gulf
of Alaska and more southern waters,
whereas S. sp. cf. aleutianus inhab-
its waters throughout the Gulf of
Alaska, Aleutian Islands, and Asia.
The distribution of the two rougheye
rockfish lineages may be related to
depth where they are sympatric. The
paler color morph, S. aleutianus, is
found more abundantly in shallower
waters and the darker color morph,
Sebastes sp. cf. aleutianus, inhabits
deeper waters. Sebastes sp. cf. aleu-
tianus, also exhibited a significantly
higher prevalence of two parasites,
N. robusta and T. trituba, than did
Sebastes aleutianus, in the 2001
samples, indicating a possible dif-
ference in habitat and (or) resource
use between the two lineages.
Genetic variation of rougheye rockfish
(Sebastes aleutianus) and shortraker rockfish
(5. borealis) inferred from allozymes
Sharon L. Hawkins
Jonathan Heifetz
Christine M. Kondzela
John E. Pohl
Richard L. Wilmot
Auke Bay Laboratory
Alaska Fisheries Science Center
National Marine Fisheries Service
11305 Glacier Highway
Juneau, Alaska, 99801-8626
E-mail address: Sharon Hawkinsia'noaa gov
Oleg N. Katugin
Vladimir N. Tuponogov
Pacific Research Fisheries Centre (TINROCentre)
4 Shevchenko Alley
Vladivostok 690950, Russia
Manuscript submitted 24 November 2003
to the Scientific Editor's Office.
Manuscript approved for publication
28 March 2005 by the Scientific Editor.
Fish. Bull. 103:524-535 (2005).
Information about the biology and
population dynamics of rougheye rock-
fish (S. aleutianus) and shortraker
rockfish (S. borealis) is limited, and
uncertainty exists about current stock
abundance and long-term productiv-
ity. As adults, these two species are
similar in appearance, have the same
zoogeography, and share the same
habitat. They were classified as a
single species, S. aleutianus (Jordan
and Evermann, 1898), until Barsukov
(1970) described S. borealis. Tsuyuki
and Westrheim (1970) also described
■S. borealis that same year (initially as
S. caenaematicus), using biochemical
methods. The distribution of rough-
eye rockfish is reported from Japan
to southeastern Kamchatka (exclud-
ing the Sea of Okhotsk), to Navarin
Canyon in the Bering Sea, throughout
the Aleutian Islands, and south to San
Diego, California (Tokranov and Davy-
dov, 1997). Shortraker rockfish has
a similar distribution; however, this
species is much more abundant than
rougheye rockfish in Russia — eastern
Russian Sebastes biomass was com-
posed of more than 90% shortraker
and less than 1% rougheye rockfish
for most regions, excepting the Com-
mander Islands (Tokranov and Davy-
dov, 1997). Both species have been
reported at depths to 875 m (Allen
and Smith. 1988), although longline
(Sigler and Zenger1) and trawl surveys
(NMFS triennial groundfish survey)
indicate they are most abundant on
the upper continental slope at 300-
400 m depths. Krieger and Ito (1999)
found the two species difficult to dis-
tinguish visually when viewed from
a submersible but believed that the
highly sedentary adults of both spe-
cies share the same habitat, prefer-
ring substrates of sand or mud and
frequent boulders and steep slopes.
Rougheye and shortraker rockfish
are highly prized commercially but
are particularly sensitive to overex-
ploitation because of slow growth, late
maturation, and long life spans. Half
of rougheye rockfish are mature at 20
Sigler, M. F., and H. H. Zenger Jr. 1994.
Relative abundance of Gulf of Alaska
sablefish and other groundfish based on
the domestic longline survey, 1989. U.
S. Dep. Commer., NOAA Tech. Memo.
NMFS-AFSC-40, 79 p. Auke Bay Labo-
ratory, 11305 Glacier Hwy., Juneau, AK
99801.
Hawkins et al .: Genetic variation of Sebastes aleutianus and 5 boreahs
525
years of age (McDermott, 1994). Rougheye rockfish have
been estimated to attain ages in excess of 200 years
and shortraker rockfish in excess of 150 years (Munk,
2001). These two species are currently managed to-
gether as the "shortraker-rougheye" assemblage within
waters managed under a North Pacific Fishery Man-
agement Council (NPFMC) fishery management plan.
Commercial catch levels in NPFMC areas of the Bering
Sea, the Aleutian Islands, and the Gulf of Alaska aver-
aged 2400 t each year from 1999 to 2001 (Heifetz et al.,
2002; Spencer and Reuter, 2002).
The annual catch quota for rockfish and most ground-
fish managed by the NPFMC is apportioned among five
relatively large geographic areas: the eastern, central,
and western Gulf of Alaska, the Aleutian Islands, and
the eastern Bering Sea. Previous work in the Gulf of
Alaska has indicated geographical segregation of the
two rougheye species (Moles et al., 1998; Hawkins et
al.2). Based on earlier designations of the International
North Pacific Fisheries Commission, area boundaries
have little biological basis. If the population structure of
a particular species has different geographic boundar-
ies than the boundaries of the designated management
areas for the species, there is risk of over-harvest. The
objective of this study is to examine the population
structure of rougheye and shortraker rockfish by using
allozyme variation. This is the first population struc-
ture study of these two species that encompasses all
the North Pacific management areas and most of their
biological ranges.
Methods
Collection
Adult rougheye rockfish were collected with bottom
trawls from the Gulf of Alaska in 1993, the eastern
Bering Sea in 1994, and from the Washington coast in
1998. They were also collected by longline from waters
north of Unalaska Island in the Aleutian Islands in
1996, the central Gulf of Alaska and the northwestern
Bering Sea near Russia in 1997, and north of Unalaska
Island (Aleutian Islands) and in the eastern and cen-
tral Gulf of Alaska in 2001. Shortraker rockfish were
collected with bottom trawls from the Gulf of Alaska in
1993, the eastern Bering Sea in 1994, and by longline in
the northwestern Bering Sea near Russia in 1997. Dates,
locations, and sample sizes are reported in Table 1 and
Figure 1.
Approximately 2-3 mL of liver, heart, and muscle
were taken from each fish, temporarily stored in either
a freezer (-20°C) or in liquid nitrogen, shipped to the
- Hawkins, S. L., J. Heifetz, J. Pohl, and R. Wilmot. 1997. Un-
publ. data. Genetic population structure of rougheye rock-
fish (Sebastes aleutianus) inferred from allozyme variation.
Alaska Fisheries Science Center, Quarterly Report Feature,
July-Aug.-Sept. Auke Bay Laboratory, 11305 Glacier Hwy.,
Juneau, AK 99801.
Auke Bay Laboratory, Alaska, and stored at -80°C. Eye
tissue was taken from the 1993 Southeast Alaska sam-
ples but was not collected during subsequent sampling
efforts because initial experimentation yielded limited
results from this tissue. Samples of heart tissue were
sent to the University of Alaska for DNA analysis. Only
liver tissue was taken from the Shumagin and Aleutian
Islands rougheye rockfish samples in 2001 (regions 9b,
14a, and 16a). The right gill arch and a 4-inch section
of the gut were sampled for parasite analysis from the
rougheye rockfish 2001 Gulf of Alaska samples. These
fish were also photographed, preserved in 10% formalin,
and shipped to the Alaska Fisheries Science Center for
future morphological studies.
Laboratory analysis
Protein enzymes from each sample were separated by
horizontal starch-gel electrophoresis as described by
Aebersold et al. (1987). Enzymes were screened by stain-
ing eye, heart, liver, and muscle tissue on each of six
buffer systems (Table 2) by using general staining pro-
cedures (Harris and Hopkinson, 1976; Aebersold et al.,
1987), and Sefrasres-specific procedures (Seeb, 1986).
Enzyme screening was designed to detect interspecific
allelic mobility differences and to identify intraspecific
multilocus enzymes by tissue. Therefore, each tissue
type from both rougheye and shortraker rockfish were
run together on each gel buffer. Of 47 enzymes screened,
23 enzymes representing 29 loci were resolved for all
rougheye rockfish except the Russian collection, for
which 25 loci were resolved, and the collections from
regions 9b, 14a, and 16a, for which only liver samples
were taken and 7 loci were resolved (data available
from senior author). Twenty-nine loci were resolved for
all shortraker rockfish collections except the Russian
collection, for which 24 loci were resolved (data avail-
able from senior author). The loci used in subsequent
analyses and the level of variation are listed in Table 2.
Nomenclature for identified loci were assigned according
to the American Fisheries Society guidelines for stan-
dardization (Shaklee et al., 1990).
Data analysis
Fish sampled from stations in close proximity were com-
bined to form regional collections (Table 1 and Fig. 1).
The software package GENEPOP (vers. 3.4, Montpellier
University, Montpellier, France) was used to calculate
genotypic frequencies for each region and to test for
departure from expected Hardy-Weinberg equilibrium
frequencies. Homogeneity of allele frequencies among
regional collections was tested with log-likelihood ratio
analysis (G-test; Sokal and Rohlf, 1981). Fu and Fst were
calculated with FSTAT (Goudet, 1995).
Heterogeneity among the collections and within some
of the collections of rougheye rockfish was such that the
fish were easily divided into two distinct "types" accord-
ing to their genotypes at five loci: ACP*, IDDH*, MPI*,
PGM-2*, and XO* (Table 3 and data available from
526
Fishery Bulletin 103(3)
Table 1
Regiona
1 group, location, sample size (n) ofS. aleutianus, S. sp. cf. aleul
ianus
U = unknown type
of S. aleutia
nus, S. boreal
s, and
latitude
longitude, depth, and date of collections.
Sebastes
Sebastes
aleutianus
Sebastes
aleutianus
sp.cf.
U
borealis
Lat.
Long.
Depth
Region
Location
(ra)
(n)
(;?)
in)
N
W
im)
Date
1
North Washington State
79
3
47.6
125.2
118-421
1998
2
S.E. Alaska, Dixon entrance
20
21
36
54.5
133.5
152-228
1993
3
S.E. Alaska, S. Baranoff Is.
32
16
10
56.0
135.2
176-260
1993
4
S.E. Alaska, Cross Sound
27
4
15
58.1
136.9
77-249
1993
5
S.E. Alaska, Cape Fairweather
19
1
1
38
58.4
139.3
123-241
1993
5a
S.E. Alaska, Cape Fairweather
2
6
2
58.4
140.4
300-400
2001
6
S.E. Alaska, Yakutat
50
3
4
53
59.3
141.2
102-198
1993
6a
S.E. Alaska, Yakutat
6
10
6
59.2
141.1
300-400
2001
7
S.E. Alaska, Cape Suckling
22
0
1
32
59.8
143.4
81-217
1993
7a
S.E. Alaska, Cape Suckling
5
42
2
59.3
143.1
300-600
2001
8
S. of Prince William Sound
4
43
58.2
148.4
300-600
1997
8a
S. E. of Prince William Sound
2
17
59.1
147.2
300-400
2001
9
Kodiak Island, S.W.
12
86
99
56.3
152.1
270-400
1996
9a
Kodiak Island, S.W.
11
0
8
58.0
152.2
140-150
2001
9b
Shumagin Island, S.W.
5
0
2
55.4
159.4
145
2001
10
South of Amlia Island
S. between Atka & Amlia Is
0
76
105
51.8
173.9
303-320
1994
South of Amlia Island
0
12
51.5
173.3
163-650
1996
11
South Atka Pass
South Atka Pass
0
22
34
51.7
175.5
309-407
1994
South of Atka Island
0
25
1
20
51.5
175.1
185-820
1996
12
South Tanaga Island
South of Tanaga Island
0
70
57
51.6
177.6
372-381
1994
West of Tanaga Island
0
24
12
51.4
178.1
90-705
1996
13
North of Semisopochnoi Island
0
28
52.5
180.0
213
1994
14
North Atka Pass
0
30
37
52.1
175.0
108-940
1996
14a
North of Amlia Island
0
11
2
52.5
173.5
230-350
2001
15
N. of Islands of Four Mountains
0
34
12
53.0
170.1
172-630
1996
16
North Unalaska Island
North of Unalaska Island
5
0
53.7
167.0
195
1994
North of Unalaska Island
6
44
53.7
167.0
121-350
1997
16a
North of Unalaska Island
8
3
1
53.6
167.5
85-303
2001
17
northwest Bering Sea, Russia
0
55
60.5
179.3E
390-384
1997
northwest Bering Sea, Russia
55
60.3
171. 4E
457-533
1997
senior author). We identified these types as Sebastes
aleutianus and Sebastes sp. cf. aleutianus (a species that
has putatively not been described but is similar to S.
aleutianus). The S. aleutianus type is characterized by
individuals with genomes of predominately ACP *100;
IDDH*100, and *500; MP/*129; PGM-2*100, *83, *91,
and *117; and XO*100. The Sebastes sp. cf. aleutianus
type is characterized by individuals with genomes of
predominately ACPM6; IDDH*500 and *750; MPI *100;
PGM-2 *83, *74, and *63; and XO* 109. We used 25
loci to perform multidimensional scaling analysis of
individual rougheye genotypes to illustrate separation
of the two types.
We chose STRUCTURE, a Bayesian clustering model
(Pritchard et al., 2000) to gain greater statistical rigor
in identifying individual types and possible hybrids of
rougheye rockfish. This model seeks to identify popula-
tions in a mixture without the availability of baseline
samples from the separate populations. The proportions
of each individual's genome belonging to the population
identified by the model and the separate population al-
lele frequencies are simultaneously estimated. A 907c
probability interval is computed for each individual's
inferred genome source proportions. For this analysis,
we used 25 loci, 100,000 iterations, and a 10,000 burn-
in period. This model assumes that loci are in Hardy-
Hawkins et al.: Genetic variation of Sebostes aleutianus and 5. borealis
527
170 00 -ISO 00' -renin' -160°00' -150°00 -140°00 -130 00'
120 00'
- 1(H) 00
6000-
50°00!
F7\
ssia ) \ vv^.
l"i
Vsf ">
i:
14
12 11 10
Aleutian Is lands
t
N
Oilliii
50 00
-170°00
-I '
-150°00'
-14o 00
-13O'0O
Figure 1
Location of rougheye tSebastes aleutianus) and shortraker rockfish (Sebastes borealis) collection sites, which
correspond to locations in Table 1.
Weinberg equilibrium within populations and in link-
age equilibrium with one another within populations.
These assumptions were tested with the PC program
GENEPOP (vers. 3.4, Univ. Montpellier, Montpellier,
France).
Regional groups were separated into two groups of
rougheye rockfish types according to the multidimen-
sional scaling analysis and Bayesian clustering model
and were retested for Hardy-Weinberg equilibrium and
homogeneity of allelic frequencies (G-test) among regions
for each type. Chord distance (Cavalli-Sforza and Ed-
wards, 1967) for 25 loci was used to assess the overall
similarities of allelic frequencies for the two rougheye
rockfish types with multidimensional scaling analysis
(Rohlf, 2000). Only 25 loci were used because the Rus-
sian collection was missing data at 4 loci. Regions 9b.
14a, and 16a were therefore not included in these analy-
ses because of the limited number of loci available.
Because the two rougheye rockfish types exhib-
ited a distinct yet puzzling pattern of distribution —
nearly all S. sp. cf. aleutianus in the Aleutian Is-
lands, nearly all S. aleutianus in the central Gulf
of Alaska, and both types in sympatry in Southeast
Alaska — we collected rougheye rockfish at different
depths in 2001 (regions 5a-9a, 9b, 16a). We ran a
Mann-Whitney rank sum test (SigmaStat, vers. 2.0,
SPSS. Chicago, IL) to test for significant differences
of the mean, standard deviation, and range of depths
between the two rougheye rockfish types. A single depth
of 350 m was used to approximate depth of catch for the
2001 Southeast Alaska rougheye rockfish collections (re-
gions 5a, 6a, and 7a) because depths were reported only
as a range from 300 to 600 m. Had we chosen a deeper
average depth in the range, the difference in depth be-
tween the two rougheye rockfish types would have been
(and in actuality may be) even greater. Because the two
rougheye types were found in sympatry, we analyzed
the length data to determine if size differences existed
between the two types. Linear regressions were used to
examine the relationships between length (tip of snout
to fork of tail) and depth of capture of both shortraker
rockfish and the two rougheye rockfish types.
528
Fishery Bulletin 103(3)
Table 2
Enzymes with associated International Union of Biochemistry Numbers (IUBNC), locus name (Shaklee et al., 1990), tissue! si.
buffer(s). and level of variability for Sebastes aleutianus. RE=both Sebastes sp. cf. aleutianus and Sebastes aleutianus, and
SR = Sebastes borealis. Tissue: M=muscle; H=heart; and L=liver. Buffers: 1= R (Ridgway et al., 1970); 2 = MF (Markert and
Faulhaber, 1965); 3 = CA6.1 and 4- CA6.9 (Clayton and Tretiak, 1972, modified pH); 5 = TC (Shaw and Prasad, 1970); and 6 =
CAME7.4 (modified from Clayton and Tretiak, 1972). Var. RE and Var. SR: 0 = monomorphic; 1 = frequency common allele >0.95;
2 = frequency common allele <0.95 for at least one region. — = Loci were not reliably scored in that species. + = loci were not reli-
ably scored in all populations and were not used in most analyses.
Enzyme
IUBNC no.
Locus
Tissue
Buffer
Var. RE
Var. SR
Acid phosphatase
3.1.3.2
ACP*
L
3
2
—
Aconitate hydratase
4.2.1.3
mAH*
H
5,6
1
1
sAH*
L
3,4
2
1
Adenosine deaminase
3.5.4.4
ADA-1*
M,H
3,6
0
2
Adenylate kinase
2.7.4.3
AK*
M,H,L
6
0
0
Alcohol dehydrogenase
1.1.1.1
ADH*
L
3
2'
2
Aspartate aminotransferase
2.6.1.1
sAAT*
L
1
2'
0
mAAT*
M,H,L
3,4,6
1
1
beta-N-Acetylgalactosaminidase
3.2.1.53
bGALA*
L
4
0'
0
Creatine kinase
2.7.3.2
CK-1*+
H
3,6
1
0
Fumarate hydratase
4.2.1.2
FH*
H,L
5
0'
1
Glucose-6-phosphate isomerase
5.3.1.9
GPI-A*
M,H,L
1,3
1
2
GPI-B*
M,H
1.3
1
1
Glycerol-3-phosphate dehydrogenase
1.1.1.8
G3PDH*
M
2
0
1
Iditol dehydrogenase
1.1.1.15
IDDH*
L
1
2
—
Isocitrate dehydrogenase
1.1.1.42
IDHP-V +
H
3
1
1
IDHP-2*
L
3
1
1
Lactate dehydrogenase
1.1.1.27
LDH*
M,H
3
0
0
Malate dehydrogenase
1.1.1.37
MDH-1*
M,H
3,6
1
—
MDH-2*
M,H,L
3,4,6
1
1
Malic enzyme
1.1.1.40
mMEP*
M,H
3,6
2'
2
Mannose-6-phosphate isomerase
5.3.1.8
MPI*
H
6
2
2
Dipeptidase (glycyl-leucine)
3.4.-.-
PEPA*
M,H,L
2
2
1
Tripeptide aminopeptidase (leu-gly-gly)
3.4.-.-
PEPB*
M,H,L
1
0
0
PEPD"+
M,H
2
—
2
PEP-LT*+
M,H
2
—
1
Phosphoglucomutase
5.4.2.2
PGM-1*
M.H.L
1,5
2'
2
PGM-2*
H
5
2
2
6-Phosphogluconate dehydrogenase
1.1.1.44
PGDH*
M,H,L
3
2'
0
Triose-phosphate isomerse
5.3.1.1
TPI-1*
M,H
1,3
0
0
TPI-2*
M,H
1,3
—
2
Xanthine Oxidase
XO*
L
2
2'
0
1 Sebastes sp. cf. aleutianus level of variablity was 1.
Parasite analysis
Although not an objective of the study, parasites were
opportunistically sampled from the 2001 Gulf of Alaska
collections of rougheye rockfish to determine if depth or
species subtype might have been a factor in the geographi-
cal segregation noted by Moles et al. in 1998. This would
also allow us to determine if the parasite data supported
results of the current allozyme work. The rougheye rock-
fish were examined for the proportion offish with the gill
parasites Neobrachiella robusta, Trochopus trituba, or the
visceral parasite Corynosoma sp. by using the procedures
of Moles et. al. (1998). A categorical analysis of variance
(SAS procedure, CATMOD: vers. 8.02. Cary, NC 1989)
was used to test whether parasite prevalence differed
among the two types of rougheye rockfish.
Hawkins et al.: Genetic variation of Sebastes aleulianus and 5. boreahs
529
Allelic frequencies
of five loci for
Table 3
all samples by type that best distinguish Sebastes aleutianus and Sebastes sp.
cf. aleutianus.
Locus
n
Allele
ACP*
aleutianus
sp. cf. aleutianus
242
486
100
46
83
0.896
0.094
0.087
0.905
0.017
0.001
IDDH*
aleutianus
sp. cf. aleutianus
287
658
100
500
750
999
0.73
0.03
0.268
0.507
0.002
0.462
0
0.001
MPI*
aleutianus
sp. cf. aleutianus
283
540
100
129
110
0.343
0.74
0.656
0.26
0.001
0
PGM-2*
aleutianus
sp. cf. aleutianus
270
586
100
83
74
63/69/59** 80
91/117**
0.775
0.003
0.185
0.333
0.005
0.508
0 0.002
0.147 0.009
0.028
0
XO*
aleutianus
sp. cf. aleutianus
295
660
100
109
0.844
0.011
0.156
0.989
"* indicates pooled all<
les.
Results
Shortraker rockfish and rougheye rockfish had different
common alleles (fixed) for 10 of 29 loci examined (sAH*,
CK-A1*, GPI-A*, G3PDH*, IDHP-2*, PEPA*, PEPB*.
PEP-LT*, PGM-2*, and SOD*). These are inexpensive
markers that can be used to differentiate shortraker
rockfish from rougheye rockfish when precise field iden-
tification, particularly in younger fish, is necessary but
difficult.
Shortraker rockfish
Nine loci (31%) were monomorphic for all regions, 11 loci
(38%) were variable (with the frequency of the common
allele greater than 0.95 for all regional groups), and 9
loci (31%) had a common allele frequency of less than
0.95 for at least one regional group. For the Russian
collection, data were unavailable from five loci {FH*,
mIDHP*, MPI*, PGM-2*, and TPI-2*). Average heterozy-
gosity of each regional group fell within a narrow range
of 0.09-0.11, and produced an overall average for 29 loci
of 0.10. All regional genotypic proportions closely agreed
with those expected under Hardy-Weinberg equilibrium;
of 128 chi-square tests, only four (3%) differed sig-
nificantly (P<0.05) from expected values. No significant
(P<0.05) heterogeneity was detected with G-tests among
regional groups, and thus no subpopulations or stock
structure was evident with this suite of allozymes.
Although no genetic differentiation was detected
among shortraker rockfish throughout their geographic
distribution, size of fish and depth of capture differed
between shortraker rockfish from the Aleutian Islands
and those from Southeast Alaska. Aleutian Island
shortraker rockfish were significantly smaller (mean
43.6 cm [±SD 7.0], range: 24-70 cm) and were caught
in deeper water (309-407 m) than Southeast Alaska
shortraker rockfish (mean 66.5 cm [±SD 10.5], range:
45-101 cm at 138-260 m depths). A regression of fish
length on depth of capture yielded a significant r2 value
of 0.452 (P<0.001).
Rougheye rockfish
Significant departure from Hardy-Weinberg equilib-
rium occurred in 37 out of 226 possible tests (16%); a
value greater than the 11 that would be expected by
chance alone at the P=0.05 level of probability (Table 4).
Thirty-six of the departures were due to an absence of
heterozygotes, a situation known as the Wahlund effect,
which typically indicates the presence of a mixture of
populations for presumably neutral genetic loci. Most
of the departure from Hardy-Weinberg expectations
occurred at ACP*, IDDH*, MPI*, PGM-2*, andXO*. Only
530
Fishery Bulletin 103(3)
Table 4
Loci not in Hardy Weinberg equilibrium (P<0.05). N/A =
= insufficient sample size
for analysis.
Location
Mixture
S. aleutianus1
S. sp. cf. aleutianus1
Dixon Entrance
ACP, sAH, IDDH
PGM-2, XO
ACP, IDDH
ACP. IDDH
S. Baranof Island
ACP, IDDH. XO
PGM-1, PGM-2
ACP, PGM-1
None
Cross Sound
ACP, IDDH, XO
None
N/A
Cape Fairweather
ACP, PGM-2
ACP
N/A
Yakutat
ACP, MPI
PGM-2. XO
MPI
N/A
Cape Suckling
None
None
N/A
Prince William Sound
IDDH, PGM-2, XO
N/A
None
Kodiak
ACP. IDDH
PGM-2. XO
None
ACP
Amlia Island
None
N/A
None
South Atka Pass
MPI
N/A
MPI
South Tanaga Island
PEP A, PGM-2
N/A
PEPA
North Semisopoehnoi Island
IDDH
N/A
IDDH
North Atka Pass
None
N/A
None
N. Is. Of Four Mountains
None
N/A
None
North Unalaska Island
ACP, PGM-2, XO
ACP. XO
None
Washington
sAH, IDDH, MPI
PGM-2
sAH, MPI
N/A
Russia
None
N/A
None
' As determined from the program
STRUCTURE (Pritchard et al„ 2000).
PGM-2* in the South Tanaga Island sample was due to
an excess of heterozygotes.
Inbreeding coefficients (Fis) indicated deviation from
panmixia. The values ranged from -0.050 for IDHP-1*
to 0.772 for ACP*. The mean value over all loci in all
collections was 0.140. Statistically significant Fis val-
ues were found at ACP* (0.521), MPI* (0.135), PGM-2*
(0.109), and XO* (0.524). All were the result of het-
erozygote deficiencies. The mean Fis value for the S.
aleutianus type collections dropped to 0.062 and for the
S. sp. cf. aleutianus types, to 0.048.
Eight of the loci showed statistically significant Fsl
values: sAAT* (0.007), ACP* (0.572), sAH* (0.037),
IDDH* (0.189), MDH-2* (0.007), MPI* (0.123), PGM-2*
(0.206), and XO* (0.551). The mean F, value for all
loci in all collections was 0.215. When analyzed by
pure S. aleutianus-type and S. sp. cf. aleutianus-
type, the mean Fsl values dropped to 0.013 and 0.012,
respectively.
Two rougheye types
The results of the rougheye rockfish analyses allowed
us to segregate rougheye rockfish individuals into two
types: S. aleutianus and Sebastes sp. cf. aleutianus.
Multidimensional scaling analysis with individual geno-
types (Fig. 2) yielded two distinct clusters with little
overlap. This outcome was confirmed by the Bayesian
clustering model in STRUCTURE (Pritchard et al.,
2000), which identified two types. We calculated the
inferred source proportions of genomes for 1027 indi-
viduals using 25 loci that were scored in most individu-
als. One hundred sixty-six individuals were missing
data for more than 30% of the 25 loci used and were
omitted from the analysis. Most of the individuals had
a very high proportion of their genome from one type;
for 851 individuals, the program assigned at least 0.80
of the individual's genes to one of the two ancestral
lines, and all had an upper 90% probability limit that
included 1.0. These fish were likely all purebreds. Ten
individuals had an inferred proportion of ancestry from
one lineage of less than 0.80 and two did not include
an upper probability interval of 1.0. These individuals
were possibly hybrids. If any of these 10 individuals
were actual hybrids of the two rougheye rockfish types,
none were of the first generation (i.e., heterozygotes at
all differentiating loci).
Significant differences of allele frequencies (G-
test) were detected between the two types at 14 loci:
P< 0.001 for sAAT*, ACP*, ADH*, sAH*, IDDH*, MDH-
2*, mMEP*. MPI*, PGDH*, PGM-1*, PGM-2*, and XO* ;
and P<0.05 for mAAT* and GPI-B*. When the two types
were analyzed independently by area (Table 4), all but
two collections were in Hardy-Weinberg equilibrium
Hawkins et al.: Genetic variation of Sebastes aleutianus and 5. borealis
531
-1.5
• S. sp. cf. aleutianus
o S. aleutianus
<9
-1.0
-0.5
0.0
X
0.5
1.0
1.5
Figure 2
Multidimensional scaling analysis of individual rougheye rockfish {Sebastes aleu-
tianus) genotypes for 25 loci.
(South Tanaga Island Sebastes sp. cf. aleutianus type,
P=0.042, and North Unalaska Island S. aleutianus
type, P= 0.023). The G-test analysis indicated no hetero-
geneity among regions except for the Russian sample,
which was significantly different from all other samples
(P<0.05). Average heterozygosity was 0.09 for S. aleu-
tianus and 0.08 for Sebastes sp. cf. aleutianus.
A significant difference in overall depth of capture
(P<0.001) was detected between Sebastes sp. cf. aleu-
tianus (mean 330+ m) and S. aleutianus (mean 208
m). We obtained both shallow and deep collections from
the central Gulf of Alaska. The fish captured at shal-
low depths, 77-249 m (regions 4-7, 9a, 9b, rc = 134),
were nearly all (94%) S. aleutianus, whereas the deep-
er dwelling fish, 270-600 m (regions 5a-7a, 8, 8a, 9,
n=204), were mostly (87%) Sebastes sp. cf. aleutianus.
Both types were captured, some within a single haul,
in southern Southeast Alaska (regions 2 and 3, /z = 89)
at depths of 150-260 m (Fig. 3).
A highly significant correlation of fish length (15-
65 cm) and depth of capture (77-260 m) was detected
for S. aleutianus in Southeast Alaska, with smaller
fish in shallower water and larger fish in deeper water
(r2=0.415, P<0.001) No length-depth trend was noted
for Sebastes sp. cf. aleutianus.
Results of the parasite analysis for the 2001 rougheye
rockfish showed that Sebastes sp. cf. aleutianus had a
significantly higher prevalence of both Neobrachiella
robusta (P=0.003) and Trochopus tntuba (P=0.022)
than did S. aleutianus (Table 5).
Discussion
The most notable conclusion of our study was that two
genetically distinct types of rougheye rockfish exist.
This conclusion corroborates prior biochemical studies in
which Tsuyuki et al. (1968) and Tsuyuki and Westrheim
(1970) conducted hemoglobin electropherogram analyses
on S. aleutianus and S. caenaematicus (=S. borealis) and
detected four blood types. Three blood types character-
ized S. aleutianus — two distinct types and a rare hybrid
type. The fourth type characterized S. borealis. Seeb
(1986) examined allozymes from several species of North
Pacific rockfish and found two color morphs of rougheye
rockfish fixed for alternate alleles at three loci. At one
of the loci, ACP*, we detected a small percentage of a
shared allele, likely because of our larger sample size. We
were unable to resolve the other two loci, GAP* (IUBNC
no. 1.2.1.12 Glyceraldehyde-3-phosphate dehydrogenase,)
and GAM* (B-Galactosaminidase). Although we are
unable to report fixed loci differences between the two
rougheye rockfish types, we did detect significant allele
frequency differences at nearly half of the loci examined.
Allelic mobilities of Sebastes aleutianus were similar to
those of Seeb's "Sebastes aleutianus," and allelic mobili-
ties of Sebastes sp. cf. aleutianus were similar to Seeb's
"Sebastes aleutianus unknown." Because simultaneous
hemoglobin and allozyme studies have never been done,
we are currently unable to correlate allozyme types with
the blood types reported by Tsuyuki et al. (1968) and
Tsuyuki and Westrheim (1970).
532
Fishery Bulletin 103(3)
170°00 -180°00 -170°00 -160°00 -15CT0O -14OC0 -13(700 -120*00
-110° CO
-100° CO
aim
50° 00-
-170° 00
60° 00
50° 00'
-160° 00
-150° 00
Figure 3
-140° 00
130° 00
Proportions of Sebastes aleutianus and S. sp. cf. aleutianus in relation to depth of capture.
Table 5
Prevalence of parasites (percentage) in both rougheye rockfish types and results of categorical analysis of variance.
Parasite prevalence
sp. cf. aleutianus (n = 61)
Neobrachiella robusta
Troehopus trituba
Corynosoma sp.
0.57
0.49
0.90
S. aleutianus (;i = 18)
0.11
0.17
0.83
Significance probability
Type
0.003*
0.022*
0.448
Size offish
0.442
0.339
0.326
The Cavalli-Sforza-Edwards (CSE) chord distance
(for 29 loci) between the two S. aleutianus types, 0.35
(SD = 0.05), was a value comparable to that for other
closely related rockfish species. Seeb (1986) reported
CSE distances between rockfish species ranging from
0.07 to 0.75 for 28 loci. Identical mobilities at the ma-
jority of loci indicated a close relationship between
the two types, which probably existed as a single type
at an earlier geologic time. Given that Tsuyuki and
Westrheim (1970) detected (2%) hybrids of the two
blood types and we did not detect fixed differences be-
tween the two rougheye rockfish types, some gene flow
may be occurring. However, the low effective number
of migrants and the sympatric distribution of the popu-
lation indicate that the gene flow is limited. Because
rockfish have internal fertilization, sibling species may
co-occur and there is little chance of cross-fertilization
of gametes.
Hawkins et al : Genetic variation of Sebastes aleutianus and S. boreahs
533
The initial objective of our study did not include col-
lection of morphological data, but in light of the genetic
differences detected, and the color morphs detected by
Seeb (1986), morphology of the two lineages should be
more closely examined. Upon processing the 2001 fish,
we noted that many were easily identified as either light
or dark in color, although some appeared intermediate.
The obvious light-colored individuals were all found
genetically to be S. aleutianus, whereas the darker
specimens were typically Sebastes sp. cf. aleutianus.
Although Tsuyuki and Westrheim (1970) reported no
distinguishing meristic or morphometric characters
between S. aleutianus blood types, Seeb (1986) sepa-
rated rougheye rockfish morphologically and by color
into two groups: one that was light pink and had spines
under the orbit of the eye (S. aleutianus); the other
was darker and had a considerable area of black on the
mouth and jaw and often lacked orbital spines (S. aleu-
tianus unknown). The lack of orbital spines in Sebastes
sp. cf. aleutianus is an important observation because
this feature is a key characteristic in distinguishing
S. aleutianus from S. borealis.
Initial observations of the distribution of the 1993
rougheye samples displayed a pattern of predominately
S. aleutianus in the Gulf of Alaska and almost entirely
S. sp. cf. aleutianus in the Aleutian Islands. A parasite
study (Moles et al., 1998) performed on the same rough-
eye rockfish reported a significantly greater (P<0.05)
prevalence of three parasites in the Aleutian Island
samples. Upon close examination of the depth of the
sample collection, we noted that the Aleutian Islands
samples were collected in deeper waters than those col-
lected in the Gulf of Alaska. Thus subsequent sampling
strategies focused on a possible depth niche. Parasite
data from both the shallow and deep water 2001 rough-
eye collections showed a significant prevalence of two
parasites in the deeper host, Sebastes sp. cf. aleutianus
(Table 5). The prevalence of the parasite T. trituba may
be dependent on host habitat. Because the hosts (two
aleutianus types) exhibited significantly different preva-
lences of the parasite T. tributa, they may be using
different resources (different diets) and (or) exhibiting
ecological segregation (Moles et al., 1998).
Both Sebastes aleutianus types are found in the Gulf
of Alaska and occur in sympatry, although the majority
of S. sp. cf. aleutianus are distributed at deeper depths
(Fig. 3). Bathymetric segregation has been noted in
other closely related rockfish. Sebastes fasciatus and
Sebastes mentella in the Atlantic Ocean elude abun-
dance estimates because of a lack of easily identifiable
morphological characteristics. In the laboratory, these
two species are nearly fixed at alternate alleles at the
allozyme locus MDH*. A bathymetric segregation is de-
tected, where S. fasciatus is found at depths of 132-315
m, S. mentella at depths greater than 355 m, and both
species and possible hybrids at intermediate depths (Ru-
bec et al., 1991). Another species pair, Sebastes carnatus
and Sebastes chrysomelas, are both shallow-dwelling
species (depth less than 20 m) that coexist only in a
narrow zone of overlap that separates exclusive depth
ranges. Factors organizing their segregation are largely
behavioral because both species expand their depths in
the absence of the other species (Larson, 1980). Rough-
eye rockfish may exhibit a similar strategy. Deep sam-
pling efforts near Washington state have indicated that
the distribution of S. sp. cf. aleutianus may diminish
in southern ranges and it appears that the distribu-
tion of S. aleutianus does not extend to the western
Aleutian Islands and Asia. This pattern of distribution
has been noted in other closely related species, such as
the northern and southern species of Lepidopsetta (Orr
and Matarese, 2000). The poorly understood ontogenetic
and seasonal movements of rougheye and other rockfish
further confound the picture. For example, S. altivelis
and S. alascanus were long thought to be deep-dwelling
and shallow-dwelling congeneric species, respectively. It
is now known that S. altivelis is a permanent deepwater
resident, whereas S. alascanus settles in shallow water,
then migrates to deep water with the onset of sexual
maturity. Competition between these two species may
be reduced by size differences; for example, where they
are sympatric, S. alascanus is much larger than S. al-
tivelis (Vetter and Lynn, 1997). Although length data
for rougheye rockfish in sympatry are limited, a single
haul (n=29) near Dixon Entrance (depth of capture=
213 m) yielded both types, and nearly all the S. aleutia-
nus individuals were much larger (mean 56.3 cm) than
Sebastes sp. cf. aleutianus (mean 37.2 cm). No age data
are currently available to add insight into these results.
The trend of smaller fish in shallower waters and larger
fish in deeper waters was significant for S. aleutianus in
the Gulf of Alaska. This was not detected for Sebastes
sp. cf. aleutianus, although their full depth range may
not have been sampled. Perhaps only younger Sebastes
sp. cf. aleutianus were collected, and the older, larger
fish are deeper and remain unsampled. It would be ben-
eficial to analyze juvenile rougheye rockfish to ascertain
genetic type composition at different depths.
A significant size difference existed between fish
in the Gulf of Alaska and those of the Aleutian Is-
lands, especially among shortraker rockfish. Aleutian
fish were smaller, despite collection at greater depth.
Growth and age of maturation differences among dif-
fering latitudes and longitudes have been noted in
other rockfish species (Westrheim, 1973; Archibald et
al., 1981; Field, 1984; Lunsford, 1999). The size differ-
ence among shortraker rockfish has been previously
noted (Orlov, 2001; Matala, 2004) and raises more
questions than it answers. It is still unknown whether
these differences are caused by different age classes or
regional ecological differences.
Allozyme data did not reveal heterogeneity within
either rougheye rockfish type or within shortraker rock-
fish throughout the sampled geographic range. Although
no heterogeneity was detected with our suite of allozyme
loci, other genetic markers, such as microsatellite loci,
may provide finer resolution of population structure.
A recent study of shortraker microsatellite variation
revealed geographically restricted homogeneity among
allele frequencies — a model consistent with the assump-
534
Fishery Bulletin 103(3)
tion of limited movement (Matala, 2004). Conversely,
Orlov (2001) proposed a synopsis of horizontal adult
migration (with increased size of shortraker rockfish
at spawning grounds) and oceanic dispersal of larvae
and juveniles.
In conclusion, it appears there are species-level differ-
ences between the two rougheye rockfish types. We have
considered the darker morph Sebastes sp. cf. aleutianus
as the new type. The paler S. aleutianus morph con-
forms more to the original S. aleutianus type descrip-
tion, an individual of which was captured at a 55-m
depth in the Gulf of Alaska. It is likely that the distri-
bution of the new species S. sp cf aleutianus stretches
from the Gulf of Alaska and west to Asia. The distri-
bution of S. aleutianus encompasses the Gulf of Alaska
and extends south to California, and the species is
found in more shallow waters where it is sympatric with
S. sp cf aleutianus. An understanding of the basic life
history, distribution, and biomass of a species is critical
for successful resource management. Ito (1999) suggest-
ed that the major fisheries management survey effort is
the NMFS Gulf of Alaska triennial trawl survey, which
may be inadequate to assess the shortraker-rougheye
rockfish assemblage because its multispecies sampling
design covers mostly depths less than 200 m. This sur-
vey may, therefore, be completely missing Sebastes sp.
cf. aleutianus altogether. An important consideration for
management is knowledge of exploitation rates. Given
the sensitivity of long-lived rockfish species to over-ex-
ploitation, basic biological studies should be undertaken
of these species to understand characteristics such as
growth, maturity, and natural mortality.
Acknowledgments
We dedicate this article in fond memory of H. R. Carlson.
His research provided a highly significant contribution
to our understanding of juvenile rockfish life history and
homing in adult rockfish, and he was anxiously awaiting
completion of our study. We thank Hanhvan Nguyen for
her support in the laboratory, and we thank all partici-
pants in the haul and longline surveys for providing the
collections. We also thank James Orr, Jerry Pella, and
Phillip Rigby for earlier reviews of the manuscript, and
Adam Moles for the parasite determinations.
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536
Abstract— The thorny skate (Ambly-
raja radiata) is a large species of
skate that is endemic to the waters
of the western north Atlantic in the
Gulf of Maine. Because the biomass
of thorny skates has recently declined
below threshold levels mandated by
the Sustainable Fisheries Act, com-
mercial harvests from this region
are prohibited. We have undertaken
a comprehensive study to gain insight
into the life history of this skate.
The present study describes and
characterizes the reproductive cycle
of female and male thorny skates,
based on monthly samples taken off
the coast of New Hampshire, from
May 2001 to May 2003. Gonadoso-
matic index (GSI), shell gland weight,
follicle size, and egg case formation,
were assessed for 48 female skates.
In general, these reproductive para-
meters remained relatively constant
throughout most of the year. However,
transient but significant increases
in shell gland weight and GSI were
observed during certain months.
Within the cohort of specimens sam-
pled monthly throughout the year, a
subset of females always had large
preovulatory follicles present in their
ovaries. With the exception of June
and September specimens, egg cases
undergoing various stages of develop-
ment were observed in the uteri of
specimens captured during all other
months of the year. For males (n = 48),
histological stages III through VI
(SIII-SVI) of spermatogenesis, GSI,
and hepatosomatic index (HSI) were
examined. Although there appeared to
be monthly fluctuations in spermato-
genesis, GSI, and HSI, no significant
differences were found. The produc-
tion and maintenance of mature sper-
matocysts (SVI) within the testes was
observed throughout the year. These
findings collectively indicate that the
thorny skate is reproductively active
year round.
The reproductive cycle of the thorny skate
(Amblyraja radiate) in the western Gulf of Maine
James A. Sulikowski
Jeff Kneebone
Scott Elzey
Zoology Department
University ol New Hampshire
Durham, New Hampshire 03824
Present address: Florida Program for Shark Research,
Florida Museum of Natural History
University of Florida
P.O.Box 117800
Gainesville, Florida 32611
E-mail address (for J A Sulikowski) |sulikow(&hotmail com
Joe Jurek
Yankee Fishing Coop
Route 1A
Seabrook, New Hampshire 03874
Patrick D. Danley
Deparment of Biology
University of Maryland
College Park, Maryland 20742
W. Huntting Howell
Zoology Department
University of New Hampshire
Durham, New Hampshire 03824
Paul C. W. Tsang
Department of Animal and
Nutritional Sciences,
University of New Hampshire
Kendall Hall, 129 Main St
Durham, New Hampshire 03824
Manuscript submitted 28 June 2004
to the Scientific Editor's Office.
Manuscript approved for publication
29 March 2005 by the Scientific Editor.
Fish. Bull. 103:536-543 (2005).
The thorny skate (Amblyraja radi-
ata) is a member of the family Rajidae
(Robins and Ray, 1986; Collette and
Klein-MacPhee, 2002). It is a cosmo-
politan species, endemic to both sides
of the Atlantic Ocean, from Greenland
and Iceland to the English Channel
in the eastern Atlantic (Compagno et
al., 1989), and from Greenland and
Hudson Bay, Canada, to South Caro-
lina, in the western Atlantic (Robins
and Ray, 1986; Collette and Klein-
MacPhee, 2002). Despite such a wide
distribution, knowledge pertaining to
the reproductive biology of this species
is limited. Templeman (1982) reported
the occurrence of egg capsules in A.
radiata, and Templeman (1987), Del
Rio (2002), and Sosebee1 examined
size at sexual maturity.
In the Gulf of Maine, these skates
were generally discarded as bycatch
because of their low commercial value
NEFMC.2'3 Recently, the rapidly ex-
panding markets for skate wing has
made this species commercially more
viable, especially because A. radiata
meets the minimum VA pound-cut
pectoral fin size sought by proces-
sors (Sosebee1; NEFMC2). Although
no comprehensive published data for
reproductive cycles currently exist for
thorny skates in the Gulf of Maine,
information from the few skate spe-
cies studied so far indicates that
sexual maturity at a late age, low
fecundity, and a relatively long life
span may also be characteristics of A.
radiata's life history (Winemiller and
Rose, 1992; Zeiner and Wolf, 1993;
Francis et al., 2001; Frisk et el.,
2001; Sulikowski et al., 2003). When
these characteristics are coupled with
the practice of selective removal of
large individuals, the thorny skate
population in the Gulf of Maine may
be highly susceptible to over-exploita-
tion by commercial fisheries (Brander
1981; Hoenig and Gruber, 1990; Casey
and Myers 1998; Dulvy et al., 2000;
Frisk et al., 2001). Because of an in-
1 Sosebee, K. 2002. Maturity of skates
in northeast United States waters. Sci-
entific Council Research Document
NAFO. no. 02/134. 17 p. [Available
from the Northwest Atlantic Fisheries
Organ., Dartmouth, NS.)
2 New England Fishery Management
Council (NEFMC). January 2001. 2000
stock assessment and fishery evaluation
(SAFE) report for the northeast skate
complex, 179 p. NEFMC, 50 Water
Street, Mill 2 Newburyport, MA 01950.
:! New England Fishery Management Coun-
cil (NEFMC). 2003. Skate fisheries
management plan, 142 p. 50 Water St.,
Mill 2 Newburyport, MA 01950.
Sulikowski et al.. The reproductive cycle of Amblyra/a rodiata
537
creasing commercial importance, declines in biomass
levels, and a paucity of specific biological information,
commercial harvests of thorny skates in the U.S. por-
tion of the western North Atlantic are now prohibited.
Thus, obtaining life history information for this skate
species is not only timely (Simpfendorfer, 1993; Frisk et
al., 2001), but it has become imperative. The objective of
the present study was to describe the patterns of sev-
eral morphological reproductive parameters manifested
during the reproductive cycle of female and male A.
racliata collected in the western Gulf of Maine.
Materials and methods
cysts in the testes of 25% or greater were considered
reproductively capable of fertilizing an ovulated follicle.
These criteria are consistent with previous studies that
reported similar characteristics for other mature elas-
mobranch species (Koob et al., 1986; Heupel et al., 1999;
Conrath et al., 2002; Sulikowski et al., 2004). Male and
female thorny skates that did not meet all the criteria
were considered to be immature. We also looked for
some other indicators of reproductive activity, such as
mating bites on female pectoral fins, and evidence of
mating activity on male claspers, but they were either
absent or not apparent in specimens examined during
the study. Sperm storage was not assessed in the pres-
ent investigation.
Sampling
Thorny skates were captured by otter trawl in an area
approximately 900 square miles centered at 42°50'N and
70°15'W in the Gulf of Maine. These locations varied
from 30 to 40 km off the coast of New Hampshire. Col-
lection of skates occurred between the 10th and 20th
of each month beginning May 2001 and ending May
2003. A comparison of samples taken from the same
month between different years revealed no variability.
Furthermore, the skates sampled in the present study
were obtained from the same population and geographic
location. Thus, the data from the same months for dif-
ferent sampling years were grouped together.
Skates were maintained alive on board the FV Mys-
tique Lady until transport to the University of New
Hampshire's Coastal Marine Laboratory (CML). There,
individual fish were euthanized (0.3 g/L bath of MS222).
Total length (TL in mm) was measured as a straight
line distance from the tip of the rostrum to the end
of the tail, and disc width (DW in mm) as a straight
line distance between the tips of the widest portion of
pectoral fins. Total wet weight (kg) was also recorded.
For males, clasper length was measured as the straight
line distance from the posterior point of the cloaca to
the end of the clasper. The gonadosomatic index (GSI)
and hepatosomatic index (HSI) were calculated as gonad
weight divided by total body weight multiplied by 100,
and liver weight divided by total body weight multiplied
by 100, respectively. The epigonal organ was included
in both male and female GSI measurements because of
its close association with the gonads (Maruska et al.,
1996).
Criteria used to determine reproductively active skates
Females whose reproductive tracts contained ovarian
follicles with a minimum diameter of 25 mm and had
a shell gland weighing at least 30 g were considered
mature (capable of egg encapsulation and oviposition).
These numbers were determined from our observations
of reproductive tracts containing egg cases that were
either fully formed or undergoing various stages of
formation. Males with calcified claspers 200 mm long
or greater, and with a proportion of mature spermato-
Gross morphology of the female reproductive tract
After removal of reproductive tracts, the ovaries, shell
glands, and uteri were dissected out, blotted dry, and
weighed to the nearest gram. Ovarian follicle dynamics
were evaluated by measuring the diameter (with a cali-
per) and counting all follicles al mm in diameter (Tsang
and Callard, 1987; Snelson et al., 1988; Sulikowski et
al., 2004). For this data set, we averaged the size of the
largest single follicle found on the right and left ovaries
of each skate. Average follicle diameters, average ovary
weights, and average shell gland weights were analyzed
to assess temporal patterns during the reproductive
cycle.
Histology of the testis
From male specimens, testes were removed, blotted
dry, and weighed to the nearest gram. A single 2-3 mm
thick segment was removed from the central portion of
a single lobe in the medial area of an individual testis
(Maruska et al., 1996; Sulikowski et al., 2004), placed
in a tissue cassette, and fixed in 10% buffered formalin
until processed by the University of New Hampshire
Veterinary Diagnostic Laboratory. There, the sample
was dehydrated, embedded in paraffin, sectioned, and
stained with hematoxylin and eosin. Prepared slides
of testicular tissue were examined and classified into
stages of spermatogenic development following the cri-
teria described by Maruska et al. (1996), Hamlett and
Koob (1999), and Tricas et al. (2000). For the develop-
mental stages of spermatogenesis described in other
elasmobranchs, hormone analyses have confirmed that
stages III through VI are associated with reproduc-
tive readiness (Heupel et al., 1999; Tricas et al. 2000;
Sulikowski et al. 2004). For this reason, we focused
our efforts on these specific stages in the thorny skate.
Briefly, these stages have the following characteristics:
stage III, spermatocysts; stage IV, spermatids; stage
V, immature spermatozoa; and stage VI, mature sper-
matocysts (Maruska et al., 1996). In the present study,
the mean proportion of testis occupied by each of these
stages was measured along a straight line distance
across one representative full lobe cross section of the
testis (Maruska et al., 1996; Conrath et al., 2002).
538
Fishery Bulletin 103(3)
Statistical analyses
The results are presented as means ±SEM and evalu-
ated by Kruskal Wallis analysis of variance followed
by a Tukey's post hoc test. Statistical significance was
accepted at P<0.05. To determine whether a relation-
ship exists in measured morphological and histological
reproductive parameters, a Pearson correlation analysis
(denoted as r) was performed.
Results
The lack of a robust sample size presents a potential lim-
itation for our study. However, over the last decade, there
61 A
has been an increasingly precipitous decline in thorny
skate populations in the Gulf of Maine, especially larger
size specimens (NEFMC2-3). These declines were evident
in our sampling trips, because large, mature individuals
were rarely caught in most trawls. The data presented
in this article are the result of 84 sampling trips that
took place over the course of two years (approximately
three to four trips per month). Moreover, the recent pro-
hibition on thorny skate landings has put an end to any
prospects regarding collection of additional specimens
in the foreseeable future. Thus, the data set we have
presented represents the best available information on
the reproductive cycle for this species.
Size ranges
Mature female skates (?i=48) ranged from
820 to 1050 mm TL (mean=917 ±7 SEM) and
from 4.4 to 10.2 kg (mean=7.7 ±0.2 SEM) in
total body mass. Mature male skates (;? = 48)
ranged from 800 to 1040 mm TL (mean=952
±11 SEM), and from 5.4 to 10.8 kg (mean=8.4
±0.3 SEM) in total body mass.
Jan Feb Mar April May June July Aug Sept Oct Nov Dec
B
Jan Feb Mar Apnl May June July Aug Sept Oct Nov Dec
Figure 1
Monthly changes in female thorny skates {Amblyraja radiata):
(A) Gonadosomatic index (GSI); (B) hepatosomatic index (HSI);
(C) shell gland weight; and (D) diameter of the two largest follicles.
Values are expressed as means +SEM. Sample sizes are indicated
above each month. Values designated with different letters are
significantly different from each other (P<0.05).
Assessment of morphological parameters in
the female reproductive tract
In females, the average GSI of skates captured
in July was lower (P<0.05) than those captured
in October and December, and those from Sep-
tember were lower than the specimens captured
in October, November, and December (Fig. 1A).
Because the number of samples from April con-
sisted of only two skates, we were unable to test
for statistical differences between other months.
Despite this limitation, the two specimens from
April displayed similar values to those in July.
Average HSI (Fig. IB) did not change <P>0.05)
over the sampling period. However, the aver-
age shell gland weight (Fig. 1C) from skates
captured in October was greater (P<0.05) than
those captured in September. Because all shell
glands from skates captured in February were
in the process of encapsulating ovulated eggs,
we were unable to obtain accurate individual
shell gland weights.
There were no differences (P>0.05) observed
in the average diameter of the two largest
follicles (Fig. ID), and no pattern of follicle
dynamics was discerned. Also, fully formed
egg cases, or those in the process of formation,
were found in the uteri of skates captured
during all months of the year, except June
and September.
Additional analysis revealed that GSI was
correlated to shell gland weight (r=0.53) and
average follicle diameter (r=0.4). Further-
more, HSI was also correlated to shell gland
weight (r=0.53) and average follicle diameter
(r=0.7).
Sulikowski et al.: The reproductive cycle of Amb/yra/a radiata
539
Assessment of morphological parameters in
the male reproductive tract
Histological stages III through VI (SIII-SVI)
of spermatogenesis were examined, and GSI
and HSI were determined for the 48 males col-
lected during 24 months of sampling. Although
the relative proportion of these four stages did
not differ among months, it is notable that the
production and maintenance of mature sper-
matocysts (SVI) within the testes persisted
throughout the year (Fig. 2A). Similarly, no
significant seasonal differences were found in
HSI or GSI (Fig. 2, B and C, respectively). In
addition, there were weak to no correlations
between spermatogenesis and either HSI or GSI
(r=-0.07 and 0.13, respectively).
Synchronicity between male and female
reproductive cycles
Results from the male and female morpho-
logical reproductive parameters indicated
that thorny skates are capable of reproducing
throughout the year in the western Gulf of
Maine. When GSI, follicle diameter in relation
to percent composition of SVI, or shell gland
weight in relation to percent composition of
SVI were compared between male and female
thorny skates, no apparent correlation was
detected (Fig. 3, A-C). In contrast, when per-
cent composition of SVI (spermatogenesis) was
plotted against percentage of captured female
skates with egg cases, a strong synchronicity
(r=0.51) was observed (Fig. 4).
Discussion
Elasmobranchs display a wide range of repro-
ductive strategies with morphological and physiological
specializations for oviparous or viviparous reproduction
(Wourms and Demski, 1993; Hamlett and Koob, 1999).
These strategies are associated with one of three basic
types of reproductive cycles: 1) reproduction throughout
the year, 2) a partially defined annual cycle with one
or two peaks, and 3) a well-defined annual or biennial
cycle (Wourms, 1977; Hamlett and Koob, 1999). Among
oviparous elasmobranchs, some species exhibit cycles
with clearly delineated period* s) of reproductive activity
interspersed between periods of little or no activity. For
example, in the clearnose skate (Raja eglanteria), the
patterns of estradiol concentrations and follicle dynamics
indicate the presence of a well-defined annual reproduc-
tive cycle, in which mating and egg deposition take place
from December to mid May (Rasmussen et al., 1999).
Likewise, hormone and morphological data also indicate
a defined annual cycle in the epaulette shark (Hemiscyl-
lium ocellatum) (Heupel et al., 1999) and that reproduc-
tive activities take place from July to December.
90 -
c
B
80 -
70 -
60 -
50 -
■/K
40 -
I
1
/
30 -
A
4
0
4 2
3
8
6
3 3
3
5
5
Jan Feb Mar April May June July Aug Sept Oct Nov Dec
34 -
32
31
Z 30 -
29
D
8 6
Jan Feb Mar April May June July Aug Sept Oct Nov Dec
Figure 1 (continued)
In contrast, other oviparous elasmobranchs exhibit re-
productive activity year round. For example, the present
study revealed that female thorny skates are capable of
reproducing throughout the year. This conclusion was
based on GSI, shell gland weight, diameter of the larg-
est preovulatory follicles, and the presence of egg cases
in specimens collected over the course of the study. We
also observed that GSI and shell gland weight were
highest in October. Thus, the period (or periods) of
enhanced reproductive activity appears to be an in-
tegral part of continuous cycles, although the specific
measured parameters or when these periods occur may
vary between species.
In a study of thorny skates sampled from August to
December in NAFO Division 3N, females were found to
be reproductively active over the entire sampling inter-
val, and peak egg case production occurred in September
(Del Rio, 2002). In contrast, although large preovulatory
follicles were present and oviposition occurred through-
out the reproductive cycle of the lesser spotted dogfish
540
Fishery Bulletin 103(3)
Stage
in
I : Stage IV
^■i Stage V
i ! Stage VI
i
0.8 -
c
07 ■
06 -
K^^
r-"
-Kj
0.5 -
0.4 ■
3 2
3
3 ;
5
5 4
7
4 5
4
Jan Feb Match April May June July Aug Sept Ocl Nov Dec
Figure 2
Monthly changes in male thorny skates (A. radiata): (A) The mean
percent of each stage of spermatogenesis (stages III through VI)
found along a transect line across one representative full lobe
cross section of a testis; (B) hepatosomatic index (HSI) and; (C)
gonadosomatic index (GSI). Sample sizes are indicated above each
month. Values are expressed as mean ±SEM.
(Scyliorhinus canicula) (Henderson and Casey, 2001),
ovary weight and egg deposition peaked during spring.
Similarly, several morphological parameters and steroid
hormones have been shown to peak in female winter
skates (Leucoraja ocellata) during the summer, and
egg-case production is highest in the fall (Sulikowski
et al., 2004). Lastly, in L. erinacea, examination of fol-
licle dynamics and egg-case production indicated that a
higher proportion of females are reproductively active
during two periods of time in the reproductive cycle: in
the winter and in the summer (Richards et al., 1963).
The fairly consistent pattern of HSI in female thorny
skates over the reproductive cycle indicated that liver
reserves (such as lipids and proteins used for oocyte
growth) were stored and metabolized continuously
throughout the year without a significant change in
whole organ biomass. This is in contrast to other ovip-
arous species, such as S. canicula, which displayed
seasonal variations in liver mass as a result of lipid
deposition occurring during different times of the re-
productive cycle (Craik, 1978).
The continual presence of mature spermatocysts with-
in the testes over the entire sampling period indicateded
that male thorny skates are also capable of reproducing
throughout the year. Information describing the annual
reproductive cycles of oviparous male elasmobranchs is
Sulikowski et al.. The reproductive cycle of Amblyro/a radiata
541
0 60
CD
28
80
75
70
s
65
73
C
a
60
55
CO
50
45
40
35
30
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
40
35
25 S
20
Figure 3
Comparisons between male and female thorny skate (A. radiata)
reproductive parameters over the course of the sampling period:
(A) GSI; (B) diameter of the two largest follicles and percentage of
spermatocysts (SVIl and; (C) shell gland weight and percentage of
spermatocysts (SVI).
very limited because studies have focused on changes
in morphological parameters (i.e., Richards et al., 1963;
Craik, 1978) or steroid hormone analyses (i.e., Sumpter
and Dodd, 1979; Rasmussen et al., 1999) in females. To
our knowledge, the only two species in which quantita-
tive methods were used to describe annual reproductive
patterns in males were H. ocellatum (Heupel et al.,
1999) and L. ocellata (Sulikowski et al., 2004). These
two species exhibit contrasting strategies in their re-
spective reproductive cycles. For example, similar to
male thorny skates from the present study, male winter
skates appear capable of continuous production of ma-
ture spermatocysts throughout the year (Sulikowski et
al., 2004). In contrast, examination of the testes and
circulating hormone concentrations in H. ocellatum
indicated that sperm production and androgen concen-
tration display a concurrent seasonal cycle that peaks
from June to October (Heupel et al., 1999).
The lack of correlation between GSI or HSI and stage
of spermatogenesis in the thorny skate was not surpris-
ing because studies do not support the assumption that
relative gonad size (or storage products in the liver)
and reproductive readiness are positively correlated
(Teshima, 1981; Parsons and Grier, 1992; Maruska et
al., 1996). For instance, neither peak sperm production
(Maruska et al., 1996) nor the pattern of testosterone
concentration was correlated with GSI in Dasyatis sa-
bina (Snelson et al. 1997) or L. ocellata (Sulikowski et
al., 2004).
Relatively few studies have assessed whether cycli-
cal patterns of reproductive morphological parameters
or hormone concentrations are coordinated between
542
Fishery Bulletin 103(3)
Comparisons
percentage of
males and females over the course of
their reproductive cycles. Among them,
coordinated peaks in gonad weight and
steroid hormone concentrations in win-
ter skates (Sulikowski et al., 2004) and
epaulette sharks (Heupel et al., 1999)
were observed in males and females over
an annual cycle. In the present study,
mature spermatocysts (SVI) and per-
centage of female thorny skates with
egg cases were also synchronized over
the course of the study. In contrast,
Henderson and Casey (2001) found that
the gonadal cycles of male and female
lesser spotted dogfish were asynchro-
nous, which they hypothesized to be
due to the storage of sperm by females.
Sperm storage has been documented in
other female elasmobranch species as
well (e.g., Pratt, 1993; Maruska et al.,
1996) and is thought to be a feature pri-
marily of species that are nomadic or
segregated by sex (Pratt, 1993). In the
current study, A. radiata was neither
segregated by sex (both genders were captured in the
same area and in the same trawls) nor found to be no-
madic in their movement patterns (Templeman, 1987;
Sulikowski, unpubl. observ. ). Moreover, because males
are capable of producing viable sperm and females ap-
pear to be reproductively active throughout the year,
there is probably no need for the population of thorny
skates that we sampled to store sperm. On the basis
of the above information, we believe that the reproduc-
tive cycle in the sampled population of thorny skates is
coordinated over an annual cycle.
In summary, according to the reproductive strategies
outlined by Wourms (1977) and later by Hamlett and
Koob (1999), the results of the present study indicate
that thorny skates have a reproductive cycle that is con-
tinuous throughout the year. For females, this conclu-
sion was based on ovary weight, shell gland weight, and
diameter of the largest follicles (the preovulatory fol-
licles). For males, this conclusion was based on the pres-
ence of mature spermatocysts within the testes over the
course of the sampling period. Moreover, comparisons
between the proportion of mature spermatocysts within
the testes and the percentage of egg-case-bearing fe-
males indicate that the reproductive cycles of male
and female thorny skates are synchronized. Currently,
analyses of circulating steroid hormone concentrations
are in progress for the thorny skates used in the pres-
ent study, which may provide additional insight into
the regulation and timing of reproductive events in
this species.
Acknowledgments
Collection of skates was conducted on the FV Mystique
Lady. We thank Noel Carlson for maintenance of the fish
25
20
Jan Feb March April May June July Aug Sept Oct Nov Dec
Figure 4
between the percentage of spermatocysts (SVI) and the
female thorny skates (A. radiata) with egg cases.
at the U.N.H. Coastal Marine Laboratory. This project
was supported by a Northeast Consortium grant (no.
NA16FL1324) to PCWT, JAS, and PDD.
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544
Effect of type of otolith and preparation technique
on age estimation of larval and juvenile spot
(Leiostomus xanthurus)
Dariusz P. Fey
Sea Fisheries Institute
Dept. of Fisheries Oceanography and Marine Ecology
ul Kollataja 1
81-332 Gdynia, Poland
E-mail address dfeyig mirgdynia pi
Gretchen E. Bath Martin
James A. Morris
Jonathan A. Hare
NOAA National Ocean Service
Center for Coastal Fisheries and Habitat Research
101 Pivers Island Road
Beaufort, North Carolina 28516-9722
Otoliths of larval and juvenile fish
provide a record of age, size, growth,
and development (Campana and Neil-
son, 1985; Thorrold and Hare, 2002).
However, determining the time of
first increment formation in otoliths
(Campana, 2001) and assessing the
accuracy (deviation from real age)
and precision (repeatability of incre-
ment counts from the same otolith)
of increment counts are prerequisites
for using otoliths to study the life his-
tory offish (Campana and Moksness,
1991). For most fish species, first
increment deposition occurs either
at hatching, a day after hatching, or
after first feeding and yolksac absorp-
tion (Jones, 1986; Thorrold and Hare,
2002). Increment deposition before
hatching also occurs (Barkmann
and Beck, 1976; Radtke and Dean,
1982). If first increment deposition
does not occur at hatching, the stan-
dard procedure is to add a predeter-
mined number to increment counts
to estimate fish age (Campana and
Neilson, 1985).
Accuracy and precision of incre-
ment counts is in part determined
by the increment formation rate,
which has been reviewed elsewhere
(Campana and Neilson, 1985; Jones,
1986; Geffen, 1987), and by the type
of otolith (asteriscus, sagitta, or la-
pillus) and the preparation tech-
nique used for aging. In most age
and growth studies of larval and
juvenile fish, the sagitta, the larg-
est of the three otoliths, has been
used (Campana and Neilson, 1985),
but there are many examples of fish
species that can be aged accurately
by using the lapillus (e.g., Hoff et
al., 1997; Bestgen and Bundy, 1998;
Escot and Granado-Lorencio, 1998;
Morioka and Machinandiarena,
2001). Although infrequently used,
the asteriscus has provided age in-
formation with similar or even bet-
ter precision and accuracy than the
sagitta and lapillus (David et al.,
1994). However, the microstructure
of asterisci is usually not as clear
as that of sagittae or lapilli, and the
extraction of asterisci is relatively
time consuming and laborious (Cam-
pana and Neilson. 1985; Neilson and
Geen, 1985). As for otolith prepa-
ration, two general techniques are
common: 1) polishing of one or both
sides of a sectioned otolith in trans-
verse view, and 2) polishing of one
side of the whole sagitta (Secor et
al., 1992). Sagittae and lapilli pro-
vide the same accuracy and preci-
sion for age estimation; however, la-
pilli may be easier to process for age
determination and may not require
processing at all (e.g., Ichimaru and
Katsunori, 1995).
Spot (Leiostomus xanthurus) is an
important fishery species along the
southeast coast of the United States
(Mercer, 1987) and is a dominant
species in coastal ecosystems owing
to its abundance (Walter and Aus-
tin, 2003). Studies of spot have il-
luminated processes that affect the
abundance of estuarine-dependent
species ( Warlen and Chester, 1985;
Flores-Coto and Warlen, 1993; Ross.
2003). Further, spot has been used
as an experimental organism for ex-
amining larval ecology (Govoni et al.,
1985; Govoni and Hoss, 2001) and
otolith chemistry (Bath Martin et al.,
2000, 2004; Bath-Martin and Thor-
rold, 2005). Although spot has been
widely studied and is an important
ecological and fishery species, basic
information necessary for otolith
analyses is not available.
Our goal was to provide a founda-
tion for the use of otolith increment
counts in examining the ecology of
larval and juvenile spot. Our specific
objectives were 1) to determine the
timing of first-increment formation of
spot (Leiostomus xanthurus) and 2) to
assess the accuracy and precision of
age estimates from increment counts
made with different combinations
otoliths and preparation techniques.
Specifically, four combinations of oto-
liths (sagittae and lapilli) and prepa-
ration techniques were compared: 1)
a transverse section of the sagitta
(polished on one side TSS-1); 2) a
transverse section of the sagitta (pol-
ished on two sides TSS-2); 3) a whole
sagitta (polished on one side WS-1);
and 4) a whole lapillus (polished on
one side WL-1).
Materials and methods
First increment formation
Six male and six female spot were
induced to spawn by injection of
human chorionic gonadotropin (HCG)
hormone at the NOAA Beaufort Labo-
ratory. Eggs were incubated in a 100-L
Manuscript submitted 14 May 2004 to the
Scientific Editors Office.
Manuscript approved for publication
29 March 2005 by the Scientific Editor.
Fish. Bull. 103:544-552 (2005).
NOTE Fey et al.: Effect of type of otolith and preparation technique on age estimation of Leiostomus xanthurus
545
tank at constant temperature (20°C) and salinity (30%<->),
under 12 h light:12 h dark photoperiod. These conditions
were maintained throughout the rearing period. Hatch-
ing occurred three days after spawning. Larvae were fed
rotifers throughout the experiment and supplemented
with enriched Artemia from day 20 through day 30.
Larvae were collected 4 days (n = 5), 12 days (n=7), and
27 days (n = 5) after hatching, and live total length (LT)
measurements were made. Larvae were then preserved
in 95% ethanol.
Sagittae and lapilli were dissected with fine-tipped
forceps and embedded on microscope slides. The incre-
ments were clearly visible and otoliths did not require
any additional preparation. All increment counts were
conducted three times by one person on different occa-
sions with a lOOx oil objective and a Nikon E600 micro-
scope with transmitted light. The light was polarized
to obtain better visibility. The reader did not know the
ages of the fish.
Known fish age and the number of observed incre-
ments were used to determine the time of first incre-
ment formation on both the sagittae and lapilli. The
number of increments deposited between sampling dates
divided by elapsed days indicated periodicity of incre-
ment formation.
Accuracy and precision
The experimental protocol and conditions were the same
as in the previous examination of first increment for-
mation, except that fish were reared for 53 days and
artificial diet was added after day 30. Larvae (?? =24,
8.8-16.1 mm LT, mean=11.8 mm LT) were collected 34
days after hatching, and juveniles (rc=34, 19.4-28.1 mm
LT, mean=24.3 mm LT) were collected 53 days after
hatching.
Sagittae and lapilli were dissected from fish with
fine-tipped forceps and embedded for sectioning on the
transverse plane (right sagitta) or polishing on the sag-
ittal plane (left whole sagitta and lapillus). Priority was
given to transverse sections, and if the right sagitta
was damaged during preparation, the left sagitta was
used (n = 8). Otoliths were sectioned with a slow-speed
saw with dual diamond wafering blades. Sections were
then ground on one side with 1000-grit sandpaper and
polished with 0.3-|i<m alumina paste. After increments
were counted on the proximal side of sections that were
polished on one side (see below for details), sections
were flipped over, ground, and polished to the core to
provide a section that was polished on two sides. The
left whole sagitta and lapillus were ground and polished
in the sagittal plane with 0.3-fjm alumina paste. One
person made all the increment counts three times for
each preparation technique on different occasions with
a lOOx oil objective on a Nikon E600 microscope with
transmitted light. The reader knew the study design,
but not the ages of the fish.
The mean number of increments counted from sagit-
tae and lapilli prepared with different techniques were
compared with known ages to determine the accuracy of
the different aging methods. The statistical significance
of differences in increment counts (accuracy) was evalu-
ated with a one-way ANOVA. Increment formation rate
was determined by comparing the number of increments
counted to known age, and by comparing the difference
in the number of increments between 34- and 54-day-
old fish and the number of actual days between these
increments (20 days).
Precision of increment counts from different otoliths
and preparation techniques was determined with the
coefficient of variation (CV), calculated by using the
three increment counts made for each individual type
of otolith and preparation technique (Chang, 1982). The
differences in CV values among the four age estima-
tion methods were analyzed by using a Kruskal-Wallis
ANOVA. The statistical significance of observed differ-
ences were estimated with a post hoc Tukey HSD for
unequal n test. All the statistical data analyses were
performed with Statistica 6.0 software (StatSoft Inc.,
Tusla, OK).
Results
First-increment formation
First-increment formation on the sagitta occurred at
hatching, but there may be problems in resolving incre-
ments near the core. Increment counts on sagittae were
variable for 4-day-old larvae. Four increments were
visible on the sagittae of one individual. The first incre-
ment was more pronounced than the others and was
interpreted as a hatching check. This increment was
approximately 8 f<m from the core. On the sagittae of
the remaining four 4-day-old larvae, only one increment
was visible corresponding to the location of the perceived
hatching check. Despite the apparent nondaily increment
formation in 4-day-old larvae, an average of 12.3 (range
12-13) increments were visible on the sagittae of 12-day-
old larvae, and an average of 26.5 (range 26-27) were
visible on the sagittae of 27-day-old larvae. The first
increment observed on the sagittae of 12- and 27-day-old
larvae corresponded to the location of the first increment
observed in the sagittae of 4-day-old larvae (Fig. 1).
First increment formation on the lapillus occurred
6-7 days after hatching. No increments were visible
on the lapilli of 4-day-old larvae. In older larvae, an
average of 6.4 (range 6-7) increments were observed
on 12-day-old larvae and an average of 20.3 (range
20-21) increments were observed on the lapilli of 27-
day-old larvae. Additionally, lapilli of 12 and 27-day
old larvae exhibited two checks in the area between
the otolith core and the first increment, but it was dif-
ficult to distinguish which check, if either, was formed
at hatching (Fig. 1).
Accuracy and precision
Increments were clearly visible regardless of otolith prepa-
ration technique (Fig. 2). Increment width increased from
546
Fishery Bulletin 103(3)
Daily increments
0 8.5 12.3
Otolith radius (urn)
Figure 1
Diagram describing hatching check deposition as well as initiation of daily otolith
increment formation in the sagittae and lapilli of spot [Leiostomus xanthurus) (A). Pho-
tographs of the otoliths of a 12-day-old larva: lapilli with six increments IB) and sagitta
with 12 increments (C). Scale bar = 8 iim. H = hatching check; FI = first increment.
the core towards the otolith edge. In both sagittal prepa-
rations, increment counts could not easily be made along
one radius owing to changes in the growth trajectories
(Fig. 2A) and to discontinuities in increment formation
(Fig. 2B). However, increment counts could be made along
one radius in the lapillus (Fig. 2C) — an advantage that
may facilitate measurements of otolith increment widths
in future studies.
A hatching check was identified in the sagittae of
34-day-old larvae and 54-day-old juveniles at a location
approximately 8.4 pm radius from the core (Table 1).
In addition to the hatching check, another well-defined
increment was observed in the core area of the sagittal
otoliths (Fig. 3A), and this second check was likely re-
lated to a dietary switch to exogenous feeding. In most
fish the second check was separated from the hatching
check by an average of 5.2 increments (t? = 49, SD = 0.59).
However, in some fish (n = 9), no increments were visible
between the hatching check and the other well-defined
increment. This observation indicates that there may be
problems resolving increments near the core, similar to
the results presented above regarding the timing of first
increment formation. Owing to the apparent problems
discerning increments near the core, the second check
was used as a starting point for increment counts. Us-
ing the second check as a starting point influenced ac-
curacy but provided a clear starting point for increment
counts in all sagittal otolith preparations.
In the lapilli, increment deposition began from a pro-
nounced check visible at ca. 12.3 urn radius from the
otolith core (Fig. 3B). This check was found at the same
distance from the core in lapilli of 12- and 27-day-old
larvae in the experiment on first-increment formation
(Table 1). Beginning increment counts from this check
would underestimate age by 6-7 days owing to the tim-
ing of first-increment formation on the lapilli.
NOTE Fey et al.: Effect of type of otolith and preparation technique on age estimation of Leiostomus xonthurus 547
"/
*
Figure 2
Otolith microstructure of an early-juvenile
laboratory-reared spot (Leiostomus xan-
thurus): (A) transverse section of the sagitta
(polished on two sides); (B) whole sagit-
ta (polished on one side); and (C) whole lapil-
lus (polished on one side). Scale bar = 30 um.
Increment formation occurred daily in both sagittae
and lapilli after the early larval period. The difference
in number of increments counted from sagittae and
lapilli from fish sampled 34 and 53 days after hatching
reflected the time elapsed between these two samplings
(Table 2) and indicated daily increment formation be-
tween the larval and early juvenile stage. The same
daily increment formation was also observed for larvae
sampled 12 and 27 days after hatching during the ex-
periment on first-increment formation (Table 2).
The accuracy of larval age estimates were similar for
all the sagittae and lapilli preparation methods (ANO-
0R
• U] S
, . '( 1 ■ '
ft!7i7fliKvfll kTh ff? m
B
% 1
^\ — 1 First
^vi — 1 increment
Figure 3
Central otolith area of early-juvenile labora-
tory-reared spot (Leiostomus xanthurus): (A)
transverse section of sagitta (polished on two
sides); five increments are visible between
hatching check (H) and, presumably, first feed-
ing check (FF); (B) whole lapillus (polished on
one side) with daily increments deposited after
the check was formed six days after hatching.
Scale bar = 10 i<m.
VA, P>0.05; Fig. 4A). For juveniles, however, there was
a significant difference in the number of counted incre-
ments among sagitta preparation methods (ANOVA,
P<0.001) (Fig. 4B). A lower number of increments were
enumerated from transverse sections of sagittae (with
one side polished) (post hoc: Tukey HSD for unequal n,
P<0.001). Moreover, -25% of otoliths within this group
were not readable.
All the otolith preparation techniques, except the PIS
transverse sections of sagitta from juveniles, underesti-
mated the age from hatching by 9-10 days. A 6-7 day
difference was expected between known age and lapilli
increment counts, owing to the time of first-increment
formation. Thus, actual fish age was underestimated by
approximately 2-4 days with lapilli increment counts. A
5-day difference was expected between known age and
548
Fishery Bulletin 103(3)
Table 1
The distance from otolith core to first increment in the sagitta (first increment formed on the first day after hatching
lapilli (first increment formed six days after hatching) of laboratory-reared spot iLeiostomus xanthurus).
) and in the
Otolith
n
Distance to the first increment (um)
Mean SD
Range
Sagittae — experiment on first-increment formation
Sagittae' — experiment on accuracy and precision of aging technique
Lapilli — experiment on first-increment formation
Lapilli — experiment on accuracy and precision aof aging technique
17
36
17
25
8.3 0.76
7.8 0.91
12.3 0.54
12.2 0.61
6.7-9.9
6.7-8.8
11.5-13.2
11.0-14.2
' Data for both whole sagittae (polished on one side) along sagittal view, and transverse sections of sagittae polished on two sides.
Table 2
Number of increments deposited on the otoliths of laboratory-reared spot (Leiostomu
parison with number of days between sampling days.
s xanthurus
) between
sampling days in corn-
Otolith
Sampling days
(days after hatching)
Days betweer
sampling
Number of increments
between sampling2
Sagittae — experiment on
first-increment formation
12 and 27
15
14.3
Sagittae' — experiment on accuracy
and precision of age determination
34 and 53
19
18.3
Lapilli — experiment on
first-increment formation
12 and 27
15
14.1
Lapilli — experiment on accuracy
and precision of age determination
34 and 53
19
18.6
' Data for both whole sagittae (polished on one side)
ind for transverse sections of sagittae (pol
shed on two sides).
2 No variance is given because the value re
presents difference between two average
increment
numbers obta
ined for two different groups offish.
whole-sagittae increments counts, owing to the initia-
tion of increments from a second check, which formed
approximately 5 days after hatching. With whole-sag-
ittae increment counts, actual fish age was underesti-
mated by approximately 5 days.
The coefficients of variation (CV), which indicates
the precision of age estimates, varied from 1.4% to
8.3% (Fig. 5). CVs were statistically different among
age estimation methods for both larvae and juveniles
(Kruskal-Wallis ANOVA, P<0.001). Lapilli from both
larvae and juveniles had lowest CVs, indicating high
precision. Whole sagittae and P2S transverse sections
for juveniles were comparable, but lower precision for
larvae was observed. However, if transverse sections
are used for aging, the preparation of both sides is
important in the case of larvae (with regard to preci-
sion; see Fig. 5) and mandatory in the case of juveniles
(with regard to accuracy; see Fig. 4B). In addition, the
confidence of the otolith reader in increment recognition
(Fig. 5) indicated that the most clear and easy to count
increments were found in the lapilli.
Discussion
First-increment formation
In prior studies, the age of larval and juvenile spot was
estimated by adding five days to the number of incre-
ments counted from sagittae (e.g., Warlen and Chester,
1985; Flores-Coto and Warlen, 1993; Ross, 2003). Our
research indicated that increment formation in sagit-
tae occurred at hatching. The only study validating
first-increment formation in spot used linear regres-
sion analysis for laboratory-reared fish (Peters et al.1).
The intercept of their regression line (age in relation to
number of increments) indicated that the first increment
Peters, D. S, Jr, J. C. DeVane, M. T. Boyd, L. C. Clements,
and A. B. Powell. 1978. Preliminary observations on feed-
ing, growth and energy budget of larval spot iLeiostomus
xanthurus). In Ann. Rep. Southeast Fish. Cent., Beaufort
Lab. to U.S. Dep. Energy, p. 377-397. Beaufort Laboratory,
National Marine Fisheries Service, Beaufort, NC.
NOTE Fey et al.: Effect of type of otolith and preparation technique on age estimation of Leiostomus xanthurus 549
Method (source of increment counts)
Sagittae
tranverse section
one-side polished
Sagittae
tranverse section
two-sides polished
Sagittae
whole
•i-' r
30
28
26
24
% 22
E
§ 20
c
o 54
a>
§ 52
* 50
48
46
44
42
40
32
(22) (22) (22)
1 2 3
B
(21) (21) (21)
(32) (32) (32)
(13) (13) (13)
12 3 12 3
Increment counts within method
Lapilli
whole
(19) (19) (19) (17) (17) (17) (23) (23) (23)
12 3 12 3 12 3
(27) (27) (27)
Figure 4
Age of laboratory-reared spot [Leiostomus xanthurus) estimated from
daily otolith growth increments counted at three different occasions
for each preparation method: (A) larvae (34 d, 11.8 mm LT); and (B)
juveniles (53 d, 24.3 mm LT). Mean and 95% confidence interval
minimum, and maximum values are presented. Values in parentheses
indicate sample number. Dashed line indicates the real age.
formed five days after hatching, which corresponds to
a time of exogenous feeding initiation in spot (Powell
and Gordy, 1980; Powell and Chester, 1985). The other
validation experiments on spot (Hettler, 1984; Siegfried
and Weinstein, 1989) provided no information on first
increment deposition time. In lapilli, increment depo-
sition occurred six days after hatching, but no other
studies are available for spot to compare and evaluate
these results.
The inconsistency in the time of first increment for-
mation on the sagittae between the present study and
Peters et al.'s study1 may be the result of underestima-
tion by the latter because they did not section or pol-
ish the otoliths. Spot otoliths are relatively large and
thick and both sagittae and lapilli are difficult to read
without otolith preparation for fish older than 25-30
days (-7-9 mm TL). Peters et al.1 found no increments
in sagittae of four- to five-day-old fish. Although in
the present study increments were not clear in sagit-
tae of four-day-old spot, fish collected from the same
tanks, 8 and 23 days later, had visible increments
since hatching. Even if it is difficult to explain why
the increments in sagittae of four-day-old-fish were not
visible, results presented in the present study support
the conclusion that first increment formation occurred
at hatching.
550
Fishery Bulletin 103(3)
s?
7
r
o
6
10
<0
>
5
o
*~
4
•V
o
3
11)
o
o
■A
1
£
(•)
(..) (....)
B
I
1
(-) (*•) (—) (•
TSS-1 TSS-2 WS-1 WL-1 TSS-1 TSS-2 WS-1 WL-1
Method (source of increment counts)
Figure 5
Precision evaluation for different aging methods employed for larval
(A) and early-juvenile (B) laboratory-reared spot: transverse section of
sagitta (polished on one side) (TSS-1), transverse section of the sagitta
(polished on two sides) (TSS-2), whole sagitta (polished on one side) (WS-1),
and a whole lapillus (polished on one side) (WL-1). The coefficients of
variation (CV) values were calculated for three independent increment
counts per otolith. Additionally, the confidence of the otolith reader in
increment recognition has been indicated by numbers of stars, i.e., poor
(*), relatively good (**), good (***), and very good (****).
Accuracy and precision of age estimates among
different types of otoliths and preparation techniques
Lack of distinct patterns in daily growth increments
in otoliths of laboratory-reared fish (e.g., David et al.,
1994) could make it difficult to conduct laboratory-
based ecological experiments with larval fish. Hettler
(1984) attempted to validate increment formation rate
in the sagittal otoliths of laboratory-reared spot (13-
16 mm SL). Within eight days after tetracycline mark-
ing, otolith radii increased approximately 18%, but no
increments were observed. Siegfried and Weinstein
(1989) confirmed daily increment formation in the sag-
ittae of field-reared spot larvae, but those reared in
the laboratory produced 17 increments instead of the
expected 30. Our results, on the other hand, provided
direct validation of daily increment formation in the
sagittae and lapilli of laboratory-reared spot (Table 2).
Even though increment formation was found to occur
daily, there were inaccuracies in the estimate of age
from otolith increment counts. Twenty-four increments
were counted on the sagittae of 34-day-old larvae; if
five increments were added for time between first-incre-
ment formation and formation of the second check (the
starting point of counts used in the present study), age
was still underestimated by 4-5 days. Similarly, 24
increments were counted on the sagittae of 34-day-old
larvae; if 6-7 days were added to account for the tim-
ing of increment formation in the lapillus, age was un-
derestimated by 3-4 days. Similar inaccuracies in age
estimates were derived for 53-day-old juveniles. Peters
et al.1 also found age inaccuracies of five days from
sagittal increments and concluded that first-increment
formation occurred five days after hatching. Given our
results and those of Hettler (1984) and Siegfried and
Weinstein (1989), we conclude that the likely explana-
tion for age inaccuracies is that the increments near
the core of the otolith become harder to read as more
otolith material is laid down and this process results in
the appearance of fewer increments. These inaccuracies
would contribute to a 10-15% underestimation of age
from sagittae and a 3-11% underestimation of age from
lapilli. To account for these inaccuracies, five increments
should be added to increment counts to estimate age.
Lapilli, compared with sagittae, exhibited very clear
patterns with increments (Fig. 2) and provided more
precise results for the ages of larval and juvenile spot.
Although there is no study presenting age data obtained
from lapilli for larval or juvenile spot, lapilli have been
used successfully for aging many other fish species.
Ichimaru and Katsunori (1995) preferred the lapillus
as a source of age data for two species of flyingfishes
larvae (Cypselurus heterurus doederleini and Cypselurus
hiraii) because increments were as clear as those in the
sagittae, yet the lapilli did not require any preparation.
Bestgen and Bundy (1998) reported increments depos-
ited on sagittae of Colorado squawfish (Ptychocheilus
lucius) were difficult to distinguish after fish were 30
days old and thus lapilli were used to age older fish.
Lapilli were the preferred otoliths for age determination
of young Lost River sucker (Deltistes luxatus) and short-
nose sucker (Chasmistes brevirostris) because of their
readability and conservative growth pattern (Hoff et
al., 1997). Escot and Grando-Lorencio (1998) concluded
NOTE Fey et al.: Effect of type of otolith and preparation technique on age estimation of Leiostomus xanthurus
551
that increments in lapilli of Barbus sclateri (Pisces: Cy-
prinidae) were more clearly defined than in sagittae and
asterisci. Similarly, our results demonstrate the utility
of lapilli for larval and juvenile fish age estimates.
In addition to the choice of the most suitable type of
otolith, the choice of the most appropriate preparation
method is an important aspect of larval and juvenile
fish age determination (Secor et al., 1992). Analysis
of PIS whole sagittae provided in the current study
similar precision and confidence in age determination
as transverse sections. Although analysis of sagittal
transverse sections have been applied to spot ( Siegfried
and Weinstein, 1989), the most frequently used method
has been the analysis of whole sagittae in sagittal view
(Hettler, 1984; Warlen and Chester, 1985; Powell et al.,
1990; Flores-Coto and Warlen. 1993; Ross, 2003). Re-
cently, Ross (2003) was able to age 40-160 day-old spot
juveniles, analyzing whole sagittae along the sagittal
view; however, polishing on both sides was frequently
necessary. For whole lapilli, however, only one prepara-
tion method (i.e., polishing along the sagittal plane) was
used in the present study and the results were more
satisfactory then those obtained for sagittae and hence
no other preparation method (i.e., sectioning) seemed
to be required.
In conclusion, first-increment formation occurs at
hatching in the sagittae and at 6-7 days after hatching
in the lapilli. Increment formation rate occurs daily in
both the sagittae and the lapilli. With sagittal and lapil-
lar increment counts, age was underestimated and the
cause appeared to be difficulty in discerning increments
near the core. Whole lapilli (prepared by polishing one
side along the sagittal section) provided age accuracy
similar to that of the three sagittal preparations, but
higher precision. Future studies would benefit from us-
ing the lapillus for ecological studies of the early life
history of spot.
