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U.S. Department
of Commerce

Volume 111
Number 1
January 2013

Fishery

Bulletin

U.S. Department
of Commerce

Rebecca M. Blank

Acting Secretary of Commerce

National Oceanic
and Atmospheric
Administration

Jane Lubchenco, Ph.D.
Under Secretary for Oceans
and Atmosphere

National Marine
Fisheries Service

Samuel D. Rauch III

Acting Assistant Administrator
for Fisheries

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The Fishery Bulletin carries original research reports and technical notes on investigations in
fishery science, engineering, and economics. It began as the Bulletin of the United States Fish
Commission in 1881; it became the Bulletin of the Bureau of Fisheries in 1904 and the Fishery
Bulletin of the Fish and Wildlife Service in 1941. Separates were issued as documents through
volume 46; the last document was No. 1103. Beginning with volume 47 in 1931 and continuing
through volume 62 in 1963, each separate appeared as a numbered bulletin. A new system
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bulletin. Beginning with volume 70, number 1, January 1972, the Fishery Bulletin became a
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for other scientific publications.

U.S. Department
of Commerce

Seattle, Washington

Volume 111
Number t
January 2013

Fishery

Bulletin

Contents

Articles

1 —12 Cowen, Robert K., Adam T. Greer, Cedric M. Guigand,

Jonathan A. Hare, David E. Richardson, and Harvey J. Walsh

Evaluation of the In Situ Ichthyoplankton Imaging System (ISIIS):
comparison with the traditional (bongo net) sampler

Companion articles

The National Marine Fisheries
Service (NMFS) does not approve,
recommend, or endorse any proprie-
tary product or proprietary material
mentioned in this publication. No
reference shall be made to NMFS,
or to this publication furnished by
NMFS, in any advertising or sales
promotion which would indicate or
imply that NMFS approves, rec-
ommends, or endorses any propri-
etary product or proprietary mate-
rial mentioned herein, or which has
as its purpose an intent to cause
directly or indirectly the advertised
product to be used or purchased be-
cause of this NMFS publication.

The NMFS Scientific Publications
Office is not responsible for the
contents of the articles or for the
standard of English used in them.

13-26 Bromaghin, Jeffrey F., Monique M. Lance,

Elizabeth W. Elliott, Steven J. Jeffries,

Alejandro Acevedo-Gutierrez, and John M. Kennish

New insights into the diets of harbor seals ( Phoca vituhna) in
the Salish Sea revealed by analysis of fatty acid signatures

27-41 Howard, Sarah M. S., Monique M. Lance,

Steven J. Jeffries, and Alejandro Acevedo-Gutierrez

Fish consumption by harbor seals ( Phoca vituhna ) in the
San Juan Islands, Washington

42-53 Rose, Craig S., Carwyn F. Hammond, Allan W. Stoner, J. Eric Munk,
and John R. Gauvin

Quantification and reduction of unobserved mortality rates for snow,
southern Tanner, and red king crabs ( Chionoecetes opilio, C. bairdi, and
Parahthodes camtschaticus) after encounters with trawls on the seafloor

54-67 Laidig, Thomas E., Lisa M. Krigsman, and Mary M. Yoklavich

Reactions of fishes to two underwater survey tools, a manned submersible
and a remotely operated vehicle

Fishery Bulletin 111(1)

68-77

Weber, Thomas C., Christopher Rooper, John Butler, Darin Jones, and Chris Wilson

Seabed classification for trawlability determined with a multibeam echo sounder on Snakehead Bank in the Gulf of
Alaska

78-89

Staaf, Danna J., Jessica V. Redfern, William F. Gilly, William Watson, and Lisa T. Ballance

Distribution of ommastrephid paralarvae in the eastern Tropical Pacific

90-106

Burchard, Katie A., Francis Juanes, Rodney A. Rountree, and William A. Roumillat

Staging ovaries of Haddock (Melanogrammus aeglefinus): implications for maturity indices and field sampling practices

107

Errata

108-109

Guidelines for authors

Evaluation of the In Situ Ichthyoplankton
Imaging System (ISIIS): comparison with
the traditional (bongo net) sampler

Email address for contact author rcowen@rsmas.miami edu

1 Rosenstiel School of Marine and Atmospheric Science
University of Miami
4600 Rickenbacker Causeway
Miami, Florida 33149

Abstract — Plankton and larval fish
sampling programs often are limited
by a balance between sampling fre-
quency (for precision) and costs. Ad-
vancements in sampling techniques
hold the potential to add consider-
able efficiency and, therefore, add
sampling frequency to improve preci-
sion. We compare a newly developed
plankton imaging system, In Situ
Ichthyoplankton Imaging System
(ISIIS), with a bongo sampler, which
is a traditional plankton sampling
gear developed in the 1960s. Com-
parative sampling was conducted
along 2 transects -30-40 km long.
Over 2 days, we completed 36 ISIIS
tow-yo undulations and 11 bongo
oblique tows, each from the surface
to within 10 m of the seafloor. Over-
all, the 2 gears detected comparable
numbers of larval fishes, represent-
ing similar taxonomic compositions,
although larvae captured with the
bongo were capable of being identi-
fied to lower taxonomic levels, espe-
cially larvae in the small (<5 mm),
preflexion stages. Size distributions
of the sampled larval fishes differed
considerably between these 2 sam-
pling methods, with the size range
and mean size of larval fishes larger
with ISIIS than with the bongo sam-
pler. The high frequency and fine
spatial scale of ISIIS allow it to add
considerable sampling precision (i.e.,
more vertical sections) to plankton
surveys. Improvements in the ISIIS
technology (including greater depth
of field and image resolution) should
also increase taxonomic resolution
and decrease processing time. When
coupled with appropriate net sam-
pling (for the purpose of collecting
and verifying the identification of
biological samples), the use of ISIIS
could improve overall survey design
and simultaneously provide detailed,
process-oriented information for fish-
eries scientists and oceanographers.

Manuscript submitted 8 December 2011.
Manuscript accepted 21 September 2012.
Fish. Bull. 111(1): 1—12 (2013).
doi:10.7755/FB. 11 1.1.1

The views and opinions expressed
or implied in this article are those of the
author (or authors) and do not necessar-
ily reflect the position of the National
Marine Fisheries Service, NOAA.

Robert K. Cowen (contact author)'
Adam T. Greer'

Cedric M. Guigand'

Jonathan A. Hare2
David E. Richardson2
Harvey J. Walsh2

2 Northeast Fisheries Science Center
National Marine Fisheries Service
Narragansett Laboratory
28 Tarzwell Drive
Narragansett, Rhode Island 02882

Regular surveys of early life stages
of fishes provide a wealth of informa-
tion for fisheries managers and fish-
ery oceanographers. Indices of larval
abundance are used quantitatively
as fishery-independent measures of
population abundance in stock as-
sessments (Scott et al., 1993; Gledhill
and Lyczkowski-Shultz, 2000; Sim-
monds, 2009). Larval fish abundance
also is used qualitatively, as evidence
for change in stock status (Smith
and Morse, 1993; Lo et al., 2010;
Richardson et al., 2010). Spawning
areas and times are inferred from
early-life-stage abundance and dis-
tribution, and they contribute to the
definition of essential fish habitat
(Brodziak, 2005; Levin and Stunz,
2005) and stock identification (Begg
et al., 1999; Hare, 2005). Larval
fish surveys combined with process-
oriented research also help forecast-
ing capability of year-class strength
(e.g., Megrey et al., 1996; Lough and
O’Brien, 2012).

Although larval fish studies make
substantial contributions to the as-
sessment of fish stocks, 3 factors
currently limit their applicability.

First, larval fishes are relatively rare
within the plankton and estimates
of variance in larval abundance can
be large, limiting the power of sta-
tistical comparisons of abundance
between years or locations (Cyr et
al., 1992). Second, larval fishes are
patchily distributed (e.g., Davis et
al., 1990; Cowen et al., 1993; Pe-
pin, 2004) but not randomly distrib-
uted; patches often are associated
with fronts, thermoclines, or specific
water masses (Cowen et al., 1993;
Kingsford and Suthers, 1994). Most
larval surveys, however, are conduct-
ed along fixed grids or as random
stratified designs; significant differ-
ences in larval abundance between
sampling times may simply reflect a
varying intersection of sampling with
dynamic larval habitat. Third, the
cost of ichthyoplankton surveys is
an important consideration and most
programs are cost-limited in terms of
ship time or the number of samples
that can be processed (Tanaka, 1973;
Lo et al., 2001; Simmonds, 2009).

In the United States, there are
numerous federally supported ich-
thyoplankton programs that provide

Fishery Bulletin 1 1 1 (1)

data for fisheries management. All these efforts are
limited by the 3 factors described above: rarity, patchi-
ness, and cost. The In Situ Ichthyoplankton Imaging
System (ISIIS; Cowen and Guigand, 2008) has the po-
tential to minimize all 3 limitations, and, if successful,
would provide the stock assessment toolbox with robust
and timely fishery-independent measures of spawning
distribution and stock size based on early-life-stage in-
formation. The overall goal of this study, therefore, was
to evaluate the effectiveness of ISIIS for quantifying
fish larvae and thus show the potential benefits of its
integration into larval surveys, with the ultimate goal
of improving stock assessments.

Specifically, we compare ISIIS with a traditional
bongo sampler, which is composed of a frame support-
ing paired nets with mouth openings on either side of
and in front of the towing wire (Posgay and Marak,
1980). The bongo has been used in ichthyoplankton
programs throughout the United States since its de-
velopment in the late 1960s: in the shelf ecosystem of
the northeastern United States since 1971 (Richardson
et al., 2010), in the Gulf of Mexico since 1982 (Lycz-
kowski-Shultz and Hanisko, 2007), and in the north-
east Pacific Ocean since 1972 (Matarese et al., 2003).
Here we present a comparison of larval fish abundance
and size distribution based on results from the ISIIS
and bongo sampler.