Acknowledgments
The authors thank Elisabeth Laban for consultation
during otolith preparation and analysis, as well as Dean
Ahrenholz and Jennifer Potts for reviewing the earlier
version of the manuscript. This research was performed
while the first author held a National Research Council
Research Associateship Award at the NOAA Beaufort
Laboratory.
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553
Preliminary use of oxygen stable isotopes and
the 1983 El Nino to assess the accuracy of
aging black rockfish (Sebastes melanops)
Kevin R. Piner
Southwest Fisheries Science Center
National Marine Fisheries Service, NOAA
8604 La Jolla Shores Drive
La Jolla, California 92037
E-mail address Kevin. Pinena'noaa. gov
Melissa A. Haltuch
School of Aquatic and Fishery Sciences
University of Washington,
1122 NE Boat Street
Seattle. Washington 98105
John R Wallace
Northwest Fisheries Science Center
National Marine Fisheries Service,
2725 Montlake Blvd East
Seattle, Washington 98112
(Campana, 2001). Recently, stable
oxygen isotopes from Pacific halibut
(Hippoglossus stenolepis) otoliths
were used to examine regime shifts
in the Northeast Pacific for the iden-
tification of changes in bottom wa-
ter temperatures (Gao and Beamish,
2003). In addition, otolith chemistry
may be used to identify environmen-
tal events that serve as natural tags
for such studies (Campana and Thor-
rold, 2001). We used a strong region-
al environmental event, the 1983 El
Nino, as a time marker to judge the
accuracy of age assignment for black
rockfish <15 years of age. The 1983
El Nino produced anomalously warm
oceanic conditions along the coast-
lines in the eastern Pacific; therefore
the stable oxygen isotope ratio from
1983 should reflect this change in
oceanic conditions.
Materials and methods
Black rockfish (Sebastes melanops)
range from California to Alaska and
are found in both nearshore and shal-
low continental shelf waters (Love et
al., 2002). Juveniles and subadults
inhabit shallow water, moving deeper
as they grow. Generally, adults are
found at depths shallower than 55
meters and reportedly live up to 50
years. The species is currently man-
aged by using information from an
age-structured stock assessment
model (Ralston and Dick, 2003).
In many studies, ages are assumed
to be accurate and there is no effort
to validate the accuracy of the ages
(Beamish and McFarlane, 1983). Re-
cent methods of age validation rely
upon environmental events that serve
as time markers (Campana, 2001).
Bomb radiocarbon released during
nuclear bomb testing has been used
to validate fish ages (Kalish et al.,
1996; Campana, 1997; Kalish et al.,
1997). Unfortunately, bomb radiocar-
bon can be used only for fish that
lived during the informative period
(-1960-70); thus the technique has
been used primarily on older ages.
For many stock assessments, the
validation of younger ages is more
critical because of their importance
in estimating vital rates, such as
growth and maturity schedules.
In this note we apply the well-
studied relationship between water
temperature and the ratio of oxygen
stable isotopes in otoliths to assess
the accuracy of young black rockfish
ages. Oxygen isotope ratios serve as
a record of past water temperatures
because the isotope ratio is incorpo-
rated into the otolith in near equi-
librium with the ratio found in the
environment (Patterson et al., 1993;
Thorrold et al., 1997) and ambient
water temperatures are inversely cor-
related with 180/160 ratios (Gao et
al., 2001). Calcified structures have
a strong history of being used in en-
vironmental reconstructions based on
incorporated trace elements and iso-
topes (Chivas et al., 1985; Holmden
et al., 1997). Otolith microchemistry
has been used to successfully recon-
struct the environmental history of
fish and to answer questions about
natal homing (Thorrold et al., 2001)
and population mixing (Campana et
al.. 1999). Variation in oxygen iso-
topes has been used to confirm vi-
sually observed growth increments
We obtained nine pre-aged black rock-
fish otoliths collected during 1987-91
from recreationally caught fish off
Cape Lookout, Oregon (~45.25°N,
145°W), from approximately 15-30
m water depth. One otolith was aged
by Oregon Department of Fish and
Wildlife scientists by using the tra-
ditional break-and-burn method; the
matching otolith was used in the
stable isotope analysis. Fish from a
range of years and ages (Table 1) were
selected to include the 1983 El Nino
year. A time series of annual summer
bottom water temperatures from the
same region and depth where the
black rockfish otolith samples were
obtained, were provided by the Pacific
Hindcast from the Columbia Univer-
sity International Research Institute
for Climate Prediction, Palisades,
New York.
To estimate the year containing
the warmest oceanic conditions, we
examined otolith material from all
opaque growth zones within each oto-
lith for oxygen isotopes (180/160) and
Manuscript submitted 13 February 2004
to the Scientific Editor's Office.
Manuscript approved for publication
8 February 2005 by the Scientific Editor.
Fish. Bull. 103:553-558 (2005).
554
Fishery Bulletin 103(3)
Table 1
Age-specific o^O values for each black rockfish tSebastes
by "N/A" indicates samples that were not reported by the
melanops), along with annulus age
stable isotope laboratory.
and collection year. Values replaced
Age
Sample number
1987-33
1987-86
1987-98
1988-7
1988-100
1991-27
1991-86
1991-168
1991-178
0+
-0.96
N/A
-0.633
-0.357
1.209
N/A
-0.128
-2.06
0.756
1+
-1.17
0.914
-0.981
-0.513
0.725
-0.53
-0.114
-1.77
0.948
2 +
-0.42
0.654
-0.644
-0.504
-0.544
-0.42
-0.358
-1.09
0.869
3 +
-0.04
0.461
-0.518
-0.579
1.037
-0.39
-0.409
-0.64
0.741
4 +
0.42
1.006
-0.202
-0.320
N/A
-0.09
-0.082
-0.85
0.338
5 +
0.28
0.946
-0.037
-0.257
N/A
-0.22
-0.218
-0.73
N/A
6+
0.957
0.630
0.137
N/A
-0.05
0.1067
0.35
0.785
7+
0.962
1.0
0.512
1.08
1.054
8+
N/A
0.805
1.07
1.113
9+
N/A
1.053
N/A
1.404
10 +
N/A
1.164
N/A
1.510
11+
N/A
1.881
Annulus
age
(yr)
6
7
7
8
7
12
12
11
11
Collection year
1987
1987
1987
1988
1988
1991
1991
1991
1991
assigned to a year of formation based on estimated age
and capture year. Chemical assay and otolith processing
were completed at the Stable Isotope Laboratory of the
University of Michigan. Each otolith was embedded in
epoxy resin and cut transversally with a low-speed dia-
mond-bladed saw. Three or four thin sections -150 /urn
thick were removed from the center of each otolith. The
thin sections were then glued with cyanoacrilate glue
to petrographic glass slides. Samples from multiple thin
sections were combined for a single assay. Each opaque
growth zone was sampled by using a Merchantek Micro-
milling system and assays were completed with a Finni-
gan 251 MAT mass spectrometer. All measurements
were reported in standard Vienna Pee Dee Belemnite
(VPDB) and notation as 6%c (per mil), where
<S180
:(((180/160
sample
/(
'O/I6O)standard)-lxl000).
A time series of 6180 was constructed for each fish by
using the assay from each year-specific sample of the
otolith material. Assay results from the collection year
were not included because of differences in the season
of capture. Years with missing results were due to
micromilling or assay errors that resulted in no results
reported by the stable isotope laboratory.
To gauge the accuracy of age assignments, we fitted
a linear model to each time series and analyzed the
residuals from the linear model fit. The <31kO value cor-
responding to the negative residual of greatest magni-
tude from that linear model would be associated with
the anomalously warmest oceanic conditions (El Nino).
If the age assignments were correct, that portion of the
otolith corresponding to 1983 would have the negative
residual of greatest magnitude because the observed
dlsO value was much lower than the linear model pre-
dicted. Temporal shifts of the most anomalous negative
residual with respect to 1983 were interpreted as either
an under- or over-estimation of age.
A randomization procedure (20,000 iterations) was
used to determine if the magnitude of the average re-
sidual in any year was more negative than expected,
thus identifying the signal associated with the 1983
El Nino. The residuals from the linear models within
each of the fish were randomized with respect to year.
Randomized residuals from all iterations were averaged
across all fish to produce a distribution of averages. The
original year-specific residual averages were compared
to the randomization distribution to estimate statis-
tical significance. We rejected the hypothesis of any
year with an average residual 2O if less than 5% of the
randomizations produced a negative average residual
of equal or greater magnitude than the observed year-
specific average residual, thus identifying anomalously
warm years.
An iterative sensitivity analysis was performed by
retrospectively removing sequential blocks of years of
data and by estimating the statistical significance of
the originally determined anomalous years with the re-
duced data sets. All data taken from years more recent
that the cutoff year were removed, and the linear model
fitting and randomization procedures were recalculated.
The cutoff year was sequentially changed beginning
with 1989 to 1986.
NOTE Piner et al : Use of oxygen stable isotopes and the 1983 El Nino to assess accuracy of aging Sebastes melanops
555
12.5 ■
12.0 •
A
11.5 ■
/ \
P 11.0 -
/\J \ f~~
10.5 ■
J \Z~ *^\
10.0 ■
9.5
V*
i i i i i i
1979 1981 1983 1985 1987 1989 1991
Year
Figure 1
Average summer water temperatures (May-
Sep) from Cape Lookout, Oregon.
Table 2
Results of the retrospective analysis that estimated the
statistical significance of the magnitude of the average
negative residual from the years 1983 and 1985. Assay
results from otolith material formed after the cutoff year
were removed from the randomization analysis.
Results
The period 1980-90 was characterized by an isolated
and historically strong 1983 El Nino event (Fig. 1), that
resulted in a 1-2°C increase in water temperatures
along the Oregon coast. Average summer water tempera-
tures declined slightly over this period. The olsO values
measured in each fish resulting from this period (Table
1) showed strong patterns that indicated temperature
differences both within fish (between years) and between
fish (same year). In addition, many fish contained trends
in 6180 across time (Fig. 2). Precision of the reported
6180 measurements ranged from 0.01 to 0.079cc (SD).
The residual patterns (Fig. 3A) showed that anoma-
lously warm conditions existed in otolith material cor-
responding to those of 1983 («=9, P=0.0338) and 1985
(ti=7, P=0.0409). Both old (ages 11-12) and young (ages
6-8) fish appeared to have similar temporal patterns
of residuals; however in older fish this pattern shifted
by 1-2 years toward more recent years (Fig. 3B). The
year-specific averaged residuals of the age 6-8 fish de-
picted a single anomalously warm year corresponding
to 1983. The anomalously warm year in the age 11-12
fish was 1984-85, thus explaining the significance re-
sult in 1985. The results of the randomization test were
not sensitive to the exclusion of data from the four most
recent years (Table 2).
Discussion
The location of the anomalously warm signal in 1983,
in the youngest and likely the more accurately aged
fish, supports the hypothesis that the 1983 El Nino can
be detected by using oxygen stable isotopes. From this
analysis, we concluded that the break-and-burn aging
method is accurate on average but has a potential ten-
dency toward underaging fish >10 years.
Confirmation of the annual banding pattern in the
ololiths of other Sebastes species has been accomplished
by using a variety of methods. Woodbury (1999) con-
firmed the accuracy of age assignment in widow {Se-
bastes entomelas) and yellowtail (S. flavidus) rockfish,
using the change in growth increment width associated
with El Nino. Piner et al. (in press) has used bomb ra-
diocarbon to confirm the annual pattern of otolith band-
ing in canary rockfish (S. pinniger) and has reported a
possible underaging bias for older fish. Andrews et al.
(1999) used radiometric age determination to confirm
the longevity of long-lived species. However, a larger
study on black rockfish with stable isotopes is necessary
to conclusively determine age estimates accurately and
potential underaging bias.
The 1983 El Nino was chosen for the present study
because it was one of the strongest recorded in the
century (Sharp and McClain, 1993). Warm water condi-
tions associated with the 1983 El Nino were sufficient
to slow growth (MacLellan and Saunders, 1995; Wood-
bury, 1999) and alter reproductive patterns (VenTresca
et al., 1995) in species occupying similar geographic
ranges. In contrast, this study attempted to indirectly
measure the environment experienced by black rock-
fish without the need to infer changes to biological
processes. Nevertheless, our results appear to support
the conclusions of MacLellan and Saunders (1995) and
Woodbury (1999) that the anomalous oceanic conditions
in 1983 are identifiable.
The analysis of model residuals rather than raw iso-
tope ratios is more appropriate because of the obvious
d^O temporal trend in some samples. Otolith process-
ing difficulties also may have contributed to the trend.
The opaque region of the otolith decreases in size with
increasing age. The narrowing of the otolith region as-
sociated with older ages made precise sampling more dif-
ficult and may have resulted in accidental sampling from
otolith material outside the opaque region. The sampling
of otolith material from outside the opaque region may
have contributed otolith material formed in cooler waters
in contrast to the sampling of areas of the otolith associ-
ated with younger ages. The increasing trend in &H0 was
not explained solely by the decreasing temporal trend of
summer water temperatures. However, an additional com-
ponent of that trend may be the result of age-dependent
fish movement to cooler waters that are deeper or more
556
Fishery Bulletin 103(3)
ID
CQ
>
o
1991-27
1991-86
.
0
q ^-"0
1
■"*
2
1987-98
1991-168
1
•
0
1
p
D
a
6 D D
2
1988-7
1991-178
1988-100
1.0
0.5
0.0
-0.5
-1.0
1.0
0.5
0.0
-0.5
-1.0
1.0
0.5
0.0
-0.5
-1.0
1.0
0.5
0.0
-0.5
-1.0
1978 1980 1982 1984 1986 1988 1990
0.5
00
-0.5
-1 0
1978 1980 1982 1984 1986 1988 1990
Year
Figure 2
The time series of 6180 (•, and left axis) and the linear model residuals
(□, and right axis) taken from each black rockfish [Sebastes melanops)
otolith used in the present study. The solid line is the linear model fit to
the 6180 data. A residual value of zero indicates perfect agreement between
observed and predicted year-specific average residuals. Sample numbers
corresponding to Table 1 are given inside each graph.
northerly. Furthermore, the isotope variability between
fish may be due to fish inhabiting different areas in the
early periods of life or to temporal differences in growth.
Finally, changes in calibration of the spectrometer be-
tween assays may be a source of uncertainty.
A critical assumption behind the present study was
that the lowest 6180 corresponds to the warmest water
temperature, and consequently the 1983 El Nino that
serves as the time marker. The 6180 values may be
impacted by salinity in addition to water temperature
(Dorval, 2004), and we assumed that salinity was con-
stant and that the changes in <5180 values were largely
influenced by changes in temperature. A further con-
founding element to this kind of study is the ability of
fish to move and potentially select microhabitats with
different temperatures than that of the average local
environment. Natural date-specific markers also must
be monitored over a number of years to ensure that
they remain identifiable within the otolith (Campana,
2001). We addressed this concern by selecting fish of
NOTE Piner et al : Use of oxygen stable isotopes and the 1983 El Nino to assess accuracy of aging Sebastes melanops 557
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
1978 1980 1982 1984 1986 1988 1990 1992
a
| 0.6 •
<
0.4
0.2
0.0
-0.2 ■
-0.4 •
-0.6
-0.8
1978 1980 1982 1984 1986 1988 1990 1992
Year
Figure 3
The year-specific average model residual from (A) all
nine black rockfish (Sebastes melanops) and (B) ages
6-8 (•, solid line) and ages 11-12 (D, dashed line) fish.
Error bars are ±1 SE.
various ages and from various collection dates and by
performing the same analysis on each fish. Lastly, this
method of age validation can be difficult to implement
for fish with small otoliths or for long-lived fish be-
cause of the difficulties in obtaining sufficient otolith
material from small growth increments.
The detection of El Nino events using oa80 may allow
the use of this reoccurring climatic event as a natural
tag for age validation. Because previous studies that
used El Nino events as time markers were forced to
measure biological reactions to environmental chang-
es, the use of dmO may be an improvement because it
avoids assuming the intermediate step, namely that
environment affects a biological process. The results
from this study, however, were based on a small sample
size and are, therefore, only preliminary. Further work
in this area is warranted.
Acknowledgments
We are grateful to Maria Marcano of the University of
Michigan geochemical laboratory for her help in setting
up the assays. Bill Miller of the Oregon Department of
Fish and Wildlife provided aging expertise.We thank
the Sea Grant Fellowship in Population Dynamics and
the National Marine Fisheries Service Northwest Fish-
eries Science Center for financial support. Finally, the
anonymous reviewers and Christian Reiss greatly helped
our efforts.
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U.S. Department
of Commerce
Volume 103
Number 4
October 2005
Fishery
Bulletin
U.S. Department
of Commerce
Carlos M. Gutierrez
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
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Volume 103
Number 4
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Fishery
Bulletin
Contents
Articles
N0>/ 0 2 2005
561-573 Kingsford, Michael J., and Julian M. Hughes
Patterns of growth, mortality, and size of the tropical
damselfish Acanthochromis polyacanthus across
the continental shelf of the Great Barrier Reef
574-587 Kotwicki, Stan, Troy W. Buckley, Taina Honkalehto,
and Gary Walters
Variation in the distribution of walleye pollock
(Theragra chalcogramma) with temperature
and implications for seasonal migration
588-600 Luthy, Stacy A., Robert K. Cowen, Joseph E. Serafy,
and Jan R. McDowell
Toward identification of larval sailfish Ustiophorus platypterus),
white marlin (Tetrapturus albidus), and blue marlin
(Makaira nigricans) in the western North Atlantic Ocean
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
(NMFSl 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.
601-619 McDonough, Christopher J., William A. Roumillat,
and Charles A. Wenner
Sexual differentiation and gonad development in striped
mullet (Mugil cephalus L.) from South Carolina estuaries
620-634 Megalofonou, Persefoni, Constantinos Yannopoulos,
Dimitrios Damalas, Gregorio De Metrio, Michele Deflorio,
Jose M. de la Serna, and David Macias
Incidental catch and estimated discards of pelagic sharks from
the swordfish and tuna fisheries in the Mediterranean Sea
635-647 Narimatsu, Yoji, Daiji Kitagawa, Tsutomu Hattori,
and Hirobumi Onodera
Reproductive biology of female Rikuzen sole
(.Dexistes nkuzenius)
Fishery Bulletin 103(4)
648-658 Porter, Steven M.
Temporal and spatial distribution and abundance of flathead sole (Hippoglossoides elassodon)
eggs and larvae in the western Gulf of Alaska
659-669 Prince, Eric D., Robert K. Cowen, Eric S. Orbesen, Stacy A. Luthy, Joel K. Llopiz, David E. Richardson,
and Joseph E. Serafy
Movements and spawning of white marlin (Tetrapturus albidus) and blue marlin (Makaira nigricans)
off Punta Cana, Dominican Republic
670-684 Stanley, Richard D., and Allen R. Kronlund
Life history characteristics for silvergray rockfish (Sebastes brevispmis) in British Columbia waters
and the implications for stock assessment and management
685-696 Weise, Michael J., and James T. Harvey
Impact of the California sea lion (Zalophus californianus) on salmon fisheries in Monterey Bay, California
697-711 Welsford, Dirk C, and Jeremy M. Lyle
Estimates of growth and comparisons of growth rates determined from length- and age-based models for
populations of purple wrasse (Notolabrus fucicola)
Notes
712-719 Bishop, Melanie J., Charles H. Peterson, Henry C. Summerson, and David Gaskill
Effects of harvesting methods on sustainability of a bay scallop fishery: dredging uproots seagrass
and displaces recruits
720-724 Diaz, Guillermo A., and Joseph E. Serafy
Longline-caught blue shark (Pnonace glauca). factors affecting the numbers available for live release
725-727 Fey, Dariusz P., and Jonathan A. Hare
Length correction for larval and early-|uvenile Atlantic menhaden (Brevoortia tyrannus) after preservation
in alcohol
728-736 Hare, Jonathan A., and John J. Govoni
Comparison of average larval fish vertical distributions among species exhibiting different transport pathways
on the southeast United States continental shelf
737 Acknowledgment of reviewers
738 List of titles
741 List of authors
743 List of subjects
747 Subscription form
561
Abstract — Age-based analyses were
used to demonstrate consistent dif-
ferences in growth between popula-
tions of Acanthochromis polyacanthus
(Pomacentridae) collected at three dis-
tance strata across the continental
shelf (inner, mid-, and outer shelf)
of the central Great Barrier Reef
(three reefs per distance stratum).
Fish had significantly greater max-
imum lengths with increasing dis-
tance from shore, but fish from all
distances reached approximately the
same maximum age, indicating that
growth is more rapid for fish found
on outer-shelf reefs. Only one fish col-
lected from inner-shelf reefs reached
>100 mm SL, whereas 38-67% offish
collected from the outer shelf were
>100 mm SL. The largest age class of
adult-size fish collected from inner-
and mid-shelf locations comprised
3-4 year-olds, but shifted to 2-year-
olds on outer-shelf reefs. Mortality
schedules iZ and S) were similar irre-
spective of shelf position (inner shelf:
0.51 and 60.0%; mid-shelf: 0.48 and
61.8%; outer shelf: 0.43 and 65.1%,
respectively). Age validation of captive
fish indicated that growth increments
are deposited annually, between the
end of winter and early spring. The
observed cross-shelf patterns in adult
sizes and growth were unlikely to be
a result of genetic differences between
sample populations because all fish
collected showed the same color
pattern. It is likely that cross-shelf
variation in quality and quantity of
food, as well as in turbidity, are fac-
tors that contribute to the observed
patterns of growth. Similar patterns
of cross-shelf mortality indicate that
predation rates varied little across
the shelf. Our study cautions against
pooling demographic parameters on
broad spatial scales without consid-
eration of the potential for cross-shelf
variability.
Patterns of growth, mortality, and size
of the tropical damselfish
Acanthochromis polyacanthus across
the continental shelf of the Great Barrier Reef
Michael J. Kingsford
Julian M. Hughes
Reef and Ocean Ecology Laboratory
School of Marine Biology and Aquaculture
James Cook University
James Cook Drive
Townsville, Queensland, Australia 4811
E-mail address (for M J Kingstord) Michael Kingsforda<|cii edu au
Manuscript submitted 10 June 2004
to the Scientific Editor's Office.
Manuscript approved 30 March 2005
by the Scientific Editor.
Fish. Bull. 103:561-573 120051.
Coral reefs are spatially diverse and
heterogeneous marine environments.
The Great Barrier Reef (GBR) is the
largest reef system and represents a
near-continuous matrix of over 2400
individual reefs spanning a distance
of some 2000 km along the coast of
Queensland, eastern Australia (Fig.
1). Coral reef habitats are subject to
the influences of environmental (e.g.,
exposure and proximity to coastlines),
as well as biotic processes (e.g., avail-
ability of food). Strong cross-shelf abi-
otic and biotic gradients (Wilkinson
and Cheshire, 1988) have the potential
to influence patterns of abundance
and demographic characteristics of
fishes associated with coral reefs. Sev-
eral studies have examined the broad-
scale abundance and distribution of a
wide variety of organisms across the
continental shelf of the GBR, includ-
ing hard corals (Done, 1982), soft
corals (Dinesen, 1983), crustaceans
(Preston and Doherty, 1990, 1994),
algae (McCook et al., 1997), and reef
fishes (Williams, 1982, 1983; Wil-
liams and Hatcher, 1983; Russ, 1984a,
1984b; Newman and Williams, 1996;
Newman et al., 1997; Gust et al., 2001,
2002). Great cross-shelf differences in
abundance are common within and
among taxa. Although environmental
gradients have often been implicated
as causing these patterns and it is also
known that environmental features
influence demographic characteris-
tics (e.g., growth), there have been few
comparisons of demographic charac-
ters by geography and spatial scale.
Demographic measures are cru-
cial to understanding population
dynamics. Population demographics
of a number of many fish species have
been shown to vary at spatial scales
ranging from 100's of m to 100's of km
(Gillanders, 1995; Meekan et al.,
2001; Gust et al., 2002). With the ex-
ception of data on a few commercially
important taxa (Munro and Williams,
1985; Williams et al., 2003) and some
others (e.g., acanthurids and scarids;
Choat and Axe, 1996), there are few
data on demographic parameters of
coral reef fishes and even less on
spatial variation within these para-
meters. Variation in demographics
may be common across the shelf.
For example, significant differences
in the size frequency, growth, mor-
tality, and longevity in populations
of three scarids (Scarus frenatus, S.
niger, and Chlorurus sordidus) and
an acanthurid (Acanthurus lineatus)
have been shown between mid- and
outer-shelf locations on the northern
GBR (Gust et al., 2001, 2002). Dud-
geon et al. (2000) found evidence that
high levels of genetic exchange oc-
curred between populations of these
fishes on mid- and outer-shelf reefs
and concluded that observed differ-
562
Fishery Bulletin 103(4)
Distance strata and i
Reef near Townsville
polyacanthus.
Table 1
eefs sampled during September and October 2001 over the continental shelf of the central Great Barrier
Australia, for analyses of growth patterns, mortality, and size of the tropical damselfish Aeanthochromis
Distance
strata
Reef sampled
Date(s) sampled
Av
?rage distance (km) to coast
of the three sites ±SE
Inner shelf
Orpheus Island
Pandora Reef
Havannah Island
4 and 5 Sep 2001
3 Sept 2001
3 and 4 Sep 2001
15.3 ±0.6
16.4 ±0.3
25.1 ±0.3
Mid-shelf
Bramble Reef
Britomart Reef
The Slashers
15 Oct 2001
16 Oct 2001
20 Oct 2001
41.1 ±0.5
38.7 ±3.0
85.3 ±2.4
Outer shelf
Pith Reef
Barnett Patches
Myrmidon Reef
18 Oct 2001
17 Oct 2001
19 Oct 2001
74.4 ±0.9
62.6 ±1.8
110.4 ±0.8
ences in the demographic and life history features rep-
resented phenotypic plasticity.
Aeanthochromis polyacanthus (Bleeker) is one of a
few species of fish that are found in abundance at all
distances across the Great Barrier Reef (Williams.
1982, 1983) and, therefore, was ideal for comparisons
of cross-shelf patterns of demographic characteristics.
Aeanthochromis polyacanthus is a polymorphic gono-
choristic pomacentrid and site-attached planktivore
that inhabits reefs of the Indo-Australian Archipelago
and adjacent regions (Allen, 1975). It is extremely wide
spread and abundant along (north-south) the GBR (Wil-
liams, 1982, 1983). It is unusual among marine reef
fishes and unique among damselfishes in that it lacks
a dispersive planktonic larval stage (Robertson, 1973).
Instead, adult A. polyacanthus lay demersal eggs and
after hatching, both parents defend a brood of larvae
and juveniles for several months (Robertson, 1973; Al-
len. 1975; Thresher, 1985a, 1995b; Kavanagh, 2000).
In contrast to other taxa, therefore, dispersal is likely
to be slow within and among reefs. Aeanthochromis
polyacanthus is one of the best studied coral reef fishes
on the GBR with respect to predation (Connell, 1996,
1998, 2000), genetics and evolution (Doherty et al.,
1994, 1995; Planes and Doherty, 1997a, 1997b), be-
havior (Robertson, 1973; Allen, 1975; Thresher, 1985a.
1995b; Nakazono, 1993; Kavanagh, 1998), reproductive
success (Thresher, 1983). and early life history (Ka-
vanagh, 2000), but no data exist on age, growth, and
demographic parameters, such as mortality rates (but
see estimates of juvenile mortality while larvae and
juveniles are brooded by adults; Connell, 1996).
The objective of this study was to compare the demo-
graphic characteristics of A. polyacanthus across the
continental shelf. Our approach was to sample replicate
reefs in the central region of the GBR at multiple dis-
tance strata from shore (inner-, mid- and outer-shelf
distances). In addition, we chose a section of the GBR
where A. polyacanthus exhibited the same color pattern
(brown anterior and white posterior) and are known
to be genetically isolated (Planes and Doherty, 1997b).
Any variation in demographic parameters, therefore,
could be largely attributed to phenotypic plasticity. The
specific objectives of this study were the following: 1) to
validate the deposition of annual growth increments for
fish of a wide range of sizes and ages by using tetracy-
cline, 2) to describe patterns of growth of populations
of A. polyacanthus within and among distance strata; 3)
to describe the age and size structures of populations of
A. polyacanthus within and among distance strata, and;
4) to calculate the instantaneous mortality and survival
rates (Z) of populations of A. polyacanthus within and
among distance strata.
Materials and methods
Study sites and sampling design
Spatial variation in demographics and structures of
cross-shelf populations of A. polyacanthus was deter-
mined by using a partially hierarchical sampling design.
Individuals of a wide range of sizes were collected from
three replicate reefs within each of three distance strata
(inner-, mid- and outer-shelf) spanning the width of the
continental shelf of the central Great Barrier Reef near
Townsville, Australia (Fig. 1, Table 1). At least 16 fish
were collected with hand spears from each of three sites
on each reef during September and October 2001. All
fish collected were the same brown and white morph
(Allen, 1975).
Sample processing
All fish were measured (standard length [SL] to the
nearest mm) and weighed (to the nearest 0.01 g). Sag-
ittal otoliths were extracted, cleaned in freshwater
to remove the sagittal membrane, and allowed to dry
Kmgsford and Hughes Growth, mortality, and size of Acanthochromis polyacanthus
563
Figure 1
Map of the nine reefs on the central Great Barrier Reef where Acanthochromis poly-
acanthus were collected. Distance strata from the mainland (i.e. inner-, mid- and
outer-shelf distances I are also indicated.
overnight. One otolith from each fish was then imbed-
ded in Struers Epofix resin that was allowed to harden
overnight in a drying oven at 60°C. A thin (250-300 jmi)
transverse section perpendicular to the long axis of the
otolith was then taken through the core (primordium)
of the otolith with a Buehler low-speed saw with two
spaced diamond blades. This section was polished by
hand with 9-,«m lapping film to remove saw blade marks,
thereby making the internal structure of the otolith
more clearly visible. The polished section was then fixed
to a labelled glass microscope slide with Crystal bond
thermoplastic glue.
Analysis of growth increments
The opaque zones visible in the internal structure of
the otolith were counted along a radius from the pri-
mordium to the outer edge of the largest sagittal lobe of
the otolith with a compound microscope (Leica DMLB)
and white incident light source. Alternating translucent
and opaque increments were interpreted as annuli. Sec-
tions were coded and examined in random order and
the opaque increments counted on two occasions by the
same observer (JMH) separated by four weeks. Counts
of annuli were compared between these two occasions
in order to assess the confidence that could be placed
in the interpretation of otolith structure. If increment
counts differed by more than two between counting occa-
sions, then the otoliths were re-examined. If, following
a third reading, agreement between the third and one
of the two other counts was not reached (all matching
counts were used in analyses), then the otolith was not
included in the analysis; 4.6% of otoliths were rejected
on this basis (n=715 fish).
Validation of growth increments
The periodicity of growth increment formation was vali-
dated by marking a group offish (of various sizes) reared
in captivity with the antibiotic tetracycline hydrochlo-
ride (Sigma-Aldrich, Ballerup, Denmark). Small (known
to be 0+ fish) and large fish were chosen to determine
if annuli are formed early and late in life. Fish were
held at the MARFU Aquarium Facility, James Cook
University. For the duration of the experiment, the fish
were held in several 70-500 L aquaria at this facility.
564
Fishery Bulletin 103(4)
Adult fish were injected in the coelomic cavity with 0.05
g/mL tetracycline in sterile saline solution at concentra-
tions equivalent to 0.05 g/kg body weight (McFarlane
and Beamish, 1987). The approximate weight of each
individual was estimated from the relationship between
weight and SL. Juveniles were mass marked by immer-
sion in a tetracycline solution (concentration: 0.5g/L)
in seawater for 12 hours (overnight). The tetracycline
generally forms a very effective time-marker in oto-
liths; it fluoresces when viewed under ultraviolet light
(Geffen, 1992).
The experiment commenced in May 2002 and fish
were sacrificed after six months, one year (June 2003),
and one-and-a-half years (November 2003). Ten fish had
readable otoliths for which validation was attempted.
Otolith sections were viewed with a compound micro-
scope and incident ultraviolet light in a darkened room.
When a fluorescing tetracycline band was identified,
its position in relation to the edge was measured. The
section was then examined under reflected white light
and measurements of increment widths and marginal
increments were recorded. Known time at liberty, ex-
pressed as a proportion of one year, was then compared
with estimated time at liberty by using the growth of
the otoliths. If estimated time at liberty equalled ac-
tual time at liberty, it supported the hypothesis that
opaque increments were deposited annually. Juveniles
and adults were collected on each occasion to determine
whether increments were deposited annually, early and
late in life.
The length of time for increment formation was also
estimated by calculating the number of days after tetra-
cycline treatment. The number of days after treatment
was estimated by comparing the position of the tetra-
cycline mark with that of the last (marginal) opaque
increment and the width of a full annual increment
with the following formula:
L,=L„[l-e-A'"-'»'],
Number of days after treatment
TE-MI
IW
x365.
where TE = otolith growth after treatment;
MI = the marginal increment; and
IW = the final full increment width.1
where La = the asymptote of the growth curve (average
maximum length);
L, = length at age t\
K = the rate at which the growth curve
approaches the asymptote (Lj\
t = age of fish in years;
t0 = the theoretical origin of the growth curve
(i.e., the hypothetical age of the fish when
it has no length); and
e = the base of the natural logarithm.
Differences in growth curves for A polyacanthus from
each reef sampled were visualized by using the tech-
nique of Kimura (1980), where 95% confidence ellipses
were generated around the parameter estimates of K and
Lx. Confidence ellipses that did not overlap indicated dif-
ferences in growth parameters and enabled the pooling
of data from sites within reefs at each distance stratum.
The parameter t0 was constrained to minus 0.05 to take
into account the approximate size of A. polyacanthus at
hatching (5 mm: Kavanagh, 1998, 2000).
Mortality
The instantaneous rate of mortality (Z) was calculated
by using log-linear regression analyses of age-frequency
data sets for A. polyacanthus populations from each
reef (Pauly, 1984). With this method, recruitment was
assumed to be consistent over time at each reef. The
natural logarithm of the number of fish sampled from
each age class was compared with their corresponding
age. Year classes to the left of the age-frequency mode
were excluded from the analysis because our sampling
technique was biased against small A. polyacanthus.
Fish greater than 60 mm were collected. The slope of
the regression line between year classes estimated the
instantaneous mortality rate (Z):
Z = F +M,
where F = fishing mortality; and
M = natural mortality (Gust et al.
2002).
Growth
It was hypothesized that patterns of growth would
vary with distance from the coast. Growth rates were
described by using von Bertalanffy growth functions
that provided the best fit to size-at-age data when com-
pared with estimates of the Schnute growth function
(Schnute, 1981). The von Bertalanffy expression for
length at age t (Lt), as a function of time is
1 We assumed similar IWs for fish older than 3 years. For
fish 3 years or younger the IW was calculated as an average
from all experimental fish.
Because there is no fishery for A. polyacanthus on the
GBR, F equals zero and therefore Z estimates natural
mortality only. Annual survival rate estimates were then
calculated according to the equation S = e~z (Ricker,
1975). Comparisons of the slopes of age-frequency rela-
tionships (for estimates of Z) were made by using analy-
sis of covariance (ANCOVA) according to the procedures
of Zar (1999). Data from each site were pooled for each
reef because in many cases sample sizes were too small
to provide reliable estimates of mortality at the site
level. Similarities in mortality rates among replicate
reefs within distance strata allowed us to pool data at
the strata level so that comparisons of mortality between
shelf positions could be made.
Kingsford and Hughes Growth, mortality, and size of Acanthochromis polyacanthus
565
Figure 2
Photographs of sectioned Acanthochromis polyacanthus (age = 5 years)
otolith showing: (upper) alternating opaque (annuli) and translucent
band pattern and (lower) the fluorescent tetracycline mark. Note the
single opaque band following the tetracycline mark (time at liberty=380
days). OTC = oxytetracline.
Results
Age validation
All fish treated with tetracycline had clear fluorescent
marks in their otoliths (Fig. 2). The positions of the
fluorescent tetracycline bands in relation to the otolith
margin were consistent with the deposition of opaque
zones on an annual basis (Table 2). In general, percent
agreement was over 75% (7/10 fish). Differences between
actual and estimated time at liberty were probably
related to slight variation in the small measurements
that were made (i.e., fractions of a mm). The timing of
deposition of the opaque increment was estimated to
occur in spring because new increments were found at
the edge of otoliths offish that had been marked in May
and sacrificed about 200 days later.
Size and age structures
There were large differences in the size-frequency dis-
tributions of fish sampled across the shelf (Fig. 3). At
566
Fishery Bulletin 103(4)
Inner shelf
Orpheus (n=41)
10
10-
Jiki
I Hi IIMl I
0
Pandora (n=45)
^L_
40 60 80 100 120 40 60 80 100 120 40 60 80 100 120
Mid-shelf
10
o
Bramble (n=105)
15r
: l : I
Britomart (n=89)
40 60 80 100 120 40 60 80 100 120 40 60 80 100 120
Outer shelf
10
is
Pith (n=100)
hi imB
10 -
40 60 80 100 120
0
Barnett Patches (n=117)
, .nill
40 60 80 100 120
Standard length (mm)
Figure 3
Size-frequency distributions for Acanthochromis polyacanthus collected
from three reefs at each distance stratum from shore. Data were pooled
for the three sites sampled at each reef.
inner-shelf reefs (77 =155), only one fish >100 mm was
collected. In contrast, between 38% and 54% offish col-
lected from outer-shelf reefs were >100 mm. A mix of
inner- and outer-shelf size-frequency distributions was
evident for mid-shelf reefs. Bramble and Britomart reefs
had 1% and 7% offish >100 mm, respectively, whereas
The Slashers had the highest proportion of fish >100
mm collected of any reef (67%) including the largest
individual fish collected (120 mm); however, this result
was more characteristic of outer-shelf reefs. Another
conspicuous feature of the cross-shelf size frequencies
was the very narrow size range of adult fish collected
on inner-shelf reefs in comparison to the size range of
fish collected from mid- and outer-shelf locations (Fig.
3). Size selectivity due to the collection technique (hand
spear) restricted the numbers offish <60 mm that could
be collected.
Maximum age of A. polyacanthus was similar at all
reefs sampled (Fig. 4; inner shelf: 9-10 yr, mid-shelf:
9-10 yr, outer shelf: 10-11 yr). The largest age class
of fish on the inner-and mid-shelf reefs comprised 3-4
year olds, whereas on the outer-shelf reefs, 2-year-old
fish made up the largest proportion of the populations.
The two oldest fish were both collected from outer-shelf
reefs (Myrmidon and Barnett Patches) and were both
11 years old. Strong age-structured cohorts offish were
found at some reefs within the same distance stratum
and these cohorts were found only at these reefs and
distance stratum. For example, there were strong year
classes at Pith and Barnett Patches in years 5 and 6
that were not found at Myrmidon (Fig. 4).
Growth
Variation in patterns of growth was greater among dis-
tance strata across the shelf than among reefs within a
distance strata (Fig. 5). There was variation in growth
between individuals from reefs within each shelf posi-
tion and this resulted in variable size-at-age relation-
ships (Fig. 5). From inner-shelf reefs, fish from Pandora
showed small asymptotic sizes and thus had lower aver-
age Lx, (Lx=77.4 mm) compared to fish from Orpheus
and Havannah (L, =87.0, 84.2 mm, respectively; Table 3).
Distinct, non-overlapping ellipses formed in 95% confi-
dence interval plots of Lx in relation to K confirmed that
growth curves for fish from Pandora differed from those
at Orpheus and Havannah (Fig. 5). Fish collected from
mid-shelf reefs (Bramble, Britomart, and The Slashers)
showed differences in growth among all reefs (non-over-
lapping 95% confidence ellipses; Fig. 5). Growth offish
Kingsford and Hughes: Growth, mortality, and size of Acanthochronvs polyacanthus
567
Inner shelf
Orpheus (n=35)
Jin!..
30
0 4 8 12
Mid-shelf
Bramble (n=100)
£ 20
cr
.2 10
0
1
0 4 8
Outer shelf
Pith (n=99)
20
Pandora (n=43)
30
lllll.l-.
Havannah (n=67)
.11
ll^
12
12
The Slashers (n=91)
30 r 30
Barnett Patches (n=113)
20-
iii
10
ll- -
Myrmidon (n=81)
lllll-
048 12 048 12 048 12
Age (years)
Figure 4
Age-frequency distributions for Acanthochromis polyacanthus collected
from three reefs at each distance stratum from shore. Data are pooled
from the three sites sampled at each reef. All age estimates were derived
from counts of otolith annuli.
Table 2
Validation
data with the use
of tetracycline
to deter
mine
the per
odicity
and timing
of opaque ring
deposition for Acantho-
chromis polyacanthus with the
use of tetracycline as a
time
marker.
TAL =
time at liberty expi-
sssed as
a proportion of one year
and derived from growth measurements
from reared fi
sh treated with tetracycline
re =
= tetrac
^cline.
Fish age
TC to marginal
TAL
TAL
as propoi
•tion
Estimated days
Actual day?
from
Percent
agreement =
lyrl
increment (mm)
(mm)
of year
from TC marking
TC mark
ing
( estimated/actual x 100 )
1
0.0423
0.30
0.43
110
158
69
1
0.0463
0.33
0.43
120
158
76
1
0.1784
0.94
0.97
344
355
97
5
0.0686
0.80
1.04
291
380
76
5
0.0739
0.83
1.04
304
380
80
5
0.1077
1.00
1.52
365
556
66
5
0.0805
0.81
1.52
295
556
53
6
0.1471
1.46
1.47
532
537
99
7
0.1034
0.90
1.12
327
409
80
7
0.0919
1.30
1.52
474
556
85
from the outer reefs (Pith, Barnett Patches, and Myr-
midon), however, was similar for fish from each of these
reefs (overlapping 95% confidence ellipses; Fig. 5).
Average maximum length (L.,) varied across the shelf
and differences among strata were generally greater
than within-distance strata. The K values for all three
568
Fishery Bulletin 103(4)
Inner-shelf reefs (n=147)
■ Orpheus Pandora " Havannah
Mid-shelf reefs (n=273)
• Bramble * Britomart * The Slashers
x
9 * *
Oufer-shelf reefs (n=296)
° Pith * Barnett Patches
10
Myrmidon
4 6
Age (years)
10
12
05 075 1 125 15 175
K
115
110
105
100
95
90
65
12
Figure 5
Von Bertalanffy growth curves for Acanthochromis polyacanthus collected from three
reefs within each distance stratum. 95% confidence ellipses are given for the parameters
K (growth coefficient) and Lx (mean asymptotic length).
shelf positions were similar and indicated that K val-
ues for A. polyacanthus converge at asymptotic sizes at
approximately the same rate of growth, irrespective of
proximity to the coast (Fig. 5 and Table 3). However, an
obvious trend for increased L , occurred with increasing
distance from the coast (inner shelf: -83 mm, mid-shelf:
-99 mm, outer shelf: -102 mm). The growth parameters
offish from The Slashers were more similar to those of
fish taken from the outer-shelf reefs than to those we
defined a priori as mid-shelf (Fig.6). The Slashers are
in fact much farther from the coast (85 km), as are Pith
Reef (74 km) and Barnett Patches (63 km) on the outer
shelf, than the other two mid-shelf reefs (Britomart:
39 km. Bramble: 41 km) (Fig. 1, Table 1).
Mortality
Mortality rates for A. polyacanthus did not differ sig-
nificantly between replicate reefs within inner-shelf
(test for slopes df(2 19„ F=0.982, P=0.39), mid-shelf (test
for slopes df(2 19l, F=1.334, P=0.29) or outer-shelf (test
for slopes df(219), F=0.658, P=0.53) locations (Table 4).
Kingsford and Hughes: Growth, mortality, and size of Acanthochromis polyacanthus
569
Age frequencies, therefore, were pooled
at the shelf level (within distance strata;
Fig 7).
Acanthochromis polyacanthus mortality
rates did not differ significantly between
the inner-, mid- and outer-shelf strata
(test for slopes df,s 63), F=0.367, P=0.70)
(Fig. 6). Although mortality estimates
were progressively lower with increased
distance from the coast, this trend was
not significant (inner shelf: -0.51, mid-
shelf: -0.48. outer shelf: -0.43; Fig. 6, Ta-
ble 4). Associated survival rate estimates
(S) varied between reefs by -9% per an-
num at inner- and mid-shelf strata and by
-6% per annum on the outer shelf (Table
3). The mean difference in survival rates
for A. polyacanthus between the inner and
mid-shelf was ~29c and between the mid-
and outer shelf was -3% (Table 4).
Discussion
■ Orpheus
o Pandora
A Havannah
• Bramble
0 Bntomart
* The Slashers
° Pith
a Barnett Patches
x Myrmidon
110
105-1
100
95 ■
90-
85
80 -I
75
The Slashers
Myrmidon
Barnett Patches
Havannah
Pandora
0.5
0.75
1 1.25
K
1.5
1.75
The demographic parameters of L x and
patterns of growth for populations of A.
polyacanthus varied across the shelf on the
central GBR. Although there was varia-
tion in body size and growth among reefs
within a distance stratum, it was minor
compared to overall cross-shelf patterns. In this study,
mortality estimates and maximum age were similar
for populations of fish across the shelf. Thus, in order
to explain the cross-shelf trend in body size, fish must
have grown faster with increasing distance from shore
(Fig. 7, Table 1).
Despite the relative paucity of age-based studies on
reef fishes (Choat and Robertson, 2002), variable rates
of growth have been previously demonstrated for fish at
local scales (hundreds of metres to kilometers: Fowler
and Doherty, 1992), medium scales (kilometers to tens
of kilometers: Choat and Axe, 1996; Hart and Russ,
1996; Newman et al., 1996; Meekan et al., 2001; Gust
et al., 2002), and large scales (thousands of kilometers:
Choat and Robertson, 2002). Gust et al. (2002) found
that growth patterns of scarids varied between the reef
crests of mid- and outer-shelf sampling locations on the
northern GBR. In contrast to the results from the cur-
rent study, however, outer-shelf populations of scarids
had smaller asymptotic sizes and slower growth rates
than mid-shelf populations. The factors influencing pat-
terns of growth, therefore, vary by group.
Differences in the shape of growth curves between
geographic regions or areas may be determined by both
genetic and environmental influences (Sebens, 1987).
Populations of reef fish are generally considered to be
genetically open systems (Sale, 1991) and it is consid-
ered unlikely that adaptation of such populations to
local conditions through genetic selection can occur
(Warner, 1991). Acanthochromis polyacanthus, how-
Figure 6
95*^ confidence ellipses for the von Bertalanffy growth parameters
K (growth coefficient) and L, (mean asymptotic lengthl for Acantho-
chromis polyacanthus from all reefs sampled.
Table 3
Parameters from von Bertalanffy growth models
on the
fishes collected from
different dis
tance strata and
reefs.
Shelf location and reef n
La
A"
r-
Inner shelf
Orpheus Island
36
87.03
0.77
0.83
Pandora Reef
44
77.43
1.39
0.92
Havannah Island
67
84.23
1.07
0.81
Mid-shelf
Bramble Reef
97
92.24
1.04
0.83
Britomart Reef
85
96.37
0.95
0.87
The Slashers
91
106.73
0.98
0.75
Outer shelf
Pith Reef
100
101.98
1.11
0.76
Barnett Patches
114
100.27
1.13
0.78
Myrmidon Reef
82
103.66
1.15
0.70
ever, possesses a unique life history trait among reef
fishes in that it lacks a dispersive larval phase. The
major implication of this characteristic is the potential
for genetic isolation of populations of these fish. Even
reefs that are in relatively close proximity to one an-
other (100's of m) may become "genetic islands" isolated
by any barrier that proves impassable to adults (e.g.,
deep water). Without gene flow, reproductively isolated
570
Fishery Bulletin 103(4)
Table 4
Estimates of mortality (M) for fishes collected from dif-
ferent distance strata
and reefs. Pooled va
ues are for all
reefs within one distance s
tratum
n = number of fish in
sample. S = animal survival rate.
Pooled
S
Pooled
Reef
n
M
M
(%)
S(%)
Inner shelf
0.51
60.0
Orpheus Island
30
0.29
74.8
Pandora Reef
34
0.40
67.0
Havannah Island
45
0.42
65.7
Mid-shelf
0.48
61.8
Bramble Reef
83
0.44
64.4
Britomart Reef
63
0.48
61.9
The Slashers
73
0.34
71.2
Outer shelf
0.43
65.1
Pith Reef
91
0.32
72.6
Barnett Patches
96
0.40
67.0
Myrmidon Reef
79
0.38
68.4
populations are expected to diverge over time with re-
spect to their genetic composition (Doherty et al., 1994).
Numerous studies have examined the genetic relation-
ships between populations of A. polyacanthus on the
GBR (Doherty et al., 1994, 1995; Planes and Doherty,
1997a, 1997b). Isozyme analyses of populations of dif-
ferent color morphs at various spatial scales have shown
significant genetic variation at both the regional ( 1000's
of km) and local (100's of m) level, which under normal
circumstances would suggest separate species for each
color morph (Doherty et al., 1994; Planes and Doherty,
1997a). However, differences in the growth rates of A.
polyacanthus across the continental shelf in this study
are unlikely to reflect genetic differences between the
populations sampled because all individuals collected
were of the same color morph and were from a rela-
tively small area (about 400 km2, cf. 450,000 km2 for
the entire GBR).
Environmental influences that can affect patterns of
growth include predation pressure, temperature, and
related effects on metabolism, variations in resources
(e.g., abundance of planktonic food), and variation in
water condition (e.g., turbidity).
High rates of predation may "drive" faster growth
(Werner, 1984), or conversely, select for early matura-
tion and smaller adult size (Reznick et al., 1990; Hutch-
ings, 1997). It is unlikely that the cross-shelf patterns
in growth that we found were determined by differences
in mortality rates. Some data on serranid abundance
(Williams, 1982) and anecdotal accounts have indicted
that predator abundance is greatest on mid- and outer
reefs of the GBR (Gust et al., 2001). Our measures of
instantaneous mortality (Z) and age maximum, how-
ever, did not vary with distance from the mainland.
Furthermore, in contrast to the patterns that Gust et
Inner shelf (n=109)
Mid-shelf (n=21 9)
4 ■
3
y=-0.48x+6.04
r2=0.89
10
12
5 1
4
3
2
1
Outer shelf ( n=266)
y=-0.43x+5.49
c2=0.95
4 6
Age (years)
10
12
Figure 7
Age-based catch curve estimates of Acanthochro-
mis polyacanthus mortality rates for reefs pooled
by distance strata.
al. (2001) found for scarids, L.y increased with distance
from the coast. Mortality rates have been shown to vary
among locations within reefs for several species of coral
reef fish (Aldenhoven. 1986; Eckert, 1987; Sale and
Ferrell, 1988; Beukers and Jones, 1997) including A.
polyacanthus juveniles (Connell, 1996), as well as over
larger spatial scales (Meekan et al., 2001; Gust et al.,
2002). In contrast to these last two studies, particularly
that of Gust et al. (2002), mortality rates for A. poly-
acanthus were similar at all three cross-shelf strata.
We acknowledge, however, that no data were available
on mortality rates of fish from zero to two years of age.
It is possible that mortality rates do vary with distance
from shore over this age range.
An increase in adult size may occur when individu-
als experience a decline in average temperature during
development (Atkinson, 1994). It is also well established
that metabolism and growth are increased at higher
ambient temperatures in ectotherms (Schmidt-Nielsen,
1990). Differences in temperature between the water
bodies spanning inner-, mid- and outer-shelf positions
in the central GBR do occur; relatively shallow near-
Kmgsford and Hughes: Growth, mortality, and size of Acanthochromis polyacanthus
571
shore waters are the warmest and outer-shelf waters
are the coolest (Wolanski, 2001). The opposite pattern
of growth to the one observed in this study would be
predicted by this cross-shelf gradient in water tempera-
ture. It is also considered unlikely that local upwelling
events on outer-shelf reefs could produce the observed
differences, but they could influence primary produc-
tivity and abundance of food (zooplankton) through
nutrient-rich waters. An increase in average annual
temperature correlates with maximum age in some
fishes (review Choat and Robertson, 2002), but we found
no differences in age maximum across the shelf. We
conclude that any differences in temperature across
the shelf are not persistent enough to affect cross-shelf
patterns of growth of A. polyacanthus.
Differences in growth profiles can be more realisti-
cally attributed to cross-shelf variation in some limiting
resource! s). This variation in resources may influence
the quality and quantity of food, suitable nest sites, ref-
uges from predators and (or) wave exposure, and density
of conspecifics and (or) other species that compete with
A. polyacanthus for resources. Correlative studies have
concluded that the distribution and abundance of coral
reef fishes is strongly influenced (directly and indirectly)
by physical factors such as wave exposure, sediment
loads, water depth, and topographical complexity, as
well as by biological factors (Williams, 1982). These
factors also have the potential to affect growth rates.
A combination of reduced resource levels and high
population densities on outer-shelf reefs strongly indi-
cated that growth profiles represent density dependence
in scarids (Gust et al., 2001, 2002). Density of con- and
hetero-specifics was not recorded for our study, but
densities of A. polyacanthus were clearly greatest on
the mid- and outer-shelf reefs. This observation is con-
trary to the pattern noted by Williams ( 1982 ) who found
greatest abundances of A. polyacanthus on inner- and
mid-shelf reefs. Thresher (1983) suggested that food
abundance is a limiting resource for A. polyacanthus
and interspecific competition for food does occur. Thus,
it is plausible that variation in abundance of and com-
petition for food across the shelf may have influenced
the growth rates observed in the present study. The
large differences in cross-shelf densities and LJs of
A. polyacanthus indicate that competition may be less
important than variation in quantity and quality of food
across the shelf.
Biomass of planktivores is generally highest at mid-
shelf reefs on the central GBR (Williams and Hatcher,
1983). Although data on cross-shelf abundance and dis-
tribution of plankton are limited, Williams and Hatcher
attributed this pattern to the increased availability of
food (zooplankton) in mid-shelf waters. Upwelling of
cold, nutrient-rich water from the edge of the continental
shelf results in high biomasses of phytoplankton. Aging
of the water (time since upwelling) is accompanied by
a shift in dominant planktonic biomass to herbivorous
and then carnivorous zooplankton. This shift in biomass
composition occurs simultaneously with the prevail-
ing wind-driven passage of water across the shelf and
ultimately leads to the greatest biomass of zooplankton
occurring in mid-shelf waters (Andrews and Gentien,
1982; Sammarco and Crenshaw, 1984; Williams et al.,
1988). Food quality has also been previously shown to
limit growth and reproduction in herbivorous coral reef
fishes (Horn, 1989; Choat, 1991).
Despite a high abundance of zooplankton near shore,
these waters also have higher turbidity than mid- and
outer-shelf reefs. Visual impairment caused by very tur-
bid waters may hinder the ability offish to feed on plank-
tonic organisms and this hypothesis has been suggested
as a factor contributing to the low relative abundances
of planktivorous fish on inner-shelf reefs (Williams et
al., 1986). It is possible that this factor may retard the
growth and influence the maximum size of planktivores
like A. polyacanthus by effectively reducing food avail-
ability. Interestingly, lowest L r values were found at the
most turbid inshore reef, Pandora. Lower visibility near
shore, however, did not appear to affect the mortality
rates of A. polyacanthus at inner-shelf reefs.
There were clear differences in growth, size maxima,
and age structures for populations of A. polyacanthus
across the continental shelf of the central GBR. Al-
though Acanthochromis polyacanthus grew faster and to
a larger size with increasing distance from the main-
land, cross-shelf mortality rates and maximum ages
were similar. Because these populations of fish are un-
likely to be genetically distinct, we suggest that biotic
and physical processes are the most plausible cause of
these cross-shelf patterns. Increased abundance of zoo-
plankton in mid- and outer-shelf waters, coupled with
potential visual impairment associated with high tur-
bidity levels on the inner shelf, are likely mechanisms
that explain the observed patterns, but multifactorial
manipulative experiments are required to determine
the relative contribution of these factors to variation in
demographic parameters. Our study therefore cautions
against pooling demographic parameters over broad spa-
tial scales without considering cross-shelf variation.
Acknowledgments
We would like to thank H. Patterson, C. Bunt, W. Rob-
bins, and the crew of the RV Orpheus for field assistance
during this study. We also thank J. Ackerman for analyt-
ical advice and expertise and J. H. Choat for constructive
comments on the manuscript. We also thank John Mor-
rison and the staff of MARFU for assistance with the
maintenance of aquarium fish. The project was partly
funded by an ARC Grant to MJK. This is a contribution
from Orpheus Island Research Station.
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Abstract — Aspects of the feeding
migration of walleye pollock iTher-
agra ehalcogramma) in the eastern
Bering Sea (EBS) were investigated
by examining the relationship be-
tween temperatures and densities
of fish encountered during acoustic
and bottom trawl surveys conducted
in spring and summer between 1982
and 2001. Bottom temperature was
used as an indicator of spring and
summer warming of the EBS. Clus-
ters of survey stations were identified
where the density of walleye pollock
generally increased or decreased with
increasing water temperature. Infer-
ences about the direction and magni-
tude of the spring and summer feeding
migration were made for five length
categories of walleye pollock. Gener-
ally, feeding migrations appeared to
be northward and shoreward, and the
magnitude of this migration appeared
to increase with walleye pollock size
up to 50 cm. Pollock larger then 50 cm
showed limited migratory behavior.
Pollock may benefit from northward
feeding migrations because of the
changes in temperature, zooplank-
ton production, and light conditions.
Ongoing climate changes may affect
pollock distribution and create new
challenges for pollock management
in the EBS.
Variation in the distribution of walleye pollock
(Theragra ehalcogramma) with temperature
and implications for seasonal migration
Stan Kotwicki
Troy W. Buckley
Taina Honkalehto
Gary Walters
Resource Assessment and Conservation Engineering Division
Alaska Fisheries Science Center
National Marine Fisheries Service. NOAA
7600 Sand Point Way NE
Seattle, Washington 981 1 5-6349
E-mail (for 5 Kotwicki) Stan kotwicki'5'noaa gov
Manuscript submitted 20 November 2004
to the Scientific Editor's Office.
Manuscript approved for publication
30 March 2005 by the Scientific Editor.
Fish. Bull 103:574-587 (20051.
Walleye pollock (Theragra ehalco-
gramma; referred to as "pollock" in
this article) migrate seasonally. Such
migrations have been described for the
northern Sea of Japan (Maeda, 1986;
Maeda et al., 1988, 1989; Kooka et
al., 1998), Korean waters (Shuntov et
al., 1993), the Okhotsk Sea (Shuntov
et al., 1987), and the western and
central Bering Sea (Fadeyev, 1989;
Bulatov and Sobolevskiy, 1990; Efim-
kin, 1991; Radchenko and Sobolevskiy,
1993; Shuntov et al., 1993; Balykin,
1996). Generally, these authors have
described a spring and summer
migration from spawning grounds to
forage areas (referred to as a "feed-
ing migrations" by many authors)
and a winter migration of pollock
returning to spawning grounds (e.g.,
Maeda et al., 1988; Radchenko and
Sobolevskiy, 1993). This pattern of
migration is believed to occur in the
eastern Bering Sea (EBS) where it
has received considerable attention
(Takahashi and Yamaguchi, 1972
Francis and Bailey, 1983; Pola, 1985
Shuntov, 1992; Shuntov et al., 1993
Stepanenko, 2001), but the evidence
for this pattern of migration is sparse.
In addition, there is a lack of infor-
mation on the magnitude of, routes
of, and size-dependent differences in
seasonal migrations.
Temperature (and other factors
closely related to temperature) af-
fects the distribution and movements
of pollock. Pola (1985) simulated
temperature-induced migrations of
pollock in the EBS occurring dur-
ing May and June. Pollock appear to
avoid some temperatures (Swartzman
et al., 1994) and prefer environmen-
tal conditions that are linked to food
availability associated with tempera-
ture gradients and fronts along the
EBS slope (Swartzman et al., 1995).
Water temperature is an especially
important indicator of the transi-
tion from winter conditions to those
supporting a spring bloom of phyto-
plankton and then zooplankton. In
the EBS. the simulated onset of the
feeding migration of pollock was de-
layed in colder years (Pola, 1985).
Annual surveys documenting the
spatial distribution of fishes in re-
lation to water temperatures can be
used to infer details about their mi-
gratory behavior. Using annual sur-
vey data, Mountain and Murawski
(1992) found that the relationship
between the distribution of season-
ally migrating species and water
temperature could indicate a change
in the overwintering location of the
fish, or a change in the timing of the
spring migration, or both. In the east-
ern Bering Sea, bottom trawl (BT)
surveys and echo-integration-trawl
(EIT) surveys are conducted in late
spring and summer (Honkalehto et
al1; Acuna et al.2), when water tem-
• 2 See next page for footnote texts.
Kotwicki et al Variation in the distribution of Theragra chalcogramma
575
peratures are generally rising
on the eastern Bering Sea shelf
(Overland et al., 1999; Stabeno
et al., 2001). Interannual vari-
ability in climatic conditions
and survey timing create vari-
ability in mean water tempera-
tures encountered during the
surveys (Acuna et al.2).
We describe the variability in
distribution of pollock with tem-
perature and propose that this
variability may be explained by
the fact that pollock migrate to
feeding grounds during spring
and summer. Temperature is
used in our study as an indica-
tor of how far into an idealized
seasonal warming cycle each
survey has occurred. Thus, the
distribution of pollock observed
in a warm year would be con-
sidered to be representative of
that seen later in a seasonal
warming cycle in a cold year.
Generally, feeding migrations
appeared to be northward and
shoreward, and the magnitude
of this migration appeared to
increase with walleye pollock
size up to 50 cm. Pollock larger
then 50 cm showed limited mi-
gratory behavior. Pollock may
benefit from northward feed-
ing migrations because of the
changes in temperature, zoo-
plankton production, and light
conditions.
Materials and methods
64 N -
62"N
60"N
58' N
56'N -
54"N -
52 N
BERING SEA
rf* °Sk
gg *- ~ssg£
66 N
64 "N
62"N
60N
58"N
56°N
54-N
176°W
172°W
168W
164°W
1 60"W
Figure 1
Locations of AFSC bottom trawl stations (dots) and echo-integration survey
transects (lines) in the eastern Bering Sea where walleye pollock {Theragra
chalcogramma) were collected during bottom trawl surveys and echo-inte-
gration trawl surveys in spring and summer between 1982 and 2001.
Data used in this investigation were collected by BT
and EIT surveys conducted by the Alaska Fisheries
Science Center.
Since 1982, BT surveys have been conducted annu-
ally over a standard area of the EBS, at the centers of
20x20 nautical-mile grids (Fig. 1). The corners of the
grid block were also sampled in areas surrounding St.
Matthew Island and the Pribilof Islands. The same
1 Honkalehto, T., N. Williamson, and S. de Blois. 2002a. Echo
integration-trawl survey results for walleye pollock (Theragra
chalcogramma) on the Bering Sea shelf and slope during
summer 1999. U.S Dep. Commerce, NOAA Tech. Memo.
NMFS-AFSC-125,77 p.
- Acuna, E., P. Goddard, and S. Kotwicki (compilers).
2003. 2002 bottom trawl survey of the eastern Bering Sea
continental shelf. AFSC Processed Report 2003-01, 169 p.
Alaska Fish. Sci. Cent., NOAA Natl. Mar. Fish. Serv., 7600
Sand Point Way NE, Seattle, WA 98115.
standard trawl (83-112 eastern otter trawl) was used
every year (Acuna et al.2) and surveys usually began in
late May or early June, and ended in August. Surveys
always began in the northeastern corner of the Bristol
Bay and proceeded westward. Samples were collected
by towing for 30 minutes at 1.54 m/s (intended speed).
Temperature data were collected during each tow us-
ing an expendable bathythermograph (XBT) until 1992
and after 1992 with a micro-bathythermograph (MBT)
attached to the headrope of the trawl. Catches were
sorted by species and weight; number of fish caught and
length-frequency data were collected for each tow.
Echo integration trawl survey transects were de-
signed to coincide with north-south lines of BT sta-
tions. Similar to the BT survey, the EIT survey began
also in the eastern Bristol Bay and proceeded west-
ward. The time lag between the survey varied from 0
to 30 days. Acoustic data were collected with a Simrad
EK500 quantitative echo sounding system. Biological
576
Fishery Bulletin 103(4)
data were collected by midwater trawl, bottom trawl,
and Methot trawl (see Honkalehto et al.1 for details).
Pollock length data from trawls were aggregated into
analytical strata based on echosign type, geographic
proximity of hauls, and similarity in size composition of
hauls. Estimates of numbers of pollock by size were de-
rived by scaling acoustic measurements with the target
strength-to-length relationship described in Traynor
(1996). Temperature data were collected with an MBT
mounted on the headrope of the trawl, although many
of the profiles did not reach bottom because the trawls
usually targeted midwater fish aggregations. For that
reason, we elected not to use the temperature data
collected during the EIT survey. Because both surveys
were conducted at approximately the same time of
year, we used the mean bottom temperature from the
BT survey as an index temperature for the EIT survey.
We used EIT data collected in years 1994, 1996, 1997,
1999, and 2000.
Because of the semidemersal nature of pollock (Bailey
et al., 1999a) and assuming that pollock do not dive as
a boat and trawl approaches, BT data are assumed to
describe the demersal part of the pollock stock within
3 m of the bottom. EIT data represented the midwa-
ter part of the stock from 3 m above the bottom to
14 m below the surface. In our calculations, we used
two density measures: CPUE in kg/ha for the BT data
and biomass (tons) per 20-mile square for EIT data
(the term "density" will be used in the present study
to refer to both of these measures). Echo integration
trawl survey 20-mile squares were centered on the BT
survey stations, so that both sets of data could be easily
compared (the term "station" will be used here to refer
to BT survey stations as well as EIT survey squares).
Because of known age-dependent behavioral differences
between pollock (e.g., Shuntov et al., 1993; Bailey et al.,
1999a), we investigated five different length classes of
pollock; up to 20 cm (mostly 1-year-old pollock), 21-29
cm (mostly 2-year-old pollock), 30-39 cm, 40-49 cm,
and pollock >50 cm. Because of differences in the year-
class strengths between years, we scaled the data by
dividing the density data for each station by the aver-
age fish density for each year within each length class.
Thus, a station with a density value of 1 has an average
density for a given year and a station with a value of 5
has a density 5 times larger for a given year.
If the pollock distribution in the EBS is assumed to
be dynamic and related to temperature, the relationship
between temperature and pollock density will be differ-
ent at each spatial location. This means that if pollock
moved from location A to location B over a period of
rising temperatures, we expected a negative relation-
ship between density and temperature in location A
and an offsetting positive relationship in location B. To
study these relationships in the EBS, we applied a two-
step approach. In the first step, we identified possible
locations where pollock density may be changing with
temperature. In the second step, we identified locations
of most significant biomass changes with temperature
and quantified these changes.
First step— identifying areas of change in fish density
with temperature
For both types of surveys, we calculated the slope of the
linear regression of scaled density against bottom tempera-
ture for each station over the time series (e.g., a slope value
of 1 indicates an increase of 1 unit of density per degree
increase of temperature). Slopes in the range between -0.3
and 0.3 were ignored because they represented areas of
low fish density or areas of no significant changes in fish
density between years. Each station slope was then plot-
ted on a map to visualize the spatial relationship between
these two variables for the BT and EIT surveys.
To contour areas with similar slopes, we interpolated
the data using inverse distance-weighted squared inter-
polation (IDW). This method was chosen because IDW
is an exact interpolator, where the maximum and mini-
mum values in the interpolated surface can occur only
at sample points and values at all sampling points are
true measured values (ArcGIS, Geostatistical Analyst
Help, 2003, ESRI, Redlands, CA). Using these maps,
we identified the main spatially correlated clusters of
stations with positive or negative slopes of the linear
regression of pollock density against temperature (Figs.
2 and 3). Stations were assigned to clusters visually by
using slope maps that overlapped the stations map. For
practical reasons we investigated only clusters with four
stations or more. Twenty-eight clusters were identified
for BT survey and 17 clusters were identified for EIT
survey (Figs. 2 and 3).
Second step— identifying areas of most significant
changes in biomass with temperature and
quantifying these changes
For each cluster, we calculated mean temperature and
percentage of total biomass of pollock present in this
cluster in each year. Total biomass and biomass within
clusters were calculated as outlined in Wakabayashi
et al. (1985). The relationship between mean bottom
temperature and percentage of pollock biomass within
each cluster was then fitted to a linear regression model.
Because the error variances for the BT survey were
not constant (variance increased with fish density), we
weighted the regression by the inverse of the variance
(Neter et al., 1996). For the EIT survey, we made no
assumptions about the variance that was due to a small
number of observations (only five years of data).
The relative strength of the relationship between the
percentage of pollock biomass and temperature within
each cluster was characterized by the P-value of the
slope (Table 1) (the P-values are not a true measure
of statistical significance because the stations were
not chosen randomly). Only clusters with the stron-
gest relationships were used in the interpretation of
results. Because the number of data points (years) in
each analysis was equal within the survey (BT sur-
veys— 20 points, EIT surveys — 5 points), P-values in-
dicate relative strength of the temperature-biomass
relationship. We plotted histograms of P-values for
Kotwicki et a\ Variation in the distribution of Theragra cholcogromma
577
Biomass decrease Biomass increase
with temperature 180 w 176°w 172°w 168°w 164°w with temperature
Clusters:
Slope < - 0.3 (biomass decreases
with temperature)
^m Slope > 0.3 (biomass increases with
^™ temperature)
Columns:
mm Predicted % of total biomass in the
^^ area during warmest year
Predicted % of total biomass in the
area during coldest year
Standard error bar
172°W 168 W 164:W
Figure 2
Clusters of positive and negative slopes of the linear regression of pollock (Theragra chalcogramma) density
(detected by echo-integration trawl survey) when plotted against temperature. Columns represent predicted per-
cent biomass offish in these clusters within the observed range of temperatures. Predicted percent of biomass is
shown only for clusters with the strongest relationship between temperature and fish density with the exception
of cluster Fl (see results for explanation). Labels are located at the geographic centers of the clusters.
578
Fishery Bulletin 103(4)
Biomass decrease
with temperature
. I8tm 176^ 172-W I68"W <U"W I60°W
A 47
Biomass increase
with temperature
B
D
14
110
I
A2 A4 A5
IB
112 13
I I I
B1 B4 B6 B7
32
17
I
64°N 01 C5
■ 5B°N 15 16
II.
D1 D5 D6
15
I.
E1 E3
172°W 168"W 164°W 160°W
Clusters:
Slope < - 0.3 (biomass decreases
with temperature)
Slope > 0.3 (biomass increases with
temperature)
Columns:
I Predicted % of total biomass in the
area during warmest year
1 Predicted % of total biomass in the
area during coldest year
Standard error bar
Figure 3
Clusters of positive and negative slopes of the linear regression of pollock IT. chalcogramma) density (detected
by bottom trawl survey) when plotted against temperature. Columns represent predicted percent biomass of
fish in these clusters within the observed range of temperatures. Predicted percent of biomass is shown only
for clusters with the strongest relationship between temperature and fish density.
Kotwicki et al.: Variation in the distribution of Theragra chalcogramma
579
Table 1
Results
of linear regression analyses and
predicted
percent
of total bioma
ss in each clustei
within an ob
served range "1
temperatures.
Standard
Percentage
Standard error
Percentage
Standard error
error
at min.
of min.
at max.
of max.
Cluster
Slope
of slope
Intercept
r2
P
temperature
percentage
temperature
percentage
Botton trawl survey
Al
3.0706
4.579
7.2013
0.024
0.511
8.82
5.07
15.49
4.89
A2
1.1579
0.382
1.6145
0.338
0.007
0.55
0.36
4.31
1.01
A3
-24.0232
6.812
98.8454
0.409
0.002
47.04
5.33
5.79
6.38
A4
3.3081
1.254
2.9747
0.279
0.017
3.14
1.22
13.75
2.84
A5
2.7928
0.837
-0.5577
0.382
0.004
0.08
0.47
10.13
2.65
Bl
6.2744
1.655
4.5969
0.444
0.001
1.98
1.21
18.30
3.13
B2
-5.7916
3.445
24.2379
0.136
0.110
21.73
6.37
5.44
3.34
B3
-0.2449
0.839
4.9690
0.005
0.774
4.86
2.07
4.07
0.70
B4
3.6720
1.880
1.4972
0.175
0.066
2.83
0.52
12.05
4.33
Bo
-26.2623
7.642
106.0603
0.396
0.003
70.17
14.89
5.08
4.06
B6
1.9462
0.756
2.9913
0.269
0.019
0.62
1.12
9.27
2.31
B7
3.4809
1.408
-0.5292
0.253
0.024
0.77
0.23
13.03
4.94
B8
0.5026
0.350
0.0979
0.103
0.168
0.10
0.44
2.47
1.30
CI
10.9174
2.355
in 7957
0.544
0.000
2.28
0.31
32.32
6.32
C2
-17.9173
5.809
60.49S7
0.346
0.006
42.49
7.89
0.51
5.72
C3
1.1807
0.731
1.5962
0.127
0.124
0.84
1.20
4.68
1.26
C4
-26.8246
7.771
116.1162
0.398
0.003
68.32
10.03
12.06
6.27
C5
5.3395
1.413
-3.3847
0.442
0.001
0.11
1.79
16.77
2.65
C6
-1.4934
0.843
6.3588
0.148
0.094
4.77
2.07
0.89
0.28
Dl
5.4677
1.368
7.2510
0.470
0.001
-0.15
0.44
15.42
3.55
D2
-1.9038
0.850
5.7227
0.218
0.038
4.50
1.39
0.87
0.45
D3
0.9668
2.954
2.9573
0.006
0.747
4.89
1.28
6.65
4.19
D4
-14.3609
5.356
65.9267
0.285
0.015
41.08
8.45
10.70
2.89
D5
3.6882
1.411
2.7672
0.275
0.018
4.92
1.18
15.81
3.02
D6
2.3974
0.830
-8.0125
0.317
0.010
0.04
0.31
2.60
0.81
El
4.5778
0.733
6.1399
0.684
0.000
-1.45
1.13
14.86
1.56
E2
-5.7776
1.910
26.8244
0.337
0.007
22.13
3.71
7.32
1.24
E3
0.6479
0.217
0.9447
0.332
0.008
0.91
0.28
3.80
1.01
Echo-integration trawl survey
Fl
16.0479
13.649
-1.2116
0.315
0.324
10.35
21.80
51.49
20.57
F2
-27.5255
9.304
79.2218
0.744
0.059
59.39
14.86
-11.18
14.02
F3
11.7970
3.622
-13.4672
0.779
0.047
-4.97
5.76
25.28
5.46
F4
5.1896
8.463
-3.8753
0.111
0.583
-0.13
13.52
13.17
12.75
Gl
32.3770
4.047
-12.0017
0.955
0.004
11.32
6.46
94.33
6.10
G2
-25.5850
10.151
75.6302
0.679
0.086
57.20
16.22
-8.40
15.30
HI
28.0501
4.012
-16.7011
0.942
0.006
3.51
6.41
75.42
6.05
H2
-10.6961
2.999
32.2026
0.809
0.037
24.50
4.79
-2.93
4.52
H3
-11.0388
3.249
38.1076
0.793
0.042
30.16
5.19
1.85
4.90
H4
-5.0998
2.465
13.8907
0.587
0.130
10.22
3.94
-2.86
3.71
11
19.1934
7.184
-13.8822
0.704
0.075
-0.06
11.48
49.15
10.83
12
-21.2245
8.449
73.6602
0.677
0.086
58.37
13.50
3.95
12.73
13
2.3497
1.169
-0.0335
0.573
0.138
1.66
1.87
7.68
1.93
Jl
-15.6292
2.465
50.1504
0.930
0.007
38.89
3.94
-1.18
3.72
J2
9.6097
4.374
-6.9678
0.616
0.115
-0.04
6.99
24.59
6.59
J3
9.7424
1.675
1.5600
0.918
0.010
8.58
2.68
33.56
2.53
■J4
-5.8055
2.571
17.1422
0.629
0.109
12.96
4.11
-1.92
3.88
580
Fishery Bulletin 103(4)
BTS
■MM,
EITS
1
04 06
P-value
Figure 4
Histograms of P-values of linear regression between fish density and
temperature calculated for all clusters. Circled bars represent the clus-
ters with strongest relationship.
each survey (Fig. 4) and the groups of clusters with
the strongest relationships between fish biomass and
temperature were chosen for further investigations.
These groups consisted of 21 clusters from BT surveys
with P-values between 0.000 and 0.066 and 15 clusters
from EIT surveys with P-values between 0.004 and
0.138. Using linear regression models (biomass against
temperature), we calculated the predicted percentage
of the total pollock biomass for each of these clusters
(Table 1) within the temperature range observed during
surveys (Fig. 5).
To evaluate a spatial scale on which biomass redistri-
bution occurred for the EIT surveys, we calculated mean
distance between clusters of negative and positive slope
(Table 2). To obtain these values, we generated 100 ran-
dom points within each of the clusters and calculated
the mean distance between all possible pairs of points
from both clusters. We did not attempt to calculate this
distance for the BT surveys because of the much more
complicated nature of the BT cluster maps.
Results
Northward and inshore shifts in pollock distribution in
warmer years were found in the EBS for all length cat-
egories. The location and magnitude of these shifts and
distance between clusters differed with the survey type
and length categories. In the present study we address
changes in pollock distribution by length category within
each survey.
Table 2
Mean distance between largest echo-integration trawl
(EIT) survey clusters. Clusters for pollock >50 cm were
not calculated because of low selectivity of the EIT survey
for these fish.
Clusters
Mean distance
(km)
99 %
confidence interval
(km)
F2-F1
241.3
2.3
G2-G1
217.5
2.5
H4, H3, H2-H1
368.3
4.7
12-11
453.7
3.9
Echo-integration trawl survey
The biomass of pollock <20 cm in cluster F2 near Zem-
chung Canyon at latitude 59°N decreased (with increas-
ing temperature) from about 59% of the total biomass
of pollock in the coldest year to 0% in the warmest
year (Fig. 2A). This decrease was partially offset by
the increase in pollock biomass in area F3, northwest
of the Pribilof Islands. The relatively weak relationship
(P-value=0.324) between pollock biomass and temper-
ature in cluster Fl (north of F2) was caused by the
extremely high abundance of <20 cm pollock within
cluster F4 during 1997. Therefore the percentage of total
Kotwicki et al.: Variation in the distribution of Theragra cholcogramma
581
biomass was particularly low in clusters Fl, F2, and F3
for that year. In cluster Fl we observed an increase in
biomass from 10% to 51%.
For pollock 21-29 cm, changes between cluster G2
and Gl resembled changes between clusters F2 and Fl.
The percentage of total biomass in these two clusters
changed from 57% to 0% and from 11% to 94%, respec-
tively (Fig. 2B).
A slightly different situation was observed for pol-
lock 30-39 cm (Fig. 2C). We identified three clusters
of decreasing biomass with temperature: H2, H3, and
H4 located, respectively, northwest of Zhemchug Can-
yon, northwest and east of the Pribilof Islands. Overall
predicted biomass change in H2, H3, and H4 decreased
from 65% to 2%. The offset for this negative change was
found in cluster HI, where we noted a positive change
from 4% to 75%.
Areas with decreasing fish biomass for pollock 40-49
cm were located within cluster 12 (Fig. 2D). Biomass de-
creased from 58% in the coldest year to 4% in the warm-
est year. We observed temperature-related increases in
biomass mostly north of 12 in cluster II (0%-49%).
A quite different situation was observed for pollock
>50 cm (Fig. 2E). Although pollock of this size seemed
to concentrate northwest and northeast of the Pribilof
Islands (similar to pollock 30-49 cm) during cold years;
in warm years they were found in EIT surveys mainly
in the southeast, as opposed to the smaller fish that are
found mainly in the north. Results for pollock >50 cm
should be treated cautiously because only a very small
part of the entire population of pollock this size can be
detected with the EIT survey (Ianelli et al.3). Because
of the benthic habits of pollock >50 cm (Shuntov et al.,
1993), most were detected in BT surveys.
Overall, our analysis of EIT survey data indicated
a northward temperature-related shift of 50-80% of
pollock <50 cm in two major areas. With increasing
temperature, the density of pollock <40 cm decreased
northwest of Zhemchug Canyon in a large area at 100 m
to 200 m depths. Similarly, the density of pollock 30-
49 cm decreased northwest of the Pribilof Islands. Off-
setting these decreases, pollock density increased in the
northernmost area of the survey (close to the U.S. -Rus-
sia Convention Line).
Although the direction of the shift was the same for
all length categories up to 50 cm, the mean distance
between the clusters with negative slopes and clusters
with positive slopes increased with fish size (Table 2).
Bottom trawl survey
For pollock <20 cm, we observed a decrease in pollock
biomass with temperature in cluster A3 covering the
3 Ianelli, J. N., T. Buckley, T. Honkalehto, N. Williamson,
and G. Walters. 2001. Bering Sea-Aleutian Islands wall-
eye pollock assessment for 2002. In Stock assessment and
fishery evaluation report for the groundfish resources of the
Bering Sea/Aleutian Islands regions, p. 1-105. North Pac.
Fish. Manag. Council. Anchorage, AK.
area west of the Pribilof Islands and north to Zhemchug
Canyon (Fig. 3A). We observed an increase in pollock
biomass in shallower areas north of Pribilof Island
(A4), as well as in the areas of 50-100 m depth east
from the Pribilof Islands (A5). The magnitude of change
was somewhat smaller than that observed for the EITS
survey (see Fig. 3A for details).
For pollock 20-29 cm, we observed a decrease in
biomass from 70% to 5% in the area northwest of the
Pribilof Islands (cluster B5). A cumulative increase in
biomass from 7% to 52% of total biomass was observed
in clusters Bl and B4 north of B5, and in clusters B6
and B7 in shallower waters (Fig. 3B). Relatively weak
relationships were found between pollock biomass and
temperature for clusters B2, B3, and B8.
For pollock 30-39 cm, we observed a temperature-
related decrease in biomass in clusters C2 and C4 (42%
to 1%, and 68% to 12% accordingly) (Fig. 2C). Increase
in biomass was observed in cluster CI (2-32%) north
from C2. Positive change was also observed in cluster
C5 (0-17%) within the shallow (<100 m) part of the
southeastern Bering Sea shelf.
Clusters D2 and D4 represented areas where we ob-
served a significant decrease in biomass for pollock
40-49 cm (from 5% to 1%, and from 41% to 11%) (Fig.
3D). Increased biomass was detected in cluster Dl lo-
cated north from D4 and in D5 located to the east of
D4 in shallower waters.
Very small changes were detected for pollock >50 cm.
Although three clusters had a relatively strong pollock
biomass and temperature relationship, the magnitude
of biomass changes within the range of observed tem-
peratures was quite small (Fig. 3E).
Overall, as with the EIT surveys, northward shifts
in distribution in warmer years were found in the BT
survey data for pollock <30 cm. The magnitude of these
northward shifts was somewhat smaller (15-30%) than
those detected by EIT surveys. In addition, these data
suggested an inshore eastward redistribution of pollock
in warmer years. Changes for pollock >50 cm were evi-
dent but small (in the range of 15%).
Discussion
Inferring seasonal pollock migration from interannual
variations in distribution
Interannual differences in the timing of the migration
from spawning grounds to forage areas are related to
water temperatures. The relationship between tem-
perature and the spatial distribution of a seasonally
migrating species could represent either a change in the
winter location of the stock or a change in the timing of
the migration or both (Mountain and Murawski, 1992).
Although the evidence is not conclusive, data suggest
that most pollock populations spawn in late winter
or early spring in the same locations year after year
(Bailey et al., 1999a). For example, large, prespawn-
ing aggregations of pollock have been surveyed around
582
Fishery Bulletin 103(4)
Bogoslof Island every year since 1988 in the winter
(Honkalehto et al.4). Further support that temperature
is related to the timing of the postspawning migration
may come from temperature effects on physiological
aspects of spawning. Cold water temperatures may delay
the onset of spawning and extend the spawning period
of walleye pollock as has been found for another gadid
(Kjesbu, 1994) and for flatfish (Lange and Greve, 1997)
in the Atlantic.
The surveyed distribution of pollock in warmer years
should be more representative of that seen later in a
typical spring-summer warming cycle than the distri-
bution of pollock seen in colder years. Bottom tempera-
tures generally increased over the EBS and northern
Bering Sea (NBS) during spring and summer (Overland
et al., 1999; Khen et al., 2001; Stabeno et al., 2001).
Our results show that the warmer the bottom water
during spring-summer groundfish surveys, the farther
away pollock <50 cm are found from their major spawn-
ing grounds. Thus, we interpret areas having lower
pollock density with increasing temperature (clusters
with negative slope) to be areas from which pollock are
emigrating, and areas having higher pollock density
with increasing temperature (clusters with positive
slope) to be areas to which pollock are immigrating
(Figs. 2 and 3).
Routes and directions of the migrations
As the water warms during spring and summer, pol-
lock generally migrate northward, northwestward, and
inshore to shallower waters. Larger pollock (>30 cm)
begin their feeding migration from spawning grounds.
In many areas (white areas — Figs. 2 and 3) we did
not detect a significant increase or decrease in pol-
lock abundance in relation to temperature, e.g., in the
major pollock spawning area north of Unimak Island
(Hinckley, 1987; Bulatov, 1989), and this finding may
indicate that migration progressed beyond this area
before it was surveyed, even in the coldest years, or that
migrations were not pronounced in this area. However,
we observed a very large decrease in biomass with
increasing temperature in the Pribilof Islands area (i.e.,
within clusters A3, B5, C4, D4, E2, H3, and 12), which is
another important pollock spawning location (Maeda and
Hirakawa, 1977; Hinckley, 1987; Bulatov, 1989; Bailey
et al., 1999a). An offsetting increase in biomass was
observed in the northernmost part of the survey area
(clusters Bl, CI, Dl, Fl, Gl, HI, and ID and in shallower
waters (clusters A4, A5, B6, B7, C5, and D5), which may
indicate that pollock migrate north and inshore during
the warming season. Echo integration trawl data indi-
Honkalehto, T., N. Williamson, D. Hanson. D. McKelvey, and
S. de Blois. 2002b. Results of the echo Integration-trawl
survey of walleye pollock (Theragra chalcograma) conducted
on the southeastern Bering Sea shelf and in the southeastern
Aleutian Basin near Bogoslof Island in February and March
2002. AFSC Processed Report 2002-02, 49 p. Alaska Fish.
Sci. Cent., NOAA, Natl. Mar. Fish. Serv., 7600 Sand Point
Way NE, Seattle, WA 98115.
cate that smaller pollock (<29 cm) probably begin their
migration from overwintering areas (clusters F2 and
G2) located mainly northwest of the Zhemchug Canyon.
These results agree with observations made by Bailey
et al. (1999b) that small age-0. age-1, and age-2 pollock
are distributed farther north than larger age-3 and older
pollock. Migrations continued generally northward to
the U.S. -Russia Convention Line. The near-bottom part
of the pollock population (detected in the BT survey)
also migrates northeastward into shallower waters. At
this point we cannot describe the exact starting and
ending points of migration but only the general direc-
tion, because surveys are performed after most of the
spawning has been completed, and we lacked data for
the NBS, where part of the pollock EBS population is
probably migrating.
The direction of movements indicated by the EIT
survey data and the BT survey data were somewhat
different because of the effect of depth on the avail-
ability of pollock to each survey. As pollock migrate into
shallower water they become more available to the BT
survey and less available to the EIT survey. Therefore
the BT survey indicates greater movement into shal-
lower water, whereas the EIT survey indicates greater
movement in a northerly direction.
Seasonal migrations by pollock in the EBS are broad-
ly recognized as occurring but have not been well sub-
stantiated; however, most of the general observations
and descriptions are in agreement with our results. It
is generally recognized that the feeding migration of
some EBS pollock takes them northwestward beyond
our survey area and into Russian waters (Shuntov et
al., 1992; 1993; Stepanenko, 2001). Pola (1985), in her
numerical simulation of pollock migrations in the EBS
identified two types of pollock feeding migration. One
was temperature induced in the northward direction,
and the other was seasonal in the northeastern direc-
tion toward shallower waters. Shuntov et al. (1993)
considered migrational activity to start with the on-
set of sexual maturity, but our findings indicate that
immature pollock do undergo feeding migrations in a
northwestward direction, but over shorter distances
than those traveled by mature pollock. Stepanenko
(2001) also recognized migration by immature pollock.
Only a few pollock tagged in the EBS have been recov-
ered (Yoshida, 1985), but the relationships between the
release and recovery locations are consistent with our
findings of a northwestward feeding migration during
the spring and summer over most of the EBS shelf and
a northeastward migration into shallower water on the
southeast EBS shelf.
Length-based differences in migration patterns
Our analysis of the EIT surveys indicates that the
migrations of pollock <30 cm are shorter than those of
pollock 30-50 cm. The distance pollock need to cover
from clusters F2 and G2 to clusters Fl and Gl (241.3
km and 217.5 km) is much shorter than the distance
to be covered by larger fish from clusters H4, H3, H2,
Kotwicki et al : Variation in the distribution of Themgro chalcogrommo
583
and 12 to clusters HI and II (368.3 km and 453.7 km,
respectively). Similar size-dependent differences in the
distance of seasonal migrations were reported for Pacific
hake (Merluccius productus), another gadoid from the
north Pacific (Dorn, 1995). These observations may
support the length-based hypothesis of Nottestad et al.