Methods

This study was conducted 54 km south of Woods Hole,
Massachusetts, (Fig. 1), on 23-24 October, 2008, on

the NOAA Ship Delaware II. The cruise immediately
followed the passage of a low-pressure system, which
brought strong winds to the study area; these winds
diminished throughout the duration of the cruise. Sam-
pling was completed along 2 parallel transects, which
were 41.4 and 27.7 km in length and separated by -6
km. To complete the comparison, the prototype ISIIS- 1
(herein referred to as ISIIS) was towed along a tran-
sect; then the ship returned to the beginning of the
transect, and net samples were made with the bongo
over the same transect. Sampling along each transect
encompassed both day and night periods, but no at-
tempt was made to compare day and night differences
in larval abundance or vertical distribution. Morse
(1989) compared daymight catches in the region and
found no significant differences for most of the taxa
captured in this study. He did find some daymight bias
at larger transect lengths, but, in our study, both the
bongo net and ISIIS sampled during day and night,
and therefore we assume this length bias was random-
ly distributed between the gears.

Sampling gear

The imaging output from ISIIS is unique in that it pro-
vides a continual image for the entire tow duration,
with a pixel resolution of -68 pm. Such fine resolu-
tion enables detection of particles as small as a 100 pm
(e.g., diatoms), although the ability to clearly resolve
particles is typically in the range of 700 pm (i.e., small
copepods and larvaceans) and larger sizes (e.g., larval
fishes, chaetognaths, and ctenophores). One distinctive
feature of ISIIS is its large depth of field (—30 cm for

Figure 1

Eight-day average (20-27 October 2008) sea-surface temperature (SST, °C) of northeastern U.S. continental shelf from
Cape Hatteras, North Carolina, to Nova Scotia, Canada. (A) The sampling location offshore of Martha’s Vineyard,
Massachusetts. (B) The inset shows the 2 In Situ Ichthyoplankton Imaging System (ISIIS) transects and the bongo
collection locations marked by black dots along the same transects. Note the change in SST scale between the 2 panels.

Cowen et at: Evaluation of the In Situ Ichthyoplankton Imaging System and comparison with the bongo-net sampler

mesozooplankton), which enables the concentration of
even relatively rare mesoplankters, such as larval fish-
es and gelatinous zooplankton, to be quantified (Cowen
and Guigand, 2008; McClatchie et ah, 2012). Using
the image analysis software that we have developed
(Tsechpenakis et al., 2007, 2008), we could essential-
ly quantify the plankton field for every centimeter of
our tow, and we could match these data centimeter by
centimeter with the corresponding environmental data
collected by the onboard sensors (pressure [depth],
temperature, salinity, and fluorometry). Consequently,
ISIIS can evaluate from very fine-scale (centimeters)
to submesoscale features. ISIIS sensors for this study
were those for temperature (SBE 31 Sea-Bird Electron-
ics, Inc., Bellevue, WA) and conductivity (SBE 4) and
a fluorometer (ECO FLRT, WET Labs, Philomath, OR).

A 61-cm bongo sampler was used and fitted with
505- and 333-pm mesh nets (Posgay and Marak, 1980).
A flowmeter (General Oceanics, Miami, FL) was at-
tached in the center of each mouth opening to quantify
the volume of water filtered by the net. A conductivity,
temperature, depth (CTD) instrument (SeaCAT SBE
19) was attached to the tow wire above the bongo net.
The CTD was used in real time to monitor the depth of
the bongo net during deployment.

Sampling approach

For this study, ISIIS was towed at a speed of 2.5 m s-1
in a tow-yo (vertically undulating) fashion between the
surface and a target depth of 10 m above the seafloor,
thereby following changes in seafloor depth. The ISIIS
was towed in an undulating manner by paying cable in
and out from the winch, and therefore continual winch
operation was required. (Since this study, a self-undu-
lating version of ISIIS has been designed and the need
for continual winch operation has been eliminated).
Each undulation (surface to depth to surface) took ~10
min, resulting in a distance covered of 1.5 km, which
also equates to the distance between downcasts (or up-
casts). While being towed, ISIIS records environmental
data (temperature, salinity, fluorescence) and imagery
continually, sending the data up the fiber-optic cable
for onboard recording. The continual imagery is parsed
into single images of 13x13 cm at a rate of 17.3 images
s-1. Thus, ISIIS generates -64,000 images h1, and for
this study, an estimated total of -478,000 images over
-7.68 h of total recording time.

Because the focus of this study was specifically lar-
val fishes, processing of images specifically targeted lar-
val fishes, thereby eliminating the need to capture and
classify all imaged particles (e.g., copepods, larvaceans,
medusae, and cfenophores). Consequently, all images
were manually reviewed for larval fishes. This process
is relatively rapid, although -3 months were required

1 Mention of trade names or commercial companies is for
identification purposes only and does not imply endorsement
by the National Marine Fisheries Service, NOAA.

to complete this task because of the large number of
images. Future development of ISIIS will include auto-
mated image processing; however, the current manual
processing requires viewing each image. When a lar-
val fish was present, that portion of the image was ex-
tracted and saved to a file. All fish images were then
reviewed for identification to the lowest taxonomic
level possible and measured with ImageJ (National
Institute of Health public domain Java-based image-
analysis program available at http://rsbweb.nih.gov/
ij/). Environmental data from ISIIS were interpolated
across each transect with a cubic interpolation function
in Matlab (vers. 7.11.0.584 [R2010b], The MathWorks,
Inc., Natick, MA). The depth and environmental vari-
ables associated with each fish larva were obtained by
matching time stamps from image and environmental
data.

The bongo tows were conducted in standard fashion
by following Jossi and Marak (1983). For each tow, the
wire was paid-out at a rate of 50 m min 1 to a depth of
10 m above the seafloor, then the wire was retrieved
to the surface obliquely at 20 m min-1, while the ship
moved at 0.75-1.0 m s-1. At completion of each tow,
the nets were washed down and the contents rinsed
onto a 333-pm sieve. The sample was preserved in 5%
buffered formalin. Samples were then sorted for larval
fishes under a dissecting microscope and identified to
the lowest taxonomic level following Fahay (2007). The
333-pm mesh bongo samples were used for compari-
sons of the bongo and ISIIS methods since this mesh
size is the one that has been used for more than 20
years by the Northeast Fisheries Science Center for
ichthyoplankton surveys.

To compare larval fish concentrations, each bongo
tow and each ISIIS undulation were treated as rep-
licates. There are potential statistical problems with
this assumption, but to date, the decorrelation length
scale in ichthyoplankton distributions in the study re-
gion has not been calculated. This assumption will be
examined in future studies with ISIIS. The larval fish
concentrations were transformed by the natural log,
and a Shapiro test was performed to test for normal-
ity of larval fish concentrations within each gear type.
Where the null hypothesis of normality was accepted,
a Welch’s f-test was used to compare larval fish con-
centrations between transects within gear and then
between gear across both transects. Comparisons were
made for total larvae, family-level larvae, and species-
level larvae both within and between gears for abun-
dance and size differences. In these tests, the nonpara-
metric Kruskal-Wallis test was used because concen-
trations at the family level were zero-inflated, making
transformations to a normal distribution impossible.
All counts per tow (or undulation) were standardized
to volume sampled (number of fish larvae per cubic
meter).

All larvae collected in the bongo net were measured
to the nearest 0.1 mm for notochord (preflexion) or
standard length under a dissecting microscope with

Fishery Bulletin 1 1 1 (1)

an ocular micrometer. Larvae observed in ISIIS im-
ages were measured digitally with Imaged software
after each image was calibrated to standard pixel size.
Fishes were measured for notochord or standard length
(the position of the posterior end of the hypural plate
was estimated if the pigmentation on a fish was too
dense for the internal caudal fin structure to be vis-
ible). A subset (6 out of 409) of the fish images was
discarded because orientation of the fish precluded ac-
curate measurement. Despite our effort to remove such
images from measurement, some fish sizes likely were
underestimated when the observer was not able to dis-
cern the offset that may have occurred where the orien-
tation was not exactly parallel to field of view. Lengths
of all larvae were compared between the 2 gears and
the 2 transects. To avoid pseudoreplication, the average
length of all larvae, family-level larvae, and species-
level larvae from a bongo tow or ISIIS undulation was

used for comparison. Size distributions were all highly
skewed, and therefore a Kruskal-Wallis test was used
to compare sizes within and between gear types. Statis-
tical analyses were performed in R software, vers. 2.14
(R Development Core Team, 2011) with the package
“plyr” (Wickham, 2011) as well as visualization tech-
niques with the package “ggplot2” (Wickham, 2009).

Results

Along 2 transects, we completed 24 and 12 ISIIS un-
dulations and 6 and 5 bongo tows, respectively. ISIIS
sampled an estimated 297 m3 h 1 (or an average of 63
m3 per tow-yo (i.e., down and up undulation), for a total
sampled volume of 2281 m3. The actual volume sam-
pled was lower than the maximum possible because
of a slight misalignment in the mirrors that occluded

1 b b

: 14.5

Transect 1

Transect 2

Latitude (°N)

Figure 2

Fluorescence (voltage), temperature (°C), and salinity (ppt) measured from ISIIS along the western (transect 1)
and eastern (transect 2) transects during 23—24 October 2008. Dotted lines in the fiuorometry panels represent the
undulations of the In the Situ Ichthyoplankton Imaging System (ISIIS). The vertical solid lines represent the ap-
proximate tow positions for the bongo sampler which was deployed along the length of the same transect once the
ISIIS tow was completed.

40.7

40.8

40 9

40.7

40.8

40.9

14.5

-101
-20:

-30
-40
-50:

40.7 40.8 40.9

i J33
|

|32.5

Cowen et al Evaluation of the In Situ Ichthyoplankton Imaging System and comparison with the bongo-net sampler

Figure 3

Example of a full-frame image collected with the In Situ Ichthyoplankton Imaging System (ISIIS). Larval fish (small [~4 mm],
Paralichthys dentatus ) and other plankters (especially copepods) are evident throughout. The small circular and elongate
particles are diatoms (centric and pinnate) and diatom chains, which can be detected but are too small to clearly resolve. Also
seen is a ~1.5-cm ctenophore with tentacles retracted. Several small aggregates (marine snow) are evident in the full-frame
image. Overall, the full frame provides a good indication of the plankton field encountered by the observed larval fish. Sur-
face is to the top of the image. Select plankters are shown to the right of the full frame in higher magnification (from top to
bottom): (A) chaetognath (note that an improved image has been substituted for demonstration purpose only), (B) preflexion
stage larval fish, (C) marine snow, (D) small copepod, (E) 2 copepods, (F) diatom chain (rotated to fit figure), and (G) copepod.

about 15% of the imaging field (i.e., the image field of
view was 11 cm versus 13 cm). In comparison, the typi-
cal bongo sampled 137 m3 per oblique tow, for a total
volume sampled of 1506 m3. The maximum depth of
tows was 49 m for ISIIS tows and 52 m for the bongo
tows.

The water column along both transects was defined
by limited vertical stratification, especially in its upper
35 m (Fig. 2). A slight decrease in chlorophyll concen-
tration below a depth of -35 m in the inshore portion
of the easterly transect was apparent and also was
observed with a change in temperature and salinity;
still, the differences were small. In contrast, consider-

able horizontal variation (south to north) was observed
in hydrography along both transects with tempera-
ture lower, salinity lower, and chlorophyll fluorescence
higher in the inshore (northern) portions than in the
offshore (southern) portions (Fig. 2).

The productivity of the water column was evident
in ISIIS imagery as a preponderance of diatoms vis-
ible throughout most images (Fig 3). Also imaged were
a variety of invertebrate plankters, ranging from co-
pepods and larvaceans to ctenophores and medusae
to invertebrate larval types, such as echinoderm plu-
teus. Because most imagery was dominated by the
smaller plankton (diatoms, copepods, and larvaceans;

Fishery Bulletin 1 1 1 (1)

5 mm

5 mm 5 mm

Figure 4

Examples of close-up, in situ images of different lar-
val fish taxa imaged with the In Situ Ichthyoplankton
Imaging System (ISIIS). (A) Paralichthys dentatus (4
mm); ( B) Gobiidae (8 mm); (C) Gadidae (32 mm); (D)
Clupeidae (21 mm); (E) Merluccius spp. (14 mm); (F)
unknown (preflexion stage) (3.2 mm).

see Fig. 3), and larval fishes were relatively rare, the
imagery provided a relative measure of abundance of
different plankters. In most cases when fish larvae
were encountered, the imagery was sufficient to dis-
cern characteristics valuable for identification at the
family or genus level (e.g., shape, number and location
of fins, overall body shape, fish size, and, in some cases,
certain skeletal features; see Fig. 4).

The 2 sampling methods allowed us to detect com-
parable quantities of larval fishes. ISIIS imaged a total
of 409 larvae, and the bongo tows collected a total of
359 larvae. When standardized for the volume of wa-
ter actually sampled, ISIIS estimated -0.18 fish larvae
(±0.015 standard error of the mean [SE] nr3), a value
that was not significantly different from the estimate
from the bongo tows (0.24 ±0.037 SE nr3; P=0.074).
Similarly, within gears, there were no differences in
larval fish concentrations between transects.

The estimates of larval abundance, however, were
made on the basis of the 2 gears sampling different

portions of the water column. The bongo net sampled
all depths equally as it was towed from depth to the
surface, but ISIIS spent less time at depths >40 m
than at depths near the surface (Fig. 5A). This sam-
pling effect is evident in the difference in measured
fish abundance by depth (Fig. 5B), where the apparent
pattern was for a continual increase in fish abundance
with depth from the surface down to 40 m and then
a decrease in abundance by depth beyond 40 m. This
decrease was directly coincident with the drop-off in
sampling time with depth by ISIIS. When an adjusted
abundance was estimated by computing depth-specific
concentrations (Fig. 50, then with the assumption
of equal sampling effort per depth as with the bongo
tows, an adjusted mean ISIIS fish concentration was
0.22 fish larvae rm3, which is very close to the bongo
estimate.

The taxonomic diversity collected by each gear also
was similar; both collected larval fishes representing
the same 7 families (Table 1), although bongo samples
were typically identifiable to lower levels (genus and
species) than those in ISIIS samples. Images of fish
larvae from ISIIS were identifiable to at least the ge-
nus level for -35% of larvae (143 out of 409). On the
other hand, larvae were unidentifiable in 60 fish im-
ages and most of these unidentifiable fishes were in the
early preflexion stages (-15%); in contrast, all bongo
tow larvae were identified at least to the family level.
Comparison of the relative proportions of taxa between
the 2 sampling methods indicates that they were simi-
lar. There were a few notable exceptions: ISIIS under-
estimated paralichthyids and scopthalmids and esti-
mated relatively greater proportions of phycids and
ophidiids than the bongo sampler. The total number
of larvae sampled was similar, but it is not known if
the “unknown” category would have evened these dis-
crepancies or added further differences among certain
taxa.

Size distributions of larvae differed considerably be-
tween the 2 sampling methods. ISIIS imaged a larger
size range and larger mean size of fish larvae than the
bongo sampler (Fig. 6, Table 2). This sampling gear
pattern was evident across several individual taxa, no-
tably the gadiform fishes, Phycidae and Gadidae, with
the latter mean size from ISIIS samples being more
than 3 times the mean size of this family from bongo
samples (Table 2). There was also a significant differ-
ence between gear types with respect to size of Para-
lichthyidae, although this very small difference (0.103
mm) may not be biologically meaningful and likely was
significant only because of the rank nature of the Krus-
kal-Wallis test. There was a significant difference in
overall larval size between transects for the ISIIS sam-
ples, but there was no significant difference in overall
larval size for the bongo tows between the 2 transects
or for any taxonomic group between transect within
gear type (Fig. 6, Table 2). Therefore, most of the dif-
ferences in size were attributed to sampling gear.

Cowen et al.: Evaluation of the In Situ Ichthyoplankton Imaging System and comparison with the bongo-net sampler

-10

£ -20

Q -30

-40

-50

Volume sampled (m3)

Number of larvae

Concentration (number rrr3)

Figure 5

Vertically discrete (by depth) larval fish (A) sampling
effort and (B) counts measured with the In Situ Ich-
thyoplankton Imaging System (ISIIS) in this study
conducted south of Woods Hole, Massachusetts, in Oc-
tober 2008. (C) Larval concentration was calculated
from data in A and B, and a linear regression was fit-
ted to the data (coefficient of determination |r2]=0.96).
The star denotes the mean water-column concentra-
tion value (0.22).

Discussion

Design of larval fish surveys requires a balance of ship
time, sample-processing time, and adequate sampling
effort for resolution of the spatial (and temporal) varia-
tion to provide a robust measure of spatial distribution
and abundance of this life-history stage. In essence,
survey design is a cost-benefit issue. Greater sampling
frequency will improve precision of estimates (e.g., Cyr
et al., 1992), but it does so at a cost of greater ship
time and laboratory sample processing. Consequently,
surveys are limited, in part, by the sampling tool of
choice (and its inherent limitations and benefits).

Results indicate that data collected with this proto-
type version of ISIIS are comparable to data collected
with a bongo sampler. Measurements of larval concen-
trations were similar, although identifications of larvae
fish were possible with ISIIS only at a coarser level of
taxonomic resolution compared to that with the bongo
sampler. In waters with relatively low species diversity
of ichthyoplankton, like the shelf of the northeastern
United States, the taxonomic resolution possible with
ISIIS is adequate for conducting an array of studies,
particularly when data are verified with net samples.
However, in species-rich waters, the taxonomic resolu-
tion possible with ISIIS may limit the applications of

Fishery Bulletin 1 1 1 (1)

Table I

(Upper): Comparison of taxonomic resolution between bongo and In Situ Ichthyoplankton Imaging System
(ISIIS) samples collected south of Woods Hole, Massachusetts, in October 2008 as part of this study. Data are
presented as “total,” which is the combined lowest level of identification across all taxa; “family,” which is a
comparison just at the family level (where all taxa are subsumed into relevant family taxa), and “species,”
where only identifications to species level are presented. (Lower): Summary comparison between the bongo
sampler and ISIIS gears for number and proportion of identifications at family, genus, and species levels, as
well as number and proportion of unknowns.

Identification level

Taxa

Total (lowest)

Family level

Species level

Bongo

ISIIS

Bongo

ISIIS

Bongo ISIIS

Clupeidae

Brevoortia tyrannus

1 0

Gadidae

Merlucciidae

Merluccius bilinearis

48 44

Phycidae

104

Urophycis spp.

48 21

Ophidiidae

Lepophidium profundorum

7 5

Gobiidae

Paralichthyidae

217

135

Citharichthys arctifrons

14 0

Etropus spp.

10 8

Paralichthys oblongus

4 0

Paralichthys dentatus

188

188 65

Scopthalmidae

Unknown

Total larvae

359

409

Numbers

Proportion

Bongo

ISIIS

Bongo

ISIIS

Family

206

0.11

0.50

Genus

0.16

0.07

Species

262

114

0.73

0.28

Unknown

0.00

0.15

Total

359

409

the technology. The version of ISIIS used in this study
was an early prototype (Cowen and Guigand, 2008);
considerable advancements have been made in the
image sharpness and depth of field since the field
work reported here, and these changes should improve
identification of individual fishes, especially of smaller
taxa.