(1999) for feeding migrations in pelagic fish. Focusing
on the energetic cost-benefit relationship of long distance
migration, they concluded that migration distance is a
function of length, weight, and age. Smaller fish may
undergo shorter feeding migrations because the ener-
getic cost of migration can exceed their total energy
intake resulting from the of greater hydrodynamic drag
associated with smaller fish size.
Migrations of the largest pollock (>50 cm), detected
from the BT survey data, were of much lower magnitude
then those of smaller fish. Our models indicate that only
about 15% offish in this length category move between
clusters in the northeastern direction toward shallower
waters. These small changes detected in BT data con-
tradict those seen in EIT data. Whereas a small north-
ward shift in biomass (mostly from cluster E2 to cluster
E4) was detected with BT data, a southeastward shift
was detected with EIT data. However, because the EIT
survey is not well suited for estimating the distribution
of pollock >50 cm, we are inclined to put more weight
on the BT data to explain temperature-related changes
in biomass distribution for this length category. Larger
pollock (>50 cm) appear to change their migratory be-
havior. Shuntov (1992) noticed that the distribution
of larger pollock (>54 cm) fundamentally differs from
that of smaller pollock and that larger pollock are more
benthic in behavior and feeding. Stepanenko (2001) did
not observe any migrations to the Russian zone for pol-
lock six years or older. We propose that the difference
in the migratory behavior between pollock <50 cm and
pollock >50 cm is linked to a well-known shift toward
a diet offish with increasing pollock size (Bailey and
Dunn, 1979; Dwyer et al., 1987).
Why do pollock migrate?
Pollock feeding migrations in the EBS may be driven by
a combination of four factors: temperature, zooplankton
production, currents, and length of daylight.
Changes in the water temperature may affect pol-
lock migrations. Bottom water temperature over the
Bering Sea shelf rises between April and September
(Pavlov and Pavlov, 1996; Overland et al., 1999; Khen
et al., 2001; Stabeno et al., 2001). Our results indicate
that with rising temperature pollock generally migrate
northward and inshore. Pollock appear to avoid tem-
peratures below 0°C (Swartzman et al., 1994); therefore
a seasonal increase in temperature above 0°C can open
new geographic areas for migration. Temperature was
presented as one of several important stimuli affect-
ing fish movements by Harden Jones (1968) and by
Wielgolaski (1990), who noticed that capelin (Mallotus
villosus), Atlantic cod (Gadus morhua), and haddock
(Melanogrammus aeglefinus) in the Barents Sea migrate
north towards a preferred temperature, either directly
to satisfy metabolic requirements, or indirectly, as when
attracted by food organisms.
Seasonal patterns in zooplankton production and prey
availability largely coincide with seasonal patterns in
pollock migration and distribution. The role of food
availability in driving fish-feeding migrations has been
described for other zooplanktivores such as Pacific hake
(Dorn, 1995), Atlantic herring (Clupea harengus), blue
whiting iMieromesistius poutassou), mackerel (Scomber
scombrus) and capelin (Nottestad et al., 1999). In the
Bering Sea, the abundance of zooplankton is high on
the EBS and NBS shelf throughout spring and sum-
mer, but it remains high in autumn only in the NBS
(Springer et al., 1989; Chuchukalo et al., 1996; Coyle
et al., 1996). Copepods and euphausiids are major prey
groups for pollock during spring and summer in the
northwest area of the EBS shelf, but in autumn, 30-49
cm pollock increase their feeding on fish and decapods
(Dwyer et al., 1987) which may be related to a decrease
in the availability of these prey (Willette et al., 1999) in
this area. Further north in the Navarin-Anadyr area,
copepods and euphausiids remain major prey compo-
nents in the diet of pollock <50 cm through summer and
autumn (Shuntov et al., 2000). The migration pattern
of pollock indicates they may follow their food supply as
the production and abundance of zooplankton proceeds
northward. Pollock larger than 50 cm do not undergo
northward feeding migrations because small pollock,
other fish, and benthos are the main components of
the diet (Dwyer et al., 1987; Yoshida, 1994; Shuntov
at al., 2000).
In the area of pollock migrations northwest of Pribilof
Islands current speeds are in the range of 1-5 cm/s at
the 100 m depth and they generally run in the north-
west direction (Stabeno et al., 2001). Current direction
coincides with the direction of pollock migrations, so
that the cost of the migration may be offset by swim-
ming in the same direction as the transporting cur-
rent (Nottestad et al., 1999). Water currents can also
influence fish migration indirectly by providing visual
stimuli arising from the moving background (Harden
Jones, 1968) or by transporting food. Springer et al.
(1989) suggested that the transport of zooplankton by
the northwest current may cause greater levels of zoo-
plankton concentration in the NBS. Because of the lack
of data on current speed, he speculated that a current
velocity in the range of 20 cm/s was needed to explain
these high levels of zooplankton in the NBS if the high
levels of zooplankton are based only on currents. The
latest observations of current on the Bering Sea shelf
do not support these hypotheses (Stabeno et al., 2001).
However northwestern currents may contribute to high-
er zooplankton biomass in the NBS.
Nottestad et al. (1999) suggested that light conditions
may play a role in fish feeding migrations because dur-
ing summer day-length increases the farther north fish
travel, thus potentially increasing feeding duration for
pelagic visual predators. Pollock are visual predators
and light conditions affect feeding efficiency of pollock
584
Fishery Bulletin 103(4)
(Ryer and Olla, 1999; Ryer et al., 2002); therefore it may
be that longer days at northern latitudes make a north-
ward feeding migration beneficial by possibly providing
an extended window of search time if the pollock happen
to be in a locally depauperate area. However, day-length
remains long enough in the entire Bering Sea for pollock
to feed to satiation, and their gastric evacuation rate is
slow (Dwyer et al., 1987), making the need to entirely
fill their stomachs every day very unlikely.
62" N
6CTN
58:N -
56:N -
54°N
62°N -
60°N
58 N -
56"N
54°N
180°W 175°W
1
1 70"W
t — r
165°W 180°W
At this time it is impossible to assess which factor
is most important in driving pollock migrations, but in
summary we can conclude that pollock, as visual pelag-
ic predators, benefit from northward feeding migrations
during seasonal warming. Because three of the factors
(excluding current) are similar throughout the Northern
Hemisphere, we should see similar migration patterns
for other pelagic fish of the north. Other examples in-
clude Pacific hake migrating along the North American
west coast from California to British Columbia
(Francis and Bailey, 1983; Dorn, 1995). Her-
ring in the Norwegian Sea undergo seasonal
feeding migrations in the northwestern direc-
tion from the south-central coast of Norway to
the areas located northeast of Iceland (Ferno,
1998). Blue whiting, mackerel, and capelin
from the north Atlantic undergo northward
feeding migrations (Nottestad et al., 1999).
Pacific saury (Cololabis saira), chub mackerel
(Scomber japonicus). Pacific sardine (Sardinops
sagax melanosticta), and Japanese anchovy
(Engraulis japonicus) from the western North
Pacific are reported to migrate northwards
during the summer (Novikov, 1986). Capelin,
Atlantic cod, and haddock in the Barents Sea
migrate north towards a "preference" tempera-
ture during summer (Wielgolaski, 1990). All
these species have characteristics similar to
those of Bering Sea pollock — that is, a pelagic
or semipelagic life style, a diet of zooplankton,
winter or spring spawning activity, and feed-
ing migrations that take place during spring
and summer.
64°N
62°N
60°N
58°N
56° N
- 64 'N
_ 62- N
- 60"N
-\-- 58°N
- 56°N
175'W
170 W
165 -W
1 60"W
Figure 5
Bottom water temperature contours during the bottom trawl
survey in the coldest year (1999 — upper map I and warmest
year (1996 — lower map).
Why is temperature important?
Temperature may affect the proportion of the
stock that is in the standard EBS survey area.
Ianelli et al.,3 using population modeling, esti-
mated that fewer pollock were detected during
the BT survey in the EBS with increasing tem-
perature, and fewer pollock would indicate that
pollock are probably leaving the survey area
during seasonal migrations. We conclude that
a significant part of the EBS pollock popula-
tion migrates into the Navarin-Anadyr area,
which can have an impact on the way the EBS
stock is managed. We should account for land-
ings of pollock in the Navarin-Anadyr area,
estimate how much of these landings include
pollock from the EBS stock, and use this esti-
mate in determining the EBS total allowable
catch. Further research is needed to quantify
the proportion of the EBS stock migrating
into the Russian fishing zone and to estimate
the number of pollock caught there. Stokes5
suggested that the biomass estimates from
the NBS are in the range of 0.5-1.0 million
' See next page for footnote text.
Kotwicki et al.: Variation in the distribution of Theragra chalcogramma
585
metric tons per annum and the exploitation rate is in
the range of 0.5 million metric tons (50-100% of the
total estimate).
Ongoing climate changes may affect pollock distri-
bution between the U.S. and Russian EEZs. Stabeno
and Overland (2001) reported a shift toward an earlier
spring transition in the Bering Sea. This can affect
the starting time of pollock migrations and the length
of time fish spend in the Russian EEZ, increasing the
availability of fish to the Russian fleet. This situation
should encourage us to closely monitor changes in mi-
gration patterns of pollock in the Bering Sea.
Significant bias or error variation may be caused by
the interaction of fish movement with survey protocol.
For even relatively low fish migration velocities (<0.5
m/s), bias in estimated fish biomass can be very large
(McAllister, 1998). Therefore, fish migration vectors
should be estimated to minimize the bias created by
not taking into account these migrations in biomass
estimates.
Acknowledgments
The authors thank Angie Greig and Jan Benson for an
introduction to ArcGIS and help with geospatial prob-
lems that occurred during analyses of data. We also want
to thank Kevin Bailey, Jerry Hoff, Jim Ianelli, Jay Orr,
David Somerton, Phyllis Stabeno, Gary Stauffer, Neal
Williamson, and three anonymous reviewers for discus-
sions and review of earlier versions of this manuscript.
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588
Abstract — The identification of larval
istiophorid billfishes from the western
North Atlantic Ocean has long been
problematic. In the present study, a
molecular technique was used to posi-
tively identify 27 larval white marlin
(Tetrapturus albidus), 96 larval blue
marlin (Makaira nigricans), and 591
larval sailfish (Istiophorus platyp-
terus) from the Straits of Florida
and the Bahamas. Nine morphometric
measurements were taken for a subset
of larvae (species known), and lower
jaw pigment patterns were recorded
on a grid. Canonical variates analysis
(CVA) was used to reveal the extent
to which the combination of morpho-
metric, pigment pattern, and month
of capture information was diagnos-
tic to species level. Linear regression
revealed species-specific relationships
between the ratio of snout length to
eye orbit diameter and standard
length (SL). Confidence limits about
these relationships served as defining
characters for sailfish >10 mm SL and
for blue and white marlin >17 mm SL.
Pigment pattern analysis indicated
that 40% of the preflexion blue marlin
examined possessed a characteristic
lower jaw pigment pattern and that
62% of sailfish larvae were identi-
fiable by lower jaw pigments alone.
An identification key was constructed
based on pigment patterns, month of
capture, and relationships between
SL and the ratio of snout length to
eye orbit diameter. The key yielded
identifications for 69.4% of 304 (blind
sample) larvae used to test it; only
one of these identifications was incor-
rect. Of the 93 larvae that could not
be identified by the key, 71 (76.3%)
were correctly identified with CVA.
Although identification of certain
larval specimens may always require
molecular techniques, it is encour-
aging that the majority (92.4%) of
istiophorid larvae examined were
ultimately identifiable from external
characteristics alone.
Toward identification of larval sailfish
(Istiophorus platypterus), white marlin
(Tetrapturus albidus), and blue marlin
(Makaira nigricans) in the western
North Atlantic Ocean*
Stacy A. Luthy
Robert K. Covwen
Rosenstiel School of Marine and Atmospheric Science
University of Miami
4600 Rickenbacker Causeway
Miami, Florida 33149
Present address (for S. A. Luthy): Baruch Marine Field Laboratory
PO. Box 1630
Georgetown, South Carolina 29442
Email address (for S A. Luthy). stacy@belle.banjch.se edu
Joseph E. Serafy
National Marine Fisheries Service
Southeast Fisheries Science Center
75 Virginia Beach Drive
Miami, Florida 33149
Jan R. McDowell
The Virginia Institute of Marine Science
School of Marine Science
College of William and Mary
PO Box 1346
Gloucester Point, Virginia 23062
Manuscript submitted 14 July 2004
to the Scientific Editor's Office.
Manuscript approved for publication
6 April 2005 by the Scientific Editor.
Fish. Bull. 103:588-600 (2005).
Research on the early life history of
exploited fishes benefits management
efforts by elucidating the temporal
and spatial distribution of spawning,
cohort strength, and biological and
physical factors affecting recruitment
(Lasker, 1987). The ability to confi-
dently identify specimens to species
is necessary in any early life history
study (Collette and Vecchione, 1995).
This has not yet been achieved for
larval billfishes of the family Istio-
phoridae from the Atlantic Ocean:
sailfish (Istiophorus platypterus),
blue marlin (Makaira nigricans),
white marlin (Tetrapturus albidus),
and longbill spearfish (Tetrapturus
pfluegeri).
Larval istiophorids are easily dis-
tinguished from larval swordfish
(Xiphias gladius, family Xiphiidae).
However, larval istiophorids are dif-
ficult to identify below the family lev-
el. Full fin-ray complements are not
present until a larva reaches 20 mm
in length, and even then, meristic
counts are of limited use for identifi-
cation because of significant overlap
in counts among species. At best, spe-
cies possibilities can be eliminated
only for specimens with counts in the
extremes of their ranges (Richards,
1974). The only definitively diagnos-
tic count is the vertebral formula for
Makaira (11 precaudal and 13 caudal)
versus that of the other istiophorids
(12 precaudal and 12 caudal) (Rich-
ards, 1974). Larger blue marlin lar-
* Contribution SFD-2003-0010 from NOAA
Fisheries Sustainable Fisheries Division,
Southeast Fisheries Science Center, 75
Virginia Beach Drive, Miami, Florida
33149.
Luthy et al. Identification of larval sailfish, white marlm, and blue marlin in the western North Atlantic Ocean
589
vae may also be identified by the presence of a complex
lateral line. Ueyanagi (1964) found this character in
Pacific blue marlin of 20 mm standard length (SL), but
the smallest SL of an Atlantic blue marlin from a recent
collection in which a complex lateral line was visible
was 26.9 mm. At lengths <20 mm, specific identifica-
tion of istiophorids is even more uncertain. Ueyanagi
(1963; 1964) based the identification of Indo-Pacific
istiophorids <5 mm SL on four characters: 1) anterior
projection of the eye orbit; 2) the position of the tip of
the snout in relation to the middle of the eye; 3) pres-
ence of pigments on the branchiostegal and gular mem-
branes; and 4) whether the pectoral fins are rigid — a
character that applies to larval black marlin tMakaira
indica), a species not known to spawn in the Atlantic
Ocean. For fish >5 mm SL, the characters of relative
snout length and eye size are used. Ueyanagi (1964)
described sailfish, striped marlin (Tetrapturus audax,
the Pacific counterpart to white marlin), and shortbill
spearfish {Tetrapturus angustirostris) between 10 and
20 mm SL as having long snouts. The short snout group
comprised blue marlin and black marlin. The angles at
which the pterotic and preopercular spines protrude
from the body have also been useful in identifying Indo-
Pacific specimens (Ueyanagi, 1974a).
A troubling aspect of current larval istiophorid iden-
tification methods is the difficulty in using some of the
above characters. If a specimen is fixed with its mouth
open, snout position with respect to eye is an unread-
able character (Richards, 1974), and misidentifications
can occur (Ueyanagi, 1974a). Evaluation of certain char-
acters (e.g., whether the eye orbit projects anteriorly)
can be highly subjective. The lack of confirming identi-
fication characters compounds the problem; if just one
character cannot be assessed, identification may not
be possible (Richards, 1974). An additional problem is
the apparently high variability in characters such as
pigment locations and head spine angles in Atlantic
istiophorids (Richards, 1974).
Most of the larval specimens examined by Ueyanagi
came from the Indo-Pacific; he assumed that the same
identification characters would apply to their Atlantic
counterparts (Ueyanagi, 1963, 1974a). Although recent
genetic evidence supports Morrow and Harbo's (1969)
opinion that Atlantic and Indo-Pacific sailfish are actu-
ally populations of a global species (Finnerty and Block,
1995; Graves and McDowell, 1995), morphological dif-
ferences have been noted in sailfish, especially at 90
cm. Specifically, the pectoral fin is longer, in relation
to the body, in Atlantic sailfish than in Indo-Pacific
sailfish. Differences in the spread of the caudal fin and
maximum total length have also been observed. These
characters were the impetus behind the separation of
sailfish, at least to subspecies, by ocean basin (Naka-
mura, 1974). Regardless of the taxonomic status of the
Atlantic and Indo-Pacific billfishes, physical attributes
of istiophorid species may vary by region. Therefore, the
assumption that the larvae of Atlantic istiophorids can
be identified by using the same characters attributed to
Indo-Pacific istiophorids may not be valid.
Billfishes are not the only group whose larval iden-
tification has proven difficult. Species of the genus
Sebastes, the rockfishes, have some morphological and
pigmentation differences as larvae, but identification
was difficult and uncertain until genetic methods were
employed (Rocha-Olivares et al., 2000). Fulford and
Rutherford (2000) solved a similar problem by combin-
ing allozyme analysis of larval tissues with landmark-
based morphometries to distinguish between species of
the genus Morone. In each study, a molecular technique
was used to confirm larval species identity, facilitat-
ing the development of morphometric identification
techniques.
Several molecular methods for identifying adult
billfishes have been developed (Chow, 1993; Innes et
al., 1998; McDowell and Graves, 2002). In the present
study, larval istiophorids from Atlantic waters were
identified to species using restriction fragment length
polymorphism (RFLP) analysis of a 1.2-kb segment
of nuclear DNA, as described for adult billfishes by
McDowell and Graves (2002). In this article we pres-
ent data for genetically identified istiophorid larvae,
analyses of morphometric and qualitative characters,
and a key for the identification of larval istiophorids of
the Straits of Florida and the Bahamas.
Materials and methods
Larval material
Larval istiophorids were collected between June 1998
and April 2002 from the Straits of Florida and Exuma
Sound, Bahamas. Several preservation fluids were used,
but the majority of the larvae (-1000) were preserved
in 70-95% ethanol. Butylated hydroxytoluene (BHT)
saturated ethanol was used to preserve 150 larvae.
Approximately 300 larvae were fixed in 10% unbuffered
formalin and then transferred to 70% ethanol. In the
laboratory, each fish was assigned a unique identification
number and stored separately.
Molecular identification
Total DNA was extracted from the right eyeball of each
larva, using either a quick-digest method (Ruzzante et
al., 1996) or a standard high-molecular weight DNA
extraction protocol (Sambrook et al., 1989). Larval
identification was achieved by PCR amplification of
the nuclear locus MN32-2 (Buonaccorsi et al., 1999),
and subsequent RFLP analysis (restriction endonucle-
ases Dra I and Dde I, Life Technologies, Bethesda,
MD). If the restriction fragment pattern (Fig. 1) of a
larva matched one of those described for a known-iden-
tity adult, the larva was assigned to that species. See
McDowell and Graves (2002) for detailed protocols and
reaction parameters. Preliminary attempts to amplify
DNA from formalin-fixed larvae failed; only ethanol-
preserved specimens were used in subsequent molecular
work.
590
Fishery Bulletin 103(4)
1Kb Plus DNA ladder
sailfish
white marlin
blue marlin
blue marlin
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650—
650—
500—
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400—
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200—
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Figure 1
Common Dele I and Dra I restriction patterns for the MN.32-2 1
)CUS
rf positively
identified larval istiophorids from the Straits of Flori
da an
d the
Bah
amas.
The left lane of each gel contains a DNA size standa
•d (Life Te
chno
ogies,
Bethesda,
MD), measured in base pairs.
Characters
A subset of the molecularly identified istiophorid larvae
were examined to ascertain which morphological char-
acters might aid in specific identification and possibly
obviate the need for future molecular work. The measure-
ments made by Richards ( 1974) served as a starting point
for quantitative larval descriptions: standard length (SL);
snout length (SN); tip of the snout to the center of the
eyeball (SN-E); diameter of the eye (ED); diameter of the
eye orbit (OD); head length (HL); and difference in length
between the upper and lower jaws (JD). To this suite
were added measurements of the preopercular (PRO)
and pterotic (PTS) head spines. All measurements were
taken with Image-Pro Plus software (version 4.5, Media
Cybernetics, Silver Spring, MD), and each specimen was
viewed through a CoolSNAP-PROcf monochrome digital
camera (Media Cybernetics, Silver Spring, MD) which
was connected to a Leica MZ12 dissecting microscope (at
magnifications 0.8-10. Ox). Each larva was soaked in tap
water for one minute before measurements were taken,
to rehydrate the fish and facilitate handling. SL and
PRO measurements were made from the dorsal view, JD
measurements were made from the ventral view, and all
other measurements were made from the left lateral view
(Fig. 2). Because the preopercular spine often prevents
an istiophorid larva from lying on its side, a side view
was obtained by using the surface tension of the still-wet
larva to adhere it to the side wall of a Petri dish. Care
was taken to maintain the two points of measurement
on a plane parallel to the microscope lens.
Pigments observed on the ventral surface of the lower
jaw rami, gular membrane, and branchiostegal mem-
branes of each larva were drawn onto a generalized dia-
gram of the larval istiophorid lower jaw (Fig. 3). A grid
was then superimposed on the diagram, and the shape
(pointate or stellate) and number of chromatophores in
each grid cell were recorded. Pigment data were also
recorded as binary presence or absence per grid cell.
Two other categorical variables assessed were flexion
stage (i.e., preflexion, flexing, postflexion) and the posi-
tion of the tip of the snout with regard to a plane passing
through the center of the eye and the mid-line of the body
(i.e., below, even, above). Although the latter character is
useful for identifying Indo-Pacific istiophorids (Ueyanagi,
1963. 1964), in our collection it was highly variable with-
in species, and therefore it was not analyzed further.
Month of capture was considered a partially discrimi-
nating character based on differences in the length and
timing of spawning seasons of local populations. Spawn-
ing seasons were determined by de Sylva and Breder
(1997) by gonad histology studies.
Luthy et al : Identification of larval sailfish, white marlin, and blue marlm in the western North Atlantic Ocean
591
Figure 2
Morphometric measurements illustrated on a 10.7-mm SL sailfish. SN =
snout length; SN-E = snout to mid-eye; OD = eye orbit diameter; ED = eye
diameter; PTS = length of pterotic spine; PRO = length of preopercular
spine. Drawings by S. Luthy.
Gular membrane
Branchiostegal
membrane
Figure 3
Lower jaw pigments were characterized by drawing chromatophores onto
a generalized lower jaw diagram (A), reproduced from Richards (1974). A
grid (B) was then superimposed onto the diagram and the number and
shape of chromatophores were recorded for each grid cell. The numbers in
diagram B are numbers used to identify the cells of the grid and not the
number of chromatophores per cell.
592
Fishery Bulletin 103(4)
Data analyses
Canonical variates analysis (CVA) was used to visualize
the separation between species and the relative impor-
tance of all variables (morphometric characters, pigment
patterns, and month of capture) in that separation.
Results from the CVA were used to help drive charac-
ter selection for subsequent analyses. The significance
of the canonical axes was obtained with a Monte Carlo
permutation test (499 iterations). The canonical analyses
were performed with the software CANOCO (version 4.5,
Microcomputer Power, Ithaca, NY), and plotted with the
associated software CANODRAW.
In the CVA, all the molecularly identified white mar-
lin (21) and blue marlin (68) with full measurement sets
(i.e., no missing values) and a subset of sailfish (135)
with full measurement sets were compared. Every at-
tempt was made to include fish from different locations,
different years and months of collection, and across
the full available size range of each species, in order to
capture as much intra- and inter-species variation as
possible. Forward selection was used as a guide for the
creation of a reduced set of variables by retaining those
that were significant for discrimination at oc=0.05 in a
Monte Carlo permutation test (499 iterations). Months
that were excluded by selection were restored to the
variable set to insure that the entire spawning season
was represented. It was assumed that pigment on the
right lower jaw ramus was of equal importance as pig-
ment in the corresponding location on the left lower jaw
ramus; thus if a pigment grid from only one side of the
jaw was selected, the corresponding grid from the other
side of the jaw was added back to the reduced set.
In addition to its function as an exploratory tool for
character selection, CVA with the reduced set of vari-
ables was used to identify unknown larvae to species.
Ordination coordinates of an unknown larva were ob-
tained by summing the products of the canonical coef-
ficients and the character values for the unknown (stan-
dardized to mean 0, standard deviation 1). The identity
of an unknown larva was determined by its placement
in the ordination with respect to the reference larvae.
The CVA provided clues as to which individual pig-
ment grid cells were important for species discrimina-
tion, but cluster analysis was employed to examine
overall lower jaw pigment patterns. Simple average
link cluster analysis of Jaccard similarity indices was
executed on pigment grid cell presence (binary coding)
in the suite of lower jaw grid cells with BioDiversity
Pro1 software for the 26 white marlin with undamaged
lower jaws and for equal numbers of randomly chosen
blue marlin and sailfish. Analyses were conducted on
all larvae together, and separately by flexion stage. Pig-
ment drawings of the individual larvae within single-
1 McAleece, N., P. J. D. Lambshead, G. L. J. Paterson, and J.
D. Gage. 1997. The National History Museum and The
Scottish Association for Marine Science. Website: http://
www.sams.ac.uk/. [Accessed 5 February 2003.]
species clusters were examined visually for commonali-
ties. If a pattern was detected, the entire database of
pigment position, number, and shape of all molecularly
identified larvae was searched for that pattern. Lower
jaw pigment patterns that were confined to one species
only were deemed diagnostic characters.
Lower jaw pigment patterns alone did not resolve the
differences among the species sufficiently for identifica-
tion of all larvae. Therefore, for each species, continuous
variables related linearly to SL were regressed against
SL by using SAS (version 8.02, SAS Institute, Cary,
NO software. Two ratios were also examined in this
way — snout length divided by eye orbit diameter, and
snout length divided by eye diameter. Both ratios were
suggested by the results of the full-model CVA because
the influence of snout length was large and opposite in
sign to the large and similar vectors of orbit diameter
and eye diameter. The former ratio was also considered
by Ueyanagi (1963, 1964, 1974b) to be an important
distinguishing character for istiophorid larvae. The
same larvae that were used in the CVA analyses were
used for the regressions, plus three white marlin, two
sailfish, and two blue marlin that were excluded from
CVA because of a missing measurement. Suitability
of the characters for linear regression was assessed
visually. Confidence intervals of 95%, 99%, and 99.9%
were constructed around the regressions. Intersections
of the three levels of confidence intervals for the three
species were examined for maximum discrimination at
the smallest standard length. The relationships that
provided the best separation were included in the iden-
tification key.
The identification key was constructed from the vari-
ous characters that showed differences among the three
species. All of the larvae used in developing the key
were tested with it, as well as 12 blue marlin and 61
sailfish that were previously excluded from the analy-
ses. A set of 50 larvae were independently identified by
two observers unfamiliar with the key (naive observ-
ers). The only information about the fish provided to
them was month of capture, so that each made his own
measurements and pigment evaluations. The percent
accuracy of their identifications was taken as a measure
of the utility of the key.
Results
Molecular identification
The molecular identification technique was applied to
1044 larvae. Amplification success rates appear to have
been negatively affected by the addition of BHT to etha-
nol and by the use of the Ruzzante et al. (1996) DNA
extraction protocol. Overall, 714 (68.4%) istiophorids
were successfully identified to the species level. Sailfish
represented 82.8%- of this group (591 larvae), whereas
96 blue marlin (13.4%) and 27 white marlin (3.8%) were
identified. No longbill spearfish were identified. Sailfish
larvae (2.9 mm-18.3 mm SL) were collected from April
Luthy el al Identification of larval sailfish, white marhn, and blue marhn in the western North Atlantic Ocean
593
T
CONTINUOUS VARIABLES
■
rna^ch
o
NOMINAL VARIABLES
A
SAMPLES
BLUE MARLIN
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SAILFISH
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Figure 4
Canonical variates analysis with the reduced set of variables. Arrows
indicate the direction of increase in continuous variables and may
be extended backward through the origin of the graph to show a
decrease in the value of the character. Variables that extend far-
thest from the origin are most useful in the separation. SN = snout
length; JD = difference in the lengths of the jaws; ED = eye diameter;
PRO = length of preopercular spine; p (number i = presence of pig-
ment in lower jaw grid cell (number).
through September, white marlin (4.5 mm-20.3 mm SLi
were collected from March through June, and larval blue
marlin (3.8 mm-22.1 mm SL) were collected from June
through September. Month of capture closely matched the
reported spawning seasons for these species in the west-
ern North Atlantic: April through October for sailfish,
March through June for white marlin, and July through
October for blue marlin (de Sylva and Breder, 1997).
Because blue marlin larvae were also caught in June, the
blue marlin spawning season was expanded to include
that month for the purposes of the identification key.
Canonical variates analysis
In the CVA with all variables included, separation of the
three species was achieved with little overlap. Sailfish
larvae were separated from the marlins along canoni-
cal axis 1 (eigenvalue = 5.45). The separation was driven
mainly by ED, OD, and lower jaw pigmentation. White
marlin larvae separated from blue marlin primarily
along canonical axis 2 (eigenvalue = 0.79), largely by
month of capture, as well as SN, SN-E, and JD . The
overall ordination was significant at P=0.002.
The forward selection process, along with the re-addi-
tion of counterpart pigment grids and the full spawning
season, yielded the following 21 out of 32 variables:
March, April, May, June, July, August, September, SN,
JD, ED, PRO, and pigment grids 1-4, 6-9, 11, and 12.
The following variables were ultimately excluded from
the data set: SL, SN-E, OD, HL, PTS, and pigment
grids 5, 10, and 13-16. The degree of species overlap
was similar to that in the full model (Fig. 4). This
overall ordination was also significant at P=0.002. The
eigenvalue of the first canonical axis was 4.71, whereas
the eigenvalue of the second canonical axis was 0.71.
Coordinates obtained from the canonical coefficients
and character values, standardized by reference set
character means and standard deviations (Table 1),
accurately placed test "unknowns" in the ordination of
the reference larvae.
594
Fishery Bulletin 103(4)
2.5
2-
=5 1 5
05
D
O
0
sailfish 99% CI
sailfish individuals
white marlin 99% CI
white marlin individuals
blue marlin 99% CI
blue marlin individuals
O
v
aifi
i
aft''
-cf'
1 1
„"' cP -"
□ ° ,,* ^^^
,'
s
0
0
"23
t
0
i i i
-
25
75 10 125 15
Standard length (mm)
17.5
20
225
Figure 5
Relationship of the ratio of snout length to orbit diameter with standard length. Lines
represent 99% confidence intervals.
Lower jaw pigment patterns
Sailfish of all flexion stages with chromatophores on
one or both sides of the lower jaw rami and sometimes
in the middle of the gular membrane comprised single-
species clusters. Examination of all molecularly identi-
fied larvae showed that many sailfish had pigment on
the posterior % of the lower jaw, but a few marlins also
had stray pigments in that region. The minimum crite-
rion to identify sailfish by lower jaw pigment without
misidentifying other species was pigment in at least
three of lower jaw pigment grids 1, 2, 3, 7, 8, 9, and
11. The shape and number of chromatophores within
the grids was inconsequential. Not all sailfish larvae
possessed the putative sailfish pattern, but 61.8% of
molecularly identified sailfish (353 of 571 with intact
lower jaws) could be identified by their lower jaw pig-
ments alone.
Preflexion and flexing blue marlin also formed single-
species clusters owing to the pattern of a single, pointate
chromatophore in each of lower jaw grid cells 4 and 6, but
without any other pigment (except occasionally in grid cell
12 or 13). However, not all small blue marlin exhibited
this pattern. Eight of the 20 (40%) preflexion, molecularly
identified blue marlin with intact lower jaws could be ac-
curately identified by lower jaw pigments. Although some
postflexion white marlin had a similar pattern, no preflex-
ion or flexing larvae of other species were misidentified as
blue marlin by virtue of this pigment pattern.
Linear regressions
Residual plots showed no deviations from homogeneity
of variance. Snout length, snout to mid-eye, ratio of
snout length to eye diameter, and ratio of snout length
to orbit diameter were all linearly related to SL. Jaw
difference was linear and appeared to be helpful for dis-
criminating istiophorids >12 mm SL, but too few larvae
of this size were available for meaningful regressions.
The ratio of snout length to orbit diameter provided the
most separation between the species as indicated by the
full model CVA. The 99% upper limit of the regression
of this ratio against SL for white marlin was used to
separate sailfish from both marlin species at 10 mm SL.
If white marlin is ruled out as a possibility by month
of capture, sailfish can be separated from blue marlin
by the blue marlin upper 99% confidence limit for the
regression of the ratio of snout length to orbit diameter
at 8 mm SL. The lower 99% confidence limit for the
regression of the ratio of white marlin snout length
to orbit diameter separated them from blue marlin at
17 mm SL (Fig. 5, Table 2).
Luthy et al : Identification of larval sallfish, white marhn, and blue marlin in the western North Atlantic Ocean
595
Table 1
Canonical coefficients, mean, and standard deviation of each
character from the canonical variates analysis (reduced set of char-
acters).
The coordinate of a larva on
canonical axis 1 (x
can
be found by x=%c,jZ,
, where c = canonical coefficient and z = Ichar-
acter va
lue- character mean (/character
standard deviation.
The coordinate 'of a
larva on canonical axis
2 ' vi can be found by
-V=X<V,
PRO = pre-opercular; SN =
snout length; ED =
= eye
diameter; and JD =
difference in length between
upper and lower
jaws.
Canonical
Canonical
Character
i
coefficient, cv
coefficient, c2.
Character
standard
I iterativ
e
for canonical
for canonical
mean
deviation
count)
Character
axis 1
axis 2
(reference seti
(reference set)
1
March
-0.0963
0.7538
0.0134
0.1149
2
April
0.0772
0.7354
0.0357
0.1856
3
May
0.1961
0.7347
0.1786
0.3830
4
June
0.1267
0.6460
0.3036
0.4598
5
July
-0.0369
-0.2988
0.2054
0.4040
6
August
0.3465
0.2116
0.2143
0.4103
7
September
0.0000
0.0000
0.0491
0.2161
8
PRO
0.6697
-0.6728
2.0781
0.7076
9
SN
3.1678
0.9640
1.4978
0.8711
10
ED
-2.8386
0.0739
1.2011
0.4426
11
JD
-0.9464
-0.4947
0.1806
0.2222
12
Pigment 1
0.1450
-0.1156
0.2366
0.4250
13
Pigment 2
0.3483
-0.0953
0.2366
0.4250
14
Pigment 3
0.3564
0.1262
0.3036
0.4598
15
Pigment 4
0.0887
-0.2251
0.7768
0.4164
16
Pigment 6
-0.0263
-0.1084
0.8214
0.3830
17
Pigment 7
-0.0375
-0.1584
0.3259
0.4687
18
Pigment 8
0.2684
-0.0507
0.2098
0.4072
19
Pigment 9
0.3262
-0.0603
0.2545
0.4356
20
Pigment 11
0.4757
-0.1622
0.4241
0.4942
21
Pigment 12
0.2250
-0.1191
0.3438
0.4750
Regression of the ratio of snout length
offish in sample.
Table 2
to orbit diameter against standard length, r2
= coefficient of det
ermin
ation
and n -
- number
Species
Regression equation
r'~
n
Sailfish (Istiophorus platypterus )
White marlin (Tetrapturus albidus)
Blue marlin (Makaira nigricans)
SN.OD = 0.092SL + 0.242
SN:OD = 0.052SL + 0.373
SN:OD = 0.026SL + 0.510
0.94
0.95
0.74
137
24
70
Identification methods
Combination of species diagnostic lower jaw pigment
patterns, regression equations, and month of capture
resulted in the identification key found in Table 3. Of
the 304 larvae that were examined with the key by
the authors, only one was misidentified. This was an
8.02-mm blue marlin that was mistakenly identified
as a sailfish by question 6a in part I of the key. Of the
remaining fish, 31 larvae, all between 4 mm and 10 mm
SL could not be identified with the key. An additional
62 larvae, again mostly less than 10 mm SL, could be
narrowed down to only two species possibilities. Overall,
69.1% of the fish were correctly identified to species.
Accuracy improved with size. Eighty-five of the 93 larvae
that could not be identified by the key were plotted as
unknowns on the ordination (reduced set of variables),
at which time correct identification was obtained for
71 of them. Seven larvae could not be identified at all,
and seven were incorrectly identified because they were
plotted at the interface of two species groupings. The
remaining eight were incompatible with CVA because
596
Fishery Bulletin 103(4)
Table 3
Key for ethanol-preserved larvae and postlarval specimens of Istiophoridae caught in the Straits of Florida and the Bahamas.
Part I: for larvae <10 mm standard length (SL)
la Preflexion or flexing: a single, pointate chromatophore in each of lower jaw pigment grids 4 and 6:
with or without a single pigment in either grid 12 or 13; no other lower jaw pigments Makaira nigricans
lb Not as above 2
2a Any flexion stage; chromatophores of any number or shape in 3 or more of lower jaw pigment
grids 1, 2, 3, 7, 8, 9, 11 Istiophorus platypterus
2b Not as above 3
3a Larva caught in March, April, or May either Istiophorus platypterus or Tetrapturus albidus
3b Larva caught in June or later 4
4a Larva caught in June either Istiophorus platypterus, Tetrapturus albidus, or Makaira nigricans
4b Larva caught in July, August, September, or October 5
5a Standard length a8 mm 6
5b Standard length <8 mm either Istiophorus platypterus or Makaira nigricans
6a Snout length / orbit diameter >0.030SL + 0.551 Istiophorus platypterus
6b Snout length /orbit diameter s0.030SL + 0.551 Makaira nigricans
Part II: for larvae >10 mm SL
la Chromatophores of any number or shape in 3 or more of lower jaw pigment
grids 1, 2, 3, 7, 8, 9, 11 Istiophorus platypterus
lb Without the above lower jaw pigment pattern 2
2a Snout length / orbit diameter >0.057SL + 0.427 Istiophorus platypterus
2b Snout length / orbit diameter s0.057SL + 0.427 3
3a Larva caught in March, April, or May Tetrapturus albidus
3b Larva caught in June or later 4
4a Larva caught in July, August, September, or October Makaira nigricans
4b Larva caught in June 5
5a Standard length >17 mm 6
5b Standard length <17 mm either Makaira nigricans or Tetrapturus albidus
6a Snout length / orbit diameter >0.047SL + 0.319 Tetrapturus albidus
6b Snout length / orbit diameter <0.047SL + 0.319 Makaira nigricans
a measurement was missing. Thus, when the key and
CVA analyses were combined, 92.4% of the tested larvae
were correctly identified.
One of the two naive observers found that one larva
out of the test set of 50 was too damaged to be evalu-
ated. He correctly identified 35 larvae and found 14 to
be unidentifiable with the key. Overall, his success rate
was 71.4%. The other observer correctly identified 30
larvae, misidentified one (the larva not evaluated by
the other observer and the same larva misidentified by
the authors), and found 19 to be unidentifiable by the
key. His overall success rate was 60%. The difference in
the number of larvae that could not be identified with
the key was the result of differences in interpretation
of the lower jaw pigment position for larvae less than
10 mm SL.
Discussion
Because adults of four istiophorid species are found in
the Straits of Florida and Bahamian waters, a reliable
larval identification technique for these species is neces-
sary (Voss, 1953). Incorrect species identifications can
have serious ramifications on other areas of istiophorid
early life history research. For example, studies on early
growth would suffer if a larval blue marlin, which is
thought to reach 174 cm lower jaw fork length (LJFL)
by age one (Prince et al., 1991), were to be confused
with a larval sailfish, which reportedly grows to only
108.9 cm LJFL (Hedgepeth and Jolley, 1983; Prager et
al., 1995) by age one.
Few characters are available to separate the spe-
cies of larval istiophorids (Richards, 1974). Although
Luthy et al.: Identification of larval sallfish, white marlin, and blue marlin in the western North Atlantic Ocean
597
a single character may be used to separate fish into
groups, early work has lacked a means to confirm the
identity of the groups. Molecular techniques provided a
solution to this problem. A limitation of the molecular
identification technique that we used was that only
those larvae preserved in ethanol could be identified.
Formalin fixation does not always preclude the use
of PCR-based methods, but work is usually limited to
small fragments; 570 bp is considered large for success-
ful amplification (Shedlock et al., 1997). In the present
study, DNA quality was too low in the formalin-fixed is-
tiophorid larvae for PCR to amplify the 1.2-kb MN32-2.
Consequently, only ethanol-preserved larvae could be
used for key development and testing. Because of likely
differences in length shrinkage between larvae pre-
served only in ethanol and those fixed in formalin, it is
possible that the regressions presented in the present
study are not valid for the latter.
No longbill spearfish were among the molecularly iden-
tified larvae; thus this species could not be included in
the key. Very little is known about the longbill spearfish,
but it is reported that larvae are found offshore (Uey-
anagi et al., 1970), and that even adults are quite rare
in United States and Bahamian waters (Robins, 1975).
The longbill spearfish spawning season appears to range
from late November to early May and peaks in Febru-
ary (Robins, 1975; de Sylva and Breder, 1997). Although
there is some overlap in the spawning season of longbill
spearfish with the spawning seasons of other Atlantic
istiophorids, because of the rarity and predominantly
offshore occurrence of the longbill spearfish, its absence
from the key may not pose major problems for the iden-
tification of istiophorid larvae from our study area.
The larval istiophorids used to create and test the
identification key were all captured either in the Straits
of Florida or in Bahamian waters and were all smaller
than 22 mm SL. Caution must be used when apply-
ing the key to larvae from other parts of the world
or to larger sizes. Ueyanagi (1963) assumed that spe-
cies pairs from different oceans (white marlin and
striped marlin [Tetrapturus audax], longbill spearfish
and shortbill spearfish [Tetrapturus angustirostris],
Atlantic and Pacific blue marlin, Atlantic and Pacific
sailfish]) would be identifiable by the same characters.
Although these pairs exhibit the same RFLP patterns
at the MN32-2 locus (McDowell and Graves, 2002), we
have not tested the key with Pacific larvae and cannot
be certain that their measurements would fall within
the same regression limits or that they would have
the same lower jaw pigment patterns. Even within the
Atlantic Ocean, spawning seasons vary with location
(e.g., Bartlett and Haedrich [1968] collected larval blue
marlin off the coast of Brazil in February and March).
Month of capture was crucial in our analyses for dis-
criminating between small marlins when spawning
season overlap is minimal; therefore our key may need
adjustment to reflect local spawning seasons when ap-
plied to other locations.
As in Indo-Pacific istiophorid larvae (Ueyanagi, 1964,
1974b), snout length, eye orbit diameter, and lower jaw
pigmentation are important characters for identifying
larval istiophorids of the western Atlantic. However,
white marlin differ markedly from their Indo-Pacif-
ic counterpart, striped marlin. White marlin larvae,
long-held as members of the "long-snout group" of istio-
phorids, actually more closely resemble the short-snout-
ed blue marlin until 17 mm standard length (Fig. 6).
After they reach this size, snout length is intermediate
between that of blue marlin and sailfish. This result
cautions against the assumption that even large larvae
with short snouts are blue marlin. Snout length may be
useful as a character in phylogeny studies.
The identification methods presented in the present
study reduce subjectivity in the evaluation of charac-
ters. This study also brings to light the caveats of using
lower jaw pigment patterns as a means of identification
and limits which pigment patterns qualify as diagnos-
tic. Although there is a family of lower jaw pigment
patterns that appears to mark sailfish only, if this char-
acter were the only means of identifying sailfish, nearly
40% of our sailfish (as confirmed by RFLP analysis)
would have been misidentified or escaped classification.
Likewise, the preflexion blue marlin pigment pattern
will not lead to misidentifications, but too many preflex-
ion blue marlin lack the pattern to justify its use as a
stand-alone identification character. Lower jaw pigment
patterns have also been suggested as potentially useful
characters for separation of subspecific populations of
both sailfish (Ueyanagi, 1974a, 1974b) and striped mar-
lin in the Indo-Pacific (Nishikawa, 1991). The hypoth-
esis of pigment-delineated sailfish populations was not
borne out (Leis et al., 1987), and the high variability of
lower jaw pigments among larvae of each species from
our study area casts further doubt on the notion of us-
ing pigments alone to distinguish populations.
Our identification key does not enable separation of
species for certain classes of istiophorid larvae. For
example, larvae that are caught in June, are less than
10 mm SL, and possess none of the diagnostic lower
jaw pigment patterns are especially problematic. In
these "dead end" cases, discriminant analysis (CVA) is
useful. Although a few larvae were misidentified with
the CVA, these larvae were plotted near the interface
of two species groupings; this position alerts the user to
the fact that misidentification is a possibility. One dis-
advantage of using CVA (or any discriminant analysis)
for identification is that all of the variables must have
a value, meaning that a larva with broken preopercular
spines, for example, cannot be entered into the analysis.
When the species possibilities are narrowed down to
blue marlin and either sailfish or white marlin, it may
be feasible to identify larvae by vertebral formula. Rich-
ards (1974) suggests that this is difficult with larvae
less than 20 mm SL, but it is the method that Prince
et al. (1991) used to identify blue marlin that were 5-10
mm SL. Molecular identification is always an option for
resolving dead ends.
The identification of larval istiophorids has never
been an easy task. Molecular identification is reliable,
but can be relatively more labor intensive and expensive
598
Fishery Bulletin 103(4)
v.
Figure 6
Size series of genetically identified representatives of each species. Top row: sailfish. Middle
row: white marlin. Bottom row: blue marlin. Left column: ~5 mm SL. Middle column: -10 mm
SL. Right column: -15 mm SL.
Luthy et al : Identification of larval sailfish, white marlin, and blue marlin in the western North Atlantic Ocean
599
than traditional methods. The creation of a key based
on characters developed from molecularly identified At-
lantic larvae makes it possible to use more traditional
methods to make reliable identifications. Despite the
limitations of the key, it works well for larvae caught
in our area. We recommend further testing with istio-
phorid larvae from other waters, and the inclusion of
longbill spearfish larvae.
Acknowledgments
The authors appreciate financial support provided by
Network Miami and Anheuser Busch, the American
Institute of Marine Science, the Miami Billfish Tour-
nament's Captain H. Vernon Jr. Scholarship, the Inter-
national Light Tackle Tournament Association, and the
University of Miami's Center for Sustainable Fisheries.
We thank G. Diaz, K. Gracie, L. Leist, M. Williams, O.
Bowen, C. Schmitz, C. Faunce, D. Schuller, G. Meyers,
and M. Feeley for volunteering their time for specimen
collection and J. Post, T. Capo, J. Ault, S. Smith, and J.
Luo for early instruction. Laboratory advice and com-
miseration were provided by C. Campbell. P. Walsh, J.
van Wye, and all the members of the VIMS genetics
laboratory. We offer special thanks to J. Graves, in
whose laboratory the molecular work was carried out.
We are grateful to T Grothues for sharing his CVA
wisdom and to J. Llopiz, D. Richardson, and K. Denit for
testing our key. W. Richards, D. deSylva, and C. Paris
were instrumental in the interpretation of identification
characters. This work could not have been carried out
without the generosity and enthusiasm of D. Frazel and
his family in donating their time and the use of their
boat. Larvae were collected under NMFS permits HMS-
EFP-00 through 03, and under University of Miami
animal care protocols (02-063).
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Abstract — This study examined the
sexual differentiation and reproduc-
tive dynamics of striped mullet iMugil
cephalus L.) in the estuaries of South
Carolina. A total of 16,464 specimens
were captured during the study and his-
tological examination of sex and matu-
rity was performed on a subsample of
3670 fish. Striped mullet were sexually
undifferentiated for the first 12 months,
began differentiation at 13 months, and
were 90% fully differentiated by 15 to
19 months of age and 225 mm total
length (TL). The defining morphologi-
cal characteristics for differentiating
males was the elongation of the pro-
togonial germ tissue in a corradiating
pattern towards the center of the lobe.
the development of primary and sec-
ondary ducts, and the lack of any rec-
ognizable ovarian wall structure. The
defining female characteristics were the
formation of protogonial germ tissue
into spherical germ cell nests, separa-
tion of a tissue layer from the outer
epithelial layer of the lobe-forming ovar-
ian walls, a tissue bud growing from
the suspensory tissue that helped form
the ovary wall, and the proliferation of
oogonia and oocytes. Sexual maturation
in male striped mullet first occurred
at 1 year and 248 mm TL and 100%
maturity occurred at age 2 and 300
mm TL. Female striped mullet first
matured at 2 years and 291 mm total
length and 100% maturity occurred at
400 mm TL and age 4. Because of the
open ocean spawning behavior of striped
mullet, all stages of maturity were
observed in males and females except
for functionally mature females with
hydrated oocytes. The spawning season
for striped mullet recruiting to South
Carolina estuaries lasts from October
to April; the majority of spawning activ-
ity, however, occurs from November to
January. Ovarian atresia was observed
to have four distinct phases. This study
presents morphological analysis of
reproductive ontogeny in relation to
size and age in South Carolina striped
mullet. Because of the length of the
undifferentiated gonad stage in juve-
nile striped mullet, previous studies
have proposed the possibility of pro-
tandric hermaphrodism in this species.
The results of our study indicate that
striped mullet are gonochoristic but
capable of exhibiting nonfunctional
hermaphroditic characteristics in dif-
ferentiated mature gonads.
Manuscript submitted 11 March 2003
to the Scientific Editor's Office.
Manuscript approved for publication
31 May 2005 by the Scientific Editor.
Fish. Bull. 103:601-619 (2005).
Sexual differentiation and gonad development
in striped mullet iMugil cephalus L.)
from South Carolina estuaries*
Christopher J. McDonough
William A. Roumillat
Charles A. Wenner
Marine Resources Research Institute
South Carolina Department of Natural Resources
217 Fort Johnson Road
Charleston, South Carolina 29412
E-mail address (for C J Mcdonough) mcdonoughcsdnr.scgov
The striped mullet (Mugil cephalus L.)
is distributed circumglobally in tropi-
cal and semitropical waters between
latitudes 42°N and 42°S (Thomson,
1963; Rossi et al., 1998). Even though
considered a marine species, striped
mullet are euryhaline and can be
found year round throughout the full
range of estuarine salinities in the
southeastern United States (Jacot,
1920; Anderson, 1958). Striped mullet
are important throughout the world
for commercial fisheries and aqua-
culture. In the southeastern United
States there are large-scale commer-
cial fisheries for striped mullet in
North Carolina and Florida. South
Carolina and Georgia have much more
limited landings (NMFS1).
The commercial effort in the south-
eastern United States targets "roe"
fish (fish containing roe) during the
fall spawning migration. Throughout
the rest of the year mullet are fished
commercially for human consump-
tion (particularly the west coast of
Florida) and bait (Anderson, 1958).
Striped mullet have a significant eco-
nomic impact in the southeast where
they represented a landings value of
16.4 million dollars from 1994 to 2000
(NMFS1). Striped mullet landings in
the Gulf of Mexico were significantly
higher with a landings value of 86.2
million dollars for the same time
period. Striped mullet are also one
of the most important forage fishes
that occur in the estuaries of the
southeast and represent a significant
food source for upper level piscivores
(Wenner et al.2).
General information on the biol-
ogy of striped mullet has been well
documented (Jacot, 1920; Anderson.
1958; Thomson, 1963, 1966; Chubb
et al., 1981) but limited information
is available on the reproductive biol-
ogy of wild populations (Anderson,
1958; Stenger, 1959; Greeley et al.,
1987; Render et al., 1995). There is a
large body of work concerning striped
mullet reproduction in aquaculture
but many of these studies have con-
centrated on females by using arti-
ficial manipulation of the reproduc-
tive cycle. Although the maturation
process of oocytes may be the same
as that in wild striped mullet, the
environment and conditions under
which maturation occurred in these
studies was artificial (Shehadeh et
al., 1973; Kuo et al., 1974; Pien and
Liao, 1975, Kelly, 1990; Tamaru et
al., 1994; Kuo, 1995). This lack of in-
* Contribution 564 of the Marine Re-
sources Research Institute, South Caro-
lina Dept. of National Resources, Charles-
ton, SC 29412.
1 NMFS (National Marine Fisheries
Service). 2001. Unpubl. data. Sta-
tistics and Economic Division, 1315 East-
West Highway, Silver Spring, Md. 20910.
http://www.st.nmfs.gov/stl/index.html.
2 Wenner, C. A., W. A. Roumillat. J. E.
Moran, M. B. Maddox, L. B. Daniel, and
J. W. Smith. 1990. Investigations on
the life history and population dynamics
of marine recreational fishes in South
Carolina, part 1, p. 2-22. Completion
reports, Project F-37, Charleston, and
Project F-31, Brunswick. South Carolina
Marine Resources Research Institute,
P.O. Box 12559 Charleston, S.C. 29422.
602
Fishery Bulletin 103(4)
formation on reproductive biology is surprising given
the worldwide importance of mullet. In particular, there
have been very few studies where sexual differentiation
of immature striped mullet has been examined in con-
junction with histological confirmation of maturity stage
in reproductively capable adults. One notable exception
was the work of Stenger (1959), who although thorough
in histological confirmation of the male and female de-
velopmental stages in relation to length, did not take
age into consideration at differentiation or maturity.
More recent studies (Chang et al., 1995; Chang et al.,
1999) have examined gonad histology and plasma sex
steroids during sex differentiation in young-of-the-year
striped mullet up to 12 months old, but these studies
did not provide any detail on fish length during devel-
opment and differentiation. Other studies have exam-
ined oocyte development and relative fecundity for the
reproductive assessment of female striped mullet but
did not examine reproductive development in males or
take into consideration an independent confirmation of
fish age (Greeley et al., 1987; Render et al., 1995). Few
studies have described the process of spermatogenesis
in striped mullet because most efforts on the propaga-
tion and enhancement of striped mullet reproduction
have concentrated on female development because of
their commercial value. Grier (1981) used striped mul-
let in describing the cellular organization of testes and
spermatogenesis as a model for synchronously spawning
fishes but did not describe size and age in relation to
spermatogenesis.
Striped mullet are considered isochronal spawning
fishes (Greeley et al., 1987; Render et al, 1995). There
are only a few observations of offshore spawning activ-
ity (Arnold and Thompson, 1958), and eggs and larvae
have rarely been collected offshore (Anderson, 1958; Fi-
nucane et al., 1978; Collins and Stender, 1989). Collins
and Stender (1989) concluded that striped mullet spawn
in and around the edge of the continental shelf off the
coasts of North Carolina, South Carolina, Georgia, and
the east coast of Florida (an area often referred to as
the South Atlantic Bight), but may also spawn outside
the South Atlantic Bight (SAB). They also indicated a
protracted spawning season that extended from October
to April. This contrasts with the estimated spawning
season from previous studies (2-5 months from No-
vember through March) (Jacot, 1920; Broadhead, 1956;
Anderson, 1958; Arnold and Thompson, 1958; Stenger,
1959; Dindo and MacGregor, 1981; Greeley et al., 1987;
Render et al., 1995; Hettler et al., 1997). Female mul-
let were thought to mature at three years of age at a
size of 230 to 350 mm standard length (Thomson, 1951,
1963; Greeley et al., 1987).
This study had three purposes: 1) to determine at
what size and age striped mullet become fully sexually
differentiated and to describe the morphological char-
acteristics of sexual differentiation in both male and
female striped mullet; 2) to determine the size and age
at first maturity for each sex; and 3) to describe the
timing and process of gametogenesis in relation to size
and age in both males and females in order to provide a
histological baseline for the evaluation and reproductive
staging of striped mullet.
Materials and methods
Sampling and data collection
Collections of striped mullet were conducted from Octo-
ber 1997 through December 2000. Collections were based
on a protocol of monthly random stratified sampling
conducted in the Cape Romain, Charleston Harbor, and
the ACE Basin estuaries in South Carolina (Fig. 1). The
Charleston Harbor estuarine system is made up of three
river systems: the Ashley, Cooper, and Wando rivers. In
addition, Charleston Harbor proper was sampled as a
separate stratum. The ACE Basin estuary is formed by
the confluence of the Ashepoo, Combahee, and Edisto
rivers and was sampled as a single estuary. One of the
problems initially encountered with sampling was the
ability to sample striped mullet throughout their estua-
rine salinity range. The primary sampling gear used
was a 184-meter trammel net with 356-mm stretch mesh
outside panels and a 64-mm stretch mesh inner panel.
Because striped mullet use the full range of estuarine
habitats and freshwater, the use of alternate gear was
necessary to obtain a representative sample of the popu-
lation within all salinity regimes. Specimens collected
with additional gear types in low salinity and freshwater
habitats supplemented those specimens sampled with a
trammel net. The additional gear types were an electro-
shock boat, cast nets, and gill nets. The electroshock boat
samples were obtained from the South Carolina Depart-
ment of Health and Environmental Control from the
major coastal river basins in South Carolina, including
freshwater portions of the Waccamaw, Black, Pee Dee,
Sampit, Santee, Cooper, Edisto, Ashepoo, Combahee, and
Broad rivers (Fig. 1). Cast nets were used primarily in
different portions of the Charleston Harbor estuary in
tidal creeks and in areas where the trammel net could
not be used effectively . The cast nets were 1.84 meters
in diameter and had 10-mm mesh. The gill net was a
200-meter net with 64-mm stretch mesh that was used
to test the efficiency of the trammel net sets.
Standard morphological measurements were total
length (TL), fork length (FL), standard length (SL)
in mm, and body weight (BW) in grams (g). Any sub-
sequent mention of fish length in the remaining text
will be total length unless otherwise noted. Sagittal
otoliths were removed for estimating fish ages. A gross
examination of the gonads was used for initial sex and
maturity assessment. If the gonads were estimated to
weigh more than 1 g they were also weighed. A small
sample of gonad tissue was removed from the posterior
portion of the gonad where the lobes were joined and
was fixed in 10% neutral buffered formalin for histologi-
cal examination. The tissue samples used for histologi-
cal evaluation were taken from the posterior section of
the gonad because earlier developmental stages and
differentiation were more evident where the ductwork
McDonough et al.: Sexual differentiation and gonad development in Mugil cephalus
603
Aw
C^
4 (*- - ^rr"-^, S' Helena Sound
A' frills Bay Cape Remain
5^
^LM Charleston Harbor
SOUTH CAROLINA
Ji_
Figure 1
Map of coastal South Carolina with estuaries where trammel net collections were made: Cape Romain, Charleston
Harbor, and Ashepoo River, Combahee River, Edisto River (ACE) Basin, as well as the coastal rivers where elec-
troshock collections were made.
and gonad tissue joined in striped mullet (Chang et
al., 1995). Comparisons of oocyte density from different
sections of striped mullet ovary have also demonstrated
uniform distribution throughout the ovary (Shehedeh et
al., 1973; McDonough et al., 2003). A gonadosomatic in-
dex (GSI) was calculated for specimens according to the
method of Render et al. (1995) where GSI was expressed
as a percentage of gonad weight (GW) divided by body
weight (BW) minus gonad weight, such that
GSI = (GW/(BW-GW))x 100.
Histological processing
The tissue samples were processed by using standard
wax histology techniques (Humason, 1967). Tissues
were embedded in paraffin and cut on a rotary micro-
tome. The sections, which ranged from 5 to 7 ^m thick,
were then placed on microscope slides and stained with
standard haematoxylin and eosin-Y staining techniques
(Humason, 1967). After staining, tissue sections were
sealed under a cover slip and evaluated for sex and
maturity with a compound light microscope at lOOx
magnification. The sex of each specimen was determined
to be male, female, or undifferentiated. Maturity was
assessed according to a modified version of the sched-
ule used by Wenner et al. (1986) that was adapted by
the authors to work with isochronal spawning fish, as
well as assessed with previous models of reproductive
development (Stenger, 1959; Grier, 1981; Wallace and
Selman, 1981) (Table 1). Ovarian atresia was divided
into four distinct phases as described by Hunter and
Macewicz (1985). For the sake of consistency, the same
terminology was used to describe the four phases of
ovarian atresia in striped mullet in this study: alpha,
beta, gamma, and delta (see Table 2). These evaluation
methods were based on identification of morphological
characteristics evident in histological sections. Speci-
mens were evaluated by two readers to avoid bias. Any
discrepancies of maturity stage between readers were
either mutually resolved or the specimen was excluded
from further analysis.
604
Fishery Bulletin 103(4)
Table 1
Histological criteria used to determine reproductive stage in striped mullet (Mugil cephalus) once sexual differentiation has
occurred. Modified from Wenner et al. ( 1986).
Reproductive stage
Male
Female
1. Immature
Developing
3. Running, ripe
4. Atretic or spent
5. Inactive or resting
Inactive testes; small transverse sections
compared to those of resting male; sper-
matogonia and little or no spermatocyte
development.
Development of cysts containing primary
and secondary spermatocytes all the way
through accumulation of spermatozoa in
lobular lumina and ducts.
Predominance of spermatozoa in lobules
and ducts and little occurrence of sper-
matogenesis.
No spermatogenesis occurring but some
residual spermatozoa in shrunken lobules
and ducts.
Larger transverse sections compared to
those of immature males; little or no sper-
matocyte development; empty lobules with
well-developed secondary ductwork and
some residual spermatagonia.
Inactive ovary with previtellogenic oocytes and no
evidence of atresia. Oocytes are <80 (ira, lamellae lack
muscle, and connective tissue bundles are not as elongate
as those in mature ovaries, ovary wall is very thin.
Developing ovary have enlarged oocytes generally greater
than 120 um in size. Cortical alveoli become present and
actual vitellogenesis occurs after oocytes reach 180 .um
in size and continue to increase in size. Abundant yolk
globules with oocytes reach a size range of >600 um.
Completion of yolk coalescence and hydration in most
oocytes.
More than 30f? of developed oocytes undergoing the
atretic process. See Table 2 for detailed description of
the atretic process.
Previtellogenic oocytes with only traces of atresia. In
comparison to those of immature females, most oocytes
are >80 ,«m, lamellae have some muscle and connective
tissue bundles; lamellae are larger and more elongated
than those of immature females and the ovarian wall
is thicker.
Table 2
Histological criteria used to determine atretic stage in striped mullet Mugil cephalus). Criteria based on ovarian atretic process
described by Hunter and Macewicz (1985) and observational data of striped mullet ovaries from this study.
Atretic stage
Description
1. Alpha atresia a Vitellogenic oocytes are present with distinct yolk globules, which are beginning to break down. The
most developmentally advanced oocytes will undergo atresia first, followed by less developed oocytes.
The oocyte will break down from the interior outward; the vitelline membrane and follicle layers are
the last portion of the oocyte to decay. As the oocyte breaks down, a series of vacuoles of various sizes
will appear within the oocyte.
/! The oocytes continue to become reduced in size as they decay. The vacuoles that began to form during
the alpha stage are now coalescing together to form one large vacuole within the oocyte. This gives
the lamellae a distinct hollow matrix and just the outer layers of the oocyte and follicle are now left.
This appears to be the shortest atretic phase.
7 The oocytes that were left in the hollow matrix during the beta stage now begin to shrink in size and
the outer layers fold in on themselves as the oocyte collapses. The areas in and around the collapsed
oocytes and lamellae become highly vascularized during this stage in order to facilitate rapid
resorption of decaying cellular material. There will still be some vacuoles present within the collapsed
oocytes but they have become much smaller and there are far fewer of them. This stage continues
until most of the remaining oocytes that developed for spawning are no longer recognizable as oocytes.
4. Delta atresia A The remnants of old oocytes at this stage are identifiable only as decaying cellular material and
will stain a distinct yellow-brown color and are still present in (approximately) 30% or more of the
material within the ovary. Undeveloped oocytes have a much more distinct and numerous presence
within individual lamellae. The amount of vascularization seen in the gamma stage is reduced
because most of the old material has been reabsorbed.
Beta atresia
3. Gamma atresia
McDonough et al.: Sexual differentiation and gonad development in Mugil cephalus
605
Aging techniques
Age was determined by using the left
sagittal otolith, which was embedded in
epoxy resin. A 0.5-mm transverse section
encompassing the otolith core was cut with
an Isomet low speed saw with diamond
wafering blades. The thin section of otolith
embedded in the epoxy was observed with
a dissection microscope at 20x magnifica-
tion, and age was recorded as the number
of annular rings present. The otoliths were
initially aged by one reader. A second reader
then evaluated a subsample of specimens
from 1998 and 2000 and all the otoliths
from 1999. The two groups of ages were
compared by the percentage of agreement
between the different age determinations
and by a paired Mest that allowed a com-
parison of the means and variances of the
two groups iCampana et al., 1995). Ages
were then validated by marginal increment
analysis in order to establish the timing
and periodicity of increment deposition
(Campana. 2001). In addition, the precision
of the ages was compared by using average
percent error (APE) between the two sets of
ages. "Precision" was defined as the repro-
ducibility of age determinations (Beamish
and Fournier, 1981; Chang, 1982). Using
the Levenburg-Marquardt procedure (Zar,
1984). we determined the growth curve
with a nonlinear least squares regression
of total length on age.
Results
Age structure
CL 20
0123456789 10
Age
Figure 2
Age-frequency distribution (expressed as a percentage) for striped
mullet 'Mugil cephalus L. i from South Carolina estuaries October
1997 to December 2000. n = 3760.
We recorded the age of 3760 specimens
and examined these specimens histologi-
cally to determine sex and maturity stage.
An additional 2524 young-of-the-year (age
0) specimens were used for the nonlinear
regression of total length on age. as well
as the sex ratios by both size and age. The
age range for striped mullet in this study
was 0 to 10 years, and 1- and 2-year-olds
dominated the age distribution (Fig. 2).
There was 81.7% agreement for age data
between the two readers, and 99.5% agree-
ment within one year for both readers. A
Mest indicated no significant difference
between the two sets of age estimations
(r=2.898. df=1.233. P<0.05). The average
percent error (APE) (Beamish and Fournier, 1981)
between the two sets of age estimations was 0.41%.
Marginal increment analysis indicated that growth
increments were deposited during July 'Fig. 3). The
0.35
0.30-
E 0.25
E
| 0.20
i 0.15
0.10
0.05-
0.00
— i — i — i — n— i—
1998
1999
2000
Figure 3
Mean marginal increment distance by month for striped mullet i Mugil
cephalus L. I from South Carolina estuaries, October 1997 to December
2000. n = 3760. Marginal increment equals the otolith section radius
minus the distance from the core to the last annular increment.
total length at age regression demonstrated a strong
relationship <r2 = 0.864, df=3759, Fstat=21,742, P<0.05).
Despite this strong relationship, there was a wide
range of sizes among the 1-, 2-. and 3-year-olds (Fig. 4).
606
Fishery Bulletin 103(4)
There was a lag period between the time of formation
of the first annual growth mark and the actual one-
year birthdate. The first annular mark was deposited
between 15 and 19 months of age or at 1.25 to 1.6
years of age (Wenner and McDonough3).
700
600
.
B 500
E
' 400
— — t"""*"T i • i
en
x 300
-
| 200
/
100
TL = 103.7+ 166.4 I^G£)"'4
0
,-;= 0.847 P = 0.000
i i i i i i i i i i
(
)
2 3 4 ? 6 7 8 9 10 11
Age
Figure 4
Nonlinear re£
'ression of total length on age for striped mullet (Mugil
cephalus L. ) from South Carolina estuaries, October 1997 to Decem-
ber 2000. ;; =
3284.
Sexual differentiation
The smallest sexually differentiated male was 137 mm
(Fig. 5). Male striped mullet 126 to 150 mm TL were
eight to twelve months old (McDonough and Wenner,
2003). The first sexually differentiated
female was 164 mm TL. Females 151 to
175 mm would have been approximately one
year old (McDonough and Wenner, 2003).
Specimens greater than 200 mm were at
least 50% sexually differentiated. Only
1.5% of specimens over 300 mm remained
undifferentiated. The largest sexually
undifferentiated specimen was 325 mm.
All fish >325 mm, although still possibly
sexually immature, were fully sexually dif-
ferentiated. The ratio of males to females
was 2:1 until the fish were larger than 325
mm <x2n=0 05=2543.9, df=2). The ratio of
males to females was 1:3.8 for fish >325
mm(/2„=005=352.8, df=l).
The sex ratio by age class showed 98.9%
of the age-0 specimens were sexually undif-
ferentiated (Fig. 6). The few age-0 fish that
were differentiated were all males. At first
annulus deposition, 91.9% of the specimens
had differentiated. There were a few speci-
mens (0.8% I that remained undifferenti-
ated to 3 years old, but all striped mullet
age 4 or older were completely differen-
tiated. The sex ratio of males to females
in the one-year-old age class was 1.0:0.25
80
70
<d 60
0= 50
10
I
I
tototoOtoOtoOtoto.toOtoO.to
<V to *. O IV v v <y <V „to A 4? <J/ <p A ,
toOtoOtoO.toO
<V to \ ,o ,<v ,to A ,o
V V > to to to to <0
ri7toto*^fo'^to'-.to'^toK~to*^.to^to''--.<£
^ ^.V^J^ fv fv (V <V ^ <0 <0 °D > > > >
- to -- .to
o 0/ to 'v
to to to to
Undifferentiated
Male
Female
Size class (mm)
Figure 5
Sex by size class (25-mm size classes) for striped mullet iMugil cepha-
lus L.) from South Carolina estuaries, October 1997 to December
2000. n = 6284.
<r„=
- = 1065.4, df=2). At age 2 the ratio
was 1.0:0.68 (x2a=oos =502.6, df=2) and at
age 3 the ratio had reversed to 0.32:1.0
(^(,05=312.5, df=2).
Size and age at maturity
The onset of spermatogenesis in males was
first observed at 248 mm (Fig. 7A). The first
running, ripe males occurred at 291 mm
and this developmental stage was found in
all larger sizes. Postspawning males were
found only between November and March
in mullets larger than 325 mm. Resting
mature males were found in every month
and occurred in most size classes greater
than 251 mm. These resting males made
up fewer than 50% of the specimens from
any particular size class. A small percent-
tenner, C. A., and C.J. McDonough. 2001. Co-
operative research on the biology and assess-
ment of nearshore and estuarine fishes along
the southeast coast of the U.S.: Part IV: Striped
mullet, Mugil cephalus, p. 17-23. Final Report,
Grant no. NA77FF0550. Marine Resources
Research Institute, South Carolina Dep. Natu-
ral Resources, P.O. Box 12559 Charleston, SC
29422-2559.
McDonough et al.: Sexual differentiation and gonad development in Mugil cephalus
607
age (2.5% ) of immature males were found in size classes
greater than 325 mm. Male striped mullet showed 50%
maturity at 275 mm, and 100% maturity by 350 mm.
Oogenesis began in specimens as small as 291 mm
(Fig. 7B) and there were 15 females below 325 mm
undergoing oogenesis (4.5% of all developing females!.
Ovaries were found in three small females (<300 mm).
Immature females were not found larger than 400 mm
or older than 3 years. All females greater than 400
mm were mature, regardless of their age. The majority
of females over 425 mm (88.3%) were developing and
found only in the fall. No ripe female striped mullet
were found. Ovarian atresia was found from December
through May. Female striped mullet showed that 50%
maturity was reached at 325 mm, and 100% maturity
occurred in specimens 400 mm.
Gametogenesis occurred in each sex between the first
and second year (Fig. 8). However, the majority of speci-
mens at age 1 (65%) were immature. Males and females
showed 50% maturity at 2 years. Males showed 100%
maturity at age 4 and females at age 5. Running, ripe
males were first observed at age 1 but were found in
much greater numbers at ages 4-6. Resting males oc-
curred in every age class except age 6 (Fig. 8A). The
abundance of males aged 3 and older was far lower
(by at least an order of magnitude) than that of 1- and
2-year-olds (Fig. 8A). Atretic ovaries were found in all
age classes, and resting females were found in every
age class except age 0 (Fig. 8B).
Maturity stages by month showed immature and rest-
ing (but sexually mature) male and female striped mul-
let occurred in every month (Fig. 9). Developing males
were found from August through February, and run-
ning, ripe males from October through February. Males
(atretic) were found from November through March. De-
veloping females occurred from August through April.
Mean monthly GSI for males and females showed notice-
ably increased gonad size in November and December,
and obviously enlarged gonads occurred from October
through March (Fig. 10).
Histological descriptions: undifferentiated juveniles
The primordial gonad lobes were suspended by mes-
entery connected dorsally to the peritoneum and were
attached ventrally to the intestines (Fig. 11A). Gonads
from specimens <100 mm were identifiable only through
histological examination of whole-body cross sections.
The gonads in specimens less than 50 mm had lobes
ranging from 70 to 100 ,um in length (Fig. 11B). Lobes
were made up of somatic cells and a peripheral germi-
nal epithelium. The lobes were attached along their
dorsomedial surface by loose fibrous connective tissue,
known as stromal tissue. No defining male or female
characteristics were present at this fish length.
In specimens ranging from 50 to 100 ,i<m gonad lobes
had increased to 150 um and appeared more vascular-
ized (Fig. 11C). The lobes were attached to the suspen-
sory mesentery, which was attached to the peritoneum.
A few deuterogonia were visible along the lateral pe-
S 40
^m Undifferentiated
i i Male
■n Female
Figure 6
Sex by age class in years. Age is the number of annuli
present on the sagittal otoliths. rc = 6284.
riphery of each lobe. The remainder of the lobes con-
tained somatic tissue. The individual germ cells were
approximately 5 ;im in size. In some specimens, somatic
tissue was beginning to form bands that would later
develop into ductwork.
In specimens ranging from 100 to 150 mm, the gonad
lobes were obviously vascularized and had attained a
size of 200 to 300 um (Fig. 11D). Early ductwork was
beginning to become evident. Deuterogonia were en-
larging and forming nests along the lateral and distal
portions of the lobes. Somatic cells made up a large por-
tion of each lobe and the stromal tissue was now more
stalklike, attaching each lobe to the suspensory tissue.
There were only four specimens in this size range that
had started to differentiate as males. Gonads destined
to be males were identified by duct structures within
the gonad lobe as well as by more elongated germ cell
nests. These morphologically distinct features resulted
in an early demonstration of the corradiating pattern of
ducts and lobules seen in more advanced testes.
The 150 to 200 mm size class showed that 0.2%
of females and 37.3% of males began initial differ-
entiation, but the majority of all specimens (62.5%)
remained undifferentiated. The undifferentiated go-
nads had become larger, and lobe size was 600 to 800
um (Fig. HE). There was increased vascularization,
particularly along the medial portion of the stroma.
Germ-cell nests were now more organized, with 4 to 8
cells visible in each.
More than 83% of specimens >200 mm had become
sexually differentiated. The undifferentiated gonads
in specimens >200 mm were highly vascularized and
had both the presence of ductwork, rounded germ cell
nests, and lobule-like structures. In some cases, germ
cell nests that were characteristic of female precursors
608
Fishery Bulletin 103(4)
could also be found in the center portions of lobes adja-
cent to the characteristic male precursor lobule struc-
tures. The primary duct was now well formed; however
there were still no definitive morphological characterstic
that would enable sex determination.
Male differentiation
The initial differentiation of males was evident in the
morphological features of the germ-cell tissue located
along the peripheral portions of each lobe. The germ
tissue began to form elongated bands perpendicular to
the edge of the lobe, whereas the somatic tissue began
to form fibrous bands originating along the edges of the
600
500 -
400
300
200
100
Males
n_
,
j\\N Immature
H"'"""1 Developing
■■ Atretic
i i Resting
H
Pfl^T-r ,
W In N Q
"V 'V "> T> '
<o N1 <y rQ v? IV <S" ,«V ^
iv,' ~ ^ V V v *> ' *>
<*~. IS Qn <%
I55 I '
250
it 200 -
150
100
50
B
Females
r$ 171
l\\\l Fern 1mm
Mi^l Fern Dev
^H Male Atr
Fern Resl
i £5 v- C *~.
1 (3s rj Of <V
iSJ- r\/ o,' i\y
/ lv,l ■
V ^ ft/ ^ V O IV H
Size class (mm)
Figure 7
Maturity stage by size class for male and female striped mullet
{Mugil cephalus L. ) from South Carolina estuaries, October 1997
to December 2000. Males, n=1850; females, n=1250.
primary duct (Fig. 12A). The primary duct was defined
structurally at this point. With continued increase in
fish length, lobes increased in size and vasculariza-
tion. The germ tissue continued to elongate medially
within the lobe in a corradiating pattern (Fig. 12B).
Somatic tissue continued to form bandlike structures
that would eventually become secondary ductwork, and
the germ-cell expanded to form lobules (Fig. 12C). As the
lobules became more developed, spermatogonia began
to line the lobules as part of the germinal epithelium
(Fig. 12D). Sertoli cells were not visible because of the
lack of resolution at this magnification (400x) level.
Mitotic proliferation of spermatogonia caused lobular
enlargement, a;though spermatogonia were very small at
this stage (2-3 f*m). The overall male aspects of
the physical structure of the lobes was clear at
this point (Fig. 12E). Melanomacrophages were
found in the lobes of some specimens (Fig. 12F).
The melanomacrophages were found only in
immature and differentiating males.
Female differentiation
The first sign of female sexual differentiation
was the organization of germ-cell tissue into
round nests of 8-10 cells each (Fig. 13A). The
germ-cell nests, which eventually gave rise to
oogonial nests, were first found along the lat-
eral periphery of the lobe and were infrequently
scattered within the gonad lobe. There was
evidence of early ovarian wall development,
which consisted of a single layer of cells form-
ing the outer layer of the lobe, separate from
the oogonial nests (Fig. 13B). Although some
ductwork was present, there was no evidence of
the formation of lamellae. Ductwork tended to
become reduced as the germ-cell nests became
more numerous. With continued development,
individual cells within the nests became more
visible and the ovary wall became more evi-
dent (Fig. 13B). Stalks or buds of tissue were
observed growing out of the base of the stroma
on the dorsolateral surface (Fig. 13C). As devel-
opment progressed, the ovarian wall attached
to these stalks or tissue buds appeared to grow
over the dorsal surface of each ovarian lobe.
This ovary-wall stalk bud was not necessarily
an indicator of female differentiation because
a small number of samples (0.6%) with definite
male structure also had indications of these
stalk buds. However, these tissue stalks were
present in 68% of the differentiating females.
The presence of both the ovary wall stalk
buds and the rounded germ-cell nests located
throughout the gonad lobe were diagnostic of
female differentiation.
Primary growth oocytes increased in num-
ber and began to aggregate, forming distinct
lamellae (Fig. 13D). The ovary wall continued
to differentiate at this point but was only a few
McDonough et al. Sexual differentiation and gonad development in Mugil cephalus
609
cell layers thick. There was still a great deal of
stroma and somatic tissue left in the ovary, but
it began to form bands of fibrous tissue, result-
ing from the regression of stroma and somatic
tissue (where present) as the lamellae contin-
ued to develop. The primary duct was greatly
reduced. Oogonia began proliferating and dif-
ferentiating into primary growth oocytes as fol-
liculogenesis commenced. The ovary wall, now
becoming vascularized, began to separate from
the lamellae, opening a space that would become
the ovarian lumen (Fig. 13, D-F). The ovary
wall was made up of squamous cells on the in-
side layers and collagen and elastic tissue on
the outer layers. The stroma and somatic cells
continued to be reduced until they were primar-
ily fibrous tissue from which the lamellae were
suspended. Histological ovarian cross-sections
changed from the leaf or spade shape of the
undifferentiated gonad to a more rounded one.
Once ovarian differentiation was completed, the
individual lamellae were seen to have oocytes
within each and the stroma was reduced to sus-
pensory tissue for the lamellae (Fig. 13F). The
primary growth oocytes present in the lamellae
remained small (80 to 100 pm) and relatively
uniform in size. At the initiation of reproductive
development, the oocytes started to grow from
the arrested prophase of the first meiotic divi-
sion (Stenger, 1959; Kuo et al., 1974).
Morphological features of atretic females
Females undergoing atresia were captured in all
months except August-October, and 78% were
seen January-March of each year. The first sign
of alpha atresia was the breakdown of the most
advanced residual oocytes. Vacuoles (of various
sizes) began to appear (Fig. 14A), merging to
form large spaces within the decaying oocyte.
The overall diameter of oocytes decreased from
600 to 300-400 Jim; however oocytes retained
their overall shape during alpha atresia and
showed no signs of collapse (Fig. 14B). Beta
atresia was the shortest phase. The oocytes had shrunk
in size (<300 |um) but retained their previous overall
structure and shape. A distinct hollow matrix retaining
only the outer layers of the oocyte (follicle layers and the
vitelline membrane) was the defining characteristic for
beta atresia (Fig. 14C). The tissue retained this structure
while the oocyte continued to decrease (150-180 t/m).
During gamma atresia the oocytes collapsed (Fig. 14D)
or shrank. Some vacuoles remained in partially collapsed
oocytes, but they were fewer in number and smaller in
size (<150 f/m) (Fig. 14E). The areas in and around the
collapsed oocytes and ovarian lumen became more vas-
cularized during this stage, and this helped facilitate
rapid resorption of decaying cellular material (Fig. 14F).
Undeveloped oocytes became more visible and numerous.
Gamma atresia ended when only masses of broken-down
i:o(i
iiiiiii
roo -
(.00
40(1
Males
r^i
K\M Immature
I I Developing
^^B Alretie
Resting
1
1
0 1 2
i I 1 i r 1 1 —
4 5 6 7 8 9 10
500
300
200
100
B
Females
-T
iwm Immature
i- ■ ■ i Developing
■■ Atretic
I 1 Resting
-,.
I
G
H W M = _
4 5 6 7
Age
10
Figure 8
Maturity stage, by age class, for male and female striped mullet
{Mugil cephalus Ljfrom South Carolina estuaries, October 1997
to December 2000. Males, n = 1850; females, rc = 1250.
cellular material remained. Delta atresia was character-
ized by the presence and decay of nondescript cellular
material from the previous spawning (Fig. 14G). Delta
atresia was present in approximately 30% or more of
the ovary. There was also a decrease in the amount
of vascularization within the ovarian lamellae during
this stage because most of the old oocyte material had
been resorbed. The lamellae contained only undeveloped
oocytes and all the remaining material from the previous
spawn was concentrated medially in the lamellae.
In the resting stage, no reproductive activity occurred
in the ovaries. Infrequently, resting ovaries showed
some minor evidence of the previous spawning. The
remaining undeveloped oocytes were previtellogenic
and varied widely in size (80-120 um). The ovary wall
was relatively thick, particularly in comparison to the
610
Fishery Bulletin 103(4)
Immature males
ii = 1190
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Developing males
n = 339
r~i
XI
a
E
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Atretic males
n = 10
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Inactive males
n = 293
nfl
Immature females
n =415
n
n
n
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Developing females
n = 276
n
n
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Atretic females
r
ii =62
1 > — i 1 inn
nn
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
ajo-
Inactive females
150-
n = 539
■■ -
50-
~~ 1 :
1 n r nn
—
,-nn
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Month
Figure 9
Frequency of occurrence of each maturity stage by month for male and female striped mullet (Mugil cephalus
L.) from South Carolina estuaries, October 1997 to December 2000.
McDonough et al. Sexual differentiation and gonad development in Mugil cephalus
611
immature ovaries, and had distinct smooth
muscle layers (Fig. 14H). Any stromal tissue
left in the ovary at this point was also greatly
reduced and was essentially the mesentary
from which the lamellae were suspended.
Discussion
Age structure
o
The abundance of 1- and 2-year-old striped
mullet in South Carolina indicated that imma-
ture fish dominate the estuarine population.
The importance of proper age validation in
order to make comparisons of age and sexual
maturity cannot be understated. The most
important aspect of age validation is to obtain
a degree of precision that allows repeatability
in age determinations (Campana, 2001). The
periodicity of growth increment formation was
validated by marginal increment analysis, and
the precision of these age estimates was then
tested by comparing age counts of two inde-
pendent readers.
Marginal increment analysis showed that
annual growth increments were deposited in striped
mullet in July in the entire data set, as well as sepa-
rately for ages 1-5. By validating increment periodicity
separately for different age groups, a consistent pat-
tern for the species can be determined (Campana et
al., 1995; Campana, 2001). The percent agreement be-
tween the two readers and a r-test for independent age
determinations allowed direct comparisons of the two
groups of ages for consistency (Campana et al. 1995).
However, these two methods were both independent of
the age of the species. Therefore, average percent error
(APE) was used to compare the different sets of ages
because it is not independent of the age of a species
(Beamish and Fournier, 1981). The low APE (0.41%)
found between the two different age estimates indicated
a high degree of precision, which allowed acceptance of
these age determinations.
Sexual differentiation
Striped mullet are gonochoristic and sex is genetically
determined. In contrast to mammals, gender of the
mature germ cells of teleosts present in the gonad rather
than the gender of the duct system forms the basis for
classifying an individual as male or female (Shapiro,
1992). Early duct structures of the undifferentiated gonad
characteristic of male development regress on female
development. Initial duct development, along with germ
tissue placement, takes on characteristics of the eventual
sex once the process of differentiation begins (Asoh and
Shapiro, 1997). Because of the plasticity of their gonad
development, striped mullet retain some characteristics
of the opposite sex (such as singular oogonia in males or
Males
Female
MAY JUN JUL AUG SEP
OCT NOV DEC
Month
I \\ 111; \l \K M'K
Figure 10
Mean gonosomatic index value by month for male and female
striped mullet (Mugil cephalus L.) from South Carolina estuaries
from 1998 to 2000. n = 455.
duct-work in females) during the initial stages of differen-
tiation. The term that has been used to describe this phe-
nomenon is "intersex" (Yamamoto, 1969) but this state
could more accurately be defined as the hermaphroditic
stage of some gonochoristic species. Numerous descrip-
tions of intersex exist for teleosts (Atz,1964). Previous
studies have brought up the possibility of hermaphrodism
in striped mullet (Stenger. 1959; Atz, 1964; Moe, 1966);
however, there is only one example of a simultaneous her-
maphroditic striped mullet in the literature (Franks et
al., 1998). Once differentiation advances, these secondary
characteristics atrophy, and the gonad develops toward
the genetically determined sex.
We found that at first annular increment deposition
(15-19 months), most (95%) immature striped mullet
were sexually differentiated. Chang et al. (1995), us-
ing cultured striped mullet, found that differentiation
began only after 12 months of age, and 70% to 90% of
immature fish at 15 to 17 months had differentiated
sexually. We found only a small percentage (1.2%) of
differentiated specimens at 12 months of age. Chang et
al.(1995) did not report fish sizes, and Stenger (1959)
studied sizes at sexual differentiation without reporting
age. Stenger (1959) concluded that striped mullet up
to 150 mm generally were not differentiated sexually.
We found four specimens in which differentiation had
occurred in the 126-150 mm size range, which repre-
sented specimens 12 months or less in age. Once our
specimens reached the 176-200 mm size range, just
over 60% had sexually differentiated, which was also
approximately the size range at which the first annulus
appeared (Wenner and McDonough3).
Chang et al. (1995) found that females differentiated
earlier than males; we, on the other hand, showed sex
612
Fishery Bulletin 103(4)
C 'T*\Sft5
DW
V
»££
'tftJ
rv ■ Jr
-''.'* " <S#.
- - #r * » -'
•• >
_I)NV
.*£*.
'>? &f?A ,J fj
/
n n
^ '-.•„
v>q 7
BV
I)
iilMPs31i
Figure 11
Photomicrographs of histological sections of undifferentiated juvenile striped mullet (Mugil cephalus L.) (A) 35-mm
specimen at lOOx (scale bar=50 um) and (B) 600x (scale bar=10 ,«m) respectively; (C) 55-mm specimen at 400x, scale
bar=20 jim; (D) 135-mm specimen at 400x, scale bar=20 ,um; (E) 184-mm specimen at 400x, scale bar=20 f<m (see text
for detailed descriptions of each). Labels: G = primordial gonad; GE = germinal epithelium; SC = somatic cells; D = deu-
terogonia, DW = duct work; BV = blood vessel; ST = suspensory tissue; LV = liver; IN = intestine.
McDonough et al.: Sexual differentiation and gonad development in Mugil cephalus
613
*
RfJt
,GT
B
&
c W£-:-ia*g
■■• ' '
pi)
^,. ^
L,GT
V.-*
Figure 12
Photomicrographs of histological sections of sexually differentiating male striped mulletlMug// cephalus L.) . (A) Early
differentiation of a 164-mm specimen at 400x, scale bar=20 fim; (B) early differentiation of a 204-mm specimen at 400x,
scale bar=20 j<m; (C) advanced sexual differentiation of a 247-mm specimen at lOOx, scale bar=100 jim; (Dl advance
sexual differentiation of a 258-mm specimen at 400x, scale bar=20 j<m; (E) same specimen as previous photo at lOOx
showing full differentiation, scale bar=250 iim; iF) differentiated testes with melanomacrophages centers present in a
261-mm specimen, scale bar=250 i<m (see text for detailed descriptions). Labels: ST = somatic tissue; GT = germ tissue;
PD = primary duct; SD = secondary ductwork; BV = red blood vessels; GE = germinal epithelium; SPG = spermatogonia:
MMP = melanomacrophages: L = lobule.