Larval lengths were different for ISIIS and the bon-
go sampler. The bongo sampler collected smaller larvae,
indicating limitations with our ISIIS image-processing
procedures for recording larval fishes <5 mm (and obvi-
ous diagnostic morphological features on small larvae).
On the other hand, ISIIS imaged larger larvae, indicat-
ing that avoidance of the ISIIS by larger larvae was
reduced. With the potential of an increase in image

resolution to advance identification of smaller larvae
(e.g. the improved image of a chaetognath in Fig. 3,
upper right), the overall size range sampled by ISIIS
could be a significant improvement over the range of
the bongo sampler that has been used by the NEFSC
for the past 30-plus years. If there is an effort to merge
abundance time series between the bongo and ISIIS,
careful calibration studies would be required to account
for variances, including length-based, diel, and regional
differences in detectability. These types of calibration
studies also are necessary to combine data across dif-
ferent mesh sizes of the bongo sampler (see Johnson
and Morse, 1994; Richardson et ah, 2010).

Our results indicate that ISIIS could be a valuable
addition to the survey sampling toolbox because it sue-

Cowen et al.: Evaluation of the In Situ Ichthyoplankton Imaging System and comparison with the bongo-net sampler

20-

15-

• •

• i

c f)

o ■

i i ,

0 -

— j

Bongo 1

, - — 1 - I ~

Bongo 2 ISIIS 1 ISIIS 2

Sample gear

Clupeidae -

Phycidae -

-ID- •

Merlucciidae .

-on — •

Gadidae -

Ophidiidae .

-a-

Gobiidae -

Scopthalmidae -

-D- •

Paralichthyidae .

--D— -

Unknown .

Clupeidae .

— i n-

Phycidae .

HE —

Merlucciidae .

1 1 1

Gadidae .

i i(

Ophidiidae .

-m — •

Gobiidae .

- i- •

Scopthalmidae .

-H3—

Paralichthyidae .

— {D —

Unknown .

— 1 ! 1 1 1 —

0 5 10 15 20

Standard length (mm)

Figure 6

(A) Summary statistics (box plot) of larval size distribu-
tion by sampling gear and transect (1 and 2). The vertical
bars of the box plot represent the range, the box repre-
sents the 1st (lower) and 3rd (upper) quartile, and the cen-
tral (horizontal) line is the median of the distribution of
observations. Perceived outliers are denoted as separate
points beyond the range. Sampling was conducted with
the In Situ Ichthyoplankton Imaging System (ISIIS) and
a bongo sampler south of Woods Hole, Massachusetts, in
October 2008. (B) Taxon-specific comparison of fish lengths
between bongo sampler (top) and ISIIS (bottom). Note: the
box plots are rotated 90°relative to A; however, basic fea-
tures are the same as in A.

cessfully has estimated larval fish concentration, and,
in an environment of relatively low diversity, as in this
study, resolved the taxonomic composition of the larval
ichthyofauna. Under such conditions, the rapid sam-
pling speed of ISIIS could be used to increase spatial
and temporal resolution of ichthyoplankton patchiness,
without the need for additional ship days. For example,
rapid undulation of ISIIS resulted in 24 vertical forays
through the water column being repeated every 1.7 km
along the 41.4-km transect in just 4.6 h. In comparison,
6 bongo tows were completed along the same transect
in ~6 h for a spatial resolution of 6.9 km. Therefore,
ISIIS can provide 3-4 times the spatial resolution of
a bongo sampler over a comparable (or shorter) time
frame. Other benefits of ISIIS include its ability to re-
solve very fine-scale patchiness because its sampling
rate is both continuous and rapid. Consequently, de-
pending on how it is towed, ISIIS can be used to assess
detailed vertical distributional data, a feat that is not
possible with a bongo sampler, or even with opening
and closing net systems, without very extensive (and
expensive) sampling efforts. Further, simultaneous
sampling by other environmental sensors provides de-
tailed concurrent image and physical data. Information
about nearest-neighbor scaling and fish larval distri-
bution in relation to their predators and prey, as well
as environmental conditions, would be possible because
of the fine-scale, in situ information available in the
ISIIS imagery. Such sampling with ISIIS would allow
targeted, process-oriented studies, even while general
survey designs are being employed.

Still, the results of this study indicate several specif-
ic functional aspects that need to be considered or ad-
dressed for ISIIS to be a highly effective sampling tool
for survey and process-oriented studies. First, ISIIS
detected fewer smaller larvae than did the bongo sam-
pler. Further, the small larvae detected with ISIIS were
largely classified as unknown. These results indicate
that the image resolution of ISIIS should be improved
to increase the detectability and identification of small
larvae, although preflexion larvae will likely always be
problematic because of their limited morphological dis-
tinctiveness. An increase in detectability will require
an increase in the depth of field such that particles
that pass between the viewing ports are all in focus,
thereby eliminating regions of out-of-focus particles
that potentially can obscure the remaining image. The
current version of ISIIS (ISIIS-2) has been successful
at extending the depth of field from -30 cm to the full
50-cm space between viewing ports, adding to the vol-
ume sampled and the overall clarity of imagery (Cowen
and Guigand, unpubl. data).

The second issue is the need for rapid, accurate im-
age processing. The large number of images produced
makes computer-aided image analysis a requirement
for large-scale application of this instrument. We were
able to use manual assessment of the images taken in
the current study (by focusing only on fish larvae), but
further analysis of these data or more extensive surveys

Fishery Bulletin 1 1 1 (1)

Table 2

Kruskal-Wallis test for comparison of size difference (in mm) by transect and sampling gear for all fishes
combined, as well as for the 3 most dominant fish families, from this study where 2 gear types were used:
bongo sampler and the In Situ Ichthyoplankton Imaging System (ISIIS), to sample fish larvae south
of Woods Hole, Massachusetts, in October 2008. (Upper): comparison within gear between transects.
(Lower): comparison between gears. Asterisks (*) denote significant differences.

Bongo
Transect 1

Bongo
Transect 2

ISIIS

P Transect 1

ISIIS

Transect 2

Mean size — all larvae

3.514

4.397

0.275

7.223

4.959

0.001*

Paralichthyidae mean size

3.809

5.044

0.547

4.672

4.122

0.061

Phycidae mean size

2.335

2.980

0.221

4.617

4.295

0.199

Merlucciidae mean size

3.998

3.550

0.783

13.701

12.037

0.496

Bongo

ISIIS

Mean size — all larvae

3.858

6.468

1.67E-12*

Paralichthyidae mean size

4.385

4.488

0.0001*

Phycidae mean size

2.622

4.486

5.41E-05*

Merlucciidae mean size

3.795

13.398

3.806E-06*

with ISI IS will require automated computer analysis.
Several different options may be available for address-
ing some of these needs (e.g., Davis et ah, 2004; Hu
and Davis, 2005; Luo et ah, 2005;; Culverhouse et ah,
2006; Benfield et ah, 2007; Zhao et ah, 2010), although
these alternatives have not been tested with repeti-
tive processing of millions of images. Consequently, we
are currently developing and testing algorithms suit-
able for segmenting and classifying individual organ-
isms from full image files. These algorithms must be
capable of processing data at high speeds (or with
multiprocessor computers) and must be able to handle
large data sets (e.g., Tsechpenakis et ah, 2008). With
such analysis capabilities, the typical time between re-
search cruise and ultimate data analysis could be re-
duced greatly.

Conclusion

Although ISIIS can be a powerful tool for resolving fine
to mesoscale patchiness in both vertical and horizon-
tal distributions of plankton, it is limited by the fact
that it is a nondestructive sampler (i.e., it does not
collect specimens). ISIIS will not replace nets for all
studies. There is still a strong need for sample collec-
tion, whether for identification verification (for larvae
or eggs) or for more specific studies, such as projects
on food habits, growth, and genetics, that require speci-
mens. In addition, many nets, including bongo nets, can
be used by a greater variety of vessels and in a wider
range of weather conditions than the ISIIS instrument
package. When these different tools are combined, how-
ever, ISIIS could be used to establish the vertical and
spatial setting of fish larvae. This information could be

used to identify locations for targeted net samples. This
melding of samplers also would lead to more efficient
requirements for ship time and processing time (i.e.,
less time spent with nets and on processing the survey
samples from areas where the targeted specimens are
rare or absent). Therefore, ISIIS (and the technology it
represents) is a valuable addition to both process-ori-
ented studies and routine surveys. This technology can
contribute both to the understanding of the relation
between larval fishes and their biological and physi-
cal oceanographic habitat and to the quantification of
larval fish abundance and distribution for use in stock
and ecosystem assessments.

Acknowledgments

The authors wish to acknowledge the crew and cap-
tain of the NOAA Ship Delaware II for their support in
deploying our instrumentation. We also acknowledge K.
Hyde (NOAA Northeast Fisheries Science Center) for
providing the satellite data depicted in Figure 1. We
appreciate funding from several sources, especially the
National Marine Fisheries Service’s Advanced Sam-
pling Technology Working Group and the Geosciences
Directorate of the U.S. National Science Foundation.
This manuscript was improved by careful reading and
comments from D. Johnson (NOAA).

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Abstract — Harbor seals (Phoca
vitulina) are an abundant preda-
tor along the west coast of North
America, and there is considerable
interest in their diet composition,
especially in regard to predation on
valued fish stocks. Available infor-
mation on harbor seal diets, primar-
ily derived from scat analysis, sug-
gests that adult salmon ( Oncorhyn -
chus spp.), Pacific Herring (Clupea
pallasii ), and gadids predominate.
Because diet assessments based on
scat analysis may be biased, we in-
vestigated diet composition through
quantitative analysis of fatty acid
signatures. Blubber samples from
49 harbor seals captured in west-
ern North America from haul-outs
within the area of the San Juan Is-
lands and southern Strait of Georgia
in the Salish Sea were analyzed for
fatty acid composition, along with
269 fish and squid specimens rep-
resenting 27 potential prey classes.
Diet estimates varied spatially, de-
mographicaily, and among individual
harbor seals. Findings confirmed the
prevalence of previously identified
prey species in harbor seal diets, but
other species also contributed sig-
nificantly. In particular. Black ( Se -
bastes melanops) and Yellowtail (S.
flauidus) Rockfish were estimated to
compose up to 50% of some individu-
al seal diets. Specialization and high
predation rates on Black and Yellow-
tail Rockfish by a subset of harbor
seals may play a role in the popu-
lation dynamics of these regional
rockfish stocks that is greater than
previously realized.

Manuscript submitted 31 January 2012.
Manuscript accepted 31 October 2012.
Fish. Bull. 111:13-26 (2013).
doi:10.7755/FB.111.1.2

The views and opinions expressed
or implied in this article are those of the
author (or authors) and do not necessar-
ily reflect the position of the National
Marine Fisheries Service, NOAA.

New insights into the diets of harbor seals
(Phoca vitulina) in the Salish Sea revealed by
analysis of fatty acid signatures

Jeffrey F. Bromaghin (contact author)’

Monique M. Lance2

Elizabeth W. Elliott3

Steven J. Jeffries2

Alejandro Acevedo-Gutierrez4

John M. Kennish3

Email address for contact author: |bromaghin@usgs gov

U. S. Geological Survey
Alaska Science Center
4210 University Drive
Anchorage, Alaska 99508

Washington Department of Fish & Wildlife
Wildlife Research Division
7801 Phillips Road SW
Lakewood, Washington 98498

3 Department of Chemistry and Applied

Sciences, Engineering and
Technology (ASED Laboratory
University of Alaska Anchorage
3211 Providence Drive
Anchorage, Alaska 99508

4 Department of Biology
Western Washington University
516 High St MS 9160
Bellingham, Washington 98225-9160

The harbor seal (Phoca vitulina) is

the most abundant pinniped spe-
cies in the protected coastal waters
of Washington State and British
Columbia, Canada (Jeffries et ah,
2003). This species is a generalist
piscivorous predator, at or near the
apex of marine food webs. Such large
and mobile endothermic predators
require high caloric intake to support
growth, reproduction, and foraging
activity (e.g., Williams et ah, 2004).
Given their abundance and trophic
position, harbor seals undoubtedly
make up an influential component
of their marine ecosystems (Sergio
et ah, 2006; Heithaus et ah, 2008;
Schmitz et ah, 2010).

Numerous fish stocks of historic
commercial importance are depressed
or have declined significantly in the
Salish Sea of western North Amer-
ica, including Pacific Herring (Clu-
pea pallasii), Chinook Salmon ( On -
corhynchus tshawytscha) in Puget
Sound, Steelhead Trout ( O . mykiss),
Pacific Hake ( Merluccius productus ),
Walleye Pollock (Theragra chalco-
gramma), and many species of rock-
fish ( Sebastes spp.) (Federal Register,

2007). Under the Endangered Species
Act, the Puget Sound and Georgia
Basin distinct population segments
of Yelloweye (S. ruberrimus) and Ca-
nary (S. pinniger) Rockfish recently
were listed as threatened, and Bo-
caccio (S. paucispinis) was listed as
endangered (Federal Register, 2010).
Three additional rockfish species —
Brown Rockfish (S. auriculatus). Cop-
per Rockfish (S. caurinus), and Quill-
back Rockfish (S. maliger) — now are
considered federal species of concern,
and the remaining 7 species found in
the Salish Sea are listed as species
of concern by the State of Washing-
ton (M. Lance, personal commun.).
Continued declines in fish abundance
and the failure of depleted popula-
tions to recover have elevated con-
cerns among fishing crews, manag-
ers, and conservationists (Musick et
ah, 2001; Williams et ah, 2010).

The concurrence of abundant har-
bor seals and depressed fish popula-
tions has stimulated debate about
the degree to which harbor seals may
regulate prey abundance (Orr et ah,
2004). Numerous factors may have
contributed to the declines in fish

Fishery Bulletin 111(1)

abundance, although overexploitation has likely played
a prominent role (e.g., Levin et al., 2006). Predation
may have contributed to historic declines or may be
inhibiting recovery, because the abundance of Salish
Sea pinnipeds has been increasing and is thought to be
near carrying capacity (Jeffries et al., 2003). Although
pinnipeds have the potential to deplete local fish stocks
or hinder management actions that would promote
the recovery of depleted stocks (Harwood and Croxall,
1988; Bowen et al., 1993; Fu et al., 2001; Bjprge et al.,
2002; Boyd, 2002; MacKenzie et al., 2011), there is no
direct evidence to that effect in the Salish Sea. Conse-
quently, an improved understanding of the role of pin-
niped predation in regulation of prey abundance would
enhance our knowledge of marine ecosystem dynam-
ics and potentially inform the effective management of
fish stocks.

The diets of harbor seals in this region are thought
to be composed primarily of adult salmon (Oncorhyn-
chus spp.), Pacific herring, and gadids (Scheffer and
Slipp, 1944; Olesiuk, 1993; Tollit et al., 1997; Browne
et al., 2002; Wright et al., 2007; Thomas et al., 2011;
Lance et al., 2012). However, seals are considered op-
portunistic predators that target locally abundant prey
and switch between prey species in response to chang-
es in prey abundance — a type-III functional response
(Holling, 1959; Middlemas et al., 2006). Such predatory
behavior, in combination with local and seasonal diver-
sity in the availability of prey (Stasko et al., 1976; Will-
son and Womble, 2006; Therriault et al., 2009; Thomas
et al., 2011), implies harbor seal diet composition will
vary both spatially and temporally, and thus compli-
cate accurate diet assessment.

Prior investigations of harbor seal diets in the Pa-
cific Northwest have relied primarily on observational
studies, stomach content analyses, and especially scat
analyses (Scheffer and Slipp, 1944; Everitt et al., 1981;
Brown and Mate, 1983; Olesiuk, 1993; Zamon, 2001;
Orr et al., 2004; Wright et al., 2007; Thomas et al.,
2011; Lance et al., 2012). Such methods provide im-
portant insights into predatory behavior and document
the presence of particular prey species in predator di-
ets; however, several well-known factors can limit their
utility in quantitative investigations of diet (Phillips
and Harvey, 2009; Klare et al., 2011). For example, scat
analyses frequently are compromised by unequal prob-
abilities of detecting prey classes, as well as by dif-
ficulty in derivation of quantitative estimates of diet
composition from frequency-of-occurrence data. In ad-
dition, results pertain only to a short period of time,
ranging from the last predatory event in observational
studies to 1-2 days in scat-based investigations (Har-
vey, 1989; Cottrell and Trites, 2002; Tollit et al., 2004;
Trites and Joy, 2005; Hauser et al., 2008; Phillips and
Harvey, 2009).

Quantitative fatty acid signature analysis (QFASA;
Iverson et al., 2004) has important advantages over
other methods of diet assessment. Perhaps, most im-
portant, the method produces statistical estimates of

diet composition and measures of precision. The num-
ber of fatty acids that can be biosynthesized by animals
is limited (Ackman, 1989); therefore, the presence of
some compounds can be attributed to diet alone. This
fact, in combination with the large number of fatty
acid compounds present in adipose tissue, particular-
ly in marine ecosystems, enables QFASA to estimate
the contribution of a large number of prey classes to
diets, limited primarily by the diversity of fatty acids
among prey classes. In addition, although most meth-
ods of diet assessment provide information only on re-
cent consumption, sampling of adipose deposits may
provide insights into diets over a period of weeks to
months (Iverson et al., 2004; Budge et al., 2006). QFA-
SA requires the development of comprehensive data on
the fatty acid composition of potential prey, work that
may be costly or otherwise difficult. Although predators
must be captured and handled, only a small incision
is required for sampling and predators can be quickly
released. Overall, QFASA presents predators with lim-
ited negative consequences and can produce diet com-
position estimates that largely avoid potential biases
characteristic of other methods.

We used QFASA to investigate the diets of harbor
seals captured from haul-out sites among the San Juan
Islands of Washington State and the southern Gulf Is-
lands of British Columbia; both island groups are with-
in the Salish Sea. Blubber samples were collected from
captured harbor seals and representative specimens
of known or potential prey species also were collected.
Samples from both predators and potential prey were
analyzed to determine their fatty acid composition, and
diet compositions of sampled harbor seals were esti-
mated with QFASA mixture modeling. The resulting
estimates provide new insights into harbor seal preda-
tion on depressed fish populations and reveal dietary
heterogeneity on spatial, demographic, and individual
scales.

Materials and methods
Study area

The San Juan Islands and the southern Gulf Islands
lie in the transboundary waters of Washington State
and British Columbia between the Strait of Georgia,
Strait of Juan de Fuca, and Puget Sound (Fig. 1). This
area is characterized by hundreds of large and small
islands, rocky intertidal reefs, protected bays and estu-
aries, and rich marine life. Harbor seals use more than
150 haul-out locations in the study area, including
intertidal sandbars and numerous small islands and
rocky reefs distributed throughout the region. Harbor
seals are abundant throughout the Salish Sea (Jeffries
et al., 2003).

Bromaghm et al: Diets of Phoca vituhna in the Salish Sea revealed by analysis of fatty acid signatures

123°20'0"W 123°0'0"W 122°40'0"W 122°20’0"W

U~>

''T

•'tf-

CNJ

Map of the San Juan Island region, where samples were collected for our investigation of the diet
composition of harbor seals ( Phoca vitulina) in the Salish Sea. Harbor seals were captured in the
vicinity of Padilla Bay, Bird Rocks, Vendovi Island, and the Belle Chain Islets.

Sampling of predator and prey

Harbor seals were captured from April 2007 to March
2008 at 3 sites in the San Juan Islands of Washington
State and at a fourth site in the adjacent Gulf Islands
in British Columbia (Fig. 1). Padilla Bay (48°28.37 N,
122°30.88'W) is characterized by estuarine-mudflat
habitat, Vendovi Island (48°67.10'N, 122°61.10'W) con-
sists of rocky reef habitat located in close proximity to
Bellingham, Samish, and Padilla Bays, and Bird Rocks
(48°29.16'N, 122°45.61'W) comprises rocky reef habitat
in Rosario Strait. The fourth site was the Belle Chain
Islets, a rocky reef in the southeastern Gulf Islands of
British Columbia (48°49.67'N, 123°11.56'W) with habi-
tat similar to that of Bird Rocks.