614
Fishery Bulletin 103(4)
)W ! ^>*Jt$'t \
\ Mm*
D
*ST
LA
I
ow
OL
Figure 13
Photomicrographs of histological sections of sexually differentiating female striped mullet iMugil cephalus L.). (A) Early
differentiation of germ cell nests in a 239-mm specimen at lOOx, scale bar=100 um: (Bl early differentiation of germ
cell nests in a 205-mm female at 400x, scale bar=20 ,«m; (C) mid-differentiation in a 225-mm female at lOOx, scale
bar=100 jim; (D) advanced sexual differentiation with developing lamellae and ovarian wall in a 279-mm female at lOOx,
scale bars = 100 f<m; (E) advanced sexual differentiation in a 267-mm female at lOOx, scale bar=100 j<m; <F) full differ-
entiation of a 284-mm female, scale bar = 100 ,«m. Labels: GCN = germ cell nests; OW = ovary wall; ST = suspensory
tissue; OWS = ovary wall stalks; S = stroma; OG = oogonia; LA = lamellae; DW = ducts: OL = ovarian lumen.
McDonough et al.: Sexual differentiation and gonad development in Mugil cephalus
615
E
' D
B
* F
Figure 14
Photomicrographs of histological sections of ovarian atresia and the inactive reproductive stage in mature
female striped mullet (Mugil cephalus L.). I A) Alpha-stage oocyte atresia, scale bar=100 um; (B) Late
alpha-stage oocyte atresia, scale bar=100 ,um; (C) Beta-stage oocyte atresia, scale bar=100 um; ID) Early
gamma-stage oocyte atresia, scale bar=100 ,um; (El Gamma-stage oocyte atresia, scale bar=100 um; iFl Late
gamma-stage and early delta-stage oocyte atresia, scale bar=100 um; iGi Delta-stage oocyte atresia, scale
bar=100 um; (H) Reproductively inactive striped mullet ovary with degraded cellular material from previ-
ous spawning, scale bar=100 um. Labels: YG = yolk globules; VAC = vacuoles; AO = atretic oocytes; COL =
collapsed outer cell layers; UO = undeveloped oocytes; BV = blood vessels; OSM = old spawn material;
OW = ovary wall; OL =ovarian lumen; LA = lamellae.
616
Fishery Bulletin 103(4)
ratios at size indicating that males differentiated first.
This difference may be explained by the experimental
methods because the differentiation process was likely
similar between the cultured and wild fish. Chang et
al. 11995) showed that female development occurred
before male development based on levels of plasma sex
steroids. However, this finding was later corrected to
show that plasma sex steroid levels were the same for
males and females throughout sexual differentiation
(Chang et al., 1999).
The formation of lobules with the proliferation of
germ tissue has been previously described as a male
developmental pattern (Stenger, 1959; Grier, 1981;
Grier and Taylor, 1998; Grier, 2000). The morphologi-
cal progression seen in the present study was similar
to that previously described in histological examina-
tions of differentiation in striped mullet in conjunction
with size (Stenger, 1959) and age (Chang et al., 1995).
However, ours is the first study to examine sexual dif-
ferentiation of both male and female striped mullet with
changes in size and age and to describe these changes
histologically.
The undifferentiated gonad appeared to have male
morphological characteristics. The first morphological
signs of female differentiation were the movement of
deuterogonial germ-cell nests from the periphery of
the gonad. This pattern of development was similar to
the ontogeny of differentiation described previously for
striped mullet (Stenger, 1959). However, the presence
of the tissue stalk at the base of the suspensory tissue,
to which the ovary wall was attached, has not previ-
ously been described. The tissue stalk was present on
the majority (68%) of differentiating ovaries and only
a few (0.25%) of the differentiating testes. The pres-
ence of this stalk in differentiating testes indicated
that this characteristic alone should not be used to
determine genetic sex. However, the presence of the
tissue stalk, in addition to the rounded oogonial nests
throughout the gonad, strongly indicated that the speci-
men was female. There were no specimens observed to
be developing an ovary wall that also had developing
lobules or duct-work (male characters). Therefore, from
a morphological standpoint, the initial definitive identi-
fication of the differentiating ovary was the formation
of the ovary wall along with rounded germ cell nests
throughout the lobe. A primary duct at the center of
the developing ovary was present at this stage but any
secondary duct-work had begun to atrophy. It was also
observed that oogonial and oocyte proliferation could
occur throughout the lobe without a definitive ovary
wall, which would also be a strong indicator of the
female sex.
Size and age at maturity
Once sexual differentiation had occurred, the earliest
indication of spermatogenesis occurred at just under
250 mm (two specimens) and one year of age. However,
the majority of the developing specimens (89.9%) did
not show signs of spermatogenesis until they reached
300 mm and age 2. The greater abundance of immature
males under 300 mm would also indicate that full matu-
rity was reached by this length. Almost all the males
over 325 mm were in some state of reproductive activity,
either developing or running, ripe, because most of these
larger males were captured only during the spawning
season. October, November, and December were the only
months when we saw these larger fish, except for some
atretic-stage specimens taken from freshwater during
the spring. The first signs of spermatogenesis for striped
mullet, both from eastern Florida (Stenger, 1959) and
South Carolina, were found in August.
Greeley et al. (1987) did not age female striped mul-
let but used the growth schedule of Thomson (1966) to
conclude that striped mullet in eastern Florida reach
sexual maturity at 2.25 to 2.5 years, which is 1 to 2
years earlier than that previously reported (Jacot, 1920;
Broadhead, 1956; Anderson, 1958; Thomson, 1966). One
problem in earlier studies was the use of scale-based
age estimates (Jacot, 1920; Thomson, 1951, 1966; Ti-
moshek, 1973). The otoliths used in our study showed
more repeatability than would scales. Age schedules
based on scales were likely to contain problems with
the error terms and overestimation. Another factor may
have been the lack of a proper age-validaton protocol.
The lag in time between the actual birthdate and the
first increment formation was not incorporated into
the age model. A fish with a single annular ring that
appeared to be mature could actually have been up to
30 months old. Male striped mullet did not begin to
mature until they were one year old, and almost 100^
had reached sexual maturity by age 3. Ripe and atretic
males were also found at age 1.
Size at maturity for female striped mullet was re-
ported to be from 290 to 430 mm (Thomson, 1951, 1966;
Broadhead, 1956; Chubb et al., 1981). This wide range
in size at maturity depended on whether gonads were ex-
amined by gross morphological examination (Thomson,
1951, 1966; Broadhead, 1956) or histologically (Stenger,
1959; Chubb et al., 1981). Stenger (1959) found that oo-
cyte development occurred in specimens as small as 270
mm fork length (300 mm TL). Greeley et al. (1987) re-
ported the minimum size at maturity for female striped
mullet in eastern Florida was 230 mm SL (290 mm TL).
The minimum size at which a female was found to be
undergoing active vitellogenesis in the present study
was 291 mm. The first signs of female maturity were
evident in small numbers (15) in the 2-year-olds. The
first atretic females were also found at age 2. The age
at maturity for female striped mullet in our study was
similar to that found by Greeley et al. (1987) who used
length-based predicted ages. Therefore, it appears that
striped mullet in South Carolina have a similar matu-
rity schedule to those found in eastern Florida.
Immature and inactive males and females were found
every month of the year. The presence of ripe males
from October through February and the presence of
developing females from August through March support
the idea of an extended spawning season from October
through April.
McDonough et al.: Sexual differentiation and gonad development in Mugil cephalus
617
The presence of developing females indicated repro-
ductive activity through April: however numbers were
small (McDonough et al., 2003). Most of the specimens
collected in March and April were either immature or
inactive. It has also been demonstrated that striped
mullet in closed freshwater systems, such as impound-
ments, can begin reproductive development. However,
unless artificially manipulated, spawning did not oc-
cur in freshwater and the fish resorbed the developed
gametes (Shireman, 1975; Tamaru et al., 1994). The
re-absorption of gametes would undoubtedly have a
positive effect on growth rates and may contribute to
some of the variation in size at age. Reproductively
inactive (but mature) females present every month
could indicate that mature mullet do not spawn every
year or that fish that remain in the estuary do not
migrate offshore to spawn. The most likely possibility
would be that inactive females found in the early part
of the spawning season may not spawn until much
later. However, the presence of developing oocytes be-
ginning in August would indicate that a few months
were required for complete recrudescence. It has been
shown that striped mullet undergoing the spawning
migration between the Black Sea and the Sea of Azov
required two months for full ovarian development (Ape-
kin and Vilenskaya, 1978). Also, inactive females from
the mid to late spawning season could have spawned
early, returned to the estuary, and their ovaries could
have regressed. We found no ripe female mullet in
the estuaries during the entire study; their absence
was likely due to their migration from coastal waters.
Evidence of striped mullet spawning (through the back
calculation of birthdates from daily growth increments
from juveniles) has also shown that the spawning sea-
son extends from October through April (McDonough
and Wenner, 2003).
Sexual development
It is not known what cue initiates gametogenesis in
striped mullet, but it is generally accepted that changes
in temperature and photoperiod help regulate the sea-
sonal reproductive cycle (Anderson, 1958; Kuo et al.,
1973; Greeley et al., 1987; Kelly et al., 1991; Render
et al., 1995). It has been shown that although striped
mullet can mature in a range of salinities, the best pro-
duction is reached when their gonads develop in salini-
ties of 13 to 35 ppt (Brusle, 1981; Tamaru et al., 1994).
Previous studies of striped mullet (Kuo et al., 1974)
and other fall spawning fishes that migrate offshore
to spawn (de Vlaming, 1974; McQuarrie et al., 1978;
Whitehead et al., 1978) have indicated that a shortening
day length was the key stimulus for annual reproduc-
tive development and migration. Dindo and MacGregor
(1981) demonstrated a high correlation between the
levels of serum gonadal steroids and the gonadosomatic
index in striped mullet during the reproductive cycle;
a shortening photoperiod was suggested as the major
factor in stimulating reproductive activity. In our study
the most reproductively advanced specimens (late recru-
descence) in freshwater were captured in October and no
other specimens of similar development were captured
during the rest of the spawning season in freshwater.
In contrast, the majority of the specimens undergoing
vitellogenesis were captured in the lower portions of the
estuaries during November and December in salinities
greater than 15 ppt. This finding indicated movement
of these developing fish from the freshwater portions of
the estuary toward the ocean for the spawning migra-
tion. This migration time-period also coincided with a
mean monthly temperature decrease in temperature
(from 21.8° to 13.6°C) and in photoperiod in both the
freshwater and brackish portions of the estuaries.
The ovarian atretic process in female striped mullet
was characterized by four distinct stages that followed a
very similar progression to that described for the north-
ern anchovy (Hunter and Macewicz, 1985). Our study is
the first to describe the atretic process in striped mullet
ovaries in detail and to apply the classification system
developed by Hunter and Macewicz (1985). Knowledge
of ovarian atresia is useful for the timing of spawning.
However, the lack of immediate atretic-stage fish, with
indicators such as postovulatory follicles, prevented us
from determining the temporal duration of the different
atretic stages. The detailed morphological descriptions
of ovarian atresia presented in our study would be of
value for future studies to determine the specific timing
of the atretic process.
The histological descriptions for male and female
developmental stages in association with both size and
age data provide a clear picture of these parameters at
differentiation and maturity in South Carolina striped
mullet. Previous studies of striped mullet reproduction
concentrated on just one sex or used cultured fish exten-
sively and may have considered size or age but not both
in a single study. Because of the length of the undiffer-
entiated gonad stage in juvenile striped mullet, previous
studies have proposed the possibility of protandric her-
maphrodism in this species. However, the results of our
study indicated that striped mullet are gonochoristic but
capable of nonfunctional hermaphroditic characteristics
in differentiated mature gonads. It is hoped that the
descriptions of developmental morphological features
presented in the present study will be useful for future
studies by providing a key to reproductive ontogeny that
relates directly to somatic growth and age in striped
mullet. In particular, the morphological characteristics
of sexual differentiation could enable more precise de-
terminations of sex in immature mullet, which, in turn,
would indicate the sex ratio of males and females in a
given population and allow the development of better
management strategies.
Acknowledgments
This study would not have been possible without the
assistance of everyone, past and present, at the Inshore
Fisheries group at the Marine Resources Research
Institute of the South Carolina Department of Natural
618
Fishery Bulletin 103(4)
Resources — Myra Brouwer, John Archambault, Hayne
Von Kolnitz, Will Hegler, Erin Levesque, Alice Palmer,
Robin Freeman, Chad Johnson, Richie Evitt, Larry
Goss, and Katy Maynard. We especially thank Chad
Altman of the South Carolina Department of Health and
Environmental Control for collection of freshwater speci-
mens. In addition, we thank Myra Brouwer and David
Wyanski and the three anomymous reviewers for their
careful review of and suggestions for this manuscript.
This research was made possible by National Marine
Fisheries Service MARFIN Grant no. NA77FF0550.
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620
Abstract — Large pelagic sharks are
caught incidentally in the swordfish
and tuna fisheries of the Mediterra-
nean Sea. In our study, twelve shark
species were documented as bycatch
over three years from 1998 to 2000.
Blue shark (Prionace glauca) was
the predominant species in all gears
and areas examined. Shortfin mako
llsurus oxyrinchus), common thresher
shark tAlopias vulpinus), and tope
shark (Galeorhinus galeus) were the
next most abundant shark species —
found in more than half of the areas
sampled. Catch composition varied
both in the areas and gears investi-
gated. Sharks represented 34.3% in
weight of total catches sampled in the
Alboran Sea and 0.9% in the Straits
of Sicily. Higher shark catches were
observed in the swordfish longline
fishery, where a nominal CPUE value
reached 3.8 sharks/1000 hooks in the
Alboran Sea. Size distribution by fish-
ing gear varied significantly. Alba-
core longline catches consisted mainly
of juveniles, whereas subadult and
adult specimens were more frequent
in the swordfish longline and drift-
net fishery. The percentage of sharks
brought onboard alive was exception-
ally high; only 5.1% of the specimens
died. Few discards (seven blue shark I
were recorded in the Greek longline
fleet during onboard sampling in the
Aegean Sea.
Incidental catch and estimated discards
of pelagic sharks from the swordfish
and tuna fisheries in the Mediterranean Sea
Persefoni Megalofonou
Constantinos Yannopoulos
Dimitrios Damalas
Department of Biology
Section of Zoology-Marine Biology
University of Athens
Panepistimiopolis, llissia
Athens 15784, Greece
E-mail address (for P. Megalofonou) Pmegaloa biol uoa gr
Gregorio De Metrio
Michele Deflorio
Department of Animal Health and Welfare
Faculty of Veterinary Medicine
University of Ban
Str. Prov. Per Casamassima
70010, Valenzano Ban, Italy
Jose M. de la Serna
David Macias
Instituto Espanol de Oceanografia
Malaga, Apartado 285
29640 Fuengirola, Malaga, Spain
Manuscript submitted 18 August 2003
to the Scientific Editor's Office.
Manuscript approved for publication
8 April 2005 by the Scientific Editor.
Fish. Bull. 103:620-634(2005).
The effect of fishing on shark stocks
has become the focus of considerable
international concern. The fishery-
induced depletion of stocks is made
worse by the slow growth, late matu-
rity, and low fecundity of sharks, all
of which make them extremely vulner-
able even to modest levels of fishing.
Although no pelagic shark-directed
fishery exists in the Mediterranean
Sea, other pelagic fisheries may be
a great threat, because species with
higher production rates, such as
swordfish and tuna, continue to sup-
port the fishery while species with
lower rebound potential are driven to
stock collapse or extirpation (Musick
et al., 2000). In recent years sharks,
which were once considered bycatch
(and discarded), have become a target
species of the Spanish swordfish fleet
because highly restrictive measures
regulating swordfish catch have been
established in the Atlantic Ocean,
coupled with the fact that the inter-
national market is now more open to
pelagic sharks and their derivatives
(Mejuto and de la Serna, 2000).
Most pelagic sharks are migratory
species. Thus, effective management
proposals require reliable data that
reflect migratory patterns, and mul-
tilateral international agreements are
needed between all Mediterranean
countries involved. During the last
40-year period, Spanish, Italian, and
Greek longline and driftnet fleets
have operated throughout the Medi-
terranean, targeting mainly sword-
fish or albacore and bluefin tuna.
Catches began to expand slowly af-
ter 1962, increased rapidly with the
advent of monofilament driftnets, and
peaked in the late 1980s (Anonymous,
1999). Until recent years sharks were
the most abundant incidental catch
(landed, but not specifically targeted,
or discarded). But they may become
Megalofonou et al .: Incidental catch and estimated discards of pelagic sharks in the Mediterranean Sea 621
Figure 1
Map of the Mediterranean Sea, showing the nine study areas used for sampling sharks during
1998-2000. l = Alboran Sea. 2 = Balearic Islands area, 3 = Catalonian Sea, 4=Tyrrhenian Sea,
5 = Straits of Sicily, 6=Adriatic Sea, 7 = Ionian Sea, 8=Aegean Sea, and 9 = Levantine basin.
target species because their current low market value
now appears to be increasing. Many of the data re-
quirements of pelagic shark assessment are similar
to those for assessing other highly migratory species:
knowledge of stock structure, age and growth rates,
natural mortality rates or fishery statistics. However,
there is scant information about either the population
biology or the catch levels of most incidental species.
Primary literature on pelagic shark incidental catch
in the Mediterranean Sea is rare and relates only to
subareas that are not studied in a coordinated manner
(De Metrio et al., 1984; Filanti et al., 1986; Buencuerpo
et al., 1998; Di Natale, 1998; Mejuto et. al., 2002). IC-
CAT reports on pelagic shark catch show great annual
variation in catch statistics and are fragmented because
not all countries submit data for the entire time series.
Catches of Selachii reported by FAO statistics for Spain,
Italy, and Greece in the Mediterranean amount to 4209
metric tons in 2000, but include pelagic and benthic
sharks, skates, rays, and chimaeras together.
Given the scarcity and heterogeneity of the available
data, an international project was established (Megalo-
fonou et al.1) to collect fishing and biological data with
standardized methods from all commercial fisheries of
the European countries that catch pelagic sharks in the
Mediterranean. This article presents the results of the
Megalofonou, P., D. Damalas, C. Yannopoulos, G. De Metrio,
M. Deflorio, J. M. de la Serna, and D. Macias. 2000. By-
catches and discards of sharks in the large pelagic fisheries
in the Mediterranean Sea. European Union Project 97/50
Directorate General XIV/C1, 336 p. Directorate-General
for Fisheries and Maritime Affairs, European Commission,
Rue Joseph II, 99, B-1049 Brussels.
investigations carried out by observers at landing sites
and onboard fishing vessels that target swordfish and
tunas with longlines and driftnets. The main objective
of this study was to analyze shark incidental catch and
discards and to provide information on species composi-
tion, distribution, and abundance. The status of each
shark brought on board (alive, dead, or damaged) and
the disposition of sharks caught on some vessels (kept
or discarded) were examined by using onboard obser-
vations to obtain essential data for effective fisheries
management.
Materials and methods
Sampling areas
The Mediterranean Sea is a semi-enclosed area with
pronounced oligotrophy in the surface waters due to
small amounts of nutrient discharge from the land. The
shallow and narrow Strait of Gibraltar connects it to the
Atlantic. It consists of two nearly equal-sized basins, the
eastern and the western basin, connected through the
narrow and shallow Straits of Sicily. A network of sam-
pling ports throughout the Mediterranean was estab-
lished in order to cover a wide range of fishing grounds,
fleets, and gears. The sampling areas, shown in Figure
1, were the following: the Alboran Sea (1), the Balearic
Islands area (2), the Catalonian Sea (3), the Tyrrhenian
Sea (4), the Straits of Sicily (5), the Adriatic Sea (6), the
Ionian Sea (7), the Aegean Sea (8), and the Levantine
basin (9). Researchers from Greece, Italy, and Spain
were involved in data collection concerning incidental
catch of pelagic sharks in the Mediterranean Sea.
622
Fishery Bulletin 103(4)
Description of gear
Fleets sampled by observers targeted swordfish (Xiphias
gladius), albacore (Thunnus alalunga), or bluefin tuna
(Thunnus thynnus). Five fishing gears were studied:
swordfish longline (SWO-LL), "American type" swordfish
longline (SWO-LLA), albacore longline (ALB-LL), bluefin
tuna longline (BFT-LL), and driftnet (DN).
The swordfish longline consists of a nylon monofila-
ment main line, 2 to 3 mm in diameter, hung in a sag-
ging curve between surface floats. Branch lines with
a length of 5-18 m descend from the main line, each
terminating in a single baited J-hook. The number of
hooks ranges from 800 to 2800 and hook size varies
from no. 0 to 5. The "American type" swordfish longline,
a variation of the aforementioned gear and used mainly
in Greece, was introduced in the Greek fishery in the
mid 1980s. It consists of fewer hooks (350-700) of size
2, much longer branch lines (15-50 m), and a fish at-
tractant light stick (Duralumes" Lindgren-Pitman Inc.,
Pompano Beach, FL) attached to each branch line, 1 m
above the bait. The albacore longline is a more lightly
constructed longline that has 800 to 4000 J-hooks. hook
sizes 6-9, a main line from 1 mm to 1.6 mm in diam-
eter, and shorter branch lines (3-6 m). The bluefin
tuna longline is the most robust longline, having 1000
to 1200 J-hooks of size 0 or 1, a main line 5.0 mm in
diameter, and branch lines 45 m long. Frozen mackerels
(Scomber scombrus) or (Scomber japonicus) and frozen
squids (Illex sp.) or (Loligo sp.) are used as baits, as in
the swordfish and bluefin tuna fishery, whereas frozen
sardines — Sardina pilchardus or Sardinella sp. — are
the baits mainly used in the albacore fishery. Driftnets,
ranging from 2.5-20 km in length and from 24-40 m
in height and having a stretched mesh size of 380 mm,
were used mainly in Italy by the swordfish and tuna
fishery. Since 1998, after the enforcement of the regu-
latory measures for the driftnets, the traditional nets
were rejected and the Italian fishermen introduced a
smaller driftnet, called ferrettara. This net has a length
of 2.5 km, a depth from 18 to 25 m, and a mesh size
of 180 mm. All gears targeting large pelagic fish, both
longlines and nets, are shot (deployed) in the evening
and their retrieval begins after midnight. Among the
gears sampled, the swordfish longline is the main gear
used in the Mediterranean Sea.
Data collection and statistical analyses
Sampling was carried out during a three-year period
from 1998 to 2000. Catch and effort data were derived
from records taken by observers stationed both at main
fishing ports and onboard 11 commercial fishing vessels,
from January 1998 to December 1999. Biological data,
such as size and sex of sharks caught, were obtained
from January 1998 to September 2000. Observers were
present on fishing trips (702 fishing days) and at 17
landing sites, performing duties that included collecting
fishing and operational data, identifying and measuring
fish, as well as recording the exact location and date for
each fishing set. From each fishing vessel sampled at-
sea, these observers collected the following fishing and
operational data series: name of fishing boat, gear used,
duration of each trip in days, fishing effort per fishing
day (number of hooks for longline gear, net length, and
depth in meters for driftnet gear), number and weight
offish caught per fishing day by species, and number of
sharks discarded. Because fishermen generally do not
keep reliable logbooks to report their daily catch, sam-
pling at landing sites was performed through interviews,
as well as by direct observations and measurements.
From each boat sampled at the landing site, observ-
ers, interviewing fishermen or skippers of the vessels,
collected data on the duration of each trip in days, the
number of fishing days, the fishing area, and the fishing
effort per fishing day. The number and weight of fish
landed were observed and measured directly during
landing and recorded by species. Biological data for the
specimens caught included total length (TL) in cm, fork
length (FL) in cm, dressed weight (to the nearest 0.1 kg),
and sex when possible.
To investigate trends in the abundance of sharks,
we used the nominal catch per unit of effort (CPUE)
expressed as the number of individuals per 1000 hooks
for longlines, and per 1000 m of net for driftnets. Fish-
ing duration was assumed to be constant because soak
time was almost the same for all trips. Setting began at
dusk and retrieving began after midnight. Each shark
brought onboard vessels was assessed according to the
following scale: 1) good — very high motility and ac-
tive behavior; 2) fair — moderate motility; 3) poor — poor
motility but having the ability to respond to external
stimuli; 4) dead or showing no response to external
stimuli.
Chi-square <x2) tests were performed to test varia-
tions in species composition by type of fishing gear,
area sampled, and by sampling onboard or at landing
sites. Catch data were classified in rows (species) and
columns (gears, areas sampled, or sampling venue [fish-
ing vessel or landing site]) to create contingency tables
and were tested for significant association between
rows and columns, assuming that row and column clas-
sifications are independent (null hypothesis). Nonpara-
metric analysis of variance (Kruskall-Wallis test) was
performed to compare the total length medians of the
samples by fishing gear and per area. Nonparametric
analysis of variance was used because our data sets
did not meet the criteria needed to use the classical
method of analysis of variance (ANOVA) e.g., normally
distributed populations, equal variances.
Results
A total of 8733 sharks (153.6 t biomass) and 131,912
fish of other species (teleosts, rays, and skates) were
documented from 5826 fishing days sampled, 5124 at
landing sites and 702 onboard, during the two-year
period 1998-99 (Tables 1-2). In all areas examined
throughout the Mediterranean Sea, sharks represented
Megalofonou et al Incidental catch and estimated discards of pelagic sharks in the Mediterranean Sea
623
Table 1
Fishing sets bv gear type and numbe
•ofsh
arks caught
(landed
plus
disca
rded
throughout the N
editerranean areas studied
during 1998-99
on selected vessels observed at-sea an
d recorded at
land
ng s
ites.
Area nu
mbei
•s: 1=
Alboran S
ea, 2 =
Bale-
aric Islands area
, 3 = Catalonia
n Sea,
4=Tv
rrhenian Sea, 5=St
raits
of Sin
ly, 6
=Adriatic Sea, 7=
Ionian Sea.
8= Aegean
Sea,
and 9 = Levantine
basin i. Gear
abbrev
iation
s: SWO-LL =
swordfi
sh longline.
ABL-LL =
albacore longline
BFT-LL =
jluefin
tuna
longline. DN = dn
ftnet, SO-LL,
=American-
type swordfi
<h longl
me. PG=Prionace glauca, 10
=Isu
•us oxyrinc!
us,
AV=Alopias
vulpinus, GG = Galeorhinus galeus, LN
=Lamna nasus, A:-
=Alopias superciliosus.
3Z = Spltyrn a
zygaena, HG=He
tanchus griseus,
CP= Carcharinus
plumbeus, SB
=Squa
his blc
invillei. MM
=Mustelus m
tstelu
!, CM
=Cetorhinus
rn.axvm.us.
Number off
shing
sets
Num
aer of shi
arks
caug
ht
Area SWO-LL
ALB-LL BFT-LL
DN
SWO-LLA
PG
IO
AV
GG
LN
AS
SZ
HG
CP
SB
CM
MM
1 1391
0
0
0
0
5057
268
11
10
0
6
1
0
0
0
0
0
2 1312
48
19
0
0
85
42
17
4
0
0
0
0
0
0
0
1
3 290
41
0
0
0
97
3
2
2
0
0
0
0
0
2
0
0
4 9
0
0
0
0
5
0
0
0
0
0
0
0
0
0
1
0
5 23
7
2
0
0
3
0
1
1
0
0
0
3
2
0
1
0
6 771
6
0
0
0
2053
0
8
0
1
0
2
0
0
0
0
0
7 594
239
0
715
0
938
0
21
0
14
0
1
0
0
0
0
0
8 0
99
0
0
42
28
0
1
1
0
0
0
0
0
0
0
0
9 7
0
0
0
211
29
8
1
1
0
1
0
0
0
0
0
0
Total 4397
440
21
715
253
8295
321
62
19
15
7
4
o
2
2
2
1
Table 2
Number of sharks discarded (by fishing gear and per area) from observations onboard fishing vessels and from interviews
with fishermen at landing sites throughout the Mediterranean Sea during 1998-99. Area numbers: l=Alboran Sea, 2=Balearic
Islands area, 3 = Catalonian Sea, 4=Tyrrhenian Sea, 5 = Straits of Sicily, 6=Adriatic Sea, 7=Ionian Sea, 8=Aegean Sea. and
9 = Levantine basin). Gear abbreviations: SWO-LL = swordfish longline, ABL-LL=albacore longline, BFT-LL=bluefin tuna long-
line, DN=driftnet, SO-LLA=American-type swordfish longline.
Area
Sets
observed
onboard
Onboard sampling (693 sharks)
Number of discarded sharks
Sets
observed
at landings
At land
Number
ing sampling (8040 sharks)
of discarded sharks reported
SWO-LL
ALB-LL BFT-LL DN SWO-LLA
SWO-LL ALB-LL BFT-LL DN SWO-LLA
1
70
0
—
1321
0
— — — —
2
192
0
0 0
1187
0
— — — —
3
56
0
0
275
0
— — — —
4
9
0
_ _ _ _
0
—
— — — —
5
32
0
0 0
0
—
— — — —
6
75
0
0
702
0
— — — —
7
217
0
0 0
1331
0
0 0
8
39
0
— — — 7
102
0
0 — 0
9
12
0
— — 0
206
0
— 0
Total
702
0
0 0 0 7
5124
0
0 0 0
6.2% in number and 13.5% in biomass of the catch
sampled in swordfish and tuna fisheries. Sharks were
rarely discarded from vessels and the rare instances
were recorded only from areas off Greece. Out of 78
shark specimens caught by the Greek longline fishing
vessels only seven blue sharks, killed onboard before
they were unhooked, were thrown back to the sea. No
shark discarding at sea was reported by the skippers of
the fishing boats, nor by the fishermen interviewed at
landing sites (Table 2). Fishermen usually do not discard
their shark catch because there is a market demand for
sharks in the Mediterranean countries. Twelve shark
species were identified — blue shark (Prionace glauca),
being the most common in all areas and gears studied.
624
Fishery Bulletin 103(4)
Table 3
Biomass (in kg) and percentage composition of species sampled on selected vessels observed at
sea and at
reported at landin
I sites.
by fishing gear in
the large pelagic fi
iheries of the Mediterranean Sea during 1998-
99. Gear abbreviations: SWO-LL = swordfish
longline, SWO-LL
A=American-type swordfish longline, ABL-LL = a
lbacore
longline.
BFT-LL --
:bluefin tuna long'
ine, DN=driftnet.
Species
SWO-LL
SWO-LLA
ALB-LL
BFT-LL
DI\
Tote
1
kg
%
kg
%
kg
%
kg
%
kg
%
kg
%
At landing sites
Sharks
139,056
19.01
1004
1.86
399
0.37
—
—
11,099
11.25
151,558
15.29
Swordfish
551.998
75.46
42,597
78.94
32,573
30.47
—
—
49,226
49.91
676,394
68.25
Bluefin tuna
17,511
2.39
9496
17.60
4500
4.21
—
—
31,224
31.66
62,731
6.33
Albacore
527
0.07
192
0.36
65,149
60.95
—
—
7085
7.18
72,953
7.36
Other
22,457
3.07
675
1.25
4266
3.99
—
—
;
;
27,398
2.76
Total
731,549
53,964
106,887
—
—
98,634
991,034
On board
Sharks
11,793
9.64
785
8.08
267
0.26
297
2.10
258
14.45
13,400
5.33
Swordfish
82,885
67.77
7146
73.57
5259
5.07
192
1.36
1486
83.22
96,969
38.54
Bluefin tuna
2981
2.44
1617
16.65
13,474
13.00
13,459
94.99
42
2.33
31,572
12.55
Albacore
55
0.05
23
0.24
79,107
76.32
0
0.00
0
0.00
79,185
31.47
Other
24,584
20.10
142
1.46
5546
5.35
221
1.56
;
1
30,493
12.12
Total
122,298
9713
103,653
14,169
1786
251,619
All
Sharks
150,849
17.67
1789
2.81
666
0.32
297
2.10
11,357
11.31
164,958
13.27
Swordfish
634,884
74.37
49,743
78.12
37,833
17.97
192
1.36
50,712
50.50
773,364
62.23
Bluefin tuna
20,492
2.40
11,113
17.45
17,974
8.54
13,459
94.99
31,266
31.13
94,303
7.59
Albacore
582
0.07
215
0.34
144,255
68.52
0
0.00
7085
7.06
152,138
12.24
Other
47,041
5.51
817
1.28
9812
4.66
221
1.56
;
i
57,891
4.66
Total
853,848
63,677
210,540
14,169
100,420
1,242,654
1 No weight data were available
for other species.
Shortfin mako {Isurus oxyrinchus), common thresher
shark (Alopias vulpinus), and tope shark (Galeorhinus
galeus) were the next most abundant shark species and
were found in more than half of the areas sampled.
The rest of the shark species identified were the por-
beagle (Lamna nasus), bigeyed thresher shark {Alopias
superciliosus), smooth hammerhead iSphyrna zygaena),
bluntnose sixgill shark (Hexanchus griseus), sandbar
shark (Carcharinus plumbeus), longnose spurdog tSqua-
lus blainvillei), smoothhound (Mustelus mustelus), and
basking shark (Cetorhinus maximus).
The proportions of shark catches were significant-
ly different among fishing gears (x2 = 15970.7, df=36,
P=0.000<0.001). Total shark catches in biomass rep-
resented 17.7% on swordfish longline gear, 11.3% on
driftnet gear, and only 0.3% on albacore longline gear
(Table 3). Comparisons of catch composition among the
fishing gears in the same area showed similar results.
In the Ionian Sea, shark percentage was higher in the
swordfish longline catch than in the driftnet and alba-
core longline catch (Table 4). Catch composition also
differed significantly by area (%2 = 494558.4, df=112,
P=0.000<0.001). The higher percentage of sharks,
34.3%, was found in the Alboran Sea and the lower
percentages, in the Straits of Sicily and the Catalonian
Sea (Table 5). Statistically highly significant differ-
ences were detected in catch composition among types
of sampling (X2=29760.41, df=17, P=0.000<0.001). In
all fishing gears and areas examined throughout the
Mediterranean Sea, sharks represented 15.3% of the
total catch in biomass at landings and only 5.3% on-
board vessels. Among areas sampled, three areas (the
Alboran Sea, Catalonin Sea, and Balearic Island area)
revealed higher shark percentages at landing sites than
onboard vessels (Table 5).
Relative shark abundance varied between fisheries.
Higher shark catch rates were observed in swordfish
fisheries both onboard vessels and at landing sites
(Table 6 and 7). Overall CPUE reached 1.30 and 0.56
fish/1000 hooks in SWO-LL and SWO-LLA, respectively
(Table 8). Shark catch rates were higher in the Alboran
Sea and the Adriatic Sea, where the average CPUEs
were 3.80 fish/1000 hooks and 1 fish/1000 hooks, re-
spectively in SWO-LL (Table 8). The driftnet fishery
had a catch rate of only 0.04 fish/1000 m of nets. The
comparison of catch rates (number of shark per set)
among the different gear types in the same area (the Io-
nian Sea) revealed that the highest CPUE values were
Megalofonou et al.: Incidental catch and estimated discards of pelagic sharks in the Mediterranean Sea
625
Table 4
Biomass (in kg
and percentage composition of
species by fishing gear sampled
on selected vessels observed at-
sea and as reported
at landing sites
in the Ionian Sea during
1998
-99. Gear abbreviations
: SWO-LL = swordfish
longline
ABL-LL
= albacore longline.
DN=driftnet.
Species
SWO-LL
ALB-LL
DN
Total
kg
%
kg
%
kg
%
kg
%
Sharks
9787
13.4
568
0.5
11,357
11.3
21.711
7.5
Swordfish
43.395
59.5
35,122
30.6
50,713
50.5
129,229
44.9
Bluefin tuna
5838
8.0
5127
4.5
31,266
31.1
42,231
14.7
Albacore
0
0.0
67,594
58.9
7085
7.1
74,680
25.9
Other
13,921
19.1
6298
5.5
i
;
20,219
7.0
Total
72,941
100.0
114,709
100.0
100,421
100.0
288,070
100.0
- No available weight data were ava
lable for
)ther s
pecies.
Table 5
Biomass (% ) by species and area from data collec
,ed at 1
inding sites
and from selected longline vessels observed at-sea
in the
Mediterranean Sea during
1998-99.
Ar
ea numbers: l=Alboran Sea, 2
= Balearic Islands area, 3 = Catalonian S
ea, 4=Tyrr
rienian
Sea, 5 = Straits of Sicily, 6 =
Adriatic Sea
7=Ionian Sea, 8 =
=Aegean Sea
and 9=Levantine basin. Other
= other
species.
Species
Areas
Total
1
2
3
4
5
6
7
8
9
At landing sites
Sharks
35.74
2.06
1.78
—
—
14.32
7.03
0.25
1.87
15.29
Swordfish
61.77
93.24
97.80
—
—
78.24
45.68
2.68
79.12
68.25
Bluefin tuna
1.83
1.89
0.28
—
—
2.62
16.12
3.39
17.42
6.33
Albacore
0.07
0.18
0.01
—
—
0.00
26.15
87.86
0.35
7.36
Other
0.59
2.62
0.13
—
—
4.82
5.02
5.82
1.24
2.76
Aboard longline vessels
Sharks
7.82
1.14
0.78
5.63
0.89
19.57
10.69
11.18
2.89
5.33
Swordfish
81.04
38.15
12.91
42.66
31.73
44.40
39.73
81.31
60.60
38.54
Bluefin tuna
0.06
19.24
19.02
0.00
3.93
3.99
5.49
5.72
34.97
12.55
Albacore
0.00
33.91
67.06
0.00
44.44
4.34
24.53
0.28
0.17
31.47
Other
11.08
7.56
0.24
51.71
19.01
27.70
19.56
1.51
1.38
12.12
All
Sharks
34.34
1.74
1.35
5.63
0.89
15.11
5.52
4.88
1.93
13.45
Swordfish
62.74
73.95
61.09
42.66
31.73
73.16
41.84
35.97
77.97
63.27
Bluefin tuna
1.74
7.97
8.38
0.00
3.93
2.83
5.84
4.38
18.52
5.52
Albacore
0.07
11.99
29.01
0.00
44.44
0.65
36.02
50.79
0.34
12.70
Other
1.11
4.35
0.18
51.71
19.01
8.25
10.77
3.99
1.25
5.07
found in the swordfish longline, about 1.02 fish/fishing
set, followed by the driftnet and the albacore longline
CPUE values (Table 9).
Seasonality in catch rates was evident in the sword-
fish longline fishery; shark CPUE peaked during late
spring and summer, whereas swordfish CPUE peaked
during fall and winter (Fig. 2). In the driftnet fishery,
shark CPUE peaked during June and swordfish CPUEs
were higher during June and July (Fig. 3).
Blue shark was the most abundant shark species in
all areas and gears examined. It accounted for almost
95% of all sharks caught. Higher catch rates were ob-
served in the swordfish fishery with an average value
of 1.24 fish/1000 hooks in SWO-LL and 0.45 fish/1000
hooks in SWO-LLA fishery. Analysis of catch rates by
area showed that blue shark was caught more frequently
in the Alboran and Adriatic Sea, reaching 3.59 fish/1000
hooks and 1.00 fish/1000 hooks, respectively (Table 8).
626
Fishery Bulletin 103(4)
Table 6
Fishing sets, effort (xlOOO hooks
or 1000
m of net) and catch
rates (number offish/1000 hooks or number offish/1000
m of net )
of sharks
and target species sampled on
board in
the large
pelagic fisheries of the Mediterranean Sea during 1998-
99. Gear
abbreviations: SWO-LL = swordfi
sh longl
me, SWO-LLA=American-type
swordfish
longline, ABL-LL = a
bacore longl
ne, BFT-
LL=bluefin tuna longline, DN=
iriftnet.
Abbreviations for species: PG =
-Prionace
glauca, 10 =
Isurus oxyrinchus, AV
=Alopias
vulpinus,
GG = Galeorhinus galeus. Target species
for specific
gears: Xiphias gladius for SWO-LL, SWO-LLA and DN;
Thunnus
alalunga
for ALB-LL; and Thunnus thynnus for BFT-LL.
Fishing
Catch rate
Other
Total
Target
gear
Area
Sets
Effort
PG
IO
AV
GG
sharks
sharks
species
SWO-LL
Ionian
140
267.4
0.759
0.000
0.000
0.000
0.004
0.763
3.152
Adriatic
69
166.3
1.678
0.000
0.048
0.000
0.000
1.726
3.879
Tyrrhenian
9
18.5
0.270
0.000
0.000
0.000
0.000
0.270
8.428
Strait of Sicily
23
46.4
0.065
0.000
0.022
0.022
0.108
0.216
14.526
Balearic
125
373.1
0.027
0.029
0.008
0.005
0.003
0.072
8.003
Alboran
70
174.4
0.304
0.092
0.011
0.000
0.000
0.407
5.860
Catalonian
15
43.5
0.299
0.023
0.023
0.023
0.046
0.414
6.989
Total
451
1089.6
0.519
0.026
0.014
0.004
0.008
0.571
6.085
SWO-LL
^ Aegean
39
17.4
1.264
0.000
0.057
0.057
0.000
1.379
11.609
Levantine
12
4.8
0.417
0.208
0.000
0.000
0.000
0.625
14.167
Total
51
22.2
1.081
0.045
0.045
0.045
0.000
1.216
12.162
ALB-LL
Adriatic
6
15.3
0.000
0.000
0.000
0.000
0.000
0.000
22.222
Ionian
47
112.9
0.168
0.000
0.000
0.000
0.000
0.168
13.853
Strait of Sicily
7
17.5
0.000
0.000
0.000
0.000
0.000
0.000
127.143
Balearic
48
158.7
0.000
0.006
0.000
0.000
0.006
0.013
23.732
Catalonian
41
142.1
0.070
0.007
0.000
0.000
0.000
0.077
29.141
Total
149
446.5
0.065
0.004
0.000
0.000
0.000
0.069
26.957
BFT-LL
Strait of Sicily
2
2.8
0.000
0.000
0.000
0.000
0.000
0.000
5.357
Balearic
19
20.9
0.287
0.000
0.000
0.000
0.000
0.287
3.876
Total
21
23.7
0.253
0.000
0.000
0.000
0.000
0.253
4.051
DN
Ionian
30
300.5
0.023
0.000
0.000
0.000
0.000
0.023
0.206
Of the 3771 blue sharks measured, individuals
ranged from 40 to 368 cm TL (163.3 cm mean length
and 37.7 cm SD). The overall length-frequency dis-
tribution is shown in Figure 4. The size distribution
by fishing gear varied significantly (Kruskall-Wallis,
test statistic=350.2, P=0.000<0.05); larger specimens
were caught in the SWO-LLA and DN fishery (Fig. 5).
The Levantine basin had larger individuals whereas
the Catalonian Sea had smaller ones (Fig. 6). Out of
564 blue sharks, 346 were determined to be males
and 218 to be females. The sex ratio (males:female) fa-
vored males in almost all areas ranging from 1.29-2.50
males :1 female. The only exception was in the Alboran
Sea where females were predominant (0.61 males:l
female). Relationships between TL and FL and dressed
weight are given below:
TL = 4.1+1.176 FL
TL = 74.6 DW° 307
[r-=0.99, ;;=723]
[7^ = 0.95, n = 555].
The shortfin mako was reported in five out of
nine areas examined and represented 3.7% of the
overall shark catches. This species was caught more
often in the swordfish fishery with a mean CPUE of
0.07 fish/1000 hooks in SWO-LLA and 0.05 fish/1000
hooks in SWO-LL. Shortfin makos were more abun-
dant in the Alboran Sea and the Levantine basin
(Table 8).
The total length-frequency distribution for the 257
specimens measured is shown in Figure 4. For shortfin
makos collected, almost all were juvenile and ranged
from 62.5 cm to 272 cm TL (mean length of 120.6 cm
and 30.9 cm SD). Each fishing gear caught a statistical-
ly significant different average TL size (Kruskall-Wallis,
test statistic=23.8, P=0.000006<0.05), and larger speci-
mens were observed in the SWO-LL A fishery (Fig. 5). As
with the blue shark, larger makos came from the Le-
vantine basin and smaller ones from the Catalonian Sea
(Fig. 6). Out of 56 shortfin makos, 27 were determined
to be males and 29 to be females. Sex ratio was almost
equal (0.9 male:l female). The relationship between FL
and TL is given below:
TL = 1.136 FL - 2.5
[^ = 0.98, n =49].
Megalofonou et al Incidental catch and estimated discards of pelagic sharks in the Mediterranean Sea
627
Table 7
Fishing sets, effort (xlOOO hooks or 1000 m of net) and catch rates (number of fish/1000 hooks or number of fish/1000 m of
net) of sharks and target species sampled in the large pelagic fisheries of the Mediterranean Sea during 1998-99 as reported
at landing sites. Gear abbreviations: SWO-LL = swordfish longline, SWO-LLA=American-type swordfish longline, ABL-LL =
albacore longline, DN = driftnet. Abbreviations for species: PG=Prwnace glauca, IO=Isurus oxyrinchus, AV=Alopias vulpi-
nus, GG = Ga!enrhinus galeus. The target species for specific gears: Xiphias gladius for SWO-LL, SWO-LLA and DN; Thunnus
alalunga for ALB-LL.
Fishing
gear
Area
Sets
Effort
Catch rate
PG
IO
AV
GG
Other
sharks
Total
sharks
Target
species
SWO-LL
Ionian
454
883.5
0.457
0.000
0.001
0.000
0.002
0.461
2.521
Levantine
7
7.0
0.000
0.000
0.000
0.143
0.000
0.143
7.714
Adriatic
702
1895.3
0.936
0.000
0.000
0.000
0.001
0.937
3.562
Balearic
1187
795.7
0.087
0.038
0.018
0.003
0.000
0.145
15.474
Alboran
1321
1232.3
4.061
0.204
0.007
0.008
0.005
4.285
11.259
Catalonian
275
478.6
0.155
0.002
0.002
0.002
0.000
0.161
5.894
Total
3946
5292.4
1.384
0.053
0.005
0.003
0.001
1.445
7.188
SWO-LL
v Aegean
3
1.1
0.000
0.000
0.000
0.000
0.000
0.000
5.714
Levantine
199
90.1
0.300
0.078
0.011
0.000
0.011
0.400
15.461
Total
202
91.2
0.296
0.077
0.011
0.000
0.011
0.395
15.348
ALB-LL
Aegean
99
151.0
0.040
0.000
0.000
0.000
0.000
0.040
5.589
Ionian
192
414.1
0.075
0.000
0.000
0.000
0.000
0.075
21.166
Total
291
565.1
0.065
0.000
0.000
0.000
0.000
0.065
15.868
DN
Ionian
685
8035.8
0.034
0.000
0.002
0.000
0.001
0.038
0.215
Common thresher shark, the third most abundant
shark reported in eight out of nine areas studied, ac-
counted for 0.74% of the total shark catches. Catch rates
per fishing gear were higher in the SWO-LLA fishery
with a mean CPUE of 0.02 fish/1000 hooks and per area
sampled in the Aegean Sea, reaching 0.05 fish/1000
hooks (Table 8).
A total of 48 juvenile and adult common thresher
sharks were measured. Length-frequency distribution
was discontinuous and not very revealing because of
the small number of sharks sampled (Fig. 4). Specimens
ranged from 75 to 514 cm TL (mean value of 316.8 cm
and SD 86.4 cm). No statistically significant differences
were observed (Kruskall-Wallis, test statistic=0.638,
P=0.73>0.05) in average size of specimens by fishing
gear (Fig. 5). Larger specimens were reported from
the Levantine basin area and a smaller one was re-
ported from the Balearic Sea (Fig. 6). Out of 27 common
thresher shark sexed, 15 were males and 12 females.
Sex ratio was 1.25 male:l female. The TL-FL and TL-
dressed weight relationships are given below:
TL = 20. 2 +1.707 FL
TL = 69.7 DW° 35i
[7^ = 0.95, n=24]
[^=0.99, n=18].
The remaining nine shark species observed accounted
for only 0.87% of the total shark catches. In total, 26
tope sharks were measured (ranging from 35 to 190 cm),
15 porbeagles (ranging from 87 to 277 cm), 7 bigeyed
thresher sharks (ranging from 146 to 353 cm) and 4
smooth hammerheads (ranging from 277 to 300 cm TL).
Only three bluntnose sixgill sharks (mean weight of
10.7 kg), two sandbar sharks (mean weight of 17 kg), two
longnose spurdogs (mean weight of 1.7 kg), two basking
sharks, and one smoothhound were reported, but no
length measurements were available for these species.
A total of 571 specimens were examined for life condi-
tion on capture. The majority were very active follow-
ing capture and their physical condition was especially
good. Only 5.1% of the specimens brought onboard were
dead (Table 10).
Discussion
Our results show that most of the sharks caught by the
swordfish and tuna fisheries in the Mediterranean Sea
are typically pelagic or coastal-pelagic species of wide-
spread distribution in temperate and tropical waters
throughout the world. However, some sporadic catches of
poorly known, deepwater species of the families Hexan-
chidae and Alopiidae were also observed. The most
plausible reason for these catches is that the deepwater
species ascend close to the surface at night where they
may be taken by longlines targeting swordfish (Castro
et al., 1999).
628
Fishery Bulletin 103(4)
Table 8
Fishing set
s, effort 1x1000 hook
5 or 1000
m of net), and catch r
ates (number offish/1000 hooks or
number offish/1000
m of net ) of
sharks and target species samp
ed in the large pelagic fisheries of the Mediterranean
Sea during 1998-99
Sampling conducted
both at sea
and at landing sites.
PG =Pri
maceglaaea, 10=Isurus oxyrinet
us, AV=Alopias vulpinus, GG = Galeorhinus
galeus. The
target species for specific gears
Xiphias
gladius for SWO-LL
SWO-LLA
and DN; Th
unnus alalunga for ALB-LL; and Thunnus
thynnus for BFT-LL.
Fishing
Catch rate
Other
Total
Target
gear
Area
Sets
Effort
PG
IO
AV
GG
sharks
sharks
species
SWO-LL
Ionian
594
1151.0
0.53
0.00
0.001
0.00
0.003
0.53
2.67
Levantine
7
7.0
0.00
0.00
0.00
0.14
0.00
0.14
7.71
Adriatic
771
2061.6
1.00
0.00
0.004
0.00
0.00
1.00
3.59
Tyrrhenian
9
18.5
0.27
0.00
0.00
0.00
0.00
0.27
8.43
Strait of Sicily
23
46.4
0.06
0.00
0.02
0.02
0.11
0.22
14.53
Balearic
1312
1168.8
0.07
0.04
0.01
0.003
0.001
0.12
13.09
Alboran
1391
1406.7
3.59
0.19
0.008
0.007
0.004
3.80
10.59
Catalonian
290
522.1
0.17
0.004
0.004
0.004
0.004
0.18
5.99
Total
4397
6382.0
1.24
0.05
0.006
0.003
0.002
1.30
7.00
SWO-LLA
Aegean
42
18.5
1.19
0.00
0.05
0.05
0.00
1.30
11.27
Levantine
211
94.9
0.31
0.08
0.01
0.00
0.01
0.41
15.40
Total
253
113.4
0.45
0.07
0.02
0.01
0.01
0.56
14.72
ALB-LL
Aegean
99
151.0
0.04
0.00
0.00
0.00
0.00
0.04
5.59
Adriatic
6
15.3
0.00
0.00
0.00
0.00
0.00
0.00
22.22
Ionian
239
527.0
0.09
0.00
0.00
0.00
0.00
0.09
19.60
Strait of Sicily
7
17.5
0.00
0.00
0.00
0.00
0.00
0.00
127.14
Balearic
48
158.7
0.00
0.006
0.00
0.00
0.006
0.013
23.73
Catalonian
41
142.1
0.07
0.007
0.00
0.00
0.00
0.08
29.14
Total
440
1011.6
0.07
0.002
0.00
0.00
0.00
0.07
20.76
BFT-LL
Strait of Sicily
2
2.8
0.00
0.00
0.00
0.00
0.00
0.00
5.36
Balearic
19
20.9
0.29
0.00
0.00
0.00
0.00
0.29
3.88
Total
21
23.7
0.25
0.00
0.00
0.00
0.00
0.25
4.05
DN
Ionian
715
8336.3
0.03
0.00
0.002
0.00
0.001
0.04
0.21
Table 9
Fishing sets and catch rates (number of fish/fishing set) of sharks and
the Ionian Sea during 1998-99. PG=Prionaee glauca, \0=hurus oxyrin
The target species for specific gears: Xiphias gladius for SWO-LL and DN
target species in the three fishing gears studied in
chus, AV=Alopias vulpinus, GG=Galeorhinus galeus.
Thunnus alalunga for ALB-LL.
Fishing gear
Catch rate
Sets PG
IO
AV GG
Other sharks
Total sharks
Target species
SWO-LL
ALB-LL
DN
594 1.02
239 0.21
715 0.39
0.00
0.00
0.00
0.00 0.00
0.00 0.00
0.03 0.00
0.01
0.00
0.02
1.03
0.21
0.44
5.17
43.22
2.50
Onboard observations and interviews with fishermen
at landing sites revealed that shark discarding is not
a common practice in the large pelagic fisheries in the
Mediterranean Sea. Very few shark discards were re-
corded and only from Greek vessels (seven blue sharks
out of 78 total). The fishermen usually retain their in-
cidental catches because there is a market demand for
sharks in Europe. However, wholesale shark flesh prices
are quite variable, ranging from 2 to 8 euros. Moreover,
the jaws and tails of some shark species are often sold
Megalofonou et al.: Incidental catch and estimated discards of pelagic sharks in the Mediterranean Sea
629
100
90
13 80
a.
o
70
60
50
-•- Xiphias gladius
-•- Sharks
25
2.0
o
15 2
•■ 1 0
■■05
00
Jan Feb Mar Apr May
Jun Jul
Months
Aug Sep Oct Nov Dec
Figure 2
Monthly variation in sharks and swordfish longline CPUE (catch in num-
bers/1000 hooks) in the swordfish longline fishery of the Mediterranean Sea
during 1998-99.
0 35 ■
0 30 ■
E
0 25 ■
n
1. 1
LJ
0 20 ■
o
1
III
015 ■
■>
0.
o
010 ■
0 05
0 00
Xiphias gladius
Sharks
Jan Feb Mar
Aug Sep Oct Nov Dec
Figure 3
Monthly variation in sharks and swordfish CPUE (catch in numbers/1000 m net)
in the driftnet fishery of the Mediterranean Sea during 1998-99.
in local markets. The very low discard rate of shark —
about 1% of the sharks caught during onboard sampling
was discarded — confirmed that sharks contribute to
fishermen's income and may become target species with
future increases in their market value. That discard-
ing was observed only in the Greek swordfish fleets is
probably due to the low market prices of shark meat
compared to the high price of swordfish in this country.
Sometimes during long trips fishermen are reluctant to
retain them onboard and loose cool storage space for
more valuable species such as swordfish or tuna.
The analysis of catch composition by gear and areas
indicated that the various gears used in the swordfish
and tuna fisheries affect the shark populations dif-
ferently and that the proportion of shark catches is
related both to the type of fishing gear and the sam-
pling area. This finding is consistent with previous
findings for the Mediterranean Sea where incidental
shark catch in the swordfish fisheries varied from in-
significant to dominant, depending on the area studied
(De Metrio et al., 1984; Di Natale, 1998; Filanti et al.,
1986; Buencuerpo et al., 1998; Mejuto et. al., 2002).
The highest shark incidental catches were found in
the Alboran Sea and were probably related to their
location (Alboran Sea), adjacent to the Atlantic Ocean.
Shark bycatch in the Atlantic swordfish fishery is one
630
Fishery Bulletin 103(4)
-
Blue
shark (Prionace glauca)
8"': ■
L
n=3784
6 -
n
n
4% -
tl " "
: -
J]
n
r
I
..■k.-.-j. nnil-ftTYTTi-v.n,,-
40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360
Total Length (cm)
Shortfm mako (Isurus oxyrinchus)
n=257
B,,« n
40 60 80 100 120 140 160 180 200 220 240 260 280 300
Total Length (cm)
12 ■
Common threshe
■ shark (Alop
ias vulpinus)
10' ■
8% ■
n=50
':" '
4% ■
1
2% ■
0%
1 1
1
1 1
50 100 150 200 250 300 350 400 450 500 550
Total length (cm)
Figure 4
Length-frequency distribution (in percentage by 5-cm size classes)
for Prionace glauca, Isurus oxyrinchus, and Alopias vulpinus sampled
in the Mediterranean Sea during 1998-2000.
of the highest in the world, rarely dropping
below 30% of the total catch in numbers
of fish (Amorim et al., 1998; Buencuerpo
et al., 1998; Hazin et al., 1998; Marin et
al., 1998). The higher incidence of sharks
in the Alboran Sea could also be due to
the higher trophic potential of the western
Mediterranean compared to the eastern
part. The discrepancies in observed at-sea
and at-landing data, especially in the west-
ern Mediterranean Sea catch composition,
could be mainly due to the discarding of
"other species." In addition, the discarding
of undersize target species, such as sword-
fish and tunas, could be another reason for
the discrepancies observed. It is reasonable
that observers at landing sites were not
able to record exactly the entire nonshark
discards at sea from the information that
fishermen provided; thus shark landings
do not always reflect actual percentage of
catch composition caught at sea.
The shark catch rates obtained in our
study were lower than those reported in
previous studies for various areas of the
Mediterranean Sea (Table 11) probably be-
cause of the fishing pressure throughout
the years.
A comparison of the shark catch rates in
the Mediterranean and Atlantic indicated
that the catch rates are generally lower
throughout the Mediterranean (Table 11).
Possible reasons could be either the lower
productivity of the Mediterranean Sea, or,
as alluded to above, lower availability of
sharks in the Mediterranean due to re-
gional depletion from historical fishing, or
both. The configuration and effectiveness
of fishing gears used could be another rea-
son for the higher CPUE in the Atlantic
Ocean. Hazin et al. (1998) and Kotas et
al.2 reported an increase in use of wire
snoods in Atlantic swordfish fisheries to
retain more sharks for the growing market
for shark fins.
Monthly analysis of catches indicated
that maximum catch rates occur during
late spring and summer (May-August) in
the swordfish longline (SWO-LL) fishery,
and in June in the driftnet fishery. Month-
ly variations in catch rates were found also
by Buencuerpo et al. (1998), who reported
peaks of shark catch in April and Septem-
Kotas. J. E., S. dos Santos, V. G. de Azevedo.
J. H. de Lima, J. D. Neto, and C. F. Lin.
2000. Observations on shark by-catch in the
monofilament longline fishery off southern
Brazil and the National ban on finning, 8 p.
IBAMA-REVIZEE research. [Copyright: www.
wildaid.org.l
Megalofonou et al : Incidental catch and estimated discards of pelagic sharks in the Mediterranean Sea
631
600
500
400
300
100
600
500
400
300
200
100
—I— Max Pnonace glauca
_ Min n=3771
I I Mean+SD
Mean-SD
o Mean
I
Q
□
I
SWO-LL ALB-LL BFT-LL DN SWO-LL,
Isurus oxyrinchus
n=257
1
I
□
600
500
400
300
200
100
SWO-LL ALB-LL BFT-LL DN SWO-LL,
Aloptas vulpinus
n=48
I
I
SWO-LL ALB-LL BFT-LL DN
Fishing gear
SWO-LL,
Figure 5
Size-range variation for Prionace glauca, Isurus oxy-
rinchus, and Alopias vulpinus by fishing gear in the
Mediterranean Sea during 1998-2000. See Table 1 for
definitions of abbreviations for fishing gear along x axis.
600
300
200
100
600
500
400
200
100
— ^ax Prionace glauca
Min n=3771
CD Mean+SD
Mean-SD
□ Mean
I
M
T
T
I
T
Isurus oxyrinchus
n=257
i
600
500
300
200
100
Alopias vulpinus
n=48
I
T
1 23456789
Area
Figure 6
Size-range variation for Prionace glauca, Isurus oxy-
rinchus, and Alopias vulpinus by area sampled in the
Mediterranean Sea during 1998-2000. See Table 1 for
definitions of area numbers along the x axis.
ber in the eastern N. Atlantic and Straits of Gibral-
tar. Probably, certain water temperature preferences of
sharks during their biological cycle force them to shift
to shallower and warmer water masses, especially in
summer. At these depths sharks are more vulnerable
to surface gears and that is reflected in higher catches.
Higher catch rates in late spring and summer could
be also attributed to juvenile recruitment (Strasburg,
632
Fishery Bulletin 103(4)
Table 10
Life-status condition of 571 sharks at time of capture, by species, and per fishing gear, observed onboard commercial fishing ves-
sels in the Mediterranean Sea during 1998-2000. Gear abbreviations: SWO-LL = swordfish longline, SWO-LLA=American-type
swordfish longline, ABL-LL=albacore longline, DN=driftnet, BFT-LL=bluefin tuna longline.
Good
Fair
Poor
Number
%
Species
P. glauca
364
71.0
I. oxyrinchus
7
22.6
A. vulpinus
3
18.8
G. galeus
4
80.0
A. superciliosus
1
100.0
C. plumbeus
0
0.0
H. griseus
3
100.0
Fishing gear
SWO-LL
334
66.8
SWO-LL^
34
97.1
ALB-LL
12
46.2
DN
2
40.0
BFT-LL
0
0.0
Total
382
66.9
Number
%
69
13.5
10
32.3
4
25.0
1
20.0
0
0.0
2
100.0
0
0.0
76
15.2
0
0.0
6
23.1
2
40.0
2
40.0
86
15.1
Number
%
57
11.1
9
29.0
8
50.0
0
0.0
0
0.0
0
0.0
0
0.0
64
12.8
0
0.0
6
23.1
1
20.0
3
60.0
74
13.0
Dead
Number
%
23
4.5
5
16.1
1
6.3
0
0.0
0
0.0
0
0.0
0
0.0
26
5.2
1
2.9
2
7.7
0
0.0
0
0.0
29
5.1
1958; Carey and Scharold, 1990; Nakano, 1994; Bigelow
et al., 1999).
The abundance and widespread distribution of blue
sharks throughout the Mediterranean that we deter-
mined supports previous findings. However, our ob-
served catch rates were lower than those reported ear-
lier for the same areas (De Metrio et al., 1984; Filanti
et al., 1986; Buencuerpo et al., 1998; Di Natale, 1998;
Relini-Orsi et al., 1999; De Zio et al., 2000). Varia-
tion in sex ratio and size distribution between differ-
ent areas studied indicated sexual or size segregation,
or both. Spatial and temporal segregation of pelagic
sharks by sex and size was well documented by Stras-
burg (1958) and Nakano (1994) in the Pacific Ocean.
Further analysis regarding distribution by latitude-
longitude, time of year, and size classes of specimens
is needed to establish a possible blue shark migratory
pattern in the Mediterranean Sea. Pratt's estimates on
the sexual maturity of blue shark (215 cm TL for males,
257 cm TL for females) from the North Atlantic Ocean
(Pratt, 1979) indicate that in all areas studied in the
Mediterranean Sea, albacore and swordfish longline
fisheries generally capture immature to subadult speci-
mens and driftnets and American type swordfish long-
lines capture adults. Of all blue sharks captured in the
large pelagic fisheries of the Mediterranean during our
study, 91.1% were under 215 cm TL and 96.3% under
257 cm TL. This observation, which indicates that the
majority of Mediterranean blue sharks caught have not
reached maturity, is of concern and reinforces the need
for global assessments of this species. In the Atlantic
and Pacific Ocean results based on a considerable time
series of data show a decrease in abundance (Cramer,
1996) and in average size (Holts et al., 1998) of blue
sharks. Because blue sharks are an incidental catch in
the large pelagic and highly migratory species fisheries
in the Mediterranean, standardizing catch rates is very
difficult. Average size may be a more sensitive indicator
of shark stock status than catch rates when there is a
long enough time-series of data.
We found a much lower incidental catch of shortfin
mako than other authors have reported in the Medi-
terranean (Dai, 1997; Buencuerpo et al., 1998). This
species seems more abundant in the Atlantic Ocean
where in some areas it represents more than 10% of
total catches (Buencuerpo et al., 1998; Stone et al.,
2001). The almost equal sex ratio reflects the findings
of Buencuerpo et al., (1998) and Moreno et al., (1992).
As with blue sharks, larger makos were observed in the
Levantine basin although in small numbers. Because
males mature at 195 cm TL (Compagno, 1984) and
females between 273 and 298 cm (Mollet et al., 2000),
98.4% of shortfin makos in our study were smaller than
the size of first maturity. The absence of a consistent
time series of abundance data did not allow us to es-
timate the trend in the status of the shortfin mako
population in the Mediterranean Sea. Cramer (1996)
outlined a steady decline in catch indices for this spe-
cies from 11.86 fish/1000 hooks in 1985, to 3.52 in 1996
for the U.S. commercial Atlantic longline fishery in the
Caribbean and the Gulf of Mexico. The Azorean fleet
mako landings decreased by almost 50% in numbers
from 1987 to 1994 (Castro et al., 1999). Together with
the low catch rates in the Mediterranean Sea, short-
Megalofonou et al.: Incidental catch and estimated discards of pelagic sharks in the Mediterranean Sea 633
Table 1 1
Comparison of shark catch rates (CPUE in number offish/1000 hooks) in longline fisheries during investigations in the Mediter-
ranean Sea and the Atlantic Ocean. SWO-LL= swordfish longline; Tuna-LL=tuna longline gear.
Author
De Metrio et al. (1984)'
Filantietal.(1986l
DeZioetal. (2000)
DiNatale(1998)
Buencuerpo et al. ( 1998 1
Present study
Present study
Present study
Present study
Buencuerpo et al. ( 1998 )
Stone and Dixon (2001)
Hazinetal. (1998)
Area
Period
Ionian Sea
Ionian Sea
Adriatic Sea
Tyrrhenian Sea, Strait of Sicily
Gibraltar Strait
Ionian Sea
Adriatic Sea
Strait of Sicily
Alboran Sea
E. Atlantic
NW Atlantic
W. Atlantic
1984
1978-85
1984-98
1991-92
1991-92
1998-99
1998-99
1998-99
1998-99
1991-92
1999
1983-97
t ;<\u
SWO-LL
SWO-LL
SWO-LL
SWO-LL
SWO-LL
SWO-LL
SWO-LL
SWO-LL
SWO-LL
SWO-LL
SWO-LL
Tuna-LL
CPUE
0.9-2.2
1.5-3.0
2.4
0.4
24.2
0.5
1.0
0.2
3.8
9.9-37.J
43.8
16.8
Blue shark catch rates only.
fin makos may be one of the most over-fished pelagic
sharks in the Mediterranean Sea.
Our low catch rates for common thresher shark in the
Mediterranean were almost identical with the findings
of Buencuerpo et al. (1998) for the Gibraltar Strait re-
gion. However, the abundance of this species supports
directed fisheries in some areas. Such a case occurred
off California waters during 1977-85, when thresher
shark CPUE in the driftnet fishery ranged from 0.13 to
1.92 fish/fishing set (Holts et al., 1998). In our study,
one third of the specimens caught came from the Io-
nian driftnet fishery but the largest individual was
captured in the Levantine basin (514 cm TL) with the
swordfish longline. Pacific females mature at 315 cm
TL (Strasburg, 1958) and males mature at about 333
cm TL (Cailliet and Bedford, 1983), and we calculated
that 40% of the female common thresher sharks caught
were below 315 cm and 50% of the males were below
333 cm. Although the above data indicate that most
were caught as immature sharks, there are no data on
the first maturity of common thresher sharks in the
Mediterranean Sea. There is doubt, however, that fe-
males mature at a smaller size than males in the same
region and we therefore deduced that fishing pressure
was very intense on juvenile and subadult groups.
The low capture numbers for other shark species could
be due either to the scarcity of these species in the Medi-
terranean Sea or to the "fished-down" condition of shark
populations, or both could be causes. Another reason
could be the low capture efficiency of the gears used.
The high proportion of sharks that were alive on cap-
ture agrees with Kotas et al.2, who reported that 97%
of blue sharks and 78% of shortfin makos were alive
when landed on deck. These high survival rates are en-
couraging and could become the basis for conservation
measures in the future, such as releasing immature fish
or enforcing catch quotas.
Our study provides a reference point for the present
status of pelagic sharks in the Mediterranean Sea, the
effect of fisheries on them, and a baseline for future
monitoring. Fishing for swordfish and tunas affects
much of the pelagic ecosystem by taking predators of
swordfish and tunas (large pelagic sharks), their prey
(small tunas), and their competitors, such as other elas-
mobranchs, billfishes, and tunas. Up to now, there has
been little documentation and understanding of fishing
effects on the wider ecosystem. To strengthen manage-
ment for large pelagic fishes such as sharks, a multi-
species assessment with an ecosystem approach should
be adopted. To achieve this goal, long-term monitoring
programs should be established and exploitation strat-
egies should be linked to conservation plans for shark
species in the Mediterranean Sea.
Acknowledgments
We thank the Greek, Italian, and Spanish fishermen
who collaborated during sampling procedures. We thank
also the two anonymous reviewers who improved the
manuscript with their valuable suggestions. This study
was performed under the financial aid of the Commis-
sion of the European Communities (Project no. 97/50
DG XIV) and does not necessarily reflect the views of
the European Commission and in no way anticipates the
Commission's future policy in this area.
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635
Abstract — The annual ovarian cycle,
mode of maturation, age at maturity,
and potential fecundity of female
Rikuzen sole (Dexistes rikuzenius)
from the North Pacific Ocean off the
coast of Japan were studied by 1) his-
tological examination of the gonads,
21 measurement and observation of
the oocytes, and 3) by otolith aging.
The results indicated that ovulation
occurs from September to December
and peaks between September and
October. Vitellogenesis began again
soon after the end of the current
season. Maturity was divided into
eight phases on the basis of oocyte
developmental stages. Mature ova-
ries contained developing oocytes and
postovulatory follicles but no recruit-
ing oocytes, indicating that this spe-
cies has group-synchronous ovaries
and is a multiple spawner. Almost
all females matured first at an age
of 1+ year and spawned every year
until at least age 8+ years. Poten-
tial fecundity increased exponentially
with body length and the most fecund
fish had 15 times as many oocytes as
the least fecund fish. Potential fecun-
dity and relative fecundity were both
positively correlated with age from 1
to 6+ years, but were negatively corre-
lated, probably because of senescence,
in fish over 7 years. These results
emphasize that the total productivity
of aD. rikuzenius population depends
not only on the biomass of females
older than 1+ but also on the age
structure of the population.
Reproductive biology of female Rikuzen sole
(Dexistes rikuzenius)*
Yoji Narimatsu
Daiji Kitagawa
Tsutomu Hattori
Tohoku National Fisheries Research Institute
Fisheries Research Agency
Hachinohe Branch. Same-machi
Hachinohe, Aomon, 031-0841 Japan
E-mail address (for Y. Narimatsu) nary@aftrc go ip
Hirobumi Onodera
Iwate Fisheries Technology Center
Hirata, Kamaishi
Iwate, 026-0001 Japan
Manuscript submitted 10 January 2004
to the Scientific Editor's Office.
Manuscript approved for publication
10 April 2005 by the Scientific Editor.
Fish. Bull. 10.3:635-647 (2005).
To understand fish population dynam-
ics, reproductive information, such as
the maturation of oocytes, the size
and age at first maturity, and fecun-
dity, is indispensable. Gonadal matu-
ration is determined from the external
appearance of the gonads, the gonad-
osomatic index, and oocyte size, or
from observations of histologically
prepared gonads (West, 1990). With
the former two methods it is possible
to measure samples in the field and
to record data on numerous samples
in a short period of time; however, the
mode of oocyte development can only
be clarified by using observations of
histologically prepared gonads (Wal-
lace and Selman, 1981). The methods
used to determine if an individual has
spawned and to measure the number
of eggs spawned in the current repro-
ductive season differ with the mode of
oocyte development (West, 1990).
In fishery models, reproductive
potentials are conventionally repre-
sented by spawning stock biomass
(Ricker, 1954; Beverton and Holt,
1957; Trippel et al., 1997). Howev-
er, at the population level spawning
stock biomass does not always corre-
late with egg productivity. Length at
first maturation, the frequency of oc-
currence of degenerated oocytes, and
fecundity (that is, the total number
of offspring produced in a reproduc-
tive season by an individual female)
are closely related to the age and
energetic conditions of an individual
(Hunter and Macewicz, 1985a; Hor-
wood et al., 1986, 1989; Trippel et
al., 1997; Sampson and Al-Jufaily,
1999; Kurita et al., 2003). Therefore,
examination of age and body size in
relation to fecundity is useful in de-
termining the abundance of eggs laid
in a population.
Oocyte development can be divided
into three types (Wallace and Sel-
man, 1981). In determinate fecundity,
fecundity is fixed before spawning
starts, such as in species which have
synchronous or group-synchronous
ovaries. In indeterminate fecundity
(i.e., for those species whose ovaries
develop asynchronously), unyolked
oocytes grow to maturity after the
onset of spawning (Hunter and Mace-
wicz, 1985b; Hunter et al., 1992). In
addition, the development of oocytes
can vary even among populations of a
single species (Sampson and Al-Jufai-
ly, 1999) and some females classified
as maturing or mature by external
observation are often actually imma-
ture, and vice versa (Hunter et al.,
1992; Zimmermann, 1997). Hence,
with a species or a population for
1 Contribution B57 from Tohoku National
Fisheries Research Institute, Fisher-
ies Research Agency of Japan, Miyagi,
Japan.
636
Fishery Bulletin 103(4)
which little information is available, it is important to
determine specific reproductive traits by using the most
accurate methods and to compare the results with those
of simpler methods.
Rikuzen sole (Dexistes rikuzenius) (also known as
Rikuzen flounder, FAO) is a coastal flatfish that lives at
depths of 100 to 360 m in the waters off the south coast
of southern Hokkaido, Japan, and the southern Korean
Peninsula (Sakamoto, 1984). It inhabits sandy bottoms
and preys mainly on benthic invertebrates (Fujita et al.,
1995). It is relatively abundant in the North Pacific off
the coast of Japan and is an important fishery resource
for bottom trawlers (Ishito, 1964; Ogasawara and Ka-
wasaki, 1980). The commercial catch of flatfish such as
the Rikuzen sole has fluctuated widely in this area over
the past few decades (Anonymous, 2002), and therefore
fisheries management is needed to maintain stable and
appropriate fish-density levels.
In addition to fisheries, various internal and external
conditions may affect the fluctuations in abundance of
fish populations. Understanding reproductive traits,
or survival in the early life stages, is a step toward
revealing population dynamics. Although both sexes
have indeterminate growth trajectories, conspicuous
sexual dimorphism occurs during the growth and life
span of Rikuzen sole. Females are larger at any given
time after age 1+ and live longer than males (Ishito,
1964). The spawning period of the Sendai Bay popula-
tion occurs from late October to late January and peaks
from November to December (Ogasawara and Kawasaki,
1980). Using measurements of oocyte diameter and the
appearance of the whole ovary, Ogasawara and Kawa-
saki (1980) revealed that females spawn several batches
of eggs during one spawning season. However, because
histological observations of the gonads have not been
conducted, details of the reproductive biology, such as
annual cycle of oocyte development, and body size and
age at maturity, have not been determined. In addition,
no information about fecundity has been reported.
We examined the oogenesis of Rikuzen sole caught
in the North Pacific Ocean off the coast of Japan over
a period of one year. The aim was to determine the
mode of maturation, annual reproductive cycle, and age
at first maturity based on histological examinations,
age determinations from otolith growth increments,
and gonadosomatic indices (GSIs). Using these results,
we were able to estimate body size and age-related
potential fecundity and were able to develop a simpler
method for determining potential fecundity.
Materials and methods
From May 2000 to April 2001, except for July and
August when commercial bottom trawl fishing was pro-
hibited, Rikuzen sole samples were collected once or
twice a month from the fisheries market in Hachinohe,
Aomori Prefecture, Japan. All samples were caught by
bottom trawl nets in the coastal waters off Shitsukari
(41°22\ 141°33'E) and Hachinohe (40°43'N, 144°44'E),
128°
132°
136°
140
144°
146°
44°
N
A
/
40°
•°
<
V
36°
^
f r
-^ 1
32°
44
40°
36°
32
128' 132: 136° 140° _ I 144"
41- -
40°
39°
38L
37°
Sendai Bay
140°
14V
142° 143°
Longitude (E)
1 44°
145°
Figure 1
Catch area for Rikuzen sole (Dexistes rikuzenius)
in the Northern Pacific Ocean off the northeast
coast of Japan, 2000-2001.
from depths of 70-300 m (Fig. 1). During July and
August, samples were collected with bottom long lines
off the coast at Onezaki (39°12'N, 141°56'E) from a depth
of 85-109 m.
A total of 1031 females were collected and their
standard lengths (SL) to the nearest mm, total body
weights, eviscerated body weights, and ovary weights
to the nearest 0.1 g were measured. The GSI and body
condition (BC) of each specimen were calculated with
the following formulas: GSI = (gonad weight/eviscerated
body weight)xl00, and BC = (eviscerated body weight/
SL3)x 100. Ovaries and sagittal otoliths were removed
Nanmatsu et al.: Reproductive biology of Dexistes rikuzemus
637
An (86) (60) (84) (27) (114) (77) (64) (79) (66) (75) (129) (80) (90)
Jan Feb Mar Apr May Jun
Jul
Month
Aug early late Oct Nov Dec
Sep Sep
Figure 2
Annual changes in the gonadsomatic index (GSI) and body condition IBC) values
of female Rikuzen sole {Dexistes rikuzenius). Solid and open circles show the mean
values of GSI and BC, respectively. Vertical bars represent the standard deviations
of these means. Sample numbers are shown in brackets.
within a day after each catch for histological observa-
tions and age determination, respectively. The otoliths
were washed with distilled water and left to dry until
preparation for age determination. Ovaries were fixed in
10% buffered formalin for 24 hours. The middle portions
of eyed-side ovaries of 309 specimens were extracted,
dehydrated, embedded in paraffin, sectioned at 8 f<m,
and stained with Mayer's hematoxylin and eosin (HE)
and periodic acid Schiff (PAS).
Prepared sections were examined under a light micro-
scope. The oocytes were then divided into eight stages ac-
cording to the guidelines of Yamamoto (1956). Postovula-
tory follicles (POFs), which indicate spawning experience,
were also examined. New POFs are easily identifiable,
but those that have degenerated are difficult to distin-
guish from atretic follicles. In our study, only those that
could be easily identified were defined as POFs. Atretic
oocytes, namely advanced yolked oocytes that have been
resorbed into the ovaries, were also determined; simi-
larly, only those easily identifiable were defined as atretic
oocytes. The percentage of advanced oocytes that were
atretic was determined monthly for 10 randomly selected
2-7+ year-old fish (body size range: 143-210 mm SL).
Maturity was classified by the stage of the most ad-
vanced oocyte and the presence of POFs. By observing
maturity and advanced oocyte diameter, we tested 15
ovaries for possible differences in oocyte development
between anterior, middle, and posterior positions in the
eyed-side ovary lobe, and between eyed-side and blind-
side ovary lobes.
Oocyte diameter distributions in the late vitellogenic
maturity phase were examined; the reason this maturity
phase was selected is described in the "Results" section.
The diameters of 50 randomly selected oocytes, extracted
from the middle portions of the ovaries, were measured
under a dissecting microscope to the nearest 20 /.im.
Potential fecundity was estimated with the gravimetric
method by using ovaries in the late vitellogenic maturity
phase. Extracted ovaries were rinsed and then weighed
to the nearest 0.0001 g, and only developing oocytes,
whose size is also described in the "Results" section,
were counted.
Age was determined for all fish samples. Blind-side
otoliths were used for the analyses according to the
methods of Ishito (1964). The lateral surfaces of the
otoliths were polished with 1500-grit sand paper until
the transparent zones were visible. Ishito (1964) re-
vealed that one transparent zone is formed at the edge
of the otolith each winter and suggested that this may
be regarded as an annual mark. However, the most
interior ring appears when fish are aged 0+ (Ishito,
1964); therefore the number of transparent zones minus
the 0-year-old zone was the formula used for aging, and
the relationship between age and potential fecundity
was analyzed.
Results
Annual changes in gonadosomatic index
and body condition
The annual changes in gonadosomatic index (GSI) and
body condition (BC) are shown in Figure 2. The GSI was
638
Fishery Bulletin 103(4)
SY
LP
Figure 3
Histology of the ovarian maturity and oocyte developmental stages of Rikuzen sole tDexistes rikuzenius).
(A) Spent phase. Bar: 200 ^im. (B) Middle vitellogenic phase. Bar: 200 jim. (C) Late vitellogenic phase. Bar: 200 um.
(D) Maturity phase. Bar: 200 urn. (E) Oocyte at the cortical alveolus stage. Bar: 50 um. (F) Oocyte at the premature
stage. Bar: 50 urn. EP=early perinucleolus stage, LP=late perinucleolus stage, CA=cortical alveolus, PY=primary
yolk stage, SY=secondary yolk stage. TY=tertiary yolk stage, MN = migratory nucleus stage, AT=atretic oocyte,
POF=postovulatory follicle.
relatively low, less than 2.0, from January to March,
increased steeply from April to August, and progressed
to more than 15.0 during September to October. Values
then rapidly decreased from October to November. The
BC was low from January to April, increased to a maxi-
mum value of 18.3 in August, and then decreased to
13.7 in November.
Histological observations of oocyte development
Although oogenesis is continuous, in order to explain
the developmental process, oocyte development was
divided into eight stages, basically according to Yama-
moto (1956) (Fig. 3). The characteristics of oocytes, cell
and nuclear diameters, and time of occurrence of each
stage of oocyte and POF are shown in Table 1.
Maturity
Ovary maturity did not differ among positions in the
ovarian lobe or between eyed-side and blind-side lobes.
In addition, the diameters of the largest oocytes did
not vary significantly among positions (ANOVA, F2 42=
0.354, P=0.704) or between lobes (paired t-test, /=14,
r=0.058, P=0.955). Therefore, maturity was determined
from observations of the middle portions of eyed-side
ovaries.
Maturity was classified into eight phases, the charac-
teristics of which are shown in Table 2. Because oocytes
younger than the late perinucleolus stage occurred
throughout the year, maturity was determined as oc-
curring from this phase onwards. GSI values signifi-
cantly varied among maturity phases (ANOVA, F4205,
Nanmatsu et at: Reproductive biology of Dexistes nkuzenius
639
Table 1
Characteristics, cell and nuclear diameters, and occurrence of oocytes and postovulatory follicles at each developmental stage.
Developmental stage and measurements were determined by histological observations ( EP=early perinucleolus, LP=late perinucle-
olus, CA=cortical alveoli. PY=primary yolk, SY=secondary yolk, TY=tertiary yolk. MN=migratory nucleus, PM = prematuration,
POF= postovulatory follicle). HE=hematoxylin and eosin; PAS=periodic acid Schiff.
Developmental
stage
Characteristics
Cell
diameter
( jim)
Nuclear
diameter
(jim)
Occurrence
EP
The ooplasm is strongly stained by haematoxylin.
Several basophilic nucleoli stained by hematoxylin
are present inside the nuclear membrane.
20-70
10-35
year round
LP
The ooplasm increases in volume with growth
of the oocyte and becomes less basophilic than that
of the previous EP stage.
70-150
35-80
year round
CA
Cortical alveoli, which appear in the ooplasm,
are seen as a small empty spherical structure with
conventional HE preparations, and are stained reddish
by PAS reagents.
160-200
80-120
Feb. Jun, Aug, Oct
PY
The yolk granule occurs at the periphery of the oocytes.
180-220
80-120
year round
SY
The yolk granule increases in number and occurs
towards the nuclear membrane, and the ooplasm
occurs slightly at the periphery of the nuclear membrane.
260-440
90-130
Jan to Oct
TY
The oocyte is characterized by occupancy of the total
volume of the oocyte by a yolk granule. The nucleus of the
oocyte is still located at the center of the oocyte.
420-680
120-170
May to Dec
MN
The germinal vesicle migrates to the periphery of the
oocyte and becomes elongated and globular in shape.
600-740
130-190
Sep to Dec
PM
The germinal vesicle has broken down. Yolk granules
fuse with each other, and are stained light pink by eosin.
620-800
—
Sep to Nov
POF
The POF, containing granular, is a convoluted folded shape.
—
—
Sep to Jan
F=124.1, P<0.0001) and became significantly higher in
each successive stage of maturity (Fisher's PLSD test,
P<0.05), except for the first two phases (P=0.687). The
mature- and spent-phase ovaries were excluded from
the test because their values fluctuated depending on
spawning times or the degree of POF absorption.
Ovaries in the late vitellogenic maturity phase, which
occurred from May to September, contained oocytes in
the tertiary yolk stage, secondary yolk stage, cortical
alveoli stage, and late and early perinucleolus stages,
but not in the primary yolk stage (Table 3). Ovaries in
the premature phase, which occurred from September to
October, also revealed two peaks and a hiatus in oocyte
developmental composition. As described before, ovaries
with POFs also contained maturing oocytes. These re-
sults show that this species is a multiple-spawner and
has group-synchronous ovaries (Wallace and Selman,
1981; Takano, 1989); therefore, fecundity is fixed before
spawning starts.
On the other hand, ovaries in the mid-vitellogenic
phase were observed from January to September and
contained oocytes in the secondary and primary yolk
stages, and in the late perinucleolus stage. Cortical
alveoli are very small and were present in only 10 of
the 309 ovaries observed in our study. It is possible
that the duration of this stage is very short. Therefore,
in the ovaries oocytes do not divide into two groups,
those that spawn in the next reproductive season and
those that do not, until they have progressed to the late
vitellogenic maturity phase.
Oocyte composition
Table 3 shows the annual changes in oocyte composi-
tion. One ovary observed in January contained POFs
and perinucleolus stage oocytes, whereas the others
contained oocytes in the primary and secondary yolk
stages. Of those observed from February to April, none
contained POFs. Frequency of occurence of ovaries
with secondary yolk-stage oocytes increased during the
season. From May to August the most advanced oocyte
observed was in the tertiary-yolk vitellogenic stage, and
the frequency of this stage also increased in number
throughout this season. Migratory-nucleus-stage and
640
Fishery Bulletin 103(4)
Table 2
The characteristics, occurrence and gondadosomatic index values of each maturity phase,
abbreviated as follows: EP=early perinucleolus, LP=late perinucleolus, CA=cortical alveoli
yolk, TY=tertiary yolk, MN=migratory nucleus. PM=prematuration, POF=postovulatoi
PAS=periodic acid Schiff.
Developmental oocyte stages were
, PY=primary yolk, SY=secondary
y follicle. n=number of samples.
The most
advanced
GSI
Maturity phase
Characteristics
oocyte observed
Occurrence
(mean±SD)
;?
Immature
Ovaries contain only EPs and LPs, but not POFs.
LP
Jan to Apr
1.57 ±0.34
13
Previtellogenic
This phase can be discriminated by PAS staining.
Specimens in this phase were scarce.
CA
Feb
1.67
1
Early vitellogenic
Ovaries consist of PY and unyolked oocytes, and
occur prevalently from March to April.
PY
Jan to Oct
2.09+0.61
41
Mid-vitellogenic
Ovaries contain SY and all stages of oocytes younger
than the SY stage. SY
Jan to Oct
4.40 ±1.72
61
Late vitellogenic
Ovaries contain TY and all stage oocytes younger
than TY, but not SY.
TY
May to Dec
12.98 ±5.74
67
Premature
Ovaries lack PY and SY. occurs prevalently during
September.
MN or PM
Sep to Dec
17.56 ±5.00
28
Mature
Ovaries contain both empty follicles and oocytes
that have advanced beyond the secondary
yolk stage.
advanced more
than SY
Sep to Dec
16.21 ±8.34
25
Spent
Ovaries contain empty follicles but oocytes that
have advanced beyond the secondary yolk stage
are absent.
LP
Sep to Jan
2.71 ±2.41
73
premature-stage oocytes and POFs began to occur in
September. The composition of oocytes observed during
this month was divided into three groups: premature,
maturing, and postmature oocytes. In October, almost
all ovaries (96.2%) contained POFs. Of these, 28.0%
also contained oocytes at the tertiary yolk stage or
migratory-nuclear stage (or at both stages) and the
remaining 72.0% contained primary-yolk stage or less
advanced stage oocytes (or both of these stages). From
November to December, all ovaries contained POFs and
only a few (3.7% in November and 5.3% in December)
also contained vitellogenic oocytes. Therefore, almost all
individuals had finished spawning by October, although
a few continued to spawn until December.
Atretic oocytes were found in samples throughout the
year, except February, in ovaries of various maturity
phases. Frequency of occurrence was highest in May,
and gradually decreased until the spawning season
(Table 3). Oocytes that ovulated but remained in the
ovigenous folds and were resorbed later were treated
as atretic oocytes because it was difficult to distinguish
between them and atretic oocytes if they were somewhat
absorbed. Atretic oocytes did not always correspond to
the most advanced oocytes in the ovaries. They occupied
0.3-1.8% (mean ±SD = 1.0 ±0.5) of the yolked, advanced
oocytes observed in the ovaries in May (the number of
oocytes counted in 10 ovaries ranged from 117 to 615),
and from 0.4 to 1.8% (1.0 ±0.4) of those observed in
August (range: 108-383 oocytes in 10 ovaries).
Body length and age at first maturity
The relationship between SL or age and maturity
of the fish caught between the prespawning month
(August) and the late-spawning month (December) was
examined. Otolith growth increments were counted for
all specimens. Because the spawning season occurs
from September to December, the birth dates of all
fish were conveniently defined as 1 January; age was
then determined accordingly. SL ranged from 114 to
237 mm (;? = 189, 170.6 ±25.3) and age, from 1 to 8 +
years (2.8 ±1.4). Individuals grew steeply until 2 years
and moderately until 6 years, after which time their
growth was slow (Fig. 4). All females whose ages were
estimated at more than 2+ years (n=152) were iden-
tified as maturing or spent-stage females. Only one
1+ year-old specimen (131 mm SL) was classified as
immature, whereas the other 1+ specimens (?i=36, 140.0
±11.8) were classified as maturing or postmaturation
females (Fig. 4).
Potential fecundity
The diameters of oocytes in late vitellogenic maturity
phase ovaries were measured because potential fecun-
dity was determined as occurring before this maturity
phase. Oocytes ranged in diameter from less than 100
to 950 f*m and were separated into a small (less than
200 ;im) or large group (larger than 300 ^m, Fig. 5).
Nanmatsu et al. Reproductive biology of Dexistes nkuzenius
641
Table 3
Annual changes in the composition of female Rikuzen sole oocytes in each maturity phase. Some maturing and spent ova-
ries contained ovulated but not spawned oocytes. Such ovaries were included under "Number of samples with atretic oocytes."
Developmental oocyte stages were abbreviated as follows: EP=early perinucleolus, LP=late perinucleolus, CA=cortical alveoli,
PY=primaryyolk,SY=secondary yolk, TY= tertiary yolk, MN=migratory nucleus, PM = prematuration,POF=postovulatory follicle.
Year Month
EP LP
CA
PY
SY
TY
MN
PM
POF
Maturity phase
Number of
samples with
atretic oocytes
2000 Mav
Jun
Jul
Aug
early Sep
late Sep
Oct
Nov
Dec
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
4
Early vitellogenic
4
19
Mid vitellogenic
15
1
Late vitellogenic
1
18
Mid vitellogenic
10
1
Mid vitellogenic
0
3
Late vitellogenic
2
7
Mid vitellogenic
2
4
Late vitellogenic
1
1
Early vitellogenic
0
1
Mid vitellogenic
0
4
Mid vitellogenic
1
33
Late vitellogenic
9
1
Late vitellogenic
0
2
Mid vitellogenic
1
4
Late vitellogenic
0
6
Late vitellogenic
2
1
Premature
0
8
Premature
1
2
Premature
1
4
Spent
1
3
Spent
1
11
Mature
3
2
Mature
0
3
Late vitellogenic
0
1
Late vitellogenic
0
12
Late vitellogenic
2
1
Premature
0
12
Premature
1
2
Premature
1
3
Mature
2
1
Premature
0
10
Spent
4
1
Spent
0
7
Spent
4
2
Mature
1
5
Mature
3
24
Spent
15
2
Spent
1
1
Mature
1
13
Spent
5
5
Spent
1
1
Mature
0
continued
Those in the large-diameter group were regarded as
advanced yolked oocytes that would be spawned in the
next reproductive season and were used for estimations
of potential fecundity. Potential fecundity varied widely
among individuals from 24,765 (114 mm SL) to 393,212
(204 mm SL) eggs (an average of 161,340 ±90,688 eggs
(165 ±25 mm SL)). Potential fecundity (PF) was posi-
tively correlated with body size and the relationship was
expressed by the following equation:
PF=0.000235SL3
(Fig. 6).
Potential fecundity and relative fecundity (poten-
tial fecundity /eviscerated body weight) increased with
642
Fishery Bulletin 103(4)
Table 3 (continued)
Number of
samples with
Year
Month
EP
LP
CA
PY
SY
TY
MN
PM
POF
n
Maturity phase
atretic oocytes
2001
Jan
+
+
+
+
+
2
8
Immature
Early vitellogenic
1
0
+
+
+
+
2
Mid vitellogenic
0
+
+
+
1
Spent
0
Feb
+
+
+
+
+
+
+
+
5
1
5
Immature
Previtellogenic
Early vitellogenic
0
0
0
+
+
+
+
1
Middle vitellogenic
0
Mar
+
+
+
+
+
3
15
Immature
Early vitellogenic
0
2
+
+
+
+
1
Mid vitellogenic
1
Apr
+
+
+
+
+
3
10
Immature
Early vitellogenic
0
3
+
+
+
+
6
Mid vitellogenic
1
Total
309
104
growth at age s6+ years and decreased at a7+
years (Fig. 7). Comparisons of the relative fe-
cundity among age groups (1-2+, 3-4+, 5-6+,
and 7-8+) revealed significant differences with
age (ANOVA, F3 38=7.431, P<0.0005). In addi-
tion, post hoc tests (Fisher's PLSD, P<0.05)
revealed significant differences between the
following age groups: 1-2+ and 3-4+, 1-2 +
and 5-6+, and 5-6+ and 7-8+. The GSI and
BC values of individuals aged ;»7+ years were
also lower than those of individuals aged 5 +
and 6+ years, but the differences were not sig-
nificant (aq-test, P>0.05); however, the sample
size was very small; therefore the tests have
little power.
Discussion
Gonadal maturation
GSI and histological examinations showed that
oocytes develop rapidly from May to August and
that the reproductive season lasts from Septem-
ber to December; mainly from September to October in
the study area. Mature females in the Sendai Bay area
were also observed for four months, but the reproductive
season in this area occurs from October to January and
peaks in November (Ogasawara and Kawasaki, 1980),
which was later than the peak documented in the pres-
ent study for the area off the Hachinohe coast. The
Sendai Bay catch area was located at a lower latitude
(37°00'N-38°05'N; Ogasawara and Kawasaki, 1980)
than that of the Hachinohe study area (Fig. 1); this
difference is relevant because gonadal maturation is
usually dependent on water temperature (Kruse and
250
.• * •
f
200
e & * ? : :
** kj H
£ 150
E
1. * T •
_i
•
co 100
50
01 23456789
Age (years)
Figure 4
Relationship between age, including maturity, and the standard
length of Rikuzen sole (Dexistes rikuzenius) caught between
August and December. Solid circles represent maturing or spent
individuals and the open circle at age 1+ represents an imma-
ture individual.
Tyler, 1983; Asahina and Hanyu, 1983; Conover, 1990).
In 2000, the water temperature in the Hachinohe study
area decreased faster than that of Sendai Bay in 1977
and 1978 when studied by Ogasawara and Kawasaki
(TNFRI1). These results indicate that gonadal matura-
tion in Rikuzen sole also depends on water temperature.
TNFRI (Tohoku National Fisheries Research Institute).
2004. Unpubl. data. Water temperature data. Tohoku
National Fisheries Research Institute, Fisheries Research
Agency of Japan. Shiogama City, Miyagi Prefecture 985-
0001 Japan.
NarimatSU et a\ : Reproductive biology of Dexistes rikuzenius
643
II .JJI
100 200 300 400 500 600 700 800 900 1000 100 200 300 400 500 600 700 800 900 1000
£ 10
100 200 300 400 500 600 700 800 900 1000 100 200 300 400 500 600 700 800 900 1000
lj|ta
100 200 300 400 500 600 700 800 900 1000 100 200 300 400 500 600 700 800 900 1000
Oocyte diameter (urn)
Figure 5
Oocyte diameter distributions just before the spawning season of Rikuzen sole [Dexistes
rikuzenius). Oocyte diameter was divided into small-scale (less than 200 j<m) and
large-scale groups (more than 300 ,«m).
Rikuzen sole require a long period of time
for vitellogenesis and therefore the repro-
ductive cycle may differ among areas.
In some flatfishes, it has also been re-
ported that oocytes in the cortical alveoli
stage appear for only a short period of time
because they develop rapidly into the pri-
mary yolk stage (Yamamoto, 1956; Janssen
et al., 1995). In the present study, only a
small percentage of individuals contained
this stage of oocytes; however, cortical
alveoli were present throughout various
months from June to October and in Feb-
ruary. These results are similar to results
for other flatfish and may indicate that the
absence of cortical alveoli oocytes in some
ovaries does not represent an incontinuity
of oocyte composition.
From October to December some females
possessed primary yolk-stage oocytes,
450000
400000
•
~ 350000
"D
Sm
=J 300000
• */
— 250000
m
c 200000
£
[£ 1 50000
100000
•
•
•
50000
0
1(
0 120 140 160 180 200 220
Standard length (mm)
Figure 6
Relationship between the standard length and potential fecundity of
Rikuzen sole (Dexistes rikuzenius). Potential fecundity was measured
only for advanced yolk oocytes in late vitellogenic maturity phase
ovaries. The equation of the regression curve is shown in the text.
644
Fishery Bulletin 103(4)
450000
2500
400000
•
>. 350000
c 300000
3
e e
o 8
o
o 0
•
o
o J to °
8 Sq «°
o «s to -e
•° *
• to o
i f
Relativ
o o
o o
o in
rc 250000
~ 200000
c
£ 1 50000
o
0_
e fecundity
o
o
o
100000
i
500
50000
■ •
•
0 2
4 6 8 10
Age (years)
Figure 7
Relationship between
age (years) and potential fecundity (solid circle.
oocyte number/femal
e) and relative fecundity (open circle, oocyte
number/female per g
) of Rikuzen sole (Dexistes rikuzenius) in the
late vitellogenic maturity phase.
although they had no other vitellogenic oocytes. There
are three potential hypotheses to explain the fate of
these primary yolk oocytes. One explanation is that the
oocytes are spawned in the current reproductive season.
Maddock and Burton (1999) showed that in American
plaice (Hippoglossoides platessoides), a group-synchro-
nous spawner, the size frequency of oocytes during the
prereproductive season was not continuous, whereas
during the reproductive season the size frequency was
continuous. The reason for this difference was that
during the reproductive season cortical alveoli stage oo-
cytes are larger than those during the prereproductive
season. It is unclear, however, whether these cortical
alveoli oocytes will be spawned during the reproductive
season (Maddock and Burton, 1999). Although similar
to those of the American plaice, all Rikuzen sole ovaries
with primary yolk-stage oocytes contained no secondary
or more advanced stage oocytes. In addition, oocytes
that would be spawned in the current reproductive sea-
son developed beyond the secondary yolk stage before
the beginning of the reproductive season. Therefore,
primary yolk-stage oocytes occurring late in the repro-
ductive season might not be spawned that season.
Primary yolk-stage oocytes were found from October
to August (the late reproductive to vitellogenic season)
(Table 3). From October to December only a small per-
centage of individuals possessed oocytes in this stage,
whereas their ratio increased from January to April.
These results indicate that females begin vitellogenesis
for the next reproductive season shortly after spawning.
This hypothesis is supported by reports that the vitel-
logenesis of flatfishes takes a long time (Yamamoto,
1954, 1956; Ishida and Kitakata, 1982; Zamarro, 1992;
Harmin et al., 1995).
Atretic oocytes were present in low proportions from
March to April and in high proportions in May. The
mature phase of ovaries with atretic oocytes did not
differ from that of ovaries without atretic oocytes. In
addition, developmental stage did not differ between
atretic and normal oocytes in any ovary. Therefore, it
seems that the primary yolk-stage oocytes observed late
in the reproductive season will not selectively degener-
ate, rather they will be spawned.
Decisions regarding maturity and age at maturity
POFs were present from September to January and all
specimens caught during this period had either oocytes
in the advanced yolk stage or POFs in their ovaries. All
specimens caught between November and December con-
tained ovaries with POFs, whereas they were observed
only in a small percentage of the specimens caught in
January. The spawning season lasted from September
to December, but almost all spawning had finished by
October. These results indicate that the duration until
resorption of the POFs ranges from a few weeks to two
months. For a few weeks immediately following spawn-
ing, the presence of POFs can be used as a criterion for
the differences between post- and prespawning individu-
als. This feature is consistent with that of other flatfish
in which POFs degenerate within one or two months
(Barr, 1963; Janssen et al., 1995).
By noting the presence of POFs and advanced yolked
oocytes, we were able to classify individuals as mature
or immature. All but one individual caught during the
reproductive period were maturing or had spawned.
The body size of the mature females ranged from 114
to 237 mm SL, which corresponded to an age from 1 to
8+ years, respectively, whereas the immature female
(131 mm SL) was age 1+. These results indicated that
most female Rikuzen sole in this population mature at
2 years old, or at the latest at 3 years old, and spawn
every year after maturation. Almost all (99.5%) fish
caught commercially are adult individuals.
Nanmatsu et al : Reproductive biology of Dexistes nkuzemus
645
Fecundity
The potential fecundity of group-synchronous spawning
fish can be determined prior to the spawning season
(Takano, 1989). In Rikuzen sole, oocyte-stage composi-
tion became discontinuous beyond the late vitellogenic
maturity phase, when a gap was found between secondary
or tertiary yolk stages and the late perinucleolus stage.
Oocyte diameter distributions in late vitellogenic maturity
phase ovaries revealed that oocytes could be divided into
small (less than 200 jim) and large (more than 300 jmi)
scale groups. Taking into account the oocyte diameters
observed in the histological sections, small-scale group
oocytes corresponded to cortical alveoli or less advanced
stage oocytes, whereas larger oocytes corresponded to
secondary yolk or more advanced stage oocytes.
The occurrence of atretic oocytes was highest in May
and became lower as the season progressed until the
end of the spawning season. These phenomena may cor-
relate with both annual feeding cycles and maturation.
Ogasawara and Kawasaki (1980) showed that in the
Sendai Bay population, Rikuzen sole feed actively for
a few months after spawning and then feed passively
for the next few months. Gut-content weight began to
increase again in June. In our study area, BC increased
from about May, corresponding to the time when the
oocytes begin to mature rapidly. As described before,
vitellogenesis in this species takes a long time. Because
oocytes are metabolically active in the season when the
energetic condition of Rizuzen sole is still recovering, a
higher proportion of atretic oocytes occur during this
period.
Potential fecundity may not correspond to annual fe-
cundity because of the presence of atretic and residual
oocytes (Witthames and Greer Walker, 1995; Kurita et
al., 2003). Therefore, we examined the potential fecun-
dity of fish in the late vitellogenic maturity phase just
before the spawning season. The frequency of occurrence
of atretic oocytes may be underestimated because these
oocytes have shrunk and are smaller than the maturing
yolked oocytes. In addition, atretic oocytes may occur in
the ovaries during the premature maturity phase. How-
ever, in our samples a low percentage of atretic oocytes
were observed. Only a small percentage of premature
ovaries were found on or before the reproductive season;
this finding seems to indicate that the oocytes of this
species take a short time to develop from the tertiary
vitellogenic stage to maturation. These results make
clear that potential fecundity differs from annual fecun-
dity, but the extent of this difference was nevertheless
relatively small in the samples. Moreover, ovulated, but
not spawned oocytes were observed in the maturing
and spent ovaries; these oocytes have the potential to
cause an overestimation of annual fecundity. However,
the frequency of ovaries with residual ovulated oocytes
was small; therefore, such oocytes may not seriously
influence annual fecundity, as with the case of Dover
sole (Microstomus pacificus) (Hunter et al., 1992).
Vitellogenesis in American plaice was seen to begin
soon after spawning ( Zamarro, 1992), as with Rikuzen
sole. Separation of oocyte diameter in this species oc-
curs approximately three months before the start of
the spawning season. In Rikuzen sole, potential fe-
cundity was determined as being much closer to the
reproductive season. Reproduction occurred from early
September, but occurrence of the maturity phase in
August varied largely among individuals. The potential
fecundity of almost all fish (85%) could be determined
until August. These results indicate that certain condi-
tions and measurements are necessary when examining
potential fecundity without histological methods.
Potential fecundity became determinate for the first
time at maturity during the late vitellogenic phase.
Some of the maturity phase ovaries contained second-
ary yolk-stage oocytes and all contained tertiary yolk-
stage oocytes. The secondary yolk-stage oocytes ranged
in diameter from 260 to 440 jim — a range that does not
overlap with the diameter range of primary yolk-stage
oocytes (180-220 f<m). Therefore, to measure potential
fecundity without histological observations, it is first
necessary to clarify the division of oocyte diameter into
large- and small-scale groups in order to identify de-
terminate fecundity. In ovaries that contain large- and
small-scale oocytes, only oocytes greater than 260 fim
in diameter but that do not experience ovulation be-
tween May and August are targets for potential fecun-
dity measurements. This method will make it easier to
measure the potential fecundity of this population in
the future.
Potential fecundity increased curvilinearly with SL.
The body size of the females continued to grow even
after maturation; the most fecund individual had 15
times more maturing oocytes than the least fecund one.
Potential fecundity also increased until age <6+ years
but decreased in individuals at 27+ years. One reason
that older fish have less potential fecundity is a lesser
energetic condition with senescence. Fecundity has been
also reported as declining with age in other fish. As
American plaice in the tail of the Grand Bank of New-
foundland become older, the number of eggs produced
by females decreased (Horwood et al., 1986). Orange
roughy, mature first at 25 years old and live for more
than 100 years; their fecundity increases from an age
of 25 to 60 years old, then decreases in individuals
aged over 60 years old (Koslow et al., 1995). Fecundity
is positively correlated with BC in the orange roughy.
The oldest Rikuzen sole to appear in that study area
was 10+ years (Ishito, 1964) and body growth almost
finished by age 6+ years (Fig. 6). In addition, both the
BC and relative fecundity of fish over 7+ years were
lower than those of fish from 4 to 6+ years.
Spawning stock biomass (SSB) has been used to ex-
amine the relationship of spawning fish and recruit-
ment; however, recent studies have indicated that SSB
is not always linked to reproductive potential, mainly
because age composition and nutrient conditions also af-
fect fecundity (Hunter et al., 1985a; Trippel et al., 1997;
Marshall et al., 1998). Our study shows that relative
fecundity is positively correlated with body length. In
addition, both relative and potential fecundity increase
646
Fishery Bulletin 103(4)
with age, but decrease again in later years. These re-
sults support previous studies and emphasize the impor-
tance of understanding the demographic structure and
reproductive biology of a population for the management
of fish resources.
Acknowledgments
We are grateful to Hiroyuki Munehara for his valuable
discussion and comments on the early version of this
manuscript and to Yoshio Ishito for his support in col-
lecting samples. This work was financially supported
by the DEEP Program of the Ministry of Agriculture,
Forestry, and Fisheries, Japan.
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Sea Res. 29:205-209.
Zimmermann, M.
1997. Maturity and fecundity of arrowtooth flounder,
Atheresthes somias, from the Gulf of Alaska. Fish.
Bull. 95:598-611.
648
Abstract — Data from ichthyoplankton
surveys conducted in 1972 and from
1977 to 1999 (no data were collected
in 1980) by the Alaska Fisheries Sci-
ence Center (NOAA, NMFS) in the
western Gulf of Alaska were used
to examine the timing of spawning,
geographic distribution and abun-
dance, and the vertical distribution
of eggs and larvae of flathead sole
iHippoglossoides elassodon). In the
western Gulf of Alaska, flathead sole
spawning began in early April and
peaked from early to mid-May on
the continental shelf. It progressed
in a southwesterly direction along the
Alaska Peninsula where three main
areas of flathead sole spawning were
indentified: near the Kenai Penin-
sula, in Shelikof Strait, and between
the Shumagin Islands and Unimak
Island. Flathead sole eggs are pelagic,
and their depth distribution may be a
function of their developmental stage.
Data from MOCNESS tows indicated
that eggs sink near time of hatching
and the larvae rise to the surface to
feed. The geographic distribution of
larvae followed a pattern similar to
the distribution of eggs, only it shifted
about one month later. Larval abun-
dance peaked from early to mid-June
in the southern portion of Shelikof
Strait. Biological and environmental
factors may help to retain flathead
sole larvae on the continental shelf
near their juvenile nursery areas.
Temporal and spatial distribution and abundance
of flathead sole iHippoglossoides elassodon)
eggs and larvae in the western Gulf of Alaska
Steven M. Porter
Alaska Fisheries Science Center
7600 Sand Point Way NE
Seattle, Washington 98115
Email address: steve.porter@noaa gov
Manuscript submitted 13 September 2004
to the Scientific Editor's Office.
Manuscript approved for publication
6 April 2005 by the Scientific Editor.
Fish. Bull. 103:648-658 (2005).
Flathead sole iHippoglossoides elas-
sodon) inhabit the continental shelf
waters of the North Pacific Ocean from
the northwest coast of North America
to the Sea of Okhotsk in Asia (Alder-
dice and Forrester. 1974). The west-
ern Gulf of Alaska is an important
area for adult, juvenile, and larval
flathead sole. The continental shelf
from the entrance to Prince William
Sound to Unimak Island contains the
highest relative abundance of adult
flathead sole (as expressed as kg/ha)
off the west coast of North America
(Fig. 1; Wolotira et al.1). Adult flat-
head sole are most abundant between
depths of 100 and 200 m in this area
(Wolotira et al.1). During the spring
adult flathead sole move from winter-
ing grounds on the upper continental
slope onto the continental shelf (Rose,
1982). Spawning flathead sole are
found from February to August, and
the greatest proportion of spawning
fish occurs in April and May at depths
between 100 and 200 m (Hirschberger
and Smith2). Flathead sole eggs
range in size from 2.75 to 3.75 mm
(Matarese et al., 1989), and under
environmental conditions similar to
those they could experience in the
Gulf of Alaska (temperature = 5.5°C
and salinity=31 PSU) it takes them
about 15 days to hatch (Alderdice and
Forrester, 1974). During the spring,
flathead sole are the most abundant
pleuronectid larvae in western Gulf
of Alaska (Rugen3). Standard length
at hatching is 6.89 ±0.40 mm (95%
ethanol-preserved size; S. Porter
unpubl. data). Under conditions that
flathead sole larvae could experience
in the Gulf of Alaska, first feeding
occurs about 1 week after hatching,
and in about 2 weeks the yolk is
exhausted (Alderdice and Forrester,
1974). Copepod nauplii 150-350 fim
in size are their predominant prey
(Watts, 1988). In Auke Bay, Alaska,
flathead sole larvae undertake reverse
diel vertical migrations; they are con-
centrated near 5 m depth during the
day and then disperse over a wider
range of depths at night (Haldorson
et al., 1993). The bays of the Alaska
Peninsula and Kodiak Island provide
nursery areas for juvenile flathead
sole (Norcross et al., 1999).
Studies of the drift of walleye pol-
lock (Theragra ehalcogramma) larvae
in Shelikof Strait have shown that
there are physical processes that can
slow the drift of these larvae out of
Shelikof Strait and keep them near
shore (Bailey et al., 1997). The pro-
1 Wolotira, R. J., T. M. Sample, S. F. Noel,
and C. R. Iten. 1993. Geographic and
bathymetric distributions for many com-
mercially important fishes and shellfishes
off the west coast of North America,
based on research survey and commer-
cial catch data, 1912-84. NOAA Tech.
Memo. NMFS-AFSC-6, 184 p. Alaska
Fisheries Science Center, 7600 Sand
Point Way NE, Seattle, WA 98115.
2 Hirschberger, W. A., and G. B. Smith.
1983. Spawning of twelve groundfish
species in the Alaska and Pacific coast
regions, 1975-81. NOAA Tech. Memo.
NMFS F/NWC-44, 50 p. Northwest and
Alaska Fisheries Center, 2725 Montlake
Boulevard East, Seattle, WA 98112.
1 Rugen, W. C. 1990. Spatial and tem-
poral distribution of larval fish in the
western Gulf of Alaska, with emphasis
on the period of peak abundance of wall-
eye pollock (Theragra ehalcogramma)
larvae. U.S. Dep. Commer., NWAFC
Processed Rep. 90-01, 162 p. Alaska
Fisheries Science Center, 7600 Sand
Point Way NE, Seattle, WA 98115.
Porter: Temporal and spatial distribution and abundance of eggs and larvae of Hippoglossoides elassodon 649
60 -
58 -
56°-
54 -
52-
174°
_1_
170°
166"
L_
162"
i
158°
i
154°
I
150°
1_
146°
Kenai
Peninsula
Prince
William
Sound
Bering
Sea
»«?
V
c^-
Umnak
Island
Unimak
Island
Shumagm
Islands
s Kodiak
Island
Gulf of Alaska
w
170°
— I
166°
I
162"
158"
I
154°
— I
150' W
t.;1
-60°
■5S
-56°
-54°
■52°N
Figure 1
The western Gulf of Alaska where ichthyoplankton surveys were conducted in 1972 and from
1977 to 1999 by the Alaska Fisheries Science Center to examine the timing of spawning,
geographic distribution and abundance, and vertical distribution of flathead sole (Hippoglos-
soides elassodon).
cesses that affect the drift of walleye pollock larvae
may also affect the drift of flathead sole larvae in this
area. For example, the drift of walleye pollock larvae in
Shelikof Strait can be slowed if they become entrained
in eddies that form there (Bailey et al., 1997). The
Alaska Coastal Current flows southwest through She-
likof Strait and branches just south of it; one branch
continues along the continental shelf, and the other
heads seaward (Bailey et al., 1997). Whether larvae will
stay near shore or move off shore is determined by one
or other of these two branches of the current.
Information about the early life history of flathead
sole in the Gulf of Alaska is lacking. Data from ich-
thyoplankton surveys conducted in the western Gulf of
Alaska were used to examine the timing of spawning,
geographic distribution and abundance, and the verti-
cal distribution of flathead sole eggs and larvae. The
purpose of this study was to give a general overview of
flathead sole egg and larval distribution and abundance
in the Gulf of Alaska during the calendar year.
Materials and methods
The study area covered the continental shelf (approxi-
mately 300 m depth and less) of the western Gulf of
Alaska from the Kenai Peninsula southwest along the
Alaska Peninsula to Umnak Island (Fig. 1). Also covered
was the east side of Kodiak Island out to the continental
shelf break (Fig. 1). The Alaska Stream and the Alaska
Coastal Current are two major surface currents that
flow through the study area. Both currents flow south-
westerly: the Alaska Stream along the shelf break and
the Alaska Coastal Current through Shelikof Strait
(Kendall et al., 1996).
A series of ichthyoplankton surveys were conducted in
1972 and from 1977 to 1999 (no data were collected in
1980) by the Alaska Fisheries Science Center (NOAA,
NMFS) in the western Gulf of Alaska (Tables 1 and
2). Data were used from 75 surveys. Surveys were con-
ducted from February to November; the most intensive
sampling was in April and May. Not all months were
sampled every year, and not all cruises surveyed the
same area. A 60-cm diameter bongo sampler with a
net mesh size of 333 or 505 ;<m was towed in a double
oblique fashion (from the surface to near bottom and
back to the surface) to collect samples used to examine
the geographic distribution and abundance of eggs and
larvae. Interannual variability in the abundance of
eggs and larvae in the Shelikof Strait spawning area
can vary as much as tenfold (S. Porter, unpubl. data),
but to increase sampling coverage of the study area.
650
Fishery Bulletin 103(4)
Table
1
The number of stations used each
year to assess monthl
v flat head
sole iHippoglossoides elassodon ) egg distribution in the west-
ern Gu
f of Alaska
Cruise
Apr
Apr
May
May
Jun
Jun
year
Feb
Mar
1-15
16-30
1-15
16-31
1-15
16-30 Jul Aug Sep Oct Nov
1972
;
27
40
—
—
— — — — — —
1977
—
—
—
—
—
—
—
— 11 48
1978
—
23
61
2
—
—
—
69 20 57 67 118
1979
48
40
—
—
—
58
—
— 18
1981
—
190
61
123
16
136
—
— _____
1982
—
—
55
28
—
62
—
— _____
1983
—
—
—
—
1
67
—
— _____
1984
—
2
63
66
28
—
—
_ _____
1985
—
109
87
28
62
135
54
— _____
1986
—
11
185
34
89
19
—
— _____
1987
—
—
177
83
—
59
—
15 4
1988
—
102
228
64
13
4
1
— _____
1989
—
—
128
69
132
47
1
— _____
1990
—
—
107
—
88
70
78
6
1991
—
—
90
150
119
97
—
— _____
1992
—
—
94
—
158
136
—
— _____
1993
—
—
96
—
141
90
24
— _____
1994
—
10
9
—
88
133
6
— _____
1995
1
5
—
—
—
98
—
— _____
1996
—
—
—
59
269
130
—
_ _____
1997
—
—
—
—
—
100
—
— _____
1998
—
—
—
—
72
128
—
26
1999
—
—
—
2
233
83
— _____
Total
49
492
1436
733
1320
1803
247
110 24 0 81 78 166
; No stations.
years were pooled for each month. Abundance did not
appear to affect the spatial distribution of eggs or lar-
vae; their distribution patterns were similar no matter
whether abundance was high or low. Months of highest
abundance (April, May, and June) were divided into
early to mid-month (days 1-15) and mid- to late month
(days 16-31). The area covered by the cruises was di-
vided into 50x50 km grid cells. Mean catch per cell was
calculated for each grid cell, averaging over all stations
falling within the cell. For the areas other than Shelikof
Strait, the number of stations per cell ranged from 1
to 10. The most intensive sampling was conducted in
the Shelikof Strait area, south to approximately 56°N
latitude. Cells in this area, depending on the month,
could have more than 100 stations within them. To ex-
amine larval drift, the center and ellipse (centroid) of
egg and larval abundance for early and late May 1994
and 1996 (two years with different flow regimes in She-
likof Strait) were calculated according to the methods
described in Kendall and Picquelle (1989).
The vertical distribution of eggs and larvae was exam-
ined from samples from four 1-m2 MOCNESS (multiple-
opening-closing-net and environmental sensing system)
tows. For each tow, 6 to 8 depth intervals were sampled
from near the sea floor to near the surface. The samples
were collected during peak spawning in 1991 (one tow
during day light ), 1993 (one tow during day light), and
1996 (two tows: 1996A conducted during the night, and
1996B during day light). Eggs collected in each depth
interval were categorized as early (stages 1-12), middle
(stages 13-15), and late stage (stages 16-21) according
to walleye pollock egg stages adapted from Blood et al.
(1994). The late stage was divided into two categories:
late A (stages 16-19) and late stage B (stages 20-21),
to indicate which eggs were closest to time of hatching.
Taking into account shrinkage in standard length due
to collection and preservation (Theilacker and Porter,
1995), larvae were divided into three size categories
based on development. Larvae <5 mm were classified
as recently hatched, larvae 5-6 mm as prefeeding or
first feeding, and larvae >6 mm as feeding, based not
only on size but also on the amount of yolk present, and
whether prey were visible in their gut. These catego-
ries were based on observations of fiathead sole larvae
Porter: Temporal and spatial distribution and abundance of eggs and larvae of Hippoglossoides elassodon
651
Table 2
The number
of stations
used each
year to
assess monthly
flathead
sole (Hippoglossoides
elassodon )
larval distribution
in the
western Gull
of Alaska.
Cruise
Apr
Apr
May
May
Jun
Jun
year
1-15
16-30
1-15
16-31
1-15
16-30 Jul
Aug
Sep Oct
Nov
1972
i
27
40
— —
—
— —
—
1977
—
—
—
—
—
— —
—
11
48
1978
60
2
—
—
—
69 20
—
57 67
118
1979
—
—
—
58
—
— —
—
18
—
1981
61
123
16
136
—
— —
—
— —
—
1982
55
28
—
62
—
— —
—
— —
—
1983
—
—
1
63
—
— —
—
— —
—
1984
63
66
28
—
—
— —
—
— —
—
1985
87
28
62
135
54
— —
—
— —
—
1986
185
34
89
19
—
— —
—
— —
—
1987
177
83
—
58
—
15 4
—
— —
—
1988
227
64
13
2
1
— —
—
— —
—
1989
128
69
132
34
1
— —
—
— —
—
1990
107
—
90
70
78
— —
—
6
—
1991
90
150
119
97
—
— —
—
— —
—
1992
94
—
158
136
—
— —
—
— —
—
1993
96
—
141
90
24
— —
—
— —
—
1994
4
—
89
133
6
— —
—
— —
—
1995
—
—
—
98
—
— —
—
— —
—
1996
—
59
273
130
—
— —
—
— —
—
1997
—
—
—
10(1
—
— —
—
— —
—
1998
—
—
72
128
—
26
—
— —
—
1999
—
—
6
233
83
— —
—
— —
—
Total
1434
733
1329
1782
247
110 24
0
81 78
166
7 No stations.
reared in the laboratory iS. Porter, unpubl. data). In the
laboratory, flathead sole larvae hatch with pigmented
eyes, three tail pigment bands, and an open mouth (S.
Porter, unpubl. data). Flathead sole larvae that were
collected from MOCNESS tows and that did not have
these features were classified as embryos (it was sus-
pected that handling during collection may have caused
some of the late stage eggs to prematurely hatch), and
their lengths were not included in the weighted mean
depth. For eggs and larvae, a weighted mean depth was
calculated for each stage or size category, and depths
were compared by using ANOVA and the Tukey HSD
multiple comparison test.
Results
Eggs
Geographic distribution and abundance Eggs were col-
lected as early as March but in small numbers (Figs. 2
and 3A). Most spawning began from early to mid-April
(Fig. 3B) near the Kenai Peninsula and then progressed
with time southwest into Shelikof Strait and along the
Alaska Peninsula. There are two main areas where peak
spawning (from early to mid-May) occurred: Shelikof
Strait and between the Shumagin Islands and Unimak
Island (Fig. 3C). In June, spawning generally declined in
these areas and was most intense around Kodiak Island
(3D). Eggs were collected as late as July (one station in
1978, on the eastern side of Kodiak Island).
Vertical distribution There were similar trends in the
vertical distribution of eggs among tows (Fig. 4). Abun-
dance peaked at about 20 to 35 m below the surface,
decreased at greater depth, and then slightly increased
below 125 m. Because the trend of the catches of the
tows were similar, we were able to increase sample size
in the depth intervals by pooling data from similar
depth intervals for further analyses. Eggs were pelagic
and most abundant near the surface (mean depth 43
±10 m) and at the deep sampling depths (mean depth
149 ±6 m); abundance was low in mid-water (Fig. 4).
Late-stage eggs (stages 16-21) dominated the depths of
652
Fishery Bulletin 103(4)
1 00
75 ■
50
25
■^H egg abundance
number oi stations
\
.
HI
' \
/ \
/ \
1
/ \
■
I
' \ ~u
1 1
\
/
l_
"
/
1
/
\
_l
\
/
\
/
, —
-■1
II
11
■-
m t r , — , —
Month
Jvjtt j\M S<#v O1* <W
1500
1000 =
500
Figure 2
The mean abundance of flathead sole {Hippoglossoides elassodon) eggs in the
western Gulf of Alaska during the year. Standard deviation and number of
stations used for each time period are also shown. The abundance in March
was very low (0.01 eggs/10 m2>.
high abundance. Early stage eggs were most abundant
in mid-water; they accounted for 79% of the total number
of eggs collected between 50 and 159 m depth. Sixty-
six percent of all eggs collected above 66 m depth were
middle- and late-stage A eggs. The largest numbers of
late-stage B eggs were found below 124 m depth, where
they accounted for 83% of all eggs collected. Mean egg
stage depth showed that as the eggs developed from the
early stages to the middle stages they rose toward the
surface (mean depth of the eggs changed from 54 to 28
m); then in the later stages of development the eggs sank
and hatched at depth. Late-stage B eggs were collected
significantly deeper (mean depth 90 ±37 m) than late-
stage A eggs (mean depth 35 ±7 m; ANOVA, P=0.007;
Tukey HSD multiple comparison test, P= 0.006).
Larvae
Geographic distribution and abundance Larvae were
found from early April to October, but they were most
abundant from mid-May to mid- June (Fig. 5). From
mid- to late April, larvae were most abundant near the
Kenai Peninsula (Fig. 6A), and as spring progressed
their abundance increased southwest along the Alaska
Peninsula (Fig. 6B). Peak abundance occurred during the
first two weeks of June in the southern portion of Shelikof
Strait (Fig. 6C). From mid- to late June larvae were most
abundant on the east side of Kodiak Island (Fig. 6D).
Although most of the surveys were conducted in this
area, it is possible that larvae may have been abundant
elsewhere in the study area during this time. From July
through October, only the area east of Kodiak Island was
surveyed, and larval abundance there was low.
Larval drift Satellite-tracked drifters released in May
1994 and drogued at 40 m indicated that the Alaska
Coastal Current flow was strong and moving to the
southwest — typical surface current flow for this area
(Bailey4). In May 1996, drifters showed that flow was
weak, disorganized and moving somewhat to the north-
east (Bailey et al., 1999). In early May 1994, very few
flathead sole larvae were collected; therefore the center
point of the flathead sole egg distribution was used to
infer the starting location of larval drift. Size-at-age
data have shown that the growth rate for flathead sole
larvae is 0.3 mm/day in Auke Bay, Alaska (Haldorson et
al., 1989). Using this growth rate, we determined that
larvae hatched in early May could have grown as much
as 6 mm in the 21 days between surveys. The size class
of larvae greater than 9 mm was assumed to include
larvae that had hatched from the eggs present in early
May. The location of the centers of distribution of the
early May eggs and late May larvae indicated that the
larvae had drifted southward over the continental shelf
(Fig. 7). In 1996 all the larvae collected in early May
were 7.1 mm and smaller (range 4.2 to 7.1 mm). The
area was surveyed 26 days later, and growth of about
8 mm could have occurred between surveys. For larvae
collected at the end of May, the size group longer than 12
mm was assumed to include the early May larval group.
The location of the centers of distribution of the early
May and late May larvae showed that the larvae were
retained at nearly the same location (Fig. 8).
4 Bailey, K. M. 2002. Personal commun. NOAA, Alaska
Fisheries Science Center, 7600 Sand Point Way NE, Seattle,
WA 98115.
Porter: Temporal and spatial distribution and abundance of eggs and larvae of Hippoglossoides elassodon
653
B
172° 168° 164' 160°
148" 144" 172' 168° 164° 160 156" 152' 148° 144"
168° 164° 160° 156
164° 160° 156" 152° 148 "W
C D
172° 168" 164" 160' 156 152° 148° 144" 172° 168° 164° 160° 156° 152° 148" 144"
N
60
A
58
56"
54°-
y^
*>t
>
III'
y
52°
early to mid-May
164° 160° 156° 152° 148°
168° 164° 160° 156° 152 148 W
egg abundance per 10 m2
ZD0 I !0-10
; 10-50 □ 50-100
5iiS 1 00-200
I > 200
Figure 3
The geographic distribution of flathead sole (H. elassodon) eggs in the western Gulf of Alaska
during the spawning season; I A) March, (B) early to mid-April, (C) early to mid-May, ID) early
to mid-June.
Vertical distribution There were similar trends in the
vertical distribution of larvae among tows (Fig. 9).
Abundance peaked at about 15 to 30 m below the sur-
face, then decreased, and larvae were collected from the
deepest sampling depth interval from one tow (1996A;
Fig. 9). Because the tows were alike, to increase sample
size in the depth intervals, we pooled data from simi-
lar depth intervals but from different tows for fur-
ther analyses. Larval abundance was highest near the
surface and at the deepest depths sampled (Fig. 9).
In Auke Bay, Alaska, flathead sole larvae migrated
vertically at night no more than 15 m, ending at 20 m
depth, and they were less aggregated (Haldorson et al.,
1993). This depth was much shallower than the depth
at which larvae and late-stage eggs were collected in
tow 1996A (sampling depth interval was 174-236 m).
Therefore the deep concentration of larvae in 1996 was
probably due to eggs hatching rather than to vertical
migration. The deepest sample comprised embryos and
larvae (the larvae, however, were too damaged to deter-
mine whether they were prefeeding or feeding larvae),
and samples collected above 100 m were a mixture
of embryos and prefeeding larvae (29%), and feeding
larvae (71%). The smallest larvae (<5 mm) were found
in deepest water (mean depth 166 ±32 m), and larger
larvae (>5 mm) were found in shallower water (above
about 60 m depth; ANOVA, P<0.001; Tukey HSD mul-
tiple comparison test, P<0.001). The size distribution of
the larvae indicated that soon after hatching they rise
to the surface to feed.
Discussion
Flathead sole inhabit the continental shelf of the North
Pacific Ocean, and the area used for the present study
o54
Fishery Bulletin 103(4)
Catch/10 m2
0 100 200 300 400 500 600
0 H
25 -
iP>< __-a
w_. „▼- -~ ~ . — — •
50 ■
It
L — ^ —
75 -
1 10° 1 F — o— 1991
w 125 -»
Q
*-^^_ —a— 1996A
150 •
i ~^^^^^^ t 1996B
175 -
\
200 -
V
225 J
Figure 4
The vertical distribution of flathead sole iH. elassodon) eggs collected
from four MOCNESS tows conducted in 1991, 1993, 1996 during peak
spawning. Symbols indicate the mean of the depth interval that the
samples were collected in.
40 -i
m^^m larva] abundance
number of stations
\
- 1500
30 -
\
z
E
o
~CD
£ 20 -
CD
"D
C
<
\
\
■ 1000 §
D"
o
s
■ 500 %
10 -
e*\^V^1^>*V^ ^ S°VV °* ^
Month
Figure 5
The mean abundance of flathead sole (H. elassodon) larvae in the western
Gulf of Alaska during the year. Standard deviation and number of stations
used for each time period are also shown. Abundance in early April and
October was very low, 0.06 and 0.11 larvae/10 m2, respectively.
contains the highest relative abundance of adult flathead
sole off the west coast of North America (Wolotira et
al.1). Generally, outside the study area the abundance
of adult flathead sole is low (Wolotira et al.1); therefore
these areas most likely had very little effect on the
abundance of eggs and larvae collected from within the
study area.
In the western Gulf of Alaska flathead sole spawn
in three main areas during the spring: near the Kenai
Peninsula, in Shelikof Strait, and in the area between
the Shumagin Islands and Unimak Island. Spawning
progresses in a southwesterly direction along the Alas-
ka Peninsula. Flathead sole in spawning condition are
abundant from March through May (Hirschberger and
Porter: Temporal and spatial distribution and abundance of eggs and larvae of Hippoglossoides elassodon
655
A B
172° 168° 164 160 156 152 148' 144 172= 168° 164 160 156 152" 148° 144
\
60
A
58
WJ-
56
54°
52°
mid- to late April
N
A
ErJ"""!
,# •
jp~&
#-'
II
'III'
|f l
mid- to late May
168° 164° 160° 156 152° 148" 168" 164 160° 156 152' 148'W
C D
172° 168: 164° 160° 156 152° 148° 144° 172° 168° 164 160= 156 152° 148° 144°
N
60
A
58
56
■■*;=.
54°
Willi
52°
early to mid-June
168° 164° 160° 156° 152° 148 168° 164° 160° 156° 152 148°W
egg abundance per 10 m;
0-10
] 10-50 ZZI 50-100
&£i 100-200
I =■ 200
Figure 6
The geographic distribution of flathead sole (H. elassodon) larvae in the western Gulf of Alaska
during months of the spawning season. (A) mid- to late April. (B> mid- to late May, (C) early
to mid-June, (D) mid- to late June.
Smith2), which correlates with the period when eggs
were collected in the present study. Peak spawning oc-
curred from early to mid-May. and by the end of June
spawning was nearing completion. Larval abundance
peaked from early to mid-June in the southern portion
of Shelikof Strait. In late July, late-stage flathead sole
larvae were the most abundant of larval fish collected
in the Gulf of Alaska between the Semidi Islands and
Unimak Island (Brodeur et al., 1995). Flathead sole
larvae have also been found on the east side of Ko-
diak Island during the summer (Kendall and Dunn.
1985).
Laboratory observations of the changes in density of
flathead sole eggs during development are inconsistent.
Results of one study showed that egg density decreased
throughout development to hatching (Alderdice and
Forrester, 1974). Another study found that up to 24
hours before hatching the eggs floated at the surface of
a container and then sank to the bottom and hatched
(Miller, 1969), indicating that density had increased
late in development. A field study of the vertical distri-
bution of Atlantic halibut iHippoglossus hippoglossus)
eggs in Norwegian fjords showed that later stage eggs
had a higher density (and were found deeper) than
earlier egg stages (Haug et al., 1986). Results from the
present study support the findings of Miller (1969). in
that the density of flathead sole eggs in the present
study appeared to increase near the time of hatch-
ing. For the larvae of both the arrowtooth flounder
(Atheresthes stomas) and Pacific halibut {Hippoglossus
stenolepis), small larvae were found deep and larger
sizes migrated towards the surface (Bailey and Pic-
quelle, 2002). In the present study, flathead sole larvae
had a similar vertical distribution pattern indicating
that after hatching in deep water they rise to near the
surface to feed.
656
Fishery Bulletin 103(4)
162° 161=
58° -
57°-
56°
55°-
160° 159°
158°
157° 156"
155"
154° 153°
strong southwesterly,
current flow
.A*
x^
,N%'
^
4-°
^
!
200 m
•58°
*cPv
200 f
"^
57°
■56°
55°N
161° 160 159° 158° 157°
1 56"
155° 154° 153°W
+ center of distributionof eggs in early May
+ center of distribution of larvae greater than 9 mm in late May
(assumed to include larvae that hatched from early May eggs)
Figure 7
The drift of flathead sole (H. elassodon) larvae in Shelikof Strait during
May 1994. Surface current flow was strong and southwesterly.
162° 161" 160" 159° 158° 157° 156° 155° 154°
153°
58°
57°
56°-
55°
.#
<**
weak northeasterly or l/4r'l
disorganized current fj; /[
flow s «*,
* <*.
■ *•><,
200 r
MB
200 r
161
160
159
158"
157°
156°
1 55"
154°
■57°
58
56°
55° N
153°W
+ center of distribution of all early May larvae (mean length 5.71 ±0.71 mm)
■^ center of distribution of late May larvae greater than 12 mm
(assumed to include larvae present in early May)
Figure 8
The drift of flathead sole (H. elassodon I larvae in Shelikof Strait during May
1996. Surface current flow was disorganized, or weak, and to the northeast.
Porter: Temporal and spatial distribution and abundance of eggs and larvae of Hippoglossoides elassodon
657
Catch/10 m2
0
10
20
30 40
0 1
25 \^
... T
50 Tgf—
1/b
75?/
E
100 i
CD
Q
125 I
150 H
—a— 1991
— •— 1993
— o— 1996A
t 1996B
175 '
200 -
225 -
Figure 9
The vertical distribution
of flathead sole IH. elassodon) larvae
collected from fo
it MOCNESS tows conducted in 1991. 1993,
and 1996 during peak sp
awning. Symbols
indicate the mean of
the
depth interva
1 that the samples were
collected in.
Some species of flatfish spawn offshore (e.g., ar-
rowtooth flounder and Pacific halibut, Bailey and Pic-
quelle, 2002), but the present study has shown that
flathead sole spawn on the continental shelf. Flathead
sole nursery areas have been found to be in the bays
of the Alaska Peninsula and Kodiak Island (Norcross
et al., 1999), and it is crucial that the larvae remain
on the shelf near their nursery areas. Changes in egg
density may be a mechanism for retaining flathead sole
larvae on the shelf. For arrowtooth flounder and Pacif-
ic halibut larvae in the western Gulf of Alaska, it has
been suggested that deep water currents (100-400 m
depth in sea valleys and in troughs in the continental
shelf) transport these larvae from the offshore areas
where they hatch to their nearshore nurseries (Bai-
ley and Picquelle, 2002). By sinking when they are
nearing hatching, flathead sole eggs that have drifted
southwesterly (i.e. away from nursery areas) with the
surface currents can be brought back (along with newly
hatched larvae) toward inshore juvenile nursery areas.
Alternatively, the act of sinking as they near hatching
may be a way for newly hatched larvae to avoid preda-
tion by keeping them out of the surface waters where
they are likely to encounter predators. The physical
environmental conditions of Shelikof Strait may also
serve to retain flathead sole larvae on the shelf. In
May 1994 when the Alaska Coastal Current flow was
strong and to the southwest, larvae drifted southward
but remained on the continental shelf. In May 1996
when the flow was weak, disorganized, and moving
somewhat to the northeast, the larvae remained at vir-
tually the same location for the entire month because
surface current flow in Shelikof Strait was weakened
and reversed because of anomalous atmospheric con-
ditions. Under both flow regimes larvae remained on
the continental shelf in southern Shelikof Strait. Ed-
dies may also be an important retention mechanism
for flathead sole larvae because entrainment in one
of these could slow drift. Under typical conditions in
Shelikof Strait (i.e., strong southwesterly current flow),
eddies frequently occur and they drift slower than
the water surrounding them (Kendall et al., 1996).
They can also remain nearly stationary for two weeks
(Schumacher et al., 1993). Both biological and environ-
mental factors may work together to retain flathead
sole larvae on the continental shelf and keep them
near their nursery areas.
Acknowledgments
I would like to thank Debbie Blood and Angie Lind
for determining developmental stages of flathead sole
eggs, and Susan Picquelle for assistance with egg
and larval distribution charts. Kevin Bailey and Jeff
Napp provided helpful comments on an early draft of
this manuscript. Two anonymous reviewers offered
improvements. This research is contribution FOCI-
0475 to NOAA's Fisheries-Oceanography Coordinated
Investigations.
Literature cited
Alderdice, D. R, and C. R. Forrester.
1974. Early development and distribution of the flathead
sole (Hippoglossoides elassodon). J. Fish. Res. Board
Can. 31:1899-1918.
658
Fishery Bulletin 103(4)
Bailey, K. M., N. A. Bond, and P. J. Stabeno.
1999. Anomalous transport of walleye pollock larvae
linked to ocean and atmospheric patterns in May 1996.
Fish. Oceanogr. 8:264-273.
Bailey, K. M., and S. J. Picquelle.
2002. Larval distribution of offshore spawning flatfish
in the Gulf of Alaska: potential transport pathways and
enhanced onshore transport during ENSO events. Mar.
Ecol. Prog. Ser. 236:205-217.
Bailey, K. M., P. J. Stabeno, and D. A. Powers.
1997. The role of larval retention and transport fea-
tures in mortality and potential gene flow of walleye
pollock. J. Fish Biol. 51 Isuppl. A):135-154.
Blood, D. M., A. C. Matarese, and M. M. Yoklavich.
1994. Embryonic development of walleye pollock, Ther-
agra chalcogramma, from Shelikof Strait, Gulf of
Alaska. Fish. Bull. 92:207-222.
Brodeur, R. D., M. S. Busby, and M. T. Wilson.
1995. Summer distribution of early life stages of wall-
eye pollock, Theragra chalcogramma, and associated
species in the western Gulf of Alaska. Fish. Bull.
93:603-618.
Haldorson, L.. A. J. Paul, D. Serritt, and J. Watts.
1989. Annual and seasonal variation in growth of larval
walleye pollock and flathead sole in a southeastern
Alaska bay. Rapp. P.-V. Reun. Cons. Int. Explor. Mer
191:220-225.
Haldorson, L., M. Prichett, A. J. Paul, and D. Ziemann.
1993. Vertical distribution and migration offish larvae
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101:67-80.
Haug, T., E. Kj0rsvik, and P. Solemdal.
1986. Influence of some physical and biological factors on
the density and vertical distribution of Atlantic halibut
Hippoglossus hippoglossus eggs. Mar. Ecol. Prog. Ser.
33:207-216.
Kendall, A. W., Jr., and J. R. Dunn.
1985. Ichthyoplankton of the continental shelf near
Kodiak Island Alaska. NOAA Tech. Rep. NMFS 20,
89 p.
Kendall, A. W., Jr., and S. J. Picquelle.
1989. Egg and larval distributions of walleye pollock
Theragra chalcogramma in Shelikof Strait, Gulf of
Alaska. Fish. Bull. 88:133-154.
Kendall, A. W., Jr., J. D. Schumacher, and S. Kim.
1996. Walleye pollock recruitment in Shelikof Strait:
applied fisheries oceanography. Fish. Oceanogr. 5
(suppl. 11:4-18.
Matarese, A. C., A. W. Kendall Jr., D. M. Blood, and B. M. Vinter.
1989. Laboratory guide to early life history stages of
northeast Pacific fishes. NOAA Tech. Rep. NMFS 80,
652 p.
Miller, B. S.
1969. Life history observations on normal and tumor-
bearing flathead sole in East Sound, Orcas Island
(Washington). Ph.D. diss., 131 p. Univ. Washington,
Seattle, WA.
Norcross, B. L., A. Blanchard, and B. A. Holladay.
1999. Comparison of models for defining nearshore flat-
fish nursery areas in Alaskan waters. Fish. Oceanogr.
8:50-67.
Rose, C. S.
1982. A study of the distribution and growth of flathead
sole (Hippoglossoides elassodon). M.S. thesis, 59 p.
Univ. Washington, Seattle, WA.
Schumacher, J. D., P. J. Stabeno, and S. J. Bograd.
1993. Characteristics of an eddy over a continental
shelf: Shelikof Strait, Alaska. J. Geophys. Res. 98:
8395-8404.
Theilacker, G. H., and S. M. Porter.
1995. Condition of larval walleye pollock, Theragra
chalcogramma, in the western Gulf of Alaska assessed
with histological and shrinkage indices. Fish. Bull.
93:333-344.
Watts, J. D.
1988. Diet and growth of first-year flathead sole (Hip-
poglossiodes elassodon) in Auke Bay, Alaska. M.S.
thesis, 80 p. Univ. Alaska, Juneau, AK.
659
Abstract — With a focus on white mar-
lin {Tetrapturus albidus), a concurrent
electronic tagging and larval sampling
effort was conducted in the vicinity
of Mona Passage (off southeast His-
paniola), Dominican Republic, during
April and May 2003. Objectives were
1) to characterize the horizontal and
vertical movement of adults captured
from the area by using pop-up satel-
lite archival tags (PSATs); and 2) by
means of larval sampling, to investi-
gate whether fish were reproducing.
Trolling from a sportfishing vessel
yielded eight adult white marlin and
one blue marlin (Makaira nigricans);
PSAT tags were deployed on all but
one of these individuals. The excep-
tion was a female white marlin that
was unsuitable for tagging because
of injury; the reproductive state of its
ovaries was examined histologically.
Seven of the PSATs reported data
summaries for water depth, tempera-
ture, and light levels measured every
minute for periods ranging from 28 to
40 days. Displacement of marlin from
the location of release to the point of
tag pop-up ranged from 31.6 to 267.7
nautical miles (nmi) and a mean dis-
placement was 3.4 nmi per day for
white marlin. White and blue marlin
mean daily displacements appeared
constrained compared to the results
of other marlin PSAT tagging stud-
ies. White marlin ovarian sections
contained postovulatory follicles and
final maturation-stage oocytes, which
indicated recent and imminent spawn-
ing. Neuston tows (/i=23) yielded 18
istiophorid larvae: eight were white
marlin, four were blue marlin, and
six could not be identified to species.
We speculate that the constrained
movement patterns of adults may
be linked to reproductive activity
for both marlin species, and, if true,
these movement patterns may have
several implications for management.
Protection of the potentially impor-
tant white marlin spawning ground
near Mona Passage seems warranted,
at least until further studies can be
conducted on the temporal and spatial
extent of reproduction and associated
adult movement.
Movements and spawning of
white marlin (Tetrapturus albidus)
and blue marlin (Makaira nigricans)
off Punta Cana, Dominican Republic
Eric D. Prince1
Robert K. Cowen2
Eric S. Orbesen'
Stacy A. Luthy2
Joel K. Llopiz2
David E. Richardson2
Joseph E. Serafy'
1 Southwest Fisheries Science Center
National Marine Fisheries Service
75 Virginia Beach Drive
Miami, Florida 33149
E-mail address (for E D Prince): eric pnnce@noaa gov
2 Rosenstiel School of Marine and Atmospheric Science
Division of Marine Biology and Fisheries
University of Miami
4600 Rickenbacker Causeway
Miami, Florida 33149
Manuscript submitted 24 June 2004
to the Scientific Editor's Office.
Manuscript approved for publication
31 March 2005 by the Scientific Editor.
Fish. Bull. 103:659-669 (2005).
White marlin {Tetrapturus albidus)
and blue marlin (Makaira nigricans)
are widely distributed throughout the
tropical and temperate waters of the
Atlantic Ocean and adjacent seas; the
former species is endemic only to the
Atlantic Ocean (Mather et al., 1975).
Genetic analyses and tag recapture
data have indicated that each spe-
cies has a single Atlantic-wide popu-
lation (ICCAT, 1998). Several stock
assessment indicators indicate that
the white marlin population has been
severely overfished for several decades
(ICCAT, 2001, 2002). The Atlan-
tic blue marlin stock is also heavily
over-exploited, but to a lesser degree.
The main source of adult mortality
for both stocks is the multinational
offshore longline fisheries that, in the
process of targeting tunas (Scombri-
dae) and swordfish (Xiphias gladius),
land the marlins as bycatch (ICCAT,
2002, 2003).
Despite their economic and ecologi-
cal value, little is known about the
biology and ecology of Atlantic mar-
lins (Prince and Brown, 1991). This
is especially true regarding the repro-
ductive biology of white marlin and
adult movement patterns in spawning
areas (Baglin, 1979; Mather, 1975;
White Marlin Status Review Team1;
SEFSC2). Long-term (i.e., >40 years)
commercial (Goodyear, 2003) and rec-
reational (i.e., Cabeza de Toro Billfish
Tournament, Graves and McDowell,
1995; Casilla3) fishing records indi-
cate that, every spring, white marlin
are present in relatively high numbers
off the southeastern coast of Hispan-
iola. This observation, coupled with
1 White Marlin Status Review Team.
2002. Atlantic White Marlin Status
Review Document, 49 p. Report to
National Marine Fisheries Service, South-
east Regional Office, 263 13th Avenue,
St. Petersburg, FL 33701-5511.
2 SEFSC ( Southeast Fisheries Science Cen-
ter). 2004. Atlantic Billfish Research
Plan. National Marine Fisheries Ser-
vice, Southeast Fisheries Science Center,
75 Virginia Beach Drive, Miami, FL
33149-1003.
3 Casilla, W. 2003. Personal commun.
Club Nautico de Santo Domingo, Calle
Juan Baron Fajardo #2, Ensanche
Iantini, Santo Domingo, Dominican
Republic.
660
Fishery Bulletin 103(4)
anecdotal information about gravid fish, prompted the
present examination of adult movements in a potentially
important, but as yet unconfirmed, spawning location.
The present study was conducted off Punta Cana,
Dominican Republic, during April and May 2003. Objec-
tives were 1) to characterize the horizontal and vertical
movement of adult white marlin captured from the area
using pop-up satellite archival tags (PSATs) and 2) to
investigate by larval sampling, whether marlin were
reproducing at this location.
Materials and methods
Deployment of PSAT tags on adult marlin was conducted
from a 17-m charter fishing vessel by using standard
trolling gear (9/0 long-shaft J hooks) and dead bait.
Wildlife Computers Inc. (Redmond, WA) PAT 3 model
tags were used. This tag allows the user to program
pop-up date, sampling interval, criteria for premature
release, bin demarcations for sampling temperature and
pressure (depth), as well as transmission and memory
priorities. These tags were programmed to sample depth
(pressure), temperature, and light once every minute
and the depth and temperature records were summa-
rized into histograms at 3-hour intervals. A pressure-
activated mechanical detachment device was also used
which severs the monofilament tether at a depth of about
1500 m — well before the 2000 m depth at which the tag
is crushed and disabled. This feature helps prevents data
loss in the event of fish mortality.
All PSAT tags were rigged similarly according to
methods described by Graves et al. (2002). Billfish han-
dling and tagging procedures and associated devices
reviewed by Prince et al. (2002a) were also used. The
target area for tag placement was about 4 to 5 cm ven-
tral to the dorsal midline, adjacent to the first several
dorsal spines. An effort was made to insert the anchor
through the dorsal midline, pterygiophores, and connec-
tive tissue to a depth just short of the anchor exiting
the opposite side of the fish. In addition, a conventional
streamer tag (series PS) was placed in the fish well
posterior to the PSAT tag, according to standard pro-
cedures (Prince et al., 2002a).
Two devices were used during tagging which tend
to reduce stress in captured fish and to aid in proper
tag placement. The first was a "snooter" (a wire snare
housed in a 1.5-m PVC tube), which secures to the up-
per bill and allows the tagger to maintain control of the
fish while its head remains beneath the water during
the tagging procedure (Prince et al., 2002a). The second
was a small hook "gaff" (a long shaft 9/0 hook with
point and barb removed) to manipulate the position
of the fish in relation to the tagging vessel. Captured
fish were resuscitated for 3 to 15 minutes, depending
on their apparent state of exhaustion, by moving the
vessel ahead at two to three knots while maintaining
control of the fish with the snooter. State of exhaustion
was inferred from coloration, fight time, and signs of
sluggish movement.
One white marlin died during tagging and was re-
tained for examination of its reproductive status. Whole
or quarter transverse sections of ovarian tissue were
preserved in 10% formalin. Preparation for histologi-
cal analysis followed McBride et al. (2002). Histologi-
cal determination of spawning activity was based on
oocyte classification and the presence of postovulatory
follicles (Wallace and Selman, 1981; Hunter and Mace-
wicz, 1985; Hunter et al., 1992).
Once adult marlins were located for tagging, neuston
sampling was conducted from the same fishing vessel
with methods similar to those reported by Serafy et
al. (2003). In the present study, ten-minute daytime
tows were performed with two neuston nets. Both nets
had 1000-fim mesh and were attached to 1 mx0.5 m or
2 mx 1 m rectangular aluminum frames. Water volume
filtered was measured with a mechanical flow meter;
station coordinates and water column depth measure-
ments were obtained by using a hand-held geographical
positioning system and depth sounder. Neuston collec-
tions were made along a series of transects that covered
the general area of the recreational fishery for white
marlin at this location (Fig. 1). The neuston samples
were initially stored in 150 proof white rum. Upon
returning to the laboratory (i.e., within 24-96 hours)
they were transferred to 95% ethanol. Billfish larvae
were sorted from the samples and measured by using
Image Pro image analysis software (Image Pro Plus,
version 4.5, Media Cybernetics, Inc. Silver Spring, MD).
Larval identification was conducted by using restriction
fragment length polymorphism analysis of the nuclear
MN32-2 locus following the methods of McDowell and
Graves (2002).
Results
Seven white marlin and one blue marlin were tagged
with PSAT tags off Punta Cana, Dominican Republic,
between April 23-24 and May 14-17 2003 (Table 1).
All but two tags were programmed to pop-up after 30
days; the exceptions were 40-day deployments for one
white marlin and one blue marlin. One of eight PSATs
(deployed on a white marlin) failed to transmit data and
one white marlin died prior to release (see below) from
hook-related injuries. The displacements of the six white
marlin from the original point of release ranged from
31.7 to 267.7 nmi (58.7 to 495.8 km), whereas the dis-
placement for the blue marlin was 219.3 nmi (406.2 km.
Table 1, Fig. 2). Displacements per day for white marlin
ranged from 1.1 to 7.2 nmi (average of 3.4 nmi). Cor-
responding daily displacement for the one blue marlin
was 5.48 nmi (Table 1).
The minimum and maximum depth and temperatures
monitored for the seven PSAT-tagged marlin during
the 30- and 40-day deployments showed that on most
days, marlin visited depths 2IOO m (Fig. 3). Minimum
temperatures ranged from 16.8° to 20.6°C, whereas the
maximum temperatures ranged from 28.2° to 30.0°C. In
all cases, the minimum depths for each fish monitored
Prince et al.: Movements and spawning of Tetrapturus albidus and Makaira nigricans
661
18.7 N
18.8 N
186N
18.4 N
18.2 N
18.5 N
68.3 W
68.1 W
68.6 W 68.4 W 68.2 W 68.0 W
Longitude
x-
18.5 N
68.3 W 68.1 W
Longitude
Figure 1
(A) Western part of Mona Passage off Punta Cana, Dominican Republic, showing the general area of the
recreational fishery for white marlin [Tetrapturus albidus, rectangle) and larval sampling (oval); (B)
April 23-24 sampling stations and (C) May 13-17 sampling stations. X = stations with no billfish larvae.
□ = stations with white marlin larvae, A = stations with blue marlin [Makaira nigricans) larvae,
• = stations with unidentified larval istiophorids. Larger markers indicate two billfish in sample; smaller
markers indicate one billfish in sample. Depth contours are in meters.
during April and May were recorded at the surface,
whereas maximum depths ranged from 184 to 368 m
(Fig. 3). In one case (i.e., PC-WHM01), the minimum
and maximum temperatures and depths converged at
the surface, indicating constrained vertical movement
for this individual. However, in the majority of tracks
there was a clear separation of minimum and maximum
temperature and depth (e.g., PC-WHM02, Table 1),
indicating that active vertical movements were made
each day. Only one of the transmitting tags appeared
to pop-up prematurely (PC-WHM01, Fig. 3). This tag
disengaged from its white marlin host during a deep
dive (368 m) after 28 days at large (two days early). Al-
though the fate of this fish cannot be determined, death
is a distinct possibility. In general, all marlin spent a
high proportion of the time in which they were moni-
tored in the upper 25 m and at temperatures a28°C. For
example, marlin spent from 50% to 60% of the time in
the first depth bin (0 to 25 m) and about 60% to 75% of
their time in the 28° to 30°C temperature bin (Fig. 4).
Both marlin species made dives down to 100-200 m or
more on a fairly consistent basis but generally stayed at
these depths less than 10% of the time (Fig. 4).
One female adult white marlin, measuring 157 cm
lower jaw fork length, could not be resuscitated during
pop-up satellite tagging, presumably because of damage
caused by a hook that penetrated the stomach. Based
on length-weight conversion equations (Prager et al.,
1995), the estimated weight of this fish was 21.6 kg
(47.2 pounds). The histologically examined ovaries con-
tained distinct postovulatory follicles, indicating that
spawning likely occurred within the previous 24 hours
(Fig. 5, upper panel). In addition, imminent spawning
(likely within the following 12 hours) was indicated by
662
Fishery Bulletin 103(4)
20 N
:-.fi W
60 W
0 60 120
240
360
4B0
■ Nautical Miles
Figure 2
Displacement vectors (from point of tag release to point of tag pop-up in nautical
miles, nmi) for six white marlin {Tetrapturus albidus) (solid lines, 31.7-268 nmi)
and one blue marlin (Makaira nigricans) (dashed line, 219 nmi) released off Punta
Cana, Dominican Republic, bearing pop-up satellite archival tags during April and
May 2003. Tags were programmed for either 30- or 40-day deployments.
Table 1
Summary of pop-up satellite archival tag information for seven white marlin iTetrapturus albidus, WHM) and one blue marlin
iMakaira nigricans, BUM I released from recreational gear in the vicinity of Punta Cana, Dominican Republic, April and May
2003. Net displacements are given in nautical miles (nmi) and kilometers (km). Compass direction (in degrees) indicates the
bearing from point of tag release to point of first transmission. Dashed line indicates that no value was available.
Tag number
Days
monitored
Estimated
weight
pounds (kg)
Location of
release
Location
of first
transmission
Compass
direction
Net
displacement
nmi (km)
Displacement
per day
nmi (km)
PC-WHM-01
28
40(18.14)
18.49°N, 68.38:W
19.17°N, 68.26°W
9.52°
41.21 (76.32)
1.47(2.72)
PC-WHM-02
31
40(18.14)
18.60:N, 68.27°W
19.56°N, 66.58°W
58.87°
111.87(207.18)
3.61(6.69)
PC-WHM-03
31
50(22.68)
18.49°N, 68.37°W
19.14°N, 66.25°W
71.81°
126.76(234.76)
4.09(7.57)
PC-WHM-04
30
35(15.88)
18.69'N, 68.27°W
18.16°N, 68.28°W
181.03°
31.68(58.67)
1.06(1.96)
PC-WHM-05
30
50(22.681
18.70'N, 68.29°W
17.81°N, 66.70°W
120.11°
105.22(194.87)
2.84(5.26)
PC-WHM-06
0
50(22.68)
18.29°N, 68.13W
—
—
—
—
PC-WHM-07
37
60(27.22)
18.60°N, 68.30W
14.12°N, 68.38°W
181.00°
267.73 (495.84)
7.24(13.41)
PC-BUM-01
40
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Prince et al : Movements and spawning of Tetrapturus albidus and Makaira nigricans
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Figure 3
Minimum and maximum depth and temperature per 3-hour time intervals for six white marlin (Tetrapturus albidus)
and one blue marlin {Makaira nigricans) monitored with pop-up satellite archival tags. Tags were programmed to deploy
for either 30 or 40 days, April and May 2003, in the vicinity of Punta Cana, Dominican Republic. WHM = white marlin,
BUM = blue marlin.
664
Fishery Bulletin 103(4)
White marlin
Blue marlin
0-25 26-50 51-75 76-100 101-125 126-150 151-175 176-200 201-225 226-250 >250
Depth bins (m)
White marlin
Blue marlin
0<12 12-14 14-16 16-18 18-20 20-22 22-24 24-26 26-28 28-30 30-32 32-60
Temperature bins (m)
Figure 4
Total time at depth (upper panel) and time at temperature (lower panel) for white
marlin iTetrapturus albidus) and blue marlin (Makaira nigricans) tagged with
popup satellite archival tags during April and May 2003. Tags monitored marlin
for 30 and 40 days.
some oocytes exhibiting an early state of final oocyte
maturation, including migration of the nucleus towards
the oocyte periphery and yolk coalescence (Fig. 5, lower
panel).
A total of 23 neuston net tows were made in the gen-
eral area of the recreational fishery from 23 April to
17 May 2003 (Fig. 1). These tows yielded 18 larval
billfishes. Molecular identification was successful for
12 larvae: 8 white marlin and 4 blue marlin (Table 2).
Half of the white marlin larvae were 3-4 mm standard
length (SL), two were 4-5 mm SL, one was 6.2 mm SL,
and one was 12.1 mm SL (Fig. 6). The one positively
identified blue marlin larva captured in April was 4.6
mm SL; the remainder taken in May were 3.5 mm SL,
5.1 mm SL, and 10.4 mm SL. Sizes of the six unidenti-
fied billfish larvae ranged from 3 to 6 mm SL (Fig. 6).
Discussion
Larval sampling with neuston tows and histological
analyses of adult ovaries confirmed spawning activity
of white marlin in the vicinity of Punta Cana during
April and May (2003). Co-occurrence of larval blue
marlin and white marlin in samples indicated that the
two species share this spawning location. White and
blue marlin spawning activity in the vicinity of Punta
Cana, as indicated from the data presented in our study,
Prince et al
Movements and spawning of Tetrapturus albidus and Makairo nigricans
665
also coincided in time and space with
the fishing activity of the recreational
white niarlin fishery that has operated
each spring at this location for over 40
years. From PSAT tag data, adult white
and blue marlin caught at this time and
in this area appeared to exhibit similar
vertical and horizontal movement pat-
terns in terms of time at depth, time
at temperature, average horizontal dis-
placement per day, net horizontal dis-
placement, and direction of dispersion
(compass heading).
Movements
Average displacement per day is one
possible measure to characterize daily
horizontal movement activity. We exam-
ined this metric in other PSAT stud-
ies on marlin and compared them with
our results (Fig. 7). Graves et al. (2002)
monitored eight blue marlin with PSAT
tags caught off Bermuda in July 2000 for
periods of 5 days each and reported net
displacement vectors ranging from 7.8 to
26.4 nmi/day (mean displacement for the
eight fish was 17.5 nmi/day). Kerstetter
et al. (2003) also monitored blue marlin
during the summer months with PSAT
tags in the northwest Atlantic (for 5 and
30 days) and found that displacements
ranged from 15.1 to 39.2 nmi/day (mean
for six fish was 22.9 nmi/day). Net dis-
placement findings (17.5 and 22.9 nmi/
day), presumably for blue marlin spawn-
ing times (summer months) from these
two studies were roughly 5 to 6.5-fold
higher than the average displacements
for white marlin reported in our present
study (about 3.3 nmi/day) and were 3 to
4-fold higher than the average displace-
ment for the one blue marlin monitored
in our study (Fig. 7). A recent report
(Graves and Horodysky4) has provided
displacement movements of white marlin
monitored with PSAT tags for 5 to 10 day
periods from three different areas in the
Northwest Atlantic during May (Punta
Cana, Dominican Republic), August-
September (U.S. Mid-Atlantic waters),
and November (La Guaira, Venezuela)
2002. Only the work in Punta Cana was
conducted during the presumed spawn-
ing season for white marlin. Average
displacements for these areas were 9.6
Figure 5
Upper panel. A postovulatory follicle (POF), advanced yolked oocyte
(AYO), and follicle (F) are shown in section of gonad from a female
white marlin (Tetrapturus albidus) sampled off Punta Cana, Dominican
Republic, 16 May 2003. The presence of POFs indicates recent spawning
(likely within 24 hours). Lower panel. The labeled oocyte has begun
final oocyte maturation, as indicated by the migration of the nucleus
(Nu) to the periphery and yolk coalescence (YC). Both of these steps are
among the series of events initiated hormonally that occur just prior to
spawning (likely within 12 hours).
4 Graves, G. E., and A. Z. Horodysky. 2002. Progress
report. Use of pop-up satellite archival tags to study sur-
vival and habitat utilization of white marlin released from
the recreational fishery, 34 p. Virginia Institute of Marine
Science, College of William and Mary, Gloucester Point, VA
23062-1346.
666
Fishery Bulletin 103(4)
Table 2
Summary of neuston tow information for larval collections of istiophorids in the vicinity of Punta Cana,
April and May 2003. "Unidentified istiophorids" refers to specimens for which molecular identification was
Dominican Republic,
unsuccessful.
2003 dates
Number
of tows
Volume
filtered (m3)
Number of
positive tows
Number
(length range)
of white marlin
Number
(length range)
of blue marlin
Number
(length range)
of unidentified
istiophorids
23-24 April
13-17 May
Total
11
12
23
9400
8413
17,813
7
5
12
7
(3.45-12.16 mm)
1
(6.20 mm)
8
1
(4.6 mm)
3
(3.49-10.45 mm
4
2
(3.98-5.28 mm)
4
) (3.25-4.4 mm)
6
nmi/day for Punta Cana; 9.4 nmi/day for the U.S. Mid-
Atlantic region; and 8.2 nmi/day for La Guaira Bank
(Fig. 7). Thus, the average white marlin displacements
found by Graves and Horodysky were 2 to 3-fold higher
than those reported in the present study. Black marlin
(Makaira indica, Gunn et al., 2003) and striped marlin
(Tetrapturus audax, Domeier et al., 2003) monitored
mostly outside of spawning times and areas had displace-
ments per day 2 to 4-fold higher than those in the pres-
ent study. Therefore, reproductively active white marlin
and blue marlin monitored in our study (30- or 40-day
deployments) appeared to have more constrained average
displacements per day than those in other studies where
similar PSAT technology was used to monitor marlin in
and outside of their respective spawning seasons.
Further PSAT-based research, with extended monitor-
ing durations (i.e. at least s3-4 months) on white mar-
lin and other billfish species in their spawning areas,
will be necessary to clarify the causative factors for
these findings. Interpretation of our findings also needs
to be tempered by the fact that the displacement vectors
(minimum straight line distances) used to characterize
movements in this study were limited to beginning and
end points. In theory, daily estimates of light-based
geolocation would provide improved resolution of small-
scale movement patterns. However, there is little sci-
entific agreement (Musyl et al., 2001; Hill and Braun,
2001) as to the methods and validity of daily tracks
generated from highly variable light levels, particularly
for wide ranging species near the equator.
Although we present no evidence that the horizontal
movement patterns of blue marlin (other than possi-
bly constrained displacements) reported in our study
are directly related to spawning activity, the possibil-
ity that white marlin could show fidelity to a spawn-
ing area cannot be ruled out. For example, Pepperell
(1990) examined conventional tagging results off east-
ern Australia and reported that the periodic peaks in
return frequency were possibly indicative of black mar-
lin returning to the spawning ground as part of their
annual migration cycle. The multidirectional pattern
of blue and white marlin displacements found in the
present study was very similar to the pattern reported
by Graves et al. (2002) for blue marlin monitored with
PSAT tags for five days off Bermuda. The relatively
short-term duration of PSAT tags in both studies (5-40
days) generally precludes detection of directed seasonal
horizontal movement patterns (including potential an-
nual fidelity to a spawning area) as described by Mather
et al. (1975), Pepperell (1990), and Ortiz et al. (2003).
Detailed accounts of temperature and depth prefer-
ences of electronically monitored white marlin have
been rare and those that do exist are limited to very
short (<;ten days) monitoring durations (Block et al.,
1990; Horodysky et al., 2003; Graves and Horodysky4).
We found that white marlin monitored with PSATs for
periods of 28-40 days spent the majority of time in the
upper 25 m of the water column at temperatures of
28-30°C. Similar findings were found for this species by
Graves and Horodysky4 and Horodysky et al. (2003), as
well as for blue marlin, black marlin, and striped mar-
lin reported by Graves et al. (2002); Kerstetter et al.
(2003); Gunn et al. (2003); and Domeier et al. (2003).
However, we could not directly address the depth at
which spawning occurs in our study from PSAT results,
other than to note the preference of adults for, and
capture of larvae in, surface waters. Empirical data on
the depth of spawning for istiophorids are not available,
although anecdotal evidence indicates that some species
may spawn in surface waters (black marlin observations
by Harvey, personal commun.5).
Spawning
Prior studies of gonads have indicated that white marlin
spawn in the northwest Atlantic during the spring
(Baglin, 1977, 1979; de Sylva and Breder, 1997). Spring
aggregations of white marlin have been the target of the
Cabeza de Toro billfish tournament off Punta Cana for
over 40 years (Casilla3), and the sampling of larvae in
s Harvey, G. C. McN. 2004. Personal commun. 102 Webster
Drive, P.O. Box 10499 APO, Grand Cayman Island, Cayman
Islands, British West Indies.
Prince et al.: Movements and spawning of Tetropturus albidus and Makaira nigricans
667
4- n
3-
D white marlin
■ blue marlin
n unidentified istiophond
2-
: i
r
n
1 1 [
6-7 7-8 8-9
Length (mm)
9-10 10-11 11-12 12-13
Figure 6
Length-frequency distribution for larval white marlin
(Tetrapturus albidus), blue marlin, [Makaira nigricans),
and unidentified istiophorids collected in the vicinity
of Punta Cana. Dominican Republic, April and May
2003.
the present study is the first to provide direct evidence
of springtime spawning activity in this area. Histologi-
cal assessment of the captured female ovarian tissue is
consistent with the premise that the adult white mar-
lins in the aggregation that we located during fishing
and PSAT tagging operations participated in spawning
activity. This contention is strengthened by the presence
of very small, presumably very young, white (and blue)
marlin larvae in the same location.
The presence of larvae is the most direct way of docu-
menting that a spawning event has actually occurred.
This is particularly relevant to highly mobile species,
such as billfishes, that can cover large distances in a
short time (Prince and Brown, 1991). Serafy et al. (2003)
used a similar approach to identify blue marlin spawning
grounds in the area of Exuma Sound, Bahamas. In their
neuston collections, 90 blue marlin, no white marlin, and
three sailfish larvae were captured. Because Serafy et
al., (2003) sampled during the entire month of July, it
seems possible that larval sampling in Exuma Sound
took place after the majority of white marlin spawning
had already occurred. Subsequent neuston sampling of
Bahamian waters yielded white marlin larvae in Exuma
Sound in April and in the Old Bahama Channel and
just east of Long Island in March, but no blue marlin
during these months (D. E. Richardson and S. A. Lu-
thy, unpubl. data). Extensive sampling of the Straits
of Florida (SOF) over four years resulted in sporadic
captures of white marlin larvae in May and June. Blue
marlin was the more common larval marlin in the SOF
and was captured from June to September (S. A. Luthy,
unpubl. data). In the present study, white marlin larvae
were twice as abundant in larval samples as blue marlin
larvae (which had been captured earlier in Punta Cana)
than in other areas where blue marlin larvae had been
found. These results are consistent with reports that
white marlin is primarily a spring-time spawner but
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Figure 7
Mean displacement per day (in nautical miles) for blue
marlin iMakaira nigricans), white marlin {Tetrapturus
albidus), black marlin iMakaira indica). and striped
marlin {Tetrapturus audax) monitored with pop-up sat-
ellite archival tags by Gunn et al. (2003) [Australia],
Domeier et al. (2003) [Mexico], Graves et al. (2001)
[Bermuda], Kerstetter et al. (2003) [Northwest Atlantic],
Graves and Horodysky4 [Punta Cana, Dominican Repub-
lic, La Guaira, Venezuela, U.S. Mid-Atlantic region],
and present study. In all studies, displacements were
computed from the point of tag release to the point of
first transmission from PSAT tags and are not meant to
infer tracks taken by the fish. Means are accompanied
by ± one standard deviation for each species identified as
follows: blue marlin (BUM, stippled bar), white marlin
(WHM, empty bar), black marlin ( BLK, solid bar), and
striped marlin (STM, cross hatched bar).
mark an expansion of the July to October spawning
season reported for blue marlin in the North Atlantic by
Erdman (1968) and de Sylva and Breder (1997).
668
Fishery Bulletin 103(4)
For blue marlin larvae <6.2 mm SL, Serafy et al.
(2003) found problems with estimating age from size
with the larval growth equations reported by Prince et
al. (1991). Serafy et al. (2003) suggested an exponen-
tial growth curve with an assumed size-at-hatching
of 2.5 mm SL yielded more realistic larval age values
for this growth stanza (<6.2 mm SL). Application of
the Serafy et al. (2003) growth model to the larval
blue marlin collected in the present study indicates
that larvae 3 mm SL were 2 days old, 4-mm-SL larvae
were 5 days old, and 5-mm-SL larvae were over 7 days
old. It seems possible that blue and white marlin have
similar size-at-hatching and growth rates at this early
stage of development. Given this assumption, the fact
that half of the white marlin larvae (4 out of 9) and a
third of the blue marlin larvae sampled in this study
were 3-4 mm long (i.e., only a few days old) indicates
that spawning activity was taking place in the same
general area where these larvae were captured and
where the recreational fishery for these species was
being pursued. This statement may not hold true for
the larval marlin in our collections over 4 mm SL
because increases in size and age add increased un-
certainties concerning possible spawning locations.
Providing a more precise estimate of spawning loca-
tion was beyond the scope of our study, although we
would expect that the upstream spawning locations
(assuming minimal mobility of larvae) of both marlin
species to be a function of the prevailing currents
and oceanographic features in the Punta Cana area
and the elapsed time between the spawning event and
sample collection. Future research should focus on a
more rigorous and comprehensive estimate of spawning
location for all sizes and ages of larvae. This would
require both a significant increase in the spatial and
temporal larval sampling scheme, as well as direct
aging methods for both species and sizes of marlin
larvae collected.
Implications for managment and future research
The current stock status of Atlantic white marlin indi-
cates that biomass is only at about 12% of the level nec-
essary to maintain maximum sustainable yield (MSY)
and continues to decline (ICCAT, 2002). The stock has
been estimated to be incurring fishing mortality at
a rate about eight times higher than the population
can sustain to produce MSY (ICCAT, 2002). Although
the Atlantic blue marlin stock is also considered to be
overexploited, its status is not as precarious as that of
white marlin (ICCAT, 2001). The characterization of
adult movements and larval distribution in a potentially
important spawning area is seen as a necessary "first
step" toward improved management and rebuilding of
depressed Atlantic billfish stocks, possibly with gear
restrictions (e.g., use of circle hooks. Prince et al., 2002b;
Horodysky and Graves, 2005). Improved management
seems particularly relevant in the area of Punta Cana
because the target of the 40-year-old Cabeza de Toro
tournament is, and probably always has been, a repro-
ductively active aggregation of white marlin. In light of
the ICCAT recommendation to reduce mortality on the
overexploited marlins from all Atlantic fisheries (ICCAT,
2002), a shift to catch-and-release requirements for the
white marlin recreational fishery off Punta Cana, and
the use of circle hooks during the spring months, may
be suitable options. In terms of spawning, there is an
obvious need for more detailed spatiotemporal informa-
tion on the distribution of marlin reproduction and on
the identification of nursery areas to help managers
make informed decisions regarding conservation of the
resource. In addition, more fine-scale data on adult
movement patterns in relation to horizontal and verti-
cal use of the water column, including identification of
spawning depth, are necessary.
Acknowledgments
This work was made possible through Cooperative
Research and Recover Protected Species Candidate
Plus Program funds of the National Marine Fisheries
Service and additional support from The Billfish Founda-
tion and the Lmiversity of Miami, Center for Sustainable
Fisheries, Billfish Research Initiative. We thank Noretta
Perry at the Florida Fish and Wildlife Commission's
Fish and Wildlife Research Institute for histological
slide preparations.
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1991. Estimating age and growth of young Atlantic
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2002a. In-water conventional tagging techniques devel-
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Prince, E. D., M. Ortiz, and A. Venizelos.
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Luthy.
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670
Abstract — We summarize the life his-
tory characteristics of silvergray rock-
fish (Sebastes brevispinis) based on
commercial fishery data and biologi-
cal samples from British Columbia
waters. Silvergray rockfish occupy
bottom depths of 100-300 m near the
edge of the continental shelf. Within
that range, they appear to make a
seasonal movement from 100-200 m
in late summer to 180-280 m in late
winter. Maximum observed age in
the data set was 81 and 82 years
for females and males, respectively.
Maximum length and round weight
was 73 cm and 5032 g for females
and 70 cm and 3430 g for males. The
peak period of mating lasted from
December to February and parturi-
tion was concentrated from May to
July. Both sexes are 50% mature by
9 or 10 years and 90% are mature by
age 16 for females and age 13 years
for males. Fecundity was estimated
from one sample of 132 females and
ranged from 181,000 to 1,917,000
oocytes and there was no evidence
of batch spawning. Infection by the
copepod parasite Sarcotaces aretieus
appears to be associated with lower
fecundity. Sexual maturation appears
to precede recruitment to the trawl
fishery; thus spawning stock biomass
per recruit analysis (SSB/R) indicates
that a F50rr harvest target would cor-
respond to an F of 0.072, 20% greater
than M (0.06). Fishery samples may
bias estimates of age at maturity
but a published meta-data analysis,
in conjunction with fecundity data,
independently supports an early age
of maturity in relation to recruitment.
Although delayed recruitment to the
fishery may provide more resilience
to exploitation, managers may wish
to forego maximizing economic yield
from this species. Silvergray rockfish
are a relatively minor but unavoid-
able part of the multiple species trawl
catch. Incorrectly "testing" the resil-
ience of one species may cause it to
be the weakest member of the species
complex.
Life history characteristics for silvergray rockfish
(Sebastes brevispinis) in British Columbia waters
and the implications for stock assessment
and management
Richard D. Stanley
Allen R. Kronlund
Fisheries and Oceans, Canada
Pacific Biological Station
Nanaimo, British Columbia, Canada V9T 6N7
Email address (lor R D Stanley) stanleyngipac dfo-mpo.gc ca
Manuscript submitted 6 April 2004
to the Scientific Editor's Office.
Manuscript approved for publication
31 March 2005 by the Scientific Editor.
Fish. Bull. 103:670-684 (2005).
Silvergray rockfish (Sebastes brevispi-
nis) range from the Gulf of Alaska to
central Baja California (Love et al.,
2001) and are a minor part of the trawl
and hook-and-line fisheries catch from
northern Washington to the Gulf of
Alaska (Alaska Fisheries Information
Network.1 Pacific Fisheries Informa-
tion Network,2 Pacific Biological Sta-
tion3). Coastwide commercial landings
averaged 2600 metric tons (t) from
1990 to 2000, and about two-thirds
of these landings came from British
Columbia (B.C.) waters, mostly from
bottom trawling. Hook-and-line land-
ings are the most common type in
Alaskan waters (mostly from south-
eastern Alaska) and have averaged
less than 20 t. Combined annual
trawl landings from Washington and
Oregon peaked at over 1000 t from
1977 to 1979, declined to an average
of 210 t from 1990 to 1998, and since
1999 have further declined to negli-
gible levels.
The B.C. bottom trawl fishery is
currently managed through individual
vessel quotas (IVQs) whereby a fixed
proportion of the annual quota for
each stock is allocated to each quota-
holder. Because silvergray rockfish
are currently assessed and managed
as four separate stocks (Fig. 1: Pacific
Marine Fisheries Commission areas
3CD, 5AB, 5CD, and 5E), a vessel
may possess up to four area-specific
quotas for silvergray rockfish. All bot-
tom trawlers on the outer coastal wa-
ters of British Columbia are required
to have an independent observer on
the vessel. Once vessels have reached
their IVQ for one area and species,
and have exhausted their limited op-
portunity to temporarily lease quota
from other lease-holders, they must
cease all bottom trawling even though
they may still have IVQ remaining
for other species in that area.