Forty-nine blubber samples were collected from har-
bor seals according to standard techniques (Iverson
et al., 1997; Walton et al., 2000; Walton and Pomeroy,
2003) under Marine Mammal Protection Act Research
Permit 782-1702-00. Seals were captured in salmon
landing nets and physically restrained during process-
ing following the method of Jeffries et al. (1993). The
sampling location on the left side of the pelvic region
was shaved with a razor, rinsed with isopropyl alco-

hol, scrubbed with Betadine, and rinsed again with
isopropyl alcohol. A complete cross section of blubber
from skin to muscle was collected with a sterile, 6-mm
biopsy punch. A full cross-section sample provides the
most complete information regarding diet because pho-
cid blubber is not homogenous throughout its depth
and the inner layer responds most quickly to diet shifts
(Iverson et al., 1997). The biopsy site was then filled
with antiseptic cream and left open to drain. Each sam-
ple was placed immediately in chloroform with 0.01%
butylated hydroxytoluene to inhibit oxidation in glass
vials with Teflon lids, placed on ice while in the field,
and subsequently stored frozen at -80°C until analysis.
Seal samples were associated with these covariates:
sampling location, sex, and season (Table 1). Seasons
were defined as spring (March to May), fall (October to
November), and winter (December to February).

We sampled fish and cephalopod species known to
be consumed by harbor seals in the San Juan Islands
region on the basis of previous fecal analyses (Lance et
al., 2012). Some adult salmon samples were obtained
from seafood processors and staff of the NOAA North-
west Fisheries Science Center. Other prey were cap-
tured from throughout the study area between June

Fishery Bulletin 1 1 1 (1)

Table 1

Number of harbor seal samples, by location, sex, and season, used in our investigation of diet
composition of harbor seals ( Phoca uitulina) in the Salish Sea through quantitative fatty acid
signature analysis.

Location

Female

Male

Spring

Fall

Winter

Spring

Fall

Winter

Belle Chain

Bird Rocks

Padilla Bay

Vendovi Island

and December, 2008, with a variety of gear, including
hook and line, longline, and trawl. Samples were ob-
tained from 269 specimens representing these 20 spe-
cies: Black (Sebastes melanops), Yellowtail (S. flauidus),
Copper, and Puget Sound (S. emphaeus) Rockfish; Chi-
nook, Chum ( Oncorhynchus keta), Coho (O. kisutch),
Sockeye ( O . nerka ), and Pink (O. gorbuscha ) Salmon;
Pacific Herring, Walleye Pollock; Pacific Sand Lance
( Ammodytes hexapterus); Northern Anchovy ( Engrail -
lis mordax ); Shiner Perch ( Cymatogaster aggregata );
Plainfin Midshipman ( Porichthys notatus ); Spiny Dog-
fish ( Squalus acanthias ); Opalescent Inshore Squid
( Loligo opalescens)-, Kelp Greenling ( Hexagrammos
decagrammus ); Pacific Staghorn Sculpin ( Leptocottus
armatus ); and Starry Flounder ( Platichthys stellatus).
Specimens were identified with Hart (1973) for fish
species and Roper et al. (1984) for squid. Because some
species were represented by individuals with differenc-
es in size and total fat content (for example, immature
and mature species of salmon), 27 prey classes were
defined (Table 2).

Prey specimens were placed in airtight plastic bags
and stored at -80°C as soon as possible after collec-
tion. In the laboratory, each specimen was given a
unique sample number, partially thawed, weighed and
measured (standard, fork, and total lengths), and ho-
mogenized with a medium or large mechanical blend-
er, depending on fish size. The smallest prey animals
were homogenized with a mortar and pestle because
the blender was ineffective. Stomach contents were not
removed from prey specimens, to mimic ingestion by
predators (Budge et al., 2002). Approximately 5-10 g
of homogenate was placed in labeled scintillation vials
with Teflon lids and stored in a -80°C freezer. Samples
were express shipped in a cooler on dry ice to the Ap-
plied Sciences, Engineering, and Technology (ASET)
Laboratory at the University of Alaska Anchorage.

Fatty acid extraction and selection

All samples were processed at the ASET Laboratory
through the use of a method for microscale recovery

of total lipids with the Dionex ASE 2001 automated
solvent extraction system (Thermo Fisher Scientific,
Waltham, MA), which provides lipids for the determi-
nation of 80 unique fatty acids (Dodds et al., 2005). The
total body mass, percent fat composition, and fat mass
of prey specimens were obtained for 27 prey classes
(Table 2). Total mass data were not available for ma-
ture Chinook, Sockeye, and Pink Salmon obtained from
the Northwest Fisheries Science Center; therefore, an
approximate mean mass for these prey classes (e.g.,
Quinn, 2005) was used in calculation of fat mass. Given
the large range of mass among prey classes (Table 2),
the results were insensitive to our use of these approxi-
mate values.

Extracted lipids were dissolved in hexane to a con-
centration of 100 mg/mL, hydrolyzed by a base-cata-
lyzed reaction with potassium hydroxide, and then
esterified to form fatty acid methyl esters (FAMEs)
by reaction with boron trifluoride in methanol. Each
sample was spiked with a C21:0 internal standard (25
pg/mL) and separated on a Hewlett-Packard 5890 gas
chromatograph (GC) with a flame ionization detector
(FID) (Hewlett-Packard Co., Palo Alto, California) by
using a 60-m J&W DB-23 column (Agilent Technolo-
gies, Inc., Santa Clara, CA) with a 0.25-mm inside di-
ameter and 0.25-pm cyanopropyl polysiloxane film. Sig-
nal data were collected and analyzed with Agilent GC
Chemstation software.

Supelco 37-Component FAME Mix (catalog no.
47885-U; Sigma-Aldrich Co., St. Louis, MI) was used
as a continuing calibration verification (CCV) to verify
both the retention times and recovery values. This CCV
also contained 25 pg/mL of a C21:0 internal standard,
which is required to meet a tolerance of no greater
than ±20% of actual value. Analyte identity was veri-
fied further by mass spectrometry through the use
of a Varian CP3800 GC (Agilent Technologies, Inc.)
and a Varian Saturn 2200 ion trap mass spectrometer

1 Mention of trade names or commercial companies is for
identification purposes only and does not imply endorsement
by the U.S. Government.

Bromaghin et al: Diets of Phoca vitulma in the Salish Sea revealed by analysis of fatty acid signatures

Table 2

The number of prey animals from which fatty acid signature data were obtained (n) and the prey class (class) into which
each prey type was assigned after evaluation of discriminant analysis and mean fat mass in our investigation of the diet
composition of harbor seals ( Phoca vitulina ) in the Salish Sea through quantitative fatty acid signature analysis. Prey
classes are defined as B&YR (Black [ Sebastes melanops] and Yellowtail [S. flavidus 1 Rockfish), CR (Copper Rockfish [S.
caurinus}), PSR (Puget Sound Rockfish IS. emphaeus ]), Chin (mature Chinook Salmon \Oncorhynchus tshawytscha ]), Chum
(mature Chum Salmon |0. keta\), Coho (mature Coho Salmon [O. kisutch]), Sock (mature Sockeye salmon [O. nerka ]), Pink
(mature pink salmon \0. gorbuscha}), Sal-M (medium-sized Chinook and Coho Salmon), Sal-S (small Chinook, Chum, Sock-
eye, and Pink Salmon), Pol (Walleye Pollock [ Theragra chalcogramma ]), Her (Pacific Herring [ Clupea pallasii } at least 2
years old), YH&SL (Pacific Herring less than 2 years old and Pacific Sand Lance [ Ammodytes hexapterus ]), NA (Northern
Anchovy [ Engraulis mordax]), SP (Shiner Perch I Cymatogaster aggregata ]), PM (Plainfin Midshipman [Porichthys notatus 1),
SD (Spiny Dogfish [Squalus acanthias ]), OIS (Opalescent Inshore Squid [Loligo opalescens]), G&S&F (Kelp Greenling [ Hexa -
grammos decagrammus ], Pacific Staghorn Sculpin [ Leptocottus armatus], and Starry Flounder [ Platichthys stellatus 1). For
each prey type, the sample size in), mean (mean), and standard deviation (SD) of total mass, percent fat composition, and
total fat mass are shown. Mass data were not available for mature Chinook, Sockeye, or Pink Salmon, and an approximate
mean mass was used for the computation of fat mass.

Mass (g) Percent fat Fat mass (g)

Prey type

Class

Mean

Black Rockfish

B&YR

293.8

48.3

6.5%

0.4%

19.3

4.0

Yellowtail Rockfish

B&YR

152.8

28.2

5.7%

1.5%

8.8

2.6

Copper Rockfish

201.3

195.7

2.4%

0.4%

4.7

4.5

Puget Sound Rockfish

PSR

53.9

8.9

2.2%

0.3%

1.1

0.4

Chinook, mature

Chin

10000.0

12.2%

2.3%

1218.8

233.3

Chum, mature

Chum

4955.9

784.6

15.1%

7.8%

789.7

455.6

Coho, mature

Coho

3765.4

660.8

5.5%

2.8%

208.2

125.0

Sockeye, mature

Sock

2500.0

12.4%

1.8%

309.4

45.4

Pink, mature

Pink

2000.0

5.3%

2.1%

105.6

43.0

Chinook, medium

Sal-M

133.5

70.3

3.0%

1.3%

4.8

3.1

Coho, medium

Sal-M

193.0

28.6

2.9%

0.5%

5.7

1.7

Chinook, small

Sal-S

20.9

8.0

1.3%

0.3%

0.3

0.2

Chum, small

Sal-S

62.8

24.6

2.3%

1.1%

1.6

1.5

Sockeye, small

Sal-S

15.5

2.5

1.5%

0.2%

0.2

0.1

Pink, small

Sal-S

47.2

13.6

2.4%

0.8%

1.2

0.7

Pollock

Pol

29.4

78.6

1.8%

0.4%

0.5

1.2

Pacific Herring >2 yr

Her

37.5

4.2

11.7%

3.4%

4.4

1.6

Pacific Herring <2 yr

YH&SL

5.8

0.8

3.5%

1.3%

0.2

0.1

Pacific Sand Lance

YH&SL

1.9

0.3

3.3%

0.8%

0.1

0.0

Northern Anchovy

18.8

1.7

12.2%

3.4%

2.3

0.7

Shiner Perch

21.0

5.8

6.9%

2.4%

1.5

1.0

Plainfin Midshipman

61.7

13.4

3.4%

0.7%

2.1

0.6

Spiny Dogfish

1712.5

383.8

9.0%

3.6%

160.5

83.5

Opalescent Inshore Squid

OIS

7.1

1.9

3.0%

0.4%

0.2

0.1

Kelp Greenling

G&S&F

179.7

396.3

1.5%

0.4%

3.0

6.8

Pacific Staghorn Sculpin

G&S&F

21.0

10.1

1.5%

0.6%

3.4

5.7

Starry Flounder

G&S&F

220.2

410.1

1.5%

0.6%

3.4

5.7

with a scan range of 50-400 mass-to-charge ratios
(m/z). Additionally, a National Institute of Standards
and Technology 1946 international standard was used
to externally verify the method and the quality of
recoveries.

The ASET Laboratory implements several protocols
to improve data quality that are not routinely imple-
mented in analyses of fatty acid data. Rather than
normalize the peak data of each sample to C18:0, the
laboratory adds an internal standard to all samples,
method blanks, and CCVs. This protocol is beneficial

because it provides a data point of known quantity to
each resulting set, including blanks, allowing the sig-
nificance of low-recovery peak data to be verified. In ad-
dition, because normalization to a recovered compound
incorrectly entails the assumption that all compounds
respond equally in the FID, use of an internal stan-
dard avoids errors that might otherwise result from
that assumption (Dodds et al., 2005). The laboratory
also verifies the identity of each peak by using a GC
mass spectrometer (GC-MS) — verification that is nec-
essary to eliminate misclassification of non-fatty acid

Fishery Bulletin 1 11 (1)

byproducts from the derivatization process. Finally, the
laboratory performs periodic standard calibrations of
the spectrometer at varying levels of concentration to
determine the limit-of-detection for each compound.

Several criteria were used to evaluate the suitability
of each fatty acid compound for inclusion in mixture
modeling. At a minimum, each compound had to pass
GC-MS verification, have a minimal variance for the
majority of samples collected (<20% relative standard
deviation), and average at least 1% of the total fatty
acid contained in each sample. The compounds needed
to be predominately from a dietary source, as delin-
eated in Iverson et al. (2004). Compounds 18:2n-6 and
18:3n-3 were automatically included as neither com-
pound is biosynthesized by seals. These selection crite-
ria led to a suite of 22 fatty acid compounds to be used
in mixture modeling: C16:2n-6, Cl6:2n-4, C16:4n-1,
C18:ln-9, C18:ln-7, C18:2n-6, C18:3n-6, C18:3n-4,
Cl8:3n-3, C18:4n-3, C20:ln-ll, C20:ln-9, C2Q:ln-7,
C20:2n-6, C20:3n-6, C2Q:4n-6, C20:3n-3, C20:4n-3,
C20:5n-3, C22:6n-3, C21:5n-3, and C22:5n-6. Data are
available at the Biological and Chemical Oceanography
Data Management Office of the National Science Foun-
dation (http://osprey.bcodmo.org/project.cfm?flag=viewr
&id=224&sortby=project).

Estimating diet composition

Obtaining unique estimates of diet composition with
mixture models requires the number of prey classes
to be no greater than the number of fatty acids (e.g.,
Phillips, 2001). Furthermore, combining prey classes
reduces the dimensionality of the parameter space and
can increase estimation precision. Linear discriminant
functions were used to identify prey classes with po-
tential to be merged, with R software, vers. 2.10.1 (R
Development Core Team, 2009) and function Ida of
package MASS (Venables and Ripley, 2002). The ac-
curacy of classifying individual prey into correct prey
classes was estimated with discriminant functions and
cross validation. Data from each prey specimen were
removed temporarily, discriminant functions were es-
timated from the remaining data, and the estimated
functions were used to classify the excluded specimen
to a prey class. Prey classes with the largest misclas-
sification rates were candidates to be merged, provided
that the mean adipose masses of the 2 classes were
similar.

Methods of QFASA mixture modeling closely fol-
lowed those of Iverson et al. (2004) and Beck et al.
(2007), methods that have been applied to the re-
search of numerous marine species, including harbor
seals (Nordstrom et al., 2008), gray seals ( Halichoerus
grypus ; Iverson et al., 2004; Beck et ah, 2007; Tucker
et ah, 2008; Lundstrom et ah, 2010), harp seals (Pag-
ophilus groenlandicus; Iverson et ah, 2004), northern
fur seals (Callorhinus ursinus; Hofmeyr et ah, 2010),
Steller sea lions ( Eumetopias jubatus; Hoberecht,
2006), polar bears ( Ursus maritimus; Thiemann et ah,

2008) , and various species of seabirds (Williams et al.,

2009) . A mixture model based on the Kulibaek-Liebler
(KL) distance measure (Iverson et ah, 2004) was used
to estimate the diet composition of each seal. The cali-
bration coefficients for harbor seals reported by Nord-
strom et al. (2008) were used to convert prey fatty acid
signatures (FAS) to the scale of predator FAS, and the
distance measure was evaluated on the predator scale;
note that Iverson et al. (2004) converted predator FAS
to the prey scale. Estimation variance for each seal was
estimated with 1000 bootstrap replications of the prey
FAS data. The resulting estimates of diet composition
(fat unadjusted, the pk of Iverson et ah, 2004), also
were transformed to account for adipose mass per prey,
expressing diet composition in terms of the number of
animals consumed (fat adjusted, the ab of Iverson et
ah, 2004).

Multivariate analysis of variance (function manova
in R; R Development Core Team, 2009) was used to
explore diet composition estimates for structure as-
sociated with the following covariates: sampling loca-
tion, season (spring, fall, winter), and sex. The initial
model contained these 3 main effects and all 2-way in-
teractions, and nonsignificant terms were sequentially
eliminated from the model. A significance level (a) of
0.01 was used for all tests. The mean diet composition
for a class of predators (e.g., males or females) was
computed as the sample average of their individual
diet composition estimates. The variance of mean diet
composition was assessed with the estimator of Beck
et ah (2007). Mixture proportions and variances were
estimated with a custom computer program written in
Fortran (Metcalf et ah, 2004) and compiled with the In-
tel Visual Fortran Compiler Professional Edition, vers.
11.1 (Intel Corp., Santa Clara, CA).

Results

Estimating diet composition

Given the suite of 22 fatty acid compounds used to
form FAS, the 27 original prey classes needed to be
reduced to no more than 22 prey classes for mixture
model estimates to be unique (Phillips, 2001). Among
the 27 original prey types, Black and Yellowtail Rock-
fish; medium-size Chinook and Coho Salmon; small
Chinook, Chum, Sockeye, and Pink Salmon; young Pa-
cific Herring aged 0 to 1 and Pacific Sand Lance; and
Kelp Greenling, Pacific Staghorn Sculpin, and Starry
Flounder were combined to reduce discriminant analy-
sis misclassification among prey classes (Table 2). The
resulting prey data set contained 19 prey classes, for
which 251 of 269 prey animals (93.3%) were assigned
to the correct prey class.

The mean diet composition of all 49 seals, both ad-
justed and unadjusted for differential fat mass among
prey, was estimated with FAS for 22 fatty acid com-
pounds and data for 19 prey classes. The species esti-

Bromaghin et al: Diets of Phoca vitulma in the Salish Sea revealed by analysis of fatty acid signatures

Figure 2

Mean diet composition estimates: (A) adjusted and (B) unadjusted for differential fat
mass among prey classes, for all harbor seals (Phoca vitulina) combined in our inves-
tigation of the diet composition of harbor seals in the Salish Sea. Error bars are ±1
standard error of the estimate. Prey classes are defined as B&YR (Black [ Sebastes
melanops ) and Yellowtail [S. flavidus ] Rockfish), CR (Copper Rockfish [S. caurinus]),
PSR (Puget Sound Rockfish [S. emphaeus 1), Chin (mature Chinook Salmon \Oncorhyn-
chus tshawytscha]), Chum (mature Chum Salmon 10. keta}), Coho (mature Coho Salmon
(O. kisutch ]), Sock (mature Sockeye Salmon [O. nerka J), Pink (mature Pink Salmon
10. gorbuscha]), Sal-M (medium-size Chinook and Coho Salmon), Sal-S (small Chinook,
Chum, Sockeye, and Pink Salmon), Pol (Walleye Pollock [ Theragra chalcogramma 1), Her
(Pacific Herring [ Clupea pallasii 1 at least 2 years old), YH&SL (Pacific Herring less
than 2 years old and Pacific Sand Lance [ AmmocLytes hexapterus]), NA (Northern An-
chovy [Engraulis mordax ]), SP (Shiner Perch [ Cymatogaster aggregata]), PM (Plainfin
Midshipman | Porichthys notatus ]), SD (Spiny Dogfish [Squalus acanthias]), OIS (Opal-
escent Inshore Squid [ Loligo opalescens]), G&S&F (Kelp Greenling [ Hexagrammos
decagrammus] , Pacific Staghorn Sculpin [Leptocottus armatus 1, and Starry Flounder
[Platichthys stellatus]).