The quotas for silvergray rockfish
are relatively small compared with
those for other species in the fishery;
thus fishermen can fully fill their sil-
vergray rockfish IVQs as they target
other species. However, if silvergray
rockfish become difficult to avoid
through increased abundance or avail-
ability, or if the silvergray rockfish
quota is reduced, even though catch
rates remain constant, they become
a nuisance in that fishermen cannot
fulfill their IVQs for other species
without exceeding their silvergray
rockfish IVQ. Therefore, the quotas
for minor species, such as silvergray
rockfish, now assume more impor-
tance than would be gained from
their landed value. Finally, the en-
actment of species-at-risk legislation
in Canada has led to the requirement
1 Alaska Fisheries Information Network.
2000. AKFIN Support Center, 612 W
Willoughby Ave. Suite B. Juneau, Alaska
99801.
2 Pacific Fisheries Information Network.
2000. Pacific States Marine Fisheries
Commission, 205 SE Spokane Street,
Suite 100, Portland, Oregon 97202.
3 Pacific Biological Station. 2000. Un-
publ. data. Fisheries and Oceans Can-
ada. Nanaimo, British Columbia V9T
6N7, Canada.
Stanley and Kronlund: Life history characteristics for Sebastes brevispmis
671
136°W 134°W 132°W 130'W 1283W 126°W 12-f:W 1225W
54>N
52°N'
50'N'
Moresby Trough
Reed Trough
__^.Sea Otter Trough
5 -_ V^Sfefe- '
48'N-
0 50 100 200
i Kilometers
3CD
Site A 1 Meter Station
Figure 1
Coastal waters of British Columbia showing boundaries of silvergray rockfish [Sebastes
brevispinis) stocks, trawl capture locations of silvergray rockfish (black dots) for
1996-2000, mooring site for the oceanographic metering of temperature at-depth
(Al meter station), and 500-. 1000-, and 1500-m depth contours.
to assess and protect the status of any species affected
by fishing, regardless of its commercial value.
Research on silvergray rockfish is an example of an
area that has been neglected owing to the lack of eco-
nomic importance of this species in the commercial
fisheries. Even the data that are available have been
collected incidentally during fishing operations target-
ing other species or during generic sampling programs.
Nevertheless, we show in the present article that these
data, in conjunction with detailed commercial catch and
effort data, can be used to provide insight into the biolo-
gy, assessment, and management of silvergray rockfish.
This article summarizes this information and provides
estimates of the various life history parameters needed
for stock assessment. Some of the estimates represent
updates from previous work, but we also for the first
time present estimates of fecundity and maturity at age
and size. Using these values, we also derive a target
reference point.
Materials and methods
Data sources
Data for silvergray rockfish were collected from B.C.
waters during port sampling, at-sea observer programs,
and research cruises from 1977 through 2000. These
data reside at the Pacific Biological Station, Nanaimo,
B.C., Fisheries and Oceans, Canada. As of June 2000,
the database contains information on over 40,000 speci-
mens. Of these specimens, we aged 13,671 representing
most of the specimens from which we obtained otoliths,
in addition to documenting length, sex, and maturity
stage. We, also used catch observations from the com-
mercial trawl observer program from 1996 through
2000.
Habitat
Preferred depth distributions of silvergray rockfish were
inferred from analyzing catch rates in the commercial
data. We used all bottom tows that contained silvergray
rockfish and included tow duration. Bottom depth of the
tows was determined as the midpoint between beginning
and end depth of the tows. We applied a nonparametric
locally weighted regression smoothing function (LOESS)
(Cleveland, 1979) to log-CPUE observations grouped by
20-m intervals.
Depth of peak catch rates by month were compared
with temperature-at-depth estimates based on data col-
lected from the site Al meter station on the west coast
of Vancouver Island (Fig. 1: 48°32"N by 126°12"W).
These data, collected from 1986 to 2000 (excluding El
Nino years), were taken from 35-, 100-, 175-, and 400-m
depths. The temperatures at fixed depths were then
672
Fishery Bulletin 103(4)
Table 1
Field classification of gonad maturity stages for silvergray rockfish ^Sebastes brevispinis
Region Science Branch. Fisheries and Oceans, Canada.
) used by the Groundfish Section, Pacific
Female ovaries
Male testes
1 Immature (translucent, small, color can be clear, amber, yellow, or pink)
Immature (translucent, string-like)
2 Developing (small, opaque or translucent, can be yellow, usually light pink)
Developing (swelling, brown-white)
3 Developed (eggs usually white or cream white, can be yellow or orange-yellow)
Not used
4 Fertilized (large, cream or orange-yellow eggs, translucent)
Developed (large, white, easily broken)
5 Embryos or larvae present (includes eyed eggs)
Ripe (running sperm)
6 Spent (flaccid, red, a few larvae may be present)
Spent (flaccid, creamy-brown, some milt
present but not free-flowing)
7 Resting (moderate size, firm, red-grey, red-grey, pink, or purple to almost black)
Resting (ribbon-like, small brown)
converted through interpolation to provide depth at
specific temperatures (Hourston1).
Aging and growth determinations
Ages were determined by using the otolith burnt-section
technique (MacLellan, 1997) with a minor modification.
A survey directed at studying juvenile rockfish in 1991
captured two 17-cm silvergray rockfish. An examination
of these otoliths indicated that the previous application
of the method had incorrectly assigned the first annulus
to the age count in specimens. Therefore, some previ-
ously aged specimens were probably under-estimated by
one year (MacLellan5). A faint first annulus is consis-
tent with the late spring to mid-summer parturition of
silvergray rockfish that appears to preclude significant
summer growth in its first year. The method was modi-
fied in August of 1992, and we added one year to all
previously aged specimens in the data set.
Most (85%) of the otoliths were aged by one reader.
The remaining 15% were aged by two readers to moni-
tor consistency. If there was a disagreement, the two
readers agreed on a "resolved" age.
Age and length data were fitted to a generalized
growth model (Schnute, 1981) (Appendix 1). Growth
dimorphism was calculated as the ratio of the mid-
points of fork length (maximum observed length minus
minimum observed length) between males and females
(Lenarz and Wylie Echeverria, 1991).
by tracking the proportions in each maturity stage by
month. Lacking histological confirmation for character-
izing maturity, we followed the suggestion of Wylie Ech-
everria (1987) and used only those specimens collected
from the reproductive or gestation period of March to
August. Within this subset, we grouped female stages 1
and 2 as immature, and stages 3-7 as mature. Because
most mature females exhibited fertilized eggs by March,
we assumed that females with small, nondeveloped
ovaries in March through August would not complete
parturition in the same calendar year.
We assumed that stage 1, during which testes are
translucent and string-like, was the only male imma-
ture stage. Subsequent stages 2 and 4-7 were grouped
as mature (stage 3 was not used in the field). The pro-
portion of stage-2 males (in relation to males in other
mature stages) decreased rapidly during the mating
season (September- January) indicating that many of
the specimens classified as stage 2 would become ma-
ture within the same calendar year. We emphasize,
however, that without histological support for these
classifications, the assumptions of maturity-at-age or
maturity-at-length remain tentative.
The estimated proportions of maturity at age were
computed by fitting a generalized additive model (GAM)
to the binomial maturity classes (0=immature, ^ma-
ture) (Hastie and Tibshirani, 1990). A logistic link with
a binomial error structure was applied, as well as a
second-degree nonparametric LOESS smoother.
Reproductive maturity
Maturity stage was classified macroscopically in the field
(Table 1). We examined the annual reproductive cycle
4 Hourston, R. 2003. Personal commun. Institute of Ocean
Sciences. Fisheries and Oceans Canada. 9860 West Saanich
Road, P.O. Box 6000. Sidney, British Columbia. V8L 4B2, Canada.
5 MacLellan S. 2000. Personal commun. Pacific Biological
Station, Fisheries and Oceans Canada. Nanaimo, British
Columbia. V9T 6N7, Canada.
Fecundity
Fecundity was estimated from a single sample (??=132)
of females captured by commercial bottom trawl in Sea
Otter Trough in April 1989 (Fig. 1). The catch was stored
in refrigerated seawater for four days prior to sampling.
Sampling was stratified by length to obtain a range of
ages, and from each fish we obtained measurements of
fork length, gonad weight, and somatic weight. We also
collected otoliths and counted the number of cysts con-
Stanley and Kronlund: Life history characteristics for Sebastes brevispims
673
taining the copepod parasite Sarcotaces arcticus in
the coelomic cavity. All the oocytes of all the female
gonads appeared to be in a prefertilized condition.
The ovaries that were used for fecundity esti-
mation were fixed and stored in modified Gilson's
solution (Leaman. 1988) and shaken weekly for one
year. Fecundity estimates were derived gravimetri-
cally (Leaman, 1988). Each ovary was drained and
filtered through stacked sieves (100-750 urn); each
clump was broken manually if possible. The ovar-
ian membranes and connective tissue were teased
away from eggs and discarded. The oocytes were
transferred to millipore filters, vacuumed-dried for
15 minutes, and the oocytes and filter were weighed
to 0.01 g. Four subsamples of approximately 0.1 g
and 1000 oocytes were weighed to 0.0001 g. Total
fecundity was estimated for each fish by multiply-
ing total vacuum-dried ovary weight by the mean
density of the four samples. Fecundity relationships
against age. weight, and length were examined with
a generalized additive model (GAM) (Hastie and
Tibshirani, 1990). An identity link with a Gauss-
ian error structure was used in each case. Ovaries
to be used for histological examination were fixed
in Smith's formal dichromate solution and then
stored in 39c formaldehyde. Histology samples were
imbedded, sectioned, mounted, stained with Harris'
haematoxylin, and counterstained with alcoholic
eosin (Gray, 1954).
Spawning stock biomass per recruit (SSB/R)
We combined estimates of instantaneous natural mor-
tality rate (M) of 0.06 and partial recruitment from
Stanley and Kronlund (2000) with our estimates of the
proportion mature at age and predicted fecundity at age
in order to derive estimates of the expected population
fecundity of unfished populations (Appendix 2). The
impact of fishing on spawning stock biomass per recruit
(SSB/R) can then be explored by comparing the ratio of
predicted cumulative fecundity of a cohort under exploi-
tation to predicted cumulative fecundity under no fishing
pressure (Gabriel et al., 1989; Clark, 1991).
Results
Habitat
The commercial data indicated that the highest catch
rates and most of the landings of silvergray rockfish
come from the edge of the continental shelf or along the
edges of deep troughs (Fig. 1). These tows were typically
conducted in bottom depths of 100 to 300 m, although
silvergray rockfish have been reported from tows with
mid-point bottom depths greater than 580 m. Monthly
catch rates by depth indicate a seasonal trend wherein
peak catch rates are highest in depths of 180-280 m in
March and April, but highest in depths of 100-200 m
in September and October (Fig. 2).
Feb Mar Apr May Jun Jul
Month
Aug Sep Oct Nov Dec
Figure 2
Silvergray rockfish (Sebastes brevispinis) seasonal depth
distribution. The solid lines show the median (heavy line)
and 25th and 75th percentiles (thin lines) for the number
of silvergray rockfish catch observations (observed commer-
cial trawl sets) at depth, between 1996 and 2003. The dots
indicate the estimated depth at 7.2°C ±1 standard deviation
(dotted line l.
If the shift in catch rates correctly indicates sea-
sonal movement, and the interpolated temperatures at
site Al characterize bottom temperatures on the coast,
together they indicate that silvergray rockfish tend to
maintain peak densities at bottom water temperatures
centered around 7.2°C (Fig. 2). The move to shallower
water in the late spring, however, seems to lag behind
the cooling of shallower water that results from sum-
mer upwelling (Thomson6). The return to deeper water
in the fall is coincident with the warming of water at
greater depths.
The cohabitants of silvergray rockfish were also in-
ferred from commercial trawl observations. For these
data, we selected tows with at least 50 kg of silvergray
rockfish. Silvergray rockfish represented 12.8% of the
total catch of over 36,000 t (Table 2). The dominant
species by weight in these tows were Pacific ocean
perch (Sebastes alutus), arrowtooth flounder (Atheres-
thes stomias), yellowmouth rockfish (S. reedi), yellowtail
rockfish (S. flavidus), redstripe rockfish (S. proriger),
and canary rockfish (S. pinniger). The species most
frequently co-occurring in the tows were arrowtooth
flounder, lingcod (Ophiodon elongatus), spiny dogfish
6 Thomson, R. 2003. Personal commun. Institute of Oceans
Sciences, Fisheries and Oceans Canada. 9860 West Saanich
Road, P.O. Box 6000. Sidney, British Columbia V8L 4B2,
Canada.
674
Fishery Bulletin 103(4)
Table 2
Fish species captured in
1996-99 B.C. bottom trawl tows that contained silvergray rockfish (Sebastes brei
ispinis).
% of total catch
°!c frequency
Common name
Species
(36.489,773 kg)
(10,820 tows)
Silvergray rockfish
Sebastes brevispinis
12.8
100.0
Arrowtooth flounder
Atheresthes stomias
13.0
77.2
Lingcod
Ophiodon elongatus
2.8
65.1
Spiny dogfish
Squalus acanthias
2.5
58.4
Yellowtail rockfish
Sebastes flavidus
11.3
57.4
Canary rockfish
Sebastes pinniger
5.4
55.2
Redstripe rockfish
Sebastes paueispinis
1.3
54.0
Pacific cod
Gadus maerocephalus
1.1
53.7
Pacific halibut
Hippoglossus stenolepis
0.6
48.2
Redstripe rockfish
Sebastes proriger
7.2
47.3
Rex sole
Errex zachirus
0.8
46.6
Sablefish
Anoplopoma fimbria
0.6
46.2
Spotted ratfish
Hydrolagus colliei
0.6
43.7
Pacific ocean perch
Sebastes alutus
13.9
40.4
Yellowmouth rockfish
Sebastes reedi
12.7
39.2
Dover sole
Microstomas pacificus
1.1
36.0
Petrale sole
Eopsetta Jordan i
0.4
34.5
Redbanded rockfish
Sebastes babeoeki
0.9
33.7
English sole
Pleuronectes vetulus
0.5
28.3
Widow rockfish
Sebastes entomelas
3.9
27.1
Greenstriped rockfish
Sebastes elongatus
0.3
27.0
Longnose skate
Raja rhina
0.3
26.0
Others
6.2
—
(Squalus acanthias), yellowtail rockfish, canary rock-
fish, redstripe rockfish, and Pacific cod (Gadus maero-
cephalus). All of these species were observed in more
than 50% of the selected tows.
The cohabitants varied with depth. Tows conducted in
depths less than 200 m tended to include lingcod, dog-
fish, canary rockfish, and yellowtail rockfish, whereas
catches from greater than 200 m were dominated by
arrowtooth flounder, Pacific ocean perch, redstripe rock-
fish, and yellowmouth rockfish. Fishermen report that
silvergray rockfish are typically found over relatively
"hard" bottom, often in proximity to bottom that was
not trawlable because it was too rough. They are rarely
caught in midwater trawls.
Aging and growth estimates
The maximum ages observed in Canadian samples were
81 and 82 years for females and males, respectively.
The corresponding ages at the 99.9% percentiles were
76 and 77 years.
Although we assumed that our aging methods for
silvergray rockfish provided unbiased estimates of age,
agreement between readers was poor. Agreement to ±1
year was 60-80% for ages less than 20 years and then
declined with age.
The standard errors of the growth parameter esti-
mates show that there is a significant, albeit modest,
difference in growth rates; females grow faster and
to a larger size (Table 3, Fig. 3). Maximum observed
length was 73 and 70 cm for females and males, respec-
tively. We estimated the length-weight relationship for
females and males separately and combined from 476
total specimens (Table 3, Fig. 3). The ratio of the mid-
point lengths for males and females was 97.2 (Table 4),
indicating little sexual dimorphism.
Maturation cycle
The field maturity observations were congruent for
females and males (Fig. 4). Testes began developing (stage
2) in September and October and were large and swollen
by November and December (stage 4) (Fig. 4). January
and March testes were in the late stages of mating (stage
6), whereas from April through August testes appeared
to be in a resting phase for males (stage 7). The few
observations of large swollen testes with running sperm
(stage 5) occurred from October through February. The
Stanley and Kronlund: Life history characteristics for Sebastes brevispmis
675
Table 3
Growth and fecundity parameter est
mates and standard errors for si
lvergrav
rockfish [Sebastes brevi
spinis 1 1 see Append
ix 1 for
parameter definitions).
Equation
Parameter
Females
Males
Combined
Estimate
SE
Estimate
SE
Estimate
SE
Length-at-age
Vi
48.985
0.048
47.887
0.041
48.468
0.034
y-2
60.628
0.015
56.108
0.091
57.719
0.083
a
0.0581
0.002
0.0708
0.002
0.0709
0.002
b
1.0000
1.000
1.000
T>
15.000
15.000
15.000
T2
60.000
60.000
60.000
Length/Weight lln scale)
a
-4.000
0.137
-2.506
0.411
-3.634
0.157
P
2.924
0.034
2.547
0.105
2.833
0.040
Fecundity/Somatic weight
(In scale)
a
P
3.014
1.367
0.572
0.073
Fecundity/Length
a
P
-3.454
4.2833
1.007
0.251
Table 4
Comparison of silvergray rockfish iSebastes brevispinis) fork length
(1991) (groups 2-4).
ratio (group 1) with
results from Lena
rz and Echevarria
Species group
Deep
(>125m)
Shallow
(<125m)
All rockfish
species combined
1 Silvergray rockfish (present study) Fork length ratio
0.97
2 Water-column species Number of species
Standard length ratio
12
0.88
5
0.91
17
0.89
3 Demersal species Number of species
Standard length ratio
5
0.95
12
0.98
17
0.97
4 All rockfish species combined Number of species
Standard length ratio
17
0.90
17
0.96
34
0.91
peak period of mating is presumably December to Febru-
ary. One sample of 109 males, collected in March 1988,
was recorded entirely as maturing. This one sample
accounted for all but two records of stage-4 males col-
lected in March and, therefore, contradicted the results
of 20 other March samples, totalling 364 specimens.
Although we found no evidence of a recording error, we
suggest that these specimens were misclassified and were
probably recovering instead of developing males.
The developing ovaries (stages 2 and 3), observed
from January to April, shifted to fertilized through to
resting stages (stages 3-7) in April to June. Eyed lar-
vae were commonly observed from May to July although
a few individuals with eyed larvae were observed in
February, August, and October.
We examined whether there was a relationship be-
tween the size of the female and the timing of par-
turition by categorizing July observations as either
"parturition not completed" (stages 3-5) or "parturition
completed" (stages 6-7) (Fig. 5). The results indicated
a dome-shaped relationship with length wherein it ap-
pears that a higher proportion of the smaller and larger
females had not completed parturition. There were too
few observations from June to examine the transition in
more detail or to examine whether timing varied with
latitude within B.C. waters.
Age observations from the commercial fishery indicate
that both sexes are 50% mature at about 10 years of
age and over 90% are mature at age 16 for females,
and age 13 for males (Table 5, Fig. 6). However, the
analysis was limited by the lack of young fish in the
samples. For example, there were only five 8-year old
and thirteen 9-year old females in the data set. Com-
parison of the age at maturity and partial recruitment
at age indicates that silvergray rockfish mature prior
to recruitment (Table 5, Fig. 7).
676
Fishery Bulletin 103(4)
A
70 ■
60 "
^MSm
^>r
50 ■
:••.«'"
40 -
l*r+ ■ ■'•
30 "
20 "
1 —
-i — ■
Female
— i 1 —
B
70 "
60 "
\ i-
E
o
50 ■
-■Bv^
3
jJJJWWT-':
c
_l
40 ■
30 "
20 "
Male
— i 1 1 —
0 20 40 60
Age class
80
20
40 60 80
Age class
c
70 '
60 "
50 ■
_...-— —
E
u
c
_l
40 "
30 J
Both sexes
Female
Male
20 "
— i 1 1 1 —
5000 "
D
+
+
4000 "
§
3
3000 ■
'^3¥
a
2000 "
1000 -
o -
S*
20
40 60
Age class
80
20 30
40 50 60
Length (cm)
70
Figure 3
Observed lengths at age for (A) female and (B) male silvergray rockfish
tSebastes brevispinis). Predicted length-at-age for (C) females, males, and both
sexes combined; and (D) weight at length for females ("+") and males ("o").
Fecundity and stock-assessment-parameter estimates
The total number of large oocytes ranged from 181,000
to 1,917,000 (Fig. 8). A general linear model (GLM)
treatment of log fecundity against log somatic weight
and age indicated that age was not a significant variable
after accounting for somatic weight. Although size is a
better predictor of fecundity than age, we also provide
the predicted fecundity with age (Table 5 1 for subsequent
calculation of SSB/R.
We examined histological cross-sections from 11 ma-
ture specimens in the sample. All appeared to be late
in the process of vitellogenesis, the late stage 3 of Wylie
Echeverria (1987) or stage V of Bowers (1992). The oo-
cytes in each ovary were either large, with diameters
ranging from 300 to 600 ftm or smaller than 150 f.i.
There was little variation within ovaries in the dia-
meter of the larger eggs (± 50 f<m) and thus no evidence
of additional maturing batches.
The SSB/R analysis indicated that an instantaneous
fishing mortality (F) that reduces the SSB/R to 50% of
what could be expected with no fishing, (F60% ) equates
to an F of 0.072 (Fig. 9).
Discussion
Data sources
The opportunistic assemblage of samples collected from
the commercial fishery and research cruises has two
implications if one attempts to draw inference from these
Stanley and Kronlund: Life history characteristics for Sebostes brevispims
677
data. The first is that while the overall
number of samples and specimens is large,
they are not equally distributed over time
and space. Thus, for example, we cannot
examine whether larger or older males
complete the mating earlier in the season
because of the lack of winter samples. The
second implication is that the results are
influenced by the fishing practices. This
is particularly the case for inferring depth
distribution from trawl catches.
Habitat
Silvergray rockfish appeared to be concen-
trated in the 100-300 m depth interval.
Their distribution tended to overlap the
distribution of "slope" and "shelf" assem-
blages of Weinberg (1994) that were based
on survey results from northern California
to southern British Columbia. The dis-
tribution also agrees with observations
from research surveys in B.C. waters (Nag-
tegaal, 1983). Peak catch rate at depth
indicates an annual depth migration, noted
by fishermen, of about 80 m. The timing
and range of this movement is considered
by fishermen to be typical for rockfish
(Dickens7).
The movement appears correlated with
temperature. Bottom temperature increases
in winter owing to downwelling (Fig. 2)
(Thomson6). Thus, the shift to shallower
water in the summer means that peak
catch rates throughout the year are found
in waters centered at just over 7°C. The
apparent seasonal movement has obvious
implications for stock assessments. Sur-
veys designed to track abundance among
years need to be consistent with respect to
their timing and depth. More importantly,
those who attempt to use CPUE to moni-
tor abundance must consider changes in
the distribution of fishing effort by season
among years.
There has been no research on the larg-
er scale movements of silvergray rockfish.
Barotrauma induced during traditional
trawl or hook-and line-fishing precludes
tag-recapture studies, although recent work
on other rockfish indicates there is poten-
tial for tagging in situ (Schrope, 2000;
Starr et al., 2001). Nor do we know of any
genetic studies on silvergray rockfish to
determine stock structure, although the
A
o e . O
o
o
oooooo
o
O
o OOo
0
o
O
.
O o • ■
o
° 0 o o
10
12
7 ■
6 ■
B ° • ooOOO° • • •
O O O o o •
b ■
4 ■
2 ■
. o oO
o o . . . . OO o -
1 ■
...
0,0
0.7 O
0.5 O
0.3 O
0.1 °
10 12
Month
Figure 4
The proportion of each maturity stage within each month for (Al female
and (B) male silvergray rockfish (Sebastes brevispinis) (see Table 1 for
definition of stages represented by the numbers on the y axis).
Dickens, B. 2000. Personal commun. 1678
Admiral Tryon Boulevard. Qualicum Beach,
British Columbia VOR 2T0, Canada.
1.0 -
o o
0.9 -
r-
a 0.8 "
° V°°°
CD
<D
3 °-7"
"to
c 06-
o
R 0.5 -
o
0.4 -
3^o
-~~~~~^ o
o
o
O
ouoo
350
300
250
200
150
100
0.3 -
50
1 1 1 1 1 1
40 45 50 55 60 65
Length (cm)
Figure 5
The proportion of all mature (stages 3-7, see Table 1) female silver-
gray rockfish (Sebastes brevispinis) in July samples that were clas-
sified as spent or resting (stages 6-7) against length. The number
of observations is shown in the histogram.
678
Fishery Bulletin 103(4)
Table 5
Summary of the predicted values of life history parametei
ment values from Stanley and Kronlund (2000).
s at age for
silvergray rockfish
(NA: not applicable), partia
recruit-
Age
(years)
Both sexes
Females
Males
Partial
recruitment
Length
(cm)
Weight
<g>
%
mature
Fecundity
(106)
Length
(cm)
Weight
(g)
er
mature
1
0.000
NA
NA
0.000
NA
NA
NA
0.000
2
0.000
NA
NA
0.000
NA
NA
NA
0.000
3
0.000
NA
NA
0.010
NA
NA
NA
0.000
4
0.000
NA
NA
0.020
NA
NA
NA
0.000
5
0.000
NA
NA
0.041
NA
NA
NA
0.000
6
0.000
NA
NA
0.080
NA
NA
NA
0.103
7
0.000
NA
NA
0.143
NA
NA
NA
0.195
8
0.000
42.680
1158
0.235
NA
42.386
1138
0.330
9
0.000
44.750
1233
0.352
NA
43.348
1205
0.492
10
0.002
45.698
1307
0.479
NA
44.245
1270
0.647
11
0.151
46.593
1379
0.599
NA
45.080
1332
0.770
12
0.283
47.437
1448
0.700
0.496
45.858
1391
0.855
13
0.401
48.233
1516
0.776
0.536
46.583
1448
0.909
14
0.505
48.985
1582
0.833
0.576
47.258
1502
0.942
15
0.596
49.694
1645
0.875
0.616
47.887
1553
0.961
16
0.674
50.363
1707
0.906
0.656
48.473
1602
0.974
17
0.742
50.994
1766
0.928
0.696
49.019
1648
0.982
18
0.799
51.590
1823
0.944
0.736
49.528
1692
0.988
19
0.847
52.152
1877
0.955
0.776
50.002
1734
0.992
20
0.887
52.682
1930
0.962
0.817
50.444
1773
0.995
21
0.919
53.183
1980
0.968
0.857
50.855
1810
1.000
22
0.944
53.655
2029
0.971
0.898
51.238
1845
1.000
23
0.963
54.101
2075
0.967
0.939
51.595
1878
1.000
24
0.977
54.521
2119
0.962
0.981
51.928
1909
1.000
25
0.987
54.917
2161
0.953
1.022
52.238
1938
1.000
26
0.994
55.292
2201
0.949
1.057
52.527
1965
1.000
27
0.999
55.645
2240
0.960
1.087
52.796
1991
1.000
28
0.999
55.978
2276
0.972
1.117
53.046
2015
1.000
29
1.000
56.292
2311
0.985
1.145
53.280
2038
1.000
30
1.000
56.589
2345
0.992
1.166
53.497
2059
1.000
40
1.000
58.774
2598
1.000
1.252
55.002
2210
1.000
50
1.000
59.996
2747
1.000
1.228
55.743
2287
1.000
60
1.000
60.680
2832
1.000
1.069
56.108
2325
1.000
70
1.000
61.030
2881
1.000
NA
56.288
2344
1.000
relationship of silvergray rockfish to other rockfish spe-
cies was examined by Gharrett et al. (2001).
Growth
Silvergray rockfish age estimates have not been vali-
dated as they have been for other rockfish (Bennett et
al., 1982; Culver, 1987; Leaman and Nagtegaal, 1987;
Andrews et al. 2002; Kerr et al. 2004); however, there
is evidence of a modal progression in the year classes
(Stanley and Kronlund, 2000).
Our estimated growth rates were similar to those
reported by Archibald et al. (1981), who used a small
subset of the current data. The maximum recorded
size of 73 cm for silvergray rockfish is larger than that
for most rockfish but smaller than that reported for
the largest rockfishes, such as yelloweye rockfish (S.
ruberrimus), cowcod {S. levis), shortraker (S. borealis),
and bocaccio (S. paucispinis), all of which can exceed
91 cm (Haldorson and Love, 1991). The growth rate of
silvergray rockfish is similar to that of other rockfishes
(Haldorson and Love, 1991), and weight at length was
Stanley and Kronlund: Life history characteristics for Sebastes brevispmis
679
1 o -
o-tr^^ — v~Q-—±L&xr~
cxr^
0.8"
/
0/
0 6 "
/ o
0/
04"
/
0> 0 2 "
E
^ 00"
/ °
~ 0 10 20 30 40
Proportion m
CD O
°y^r^
06"
1°
04 "
fo
Q 1
02"
J
oo-
o
0 10 20 30 40
Age
Figure 6
The estimated proportion mature at age for (A) female and (B) male
silvergray rockfish (Sebastes brevispinis).
similar between sexes as is common for most rockfishes
(Love et al., 1990).
Lenarz and Wylie Echeverria's (1991) examination of
growth dimorphism led them to categorize rockfish as
demersal versus water column, and shallow (<125 m)
versus deepwater species (>125 m). Table 4 shows that
silvergray rockfish are consistent with other demersal
rockfish in that they show relatively little sexual dimor-
phism in growth. Lenarz and Wylie Echeverria (1991)
suggested that the size dimorphism may result from
trade-offs between fecundity and size; they suggest that
among water-column species, males may optimize size
solely for survival, whereas added size for a female may
confer advantages in egg production.
Seasonal maturation and age at maturity
The difficulties in the macroscopic staging of rockfish
maturity have been widely discussed (Gunderson et
al., 1980; Love and Westphal, 1981; Wyllie Echever-
ria, 1987; Love et al., 1990; Nichol and Pikitch, 1994).
These authors are consistent in suggesting that maturity
stages should be verified by histological examination of
samples collected through all seasons.
More problematic than the staging is the possibil-
ity that commercial fishery samples may not be repre-
sentative of the overall population. If only the mature
fraction of an age class recruits to the fishery, then
age at maturity derived from commercial samples will
underestimate actual age at maturity. For the trawl
nets used in the rockfish fishery in British Columbia,
size at 100% retention for rockfish is about 30 cm. Sil-
vergray rockfish do not begin to recruit to the fishery
until about 35 cm; thus age or size at recruitment is
conditioned by behavior of the silvergray rockfish and
not by mesh size.
Given the discussion above, our conclusions on age
and length at maturity should be viewed as tentative.
Nevertheless, the available observations indicate that
most females are mature by age nine and most males
by age nine or ten. Lenarz and Wylie Echeverria (1991)
noted that in 21 of 31 rockfish species, females and
males matured at similar ages.
Mating appears to take place from September through
January and peaks from December through January.
This time range differs from the range derived from ob-
servations for southeastern Alaska where ripe male sil-
vergray rockfish were observed from January to March
680
Fishery Bulletin 103(4)
1.0
06
04
0.2"
00
Mature females
Selectivity
10
20
Age
- 1 —
30
- 1 —
40
Figure 7
Maturity at age for female silvergray rockfish iSebastes brevispi-
nis) in comparison with estimated age at recruitment.
(O'Connell8). Significant proportions of females with fer-
tilized eggs began to appear 2-3 months later in March
and peaked from April to May. This lag time does not
differ noticeably from that for other rockfish. Wyllie
Echeverria (1987) reported that fertilized eggs are usu-
ally found 1-3 months after mating. A few specimens
with eyed larvae have been observed in February and
March but significant proportions are not observed until
April. Parturition lasts through July and peaks in June.
Westrheim (1975) suggested that the principal month
of parturition was later than June for Oregon-B.C.
waters, and later than May for the Gulf of Alaska.
Phillips (1964) suggested that the timing of rockfish
reproduction could be classified into two broad seasons:
early (winter) or late (spring-summer). Silvergray rock-
fish clearly fall within the latter category.
A mating period from December to January and par-
turition in June implies a 5-6 month process. This is
longer than the average period reported for rockfish
by Wyllie Echeverria (1987) but similar to those re-
ported for greenstripe rockfish (S. elongatus) (Dec-Feb
to June), redstripe rockfish (Nov-Jan to June) and
sharpchin rockfish (S. zaeentrus) (Oct-Jan to Apr-May)
(Shaw, 1999). The longer periods may reflect that these
species and samples were from higher latitudes than
the California observations prevalent in Wyllie Ech-
everria's work. However, Shaw (1999) pointed out that
8 O'Connell, V. 1986. Spawning seasons for some Sebastes
species landed in the Southeast Alaska longline fishery for
nearshore rockfishes (1982-1985). Unpublished report,
21 p. Alaska Department of Fish and Game, Division of
Commercial Fisheries, 304 Lake St., No. 103, Sitka, AK
99835-7563.
rosethorn rockfish (S. helvomaculatus) samples from the
same latitudes indicated a maturation process of 1-2
months. Batch spawning has been reported by Moser
(1967a, 1967b) for some rockfish species but our his-
tological examination of 11 specimens taken from the
April sample provided no indication of this in silvergray
rockfish. Samples taken closer to parturition would be
more conclusive.
The July samples indicated a dome-shaped relation-
ship in the timing of parturition. As reported for dark-
blotched rockfish (Nichol and Pikitch, 1994) and yel-
lowtail rockfish (Eldridge et al., 1991), we observed
that the smaller females tended to complete parturition
later. However, unlike the results from previous stud-
ies, our results indicates that the largest females also
tended to complete parturition later.
Fecundity
Different authors have emphasized that actual fecundity
at parturition may be lower than estimates derived prior
to fertilization (MacGregor, 1970; Boehlert et al., 1982;
Haldorson and Love, 1991; Gunderson, 1997), although
this was not observed in yellowtail rockfish (Eldridge
et al. 1991). Future studies could examine fecundity
closer to parturition; however, it is difficult to capture
specimens on the verge of parturition without inducing
extrusion (Boehlert et al., 1982). We also caution that
our estimates are from one sample and Guillemot et
al. (1985) reported significant interannual variation
in gonadal development among five species of northern
California rockfish.
The presence of the Sarcotaces arcticus parasite, pre-
viously reported for silvergray rockfish (Sekerak, 1975),
Stanley and Kronlund: Life history characteristics for Sebastes brevispmis
681
1500 ■
1000
500
oo
o °° 8o o
o°oo °
°t+°8
oB +
o +
10
20
30
40
Age
50
60
70
0.6
0.5
0.4
0.3
0.2
0 1
B
10
20
30
40
Age
50
60
70
5 1500
1000
500
o'<5
-Jo o0 +
2000
3000
Somatic weight (g)
4000
Figure 8
Silvergray rockfish (Sebastes brevispinis) fecundity (thousands of eggsl versus
lA) age, (B) relative fecundity (thousands of eggs/g somatic weight) against
age, and (C) fecundity against somatic weight. Solid circles indicate two
possibly anomalous points. The plus symbols indicate females infected by
the Sareotaces areticus parasite. The dashed curves represent the limits of
point -wise 95% confidence intervals. The "rug" along the x-axis of each plot
shows the frequency of observations of age or size classes.
appears to be associated with reduced fecundity, albeit
this conclusion is based on three observations. This
conclusion is consistent with qualitative observations by
the senior author that the gonads of infected silvergray
rockfish tend to be smaller.
Silvergray rockfish fecundity appears typical of the
genus as summarized in the meta-data treatment by
Haldorson and Love (1991). Predicted fecundity for a
40-year old female exceeds 1,250,000 oocytes, although
the maximum observed fecundity in a small sample
was almost 2,000,000. The slope of the relationship of
log fecundity to log length from our study was 4.283,
close to the mean of 4.10 reported for other rockfish
(Haldorson and Love, 1991).
Haldorson and Love (1991) noted that the ratio of
fecundity at the age of 50% maturity versus fecundity
682
Fishery Bulletin 103(4)
CD
CO
w
1 o -
o
\
09 -
\
0
\
0 8 -
0 7 -
0.6 "
\
0
\
0
\
o
\
^o
o^
I
"^o^
I
0.00 0.02 0.04 0.06 0 08 0 10
F
Figure 9
Spawning biomass per recruit (SSB/R) against instan-
taneous fishing mortality (F) for silvergray rockfish
<Sebastes brevispinis).
at the age of maximum fecundity ranged from 0.01
to 0.25 for rockfish. Fecundity at 50% maturity could
not be determined because we had no observations for
females less than 12 years of age. However, if we use
fecundity at age 12 (the youngest fish in our sample)
and fecundity at age 40 (the predicted age of maximum
fecundity), the ratio exceeds 0.40. This finding supports
the contention that age at 50% maturity for silvergray
rockfish is less than 12 years and adds credibility to
the observation that the age of 50% maturity is lower
than the age at 50% selectivity.
Estimates of specific fecundity (fecundity/somatic
weight) were 356 and 482 ova/g for the 12-year-old and
40-year-old females, respectively. Given that the age at
50% maturity is probably less than 12 years; this range
in "relative investment" in reproduction appears aver-
age for rockfish (Haldorson and Love, 1991). As with
other rockfish, specific fecundity increases with size,
although it appears to reach an asymptote at age 40
for silvergray rockfish.
Age at maturity and SSB/R
An M of 0.06 places silvergray rockfish in the middle
to lower end of the mortality range for rockfishes. It
is higher than the estimates of 0.02-0.04 reported for
yelloweye rockfish (O'Connell and Fujioka9; O'Connell et
al.10; Yamanaka and Lacko, 2001) but much less than
0.14 that has been used for yellowtail rockfish, or 0.28
used for black rockfish (S. melanops) (Dorn, 2002).
The analysis of SSB/R indicates that an F-n, cor-
responds to F=0.072 or F=1.2M. This F to M ratio rep-
resents a more aggressive harvest strategy than the
range of 0.5-1.0 currently supported in the literature
(Patterson, 1992; Walters, 1998). This result is caused
by the special case of silvergray rockfish, anticipated
by Clark (1991), wherein recruitment at age is delayed
in comparison to maturity at age. If most females actu-
ally mature by age 11 or 12 years, but are still not 50%
vulnerable at age 14 (Fig. 9), then even at a relatively
high fishing mortality, most females can reproduce a
few times prior to capture.
As stated above, recruitment to the fishery may be
driven more by the stage of maturation than by size or
age. Movement to areas and depths that are the source
for most fishery samples may be governed by behav-
ioral issues associated with maturation. If fish tend to
recruit as they become mature, somewhat independent
of size or age, then we may underestimate the age of
50% maturity. In this respect, it is interesting that the
fecundity data, compared to other rockfish data, also
indicate that the age of 50% maturity may be much
less than 12 years.
Our suggestion to managers is that unless the non-
recruited population can be sampled to verify matu-
rity-at-age assumptions, then a more precautionary
approach is warranted than is implied by an F=1.2M
logic for harvest strategy. This silvergray rockfish ex-
ample emphasizes the sensitivity of an SSB/R harvest
logic to estimating age at maturity, which in turns em-
phasizes the often neglected issues of field classification
of maturity and the representativeness of samples. The
task of estimating age at maturity is perhaps too often
ignored at the expense of estimating other life history
parameters.
Conclusion
Owing to the small role that silvergray rockfish has
played in groundfish fisheries of the eastern North
Pacific Ocean, this species has received little research
attention. However, these less valuable stocks are begin-
ning to attract more attention owing to their potential to
disrupt precautionary management objectives within the
context of a multispecies fishery. With the shift to a more
precautionary paradigm, a lack of stock knowledge about
the status of any of the incidental species, such as silver-
gray rockfish, can be a basis for restricting the overall
fishery. Strategic allocation of resources by species or
stock can no longer be predicated on landed value.
u O'Connell, V., C. Brylinsky, and D. Carlile. 1991. Demersal
shelf rockfish stock assessment and fishery evaluation report
for 2004. Alaska Dep. Fish and Game Regional Information
Report J03-39, 44 p. 304 Lake St. #103, Sitka, AK 99835-
7563.
10 O'Connell, V., and J. Fujioka. 1991. Demersal shelf rock-
fish. In Status of living resources off Alaska as assessed
in 1991, p. 46-47. NOAA. Tech. Memo. NOAA-TM-NMFS-
F/NWC-211. 304 Lake St. #103, Sitka, AK 99835-7563.
Stanley and Kronlund: Life history characteristics for Sebastes brevispmis
683
Finally, we note how a meta-data analysis such as
that provided by Haldorson and Love (1991) can provide
values for stock assessment parameters in the absence
of direct estimation. By summarizing the basic life
history characteristics for silvergray rockfish in B.C.
waters, we add to the research on rockfish and improve
the basis for effective management of at least one more
minor, but potentially fishery-limiting, species in the
eastern Pacific groundfish complex.
Acknowledgments
This summary of the biology of silvergray rockfish was
much improved through discussions with four com-
mercial trawl fishermen, Capt.'s Risk Benham, Brian
Dickens, Ron Gorman, and Reg Richards. We also appre-
ciated the derivation of temperature at depth provided by
Roy Hourston and the help with the graphics from Norm
Olsen. The document was much improved by review
comments from Bruce Leaman and three anonymous
reviewers.
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Appendix 1— Growth formula from Schnute (1981)
Y(t)--
l-e
-iV6
The model involves six parameters, Q=(tv T2,y1,y2, a, b),
where r, and r„ are two arbitrary ages in the life of a
fish, such that T„>r,. The parameter y, is the size of a
fish at time rv and y., is the size of a fish at time T2 with
.Vo>Ji>0. Parameters a and b determine the shape of the
growth curve by controlling the acceleration (decelera-
tion! in growth from times t1 to t2. The parameter a has
units (in time), and b is dimensionless. Although the
mathematical expression of the model has four cases,
these four cases actually represent the limiting forms of
a single equation as a or b (or both) approach 0.
Appendix 2— Spawning stock biomass per recruit
If Na is a vector of the numbers of females at each age
under constant conditions, such that
Na+l=Nae
-iFS.+M)
where F = the instantaneous fishing mortality rate;
Sa = the partial recruitment at age a; and
M = the instantaneous natural mortality rate;
then the cumulative spawning potential of a cohort of
females over the lifetime of the cohort (under constant
FandM andSn) is
SSB/R = ^NaFecaMatn,
i
where Fecn = fecundity at age a, and
Matn = proportion mature at age a.
The spawning potential per recruit (SSB/R) can then be
calculated under various estimates of F and compared
with the unfished SSB/R (F=0) as shown in Figure 9.
685
Abstract — To assess the impact of
California sea lions (Zalophus cali-
fornianus) on salmon fisheries in the
Monterey Bay region of California,
the percentages of hooked fish taken
by sea lions in commercial and rec-
reational salmon fisheries were esti-
mated from 1997 to 1999. Onboard
surveys of sea lion interactions with
the commercial and recreational
fisheries and dockside interviews
with fishermen after their return
to port were conducted in the ports
of Santa Cruz, Moss Landing, and
Monterey. Approximately 1745 hours
of onboard and dockside surveys were
conducted — 924 hours in the com-
mercial fishery and 821 hours in the
recreational fishery (commercial pas-
senger fishing vessels [CPFVs] and
personal skiffs combined I. Adult male
California sea lions were responsible
for 98. 4*5 of the observed depredations
of hooked salmon in the commercial
and recreational fisheries in Mon-
terey Bay. Mean annual percentages
of hooked salmon taken by sea lions
ranged from 8.5% to 28.6% in the
commercial fishery, 2. 2% to 18.36%
in the CPFVs, and 4.0% to 17.5% in
the personal skiff fishery. Depreda-
tion levels in the commercial and
recreational salmon fisheries were
greatest in 1998 — likely a result of
the large El Nino Southern Oscilla-
tion (ENSO) event that occurred from
1997 to 1998 that reduced natural
prey resources. Commercial fishermen
lost an estimated $18,031-$60,570 of
gear and $225.833-$498,076 worth of
salmon as a result of interactions with
sea lions. Approximately 1.4-6.2% of
the available salmon population was
removed from the system as a result of
sea lion interactions with the fishery.
Assessing the impact of a growing sea
lion population on fisheries stocks is
difficult, but may be necessary for
effective fisheries management.
Impact of the California sea lion
{Zalophus californianus) on salmon fisheries
in Monterey Bay, California
Michael J. Weise
James T. Harvey
Moss Landing Marine Laboratories
8272 Moss Landing Road
Moss Landing, CA 95039-9647
Present address (lor M. J. Weise): Department of Ecology and Evolutionary Biology
University of California Santa Cruz
Center for Ocean Health
100 Shaffer Rd
Santa Cruz, California 95060
E-mail address (for M J Weise): weiseiu'biology ucsc edu
Manuscript submitted 13 August 2004
to the Scientific Editor's Office.
Manuscript approved for publication
10 June 2005 by the Scientific Editor.
Fish. Bull. 103:685-696(2005).
California sea lions (Zalophus cali-
fornianus) interact with almost all
commercial and recreational fisheries
along the California coast, causing
entanglement and damage to fishing
gear and loss of catch (Beeson and
Hanan1; NMFS2). The prey of these
pinnipeds has been of interest for
years because pinnipeds have been
viewed as competitors with humans for
a variety of fish species. Historically,
this competition between pinnipeds
and fishermen was of limited impor-
tance because fishes and pinnipeds
were harvested. However, the increas-
ing specialization within the fishing
industry during the twentieth century
and changing attitudes toward pinni-
peds have intensified this competition
(Harwood and Croxall, 1988). Since
the passage of the Marine Mammal
Protection Act (MMPA) in 1972, the
population of California sea lions
has increased along the West Coast
of North America (NMFS2). This
increase in pinniped populations has
resulted in an increase in the number
of reports of pinnipeds interacting
with fishing boats and depredating
the catch in fisheries along the West
Coast (Beeson and Hanan1; NMFS2).
The California sea lion popula-
tion, found from offshore islands in
Mexico north to Vancouver Island,
British Columbia, has increased
steadily throughout the latter part
of the twentieth century (NMFS2).
In the early 1900s, the over-riding
management philosophy was to limit
the California sea lion population
because of damage to commercial
catches and competition for salmonid
fishery resources (Everitt and Beach,
1982). Numbers of sea lions began to
increase in the 1940s with curtail-
ment of commercial harvests, but
bounties were paid for seals and sea
lions in Oregon and Washington until
the early 1970s. Following passage
of the MMPA in 1972, the California
sea lion population increased at an
annual average of 5.0-6.2% along the
West Coast (Carretta et al.3). There
are an estimated 204,000-214,000
sea lions in U.S. waters (Carretta et
1 Beeson, M. J., and D. A. Hanan. 1996.
An evaluation of pinniped-fisheries
interactions in California. Report to
the Pacific States Marine Fisheries Com-
mission, 46 p. Pacific States Marine
Fisheries Commission, 205 SE Spokane
St., Portland, OR 97202.
2 NMFS (National Marine Fisheries Ser-
vice). 1997. Impacts of California sea
lions and Pacific harbor seals on salmo-
nids and the coastal ecosystems of Wash-
ington, Oregon, and California. NOAA
Tech. Memo. NMFS-NWFSC-28, 150 p.
Northwest Fisheries Science Center,
2725 Montlake Blvd. East, Seattle, WA
98112-2097.
3 Carretta, J. V., M. M. Muto, J. Barlow,
J. Baker, K. A. Forney, and M. Lowry,
editors. 2002. U.S. Pacific Marine
Mammal Stock Assessments: 2002.
NOAA/NMFS Tech. Memo., NOAA-TM-
NMFS-SWFSC-346, 290 p. Southwest
Fisheries Science Center, 8604 La Jolla
Shores Drive, La Jolla, California 92037-
1508.
686
Fishery Bulletin 103(4)
al.3), and an additional 45,000-54,000 animals along
Baja, Mexico (Aurioles-Gamboa and Zavala-Gonzalez,
1994). In the Monterey Bay region, sea lions do not
breed but several important resting sites exist with a
range of 3000 to 7500 animals during the nonbreed-
ing season (Weise, 2000). In contrast to increases in
numbers of sea lions, serious declines in salmonid popu-
lations have occurred in recent years as a result of
changes and degradation in riverine habitat, declines
in water quality, overharvesting, changes in oceanic
conditions, and the development of hydroelectric power
systems that obstruct major riverine migration routes.
Chinook salmon (Oncorhynchus tshawytscha) stocks
in the Central Valley of California probably represent
85% to 95% of the chinook salmon catches south of Pt.
Arena and in Monterey Bay (PFMC4). Central Valley
chinook originate in the Sacramento River and San
Joaquin River and have four distinct runs (portion of
a salmon stock that returns to their native streams
to spawn during a specific season): fall, late-fall, win-
ter, and spring. Fall and late-fall runs are relatively
healthy, but winter and spring runs are listed as en-
dangered under the Endangered Species Act (ESA).
Salmon landed in Monterey Bay during the summer
fishing season are predominantly fall and late-fall run
Central Valley chinook salmon. Size limits and seasonal
restrictions are set to reduce retention of listed winter
run Central Valley chinook and Klamath River stocks
(PFMC4). By taking hooked fish, sea lions can affect
salmon stocks because commercial and recreational
fishermen continue to fish for salmon to replace those
taken by sea lion and this activity of predation and
compensatory fishing leads to greater numbers of fish
being removed from the population. In the ocean com-
mercial troll and recreational salmon fishery, sea lions
will swim near or follow fishing boats and will depre-
date fish once hooked.
Consumption of hooked salmon by sea lions may not
only impact salmonid stocks but impact the economic vi-
ability of fisheries. Recreational and commercial salmon
fishing is an important social and economic asset in
California, representing $28,856,000 in revenues in
1995 (PFMC5). Concern over declining salmonid stocks
has resulted in adjustments of fishing regulations, such
as allocation of harvest between ocean and inland user
groups, harvest quotas, and time and area closures
(Beeson and Hanan1). Increasing losses offish to Cali-
fornia sea lions may produce further restrictions for the
recreational and commercial salmon fisheries.
4 PFMC (Pacific Fisheries Management Council). 1999. Re-
view of 1998 ocean salmon fisheries. NOAA Award No.
NA97FC0031, sections A1-A50 and Bl-43. Pacific Fisher-
ies Management Council, 7700 NE Ambassador Place, Suite
200, Portland, OR 97220-1384.
5 PFMC (Pacific Fisheries Management Council). 1995. Re-
view of 1994 ocean salmon fisheries. NOAA No. NA57FC0007,
sections A1-A50 and B1-B43. Pacific Fisheries Management
Council, 7700 NE Ambassador Place, Suite 200, Portland,
OR 97220-1384.
During the last several decades only a few research-
ers have attempted to quantify the impact of sea lions
on fisheries in California waters and, more specifical-
ly, the Monterey Bay region. According to Beeson and
Hanan,1 the recreational ocean salmon landings in 1995
were greatest in Monterey Bay and San Francisco areas
and experienced the greatest amount of sea lion preda-
tion (charter passenger fishing vessels and private skiff
combined). In our study, we surveyed salmon fisheries
in Monterey Bay because of the particularly high rates
of interactions with sea lions (Beeson and Hanan1) in
an effort to better understand the nature and extent of
these interactions in the commercial and recreational
fisheries.
The purpose of this study was to estimate the per-
centage of salmon taken by California sea lions from
commercial and recreational salmon fisheries in Mon-
terey Bay from 1997 to 1999. We hypothesized that
the percentages of fish taken by California sea lions
in salmon fisheries would be greater than those taken
in previous years and would be part of an increasing
trend in sea lion and fisheries interactions paralleling
the growth of the sea lion population. Further, we esti-
mated the number of fish removed from the California
Central Valley chinook stock from observed percent-
ages of fish taken by sea lions in fisheries. Lastly, we
estimated the monetary losses associated with sea lions
interacting with commercial and recreational salmon
fisheries in Monterey Bay from 1997 to 1999 by quan-
tifying the value of fish lost and the type and amount
of gear lost or damaged.
Methods
From 1997 to 1999, observations of interactions between
pinnipeds and salmon fisheries were conducted onboard
boats, and interviews with fishermen were performed
at dockside at the three major ports in the Monterey
Bay region: Santa Cruz, Moss Landing, and Monterey
(Fig. 1). Salmon fishing operations included commercial
troll fishery and recreational fisheries consisting of com-
mercial passenger fishing vessels (CPFVs) and private
skiffs. The timing of the commercial and recreational
salmon fishery seasons varied each year of the study,
and sampling was conducted from the beginning to the
end of each season (Table 1). The commercial troll fish-
ery included day boats (i.e., a one-day fishing trip) and
multiple-day boats. Fishing areas included in our study
ranged from Pt. Sur north to Ano Nuevo Island. Data
regarding fisheries interactions collected at the three
different ports were pooled because fishermen from all
three ports often fish as a fleet.
Dockside surveys were conducted to achieve a greater
sampling effort than could be obtained from onboard
observations alone. Onboard surveys were conducted
to test reliability of dockside surveys and to ensure
that investigators fully understood the nature of the
interaction. Small biases have occurred when combining
onboard and dockside surveys but were attributed to
Weise and Harvey Impact of Zalophus californianus on salmon fisheries
687
Table 1
Commercial and recreational salmon fishery seasons in the Monterey Bay region from 1997 to 1999.
Commercial
Recreational
1997
1998
1999
1-31 May, 23 June-18 July, 1-30 September
1-31 May, 16 June-30 September
1 May - 21 August, 1-30 September
15 March-19 October
14 March-7 September
14 March-6 September
onboard sampling in areas where interaction was more
prevalent (Miller et al.6). During this study, captains
were requested during onboard observations to conduct
normal fishing operations and not to intentionally seek
out areas with greater or lesser rates of interaction
between sea lions and fishery operations.
Sampling of commercial and recreational salmon
fisheries was stratified by month and approximately
equal numbers of onboard and dockside surveys were
conducted monthly. Sampling days and ports were se-
lected randomly for onboard and dockside surveys of
commercial fishing operations, but onboard surveys
were limited by crew cooperation and space availabil-
ity. Each onboard survey in the commercial fishery
took a full fishing day onboard one boat, and dockside
interviews were conducted during four-hour periods in
the middle to late afternoon during the peak time that
vessels returned to port. For CPFVs, which operate
virtually every day but have a greater number of boats
and passengers on weekends, two-thirds of onboard and
dockside sampling dates were selected randomly from
possible weekend dates and one-third from all possible
weekdays. Onboard surveys of CPFV took a full fishing
day aboard one vessel, and dockside surveys took two
to three hour periods in early afternoon during peak
return times for CPFVs at a randomly selected port.
The goal of CPFV dockside surveys was to sample (for
the sampling day) all CPFVs targeting salmon and that
had returned to port. In the skiff fishery, greater num-
bers of fishing trips occurred on weekends; therefore
approximately three-quarters of sampling days occurred
on weekends, and one-quarter occurred on weekdays.
Onboard surveys in 1997 aboard one skiff took a full
fishing day, and dockside surveys from 1997 to 1999
were conducted during two-hour sampling periods in
late morning and early afternoon during the peak re-
turn time for private skiffs.
In 1997, four onboard surveys were conducted in the
commercial and CPFV fishery, and five onboard pri-
vate skiff surveys were conducted. Whereas in 1998
and 1999. in an effort to increase onboard sample size,
survey effort was concentrated in the commercial and
6 Miller, D. J., M. J. Herder, and J. P. Scholl. 1983. Cal-
ifornia marine mammal-fishery interaction study, 1979-
1981. NMFS Southwest Fish. Cent., Admin. Rep. LJ-83-13C,
233 p. Southwest Fisheries Science Center, 8604 La Jolla
Shores Drive, La Jolla, CA 92037-1508.
Figure 1
Primary fishing ports used by commercial and recre-
ational salmon vessels, and pinniped haul-out sites
in Monterey Bay, California.
CPFV fisheries; 22 surveys conducted each year in each
fishery.
Information collected at dockside included port of
call, number of fish landed, number of fish taken by
pinnipeds at or below the surface, species and number
of marine mammals involved in surface take, number of
fish released, number of released fish taken by marine
mammals, and type and amount of gear loss. Onboard
surveys included the same information collected at
dockside, as well as standard length of all fish landed.
Commercial troll and recreational salmon fisheries
use different types of fishing gear, which can affect
the nature and magnitude of their interactions with
pinnipeds. Commercial salmon trolls are designed
to catch fast-swimming fishes by using flashy lures
that are trolled behind the moving vessel on heavily
688
Fishery Bulletin 103(4)
weighted fishing lines. Multiple lines are mounted on
outrigger poles to ensure separation of the lines and
are controlled by small hydraulic winches (Starr et al.,
1998). Depending on conditions, commercial fishermen
use three to fifteen lures per line and two to six lines
per boat, totaling six to ninety lures with hooks per
boat. In recreational boats each fisherman traditionally
uses one rod, reel, line, and hook with bait.
Surface takes, also termed "definite takes," were de-
fined as takes when pinnipeds took a hooked salmon
(and when the species and number of marine mammals
involved could be determined). Surface takes were also
recorded when fish were hooked and the action of the
line indicated that a fish was no longer hooked, and a
pinniped surfaced immediately with a fish in its mouth.
Takes below the surface, or "probable takes," were de-
fined as takes when fish were removed from the hook
(and when the species and number of marine mammals
involved could not observed directly). Evidence that
indicated the occurrence of below-surface takes was in
the form of bent hooks, lost gear, or a sea lion surfac-
ing within several minutes with a salmon, provided no
other fishing boats were in close proximity. Two types of
takes were designated because takes below surface were
not witnessed, and other predators including sharks
take fish from lines, or fish may have escaped. However,
fishermen and researchers recognized that takes by
pinnipeds, specifically by sea lions, differed from takes
by sharks and other predators by the action of the line,
effect on the hook or lure (or both), and type of bite on
fish parts remaining on the hook.
Number of salmon and percentage of catch taken by
pinnipeds were compared with the total catch and the
legal catch in commercial and recreational fisheries. To-
tal catch was defined as numbers offish hooked, includ-
ing all legal-size fish, fish taken by pinnipeds, and all
undersize fish. Legal catch represented only fish of legal
size landed by anglers. Our rationale for using total
catch was that all fish, regardless of size, have an equal
probability of being taken by pinnipeds; therefore, com-
parisons with total catch were a more accurate metric
for quantifying the impact of pinnipeds on the salmon
fishery. Comparisons with the legal catch inflated the
percentage of fish taken by pinnipeds and exacerbated
the perception of the problem of pinnipeds interacting
with salmon fisheries. However, previous researchers
have compared percentage takes by pinnipeds with legal
catch; therefore we also made the comparison with legal
catch to place our results in a historical context.
Mean percentages of fish taken by sea lions in rela-
tion to total catch (referred to as "mean percentage of
fish taken by sea lions") for the commercial, CPFV, and
skiff fisheries for onboard and dockside surveys from
1997 to 1999 were non-normal in distribution and were
transformed by using the arcsine transformation for
parametric statistical comparisons (Zar, 1996). Mean
percentages of fish taken by sea lions in the three fish-
eries (commercial, CPFV, and skiff) were compared
between onboard and dockside surveys, among years
(1997 to 1999), between seasons (sea lion breeding and
nonbreeding seasons), and between takes (surface and
below surface) using a Students t-test and ANOVA or
a Mann-Whitney [/-test and Kruskal-Wallis test for
data that were non-normal and heteroscedastic after
transformation.
Sea lion breeding and nonbreeding seasons from 1997
to 1999 were determined by using aerial and ground
counts from Weise (2000). The breeding season was desig-
nated as the time when a significant decline in the num-
ber of breeding adult males was recorded at haul-out sites
in the Monterey Bay region, when animals where pre-
sumably heading for the breeding rookeries in southern
California. Typically the breeding season is from June
and July, and the nonbreeding season occurs during the
months of March, April, May, August, and September.
Mean catch per unit of effort, or the numbers of fish
hooked per day per boat, in commercial, CPFV, and
skiff fisheries data were non-normal and heterosce-
dastic, therefore, were they were transformed by us-
ing -J count + 1 (Harvey, 1987; Zar, 1996). Mean catch
per unit of effort for the three fisheries was compared
among years with an ANOVA.
To estimate the impact of California sea lion depreda-
tion on salmon populations in Monterey Bay we com-
pared estimated numbers of hooked salmon taken by
sea lions and the Central California Valley index (CVI)
for chinook salmon abundance. The CVI is the numbers
of ocean- and inland-harvested Chinook salmon and the
sum of all runs of chinook on the Sacramento Rivers
(PFMC4) and represents presumably the population
of salmon passing through the Monterey Bay region
during the fishery season. The estimated number of
salmon taken was calculated from the observed num-
ber of takes in the commercial and recreational fishery
multiplied by the percentage of the total catch that was
sampled. Percentage of the total catch sampled was es-
timated by dividing the number of observed legal-size
fish landed by the total number of legal-size fish landed
(CDF&G, unpubl. data7).
Monetary losses resulting from sea lion interactions
with salmon fisheries were estimated by evaluating
numbers of fish taken by sea lions and types and quan-
tities of fishing gear damaged or lost during these inter-
actions. Information for the analysis of monetary loses
was collected during dockside and onboard surveys for
commercial and recreational salmon fisheries.
Annual monetary losses resulting from fish taken
by sea lions were calculated by using total numbers
of estimated takes by sea lions, average dressed mass
(mass of gutted and cleaned fish) of salmon landed in
Monterey from 1997 to 1999, and average exvessel price
(wholesale price per pound of fish paid to fishermen)
for chinook salmon in California from 1997 to 1999
(PFMC4). Estimated numbers of takes by sea lions in
Monterey Bay from 1997 to 1999 were a function of
7 CDF&G (California Department of Fish and Game). 2004.
Ocean Salmon Project database. CDF&G Ocean Salmon
Project, 475 Aviation Blvd., Suite 130, Santa Rosa, CA
95403.
Weise and Harvey: Impact of Zalophus ca/iformanus on salmon fisheries
689
numbers of observed takes (based on dockside samples)
and proportions of the total catch sampled.
Estimates of lost and damaged gear were calculated
by using average costs for each type of gear used in
commercial and recreational salmon fishing operations.
A survey of the seven local retail fishing tackle stores in
Santa Cruz, Moss Landing, and Monterey was used to
estimate mean value of each type of fishing gear used
in the recreational (CPFV and skiff combined) salmon
fishery. All charter-fishing companies in the three ports
in Monterey Bay were surveyed to estimate mean cost
of a "setup" sold by charter boat companies to custom-
ers. A "setup" was defined as a hook and leader, or a
hook, leader, and a 4 oz. or 8 oz. lead sinker. Costs of
commercial fishing gear were estimated by surveying 19
local fishermen from the three ports in Monterey Bay.
Commercial fishermen buy the majority of their gear in
bulk, and often by mail order to reduce costs.
Results
From 1997 to 1999. 1745 hours of onboard surveys and
dockside interviews were conducted in the commercial
and recreational salmon fisheries. In 1997, 337 hours
of onboard and dockside surveys were conducted, 144
hours in the commercial fishery, 103 hours in the CPFV
fishery, and 90 hours in the skiff fishery. In 1998, 704
hours of onboard and dockside surveys were conducted:
370 hours in the commercial fishery, 270 hours in the
CPFV fishery, and 64 hours in the skiff fishery. During
1999, 704 hours of onboard and dockside surveys were
conducted, 410 hours in the commercial fishery, 258
hours in the CPFV fishery, and 36 hours in the skiff
fishery. Increased sampling effort in 1998 and 1999
were the result of increased onboard survey effort in
the commercial and CPFV fisheries.
During this study 101 onboard surveys and 2780
dockside interviews (number of boats sampled) were
conducted in the commercial and recreational salmon
fisheries. There were no significant differences in mean
percentages of fish taken by sea lions between onboard
and dockside surveys in the commercial (1997, P=0.329;
1998, P=0.623; 1999, P=0.653), CPFV (1997, P=0.276;
1998, P=0.660; 1999, P=0.327) and skiff fisheries (1997,
P=0.052; Fig. 2). We assumed, therefore, that dockside
surveys provided a representative measure of pinniped
takes in the salmon fisheries and onboard survey data
were pooled with dockside interview data for subsequent
analysis.
A total of 967 interviews with commercial fishermen
and 1813 interviews with recreational fishermen were
were conducted at dockside in Monterey Bay, account-
ing for 41,895 and 15,115 hooked salmon, respectively
(Table 2). In the commercial fishery a similar number
of interviews were conducted in 1997 and 1998, whereas
in 1999 approximately 21.2% greater numbers of inter-
views were conducted with the same effort. However,
the number of fish landed in 1999 was significantly less
than in 1997 and 1998. In the CPFV fishery, the trend
40'
Commercial
^^m Onboard
30
I- — t Dockside
20'
T
10
r 1
1
0
■
1
CPFV
2£
2
"g 30
Q-
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C
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c
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o
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40
J
i.
Skiff
30
20
^
10
.
0
1
n
1997 1998 1999
Figure 2
Percentage of pinniped takes in relation
to the total number of salmon hooked as
determined from dockside and onboard
surveys for the commercial, commercial
passenger fishing vessel (CPFV I, and
personal skiff fisheries in Monterey Bay,
California, from 1997 to 1999. Onboard
survey effort concentrated in CPFV and
commercial fisheries during 1998 and
1999. Error bars indicate one standard
error.
was similar to the commercial fishery, but the number
of fish landed and the number of boats surveyed was
significantly fewer overall. In the skiff fishery, there was
a steady decline in the number of fishermen surveyed
and the number of fish landed from 1997 to 1999.
Onboard observations combined with dockside inter-
views revealed that California sea lions were almost
exclusively responsible for the depredation of hooked
salmon in the commercial and recreational fisheries
in Monterey Bay, taking 98.4% of the 1199 observed
hooked salmon from 1997 to 1999. Of the estimated
2420 takes in 1997, 1072 were directly observed surface
takes and sea lions were identified in 98.6% of the takes
(Table 2). In 1998, approximately 501 of 5542 takes
690
Fishery Bulletin 103(4)
Table 2
Yearly catch statistics and estimates of the number and percentc
ge of salmon
taken by pinnipeds in the commercial.
commercial
passenger fis
hing vessel
l CPFV Land
skiff salmon fisheries dun
ng dockside surveys in Monterey Bay in
1997, 1998,
and 1999.
Catch statistics
Number of takes
Percentage
of takes
Total
Number of
Number
Number
Total %
Total %
Number
number
legal-size
Number of
offish
offish
of legal
of total
dockside
offish
fish
under-size
taken at
taken below
catch
catch
Fishery
Year
interviews
hooked
landed
fish
surface
surface
lost
lost
Commercial
1997
297
17,943
12,288
4124
522
1009
12.5
8.5
1998
293
15,446
6206
4829
97
4314
71.1
28.6
1999
377
8506
6785
966
37
718
11.1
8.9
Total
967
41,895
25,279
9919
656
6041
26.5
16.0
CPFV
1997
139
5168
3157
1577
247
187
13.7
8.4
1998
179
4694
3267
569
305
553
26.3
18.3
1999
58
362
319
35
6
2
2.5
2.2
Total
376
10,224
6743
2181
558
742
19.3
12.7
Skiff
1997
723
2926
1643
828
303
152
27.7
15.6
1998
538
1564
882
409
99
174
31.0
17.5
1999
176
401
315
70
8
8
5.1
4.0
Total
1437
4891
2840
1307
410
334
26.2
15.2
occurred at the surface, and sea lions were identified
in 98.4% of those takes. In 1999, 51 of the 779 takes
occurred at the surface, and sea lions were responsible
for 96.1% of the takes. We assumed sea lions took simi-
lar percentages of fish below the surface. As evidence
of takes below the surface, sea lions would come to the
35-,
(/)
T3
<D
§" 30-
c
Q.
£■ 25-
C
& 20-
tn
o 15-
<D
O)
CO
c 10-
QJ
O
0
<D
5 0,-
1
T
^m 1997
I 1 1998
M 1999
ii
T
.1
r
i
Commercial CPFV Skiff
Figure 3
Mean percentage of salmon taken by California sea lion (Zalo-
phus californianus) as determined from onboard and dockside
surveys of the commercial, commercial passenger fishing vessel,
and skiff fisheries in Monterey Bay, California, from 1997 to
1999. Error bars indicate one standard error.
surface within minutes with a fish. Pacific harbor seal
(Phoca vitulina richardsi) was responsible for other
observed takes.
Percentages of the catch taken by sea lions, based on
pooled dockside and onboard surveys, were significantly
different among years in the commercial (P<0.000), CP-
FV (P<0.000), and skiff fishery (P<0.000; Fig. 3).
During 1998, significantly greater percentages of
salmon were taken in the commercial (Tukey HSD
multiple comparison, P<0.000), CPFV (Tukey HSD
multiple comparison, P<0.000), and skiff fisher-
ies (Tukey HSD multiple comparison, P<0.000).
Whereas during 1999, the CPFV (Tukey HSD
multiple comparison, P<0.000) and skiff fisher-
ies (Tukey HSD multiple comparison, P<0.000)
experienced significantly smaller percentages of
sea lion takes. In the commercial fishery there
was no difference in the percentage of fish taken
between 1997 and 1999.
Although the timing of the sea lion migration
varied by year (Weise, 2000), the percentages of
takes by sea lions were greater during the non-
breeding season than during the breeding sea-
son in all three years (Fig. 4). In the commer-
cial fishery, those differences were significant for
all three years (1997, P<0.000; 1998, P=0.001;
1999, P= 0.041). In the CPFV fishery, significant-
ly more takes occurred during the nonbreeding
season in 1997 (P=0.010), and 1998 (P<0.000);
however, there was no significant difference in
1999 (P=0.358). In the skiff fishery, significantly
more takes by sea lions occurred during the non-
Weise and Harvey: Impact of Zolophus califormanus on salmon fisheries
691
401
^^ Breeding
1997
30
l.. —i Nonbreeding i
20
pC-,
r1!
10'
0
40-
J 1 li ! ■
CD
a
S 30-
CD
Q.
c
c
m
~"
1998
_°- 20-
CD
CT
ro
c 10
CD
u
o>
0-
0
40-
\
i
i
1999
30
20
10
i
'
rh
0
■ _^ ^
Commercial Charter Skiff
Figure 4
Mean percentage of fish taken by pinnipeds
during the California sea lion (Zalophus califor-
nianus) breeding and nonbreeding seasons in
the commercial, commercial passenger fishing
vessel (CPFV), and personal skiff fisheries in
Monterey Bay, California, from 1997 to 1999.
Error bars indicate one standard error.
breeding season of 1997 (P<0.000), whereas in 1998
(P=0.158) and 1999 (P=0.358) there was no significant
difference. During all three years, surveys were con-
ducted on commercial, CPFV, and skiff fisheries during
August and September; however, there was little to no
salmon fishing effort because of the perceived sea lion
problem and because the remaining fishermen targeted
albacore tuna or rockfishes (or both).
Because of the different styles of hook-and-line fishing
in the commercial troll and recreational salmon fisheries,
sea lions were more likely to take fish below the surface
from commercial trollers but to take fish at and below
the surface from recreational vessels. In the commercial
fishery, according to dockside interviews and onboard
Commercial
CPFV
Skiff
Figure 5
Mean catch per unit of effort (mean number offish caught
per day! in commercial, commercial passenger fishing
vessel (CPFV). and skiff fisheries in Monterey Bay, Cali-
fornia, from 1997 to 1999. Error bars indicate one stan-
dard error.
surveys combined, percentages of takes by sea lions
below the surface of the water varied throughout the
season and were significantly greater than surface takes
in 1997 (P=0.001), 1998 (P<0.000), and 1999 (P<0.000;
Table 2). In contrast, in the recreational fishery the per-
centages of takes by sea lions below the water's surface
and at the surface varied by year. During 1997, greater
percentages of takes by sea lions occurred at the surface
than below the surface on CPFVs (P=0.082) and skiffs
(P=0.001; Table 2). Whereas in 1998, significantly great-
er percentages of takes occurred below the surface in the
CPFV <P<0.000) and skiff fisheries <P<0.000; Table 2).
And in 1999, no differences between surface and below
surface takes were detected for CPFV (P<0.972) or skiff
fisheries (P<0.310); however this lack of significance was
likely due to small sample sizes.
The catch per unit of effort (CPUE: number of fish
landed per boat per day) was significantly less in 1998
than in 1997 for the commercial (P<0.000), CPFV
(P=0.011), and skiff fisheries (P<0.000) in Monterey
Bay (Fig. 5). In 1999, significantly fewer fish were caught
than in 1998 and 1997 in the commercial (P<0.000) and
CPFV (P<0.000) fisheries; however, there was no signifi-
cant difference in the skiff fishery. The percentage of the
CVI abundance for chinook salmon taken by sea lions
from 1997 to 1999 ranged from 1.4% to 6.2% (Table 3).
From 1997 to 1999, commercial fishermen lost an
estimated $22,333-$60,077 of gear, and $224,011-
$504,548 worth offish as a result of interactions with
sea lions (Table 4). The recreational fisheries lost be-
tween $172 and $18,533 worth of gear as a result of sea
lion interactions from 1997 to 1999. Estimates of gear
and fish loss were extrapolated from observed losses to
total losses based on percentages of the fisheries that
were sampled. Gear types varied among commercial
692
Fishery Bulletin 103(4)
Table 3
Estimates of the pinniped predation index derived from estimates of observed takes of salmon by sea lions iZalophus California-
nus) in Monterey Bay in relation to the California Central Valley ehinook abundance index from 1997 to 1999. Data for Central
Valley ehinook abundance index were obtained from Pacific Fisheries Management Council, 1999.
Estimated pinniped takes
Year Commercial Recreational
Total (Ocean + river totals) index (%)
1997 24,258 14,576
1998 40,585 9868
1999 8780 269
24,258 1,055,300 2.2
40.585 611,800 6.2
8780 636,500 1.4
Table 4
Estimates of monetary impact of California sea 1
on interactions
with commercia
and recreational sa
mon fisheries resulting in
gear and fish loss
in Mont
erey Bay from 1997 to
1999. Recreational fishery includes commercial
passenger fishing vessels and
private skiffs. Va
ue of commercial fishery revenues were obtai
ned from the Ca
lifornia Department
of Fish and Game ocean
salmon database.
n/a=not
applicable.
Percentage fishery
Value of
Value of
Commercial
Equivalent percentage of
Fishery
Year
sampled
gear loss
fish loss
revenues
commercial revenue lost
Commercial
1997
6.3
$51,609
$375,470
$2,651,499
14.2
1998
10.9
$60,077
$504,548
$598,062
84.4
1999
8.6
$22,333
$224,011
$874,100
25.6
Recreational
1997
6.1
$18,533
n/a
n/a
n/a
1998
11.5
$16,485
n/a
n/a
n/a
1999
8.9
$172
n/a
n/a
n/a
and recreational fisheries, and gear cost for each fishery
varied greatly; therefore, an average estimate for each
gear type was used to estimate gear loss for commer-
cial and recreational fisheries. Total revenue losses as
a result of fish taken by sea lions in the commercial
fishery were equivalent to between 14.2% and 84.4% of
the total salmon fishery revenues.
Discussion
Conflicts between pinnipeds and fisheries are well docu-
mented in California (Briggs and Davis, 1972; Fiscus,
1979; Ainley et al., 1982; Miller et al.6; Hanan et al.,
1989; Beeson and Hanan1; NMFS2). California sea lions
have been the primary pinniped species involved in
taking fish in ocean commercial and recreational salmon
fisheries (Miller et al. 6; Hanan et al., 1989; Beeson and
Hanan1). In comparing present results and past studies
it is imperative to distinguish between the percentage
of salmon taken by pinnipeds relative to the number of
legal size fish landed (i.e. legal catch) and number of pin-
niped takes relative to total number offish hooked (i.e.,
total catch). The former value inflates percentages by
not including undersize fish caught, whereas the latter
includes all fish hooked in the calculation and assumes
all fish, regardless of size, have an equal probability of
being taken by sea lions.
Dockside surveys were representative of the mag-
nitude of interactions between sea lions and salmon
fisheries because there were no significant differences in
mean percentages of takes by sea lions between onboard
and dockside surveys. Onboard surveys alone would not
provide sufficient samples to adequately assess levels
of interactions between sea lions and salmon fisheries;
conversely, the validity of dockside surveys alone would
be questionable because of biases associated with dock-
side surveys. Biases included fishermen not providing
truthful information, fishermen avoiding the survey,
fishermen not answering all questions, and not all fish-
ermen returning to the docks. Combining onboard and
dockside surveys enabled us to verify dockside findings,
obtain sufficient levels of sampling for comparisons,
and directly observe and understand the nature of the
interactions.
The percentage of hooked salmon taken by sea lions
in the commercial salmon fishery in relation to the legal
catch has increased by at least 8% since the 1970s and
1980s. Briggs and Davis (1972) reported that California
sea lions took 4.1% of all salmon hooked during the
Weise and Harvey: Impact of Zalophus caltfornianus on salmon fisheries
693
1969 commercial and sport salmon season. Miller et al.6
reported that in 1981 sea lions took 3.0% of the legal
catch during commercial salmon activities, and Beeson
and Hanan1 found that sea lions took 159r of the legal
catch in commercial fisheries in 1995. In Monterey Bay
in 1997, 12.5% of the legal catch was taken by sea lions,
71.1% in 1998. and 11.1 % in 1999.
Predation levels in the CPFV fishery have increased
by at least 8% since 1983, and approximately 3% since
1995. Miller et al.6 reported predation rates of 5.2 %
for the CPFV legal catch in Monterey Bay, and Beeson
and Hanan1 reported predation rates of 10.5 % of the
legal catch for the recreational fishery in 1995 (CPFV
and private skiff combined). In Monterey Bay, 13.7 %
of the legal catch was taken by sea lions in 1997, 26.3
% in 1998, and 2.5 % in 1999.
In the skiff portion of the recreational salmon fish-
ery, predation of the legal catch has increased by at
least 26% since 1983, and 17% since 1995. Miller et al.6
reported predation levels of 1.4% on the legal catch for
skiff fisheries in Monterey Bay, and Beeson and Hanan1
reported predation levels of 10.5% on the legal catch for
the 1995 recreational fishery season (CPFV and private
skiff combined). In Monterey Bay, predation on the le-
gal catch was 27.7% in 1997, 31.0% in 1998, and 5.1%
in 1999. Skiff fishermen typically fish in large groups
called "the fleet." Sea lions had a greater probability
of getting a hooked salmon when there were greater
numbers of hooks in the water; therefore, sea lions
most likely target a fleet of fishing boats. Skiff fisher-
men caught fewer fish than did commercial or CPFV
fishermen, but lost a proportionally greater number of
fish to sea lions.
The greatest levels of sea lion predation in commer-
cial and recreational fisheries occurred in spring when
the greatest numbers of adult male sea lions were mi-
grating south to breeding rookeries in southern Cali-
fornia and Baja California, Mexico. In 1997 and 1999,
predation levels dropped significantly in June and July
following a high level in May, corresponding to de-
clines in numbers of sea lions in Monterey Bay as males
headed southward to breeding colonies (Weise, 2000).
In 1998, loss of catch to sea lions was greatest in May;
slight decreases occurred in percentages of fish taken
during June and July because the decline in numbers
of adult male sea lions during the breeding season was
far less and shorter in duration than in June and July
of 1997 and 1999.
We concluded that adult male sea lions took the ma-
jority of hooked fish because animals identified taking
fish during boat surveys were almost exclusively adult
male sea lions and percentages of fish taken by sea
lions were less during the sea lion breeding season.
Briggs and Davis (1972), Miller et al. 6, and Beeson
and Hanan1 also reported greater numbers of salmon
taken in spring (the nonbreeding season) in the com-
mercial and recreational salmon fisheries. Loss of catch
to sea lions would most likely be greater during the
northward migration of male sea lions because greater
numbers of animals would be in the Monterey Bay re-
gion; however, fishing effort declined sharply and the
commercial season was closed during a portion of that
period in 1997.
Sea lions took most salmon below the water's surface
in the commercial fishery and both at and below the
surface in recreational fisheries. Commercial fisher-
men lost fish below the surface as a result of the large
amount of trolling gear used, and the time required
for pulling gear when fish were hooked. Commercial
fishermen typically need five to 10 minutes, and as
long as 20 minutes to pull hooked fish from the water,
allowing ample time for sea lions to take fish. Before
the 1994 amendments to the MMPA, sea lions were
legally killed for endangering commercial catches, gear,
and fishermen, and are still at risk for harassment for
taking fish off hooks today. Consequently, most fish in
the commercial fishery are taken below the surface and
consumed at the surface some distance from the boat
because of a combination of the time required to bring
a fish to the surface and the threat of harassment. Less
gear and perhaps different types of gear that can bring
a fish to the surface faster may reduce the number of
takes below the surface and overall predation levels. In
recreational fisheries, fishermen typically used rod and
reel, which allowed fish to be reeled in within minutes.
It has been illegal for recreational fishermen to harass
or kill sea lions since the passage of the MMPA in 1972;
therefore it is not uncommon to see sea lions swimming
next to recreational boats in close pursuit of fish that
are pulled from the water or that are taken just before
they are netted.
Increased depredation levels in the commercial and
recreational salmon fisheries in 1998 were most likely
the result of the large El Nino Southern Oscillation
(ENSO) event that occurred during 1997-98. The 1997-
98 ENSO event created large anomalies in physical and
biological conditions in the coastal waters off Califor-
nia resulting in above average seasonal norms in sea
surface temperatures and large displacements in the
distribution of many fish species (Lynn et al., 1998).
A combination of factors during the large ENSO event
contributed to increased predation on salmon catches.
These factors included shifts in sea lion prey composi-
tion, decreases in sea lion prey populations, increases in
number of sea lions in the region, decreases in fishing
effort by commercial and recreational salmon fishermen,
and decreases in number of salmon landed. Intensified
depredation of catch has been reported during past
ENSO events by commercial gillnet fishermen (Beeson
and Hanan1).
Increased intensity in depredation of hooked fish by
pinnipeds during ENSO events may be indicative of
decreased foraging success resulting from shifts in prey
availability and abundance. A significant shift in sea
lion diet occurred between 1997 and 1998 from market
squid, northern anchovy, and Pacific sardine to Pacific
sardine and anchovy (Weise, 2000). Concurrently, com-
mercial catches of squid, hake, and herring, common
prey of sea lions, were low or virtually nonexistent from
the fall of 1997 through the summer of 1998 (CalCOFI,
694
Fishery Bulletin 103(4)
1999). In May 1998, the catch rate for pelagic-young-
of-the-year rockfish was the lowest in the history of
tri-annual rockfish surveys (Lynn et al., 1998). It is,
therefore, reasonable to assume that sea lions were
probably nutritionally stressed by the lack of prey and
change in prey species and found a hooked salmon an
attractive and easy meal.
Mean numbers of California sea lions recorded dur-
ing the northward migration in summer and autumn
of 1998 were approximately 2000 individuals greater
than in the summer and autumn of 1997 and 1999,
most likely in response to poor foraging conditions in
southern California resulting from ENSO conditions
(Weise, 2000). During the 1983 and 1992 ENSO events,
numbers of sea lions increased along the central Cali-
fornia coast owing to the enhancement of the normal
northward migration of sea lions resulting from poor
food availability in the Southern California Bight (Syde-
man and Allen, 1999). During the 1983-84 ENSO,
older juvenile sea lions migrated in greater than usual
numbers from southern to central California (Trillmich
et al., 1991). Greater numbers of female sea lions were
counted on Ano Nuevo Island in summer and fall 1998,
presumably in response to poor foraging conditions in
southern California (Morris, unpubl. datas). Increases
in numbers of sea lions in Monterey Bay during 1998
were most likely due to increases in numbers of juve-
niles and adult females that moved northward because
of the lack of schooling prey species in southern Cali-
fornia resulting from the ENSO.
Presumably as a result of ENSO conditions, total
landings of salmon and the catch per unit of effort in
commercial and recreational fisheries were significantly
less in 1998 than in 1997. During our sampling effort
in 1998, approximately 2000 fewer fish were landed
in commercial and recreational fisheries than in 1997,
although approximately double the percentages of fish-
eries (total salmon landings) were sampled dockside.
Numbers of salmon landed in Monterey Bay in 1998
decreased by 59.6% in the commercial fishery and 49.4%
in the recreational fishery (PFMC4). In California dur-
ing 1998, numbers of salmon landed in the commercial
fishery were 55.7% less than in 1997, and 46.7% less in
the recreational fishery. In 1998, CPUE of the commer-
cial fishery declined proportionally more than in other
fisheries, which corresponded to proportionally greater
percentages of fish taken by sea lions. In Monterey Bay,
numbers of angler trips in 1998 declined by 38.6% in the
commercial fishery, and 39.9% in the recreational fish-
ery (PFMC4). Therefore, there were fewer boats actively
fishing, fewer fish being landed, and greater numbers of
sea lions in the area, under these conditions, when a fish
was hooked, it was more likely to be depredated.
Conversely, in 1999 the depredation levels in the com-
mercial and recreational salmon fisheries in Monterey
K Morris, P. A. 1999. Abstract. 13th Biennial conference
on the biology of marine mammals; Maui, HI, 131 p. The
Society for Marine Mammology. http://www.marinemam-
mology.org/
Bay were significantly less as a result of cool and highly
productive La Nina oceanographic conditions. Follow-
ing one of the strongest ENSO events on record during
1997-98, there was a dramatic transition to highly pro-
ductive cool-water La Nina conditions and anomalous,
upwelling-favorable, wind forcing along the West Coast
(Schwing et al., 2000). Upwelling anomalies off the
central California coast during 1999 were the greatest
in the 54-year record of the upwelling index (Schwing
et al., 2000). Record harvest levels of Pacific sardines
(CalCOFI, 2000) and greater frequency of occurrence
of sardine in the diet of sea lions in central California
during the 1999 La Nina (Weise, 2000) indicated that
ample prey fishes were available for foraging California
sea lions; therefore, depredation pressure on the salmon
fisheries was reduced.
Monterey Bay was selected for the present study be-
cause it experienced the greatest levels of depredation
during the 1995 commercial and recreational fisher-
ies season (Beeson and Hanan1). Although Monterey
Bay experienced increased levels of pinniped predation
in recreational fisheries in 1997 and commercial and
recreational fisheries in 1998, these levels were prob-
ably not representative of the whole California coast
but were more likely the worst-case scenario. Pinniped
depredation may be increasing in other areas along the
California coast as the sea lion population increases,
but probably not to the degree that was observed in
Monterey Bay. Pinniped predation of hooked fish in
salmon fisheries is probably spatially and temporally
variable. Whereas this variability complicates evaluat-
ing pinniped impacts on fisheries, it is important for
fishery managers to take this variability into account.
Estimated levels of depredation reported for the com-
mercial and recreational salmon fisheries in Monterey
Bay may be affected by many assumptions. Lack of
direct validation for information received during dock-
side surveys had unknown impacts on estimates of
predation levels, but concurrent onboard sampling ap-
peared to alleviate this bias. Commercial and private
skiff salmon boats bypass the sampling docks when
no fish are landed or they dock in a harbor slip. Boats
that bypass sampling docks may have no fish because
of predation by sea lions, and not sampling these boats
would result in underestimates of predation levels, but
the magnitude of this decrease was difficult to evaluate.
Surveys of fishermen were limited by crew cooperation
and therefore, not all fishing styles and locations were
sampled. The lack of some data would have an impact
on predation levels. Surveys of fishermen also were
limited to boats fishing for one day because boats fish-
ing for multiple days often fished outside the study area
during the course of a trip; however, boats fishing for
multiple days were surveyed at dockside so that any
biases of onboard samples would have been detected in
comparisons of dockside and onboard predation levels.
Depredation of salmon by California sea lions in Mon-
terey Bay could negatively impact salmon populations
along the Central California coast. Pinniped depre-
dation of hooked salmon from the California Central
Weise and Harvey. Impact of Zalophus califormanus on salmon fisheries
695
Valley chinook salmon population went from a low of
approximately 1.4% during a non-ENSO year to an
estimated 6.2% during an ENSO season. High harvest
levels coupled with high natural depredation of salmon
during an ENSO year could be devastating for the Cen-
tral Valley Chinook salmon population. Further, when
sea lions take fish in the fishery, fishermen continue to
fish to replace depredated fish, further impacting the
salmon population. Hooked salmon lost to sea lions are
losses to the population and need to be considered when
determining allotments, quotas, and area closures. To
better estimate impacts of sea lion predation on the
CVI, concurrent studies of sea lion and salmon fishery
interactions and sea lion food habits need to be conduct-
ed along the entire Central California coast, including
Half Moon Bay, San Francisco Bay, and the Farrallon
Islands. Sea lions are only one of many natural preda-
tors of commercially important fish species. Identifying
other natural predators and assessing their impact on
prey populations is difficult but necessary for effective
fisheries management.
It is likely that only a small proportion of the sea lion
population, particularly adult males, were responsible
for salmon taken off hooks in salmon fisheries. Percent-
ages of fish taken off the hook declined in all years
when adult males moved south during the breeding sea-
son in June and July. However, greater percentages of
takes occurred in the fisheries in August and Septem-
ber when lesser numbers of adult male sea lions were
present in the region. On any given fishing day peak
numbers of sea lions were counted at haul-out sites
from late-morning to early afternoon, which is also the
period when most fishing occurred (Weise, 2000). Miller
et al.6 suggested that the total damage to fisheries by
California sea lions was not proportional to the number
of sea lions in the area. It is likely that takes on a given
day in Monterey Bay were repeat occurrences by the
same animals. We agree with DeMaster et al. (1982)
that a reduction in the number of animals or culling
of the population would probably not reduce sea lion
depredation levels unless the few animals responsible
were identified and removed. Instead, there is a need
for nonlethal deterrents to keep sea lions from taking
hooked fish in open-ocean fisheries. A change in types of
fishing gear, a limit in the amount of gear in the water,
use of various harassment techniques, as well as area
closures and a tolerance for sea lion predation most
likely encompass other possible management options.
An increasing sea lion population and increased inter-
actions with salmon fisheries resulting in salmon and
gear losses will certainly affect individual fishermen
negatively and possibly California's economy (Beeson
and Hanan1). Comparisons of economic losses between
years and among studies must consider average fish
weight, exvessel price per year, and definitions of fish-
ing regions. For example, if greater numbers of fish
were lost in a given year but exvessel prices were low,
the overall economic impact would be less than during
a year when fewer fish were taken but the exvessel
prices were high.
In past studies, all ports in California were surveyed,
and impacts were analyzed by port, but these studies
encompassed different fishing areas under the same port
names. For example, Miller et al.fi estimated annual
losses resulting from sea lion interactions in 1980 at
$274,000 for California, and an estimated $21,536 for
Monterey Bay. It is unclear, however, if these figures
included fishing areas south of Monterey, such as Morro
Bay, and fishing areas north, such as Half Moon Bay.
Beeson and Hanan1 estimated 86,900 fish or $1,734,000
was lost in 1995 because of sea lion interactions, and
48,000 fish were taken in Monterey, representing ap-
proximately $960,000. Beeson and Hanan1 included the
Port of Princeton in Half Moon Bay in figures reported
for Monterey. Therefore, it was not possible to make
direct comparisons among studies, but it appears that
economic losses per individual fisherman have increased
since the 1980s and will probably continue to increase
if the sea lion population and interactions with salmon
fisheries increase. Assessment of economic impacts of
salmon fisheries in Monterey Bay in the present study
was limited to gear and fish loss; however impacts are
most likely widespread. For example, during the salmon
season when interactions with sea lions are great, CPFV
operators report that customers will cancel or postpone
trips, which decreases the amount of money infused into
the local economy from trip expenditures, including hotel
stays, restaurants meals, and gas. Estimating the eco-
nomic impact of sea lion interactions on the local economy
of Monterey Bay was beyond the scope of our study.
Discussions about the competition between sea li-
ons and fisheries tend to arouse controversy because of
the complex mix of biological, economic, social, politi-
cal, and moral factors involved (Harwood and Croxall.
1988). Fishermen claim regularly that their activities
are regulated, whereas predation by marine mammals
is unrestricted (Harwood, 1992). Although losses in
Monterey Bay in 1998 were most likely anomalously
large because of ENSO conditions, this anomaly offered
little reassurance to those fishermen whose livelihoods
were threatened. Growing sea lion populations have
undoubtedly intensified competition with fisheries, but
greater fishing effort, more sophisticated fish equipment
and fisheries methods, and less than rigorous fisheries
management is equally responsible. Segments of the
American public find marine mammals appealing and
demand that populations be protected; whereas other
segments demand protection from economic ruin result-
ing from marine mammal-fishery interactions. Clearly,
demands from both segments of the public must be ad-
dressed (Everitt and Beach. 1982). Continued research
to assess and refine our understanding of food habits of
marine mammals is essential, and incorporating this
information into fisheries management is equally impor-
tant. When conflicts between fisheries and marine mam-
mals are identified, population management strategies
and nonlethal deterrent solutions need to be developed.
Any management solutions need to consider not only the
specific interactions but also the ecosystem as a whole
and the viewpoints of all segments of the public.
696
Fishery Bulletin 103(4)
Acknowledgments
This study could not have been completed without all
the help from MLML students and Bird and Mammal
Laboratory interns. We thank Tomoharu Eguchi, Tony
Orr, Tony Alisea, Laird Henkel, Stori Oates, Jeff Field,
Joe Bizarro, Julie Neer, Scott Benson, Denise Greig,
Sarah Wilkin, Anu Kumar, Aviva Barsky, Meisha Key,
Sean Lema, Lydia Neilson, Guido Parra, Mimi Reyes,
Greg Cunningham, Sharon Updike, Michelle Garcia,
Inger-Marie Laursen, Cina Loarie, Judd Weiss, Kate
Willis, and Wendy Cover for the countless hours spent
undertaking dockside and onboard surveys. Scott Davis
was instrumental in aerial photography for aerial sur-
veys. We extend special thanks to the commercial, char-
ter boat, and personal skiff fishermen, deckhands, and
captains for their cooperation; this research would not
have been possible without their help. This project was
supported by funding from the Fishermen's Alliance of
California, Monterey Bay Chapter, The David and Lucille
Packard Foundation, and the National Marine Fisheries
Service. We are grateful for constructive comments by
Gregor Cailliet, Robert DeLong, and two anonymous
reviewers.
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697
Abstract — Growth of a temperate reef-
associated fish, the purple wrasse (iVo-
tolabrus fucicola), was examined
from two sites on the east coast of
Tasmania by using age- and length-
based models. Models based on the
von Bertalanffy growth function, in
the standard and a reparameterized
form, were constructed by using oto-
lith-derived age estimates. Growth
trajectories from tag-recaptures were
used to construct length-based growth
models derived from the GROTAG
model, in turn a reparameteriza-
t ion of the Fabens model. Likeli-
hood ratio tests (LRTs) determined
the optimal parameterization of the
GROTAG model, including estima-
tors of individual growth variability,
seasonal growth, measurement error,
and outliers for each data set. Growth
models and parameter estimates were
compared by bootstrap confidence
intervals, LRTs, and randomization
tests and plots of bootstrap param-
eter estimates. The relative merit of
these methods for comparing models
and parameters was evaluated;
LRTs combined with bootstrapping
and randomization tests provided
the most insight into the relation-
ships between parameter estimates.
Significant differences in growth of
purple wrasse were found between
sites in both length- and age-based
models. A significant difference in
the peak growth season was found
between sites, and a large differ-
ence in growth rate between sexes
was found at one site with the use
of length-based models.
Estimates of growth and comparisons
of growth rates determined from
length- and age-based models for populations
of purple wrasse (Notolabrus fucicola)
Dirk C. Wetsford
Jeremy M. Lyle
University of Tasmania
Tasmanian Aquaculture and Fisheries Institute
Marine Research Laboratories
Nubeena Crescent
Taroona, Tasmania 7053, Australia
E-mail address (for D. C Welsford) Dirk Welsford g utas edu au
Manuscript submitted 25 May 2004
to the Scientific Editor's Office.
Manuscript approved for publication
10 April 2005 by the Scientific Editor.
Fish. Bull. 103:697-711 (2005).
Methods for estimating growth in wild
fish stocks derive largely from two
sources: 1) age-based models, such
as the von Bertalanffy growth func-
tion (VBGF), from data for length-
at-age. where fish ages are known
or estimated from scales, otoliths,
and other hard parts; and 2) length-
based models, from recapture data
from tagged fish to describe a growth
trajectory over time at liberty (e.g.,
Fabens, 1965), or analysis of modal
progressions in length-frequency data
(e.g., MULTIFAN, Fournier, et al.,
1990). Many of these models seek to
characterize growth of the population
in terms of the three standard von
Bertalanffy parameters, viz. lx, the
theoretical asymptotic mean length; k,
the growth rate coefficient; and r0, the
theoretical age at length zero.
Despite its wide use in descriptions
of fish growth, the standard VBGF is
often criticized because the function's
parameters may represent unreason-
able extrapolations beyond available
data and hence lack biological rele-
vance (e.g.. Knight, 1968; Roff, 1980;
Francis, 1988a; 1988b), estimates of/,
produced by standard length- and age-
based versions of the model lack math-
ematical equivalence (e.g., Francis,
1988b; 1992), the statistical properties
of the parameters make comparisons
between samples difficult (Ratkowsky,
1986; Cerrato, 1990; 1991), and indi-
vidual variability introduces biases
in parameter estimates (Wang, et al.,
1995; Wang and Thomas, 1995; Wang,
1998; Wang and Ellis, 1998).
These criticisms have led to various
reparameterizations of the VBGF (see
Ratkowsky, 1986; Cerrato, 1991 for
examples). Analyses of reparameter-
izations for age-based VBGFs indicate
that the inclusion of parameters that
are expected lengths-at-age, for age
classes drawn from the data set, dra-
matically improve the statistical prop-
erties of the model (Cerrato. 1991) and
also result in parameters that have
direct biological interpretation. Repa-
rameterizations that fit this criterion
include the reparameterization of the
Francis (1988b) model for length-at-
age data, and GROTAG, a repara-
meterization of the Fabens model from
tagging data with expected growth
rates for length as parameters (Fran-
cis. 1988a). GROTAG in particular
has the advantage of being readily
parameterized to include seasonal
growth terms, and, through the ap-
plication of a likelihood function, can
include estimators of measurement
error, individual growth variability,
and the proportion of outliers in a
data set. It has been used to produce
growth estimates for cartilaginous
fishes (Francis and Francis, 1992;
Francis, 1997; Francis and Mulligan,
1998; Simpendorfer, 2000; Simpendor-
fer, et al., 2000), bony fishes (Francis,
1988b; 1988c; Francis, et al.. 1999),
and bivalve mollusks (Cranfield, et
al., 1996). Fitting of any growth mod-
el with maximum likelihood methods
also permits straightforward appli-
cation of LRTs in order to compare
parameter estimates, and to deter-
698
Fishery Bulletin 103(4)
mine optimal parameterization of models (Kimura, 1980;
Francis, 1988a). Computationally intensive methods
such as bootstrapping and randomization tests provide
a nonparametric method for approximating probability
distributions of growth parameter estimates (Haddon,
2001), for generating confidence intervals to test for
differences between parameter estimates, and for visu-
alizing relationships between parameters (Mooij, et al.,
1999). Drawing together these methods, it is possible to
fit growth models, to produce parameter estimates that
are biologically interpretable, and to use tests that are
robust for comparing populations.
The purple wrasse (Notolabrus fucicola) is a gono-
choristic, site-attached, reef-associated fish, common on
moderate to fully exposed coasts in southeastern Aus-
tralia and New Zealand (Russell, 1988; Edgar, 1997).
Both Notolabrus fucicola and its Australian congener,
the blue-throated wrasse (N. tetricus), are large benthic
carnivores that play a significant role in the trophic
dynamics of temperate reef systems (Denny and Schiel,
2001; Shepherd and Clarkson, 2001).
The development of a live fishery for N. fucicola and
N. tetricus in southeastern Australia has made temper-
ate wrasses increasingly important economically (Lyle1;
Smith, et al.2).
Most previous attempts to describe the growth of
N. fucicola (Barrett, 1995a; 1999; Smith, et al.2) have
been compromised by small sample sizes, lack of age
validation, and the use of unsuitable statistical models
to compare length-at-age between populations. Ewing et
al. (2003) recently validated an aging method and devel-
oped growth models for JV. fucicola, combining samples
from many sites from eastern and southeastern Tasma-
nia. Our study describes site- and sex-specific age- and
length-based models for this species. We also compare
methods for examining differences in growth model
parameter estimates, such as confidence intervals and
randomization tests based on bootstrap estimates, plots
of bootstrap estimates, and LRTs where comprehensive
coverage of age and length data is unavailable — a situ-
ation commonly faced in fisheries.
Materials and methods
Field methods
Notolabrus fucicola were trapped and tagged at two sites
on the east coast of Tasmania. Trapping was conducted
1 Lyle, J. M. 2003. Tasmanian scalefish fishery— 2002. Fish-
ery Assessment Report, 70 p. Tasmanian Aquaculture and
Fisheries Institute, Marine Research Laboratories, Univ. Tas-
mania, Nubeena Crescent, Taroona, Tasmania 7053, Australia.
- Smith, D. C, I. Montgomery, K. P. Sivakumaran, K. Krusic-
Golub, K. Smith, and R. Hodge. 2003. The fisheries biol-
ogy of bluethroat wrasse (Notolabrus tetricus) in Victorian
waters. Draft Final Report, Fisheries Research and Devel-
opment Corporation No. 97/128, 88 p. Marine and Freshwa-
ter Resources Institute, 2a Bellarine Highway, Queenscliff,
Victoria 3225, Australia.
at 1-2 month intervals, between July 1999 and April
2001 at Lord's Bluff (42. 53°S, 147.98°E), and between
July 2000 and March 2001 at Point Bailey (42.36°S,
148.02°E). Standard T-bar tags were inserted between
the pterygiophores in the rear portion of the dorsal fin.
Total length of each fish was recorded prior to release.
Because N. fucicola display no external sexual charac-
ters, sex of fish could only determined by the presence
of extruded gametes if fish were running ripe when cap-
tured, or by dissection at the conclusion of the study.
At the conclusion of the tag-recapture study, each site
was fished intensively. Recaptured tagged fish were eu-
thanized by immersion in an ice-slurry. Fish captured
at Lord's Bluff were measured immediately after sacri-
fice; gonads were dissected to determine sex, and sagit-
tal otoliths were collected. Untagged fish were returned
immediately; therefore otoliths that were analyzed came
from tagged fish only. All fish captured at Point Bailey
were processed in a similar fashion but were stored
frozen prior to examination.
Otolith preparation and interpretation
Sagittal otoliths were mounted in a polyester resin block,
and transverse sections (250-300 ,um thick) were cut
through the primordium with a lapidary saw. Sections
were mounted on a slide and examined under a binocular
microscope at x25 magnification. The primary author
counted annuli and individuals were allocated to a year
class, and fractional ages were assigned based on an
arbitrary birthdate of 1 October, following the method
of Ewing et al. (2003).
To determine if any significant differences existed
within or between reader estimates, a random sub-
sample of 55 otoliths, from both sites, was re-aged by
the primary reader (DW) and another experienced oto-
lith reader (GE). The frequency distribution of ages in
each population was then compared with a Kolmogo-
rov-Smirnov test. Consistency of age estimates was
also compared by using age bias plots (Campana, et
al., 1995) and the index of average percent error (IAPE
serisu Beamish and Fournier, 1981).
Preliminary inspection of the length data for thawed
individuals from Point Bailey revealed many negative
growth increments when compared to length data col-
lected from recaptures prior to the conclusion of field
sampling. Repeated measurements of N. fucicola, con-
ducted independently of our study, have shown length
changes in the order of 8-9% in frozen and thawed
individuals compared to measurements from individu-
als alive or freshly euthanized (G. P. Ewing, unpubl.
data3). Consequently, measurements taken from frozen
fish were deemed to be incompatible with measure-
ments taken from fresh fish and were removed from
the tagging and otolith data sets. Where data from
Ewing, G. P. 2002. Unpubl. data. University of Tas-
mania, Tasmanian Aquaculture and Fisheries Institute,
Marine Research Laboratories. Nubeena Crescent, Taroona,
Tasmania 7053, Australia.
Welsford and Lyle: Estimates of growth of Notolabrus fuacola from length- and age-based models
699
multiple recaptures allowed, the initial length and pen-
ultimate length measurement and their corresponding
dates were used in length-based analyses at this site.
Individual length-at-age estimates were also adjusted
according to the date of any previous reliable length
record.
Age-based growth modeling
Data consisted of ages estimated from otoliths (T) and
lengths at final recapture (or last reliable length mea-
surement at Point Bailey) (L). Kolmogorov-Smirnov tests
were conducted between sites and between sexes within
sites to determine if there were differences between
the proportional frequency distributions of fish lengths
in length-at-age data sets. Growth was modeled by
using the standard von Bertalanffy growth function
(VBGF):
L = ljl-e
-k(T-t«h
(1)
The VBGF for the two sites and sexes within sites
were modeled separately (Table 1). Fish for which sex
could not be determined were not included in the sex-
specific models.
A reparameterized version of the VBGF was also es-
timated from Equation 4 in Francis (1988b):
L = L
[ll.-lT][l-r-
']
1-r2
where r ■
(2)
(3)
and where lx, lv and lm, are the mean lengths at ages t,
v, and co=(t+u)/2 — ages chosen from within the observed
range within the data set. The values chosen for all the
otolith-based models were t=4, oj=7 and o=10 years,
encompassing the range of ages represented in the data
sets for both sites. Estimates of these parameters have
a direct biological meaning and have more statistically
favorable properties than the standard VBGF para-
meters lv, k, and t0 (Francis, 1988b; Cerrato, 1991).
Models were fitted by minimizing a likelihood func-
tion and assuming normally distributed residuals
(Eq. 4):
-A = -X,ln
^exp
2a1
(4)
The measured length of the (th fish, Lr has its corre-
sponding expected mean length at age ii,, as determined
from Equation 1 or 2 above, where ;<, is normally distrib-
uted and has a standard deviation a. The quality of the
fits was gauged visually in the first instance by the lack
of trends in plots of residuals against length-at-age.
To further investigate each model, each data set was
bootstrapped 5000 times. The bootstrapping procedure
involved randomly resampling, with replacement, from
the original data set, and then fitting the VBGF to this
new data set, thereby generating new estimates of all
model parameters (Haddon, 2001).
Based on the percentile distribution of bootstrap
parameter estimates, 95% confidence intervals (CIs)
around the original sample estimates were calculated for
each VBGF parameter. To account for any skew in the
distribution of bootstrap parameter estimates, a first-or-
der correction for bias of CIs was performed, where boot-
strap percentiles used to estimate the CIs were adjusted
on the basis of the proportion of bootstrap estimates less
than the original estimate (Haddon, 2001).
To determine whether growth showed any site or sex-
within-site (referred to as "sex-") differences, we com-
pared the overlap of first-order corrected CIs and plots
of bootstrap estimates. Simple comparison of CI overlap
as a test for parameter difference has been shown to be
overly conservative (Schenker and Gentleman, 2001).
Hence the null hypothesis of no difference was accepted
in the first instance only in cases were the amount of
overlap was obviously large. In cases were the extent
of overlap was small, and the chance of incorrectly ac-
cepting the null hypothesis existed, a randomization
test was performed. This test involved constructing the
distribution of the difference between the estimates of
the parameter of interest. Parameter estimates were
randomly selected with replacement from each set of
bootstrap estimates for the two populations, and the dif-
ferences were determined for these 5000 random pairs.
Then a 95% first-order corrected CI was constructed as
above, and the null hypothesis was rejected only if the
CI did not include zero. Likelihood ratio tests were also
conducted on the VBGFs and individual parameters
(Kimura, 1980).
Length-based growth modeling
Growth trajectories consisted of the initial length (L,),
time at first capture (Tj), time at final recapture (or pen-
ultimate recapture at Point Bailey) (T., ), change in length
from the first to the final recapture (AL), and duration in
years between capture and last recapture (AT). T1 and
T., were measured in years from an arbitrarily chosen
point, 1 January 1999 — the first day in the earliest
year in which tagging was conducted. For individuals
recaptured more than once, only information relating to
the initial and final captures was used in the analyses.
This approach maximized the time between recaptures
for any fish, increasing the chance of detecting growth,
and gave equal weight to each fish sampled.
Because the two sites were sampled over different
time periods, only samples from Lord's Bluff that were
taken at the same time as samples at Point Bailey were
considered for the purposes of between-site growth com-
parisons (Table 1). The resulting data set, designated
LBres, reduced potentially confounding effects of longer
sampling durations at Lord's Bluff.
700
Fishery Bulletin 103(4)
Table 1
Main model types (GROTAG and von Bertal
anffy growth
function [VBGF])
data sets, and sample sizes used to
produce estimate
s of growth for Nntolab
rus fucicola.
LB= Lord's Bluff.
full data set; LB = Lore
's Bluff, only
fish captured over dates equivalent to the Point Bailey
sample; PB=Point Bailey, full data set; ?
=males only;
5 5 =females only;
;? = sample size. The asterisk refers to
one individual in
this data set that was identified as an
outlier during model parameterization and
was excluded
from bootstrapping.
Model type
Data set
Total n
GROTAG
LBres
174
PB
263
LBSS
103
LB9S
69*
PBSi
96
PBS 5
89
VBGF
LB
101
PB
178
LB<J6"
47
LB2 2
54
PBc?<?
68
PBS?
104
A Kolmogorov-Smirnov test was conducted to deter-
mine whether differences existed in the proportional
frequency distributions of lengths of fish at first capture
(Lj) between sites and between sexes within sites.
Growth was modeled by using GROTAG (Eqs. 2 and 4
in Francis [1988a]), a reparameterization and extension
of the Fabens growth model for tag-recapture data that
incorporates seasonal growth:
Table 2
Parameters estimated in the five GROTAG models fitted
to each tag-recapture data set to evaluate optimal model
parameterization.
GROTAG model
Parameters estimated
ga>gpv>P
ga,gp> v,p,u,w
ga.glS,v.p.s,m
ga'gp v- u< "'• s' '"
ga,gp, v,p, u. w,s,m
ing no seasonal growth through to u=l indicating the
maximum seasonal growth effect, i.e., where growth
effectively ceases at some point each year).
The model was fitted by minimizing negative log-like-
lihood (-A) function (Eq. 9 in Francis [1988a]). For each
data set, made up of i : = 1 to n growth increments:
A = X,ln[(l-p)A,+p/i?],
where A, =exp
-^(AL,-^, -m)2/(CT,2 + s2)
[2^(cr,2 + s2)Ji
(7)
(8)
The measured growth increment of the ;'th fish, AL;,
has its corresponding expected mean growth increment,
Hr as determined from Equation 5 above, where ,i(; is
normally distributed with standard deviation or In this
study, a, was assumed to be a function of the expected
growth increment j.it (Eq. 5, Francis, 1988a):
m-
(9)
AL-
Pga-agp
Sa-gp
a-p )
AT-Ht
sin\27r(T-w)] „
where 0, = u — - fori = 1,2.
2/r
(5)
(6)
The parameters gu and g.t are the estimated mean an-
nual growth (cm/yr) of fish of initial lengths a cm and
P cm, respectively, where a<p. The reference lengths a
and p were chosen such that the majority of values of L1
in each data set fell between them (Francis, 1988a). For
site-specific estimates of growth, a and p were set at 20
and 30 cm, respectively, whereas p was set at 28 cm for
sex-specific models. Seasonal growth is parameterized
as w (the portion of the year in relation to 1 January
when growth is at its maximum) and u (u = 0 indicat-
where v is estimated as a scaling factor of individual
growth variability, assuming a monotonic increase in
variability around the mean growth increment as the
size of the increment increases.
In its fully parameterized form, the likelihood func-
tion estimates the population measurement error in AL
as being normally distributed, and having a mean of m
and standard deviation of s. To estimate the proportion
of outliers, Francis (1988a) also included p, the prob-
ability that the growth increment for any individual
could exist erroneously in the data set as any value,
within the observed range of growth increments R.
This enables the proportion of outliers to be identified.
Francis (1988a) suggested that an estimate of p>0.05
indicates a high level of outliers and therefore some
caution would be required in interpreting the overall
model fit.
The optimal model parameterization was determined
by fitting five different models, comprising different
Welsford and Lyle: Estimates of growth of Notolabrus fuacola from length- and age-based models
701
combinations of parameters (Table 2), with unfitted
parameters held at zero. A LRT was used to deter-
mine the improvement in model fit with the different
parameterizations (Francis, 1988a). For models with
an equal number of parameters, the model producing
the lowest negative log likelihood (-A) was considered
the best fit.
As with the otolith models, LRTs were conducted
on the GROTAG models to compare between sites and
sexes, and models were also bootstrapped 5000 times.
First-order corrected 959c CIs were calculated for pa-
rameter estimates (Haddon, 2001), and pairwise com-
parisons of growth parameters, by using CIs and ran-
domization tests, as described above for otolith-based
models.
Results
Otolith interpretation
Kolmogorov-Smirnov tests showed no significant dif-
ference in age-frequency distributions generated by
repeat readings of 55 otoliths by the primary reader
(Z)005=0.259, Dmax=0.072, not significant) or between
readers (D0 05 =0.259, Z)max=0.109, not significant). The
IAPE score for all three readings was calculated as 6.9%,
and no systematic under- or over-estimation of ages was
apparent in age bias plots within or between readers.
Therefore age estimates derived from the first readings
by the primary author were used for modeling.
Age-based growth modeling
Site comparisons No significant differences in length
frequencies were detected in a Kolmogorov-Smirnov test
between sites (D005=0.169, -Dmax=0.097, not significant).
Length-at-age estimates showed high variability
among individuals, as evidenced by the spread of data
points around the fitted models (Fig. 1), and estimates
of a ranged from 1.16 to 2.17 cm across all models
(Table 3). However, mean lengths-at-age were adequate-
ly described by the VBGF across the ages represented
by the samples from the two sites. The plots of the
site-specific VBGFs indicated that mean length-at-age
at Lord's Bluff was higher than at Point Bailey.
Because of the absence of young (0+ and 1+) fish in
the samples from both sites, and fish >14+ at Lord's
Bluff, the standard VBGF parameters were difficult
to interpret biologically. Confidence intervals for the
three standard VBGF parameters largely overlapped
in comparisons between sites (Table 3). Plots of the
bootstrap parameter estimates showed strong nonlinear
correlations, particularly between la and k, revealing
minimal overlap between sites, most easily visualized
with logarithmic axes (Fig. 2A). Nonlinear correla-
tion between parameter estimates and minimal over-
lap between sites were also true to a lesser extent in
estimates of lx versus t0 (Fig. 2B). LRTs showed that
differences between sites were highly significant overall
36-
34-
32-
30 —
28 —
° ° ° /* — ''
Kit,***'
■ A til . • PB
♦ °AViZ i LB
■:.*il?*T PBVBGF
26 —
E
a. 24 —
g) 22 —
0)
"" 20-
r
18 —
16 —
14 —
/*
*
1 1 1 1 1 1 1 1 1 1 1
2 4 6 8 10 12 14 16 18 20 22 24
Estimated age (yr)
Figure 1
Length-at-age estimates for Notolabrus fucicola, derived
from otoliths (symbols), and corresponding von Berta-
lanffy growth functions I VBGFs) fitted by least squares
(lines). PB = Point Bailey, LB = Lord's Bluff.
but could not be attributed to significant differences in
individual parameters (Table 4).
Confidence intervals for the Francis (1988b) repa-
rameterized version of the VBGF clearly indicated sig-
nificant differences in growth rates between sites in all
three parameters, and no overlap between sites in the
CIs of the estimates of mean length at 4, 7, or 10 years
old (Table 3). These differences were also evident in plots
of bootstrap parameter estimates, the two sites being
clearly separated in the parameter space, and showed
none of the high nonlinear correlations evident in the
standard VGBF estimates (Fig. 3B). Randomization tests
produced CIs of the difference between sites of 1.16-2.67,
2.48-3.50, and 2.82-4.44 cm for Z4, /7, and l10, respec-
tively. Highly significant differences in all individual
parameters growth parameters in the reparameterized
model were also shown in LRTs between sites, but no
significant difference in o was detected (Table 4).
Sex comparisons Confidence intervals for the standard
and reparameterized von Bertalanffy parameters sig-
nificantly overlapped in all comparisons between sexes
(Table 3). Likelihood ratio tests showed no significant
differences between models of sexes within sites — a
conclusion supported by considerable overlap in plots of
bootstrap estimates (not shown).
Length-based growth modeling
Model parameterization Site-specific data sets were
optimally parameterized under the most complex model,
702
Fishery Bulletin 103(4)
Table 3
Von Bertalanffy growth function parameter estimates for Notolabrus fucicola. Numbers in bold text are parameter estimates
from the original dataset. Numbers in parentheses are the proportion of parameter estimates from bootstrapped data sets that
were less than the estimate from the original data set. Numbers in plain text are first-order corrected bootstrap 95% confidence
intervals. LB = Lord's Bluff; PB = Point Bailey.
Dataset
Parameter estimate
Ijcm)
/;• i/yr)
f0(yr)
14 (cm)
(7(cml
/10(cm)
a (cm)
LB
44.7
0.085
-3.23
20.4
25.9
30.1
1.61
(0.48)
(0.51)
(0.50)
(0.51)
(0.50)
(0.51)
(0.57)
35.4 to 68.4
0.036 to 0.152
-5.82 to -1.59
20.0 to 20.9
25.4 to 26.3
29.4 to 30.8
1.39 to 1.87
PB
43.3
0.065
-4.65
18.5
22.9
26.5
1.79
(0.66)
(0.51)
(0.50)
(0.52)
(0.53)
(0.58)
(0.32)
37.9 to 86.7
0.021 to 0.096
-8.71 to -2.83
17.9 to 19.2
22.6 to 23.2
26.1 to 26.9
1.57 to 1.92
LBS 8
52.1
0.059
-4.46
20.3
25.5
29.7
1.38
(0.51)
(0.49)
(0.48)
(0.51)
(0.48)
(0.50)
(0.64)
34.6 to 1210.1
0.001 to 0.157
-9.21 to -1.55
19.8 to 20.9
24.9 to 25.9
28.9 to 30.5
1.16 to 1.68
LB2 5
43.2
0.095
-2.80
20.5
26.1
30.4
1.74
(0.47)
(0.51)
(0.48)
(0.51)
(0.48)
(0.49)
(0.62)
33.1 to 187.8
0.007 to 0.192
-7.42 to -0.98
19.9 to 21.3
25.5 to 26.7
29.2 to 31.7
1.45 to 2.17
PB<J<J
43.3
0.060
-5.56
18.9
22.9
26.3
1.58
(0.47)
(0.52)
(0.51)
(0.54)
(0.53)
(0.55)
(0.60)
33.3 to 163.3
0.007 to 0.138
-11.57 to -2.20
18.3 to 19.6
22.5 to 23.5
25.7 to 26.9
1.35 to 1.87
PBS?
43.2
0.065
-4.60
18.5
22.9
26.5
1.91
(0.48)
(0.43)
(0.53)
(0.45)
(0.47)
(0.45)
(0.62)
37.0 to 199.4
0.002 to 0.093
-10.61 to -2.35
17.6 to 19.3
22.5 to 23.3
25.9 to 27.0
1.73 to 2.16
incorporating seasonal growth and measurement error
estimates (Table 5). Estimates of proportion of outliers in
the data set (p) greater than zero were due to lack of fit
and dropped to zero in model 5. Preliminary bootstrap-
Table 4
Likelihood ratio tes
;s of site differences
in the
von Ber-
talanffy growth functions fitted to Notolabrut,
fucicola
length-at-age data
and inc
lvidual VBGF par
ameters,
both standard and
reparameterized. -A
= negative log-
likelihood. The bass
i case re
presents the
summed likeli-
hood for both curves
fitted separately.
Hypothesis
-A
9
X
df
P
Base case
553.0
—
—
Coincident curves
617.8
129.75
3
<0.001
= L
553.0
0.03
1
0.870
= k
553.2
0.36
1
0.548
~ 'o
553.4
0.78
1
0.376
= '4
565.7
25.47
1
<0.001
= h
602.9
99.78
1
<0.001
= '10
589.2
72.53
1
<0.001
= a
554.2
2.49
1
0.114
ping showed that fitting p regularly produced spurious
model fits. Because the full data sets were estimated
to have no outliers, it was considered reasonable to fit
model 4 (equivalent to model 5, but with p held equal to
zero) to all bootstrapped data sets for site-specific growth
estimates and comparisons.
Estimates of p also dropped to zero in model 5 when
this model was fitted to the sex-specific data sets, ex-
cept for females at Lord's Bluff. Holding p = 0 in model
4 for females at Lord's Bluff resulted in a less good fit
compared to that of model 5 and also produced slightly
different parameter estimates than those of model 5,
namely increasing growth (g.,0 andg28), growth vari-
ability (v), and measurement error (m) (Table 6). Vi-
sual inspection of residuals showed an obvious outlier
in the data set. When this was removed and model 5
was refitted, p fell to zero and the other parameters
estimates were very close to the values estimated from
fitting model 5 to the original data set, and there was
a large improvement in likelihood. Therefore the model
for females at Lord's Bluff was based on the data set
with the outlier excluded, and model 4 with p held at
zero was fitted to all bootstrap data sets for sex-specific
growth estimates and comparisons.
Site comparisons With the exception of s at Lord's
Bluff, the proportion of bootstrap parameter estimates
Welsford and Lyle. Estimates of growth of Notolabrus fuacola from length- and age-based models
703
LB
PB
to (cm)
L (cm)
k (/year)
Figure 2
Bootstrap parameter estimates for Notolabrus fucicola, by site, for the standard von Bertalanffy growth function. Note
/, and k are plotted on logarithmic axes for clarity: (A) !v vs. k (B) /, vs. tQ (C) k vs. ta. Contrasting crosses show the
location of parameter estimates based on the original data set (+, PB = Point Bailey, x, LB= Lord's Bluff).
were more or less evenly distributed around the origi-
nal parameter estimates, resulting in approximately
symmetrical first-order corrected 95% CIs (Table 7).
Based on the lack of overlap of CIs, only g.,0 differed
significantly between sites. A randomization test of the
difference in g20 produced CIs of 0.75-2.85 cm/yr faster
growth at Lord's Bluff.
Plots of bootstrap parameter estimates clearly indi-
cate differences in growth rates between sites, and little
overlap in the parameter clouds along the g20 axis when
g20 is plotted against g30 (Fig. 4A). Plots of bootstrapped
estimates of the seasonal growth parameters u and w
showed a high level of nonlinear correlation. A region
of overlap between site estimates along the w axis is
evident in Fig. 4B. However, the randomization test for
this parameter produced a CI of the difference between
the two sites of 0.02-0.33 yr, corresponding to signifi-
cantly different maximum in seasonal growth occurring
at Lord's Bluff 8-120 days after Point Bailey. Estimates
of w at Point Bailey ranged from -0.14 to 0.05 years in
relation to 1 January (Table 7), corresponding to peak
growth between austral mid-spring and mid-summer
(early November through mid-January), contrasting
with the Lord's Bluff estimate of -0.08 to 0.20 years
and indicating peak growth from austral late spring to
early autumn (mid-December through mid-Marchl.
Site differences in growth were also indicated in the
results of LRTs. The overall models were significantly
different; the growth parameter g20 and the timing of
maximum seasonal growth were significantly different
704
Fishery Bulletin 103(4)
A
,
>2"° a
2! —
♦
PB j^Jfl
LB AJU
'^^5s
r«r
25 -
21 —
2= —
.M
|j^^.-
■ ^sn
HR-?
-?VA?
22
1 1
l
/4 (cm)
E 29-
B
• PB
O LB
26
~l
27
/7 (cm)
Figure 3
Bootstrap estimates of reparameterized von Ber-
talanffy growth function mean lengths at age for
Notolabrus fucieola, by site. (A) /4 versus /- (B) l-
versus /10 mean length-at-ages at 7 and 10 years.
Contrasting crosses show the location of parameter
estimates based on the original data set (+, PB = Point
Bailey, x, LB = Lord's Bluff).
0 25
0 20 -
0 15
0 10
0 05
0 00
-0 05
-0.10 -
-0 15
-020
-0 25
"I I I I T~
2 5 3 3.5 4 4 5
g20 (cm/yr)
B
0 05 1
U
Figure 4
Bootstrap estimates of GROTAG parameters for Noto-
labrus fucieola, by site: (A) g20 versus g30, mean
annual growth at initial length 20 and 30 cm and
(B) u versus w, magnitude and timing of seasonal
growth. Contrasting crosses show the location of
parameter estimates based on the original data set
(4-, PB = Point Bailey, x, LB„ =Lord's Bluff).
at or=0.05 when tested individually (Table 8A), in agree-
ment with the results of the randomization tests.
Sex comparisons Bootstrapped parameter estimates
from sex-specific data sets were approximately sym-
metrical about the original estimates (Table 7). The
largest divergence from 0.5 was evident in estimates of
s for females at Lord's Bluff and males at Point Bailey.
Bootstrap estimates of u for Lord's Bluff males occasion-
ally extended into spurious negative values, lowering
confidence estimates of the extent of seasonal growth
in this data set (Table 7).
Based on simple overlap of CIs, no single parameter
differed significantly between sexes at either site (Ta-
ble 7). Plots of the bootstrap estimates of the growth
parameters g.,0 and g.,8 showed minimal overlap between
males and females, and separation was most evident
along the g20 axis (Fig. 5A). Plots of bootstrapped es-
timates of the seasonal growth parameters u and w
(Fig. 5B), and the measurement error parameters m and s
Welsford and Lyle: Estimates of growth of Notolabrus fuacola from length- and age-based models
705
Table 5
Parameter
estimates and
negative log
likelihoods (
-A) of models
used
in likelihood
ratio tests t(i determine
the opti
mal para-
meterization of GROTAG models for Notolabrus fucicola tagging data.
bv site. Bold text in
-A column indicates the
optimally
parameter
zed model for each data set.
Model 4 is equivalent to model 5
withp = 0 in
these instances. LBre^ =
residents of Lord's
Bluff: PB =
Point Bailey.
Parameter estimate
§20
§30
w
s
m
Data set
Model
(cm/yr)
(cm/yr)
V
u
(yr)
(cm)
(cm)
P
-A
LB
1
1.84
1.07
0.88
—
—
—
—
0.07
57.06
2
3.00
1.67
0.88
0.59
0.22
—
—
0.07
50.46
3
2.60
1.12
0.29
—
—
0.22
-0.12
0.00
20.59
4 and 5
3.30
1.42
0.26
0.45
0.14
0.22
-0.10
0.00
12.97
PB
1
1.50
1.01
0.73
—
—
—
—
0.16
87.82
2
1.55
1.15
0.82
0.31
0.13
—
—
0.07
79.02
3
1.87
1.18
0.36
—
—
0.19
-0.08
0.00
36.16
4 and 5
1.53
1.01
0.35
0.57
0.91
0.18
-0.07
0.00
23.52
Table 6
Paramete
• estimates and ne
native log
likelihoods
-A) of models
used
in
likelihood
ratio tests
to determine the optimal para-
meterization of GROTAG models for Notolabrus fucicola tagging
data.
by
sex within
site. Bold text in -
A column indicates the
optimally
parameterized model for each data set. *
indicates the parameter estimates and likelihoods when GROTAG
is fitted to
the Lord's
Bluff (LB) 2S data
set with a single outlier removed. Model 4
is
equivalent to model 5 withp =
3 in all other
instances.
PB = Point Bailey.
Pa
rameter estimate
§20
§30
w
s
m
Data set
Model
(cm/yr)
(cm/yr)
V
u
(yr)
(cm)
(cm)
P
-A
LBSS
1
1.98
1.49
0.52
—
_
—
—
0.00
43.07
2
1.88
1.54
0.50
0.23
0.04
—
—
0.00
39.24
3
2.09
1.62
0.27
—
—
0.21
-0.05
0.00
32.21
4 and 5
2.04
1.67
0.27
0.23
0.19
0.20
-0.04
0.00
29.44
LB$S
1
2.05
1.40
0.52
—
-
—
—
0.16
60.58
2
1.99
1.20
0.48
0.41
0.98
—
—
0.15
58.19
3
2.88
1.87
0.26
—
—
0.25
-0.29
0.00
41.15
4
2.75
1.75
0.25
0.32
0.96
0.24
-0.31
—
38.40
5
2.66
1.48
0.22
0.47
0.94
0.22
-0.26
0.03
36.23
4 and 5*
2.66
1.48
0.22
0.48
0.94
0.23
-0.26
0.00
30.36
PBSS
1
1.31
1.02
0.60
—
—
—
—
0.24
21.31
2
1.15
0.96
0.61
0.41
0.90
—
—
0.19
19.93
3
1.54
1.21
0.33
—
—
0.19
-0.03
0.00
6.43
4 and 5
1.15
0.93
0.32
0.81
0.88
0.18
-0.04
0.00
2.49
PB?9
1
1.49
1.15
0.68
—
—
—
—
0.16
30.55
2
1.43
1.16
0.90
0.33
0.12
—
—
0.00
28.85
3
1.96
1.32
0.38
—
—
0.20
-0.11
0.00
19.06
4 and 5
1.46
1.01
0.39
0.77
0.87
0.18
-0.12
0.00
15.78
(Fig. 5C) showed distinct relationships within the two
sexes. Randomization tests confirmed significant dif-
ferences in g20, m, and w. The CIs of these differences
were estimated to be 0.2-1.09 cm/yr faster for females
with an initial size of 20 cm, with an annual peak in fe-
male growth 3-152 days earlier than males, and with a
measurement error that overestimated female length by
2-40 mm more than the measurement error for males.
706
Fishery Bulletin 103(4)
Table 7
GROTAG parameter estimates derived from Notolabrus fucicola tag-recapture data. For all data sets, ga is the mean annual
growth of individuals with an initial length of 20 cm. gp represents the estimated mean annual growth of individuals with an
initial length of 30 cm for Lord's Bluff ( LBre,) and Point Bailey < PB (, or the estimate for 28-cm individuals for all other data sets.
Numbers in bold text are the parameter estimates from the original data sets. Numbers in parentheses are the proportion of
parameter estimates from bootstrap data sets less than the original estimate. Numbers in plain text are first-order corrected
bootstrap 95^ confidence intervals.
Data set
Parameters estimate
Sa
(cm/yr)
SB
(cm/yr)
t>
u
w
(yr)
s
(cm)
m
(cm)
LBres
3.30
1.42
0.26
0.45
0.14
0.22
-0.10
(0.50)
(0.48)
(0.54)
(0.43)
(0.47)
(0.60)
(0.48)
2.32 to 4.34
0.80 to 2.19
0.14 to 0.40
0.23 to 0.68
-0.08 to 0.20
0.18 to 0.26
-0.18 to -0.03
PB
1.53
1.01
0.35
0.57
-0.09
0.18
-0.07
(0.51)
(0.51)
(0.50)
(0.46)
(0.54)
(0.55)
(0.56)
1.21 to 1.94
0.76 to 1.31
0.27 to 0.44
0.25 to 1.00
-0.14 to 0.05
0.15 to 0.22
-0.12 to -0.01
LBf !
2.04
1.68
0.27
0.23
0.19
0.20
-0.04
(0.481
(0.51)
(0.58)
(0.45)
(0.48)
(0.57)
(0.49)
1.77 to 2.31
1.32 to 2.01
0.20 to 0.40
-0.06 to 0.43
-0.02 to 0.29
0.12 to 0.28
-0.14 to 0.06
LB??
2.66
1.48
0.22
0.48
-0.06
0.23
-0.26
(0.49)
(0.50)
(0.50)
(0.39)
(0.52)
(0.62)
(0.49)
2.27 to 2.98
1.18 to 1.83
0.13 to 0.30
0.16 to 0.69
-0.16 to 0.12
0.14 to 0.34
-0.41 to -0.10
PB?c?
1.15
0.93
0.32
0.81
-0.12
0.18
-0.04
(0.41)
(0.43)
(0.57)
(0.51)
(0.43)
(0.62)
(0.53)
0.83 tol.69
0.61 to 1.41
0.17 to 0.47
0.18 to 1.00
-0.20 to 0.10
0.14 to 0.24
-0.14 to 0.06
PB??
1.46
1.01
0.39
0.77
-0.13
0.18
-0.12
(0.50)
(0.47)
(0.56)
(0.46)
(0.47)
(0.56)
(0.51)
1.08 to 2.33
0.70 to 1.01
0.23 to 0.74
0.14 to 1.00
-0.20 to 0.14
0.09 to 0.27
-0.22 to 0.00
Table 8
Likelihood ratio tests of the GROTAG models for which bootstrap parameter estimates were generated (Tables 5 and 6): (A) Point
Bailey l PB) against Lord's Bluff (LBreJ (B) LB- S against LB? J. -A= negative log-likelihoods. The base case is the negative log-
likelihood of the data sets fitted with two wholly separate models. * = significant at a=0.05.
A Hypothesis
Base case
Coincident curves
=£20
=£.30
= V
= 11
=W
-A
36.49
51.98
42.19
37.36
37.35
36.62
38.91
37.64
36.66
30.98
11.38
1.72
1.72
0.12
4.84
2.28
0.33
df
<0.001*
<0.001*
0.189
0.190
0.623
0.028*
0.130
0.565
B Hypothesis
Base case
Coincident curves
=#20
=#28
= V
= (/
=w
df
59.80
—
- —
72.17
24.75
7 <o.oor
63.43
7.27
1 0.007
60.21
0.83
1 0.362
60.11
0.62
1 0.431
60.64
1.69
1 0.194
62.05
4.50
1 0.034
59.94
0.30
1 0.583
62.51
5.43
1 0.020
These conclusions agreed with the LRTs, which in-
dicated highly significant differences between g20 be-
tween sexes at Lord's Bluff, and significant differences
between m and w at a=0.05 when tested individually
(Table 8B). This contrasts with the results of age-based
modelling of sex-specific growth at Lord's Bluff, where
no difference between the sexes was detected in any
test.
Sex comparisons at Point Bailey revealed no sex-
specific growth differences, and neither CIs (Table 7)
Welsford and Lyle: Estimates ol growth of Notolabrus fuacola from length- and age-based models
707
b —
.... .. ■
•"fescJfei-*'''-' ° ' '■'• •
'•.:'*jri^JB»v:«-:-°54ji'° ^'° *
r'-nSi B*'^". ■ . "5^4* &•■
•"•• .-^H ; * ^fiS^fev1:
•■'*J| jrfl 111
■* j'.ScKT' -i ' villi IP* "
-. ^".vS^-. ""'.^-^P^ *-
1 —
•
• LB Males
a O LB Females
III
>! 0 -
• LB Males
LB Females
B
04
g (cm/yr)
• LB Males
LB Females
-0 4
m (cm)
Figure 5
GROTAG bootstrap parameter estimates for Notolabrus fucicnla from Lord's Bluff, by sex: (A)g20 versus g28, mean annual
growth at initial length 20 and 28 cm; (Bl u versus w, magnitude and timing of seasonal growth and (C) m versus s,
mean and standard deviation of measurement error. Contrasting crosses show the location of parameter estimates based
on the original data set (+ = males, x = females).
nor LRTs indicated significant difference in any of the
model parameters, and bootstrap plots showed large
regions of overlap (not shown).
Discussion
Comparisons of models
In this study, two methods, based on mathematically
different concepts, produced similar conclusions, namely
that growth in N. fucicola was faster at Lord's Bluff than
at Point Bailey. The results of length-based and age-
based models also produced similar conclusions regard-
ing the methods most suitable for robust comparisons of
models and parameter estimates for different groups of
fish. Confidence intervals were only reliable indicators of
difference in cases where parameters showed low levels
of correlation between estimates and where highly sig-
nificant differences existed, such as in site comparisons
of the reparameterized VBGF parameters, and hence
were of limited utility.
Likelihood ratio tests provided a robust method of
testing differences between models. However, we believe
708
Fishery Bulletin 103(4)
that evidence from more than one source is required be-
fore conclusions can be drawn about differences between
models designed to describe nonlinear processes such as
growth. In the present study, bootstrapping techniques
proved to be informative as a way of visualizing the
behavior of the models used, and the distributions and
correlations of parameter estimates that could not be
determined readily from model likelihoods alone. They
also provided a basis for estimating nonparametrically
with randomization tests the differences, and CIs, of
growth estimators between populations. Hence we rec-
ommend bootstrapping, plots of parameter estimates,
and randomization tests to complement the "traditional"
statistical tests such as the LRTs.
The standard VBGF has been criticized for the dif-
ficulty it causes in extracting biological meaning from
parameters (Knight, 1968; Roff, 1980; Francis, 1988b;
1992). The problem is particularly acute where only a
part of the size or age range (or both ranges) of animals
is available — a situation regularly faced in analyses of
fisheries data (Haddon, 2001). Data sets in our study
were limited, particularly by the lack of fish in the
lower age classes (cf. Ewing et al., 2003). Hence, any
attempt to interpret or compare la or t0 as descrip-
tors of the growth of N. fucicola would be spurious.
Furthermore, because k and lx are highly correlated,
comparisons of k cannot be independent of the effects
of size or age selectivity on a data set. Because of the
limitations of such parameters, and as la and k are
often inputs into population dynamics models and em-
pirical models estimating parameters such as natural
mortality (e.g., Pauly, 1979), extreme caution should be
exercised when extrapolating these values from limited
data. However, this instance exemplifies the utility of
the reparameterization, because even with limited data,
the useful parameters of mean lengths at age can be
estimated and compared.
Variability in growth
Models of growth can be used to estimate length-depen-
dent processes in fish populations, such as reproductive
output, increases in biomass due to individual growth,
selectivity of fishing gear, and the impact and appropri-
ateness of size limits as management tools. The results
of the present study demonstrate that growth varies
significantly across individuals, seasons, sexes, and
sites in N. fucicola.
Although the significance of estimating the variabil-
ity in growth around the population mean (v) was not
explicitly tested during model parameterization, values
of v around 0.2 to 0.7 were estimated for all data sets
modeled. Values in this range have been estimated with
GROTAG from other species of bony fishes (Francis,
1988a; b; 1988c; 1992; Francis, et al., 1999) and car-
tilaginous fishes (Francis and Francis, 1992; Francis,
1997; Francis and Mulligan, 1998; Simpendorfer, 2000;
Simpendorfer, et al., 2000), indicating that considerable
individual variability in annual growth of size classes is
common. The extent of variability in individual growth
is an important factor when quantifying growth be-
cause it may obscure other sources of growth variation,
particularly in situations where data are limited. This
effect may partially explain why age-based models failed
to detect any significant effect of sex on growth rates in
our study, whereas length-based modeling indicated that
among smaller size classes, females grew faster than
males at Lord's Bluff. On the basis of a large data set
(>1000 individuals), Ewing et al. (2003) demonstrated
that average length-at-age was significantly higher for
females than males in N. fucicola although the magni-
tude of this difference was small. No growth differences
between the sexes were evident at Point Bailey but
given slower growth rates, the absolute magnitude of
any expected growth differences related to sex would be
relatively small and difficult to detect statistically.
Our study is the first to show that growth rates of N.
fucicola vary significantly across small spatial scales;
the two sites in our study were separated by less than
25 km. At Point Bailey, few individuals reach the mini-
mum legal size limit of 30 cm until 10 years of age,
whereas at Lord's Bluff they do so at least two years
earlier (Fig. 1). An equivalent conclusion is evident
from the GROTAG estimates, indicating that a 28-cm
fish at Point Bailey will take nearly 2 years on aver-
age to exceed 30 cm, whereas fish of the same size are
likely to reach legal size in just over a year at Lord's
Bluff. Hence relative yields and rates of replacement
of recruited size and age classes are likely to be lower
at Point Bailey than at Lord's Bluff. However, because
N. fucicola can be sexually mature at lengths of 12 cm
(Patterson, 2000), some individuals are likely to have
spawned for 6-8 years before recruitment to the fishery
at Lord's Bluff (Fig. 1). This size at maturity suggests
that the minimum legal size limit provides effective
protection of the reproductive output of the prerecruit
population of TV. fucicola at both sites.
Using length-at-age estimated from whole otoliths,
Barrett (1999) found no growth differences between sev-
eral populations of N. fucicola in southeastern Tasmania
and used these findings to support the hypothesis that
populations are not resource limited. Our study did not
specifically address any hypothesis about resource limi-
tation but has clearly demonstrated that growth rates
can vary between populations at the scale of individual
reefs. Notolabrus fucicola are site-attached once they
settle out of the plankton, rarely having an ambit of
more than 500 m on contiguous reef, and rarely cross-
ing soft bottom habitat if they are resident on smaller
patch reef habitat (Barrett, 1995b). Intuitively, it fol-
lows that if productivity varies between reefs, then the
potential for growth of individual site-attached reef fish
may be limited. A variety of factors have been cited in
other temperate reef species where spatial variability in
length-at-age is evident, such as habitat type (Gilland-
ers, 1997; Barrett, 1999), conspecific competition and
variation in juvenile recruitment (Jones, 1980, 1984),
and impacts of exploitation (Buxton, 1993). Further
study is advocated to determine the factors that influ-
ence N. fucicola growth at this scale.
Welsford and Lyle: Estimates of growth of Notolabrus fucicola from length- and age-based models
709
Parameterization of seasonal growth significantly
improved the fit of the GROTAG models, indicating
that seasonal variability in growth is significant for
N. fucicola. The estimates of seasonal growth from our
study constitute the first for this species. The LRTs
indicated significant differences in the timing of maxi-
mum growth (h>) between sites and between sexes at
Lord's Bluff. This result was repeated in the randomiza-
tion tests based on the outputs of bootstrapping. Peak
growth in N. fucicola at both sites is estimated to oc-
cur over the austral spring-summer, during maximum
water temperatures and increased productivity off the
coast of Tasmania (e.g., Halpern, et al.4), and peak
growth occurs significantly later in the season at Lord's
Bluff than at Point Bailey. The mechanism affecting the
timing of seasonal growth at this reef-by-reef scale is
worthy of further investigation but is likely to include
variability in seasonal cycles of oceanography, in avail-
ability of food (Denny and Schiel, 2001; Shepherd and
Clarkson, 2001) and in temperature effects on metabo-
lism, controlling the amount and timing of resources for
allocation to growth throughout the year.
The estimate of the size of the difference in w be-
tween the sexes at Lord's Bluff had very broad CIs,
and it is difficult to propose a hypothesis that could
result in seasonal growth varying between the sexes
by as much as five months, although resource allocation
for reproduction could be involved. It may be that the
particularly small size of the female data set at this
site limited our ability to estimate seasonal growth ac-
curately with GROTAG, and further study is required
to more precisely determine how important seasonal
growth differences between the sexes are in temperate
reef fishes such as N. fucicola.
Sex-specific GROTAG analyses indicated a significant
difference in measurement errors; females were under
measured by a mean of 3 mm, compared to less than
1 mm for males at Lord's Bluff. Greater measurement
errors for females have been detected in other studies
with GROTAG (e.g., Simpendorfer, 20001, but a reason
for greater difficulty in measuring females is difficult
to determine. A possible explanation from our study is
the high individual growth variability and small sample
sizes. Both of these factors have been shown to affect
accurate estimation of measurement error in GROTAG
(Francis and Mulligan, 1998), and therefore the high
estimate of m in our study may be an artifact of the
data set.
4 Halpern, D., V. Zlotnicki, P. M. Woicheshyn, O. B. Brown,
G. C. Feldman, M. H. Freilich, F. J. Wentz, and C.
Gentemann. 2000. An atlas of monthly mean distribu-
tions of SSMI surface wind speed, AVHRR sea surface tem-
perature, TMI sea surface temperature, AMI surface wind
velocity, SeaWIFS chlorophyll-a, and TOPEX/POSEIDON sea
surface topography during 1998. Jet Propulsion Labora-
tory Publication 00-08, 102 p. National Aeronautics and
Space Administration, Jet Propulsion Laboratory, California
Institute of Technology, 4800 Oak Grove Drive, Pasadena,
CA 91109.
A significant difference in growth between the sexes
at Lord's Bluff indicates that under conditions of rapid
growth, females may grow significantly faster than
males. As discussed above, the current minimum legal
size limit is effectively protecting the reproductive out-
put of the prerecruit population of N. fucicola. However,
any significant lowering of the legal minimum size is
contraindicated where, in prerecruitment size classes,
females grow more rapidly than males, because lower-
ing the legal size may result in differences in sex-spe-
cific fishing mortality.
As demonstrated in the present study, the choice of
growth model and the methods used to compare pa-
rameter estimates are critical to ensuring that growth
is adequately described, differences in growth are de-
tected, and if detected, are interpretable. In combina-
tion, the tests we employed are shown to be generally
robust, even in situations where data sets are limited
in sample size or by coverage across the full range of
age and length classes. We recommend the use of a
combination of approaches, including growth models
with biologically interpretable parameters, statistical
tests such as LRTs, plots of bootstrap parameters, and
nonparametric randomization tests, to provide insight
into the growth dynamics of fish species.
Acknowledgments
We wish to thank Malcolm Haddon, John Hoenig, Craig
Johnson, Paul Burch, and Philippe Ziegler for their con-
structive suggestions for the manuscript. Alan Jordan
and Graeme Ewing made invaluable contributions to the
field and laboratory analyses. This study was conducted
as a part of a Ph.D. program by the primary author,
through the Faculty of Science and Engineering at the
University of Tasmania.
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712
Effects of harvesting methods on sustainability
of a bay scallop fishery: dredging uproots seagrass
and displaces recruits
Melanie J. Bishop
Charles H. Peterson
Henry C Summerson
David Gaskill
University of North Carolina at Chapel Hill
Institute of Marine Sciences
3431 Arendell St
Morehead City, North Carolina 28557
E-mail address (for M J Bishop, contact author) melaniebishop-1fgiutsedu.au
Present address (for M. J. Bishop): Department of Environmental science
University of Technology, Sydney
Corner of Westbourne St. and Pacific Highway
Gore Hill, New South Wales, Australia 2065
Fishing is widely recognized to have
profound effects on estuarine and
marine ecosystems (Hammer and
Jansson, 1993; Dayton et al., 1995).
Intense commercial and recreational
harvest of valuable species can result
in population collapses of target and
nontarget species (Botsford et al.,
1997; Pauly et al., 1998; Collie et al.
2000; Jackson et al., 2001). Fishing
gear, such as trawls and dredges, that
are dragged over the seafloor inflict
damage to the benthic habitat ( Dayton
et al., 1995; Engel and Kvitek, 1995;
Jennings and Kaiser, 1998; Watling
and Norse, 1998). As the growing
human population, over-capitalization,
and increasing government subsidies
of fishing place increasing pressures
on marine resources (Myers, 1997),
a clear understanding of the mecha-
nisms by which fishing affects coastal
systems is required to craft sustain-
able fisheries management.
Dredging, possibly the most de-
structive of common fishing meth-
ods (Collie et al., 2000), has been
the subject of many recent ecological
studies (Dayton et al., 1995; Jen-
nings and Kaiser, 1998; Thrush et
al., 1998). These studies indicate that
dredge extraction and disturbance
can have large direct effects on the
abundance, biomass, and diversity of
resident macrobenthic species (e.g.,
Caddy, 1973; Eleftheriou and Robert-
son, 1992). In addition, dredging can
indirectly affect macrobenthic species
through disturbance of benthic habi-
tat (Ramsay et al., 1998; Lenihan
and Peterson, 1998). Indirect impacts
of dredging may be particularly seri-
ous where highly structured biogenic
habitats, such as oyster reefs or sea-
grass beds, are affected (Peterson
et al., 1987; Lenihan and Peterson.
1998; Collie et al., 2000; Lenihan
and Peterson, 2004). These habitats
may be considered essential habitat
for many species of fish of commer-
cial or recreational value (Thayer
et al., 1975), providing refuges from
predators (Orth et al., 1984; Castel
et al., 1989) and abundant epibiotic
food (Virnstein et al., 1984; Sanchez-
Jerez et al., 1999).
Among fishery species dependent
on biogenic habitat is the commer-
cially and recreationally important
bay scallop (Argopecten irradians). In
the two reproductive seasons, spring
and fall, bay scallop recruits settle
onto hard substrates (Belding, 1910;
Castagna, 1975) where they remain
attached for the first few months of
their lives. They then complete their
12-24 month life cycle on the estuary
floor. In North Carolina, eelgrass is
the only hard substrate of any abun-
dance to which bay scallop recruits
can attach themselves (Kirby-Smith,
1970).
Commercial harvest of bay scallops
in North Carolina is achieved pri-
marily by toothless epibenthic dredge
(22.7 kg legal limit; NCFMC1). Dredg-
es have the advantage that, unlike
rakes, they can be used from boats in
deep as well as shallow waters. Their
disadvantage is that they decrease
the biomass and shoot density of sea-
grass in scallop beds (Fonseca et al.,
1984). Early in the North Carolina
scallop season, which extends from
December through May (NCMFC1),
most of the juveniles from the previ-
ous fall spawning are still attached
to seagrass blades (Spitsbergen-). If
these juveniles are displaced by habi-
tat destruction, reduced numbers of
scallops may be available for harvest
in the subsequent year (hypothesized
by Thayer and Stuart. 1974). Al-
though seagrasses can recover from
small-scale disturbances to shoots by
vegetative growth, large-scale dis-
turbances to their subsurface root
and rhizome system may permanent-
ly reduce the density of submerged
aquatic vegetation (SAV) (Peterson
et al., 1987) such that it may limit
settlement of the following year's
recruits or induce greater rates of
predation on them (or bring about
both). Although, in North Carolina,
the bay scallop fishery management
plan requires that the scallop sea-
son be opened after fall spawning is
completed (Peterson, 1990); it fails
to consider how methods of harvest
may indirectly effect spawning stock
biomass in years to come.
1 NCMFC (North Carolina Marine Fisher-
ies Commission). 2005. North Caro-
lina fisheries rules for coastal waters,
210 p. North Carolina Department of
Environment and Natural Resources,
1601 Mail Service Center, Raleigh, NC
27699.
2 Spitsbergen, D. 1979. A study of the
bay scallop (Argopeeten irradians) in
North Carolina waters. Report for Proj-
ect 2-256-R, 44 p. North Carolina Divi-
sion of Marine Fisheries. 3441 Arendell
Street, Morehead City, NC 28557
Manuscript submitted 30 October 2004
to the Scientific Editor's Office.
Manuscript approved for publication
1 April 2005 by the Scientific Editor.
Fish. Bull. 103:712-71912005).
NOTE Bishop et al.: Effects of harvest methods on sustainability of a bay scallop fishery
713
Implementation of gear restrictions that allow only
hand methods of harvesting scallops (i.e., hand, rake,
dip nets) may minimize impacts of harvesting on scallop
recruits by reducing damage to seagrass and the loss
of juvenile bay scallops that comprise the year class
that will be fished in the following year. Although such
restrictions were introduced to Bogue Sound in 1992
in response to the 1987 red tide that decimated scallop
populations in that water basin (Summerson and Peter-
son, 1990), this conservation-based measure was discon-
tinued in 1998 because of social pressure from fisher-
men. In the present study, we ascertain the impacts of
dredges and hand-harvesting methods on the biomass
of seagrass, as compared to undisturbed controls, 1) by
measuring the biomass of seagrass directly dislodged by
each method, and 2) by ascertaining, through measure-
ments of biomass one month later, whether this removal
affects the standing stock of seagrass over a longer
temporal scale. We also tested both direct and indirect
effects of seagrass removal on bay scallop recruits by
measuring their density before and one month after
harvesting and by ascertaining whether any document-
ed difference can be explained by the numbers directly
removed by uprooting of seagrass during harvesting.
Such an assessment of ecological impacts of dredging
on bay scallop recruits is urgently required given that
North Carolina landings of bay scallops have fallen to
an historic low since the relaxation of gear restrictions
(Burgess and Bianchi3).
Materials and methods
Nine adjacent experimental plots, 25 mx8 m, were estab-
lished as a research sanctuary, closed to commercial
fishing activity, in western Bogue Sound, North Carolina
(34°41.6'N, 76°59.1'W), prior to the opening of the scallop
season in winter 2001-2002. Although this section of
Bogue Sound has been closed to scallop dredging since
at least 1998, its high-tide water depth of 1.5 m is well
within the depth range for harvesting with this method.
Plots contained continuous seagrass beds dominated
by Zostera marina on a muddy-sand bottom. Three of
the plots were randomly assigned to each of the experi-
mental treatments: hand-harvested, dredge-harvested,
and control (undisturbed). In order to ensure that our
treatments were representative of harvesting methods
and intensities used by the industry, they were per-
formed with participation of an experienced commercial
scallop fisherman (Ted Willis of Salter Path). Dredging
was achieved with a standard 72-cm wide steel scallop
dredge, at an intensity of five parallel tows, each run-
ning along the length of the plot within a 10-minute
period. This method, which mimicked commercial fishing
1 Burgess, C. C, and A. J. Bianchi. 2004. An economic
profile analysis of the commercial fishing industry of North
Carolina including profiles for state-managed species, 243 p.
North Carolina Division of Marine Fisheries, 3441 Arendell
Street, Morehead City, NC 28557.
practices, minimized overlap between the dredge paths.
Hand scalloping involved a single fisherman collecting
scallops from the bottom by hand, also during 10-minute
periods. Care was taken to ensure that the treatments
were applied evenly over the entire plot to avoid creating
large within-plot variance that might preclude detection
of differences among plots.
Seagrass and scallops collected during harvesting
were retained for measurements. The number of adult
scallops (>40 mm shell height; Peterson et al., 1989)
obtained with each of the methods of harvest was enu-
merated. The size (to the nearest 0.1 mm) and number
of juvenile scallops collected as bycatch and the dry
weight of seagrass removed during harvesting were
quantified separately. Because not all seagrass and
juvenile scallops displaced by harvesting are retained
in the dredge or by a fisherman collecting scallops by
hand methods, an 8-m long net with 5-mm mesh that
extended from the bottom to the surface was set down-
stream from each plot and perpendicular to the flow
of the current during harvest. The nets were strung
between stakes marking the corners of the experimental
plot. Dislodged juvenile scallops and seagrass collected
by the nets were added to the amounts extracted from
the dredge to compute displacement totals. Nets were
also set downstream of controls to determine natural
rates of transport of seagrass and juvenile scallops that
could not be attributed to harvesting operations.
Each plot was sampled on 14 January 2002, immedi-
ately prior to harvesting on that same day to determine:
1) the density of bay scallop recruits (size s40 mm;
Peterson et al., 1989); 2) the size distribution of the
recruits; and 3) biomass per unit of area of seagrass.
These variables were resampled on 25 February 2002,
over one month later, to ascertain any lasting impact
of harvest. Sampling of scallops was conducted with a
0.5-m'2 cylindrical quadrat, haphazardly positioned at
nine locations within each plot. A 1.2-cm tall cylinder
of 6-mm nylon mesh, attached to the quadrat and sus-
pended by a buoyant plastic hoop that floated on the
surface of the water, isolated the volume of water above
each quadrat so that it could be sampled by suction
with a Venturi suction device (according to Peterson et
al., 1989). The suction device forced 600 mL of water
per minute through a 3-mm collecting bag. Suction
sampling was necessary because scallops, which typi-
cally recline on the bottom, can enter the water to swim
when threatened by predators or otherwise disturbed
(Peterson et al., 1982). The disturbance caused by suc-
tion sampling of only nine small areas was minimal
compared to the scale of harvesting disturbance. Upon
returning to the laboratory, seagrass was removed from
samples for measurement of dry weight biomass and
live scallops were counted, measured to the nearest
0.1 mm and categorized as adults (>40 mm) or recruits
(^40 mm) in the subsequent year class.
Seagrass was sampled in five replicate 0.25-m2 areas
within each plot by suction dredging inside a 0.56-m
diameter circular quadrat to a sediment depth of 12 cm.
Previous sampling has shown this method to be success-
714
Fishery Bulletin 103(4)
240 "
180 "
!E
O)
'53 120 ■
5
>.
Q
60 "
0 ' ' ' '
Control Hand Dredge
Treatment
Figure 1
Mean (±1 SE) dry weight of seagrass displaced from control (undisturbedl,
hand-harvested, and dredged plots of seagrass during the 10 minutes
during which the treatments were applied. n = 3.
ful in removing both roots and shoots in their entirety
(Peterson et al., 1983a). Shoots and roots, which were
collected in a 3-mm nylon mesh bag, were dried at 60°C
to constant weight to calculate total dry weight biomass
of seagrass.
ANOVAs allowed us to test for a significant inter-
action between time (before versus after) and distur-
bance (dredge versus hand-harvest versus control) in
the biomass of seagrass and recruit density of bay
scallops (a basic BACI design; Green, 1979), indicative
of an impact of harvest. The cause of any significant
time x disturbance interactions was explored by using
Student-Newman-Keul (SNK) tests. Prior to each
analysis, Cochran's (1951) C-test was done to test for
heterogeneity of variances. Where variances were hetero-
geneous, data were In (x+1) transformed to remove
heteroscedasticity at a = 0.05.
Results
Of the two methods used to harvest adult scallops, hand
harvesting had by far the greater efficiency in these
shallow waters (ANOVA, P<0.0001). Over a period of 10
minutes, an average of 156 ±12 (1 SE) scallops within
each 25x8 m plot was harvested by hand as compared
to 26 ±1 scallops with the dredge.
The two methods of harvesting differed significantly
in their impact on seagrass. Hand harvesting of scal-
lops did not increase dislodgement of seagrass above
the natural drift rate (Fig.l). Dredging, in contrast,
resulted in 127 times the export of seagrass. This ex-
traction did not, however, result in detectable reductions
in biomass per unit of area of seagrass within dredged
plots when sampled one month later. There was no sig-
nificant temporal change in the biomass of seagrass in
any of the three treatments from before to one month
after harvesting (Table 1, Fig. 2).
Fewer than 2% of the estimated total number of juve-
nile scallops in a plot were directly removed by dredg-
ing and none was removed by hand-harvesting. Never-
theless, sampling one month after harvesting indicated
depressed densities of juvenile bay scallops in dredged
plots (Table 2; Fig. 3). This difference could not be at-
tributed to natural change; small increases (16-55%) in
numbers of juvenile bay scallops in the hand-harvested
and control plots were documented over the same period
(Fig. 3). A comparison of size-frequency histograms of
juvenile bay scallops within each type of plot from be-
fore to after harvesting revealed that the decrease in ju-
venile scallop numbers in the dredged plots was primar-
ily due to losses of scallops in the smallest size classes
(<14 mm; Fig. 4). In the dredged plots, mean (±SE)
size of juveniles (<40 mm in shell height) increased
from 17.04 ±0.83 in January to 20.43 ±0.76 in February.
Over the same time period, mean size changed little in
the control (16.09 ±0.85 to 16.75 ±0.75 mm) or in the
hand-harvested (18.19 ±0.85 to 17.95 ±0.65 mm) plots.
Discussion
Previous research indicates that the implementation of
certain gear restrictions on estuarine bivalve fisheries
can minimize habitat destruction without sacrificing
harvesting efficiency (Peterson et al., 1983b; Lenihan
and Peterson, 2004). In our study, which successfully
mimicked the efficiency of commercial dredging and
NOTE Bishop et al.: Effects of harvest methods on sustainability of a bay scallop fishery
715
Table 1
BACI (Green, 1979) analysis of variance
that tes
ts for ar
impact of scallop harvest
ng on
biomass of seagrass. Nine plots of
seagrass were randomly assigned to three
treatments: undisturbed control
hand-harvested
dredged. Biomass of seagrass was
determined immediately before (Jan 2002) and one month after (Feb 2002) application of treatments to plots, n = 5.
Source
df
MS
F P
Before versus after treatment
1
0.14
0.78 0.41
Treatment
2
0.35
0.81 0.49
Plot (treatment)
6
0.43
3.50 0.00
Before vs. after x treatment
2
0.26
1.41 0.31
Before vs. after x plot (treatment)
6
0.18
1.49 0.19
Residual
72
0.12
Transformation
ln(
v+1)
Cochran's test
C=
3.16<P>0.05)
hand-harvesting of bay scallops (see Burgess
and Bianchi3), hand-harvesting yielded six
times the bay scallop harvest obtained per
unit of time by dredging, while reducing del-
eterious environmental effects. Hand-harves-
tikng did not result in uprooting of seagrass
or displacing juvenile bay scallops, whereas
dredging caused significant damage to sea-
grass. Ten minutes of dredging resulted in an
average dry weight loss of 200 g of seagrass
per plot — 9 % of the estimated biomass of sea-
grass present prior to harvest. Despite this siz-
able removal of seagrass biomass, a persistent
impact of dredging on seagrass biomass was
not detected one month later. To the contrary,
a 39% increase in seagrass biomass was seen
across the dredged plots that was not repli-
cated in the control plots. This result indicated
that dredging had only a short-term negative
impact on seagrass shoots (the necessary pro-
duction of new leaves) and instead appeared
to stimulate new production during the winter
period that was more than sufficient to replace
dredging damage.
Despite the rapid recovery of seagrass from
dredging injury, a sustained negative impact
of dredging on the density of juvenile bay
scallops within plots was detected over the one-month
period of our study. In contrast to the small increases
in juvenile scallop density that occurred in hand-har-
vested and control plots over the course of the study,
mean density of juveniles in dredged plots declined from
1.37 ±0.33 (1 SE) to 0.89 ±0.23 per 0.5 m2. This 40%
reduction in juvenile scallops in dredged plots cannot be
explained by the bycatch alone. Whereas total bycatch
of juveniles was, on average, two scallops per dredged
plot, the average reduction in the density of juvenile
bay scallops was 0.5 per 0.5-m2 quadrat or 200 per
200-m2 plot.
Instead, the reduction in density of juvenile scallops
in dredged plots is best explained by their migration
Before
After
Time
Figure 2
Mean (±1 SE) dry weight of seagrass per 0.25-m2 quadrat in con-
trol (undisturbed), hand-harvested, and dredged plots immedi-
ately before and one month after the 10-minute treatments were
applied. n=15.
after dredging injury to seagrass habitat into adjacent
undisturbed control and hand-harvested plots. Abun-
dances of juvenile bay scallops in hand-harvested and
control plots increased over the one month of our study
by an amount more than sufficient to compensate for
losses of juveniles from dredged plots. These increases
in abundances in control and hand-harvested plots can-
not be attributed to the settlement of new recruits: fall
recruitment of juvenile scallops to seagrass beds is
typically completed by the end of December (Peterson
et al., 1989), spring spawning does not commence until
March (Peterson and Summerson, 1992), and scallops
spawned during our experiment could not possibly have
grown fast enough over one month to reach a size re-
716
Fishery Bulletin 103(4)
Table 2
BACI analysis of variance testing for an impact of scallop harvesting on density of scallop recruits. Nine plots of seagrass were
randomly assigned to three treatments: undisturbed control, hand-harvested, dredged. Density of scallop recruits was deter-
mined immediately before (Jan 2002) and one month after (Feb 2002) application of treatments to plots. »=9.
Source
df MS
F
P
Before vs. after treatment
1 0.89
0.78
0.41
Treatment
2 5.57
2.74
0.14
Plot (treatment)
6 2.03
0.77
0.59
Before vs. after x treatment
2 4.57
4.01
0.08
Before vs. after x plot (treatment)
6 1.14
0.43
0.85
Residual
144
Cochran's test
C = 0.13(P>0.05)
SNK tests
Before vs. after x treatment
Before: control = hand-harvested
After: control = hand-harvested >
= dredged
dredged
tained by sieves (see Irlandi et al., 1999 for growth
rates). Scallops colonizing hand-harvested and control
plots were of the right size and of sufficient abundance
to be those missing from dredged plots. The migration
appears to have included active swimming because tidal
currents were perpendicular to the direction of scallop
movement.
Although juvenile scallops are largely sessile, our in-
terpretation that juveniles migrate in response to dredg-
ing is consistent with field and laboratory observations
of juvenile bay scallop behavior. During seasonal slough-
ing of eelgrass blades, juvenile bay scallops break away
2.4
Dredged
Hand-harvested
Control
Before
Time
After
Figure 3
Mean (±1 SE) number of juvenile bay scallops (s40 mm in
height) per 0.5-m2 quadrat in control (undisturbed), hand
vested, and dredged plots immediately before and one month
the 10-minute treatments were applied. ;i = 15.
shell
-har-
after
and re-establish byssal attachments to seagrass blades
(Thayer et al., 1975). Mesocosm observations confirm
that juveniles are capable of swimming distances of at
least several meters when displaced (Bishop, personal
observ. ). Thus, our experimental restriction on dredging
to small areas may have facilitated relocation of scallops
to adjacent, undisturbed habitat, where they remained
one month later even after seagrass had regrown in the
dredged plots. In the case of the commercial fishery,
however, juvenile scallops emigrating from disturbed
habitat over the extensive fished areas would be far less
likely to encounter undisturbed seagrass habitat for re-
attachment. Indeed, transport to unfavorable
unvegetated habitat where predation risk is
enhanced would likely inflate mortality.
In our study, juvenile scallops lost from the
dredged plots came primarily from the small-
est size classes. Small juvenile scallops are
more susceptible to benthic predators that
forage within seagrass beds than larger ju-
veniles (Pohle et al., 1991). Because the for-
aging efficiency of some predators increases
with decreasing biomass of seagrass (Prescott,
1990), a decrease in seagrass biomass, even
for a period of weeks, would likely increase
predation on juvenile scallops. Thus, small ju-
veniles probably are increasing their chances
of survival by emigrating away from depleted
and into denser seagrass. Larger juveniles, in
contrast, experience a partial size refuge from
predators (e.g., Pohle et al., 1991), and thus
have less incentive to emigrate.
This study considered the impact of only a
single bay scallop-harvesting event on sea-
grass biomass and abundance of juvenile bay
scallops within small experimental plots.
Fishing disturbances are, however, typically
chronic, occurring multiple times within a
given season, and over large spatial scales.
NOTE Bishop et al Effects of harvest methods on sustainability of a bay scallop fishery
717
Before
Control
12
6
0
12
>,
o
c
d 6
<p
l£
0
12
6
0
bCLTHl
0 10 20 30 40
Hand-harvested
-r
fk
0 10 20 30 40
Dredged
I
10
20 30
40
12
6
0
12
6
0
Shell height (mm)
After
tt_a
0 10 20 30 40
10 20 30 40
fil Ul
10
20
30
40
Figure 4
Size-frequency distribution of juvenile bay scallops (<40 mm in shell height)
collected from control, hand-harvested, and dredged plots immediately before
and one month after the 10-minute treatments were applied.
In our study, just 10 minutes of dredging resulted in
the removal of approximately 9% of the total biomass of
seagrass in the experimental plot. Repeating this fish-
ing disturbance over large spatial scales could, there-
fore, have substantial detrimental effects on seagrass
habitat and, as an indirect result, the abundance of bay
scallops that comprise the next generation. In addition,
other habitat functions of seagrass are likely compro-
mised until regrowth occurs. Peterson et al. (1987) dem-
onstrated in this same system that a one-time reduction
of 65% in seagrass biomass from gear disturbance dur-
ing clam harvesting was not replaced over a subsequent
2-year period free of additional fishing.
The results of our study raise doubt about the sus-
tainability of a bay scallop fishery in which the harvest
method is dredging. Because this species, which lives
only 12-24 months, is recruitment-limited (Peterson
and Summerson, 1992; Peterson et al., 1996), reductions
in densities of juvenile bay scallops by dredging will not
only diminish that year's harvest but also presumably
result in less spawning-stock biomass. Without restric-
tions on scallop dredging, impacts of dredging distur-
bance compounded across years may lead to the gradual
collapse of the fishery. Re-imposing gear restrictions
in shallow areas where hand harvest is practical may,
therefore, pay big dividends. When use of the less de-
structive hand method carries little or no penalty of re-
duced fishing success, restricting scallop dredging from
shallow SAV represents an appropriate ecosystem-based
management choice (Botsford et al., 1997) that may
sustain SAV habitat and restore a bay scallop fishery
now in serious decline (Burgess and Bianchi3).
Acknowledgments
We thank Ted Willis of Salter Path for advice and collab-
oration on harvesting methods and intensities. This work
was funded by the North Carolina Fishery Resource
Grant Program administered by North Carolina Sea-
Grant (to C. H. Peterson). This manuscript benefitted
from the comments of two anonymous reviewers.
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NOTE Bishop et al.: Effects of harvest methods on sustainabihty of a bay scallop fishery
719
Thayer, G. W., S. M. Adams, and M. W. LaCroix.
1975. Structural and functional aspects of a recently
established Zostera marina community. In Estuarine
research (L. E. Cronin ed.), p. 518-540. Academic Press,
New York, NY.
Thrush. S. F., J. E. Hewitt, V. J. Cummings, P. K. Dayton,
M. Oyer, S. J. Turner, G. A. Funnell, R. G. Budd, C. J.
Milburn, and M. R. Wilkinson.
1998. Disturbance of the marine benthic habitat by com-
mercial fishing: impacts at the scale of the fishery. Ecol.
Appl. 8:866-879.
Virnstein, R. W., W. G. Nelson, F. G. Lewis, and R. K. Howard.
1984. Latitudinal patterns in seagrass epifauna: do
patterns exist, and can they be explained? Estuaries
7A:310-330.
Watling, L., and E. A. Norse.
1998. Disturbance of the seabed by mobile fishing
gear: a comparison to forest clearcutting. Cons. Biol.
12:1180-1197.
720
Longline-caught blue shark {Prionace glauca):
factors affecting the numbers available
for live release*
Guillermo A. Diaz
Joseph E. Serafy
National Marine Fisheries Service
Southeast Fisheries Science Center
75 Virginia Beach Drive
Miami. Florida 33149
E-mail address (for G A Diaz): Guillermo diazffinoaa gov
temperature, set duration, season,
and area (i.e., Grand Banks and U.S.
Atlantic east coast), the proportion of
blue shark released alive (PDA) was
calculated.
Only sharks explicitly recorded as
"discarded alive" or "discarded dead"
were used and only proportions de-
rived from at least 20 observations
(i.e., captured sharks) were analyzed.
The influence of the fish size, water
temperature, set duration, area, and
season (and all possible interactions)
on PDA was assessed by using the lin-
ear model
The blue shark (Prionace glauca) is
an oceanic species that occurs in tem-
perate and tropical waters around
the globe (Robins and Ray. 1986).
This species is a major bycatch of
pelagic longline fleets that operate to
supply the world's growing demand
for tunas and swordfish (Xiphias gla-
dius) (Stevens, 1992; Bailey et al.,
1996; Francis, 1998; Francis et al.,
2001; Macias and de la Serna, 2002);
numerically, the blue shark is the top
nontarget species captured by the
U.S. longline pelagic Atlantic fleet
(Beerkircher et al.1).
Ward et al. (2004) examined the
effect of longline soak time (set du-
ration) on the catch rate of several
target and bycatch species, including
the blue shark. However, they did not
investigate the effects of fish size,
set duration, and water tempera-
ture on shark survival, and, there-
fore, numbers potentially available
for live release (Francis et al., 2001;
Campana et al.2). Knowledge of such
relationships may be of value: 1) for
minimizing bycatch mortality on this
and other highly vulnerable pelagic
species through modification of fish-
ing strategy; and 2) for blue shark
stock assessments that are based on
commercial longline catch data.
Materials and methods
Data analyses were conducted on a
portion of the U.S. Atlantic Pelagic
Observers Program (POP) database.
The POP places trained observers
aboard commercial fishing vessels
to record detailed information about
each fishing set, the catch and the
bycatch that would not otherwise
be collected. Recorded information
includes individual fish size (mea-
sured or estimated) and disposition
(alive or dead), surface water tem-
perature (°C) at gear deployment and
at haulback, and set location (lati-
tude and longitude). The duration of
each set (soak time, in hours) can
be obtained because time at start of
gear deployment and at end of gear
retrieval is also recorded. In the pres-
ent study, we restricted our analy-
ses to observed sets made from 1992
to 2002 by U.S. flag vessels north
of 35°N latitude (Fig. 1). This area
includes much of the U.S. exclusive
economic zone north of Chesapeake
Bay but also includes waters overly-
ing the Grand Banks. Data resulting
from experimental fishing conducted
from 2001 to 2004 over the Grand
Banks area (i.e., north of 35°N lat-
itude and west of 60°W longitude)
were not included because they did
not reflect typical fishing operations.
For analysis purposes, blue shark
were placed in 25-cm fork length (FL)
size classes and water temperatures
(means) and set durations into 2 C
and 2-hour intervals, respectively.
Size intervals were set at 25 cm
FL to increase the number of obser-
vations in each size category and to
reduce the bias that results from
estimating lengths versus actually
measuring them (e.g., observed in-
crease in the frequency of the esti-
mated lengths in 5- or 10-cm inter-
vals). For each combination of size,
P, = /30 + ftT, + /SD, + /33S,
+ IJ4 L,+ P5A,+ €r
where P, = to the proportion of blue
shark discarded alive;
T = the temperature;
D = set duration;
S = season;
L = length;
A = set area,
€ = the residual term of the
ith observation; and
P0 - j35 are model parameters.
Prior to regression, proportions were
arcsine-transformed according to the
methods of Sokal and Rohlf (1981). In
1 Beerkircher, L. R., C. J. Brown, and D.
W. Lee. 2002. SEFSC pelagic obser-
ver program data summary for 1992-
2000. NOAA Tech. Memo. NMFS-
SEFSC-486, 23 p. Southeast Fisheries
Science Center, Miami, FL 33149.
2 Campana S., P. Gonzalez, W. Joyce, and
L. Marks. 2002. Catch, bycatch and
landings of blue shark (Prionace glauca)
in the Canadian Atlantic. Canadian
Science Advisory Secretariat, Research
Document 2002/101, 41 p. Marine Fish
Division, Bedford Institute of Ocean-
ography. Dartmouth, Nova Scotia, B2Y
4A2, Canada.
Contribution number SFD-2005-030
from the Sustainable Fisheries Divi-
sion, Southeast Fisheries Science Cen-
ter, NMFS, 75 Virginia Beach Drive,
Miami, FL 33149.
Manuscript submitted 19 July 2004
to the Scientific Editor's Office.
Manuscript approved for publication
5 April 2005 by the Scientific Editor.
Fish. Bull 103:720-724 (2005).
NOTE Diaz and Serafy Factors affecting the number of Pnonace glauca available for live release in fisheries
721
80W
70" W 60"W
■ ■
50°W 40"W
1 i
\
'l
N
A
y-
*
^ i >'■*'» it *
^ ' " Grand
• , , Banks
50°N -
40°N -
„ — -rsnL
W
30°N -
Atlantic Ocean
20°N -
\J
^.
— i i
1 i
- 50°N
- 40"N
30=N
80= W
70='W
60°W
50=W
40"W
Figure 1
Locations of observed longline sets (1992-2002) recorded in the U.S. Pelagic
Observers Program database and analyzed in the present study.
the event that a factor was found to be nonsignificant
(P>0.05), it was removed and a regression was rerun
until all highest order model terms were significant
(Hocking, 1976; Draper and Smith, 1981). We assumed
maturity (both sexes) occurred at 185 cm FL (Pratt,
1979). The average PDA and the ratio of immature-to-
mature individuals discarded in each 0.5-degree cell
were estimated and plotted in order to visually examine
the spatial distribution of these two variables.
Table 1
Regression coefficients and associated standard error
values (SE) for the estimation of proportion of blue shark
released alive IPDA) in = 37), where fi0 corresponds to the
intercept, and fi, and /i, are coefficients associated with
blue shark fork length and set duration, respectively.
Parameters
Estimate
SE
P> If I
ft
ft
ft
0.967
0.0021
-0.0269
0.0500
0.0002
0.0037
<0.0001
<0.0001
<0.0001
Results
Data from 702 longline sets were used in analyses and
resulted in size and condition (i.e., live or dead) informa-
tion on 4290 individual blue shark. From these data, a
total of 37 proportions (i.e., PDA values) were calculated shark size and set duration had significant effects on
and used in regression analyses. PDA (r2=0.86, n=37, P<0.00001; Table 1). Plots of the
Most of the sets targeted swordfish (39%) or sword-
fish and tuna (36%), or unspecified tuna species (14%).
Bigeye tuna and yellowfin tuna were the target of 8%
and 3% of the sets, respectively. About 88% of the sets
included in the analysis were characterized as "night
sets" and the remaining were "day sets."
Overall, more blue shark were released alive (69%)
than dead. Shark sizes, water temperatures, and set
durations used in the multiple linear regression ranged
from 75 to 300 cm FL (median=175 cm), 8 to 29°C
(median=19°C), and 6 to 14 hours (median=12), respec-
tively. About 68% of all released animals measured less
than the size of sexual maturity (i.e., <185 cm FL).
Multiple linear regression indicated that no interac-
tion terms were statistically significant and that only
observed proportions and the predicted response surface
illustrate how the proportion of live releases increases
with shark size and decreases with duration of set (Fig.
2, A and B). Whereas set duration has a moderate im-
pact on the largest size classes, the proportion of live
sharks <185 FL (i.e., immature stages) is consider-
ably reduced even at relatively short set durations. For
example, predicted PDA for the smallest sharks (i.e.,
FL=75 cm) was 0.67 and 0.47 for set durations of 6 and
14 hours, respectively; for those animals measuring 250
cm FL, it was 0.94 and 0.80 for the same set durations.
Maps of mean PDA values and of the proportion of imma-
ture sharks caught indicated conspicuous differences off
the U.S. east coast versus over the Grand Banks (Fig.
3, A and B). Specifically, the proportion of live releases
722
Fishery Bulletin 103(4)
tended to be lower over the Grand Banks than off the
U.S. east coast and the mean ratio of immature blue
shark tended to be higher.
Discussion
Our results indicate that blue shark tolerance to the
stresses associated with longline capture decreases with
animal size at levels that vary with set duration. These
results are consistent with the findings of Neilson et al.
(1989) and Milliken et al. (1999) who observed greater
discard mortality among the smallest sizes classes of
Figure 2
(A) Observed proportions of blue shark discarded alive
(ra = 37) for each fork-length set duration combination;
and (B) predicted response surface.
Iongline-caught Atlantic halibut (Hippoglossus hippo-
glossus) and cod (Gadus morhua), respectively. In our
study, set duration represented the maximum possible
time a given fish was "on-hook," and thus was only the
coarsest of measures of the magnitude and duration of
stress experienced by hooked fishes. Nevertheless, this
crude measure appears to have captured enough of the
cumulative stress effects on fish survival to emerge as
a significant factor. In contrast, water temperature did
not emerge as important in our analysis. However, we
suspect this resulted because surface water tempera-
tures (the only temperature measurements available) are
poor indicators of the levels and changes in temperature
actually experienced by captured sharks. Presumably,
better predictions of condition at boat-side (and thus
live discard quantities) could be made with knowledge
of time-on-hook, depth, and temperature of capture,
rate of gear retrieval, sea conditions, etc. Unfortunately,
many of the measurements that are likely most relevant
to recording shark condition at boat-side can only be
made by distributing and retrieving large quantities of
electronic instruments (i.e., temperature-depth recorders
and hook-timers, see Boggs, 1992) near the hooks, and
for each set. Such an approach is not only costly, but also
difficult to implement without a research team dedicated
for this purpose. Similarly, only by directed research
can questions of postrelease mortality be addressed.
Clearly, the proportions of living blue shark considered
in our study are minimum estimates of fishing impacts
because they do not account for delayed mortality of
individuals released injured or otherwise impaired. For
gauging postrelease mortality of Iongline-caught blue
shark, tagging studies are warranted (Neilson et al.,
1989; Kohler et al., 2002).
Evident in the maps is that the proportion of blue
sharks available for live release was not homogeneous
throughout the spatial range examined. Overall the
proportion of blue shark released alive was higher (0.78)
along the U.S. Atlantic east coast and decreased over the
Grand Banks (0.67) (Fig. 3A). The maps also indicated
that overall the proportion of immature blue sharks was
highest over the Grand Banks (0.93) compared to the
U.S. Atlantic east coast (0.63) (Fig. 3B). In their exami-
nation of U.S. Atlantic east coast longline catches south
of the present study (i.e., between 35° and 22°N latitude),
Beerkircher et al. (2004) found that 0.87 of blue shark
caught were alive at boat-side. It seems likely, therefore,
that contributing to the relatively higher survival ob-
served by Beerkircher et al. (2004) was that only about
half of the blue shark in their analysis were immature
(as inferred from size). Blue shark interactions over the
Grand Banks deserve special attention because most in-
dividuals discarded by the U.S. pelagic longline fleet are
captured in that area. In 2002, for example, two thirds
of the estimated 4335 blue shark mortalities attributed
to U.S. Atlantic pelagic longline fleet were captured in
this area (Diaz, unpubl. data3).
Diaz, G. A. 2005. NMFS Pelagic longline logbook pro-
gram. NMFS/SEFSC Miami, FL 33149.
NOTE Diaz and Serafy: Factors affecting the number of Pnonoce glauca available for live release in fisheries
723
V ^
1
■*""<
&-*<
Atlantic
fs**- Ocean
50°N
70" W
60" W
50"W
40°W
40"N
50"N
70"W
60°W
40:N
50"W
40"W
50"N -
40 N
70 W
60"W
50"W
40"W
U 0 0 |m 0.4-0 6
HI 0.0-0.2 |] 0.6-0.8
H7?] 0.2-0 4 ■ 0.8-1.0
50N
40°N
70:W
60°W
50,:-W
40"W
Figure 3
(Ai Average proportion of blue shark released alive and (B) average proportion
of immature blue shark released in pelagic longline sets. Proportions were
estimated for 0.5-degree cells where at least one longline set was deployed in
the period 1992-2002.
Ward et al. (2004) modeled the effect of set duration
on pelagic longline catches and found that blue shark
catch rates increased with set duration. According to
our results, the increase in set durations also leads to
increases in the number retrieved dead. In concept, a
possible management measure to achieve reductions
in blue shark mortality may include shortening long-
line set durations. However, a regulation of this nature
would be difficult to implement (let alone enforce) be-
cause swordfish catch rates are also lowered when set
durations are shortened (Ward et al., 2004) and there-
fore result in negative economic impacts that would
likely be unacceptable to the industry.
Results of this analysis also have implications for
blue shark stock assessment. Stock assessments based
on longline fisheries data often use a hook selectivity
function of a logistic form, whereby hook retention is
100% for fish larger than a certain size. In the particu-
724
Fishery Bulletin 103(4)
lar case of blue shark, where most individuals caught
are released (dead or alive), fishing mortality is best
estimated from the number of animals released dead,
rather than from all animals caught. Because larger
animals have a higher probability of being released
alive, a logistic selectivity function without size or age
survival adjustment, could lead to overestimation of
impacts on the stock. Thus, a dome-shaped selectivity
function that incorporates the size-based survival infor-
mation presented in the present study may represent an
improvement over current techniques.
Acknowledgments
We thank L. Brooks, E. Cortes, S. Turner, and two
anonymous reviewers for invaluable comments on the
manuscript.
Literature cited
Bailey, K., P. G. Williams, and D. Itano.
1996. By-catch and discards in Western Pacific
tuna fisheries: a review of SPC data holdings and
literature. Tech. Rep. Ocean Fish. Programme. S.
Pac. Comm. no 34, 148 p.
Beerkireher, L. R., E. Cortes, and M. Shivji.
2004. Characteristics of shark bycatch observed on
pelagic longlines off the Southeastern United States,
1992-2000. Mar. Fish. Rev. 64(41:40-49.
Boggs, C. H.
1992. Depth, capture time and hooked longevity of
longline-caught pelagic fish: timing bites offish with
chips. Fish. Bull. 90:642-658.
Draper, N., and H. Smith.
1981. Applied regression analysis, 709 p. Wiley Inter-
science, New York. NY.
Francis, M. P.
1998. New Zealand shark fisheries: development, size
and management. Mar. Freshw. Res. 49(7):579-591.
Francis, M. P., L. M. Griggs, and S. J. Baird.
2001. Pelagic shark by-catch in the New Zealand tuna
longline fishery. Mar. Freshw. Res. 52(21:165-178.
Hocking R. R.
1976. The analysis and selection of variables in linear
regression. Biometrics 32:1-50.
Kohler, N. E., P. A. Turner. J. J. Hoey, L. J. Natanson, and R. Briggs.
2002. Tag and recapture data for three pelagic sharks
species: blue shark (Prionacea glauca), shortfin mako
(Isurus xyrinchus), and porbeagle lLamna nasus) in
the North Atlantic ocean. International Commis-
sion for the Conservation of Atlantic Tuna (ICCAT)
54(41:1231-1260.
Macias D., and J. M. de la Serna.
2002. By-catch composition in the Spanish Mediterra-
nean longline fishery, 198 p. Proc. 4th meeting of the
European Elasmobranch Association. Societe Francaise
d'Ichtyologie, Paris, France.
Milliken. H. O., M. Farrington, H. A. Carr, and E. Lent.
1999. Survival of Atlantic cod (Gadus morhua) in the
Northwest Atlantic longline fishery. Mar. Technol.
Soc. J. 33:19-24.
Neilson, D. J., K. G. Waiwood, and S. J. Smith.
1989. Survival of Atlantic halibut (Hippoglossus hippo-
glossus) caught by longline and otter trawl gear. Can.
J. Fish. Aquat. Sci. 46:887-897.
Pratt, H. L„ Jr.
1979. Reproduction in the blue shark, Prionace glauca.
Fish. Bull. 77:445-470.
Robins, C. R., and G. C. Ray.
1986. A field guide to Atlantic coast fishes of North
America. Peterson Field Guide Series, 354 p. Houghton
Mifflin, Boston, MA.
Stevens, J. D.
1992. Blue and mako shark by-catch in the Japanese
longline fishery off south-eastern Australia. Sharks:
biology and fisheries. Aust. J. Mar. Freshw. Res.
43(11:227-236.
Sokal, R. R., and F. J. Rohlf.
1981. Biometry, 2nd ed.. 859 p. W. H. Freeman. New
York, NY
Ward, P., R. A. Myers, and W. Blanchard.
2004. Fish lost at sea: the effect of soak time on pelagic
longline catches. Fish. Bull. 102:179-195.
725
Length correction for larval and early-juvenile
Atlantic menhaden (Brevoortia tyrannus)
after preservation in alcohol
Dariusz P. Fey
Sea Fisheries Institute
Dept. of Fisheries Oceanography and Marine Ecology
ul. Kollataia 1
81-332 Gdynia, Poland
E-mail address dfeyg'mirgdynia pi
Jonathan A. Hare
NOAA National Ocean Service
Center for Coastal Fisheries and Habitat Research
101 Pivers Island Road
Beaufort, North Carolina 28516-9722
Body length measurement is an im-
portant part of growth, condition,
and mortality analyses of larval and
juvenile fish. If the measurements are
not accurate (i.e., do not reflect real
fish length), results of subsequent
analyses may be affected consider-
ably (McGurk, 1985; Fey, 1999; Porter
et al., 2001). The primary cause of
error in fish length measurement is
shrinkage related to collection and
preservation (Theilacker, 1980; Hay,
1981; Butler, 1992; Fey, 1999). The
magnitude of shrinkage depends on
many factors, namely the duration
and speed of the collection tow, abun-
dance of other planktonic organisms
in the sample (Theilacker, 1980; Hay,
1981; Jennings, 1991), the type and
strength of the preservative (Hay,
1982), and the species of fish (Jen-
nings, 1991; Fey, 1999). Further, fish
size affects shrinkage (Fowler and
Smith, 1983; Fey, 1999, 2001), indi-
cating that live length should be mod-
eled as a function of preserved length
(Pepin et al., 1998; Fey, 1999).
The goal of this study was to ana-
lyze the shrinkage of late-larval and
early-juvenile Atlantic menhaden
(Brevoortia tyrannus) during pres-
ervation in 95% alcohol. A length
correction formula is presented that
allows live standard length to be
calculated from preserved standard
length.
Materials and methods
Larval and early juvenile Atlantic
menhaden were collected on three
different occasions during January-
March 2003 with a neuston net (2-m2
opening and 947-,um mesh) deployed
for 2-minute durations from a bridge
to Pivers Island, located about 2 km
inside Beaufort Inlet, North Caro-
lina. Samples were placed in a cooler
and transported to the laboratory.
Live Atlantic menhaden larvae were
sorted from the samples (?i=100) and
their standard lengths (SL) were mea-
sured to the nearest 0.01 mm with a
caliper. All specimens (19.1-31.4 mm
SL) were placed in individual vials
filled with 95% ethyl alcohol. The fish
were remeasured 3. 20, and 90 days
after preservation.
Repeated measures ANOVA and
Tukey HSD tests were used to ana-
lyze the significance of length changes
during 90 days of preservation. The
preserved length after 90 days was
than compared with live length to
test whether a single correction factor
is appropriate for a calculation of live
length (/-test analysis for the slope
difference from one). Additionally,
the precision of measurements was
evaluated by two replicate measure-
ments of all larvae three days after
preservation. Linear regression anal-
ysis was then used to describe the
relationship between the two length
measurements. The possible deviation
of intercept from zero and slope from
one was estimated (/-test) to test for
the possible significant differences
between the two measurements.
Results
Time in preservative had a significant
effect on measured length of Atlantic
menhaden larvae (repeated measures
ANOVA, P<0.0001). Fish were sig-
nificantly larger prior to preservation
compared to three days after pres-
ervation (Tukey HSD, P<0.001) and
significantly larger three days after
preservation compared to 20 and
90 days after preservation (Fig. 1)
(Tukey HSD, P<0.001). When shrink-
age is described as a relative value,
the change in length that occurred
during the first three days of preser-
vation was 3.62%. Length decreased
by an average of 0.22% during the fol-
lowing 17 days and by 0.073% during
the remaining 70 days.
Although smaller fish shrank pro-
portionally more than the larger
ones (/-test for H0: slope = 0, P<0.001)
(Fig. 2A), no size effect was observed
when shrinkage was analyzed as
absolute length (regression slope =
0.996, SE = 0.008; HQ: slope=l; /-test
of regression slope, P=0.605). How-
ever, the ^-intercept of the regres-
sion of preserved length at 90 days
on live length was significantly
different from zero (regression in-
tercepts.17; SE = 0.21; H0: y-inter-
cept=0; /-test of regression intercept,
P<0.001) (Fig. 2B). Therefore, the
significantly different from zero in-
tercept can be used as a correction
factor (i.e., SLfresh = SLpreserl.ed+l.l7
mm). The shrinkage magnitude
observed by Maillet and Checkley
(1991) was compared to the results
derived in our study (Fig 2B). Their
formula indicated shrinkage of about
2% compared to approximately 4% in
our study.
Manuscript submitted 31 March 2004
to the Scientific Editor's Office.
Manuscript approved for publication
8 February 2005 by the Scientific Editor.
Fish. Bull. 103:725-727 (2005).
726
Fishery Bulletin 103(4)
The two readings performed to estimate the measure-
ment error were not statistically different as indicated
by the parameters of the regression line fitted to the
first measurement versus second measurement data
(SL1 = 0.992 SL2 + 0.21, /-2 = 0.998). The slope was not
statistically different from one (regression slope=0.992,
SE = 0.005; H0: slope = l; ?-test of regression slope,
P=0.106), and the intercept was not statistically differ-
ent from zero (regression intercept=0.21; SE = 0.12; H0:
•10 0 10 20 30 40 50 60 70 80 90
Time of preservation (days)
Figure 1
Change in standard length of Atlantic menhaden (Brevoortia
tyrannies) (n=100) during 90 days of preservation in 95%
alcohol. Mean values and standard error of length measure-
ments obtained from repeated measurements of 100 fish.
y-intercept=0; r-test of regression intercept, P=0.418).
Measurement precision, the absolute values of the dif-
ference between the two series of length measurements
of the same specimens averaged 0.12 mm (SD = 0.09),
which corresponded to an average of 0.47% of length
(SD = 0.35). Thus, the error associated with measure-
ment is an order of magnitude less than the change in
length due to shrinkage within the first three days
of preservation. Changes in length during following
87 days were below measurement error.
Discussion
This research on late-larval and early-juvenile Atlan-
tic menhaden shrinkage is the first for this spe-
cies. Maillet and Checkley (1991) used a shrinkage
correction formula (cited as unpubl. data) in their
study on larval menhaden growth but did not provide
additional information (e.g., range offish sizes) to
accompany their formula. Their correction formula
differs from ours, and the discrepancy may be related
to differences in experimental procedure and differ-
ent developmental stages. In the present study live
fish were used, but in Maillet and Checkley 's study
(1991) it was not indicated whether larvae were alive
or dead prior to preservation. Further Maillet and
Checkley (1991) examined larval menhaden (17-24.5
mm SL), whereas we examined late-larval to early-
juvenile menhaden (19.1-31.4 mm SL).
The shrinkage of larval and early-juvenile Atlan-
tic menhaden after the first three days of preserva-
tion was significant, but small in magnitude. Be-
yond 20 days of preservation significant additional
shrinkage did not occur. In fact, the length changes
after day 3 were below the estimated measurement
7
A
33
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19 21 23 25 27 29
Live standard length (mm)
31
33
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4^^
LSL = 0.996(PSL) +
r2 = 0.993
17
19 21 23 25 27 29 31
Preserved standard length (mm)
33
Figure 2
Length changes of Atlantic menhaden (Brevoortia tyrannus) during preservation for 90 days in 95% alcohol (;i = 100). (A)
The relationship between live standard length (LSL) and relative (%) shrinkage magnitude; (B) the relationship between
live and preserved standard lengths described with linear regression. The solid line indicates the 1:1 ratio. The arrow
points to the correction curve obtained from Maillet and Checkley (1991): SL/„,,. = 0.978(SL ic1 -s "
NOTE Fey and Hare: Length correction for larval and early-|uvemle Brevoortia tyrannus
727
error. Additionally, decreasing shrinkage as a function
of increasing fish length was present when relative (%)
shrinkage was analyzed. Similar results with regard
to time and fish size effect were previously reported for
other fish species preserved with formalin and alcohol
(see Fey, 1999, for overview).
The effect of shrinkage on growth rate analysis was
described by Fey (1999) for larval sprat. If growth rate
is estimated by using a regression of length at age, the
influence of shrinkage on growth estimates depends on
the absolute value of length changes (i.e., expressed in
mm) among small and large fish, and the error may be
as high as 0.07 mm/d. However, if the absolute values
of length decrease equally across fish lengths, even
large shrinkage (on average) may have no effect on the
results of growth rate analysis. In addition to length
at age analysis, average growth rate (mm/d) may be
calculated for individual fish. The potential error in
growth estimates will then be directly proportional to
both the relative and absolute magnitude of shrink-
age. This potential bias in growth-rate calculations
described by Fey (1999) for sprat emphasizes the im-
portance of correcting for preservation. Although the
relationship between otolith size and fish size may be
used for length correction (Leak, 1986; Radtke, 1989).
Fey (1999) showed that greater accuracy is provided
when a fresh length-preserved length relationship
is used. However, such a relationship may be supple-
mented by additional measurements (i.e., body depth
and otolith size) to improve the accuracy of the correc-
tion model (Porter et al.. 2001). In the current study,
absolute changes in length (expressed in mm) of alcohol-
preserved menhaden were not dependent on fish size
and therefore a single correction factor was sufficient
for a calculation of live length. The length correction
factor provided in our study will benefit future studies
on the ecology of early life stages of menhaden, similar
to that conducted by Warlen et al. (2002), where pre-
served length measurements were used.
Acknowledgments
This research was performed while the first author held
a National Research Council Research Associateship
Award at NOAA Beaufort Laboratory. This note is also
a contribution to the State Committee for Scientific
Research (grant no. 2P04F 005 27).
Literature cited
Butler. J. L.
1992. Collection and preservation of materials for oto-
lith analysis. /;; Otolith structure examination and
analysis (D. K. Stevenson and S. E. Campana, eds. i. p.
13-17. Can. Spec. Pub. Fish. Aquat. Sci. 117.
Fey, D. P.
1999. Effects of preservation technique on the length of
larval fish: methods of correcting estimates and their
implication for studying growth rates. Arch. Fish. Mar.
Res. 47:17-29.
2001. Length correction of larval and early-juvenile her-
ring tClupea harengus) and smelt [Osmerus eperlanus >
after preservation in formalin and alcohol. Bull. Sea
Fish. Inst, ll 1551:47-51.
Fowler, G. M., and S. J. Smith.
1983. Length changes in silver hake (Merluccius bilinearis )
larvae: effects of formalin, ethanol, and freezing. Can.
J. Fish. Aquat. Sci. 40:866-870.
Hay. D. E.
1981. Effects of capture and fixation on gut contents and
body size of Pacific herring larvae. Rapp. P.-V. Reun.
Cons. Int. Explor. Mer 178:395-400.
1982. Fixation shrinkage of herring larvae: effects of
salinity, formalin concentration, and other factors. Can.
J. Fish. Aquat. Sci. 39:1138-1143.
Jennings, S.
1991. The effects of capture, net retention and preserva-
tion upon lengths of larval and juvenile bass, Dicentrar-
chus labrax iL.). J. Fish Biol. 38:349-357.
Leak. J. C.
1986. The relationship of standard length and oto-
lith diameter in larval bay anchovy, Anchoa mitchilli
iVal.). A shrinkage estimator. J. Exp. Mar. Biol. Ecol.
95:17-23.
Maillet, G. L., and D. M. Checkley Jr.
1991. Storm-related variation in the growth of otolith of
larval Atlantic menhaden Brevoortia tyrannus: a time
series analysis of biological and physical variables and
implications for larva growth and mortality. Mar. Ecol.
Prog. Ser. 79:1-16.
McGurk. M. D.
1985. Effect of net capture on the postpreservation mor-
phometry, dry weight, and condition factor of Pacific
herring larvae. Trans. Am. Fish. Soc. 114:348-355.
Pepin. P.. J. F. Dower, and W. C. Legget.
1998. Changes in the probability density function of
larval fish body length following preservation. Fish.
Bull. 96:633-640.
Porter, S. M., A. L. Brown, and K. M. Bailey.
2001. Estimating live standard length of net-caught
walleye Pollock (Theragra chalcogramma) larvae using
measurements in addition to standard length. Fish.
Bull. 101:384-404.
Radtke, R. L.
1989. Larval fish age, growth, and body shrinkage: infor-
mation available from otoliths. Can. J. Fish. Aquat.
Sci. 46:1884-1894.
Theilacker, G. H.
1980. Changes in body measurements of larval northen
anchovy, Engrciulis mordax, and other fishes due to
handling and preservation. Fish. Bull. 78:685-692.
Warlen, S. M., K. W. Able, and E. H. Laban.
2002. Recruitment of larval Atlantic menhaden [Brevoor-
tia tyrannus) to North Carolina and New Jersey estuaries:
evidence for larval transport northward along the east
coast of the United States. Fish. Bull. 100:609-623.
728
Comparison of average larval fish
vertical distributions among species
exhibiting different transport pathways
on the southeast United States continental shelf
Jonathan A. Hare
John J. Govoni
Center for Coastal Fisheries and Habitat Research
101 Pivers Island Road
Beaufort. North Carolina 28516
Present address (for J A. Hare): Narragansett Laboratory
Northeast Fisheries Science Center
28 Tarzwell Drive
Narragansett, Rhode Island 02882
E-mail address (for J A Hare) ion hareia'noaa.gov
Water currents are vertically struc-
tured in many marine systems and
as a result, vertical movements by
fish larvae and zooplankton affect
horizontal transport (Power. 1984).
In estuaries, the vertical movements
of larvae with tidal periods can result
in their retention or ingress (Fortier
and Leggett, 1983; Rijnsdorp et al.,
1985; Cronin and Forward. 1986; For-
ward et al., 1999). On the continental
shelf, the vertical movements of organ-
isms interact daily and ontogeneti-
cally with depth-varying currents to
affect horizontal transport (Pillar et
al., 1989; Barange and Pillar, 1992;
Cowen et al., 1993, 2000; Batchelder
et al., 2002).
A suite of fish species, which use
estuaries during the juvenile stage,
spawn during winter on the mid- and
outer continental shelf of the south-
east United States (Fig. 1A): Brevoor-
tia tyrannus (Atlantic menhaden),
Leiostomus xanthurus (spot), Micropo-
gonias undulatus (Atlantic croaker),
Paralichthys albiguta (Gulf flounder),
P. dentatus (summer flounder), and P.
lethostigma (southern flounder). Ver-
tically structured flow is a major part
of proposed larval transport mecha-
nisms for these species from offshore
spawning areas to estuarine nurs-
ery habitats (Govoni and Pietrafesa,
1994; Hare et al., 1999). Brevoortia
tyrannus, however, is found higher
in the water column on average than
the other species that use estuaries
during their juvenile stage (Miller
et al., 1984; Govoni and Pietrafesa,
1994; Govoni and Hoss, 2001). Fur-
ther, larvae of B. tyrannus apparent-
ly exhibit a difference in horizontal
transport compared to other winter-
spawning species that use estuarine
habitats as juveniles; B. tyrannus lar-
vae spawned on the southeast U.S.
shelf may be transported to estuarine
nursery habitats along the northeast
U.S. shelf (Warlen et al., 2002). The
effects of differences in vertical lar-
val distribution on cross-shelf lar-
val transport are unknown, and the
transport pathways from shelf spawn-
ing areas to estuarine nursery areas
remain unclear.
Other species also spawn during
winter on the southeast United States
continental shelf. Some species settle
to benthic habitats on the shelf (e.g.,
Etr'opus cyclosquamus [shelf floun-
der], E. microstomus [smallmouth
flounder], and E. rimosus [grayfloun-
der], Leslie and Stewart, 1986) or re-
main on the shelf in pelagic habitats
(e.g., Etrumeus teres [round herring],
Crawford, 1981; Schwartz, 1989).
However, some species are regularly
advected offshore, entrained into the
Gulf Stream, and exported north-
wards (e.g., Bothus spp. [peacock,
eyed, and spotted flounders], Pepri-
lus triacanthus [butterfish], Syacium
papillosum [dusky flounder], Xyrich-
tys novacula [pearly razorfish]; Hare
and Cowen, 1991; Cowen et al., 1993;
Rotunno and Cowen, 1997; Grothues
and Cowen, 1999).
The purpose of our study was to ex-
amine associations between average
larval fish vertical distributions and
general larval transport pathways
on the southeast United States conti-
nental shelf during winter. Our goal
was to determine if larval vertical
distributions differed among species
that exhibit different outcomes of lar-
val transport: export from the local
shelf, arrival at local estuaries, and
retention on the shelf. Our approach,
however, was unconventional. Rather
than couple detailed descriptions of
the flow field with detailed describi-
tions of larval vertical distributions
(including diel variation), we chose to
compare average vertical distributions
among species that exhibit overall
differences in larval transport. Verti-
cal distribution data were collected in
three separate years, over periods of
time ranging from 24 to 96 hours. If
average larval vertical distributions
are different among species, and these
differences occur consistently among
the various sampling times and in
concordance with the general outcome
of transport, then we conclude that
larval vertical distributions are an
important part of larval transport on
the southeast U.S. shelf.
Our specific objectives were two-
fold: 1) to test the null hypothesis
that there are no differences in lar-
val fish vertical distributions between
species, and 2) to evaluate significant
differences in larval depth distribu-
tion in relation to the a priori clas-
sification of the outcome of transport.
Vertically discrete data from six sam-
pling times were analyzed, and ow-
ing to differences in protocols among
sampling times, comparisons of lar-
val vertical distributions were made
within sampling times only. The re-
sults of these comparisons were then
combined to evaluate whether there
were consistent differences in larval
vertical distributions among sampling
times related to the outcome of larval
transport.
Manuscript submitted 5 April 2004
to the Scientific Editor's Office.
Manuscript approved 30 March 2005
by the Scientific Editor.
Fish. Bull 103:728-736(2005).
NOTE Hare and Govoni: Larval fish transport and vertical distributions on the southeast US continental shelf
729
Cape Hatteras
16
35
34
A 1986
■ 1989
• 1991
33
77
Longitude °W
75
Figure 1
(A) Map of the east coast of the United States rotated 18° counter-clockwise. The
spatial extent of the northeast and southeast United States continental shelves
is indicated by each rectangle. The area of panel B is shown as a trapezoid. (B)
The northern portion of the southeast United States continental shelf showing
the coastline, the 10-m, 20-m, 30-m 40-m, 50-m, and 100-m isobaths. The three
prominent capes are identified and locations of stations sampled in this study
are shown.
Material and methods
Data collection
Larval fish were collected every six hours (0600, 1200,
1800, and 2400) at an offshore and an inshore station
during three winters: 21-26 February 1986, 26 January-
1 February 1989, and 5-7 February 1991 (Fig. IB).
Offshore stations were located on approximately the
50-m isobath, and inshore stations were located on
approximately the 35-m isobath. In 1986, offshore and
onshore stations were occupied for 102 and 48 h, respec-
tively. Collections were taken horizontally at 1, 18, and
32 m at the offshore station and 1, 13, and 25 m at the
inshore station with a 60-cm opening-closing bongo net
(Weibe and Benfield, 2003) with 333-^m mesh and a
1-m2 Tucker trawl ( Weibe and Benfield, 2003 ) with 202-f<m
mesh. In 1989, offshore and inshore stations were occu-
pied for 78 and 72 hours, respectively. Collections were
taken horizontally at 1, 22, and 45 m at the offshore
station and 1. 13, and 30 m at the inshore station with
a 1-m2 Tucker trawl with 333-,um mesh. In 1991, offshore
and inshore stations were occupied for 24 and 30 h,
respectively. Collections were made with 1-m2 MOC-
NESS (Wiebe et al., 1976) with 333-jim mesh. Oblique
samples were collected within 5-m intervals from 35 m
to the surface at the offshore station and from 30 m to
the surface at the inshore station. The mid-point of each
depth stratum was used as the depth of the collection. In
1986 and 1989, volume of water filtered was measured
with a flowmeter (General Oceanics model 2030, Miami,
FL) with a standard rotor. In 1991, volume filtered was
measured with a flowmeter provided with the MOC-
NESS (BESS, Falmouth, MA).
Larval fish were sorted from collections and identified
to the lowest taxon possible. The larvae of selected taxa
were counted: Bothus spp., Etropus spp. (not including
E. crossotus). E. teres, Paralichthys spp., P. triacanthus,
S. papillosum and X. novaeula. Counts of B. tyrannus.
L. xanthurus, and M. undulatus were obtained from
Govoni and Pietrafesa (1994) and Govoni and Spach
(1999). Larval concentrations were calculated for each
depth stratum (number of larvae/100 m3).
Comparisons of larval vertical distributions
Center of mass calculations are frequently used for com-
parison offish larval depth distributions (e.g., Brodeur
and Rugen, 1994), but Pearre (1979) raised valid criti-
cisms of this approach; for example a uniform distribu-
tion still has a mean depth. To obviate these criticisms,
larval depth distributions of each taxon were compared
730
Fishery Bulletin 103<4>
by using a test of independence (Pearson chi-square.
Sokal and Rohlf, 1981; McCleave et al. 1987). Depth
distributions were averaged over each station. Compari-
sons were then made between all pairs of taxa within
a station, and a Bonferoni correction was applied to
assess the significance of the tests of independence.
Comparisions were not made between stations, because
sampling methods varied and depth distributions were
not directly comparable. The following null hypothesis
was evaluated: during each station occupation, average
larval depth distributions were independent of species.
Column and row variables were species and depth strata;
cell values were the average proportion of the larvae
captured in a depth stratum at a station. Comparisons
of center of mass were also made and the results were
very similar to the results of the test of independence
reported in the present study.
The calculation of average proportion was made in
two steps. First, the proportion of larvae (P) collected in
each depth stratum id) at each sampling time (i) during
each station occupation (J) was calculated:
the individual species comparisons were pooled across
station by the a priori assigned outcome of transport.
The number of significant differences found between
species were then compared to the number of significant
differences expected with a 5% error rate by using the
G-statistic (Sokal and Rohlf 1981). For example, in
a comparison of B. tyrannus to exported species, five
pairwise comparisons of larval depth distributions were
found to be significantly different and 12 were not sig-
nificantly different. At «=0.05, one significant and 16
nonsignificant differences are expected. The G-statistic
demonstrates that more significant differences were
found between B. tyrannus and exported species than
expected by chance. The classifications of significant
depth differences (shallower, deeper, different) were
then examined to determine the relation between larval
vertical distributions and the general outcome of larval
transport.
Results
dij
'dij
where C = larval concentration 100/m3.
Then the average proportion of larvae (P) for each depth
stratum (d) was calculated for each station (J):
IP*
where nn= the number of sampling times (;') during
station occupation (J).
Because the significance of a test of independence
depends, in part, on the magnitude of the cell values
(i.e., sample sizes), average larval concentration of each
species during each station occupation (number of lar-
vae/100 m3) was used as a weighting factor. The av-
erage proportion of larvae at depth during a station
occupation (Pd.) was multiplied by the weighting factor
to derive the cell values for use in the test of indepen-
dence. The weighting factor approximated the number
of fish larvae collected, and incorporated the effect of
variability in sampling volume.
Values of the standardized residuals, which are a
result of the test of independence, were used to classify
significant differences in depth distribution as follows:
species A shallower (<) than species B, species A deeper
(>) than species B, and species A distributed differently
(< or >) than species B. This last category was assigned
when one species was not clearly deeper or shallower
than the other species, yet its depth distributions were
significantly different.
To evaluate whether larval fish vertical distributions
were associated with larval transport, the results of
Comparison of larval vertical distributions indicated
that B. tyrannus often had the shallowest larval verti-
cal distribution. There were more significant differences
than expected by chance between the vertical distribu-
tions of B. tyrannus and exported, estuarine, and shelf-
resident taxa (Table 1). For all significant differences,
the standard deviates from the test of independence
indicated that B. tyrannus were found in shallower water
than were other taxa (Appendix 1).
Exported taxa generally were higher in the water col-
umn than estuarine and shelf-resident taxa. There were
more significant differences than expected by chance
between the vertical distributions of exported taxa and
estuarine and shelf-resident taxa (Table 1). Further, 9
of 12 significant differences between exported and es-
tuarine taxa indicated that exported taxa were found in
shallower water; 8 of 11 significant differences between
exported and shelf resident taxa indicated that exported
taxa were found in shallower water (Appendix 1).
The vertical distributions of estuarine and shelf-resi-
dent taxa were different more often than expected by
chance, but taxa of neither group were consistently
found in shallower water (Table 1). Significant differ-
ences in larval vertical distributions were distributed
evenly among the three classifications of the direction
of difference (»=4 shallower; n=2 deeper; ;; = 5 different)
(Appendix 1).
Discussion
The results indicate an overall hierarchy of larval ver-
tical distributions; B. tyrannus was found in shallower
water than were exported taxa, and exported taxa
were shallower than estuarine and shelf-resident taxa.
Although this general pattern emerged, considerable
variability in larval vertical distributions was observed,
which is a common result of many studies (e.g., Boehlert
NOTE Hare and Govoni: Larval fish transport and vertical distributions on the southeast US continental shelf
731
Table 1
Summary of the pairwise comparisons of larval depth distributions between species classified by the a priori outcome of trans-
port. In each table cell, the number to the left is the number of significant pairwise differences, the number to the right is the
total number of comparisons across the six station occupations, and the number in parentheses is the G-statistic for evaluating
the null hypothesis that the number of observed differences is as expected with a 5% error rate. The critical value at «=0.05 is
5.99 and significant values are indicated in bold. Values greater than 5.99 indicate that there are more significant differences
between species than expected by chance. Exported taxa are Bothus spp., Peprilus triacanthus, Syacium papillosum, Xyrichtys
novacula. Estuarine taxa include Leiostomus xanthurus, Micropogonias undulatus, and Paralichthys spp. Shelf resident taxa
include Etropus spp. and Etrumeus tei'es.
A priori classification of the outcome of transport
Brevoortia tyrannus
Exported
Estuarine
Shelf resident
Exported
Estuarine
Shelf resident
5/ 17(10.29)
12/15(55.35)
9/ 12(39.11)
2/17(1.17)
12/43(23.88)
11/34(25.09)
5/13(12.96)
11/30(27.96)
2/6(4.39)
and Mundy, 1994; Brodeur and Rugen, 1994). Variability
in larval fish vertical distributions (and zooplankton) is
related to processes that influence water column mixing
(e.g.. Heath et al„ 1988; Incze et al., 2001) and to spe-
cies-specific responses to diel cycles and gradients in
turbulence, temperature, and salinity (DeVries et al.
1995; Olla et al., 1996; Gray and Kingsford, 2003). The
approach used in the present study was to average over
shorter-scale variability (hours) in larval vertical dis-
tributions to examine longer-time-scale patterns (days)
in larval vertical distributions.
Average larval vertical distributions of exported,
estuarine-dependent. and shelf-resident taxa and the
implied outcomes of their larval transport are consis-
tent with the results of physical oceanographic models
and observations of shelf circulation in the southeast
United States continental shelf. The model of Janowitz
and Pietrafesa (1980) (see also Miller et al., 1984) in-
dicated a three-layered, cross-shelf flow during winter:
surface and near-bottom offshore flow, and intermedi-
ate onshore flow. Similarly, the model of Werner et al.
(1999) indicated a two-layered, cross-shelf flow during
winter: an offshore flow near the surface and onshore
flow throughout the rest of the water column. Surface
flow in the study area during winter is typically off-
shore (Govoni and Pietrafesa, 1994). On the inner and
middle shelf (water depths <40 m), average bottom flow
is onshore; on the outer shelf (water depth 40-75 m),
average intermediate flow is onshore, whereas bottom
flow is offshore (Fig. 5b in Lee et al.. 1989). Modeled
and observed flow fields may indicate that larvae in the
surface water will move offshore (exported taxa), where
the probability of entrainment into the Gulf Stream is
higher. Larvae that are in the middle or lower portion
of the water column will move onshore (i.e., estuarine-
dependent and shelf-resident taxa). Thus, the average
larval vertical distributions, the general outcome of
larval transport, and the generalized observed and
modeled vertical flow fields are consistent.
Differences between vertical distributions of larval
B. tyrannus and the other estuarine-dependent taxa
(Fig. 2; see also Govoni and Pietrafesa, 1994) imply
differences in cross-shelf transport. There are several
possibilities, none mutually exclusive. 1) Onshore trans-
port of larval B. tyrannus occurs with northeast wind
events and onshore transport of other estuarine-depen-
dent larvae occurs with southwest or northwest wind
events. This possibility is supported by the model simu-
lations of Hare et al. (1999). 2) Cross-shelf transport
of B. tyrannus larvae occurs in surface Gulf Stream
intrusions (Checkley et al., 1988; Stegmann and Yoder,
1996), whereas cross-shelf transport of other estuarine-
dependent larvae occurs by wind-driven mechanisms.
This possibility has not been adequately evaluated. 3)
All estuarine-dependent larvae are transported across
the shelf by the same mechanisms, but the rate of their
transport differs. For example, southwest wind events
cause onshore transport rates to be greater for the other
estuarine-dependent taxa because B. tyrannus larvae
spend less time in the intermediate portion of the wa-
ter column. This possibility is also supported by Hare
et al. (1999), who found that in modeled larval vertical
distributions, the outcome of larval transport was modi-
fied by circulation. From these alternative hypotheses,
it is clear that our understanding of the cross-shelf
transport of larval fishes remains incomplete and that
the effective physical and biological mechanisms are
complex.
One approach to resolving the affect of vertical dis-
tribution on cross-shelf larval transport is to develop a
specific hypothesis regarding supply of larvae to inlets
that is based on the above possibilities and then to test
these hypotheses using the long time-series of larval
ingress collected at Beaufort Inlet (see Warlen, 1994).
Three alternative patterns in ingress, based on the
three possibilities presented above, could be evaluated
by using ingress data collected at Beaufort Inlet: 1) in-
gress of B. tyrannus occurs during northeast winds, and
732
Fishery Bulletin 103(4)
Inshore- 1986
K
mm
£ 15l
q- r
Bt Sp Bs Pt Xn Ps Lx Mu Et Es
Inshore- 1989
Offshore- 1986
1-
h
£$
i-.a-
r -3- ■
:t
^
§-
■f-
f-
g-
s-
T.F..
§-
S-
§-
Bt Sp Bs Pt Xn Ps Lx Mu Et Es
Offshore- 1989
iEffl EE
B- i-
Bt Sp Bs Pt Xn Ps Lx Mu Et Es
Inshore- 1991
Bt Sp Bs Pt Xn Ps Lx Mu Et Es
Offshore- 1991
u
Bt Sp Bs Pt Xn Ps Lx Mu Et Es
Bt Sp Bs Pt Xn Ps Lx Mu Et Es
Mean proportion of larval concentration at depth
Figure 2
Mean proportions of larvae sampled at depths at six stations on the southeast United States
shelf. Error bars indicate standard deviation of mean proportions calculated by using all the
samples collected at a station. The x-axis of all panels is the same and ranges from 0 to 1.2.
The species indicated in each figure is denoted by a two letter code (P>t=Brevoortia tyrannus,
Sp = Syacium papillosum, B>s=Bothus spp., Pt=Peprilus triacanthus, Xn=Xyrichtys novacula,
Ps=Paralichthys spp., Lx =Leiostomus xanthurus, Mu=Micropogonias undulatus, Et=Etrumeus
teres, and Es=Etropus spp.). Species are grouped by an a priori assignment of their general
outcome of transport.
the ingress of other species occurs during northwest,
west, and southwest winds; 2) ingress of B. tyrannus
is not related to wind, and ingress of the other species
is related to northwest, west, and southwest winds; 3)
and ingress of all estuarine-dependent species occurs
during similar wind forcing. Other studies have estab-
lished similar a priori predictions for relations between
wind forcing and ingress, yet results have been equivo-
cal (e.g., Blanton et al., 1995). One explanation is that
cross-shelf larval transport and larval ingress occur
through multiple steps (Boehlert and Mundy, 1988; Het-
tler and Hare, 1998), effectively decoupling wind-driven,
cross-shelf larval transport from larval ingress.
Similarities in vertical distributions of larval B.
tyrannus and exported larval taxa indicate that a great-
er proportion of B. tyrannus larvae may be entrained
into the Gulf Stream than larvae of other species that
use southeast estuaries as juvenile nurseries. Once
entrained into the Gulf Stream, larvae are transported
northeastward and they either continue to move in the
Gulf Stream or are returned to the shelf edge north of
Cape Hatteras by warm-core ring streamers or in dis-
charges of Gulf Stream water (Hare and Cowen 1991,
1996; Churchill et al., 1993; Cowen et al., 1993; Hare
et al., 2002). Govoni and Spach (1999) reported offshore
exchange of B. tyrannus larvae into the Gulf Stream,
and Warlen et al. (2002) concluded that some B. tyran-
nus larvae spawned south of Cape Hatteras do enter
estuaries north of Cape Hatteras in the spring. The
mechanisms of northward transport of B. tyrannus have
yet to be studied, but transport to the northeast United
States shelf edge by the same mechanisms as those that
drive exported taxa is possible.
In marine systems, larval fish interact with verti-
cally structured flow with vertical motions and thereby
affect their horizontal transport (Cowen et al., 1993,
2000; Grioche et al., 2000). Apart from specific trans-
port mechanisms, the present study demonstrates an
overall link between larval vertical distributions and
transport for multiple species. Species that moved in-
shore or remained on the shelf were found deeper in
the water column than species that were exported from
the shelf. Cowen et al. (1993) indicated that as larvae
on the northeast U.S. shelf edge move deeper, they
become more susceptible to onshore flows. Similarly,
Cowen et al. (2000) argued that pomacentrid larvae
are distributed at mid-depths off Barbados, and these
mid-depth distributions resulted in larval retention
NOTE Hare and Govoni: Larval fish transport and vertical distributions on the southeast US continental shelf
733
closer to the island. Peterson (1998) proposed that in
upwelling systems, copepods can affect retention on the
shelf through ontogenetic vertical migrations, whereby
younger stages inhabit the upper offshore-flowing wa-
ter and older stages inhabit the lower onshore-flowing
water (see also Peterson et al., 1979). Similar models
were developed by Pillar et al. (1989) and Barange and
Pillar (1992) for euphausiids in the Benguela upwelling
zone. Additionally, Batchelder et al. (2002) indicated
that copepods can be retained nearshore in upwell-
ing systems through diel vertical migrations between
offshore-flowing surface waters and onshore-flowing
bottom waters. From these studies and the results from
the present study, a general hypothesis emerges that in
many marine systems, fish larvae and zooplankton can
affect onshore transport by moving deeper in the water
column. Thus, similar to selective tidal stream trans-
port whereby larvae use predictable tidal flows to either
remain in estuaries or enter estuaries (Forward and
Tankersley, 2001), general features in circulation may
exist across physical oceanographic systems that allow
larvae to influence their cross-shelf transport through
basic changes in their vertical distribution.
Acknowledgments
We thank the participants of the South Atlantic
Bight Recruitment Experiment for their constructive
comments throughout this study. We also appreciate
the contribution of those who assisted in the field and
the officers and crews of the NOAA Ships Oregon II
and Chapman. Dave Colby, Frank Hernandez, Patti
Marraro, Allyn Powell, Larry Settle, Petra Stegmann,
and six anonymous reviewers commented on earlier
drafts of this manuscript. This study was completed
while the senior author held a National Research
Council Research Associateship at the NOAA Beaufort
Laboratory.
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NOTE Hare and Govoni: Larval fish transport and vertical distributions on the southeast U S continental shelf
735
Appendix 1
Significant pairwise differences between the average larval vertical distributions of 10 species on the southeast United States
continental shelf. A total of 187 comparisons were made and the 69 significant differences are listed below. Significant differ-
ences between average depth distributions were determined by using a test of independence with the cell values as average
proportion of larvae at depth, averaged over a station occupation and weighted by the mean larval concentration at the station.
A Bonferroni correction was applied to significance tests within each station occupation. The direction of significant differences
(shallower [<], deeper [>], and different [<>]) was determined from the standardized residuals from the test of independence.
Year
Station
Species A
Species B
1986
Offshore
Brevoortia tyrannus
<
Peprilus triacanthus
1986
Offshore
Brevoortia tyrannus
<
Paralichthys spp.
1986
Offshore
Brevoortia tyrannus
<
Leiostomus xanthurus
1986
Offshore
Brevoortia tyrannus
<
Etropus spp.
1986
Offshore
Brevoortia tyrannus
<
Etrumeus teres
1986
Offshore
Bothus spp.
<
Peprilus triacanthus
1986
Offshore
Bothus spp.
<
Paralichthys spp.
1986
Offshore
Bothus spp.
<
Etrumeus teres
1986
Offshore
Peprilus triacanthus
>
Leiostomus xanthurus
1986
Offshore
Peprilus triacanthus
>
Micropogonias undulatus
1986
Offshore
Peprilus triacanthus
<>
Etropus spp.
1986
Offshore
Peprilus triacanthus
<>
Etrumeus teres
1986
Offshore
Paralichthys spp.
>
Leiostomus xanthurus
1986
Offshore
Paralichthys spp.
>
Micropogonias undulatus
1986
Offshore
Paralichthys spp.
<>
Etropus spp.
1986
Offshore
Paralichthys spp.
<>
Etrumeus teres
1986
Offshore
Leiostomus xanthurus
<
Etropus spp.
1986
Offshore
Leiostomus xanthurus
<
Etrumeus teres
1986
Inshore
Brevoortia tyrannus
<
Peprilus triacanthus
1986
Inshore
Brevoortia tyrannus
<
Paralichthys spp.
1986
Inshore
Brevoortia tyrannus
<
Leiostomus xanthurus
1986
Inshore
Brevoortia tyrannus
<
Micropogonias undulatus
1986
Inshore
Brevoortia tyrannus
<
Etrumeus teres
1986
Inshore
Peprilus triacanthus
>
Paralichthys spp.
1986
Inshore
Paralichthys spp.
<>
Etropus spp.
1989
Offshore
Bothus spp.
<
Etropus spp.
1989
Inshore
Brevoortia tyrannus
<
Leiostomus xanthurus
1989
Inshore
Brevoortia tyrannus
<
Etropus spp.
1989
Inshore
Brevoortia tyrannus
<
Etrumeus teres
1991
Offshore
Brevoortia tyrannus
<
Bothus spp.
1991
Offshore
Brevoortia tyrannus
<
Peprilus triacanthus
1991
Offshore
Brevoortia tyrannus
<
Paralichthys spp.
1991
Offshore
Brevoortia tyrannus
<
Leiostomus xanthurus
1991
Offshore
Brevoortia tyrannus
<
Micropogonias undulatus
1991
Offshore
Brevoortia tyrannus
<
Etropus spp.
1991
Offshore
Brevoortia tyrannus
<
Etrumeus teres
1991
Offshore
Bothus spp.
<
Leiostomus xanthurus
1991
Offshore
Bothus spp.
<
Micropogonias undulatus
1991
Offshore
Bothus spp.
<
Etropus spp.
1991
Offshore
Bothus spp.
<
Etrumeus teres
1991
Offshore
Peprilus triacanthus
<
Leiostomus xanthurus
1991
Offshore
Peprilus triacanthus
<
Micropogonias undulatus
1991
Offshore
Peprilus triacanthus
<
Etrumeus teres
continued
736
Fishery Bulletin 103(4)
Appendix 1 (continued)
Year
Station
Species A
Species B
1991
Offshore
Paralichthys spp.
<
Leiostomus xanthurus
1991
Offshore
Leiostom us xa n th u ru s
<>
Etropus spp.
1991
Offshore
Leiostomu s xa n th uru s
<>
Etrumeus teres
1991
Offshore
Etropus spp.
<>
Etrumeus teres
1991
Inshore
Brevoortia tyrannies
<
Bothus spp.
1991
Inshore
Brevoortia tyrannus
<
Paralichthys spp.
1991
Inshore
Brevoortia tyrannus
<
Leiostomus xanthurus
1991
Inshore
Brevoortia tyrannus
<
Micropogonias undulatus
1991
Inshore
Brevoortia tyrannus
<
Etropus spp.
1991
Inshore
Brevoortia tyrannus
<
Etrumeus teres
1991
Inshore
Bothus spp.
<
Peprilus triaeanthus
1991
Inshore
Bothus spp.
<
Paralichthys spp.
1991
Inshore
Bothus spp.
<
Leiostomus xanthurus
1991
Inshore
Bothus spp.
<
Micropogonias undulatus
1991
Inshore
Bothus spp.
<
Etropus spp.
1991
Inshore
Bothus spp.
<
Etrumeus teres
1991
Inshore
Peprilus triaeanthus
<>
Etropus spp.
1991
Inshore
Xyrichthys novacula
<
Micropogonias undulatus
1991
Inshore
Xyrichthys novacula
<
Etropus spp.
1991
Inshore
Paralichthys spp.
<
Micropogonias undulatus
1991
Inshore
Paralichthys spp.
<
Etropus spp.
1991
Inshore
Leiostomus xanthurus
<
Micropogonias undulatus
1991
Inshore
Leiostomus xanthurus
<
Etropus spp.
1991
Inshore
Micropogonias undulatus
>
Etropus spp.
1991
Inshore
Micropogonias undulatus
>
Etrumeus teres
1991
Inshore
Etropus spp.
>
Etrumeus teres
Acknowledgment of reviewers
The editorial staff of Fishery Bulletin would like to acknowledge the scientists
who reviewed articles published in 2004-2005. Their contributions have helped
ensure the publication of quality science.
737
Dr. David A. Ambrose
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738
Fishery Bulletin 103(4)
Fishery Bulletin Index
Volume 103(1-4), 2005
List ot titles
103(1)
1 An assessment of scup iStenotomus chrysops) and
black sea bass {Centropristis striata) discards in
the directed otter trawl fisheries in the Mid-Atlan-
tic Bight, by Eleanor A. Bochenek, Eric N. Powell,
Allison J. Bonner, and Sarah E. Banta
15 Fecundity of shortspine thornyhead iSebastolobus
alascamis) and longspine thornyhead (S. altivelis)
(Scorpaenidae) from the northeastern Pacific Ocean,
determined by stereological and gravimetric tech-
niques, by Daniel W. Cooper, Katherine E. Pearson,
and Donald R. Gunderson
23 Relative pleopod length as an indicator of size at
sexual maturity in slipper (Scyllarides squammosus )
and spiny Hawaiian (Panulirus marginatus) lob-
sters, by Edward E. DeMartini. Marti L. McCracken,
Robert B. Moffitt, and Jerry A. Wetherall
34 Seasonal changes in growth of coho salmon
(Oncorhynchus kisutch ) off Oregon and Washington
and concurrent changes in the spacing of scale cir-
culi, by Joseph P. Fisher and William G. Pearcy
52 Escapement of the Cape rock lobster (Jasus lalandii )
through the mesh and entrance of commercial traps,
by Johan C. Groeneveld, Jimmy P. Khanyile, and
David S. Schoeman
63 Quantification of drag and lift imposed by pop-up
satellite archival tags and estimation of the meta-
bolic cost to cownose rays (Rhinoptera bonasus), by
Donna S. Grusha and Mark R. Patterson
71 Effects of El Nino events on energy demand and egg
production of rockfish (Scorpaenidae: Sebastes): a
bioenergetics approach, by Chris J. Harvey
84 Application of pop-up satellite archival tag technol-
ogy to estimate postrelease survival of white marlin
{Tetrapturus albidus) caught on circle and straight
shank ("J") hooks in the western North Atlantic rec-
reational fishery, by Andrij Z. Horodysky and John
E. Graves
108 Cross-shelf and seasonal variation in larval fish
assemblages on the southeast United States con-
tinental shelf off the coast of Georgia, by Katrin E.
Marancik, Lisa M. Clough, and Jonathan A. Hare
130 Year-class formation in Pacific herring (Clupea pal-
lasi) estimated from spawning-date distributions
of juveniles in San Francisco Bay, California, by
Michael R. O'Farrell and Ralph J. Larson
142 Diet of oceanic loggerhead sea turtles (Caretta
caretta) in the central North Pacific, by Denise M.
Parker, William J. Cooke, and George H. Balazs
153 Indirect validation of the age-reading method for
Pacific cod (Gadus macrocephalus) using otoliths
from marked and recaptured fish, by Nancy E. Rob-
erson, Daniel K. Kimura, Donald R. Gunderson, and
Allen M. Shimada
161 Age and growth estimates of the thorny skate
{Amblyraja radiata) in the western Gulf of Maine,
by James A. Sulikowski, Jeff Rneebone, Scott Elzey,
Joe Jurek, Patrick D. Danley, W. Huntting Howell,
and Paul C. W Tsang
169 Age-validation, growth modeling, and mortality
estimates for striped trumpeter (Latris lineata ) from
southeastern Australia: making the most of patchy
data, by Sean R. Tracey and Jeremy M. Lyle
183 Larval development of estuary perch (Macquaria
colonorum ) and Australian bass (M. novemaculeata )
(Perciformes: Percichthyidae) and comments on
their life history, by Thomas Trnksi, Amanda C. Hay,
and D. Stewart Fielder
195 Early life history of the Argentine sandperch Pseu-
dopercis semifasciata (Pinguipedidae) off northern
Patagonia, by Leonardo A. Venerus, Laura Machi-
nandiarena. Martin D. Ehrlich, and Ana M. Parma
207 Geographic variation among age-0 walleye pollock
(Theragra chalcogramma): evidence of mesoscale
variation in nursery quality?, by Matthew T. Wilson,
Annette L. Brown, and Kathryn L. Mier
219 Tagging studies on the jumbo squid (Dosidicus gigas)
in the Gulf of California, Mexico, by Unai Markaida,
Joshua J. C. Rosenthal, and William F Gilly
103(2)
97 Age validation of quillback [Sebastes maliger)
using bomb radiocarbon, by Lisa A. Kerr, Allen H.
Andrews, Kristen Munk, Kenneth H. Coale, Brian R.
Frantz, Gregor M. Cailliet, and Thomas A. Brown
229 Sex change rules, stock dynamics, and the perfor-
mance of spawning-per-recruit measure in pro-
togynous stocks, by Suzanne H. Alonzo and Marc
Mangel
List of titles
739
246 Neonatal growth of Steller sea lion (Eumetopias
jubatus) pups in Alaska, by Elisif A. A. Brandon,
Donald G. Calkins, Thomas R. Loughlin, and Ran-
dall W. Davis
380 Maximum likelihood estimation of mortality and
growth with individual variability from multiple
length-frequency data, by You-Gan Wang and Nick
Ellis
258 Reproductive biology of carpenter seabream (Argy-
rozona argyrozona) (Pisces: Sparidae) in a marine
protected area, by Stephen L. Brouwer and Marc H.
Griffiths
270 Decline in sea otter (Enhydra lutris) populations
along the Alaska Peninsula, 1986-2001, by Douglas
M. Burn and Angela M. Doroff
280 Growth dynamics of the spinner shark (Carcharhi-
nus brevipinna I off the United States southeast and
Gulf of Mexico coasts: a comparison of methods, by
John K. Carlson and Ivy E. Baremore
292 Tracking Pacific bluefin tuna (Thunnus thynnus
orientalis) in the northeastern Pacific with an auto-
mated algorithm that estimates latitude by match-
ing sea-surface-temperature data from satellites
with temperature data from tags on fish, by Michael
L. Domeier, Dale Kiefer, Nicole Nasby-Lucas, Adam
Wagschal, and Frank O'Brien
307 Age, growth, mortality, and radiometric age vali-
dation of gray snapper (Lutjanus griseus) from
Louisiana, by Andrew J. Fischer, M. Scott Baker Jr.,
Charles A. Wilson, and David L. Nieland
320 Estimating exploitable stock biomass for the Maine
green sea urchin (Strongyloeentrotus droebachien-
sis) fishery using a spatial statistics approach, by
Robert C. Grabowski, Thomas Windholz, and Yong
Chen
331 Abundance and distribution of California sea lions
(Zalophus californianus) in central and northern
California during 1998 and summer 1999, by Mark
S. Lowry and Karin A. Forney
344 Variability in spawning frequency and reproductive
development of the narrow-barred Spanish mackerel
(Scomberomorus commerson) along the west coast
of Australia, by Michael C. Mackie, Paul D. Lewis,
Daniel J. Gaughan, and Stephen J. Newman
355 Seasonal marine growth of Bristol Bay sockeye
salmon (Oncorhyncus nerka) in relation to competi-
tion with Asian pink salmon (O. gorbuscha ) and the
1977 ocean regime shift, by Gregory T Ruggerone,
Ed Farley, Jennifer Nielsen, and Peter Hagen
392 Effects of fishing on growth traits: a simulation
analysis, by Erik H. Williams and Kyle W Shertzer
404 Preliminary evidence of increased spawning aggre-
gations of mutton snapper (Lutjanus analis) at
Riley's Hump two years after establishment of the
Tortugas South Ecological Reserve, by Michael L.
Burton, Kenneth J. Brennan, Roldan C. Munoz, and
Richard O. Parker Jr.
411 Feeding habits of European hake (Merluccius
merluccius) in the central Mediterranean Sea, by
Paolo Carpentieri, Francesco Colloca, Massimiliano
Cardinale, Andrea Belluscio, and Giandomenico D.
Ardizzone
417 Biology of queen snapper (Etelis oculatus: Lutjani-
dae) in the Caribbean, by Bertrand Gobert, Alain
Guillou, Peter Murray, Patrick Berthou, Maria D.
Oqueli Turcios, Ester Lopez, Pascal Lorance, Jerome
Huet, Nicolas Diaz, and Paul Gervain
426 Courtship and spawning behaviors of carangid spe-
cies in Belize, by Rachel T. Graham and Daniel W.
Castellanos
433 Comparison of two approaches for estimating natu-
ral mortality based on longevity, by David A. Hewitt
and John M. Hoenig
438 Effects of current speed and turbidity on stationary
light-trap catches of larval and juvenile fishes, by
David C. Lindquist and Richard F. Shaw
445 Can a change in the spawning pattern of Argentine
hake {Merluccius hubbsi) affect its recruitment?,
by Gustavo J. Macchi, Marcelo Pajaro, and Adrian
Madirolas
453 Feeding habits of the dwarf weakfish (Cynoscion
nannus) off the coasts of Jalisco and Colima, Mexico,
by Alma R. Raymundo-Huizar, Horacio Perez-Espana.
Maite Mascaro, and Xavier Chiappa-Carrara
461 Using bone measurements to estimate the original
sizes of bluefish (Pomatomus saltatrix) from digested
remains, by Anthony D. Wood
103(3)
371 Distribution, feeding condition, and growth of Japa-
nese Spanish mackerel (Scomberomorus niphonius)
larvae in the Seto Inland Sea, by Jun Shoji and
Masaru Tanaka
469 Using poststratification to improve abundance esti-
mates from multispecies surveys: a study of juve-
nile flatfishes, by Sherri C. Dressel and Brenda L.
Norcross
740
Fishery Bulletin 103(4)
489 Length at maturity in three pelagic sharks (Lamna
jiasus, Isurus oxyrinchus, and Prionace glauea ) from
New Zealand, by Malcolm P. Francis and Clinton
Duffy
601 Sexual differentiation and gonad development
in striped mullet (Mugil cephalus L. ) from South
Carolina estuaries, by Christopher J. McDonough,
William A. Roumillat, and Charles A. Wenner
501 Survey- and fishery-derived estimates of Pacific cod 620
(Gadus macrocephalus) biomass): implications for
strategies to reduce interactions between groundfish
fisheries and Steller sea lions (Eumetopias jubatus),
by Lowell W. Fritz and Eric S. Brown
516 Mitochondrial gene sequences useful for species
identification of western North Atlantic Ocean 635
sharks, by Thomas W. Greig, M. Katherine Moore,
Cheryl M. Woodley, and Joseph M. Quattro
524 Genetic variation of rougheye rockfish (Sebastes
aleutianus) and shortraker rockfish (S. borealis)
inferred from allozymes, by Sharon L. Hawkins,
Jonathan Heifetz, Christine M. Kondzela, John
E. Pohl, Richard L. Wilmot, Oleg N. Katugin, and
Vladimir N. Tuponogov
536 The reproductive cycle of the thorny skate (Ambly-
raja radiata ) in the western Gulf of Maine, by James
A. Sulikowski, Jeff Kneebone, Scott Elzey, Joe Jurek,
Patrick D. Danley, W. Huntting Howell, and Paul C.
W. Tsang
544 Effect of type of otolith and preparation technique on
age estimation of larval and juvenile spot (Leiosto-
mus xanthurus), by Dariusz P. Fey, Gretchen E. Bath
Martin, James A. Morris, and Jonathan A. Hare
553 Preliminary use of oxygen stable isotopes and the
1983 EI Nino to assess the accuracy of aging black
rockfish {Sebastes melanops), by Kevin R. Piner,
Melissa A. Haltuch, and John R. Wallace
103(4)
561 Patterns of growth, mortality, and size of the tropi-
cal damselfish Acanthochromis polyacanthus across
the continental shelf of the Great Barrier Reef, by
Michael J. Kingsford and Julian M. Hughes
574 Variation in the distribution of walleye pollock
(Theragra chalcogramma) with temperature and
implications for seasonal migration, by Stan Kot-
wicki, Troy W. Buckley, Taina Honkalehto, and Gary
Walters
588 Toward identification of larval sailfish (Istio-
phorus platypterus), white marlin (Tetrapturus
albidus), and blue marlin (Makaira nigricans) in
the western North Atlantic Ocean, by Stacy A.
Luthy, Robert K. Cowen, Joseph E. Serafy, and Jan
R. McDowell
Incidental catch and estimated discards of pelagic
sharks from the swordfish and tuna fisheries in the
Mediterranean Sea, by Persefoni Megalofonou, Con-
stantinos Yannopoulos, Dimitrios Damalas, Gregorio
De Metrio, Michel Deflorio, Jose M. de la Serna, and
David Macias
Reproductive biology of female Rikuzen sole (Dex-
istes rikuzenius ), by Yoji Narimatsu, Daiji Kitagawa,
Tsutomu Hattori, and Hirobumi Onodera
648 Temporal and spatial distribution and abundance of
flathead sole (Hippoglossoides elassodon ) eggs and
larvae in the western Gulf of Alaska, by Steven M.
Porter
659 Movements and spawning of white marlin (Tetraptu-
rus albidus) and blue marlin (Makaira nigricans) off
Punta Cana, Dominican Republic, by Eric D. Prince,
Robert K. Cowen, Eric S. Orbesen, Stacy A. Luthy, Joel
K, Llopiz, David E, Richardson, and Joseph E. Serafy
670 Life history characteristics for silvergray rockfish
(Sebastes brevispinis) in British Columbia waters
and the implications for stock assessment and
management, by Richard D. Stanley and Allen R.
Kronlund
685 Impact of the California sea lion (Zalophus califor-
nianus) on salmon fisheries in Monterey Bay, Cali-
fornia, by Michael J. Weise and James T. Harvey
697 Estimates of growth and comparisons of growth
rates determined from length- and age-based models
for populations of purple wrasse (Notolabrus fuci-
cola ). by Dirk C. Welsford and Jeremy M. Lyle
712 Effects of harvesting methods on sustainability of a
bay scallop fishery: dredging uproots seagrass and
displaces recruits, by Melanie J. Bishop, Charles H.
Peterson, Henry C. Summerson, and David Gaskill
720 Longline-caught blue shark (Prionace glauea): fac-
tors affecting the numbers available for live release,
by Guillermo A. Diaz and Joseph E. Serafy
725 Length correction for larval and early-juvenile
Atlantic menhaden (Brevoortia tyrannus) after pres-
ervation in alcohol, by Dariusz P. Fey and Jonathan
A. Hare
728 Comparison of average larval fish vertical distribu-
tions among species exhibiting different transport
pathways on the southeast United States continen-
tal shelf, by Jonathan A. Hare and John J. Govoni
741
Fishery Bulletin Index
Volume 103(1-4), 2005
List ot authors
Alonzo, Suzanne H. 229
Andrews, Allen H. 97
Ardizzone. Giandomenico D.
411
Baker Jr., M. Scott 307
Balazs, George H. 142
Banta, Sarah E. 1
Baremore, Ivy E. 280
Bath Martin, Gretchen E. 544
Belluscio, Andrea 411
Berthou, Patrick 417
Bishop, Melanie J. 712
Bochenek, Eleanor A. 1
Bonner. Allison J. 1
Brandon, Elisif A. A. 246
Brennan, Kenneth J. 404
Brouwer, Stephen L. 258
Brown, Annette L. 207
Brown, Eric S. 501
Brown, Thomas A. 97
Buckley, Troy W. 574
Burn, Douglas M. 270
Burton, Michael L. 404
Cailliet, Gregor M. 97
Calkins, Donald G. 246
Cardinale, Massimiliano 411
Carlson. John K. 280
Carpentieri, Paulo 411
Castellanos, Daniel W. 426
Chen.Yong 320
Chiappa-Carrara, Xavier 453
Clough, Lisa M. 108
Coale, Kenneth H. 97
Colloca, Francesco 411
Cooke, William J. 142
Cooper, Daniel W. 15
Cowen, Robert K. 588,659
Damalas, Dimitrios 620
Danley, Patrick D. 161. 536
Davis, Randall W. 246
De la Serna, Jose M. 620
De Metrio, Gregorio 620
Deflorio, Michel 620
DeMartini, Edward E. 23
Diaz, Guillermo A. 720
Diaz, Nicolas 417
Domeier, Michael L. 292
Doroff, Angela M. 270
Dressel, Sherri C. 469
Duffy, Clinton 489
Ehrlich, Martin D. 195
Ellis, Nick 380
Elzey, Scott 161, 536
Farley, Ed 355
Fey, Dariusz P. 544, 725
Fielder, D. Stewart 183
Fischer. Andrew J. 307
Fisher, Joseph P. 34
Forney, Karin A. 331
Francis, Malcolm P. 489
Frantz, Brian R. 97
Fritz. Lowell W. 501
Gaskill, David 712
Gaughan, Daniel J. 344
Gervain, Paul 417
Gilly, William F. 219
Gobert, Bertrand 417
Govoni, John J. 728
Grabowski, Robert C. 320
Graham, Rachel T 426
Graves, John E. 84
Grieg, Thomas W 516
Griffiths, Marc H. 258
Groeneveld, Johan C. 52
Grusha, Donna S. 63
Guillou, Alain 417
Gunderson, Donald R. 15, 153
Hagen, Peter 355
Haltuch, Melissa A. 553
Hare, Jonathan A. 108, 544, 725, 728
Harvey, Chris J. 71
Harvey, James T. 685
Hattori, Tsutomu 635
Hawkins, Sharon L. 524
Hay, Amanda C. 183
Heifetz, Jonathan 524
Hewitt, David A. 433
Hoenig, John M. 433
Honkalehto, Taina 574
Horodysky, Andrij Z. 84
Howell, W. Huntting 161, 536
Huet, Jerome 417
Hughes, Julian M. 561
Jurek, Joe 161,536
Katugin, Oleg N. 524
Kerr, Lisa A. 97
Khanyile, Jimmy P. 52
Kiefer, Dale 292
Kimura, Daniel K. 153
Kingsford, Michael J. 561
Kitagawa, Daiji 635
Kneebone, Jeff 161,536
Kondzela, Christine M. 524
Kotwicki, Stan 574
Kronlund, Allen R. 670
Larson, Ralph J. 130
Lewis, Paul D. 344
Lindquist, David C. 438
Llopiz, Joel K. 659
Lopez, Ester 417
Lorance, Pascal 417
Loughlin, Thomas R. 246
Lowry, Mark S. 331
Luthy, Stacy A. 588,659
Lyle, Jeremy M. 169, 697
Macchi, Gustavo J. 445
Machinandiarena, Laura 195
Macias, David 620
Mackie, Michael C. 344
Madirolas, Adrian 445
Mangel, Marc 229
Marancik, Katrin E. 108
Markaida, Unai 219
Mascaro, Maite 453
McCracken, Marti L. 23
McDonough, Christopher J. 601
McDowell, Jan R. 588
Megalofonou, Persefoni 620
Mier, Kathryn L. 207
Moffitt, Robert B. 23
Moore, M. Katherine 516
Morris, James A. 544
Munk, Kristen 97
Munoz, Roldan C. 404
Murray, Peter 417
Narimatsu, Yoji 635
Nasby-Lucas, Nicole 292
Newman, Stephen J. 344
Nieland, David L. 307
Nielsen, Jennifer 355
Norcross, Brenda L. 469
O'Brien, Frank 292
OTarrell, Michael R. 130
Onodera, Hirobumi 635
Oqueli Turcios, Maria D. 417
Orbesen, Eric S. 659
Pajaro, Marcelo 445
Parker, Denise M. 142
Parker Jr., Richard O. 404
Parma, Ana M. 195
Patterson, Mark R. 63
Pearcy, William G. 34
742
Fishery Bulletin 103(4)
Pearson. Katherine E. 15
Perez-Espana. Horacio 453
Peterson, Charles H. 712
Piner, Kevin R. 553
Pohl, JohnE. 524
Porter, Steven M. 648
Powell, Eric N. 1
Prince, Eric D. 659
Quattro, Joseph M. 516
Raymundo-Huizar, Alma R.
Richardson, David E. 659
Roberson, Nancy E. 153
Rosenthal. Joshua J. C. 219
Roumillat, William A. 601
Ruggerone, Gregory T. 355
453
Schoeman, David S. 52
Serafy. Joseph E. 588, 659. 720
Shaw, Richard F. 438
Shertzer, Kyle W. 392
Shimada, Allen M. 153
Shoji.Jun 371
Stanley, Richard D. 670
Sulikowski. James A. 161, 536
Summerson, Henry C. 712
Tanaka, Masaru 371
Tracey, Sean R. 169
Trnski, Thomas 183
Tsang, Paul C. W. 161, 536
Tuponogov, Vladimir N. 524
Venerus, Leonardo A. 195
Wagschal. Adam 292
Wallace, John R. 553
Walters. Gary 574
Wang,You-Gan 380
Weise, Michael J. 685
Welsford, Dirk C. 697
Wenner, Charles A. 601
Wetherall, Jerry A. 23
Williams Erik H. 392
Wilmot, Richard L. 524
Wilson. Charles A. 307
Wilson, Matthew T. 207
Windholz, Thomas 320
Wood, Anthony D. 461
Woodley, Cheryl M. 516
Yannopoulos, Constantinos 620
743
Fishery Bulletin Index
Volume 103(1-4), 2005
List ot subjects
Abundance
Argentine
hake 445
sandperch 195
California sea lion 331
flatheadsole 648
sockeye salmon 355
Acan thoch romis polyacan th us 561
Acoustic survey 445
Aerial survey 270, 331
Age
and growth
damselfish 561
gray snapper 307
shark, spinner 280
silvergray rockfish 670
striped trumpeter 169
thorny skate 161
at maturity 635
determination
Rikuzen sole 635
striped mullet 601
estimates
accuracy 544
precision 544
validation
damselfish 561
gray snapper 307
Pacific cod 153
rockfish
black 553
quillback 97
spot 544
striped trumpeter 169
Age-0 207
Aggregation 404
Alaska 97, 207, 247, 270, 355, 469,
501, 524, 553, 574, 648
Alaska Peninsula 270,648
Albacore 620
Aleutian Islands 246, 501, 524
Allozymes 524
Alopias vulpinus 620
Amblyraja radiata 161, 536
ANOVA' 685,712,725
Archival tag 292
Argentina 195
Argopecten irradians 712
Argyrozona argyrozona 258
Atlantic Ocean 516. 536, 659
southwest 445
northwest 161, 280, 553, 588, 720
western 404, 417
Australia 169, 183, 344, 561
Automated algorithm 292
Back-calculation 130. 153, 461
Bahamas 588
Band count, vertebral section 161
Bass
Australian 183
black sea 1
Batch fecundity 258
Batch spawner 15
Beaufort Inlet 725
Belize 426
Bering Sea 153, 501, 524, 574
Bioenergetics model 71
Biomass
Pacific cod 501
seagrass 712
sea urchin 320
walleye pollock 574
Bluefish 461
Body condition 635
Bogue Sound 712
Bone measurements 461
Bottom trawl
fishery 670
nets 574
Brevoortia tyrannus 725, 728
Bristol Bay 355
British Columbia 670
Bycatch mortality 574
Callinectes sapidus 433
California 130, 331, 553, 685
Canonical correspondence analysis
(CCA) 108
Canonical variates analysis
(CVA) 588
Cape rock lobster 52
Carangidae 426
Carapace base 52
Carcharhinus b?-evipinna 280
Caretta caretta 142
Carinaria cithara 142
Caribbean 420,516
Catch efficiency 438
Catch per unit of effort 438, 469,
501, 620, 670, 685
Central California Valley Index
(CVI) 685
Centropristis striata 1
Chesapeake Bay 720
ChiniakBay 469
Chi-square test 620
Chondrophore 142
Circulus spacing 34,
Cirripedia 142
Clupea pallasi 130
Cod, Pacific 153, 501
Codends 1
Colima coast 453
Commercial harvest 712
Commercial passenger fishing
vessel 685
Commercial traps 52
Commercial troll fishery 685
Conductivity-temperature-depth
probe 108
Copepod parasite 670
Coral reef 561
Courtship behavior 426
CPUE 438, 469, 501, 620, 670, 685
Crabs, blue 433
Croaker
Atlantic 728
Cross-shelf
transport 728
variation 108, 561
Current 438
Cynoscion nannus 453
Damselfish 561
Decapoda 142
Deep snapper resources 417
Demographic assessment 561
Depredation 685
Dexistes tikuzenius 635
Diet, loggerhead turtle 142
Discard 620
mortality 1,720
to-landings ratio 1
Displacement 659
Distribution
and abundance
Argentine sandperch 195
vertical larval 728
walleye pollock 574
DNA 516, 588
Dosidicus gigas 219
Drag and lift 63
Dredging 712
Egg
geographic distribution and
abundance 648
mortality 130
production 445
Elasmobranch 536
El Nino 71, 553
Southern Oscillation 685
Endangered Species Act 270
Energetic cost 63
Energy consumption 71
Enhydra lutris 270
744
Fishery Bulletin 103(4)
Escapement, from lobster trap 52
Essential fish habitat 659
Estuarine bivalve fisheries 712
Estuarine-dependent species 728
Etelis oculatus 417
Eumetopias jubatus 246, 501
External body metric 23
Fecundity
gravimetric estimates 15
Rikuzen sole 635
silvergray rockfish 670
stereological estimates 15
thornyhead 15
thorny skate 536
Feeding habits 411,453
First increment formation 544
Fisheries management 1, 229, 380,
392, 469, 501
Fishery biology 417
Fishery interaction 685
Fishing gear 620,712
Fishing mortality 720
Flatfishes 469
Flounder
gulf 728
southern 728
summer 728
Flow, vertically structured 728
G-statistic 728
Gadus macrocephalus 153, 501
Galeorh in us galeus 620
Gametogenesis 601
Gas platforms 438
Gastropoda 142
Gene sequences 516
Genetic identification 516,588
Genetic variation 524
Geographic
distribution 648
variation 207
Geolocation 292
Georgia 108
Gompertz model 280
Gonadal maturation 635
Gonad development 601
Gonadosomatic index 536, 635
Grand Banks 720
Gravimetric technique 15
Grapsidae 142
Gray's Reef National Marine
Sanctuary 108
Great Barrier Reef 561
Groundfish 469, 501
Growth 380,392
damselfish 561
dimorphism 670
effects of fishing on 392
Pacific herring 130
rate, daily 219
salmon 34
scale 355
seasonal variation 34
Steller sea lion 246
striped trumpeter 169
thorny skate 161
Gulf
of Alaska 246, 524, 648
of California 219
of Maine 161,536
of Mexico 280,438,516
Habitat
destruction 712
flatfish 469
Hake
Argentine 445
European 411
Halibut, Pacific 469
Harvesting, effects of 712
Hepatosomatic index 536
Herring, Pacific 130
Heteropoda 142
Hippoglossoides elassodon 469,
648
Hippoglossus stenolepis 469
Hook type mortality estimates 91
Horizontal transport 728
Hydrodia 142
Ichthyoplankton 108, 195, 371,
648
Identification 516, 588
Incidental catch 620
Increment formation 544
Indirect validation 153
Individual-based model 392
Individual variability 380
Interannual variability 469
Inverse distance-weighted 574
Isochronal spawning fish 610
Istiophoridae 588
Istiophorus platypterus 588
Isurus oxyrinchus 489, 620
Jalisco coast 453
Janthina spp. 142
Japan 373, 635
Jasus lalandii 52
Juvenile
Argentine sandperch 195
effects of turbidity on 438
flatfish 469
Pacific herring 130
salmon 34
scallops 712
spot 544
walleye pollock 207
Kamchatka coast 524
Kruskall-Wallis test 620
Kodiak Island 207,648
Lamna nasus 489
Larval fish
abundance 195. 648
age estimation 544
assemblages 108
Atlantic menhaden 725
billfish 588
cross-shelf variation 108
development 183, 195, 207
diet 207
distribution 371, 648
effects of turbidity 438
feeding conditions 371
flathead sole 648
geographic variation 207
growth 207,371
mortality 130
seasonal variation 108
survival 130
transport 728
Latris lineata 169
Leiostomus xanthurus 5 44, 728
Length at maturity 489
Length correction 720
Length frequency 380
Lepas spp. 142
Lepidopsetta spp. 469
Life history 183, 195, 229, 536, 670,
392
Light traps 438
Linear regression analysis 725
Linear regression model 433, 588
Lobster
Hawaiian spiny 23
slipper 23
South African Cape rock 52
Logistic 280
Longevity 433
Longline 720
Louisiana 307
Lowrie Island rookery 246
Lunar periodicity 426
Lutjanidae 420
Lutjanus
analis 404
griseus 307
Mackerel
Japanese Spanish 371
narrow-barred Spanish 344
Macquaria
colonorum 183
novemaeuleata 183
Makaira nigricans 588, 659
Maine 320
Marginal increment 161
List of subjects
745
Marlin
blue 588, 659
white 84, 588, 659
Marine mammal 331
Marine protected areas 258
Maturity
lobster 23
pelagic sharks 489
Rikuzen sole 635
silvergray rockfish 670
striped mullet 601
Maximum
age 433
likelihood 380
sustainable yield 659
Mediterranean Sea 411, 620
Menhaden, Atlantic 725, 728
Merluccius
hubbsi 445
merluccius 411
Mesh size 52
Mesoscale variation 207
Metabolic cost estimation 63
Mexico 219,453
Micropogonias undulatus 728
Mid-Atlantic Bight 1
Migration
jumbo squid 219
walleye pollock 574
Mitochondrial DNA 516
Models
Bayesian 524
bioenergetic 71
generalized additive model
(GAM) 670
general linear model (GLM) 670
growth 169,380,392,670
linear regression 433, 489
Leslie 501
Levenburg-Marquardt 601
mortality 380,433,489
Schnute growth model 670
von Bertalanffy 380,392
Monte Carlo simulation 588
Monterey Bay 685
Morphological-based maturity 23,
601
Morphometries 588
Mortality 380,433
blue shark 720
damselfish 561
gray snapper 307
hook type 84
natural, estimation of 422
release 720
sea turtle 142
striped trumpeter 169
Moss Landing 685
Movement
patterns 659
vertical 728
Mugil cephalus 601
Multivariate analysis
108
Natural mortality 433
Neonatal growth 246
Neustonic species 142
New Hampshire 536
New Zealand 489
Nonparametric analysis of variance
620
North Atlantic, western 84
North Carolina 712, 725
North Pacific, central 142
Notolab/'its fucicola 697
Nursery quality 207
Ocean regime shift 355
Oil platforms 438
Oncorhynchus
gorbuscha 355
kisutch 34
nerka 355
tshawytscha 685
Ontogenesis 411
Oocyte maturation 635
Oogenesis 601,635
Opportunistic feeders 142
Oregon 34
Original prey size 461
Otariidae 246
Otolith 97, 130, 153, 169, 307, 373,
544, 553, 561, 601, 635, 670
Otolith microchemistry 553
Ovarian atresia 601
Ovary 1, 23, 536
Oxygen isotope 55
Pacific Ocean
eastern 71, 453, 685
north 355,635
northeastern 15, 130, 292, 331,
648
Panulirus marginatus 23
Paralichthys
albiguta 728
dentatus 728
lethostigma 728
Parasites 524
Patagonia 195
Patagonian stock 445
Pelagic Observers Program,
U.S.Atlantic 720
Penaeus semisulcatus 380
Perch, estuary 183
Percichthyidae 183
Permit 426
Phenotypic plasticity 229
Phylogenetics 516
Pigmentation patterns 588
Pinguipedidae 195
Pinniped 331,685
Pleopod measurement 23
Pleuronectes asper 469
Pollock, walleye 207, 574
Pomacentridae 561
Pomotomus saltatrix 461
Population
decline 270
dynamics 229
Pop-up satellite archival tags 63, 84,
292, 659
Postrelease survival 84
Postspawning morphology 601
Poststratification 469
Potential energetic costs 63
Prawn, tiger 380
Preservation shrinkage 725
Prey size 461
Prionace glauca 489, 620, 720
Protogynous sex change 229
Pseudopercis semifasciata 195
Punta Cana 659
Pup, sea lion 246
Pyrosomas 142
Radiocarbon 97, 307
Rajidae 536
Ray, cownose 63
Recreational fishery 84
salmon 685
Recruitment
Argentine hake 445
gray snapper 307
silvergray rockfish 670
Reef fish 426,369
Reef promontory 426
Regression analysis 34, 142
Release mortality 720
Reproductive development 344, 601
Reproductive maturity 670
Reproduction
carpenter seabream 258
marlin 659
pelagic shark 489
Rikuzen sole 635
Spanish mackerel 344
thorny skate 536
striped mullet 601
Restriction fragment length
polymorphism analysis 588
Rhinoptera bonasus 63
Riley's Hump 404
Rockfish
age validation 97
black 553
bioenergetics model 71
quillback 97
rougheye 524
shortraker 524
silvergray 670
trophic ecology 71
yelloweye 97
746
Fishery Bulletin 103(4)
Rookeries 246
Russia 524
Sailfish 588
Salmon
Asian pink 355
coho 34
chinook 685
sockeye 355
Sandperch, Argentine 195
San Francisco Bay 130
Sarcotaces arcticus 670
Santa Cruz 685
Scale circuli 34, 355,
Scallops, bay 712
Scup 1
Sciaenidae 453
Scomberomorus
commerson 344
niphonius 371
Scombridae 371
Scorpaenidae 15, 71
Scyllarides squammosus 23
Sea bass, black 1
Seabream, carpenter 258
Seagrass 712
Sea lion
California 331,685
Steller 246, 501
SeaofHiuchi 373
Sea otter, northern 270
Sea-surface temperature 292
Seasonal growth 34, 179, 355
Seasonal migration 219
Seasonal variation 108
Sea turtles
loggerhead 142
Sea urchin, Maine green 320
Sebastes spp. 71
aleutianus 524
borealis 524
brevispinis 670
maliger 97
melanops 553
mystinus 74
ruberrimus 97
Sebastolobus
alascanus 15
altivelis 15
Selection differentials 392
Selectivity curves 52
Senescence 635
Semidemersal gadid 207
Sequence 516
Seto Inland Sea 371
Sexual differentiation 601
Sexual dimorphism 169, 635
Sharks 516
blue 489,620 574
coastal 280
common thresher 620
pelagic 489, 620
porbeagle 489
shortfin mako 489, 620
spinner 280
tope 620
Size at maturity 258, 601
Skate, thorny 161,536
Snapper
gray 307
mutton 404
queen 417
Sole
flathead 469
Rikuzen 635
rock 469
yellowfin 469
South Africa 52,258
South America 183
South Carolina 601
Southeast United States continental
shelf 108, 728
Sparidae 258
Spatial analysis 320
Spatial distribution 574, 648
Spatial variability 320
Spawning
aggregations 404, 426
behavior 426
date distribution 130
flathead sole 648
frequency 258, 344
habitat 659
marlin 659
mutton snapper 404
Pacific herring 130
pattern change 445
per-recruit 229
season 258
Spawning stock biomass per recruit
analysis 670
Species identification 516
Spermatogenesis 536
Spot 544,728
Squid, jumbo 219
Starch gel electrophoresis 524
Stenotomus chrysops 1
Stereological techniques 15
Stock
assessment 320, 433, 670
dynamics 229
management 670
Straits of Florida 588
Strip transect survey 270, 331
Strongylocen trotus droeboch iensis
320
Student-Newman-Keul test 685, 712
Submerged aquatic vegetation 712
Subtropical front 142
Survival rate 620
Swordfish 620
Tagging
jumbo squid 219
pop-up satellite 63, 84, 292, 659
Temperature 561, 574
Temporal distribution 648
Tetrapturus albidus 84, 588, 648
Theragra chalcogramma 207, 574
Thornyhead
shortspine 15
longspine 15
Thunnus
alalunga 620
thy turns 620
thynnus orientcdis 292
Tortugas South Ecological Reserve
404
Trachinotus falcatus 426
Trap selectivity 52
Trawl survey 445, 501, 574
echo integration 574
groundfish 469
Triangulated Irregular Networks 320
Trophic breadth variation 453
Trumpeter, striped 169
Tsitsikamma National Park 258
TukeyHSDtest 725
Tuna
bluefin 620
Pacific bluefin 292
Turbidity 438
U.S. Atlantic Pelagic Observers
Program 720
Variation
genetic 524
spawning frequency 344
Velella velella 142
Vertebral band analysis 161
Vertical distribution 728
von Bertalanffy 380
damselfish 561
gray snapper 307
Pacific cod 153
spinner shark 280
striped trumpeter 169
thorny skate 161
Washington 34, 524
Water column 728
Wax histology technique 601
Weakfish, dwarf 453
Wrasse, purple 697
Xiphias gladius 620
Year-class strength 130
Zalophus californianus 331, 685
Zoatera marina 712
Fishery Bulletin 103(4)
747
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Fishery Bulletin
Guidelines for authors
Content of manuscripts
Contributions published in Fishery Bulletin de-
scribe original research in marine fishery sci-
ence, fishery engineering and economics, as well
as the areas of marine environmental and ecolog-
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authors and not upon the editor or publisher.
Submission of an article implies that the article
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prior to submission. Articles may range from
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ods or results not supported by a large body of
data.
Manuscript preparation
Title page should include authors' full names
and mailing addresses and the senior author's
telephone, fax number and e-mail address, and
a list of key words to describe the contents of the
manuscript. Abstract should be limited to 150
words (one-half page), state the main scope of
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stracts are circulated by abstracting agencies,
it is important that they represent the research
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point Times New Roman font throughout. A brief
introduction should convey the broad significance
of the paper; the remainder of the paper should
be divided into the following sections: Materials
and methods. Results, Discussion (or Con-
clusions), and Acknowledgments. Headings
within each section must be short, reflect a logi-
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division I i.e., there can be no subdivision without
at least two items). The entire text should be
intelligible to interdisciplinary readers; there-
fore, all acronyms, abbreviations, and technical
terms should be written out in full the first time
they are used. Include FAO common names for
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different. FAO common names can be found at
http://www.fishbase.org/search.html. Follow the
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( 1984 ed. ) and the CBE Style Manual ( 6th ed. ) for
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American Fisheries Society's Common and Sci-
entific Names of Fishes from the United States
and Canada for fish nomenclature. Dates should
be written as follows: 11 November 2000. Mea-
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e.g., 58 metric tons (t); if other units of measure-
ment are used, please make this fact explicit to
the reader. Write out the numbers zero through
nine unless they form part of measurement units
(e.g., nine fish but 9 mm).
Text footnotes should be inserted in 9-point
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Footnote all personal communications, unpub-
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in the case of unpublished data, where the data
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or Working Papers, any "research" or "working"
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equipment or solutions used in the study, not in
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(e.g., SAS, vers. 6.03, SAS Inst., Inc., Cary. NC ).
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Jones, 1985). Abbreviations of serials should
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Authors are responsible for the accuracy and
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same first author, list the works alphabetically
according to the last name of following authors
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G. P., and T. P. Stuart, 1982 ). If the authorship is
identical, list works chronologically.
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reference to source is considered correct form
(e.g.. Source: Fish. Bull 97:105).
Reprints are available free of charge to the
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Submission
The Scientific Editorial Office encourages au-
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Or you may send your manuscript on compact
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clipped, not stapled — to the Scientific Editor,
at the address shown below. Send photocopies
only of figures with initial submission of manu-
script; do not send original figures. Original
figures and electronic copies of figures will be
requested later when the manuscript has been
accepted for publication.
Until August 2005
Dr. Norman Bartoo
Scientific Editor.
Fishery Bulletin
NOAA/NMFS/SWFSC
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Starting August 2005
Dr. Adam Moles
Scientific Editor,
Fishery Bulletin
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the text and tables should be submitted in Word
or Word Rich Text Format. Figures should be
sent as PDF files, Windows metafiles, or as EPS
files. Send a copy of figures in original software
if conversion yields a degraded version.
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