Fishery Bulletin 1 1 1 (1)

mated to contribute most to harbor seal diets included
Black and Yellowtail Rockfish, Chinook Salmon, adult
Pacific Herring, and Shiner Perch (Fig. 2). Large differ-
ences in fat mass among prey classes led to substantial
differences in the 2 estimates. Most
noticeably, the high fat content of
mature salmon species (Table 2)
reduced the contribution of adult
Chinook Salmon in the estimates
adjusted for fat mass, suggesting
that few individual Chinook Salm-
on need to be consumed for them
to contribute significantly to the fat
composition of harbor seals.

Multivariate analysis of variance
results revealed substantial hetero-
geneity among estimated diets of
individual seals by sampling loca-
tion (PcO.OOl) and sex (P<0.001),
although the interaction was not
statistically significant (P=0.111).

For that reason, the 49 seals were
independently stratified by sam-
pling location and sex and the mean
diet composition, unadjusted for dif-
ferential fat mass, was estimated
for the seals in each stratum. Sea-
son was eliminated from the model
because it was not a statistically
important covariate (see Discussion
section). Seals sampled in the vicin-
ity of Belle Chain and Bird Rocks,
both of which are characterized by
rocky, high-current habitat, had the
most diverse diets, with important
contributions from Black and Yel-
lowtail Rockfish, adult salmon spe-
cies, Pacific Herring, Shiner Perch,
and Spiny Dogfish (Fig. 3). Con-
versely, seals sampled from Padilla
Bay, which consists of shallow estu-
arine habitat, had diets that were,
on average, dominated by Shiner
Perch. Harbor seals sampled near
Vendovi Island, which has rocky
habitat with nearby access to sev-
eral bays, appeared to have an in-
termediate diet.

Male harbor seals were esti-
mated to consume larger quanti-
ties of Black and Yellowtail Rock-
fish, Pacific Herring, and Spiny
Dogfish than females, for which
Shiner Perch appeared to be more
important (Fig. 4). Diet estimates
for individual seals reflected ad-
ditional between-seal heterogene-
ity that was not explained by the
covariates. For example, although

Black and Yellowtail rockfish were estimated to be
more important to males than females overall, males
were not consistent in their reliance on rockfish spe-
cies. Of the 24 males sampled, 10 had an estimated

Prey group

Figure 3

Estimates of mean diet composition for harbor seals {Phoca uitulina) in the
Salish Sea, unadjusted for differential fat mass among prey classes, by sam-
pling location: (A) Belle Chain Islets, (B) Bird Rocks, (C) Padilla Bay, and
(D) Vendovi Island. Error bars are ±1 standard error of the estimate. Prey
classes are defined as B&YR (Black [Sebastes melanops] and Yellowtail [S.
flavidus] Rockfish), CR (Copper Rockfish [S. caurinus]), PSR (Puget Sound
Rockfish [S. emphaeus]), Chin (mature Chinook Salmon [Oncorhynchus
tshawytscha 3), Chum (mature Chum Salmon [O. keta}), Coho (mature Coho
Salmon [O. kisutch]), Sock (mature Sockeye Salmon [O. nerka ]), Pink (mature
Pink Salmon [O. gorbuscha]), Sal-M (medium-size Chinook and Coho Salm-
on), Sal-S (small Chinook, Chum, Sockeye, and Ppink Salmon), Pol (Walleye
Pollock [Theragra chalcogramma]), Her (Pacific Herring [Clupea pallasii ]
at least 2 years old), YH&SL (Pacific Herring less than 2 years old and
Pacific Sand Lance [Ammodytes hexapterus]), NA (Northern Anchovy [En-
grauiis mordax] ), SP (Shiner Perch [Cymatogaster aggregata ]), PM (Plainfm
Midshipman [ Porichthys notatus]), SD (Spiny Dogfish [ Squalus acanthias]),
OIS (Opalescent Inshore Squid [ Loligo opalescens]), G&S&F (Kelp Greenling
[Hexagrammos decagrammus ], Pacific Staghorn Sculpin [Leptocottus arma-
tus], and Starry Flounder [Platichthys stellatus}).

Bromaghm et al: Diets of Phoca vitulina in the Salish Sea revealed by analysis of fatty acid signatures

diet composition of 0.0% for Black and Yellowtail Rock-
fish, and estimates for the remaining 14 males ranged
from 8.2% to 51.4% and averaged 31.8%. Although fe-
males were more consistent in their reliance on Shiner

Perch, the estimated contribution of Black and Yellow-
tail Rockfish exceeded 25% for 3 individuals. There
were no discernible patterns in the capture location
or date with respect to the magnitude of rockfish
estimates for either males or fe-
males, a result that is consistent
with the nonsignificant interaction
between location and gender in the
linear model. One female seal was
captured twice, at Padilla Bay in
spring 2007 and at Vendovi Island
in winter 2008. The diet composi-
tion of this female was estimated to
be -90% Shiner Perch and -9% Chi-
nook Salmon, with negligible contri-
butions from other prey classes, on
both occasions.

Discussion

Our findings re-affirm the impor-
tance of several commercially impor-
tant fish species to harbor seal diets,
particularly salmon species, Pacific
Herring, and Shiner Perch, reported
by prior investigators (Scheffer and
Slipp, 1944; Everitt et al., 1981;
Brown and Mate, 1983; Olesiuk,
1993; Zamon, 2001; Orr et al., 2004;
Wright et al., 2007; Thomas et al.,
2011; Lance et al., 2012). However,
our results also reveal that rockfish
species contribute more substan-
tially to harbor seal diets than has
been recognized previously, exceed-
ing 10% of the average diet of all
harbor seals combined. Given that
QFASA estimates are thought to
describe diets integrated over a pe-
riod of weeks to months (Iverson et
al., 2004; Budge et al., 2006), esti-
mates of this magnitude may reflect
substantial periodic (and, perhaps,
sustained) predation on species of
rockfish. Although quantitative esti-
mates of rockfish abundance are un-
available, rockfish populations are
considered depressed and, given the
regional abundance of harbor seals
(Jeffries et al., 2003), the predation
rates indicated by these findings
may be sufficiently high to influ-
ence their population dynamics, on
a local or, perhaps, regional scale.
Consequently, management plans
to enhance rockfish abundance may
need to give greater consideration to
the potential influence of pinniped

O 0.4

O 03

0.2

0.5

0.2

^ =5? <?^ 6° o

Prey group

Figure 4

Mean diet composition estimates for harbor seals ( Phoca vitulina) in the
Salish Sea, unadjusted for differential fat mass among prey classes, by
sex: (A) females and (B) males. Error bars are ±1 standard error of the
estimate. Prey classes are defined as B&YR (Black \Sebastes melanops ]
and Yellowtail [S. flavidus] Rockfish), CR (Copper Rockfish (S. caurinus]),
PSR (Puget Sound Rockfish [S. emphaeus]), Chin (mature Chinook Salm-
on [ Oncorhynchus tshawytscha ]), Chum (mature Chum Salmon 10. beta]),
Coho (mature Coho Salmon 10. kisutch)), Sock (mature Sockeye Salmon
10. nerka]). Pink (mature Pink Salmon [O. gorbuscha]), Sal-M (medium-
size Chinook and Coho Salmon), Sal-S (small Chinook, Chum, sockeye, and
Pink Salmon), Pol (Walleye Pollock [ Theragra chalcogramma )), Her (Pacific
Herring \Clupea pallasii ] at least 2 years old), YH&SL (Pacific Herring
less than 2 years old and Pacific Sand Lance [Ammodytes hexapterus ]), NA
(Northern Anchovy \Engraulis mordax]), SP (Shiner Perch I Cymatogaster
aggregata]), PM (Plainfin Midshipman [Porichthys notatus]), SD (Spiny
Dogfish [Squalus acanthias]), OIS (Opalescent Inshore Squid [ Loligo opal-
escens]), G&S&F (Kelp Greenling [ Hexagrammos decagrammus]. Pacific
Staghorn Sculpin [Leptocottus armatus ], and Starry Flounder [Platichthys
stellatus]).

Fishery Bulletin 111(1)

predation. Additional research to verify and refine our
estimates of diet composition, and to begin quantifying
rockfish population dynamics and the influence of pin-
niped predation through incorporation of information
on harbor seal consumption rates (Howard, 2009; How-
ard et ah, 2013) is warranted.

Although rockfish species appear to constitute a
more foundational prey resource for harbor seals than
was recognized previously, harbor seal diets do not ap-
pear to be homogeneous, a finding that is consistent
with the results of observational studies of preda-
tory behavior (Suryan and Harvey, 1998; Tollit et al.,
1998; London, 2006; Wright et al., 2007; Hardee, 2008;
Thomas et al., 2011; Peterson et al., 2012). Substan-
tial spatial heterogeneity in diet composition was de-
tected among seals from the 4 sampling locations. For
example, the mean diet of seals sampled near Padilla
Bay was dominated by Shiner Perch, a common spe-
cies in bays and estuaries throughout the west coast
of North America (Hart, 1973). Seals sampled from the
other locations, which are characterized by deeper and
more open waters and greater rocky relief, tended to
rely more on species of rockfish and salmon and Pa-
cific Herring. Spatial patterns of habitat suitability un-
doubtedly underlie the relative abundance of prey in
local areas — a dynamic that is subsequently reflected
in seal diets. Heterogeneity among sexes also was ob-
served; a more diverse diet and greater use of rockfish
species and Spiny Dogfish were observed for male seals
than for females. Sex-based heterogeneity in diet was
not expected, given the slight sexual dimorphism in
harbor seals, but it may reflect a number of factors, in-
cluding intersexual competition for food resources, for-
aging behavior, predatory efficiency, and differences in
reproductive investment. For example, reproductively
active females tend to make shorter foraging trips dur-
ing early lactation (Boness et al., 1994) — behavior that
may reduce their access to some prey classes.

Although the sampling location and sex covariates
explained primary patterns among estimates of seal
diet composition, substantial unexplained heterogene-
ity was observed in the estimates. In particular. Black
and Yellowtail Rockfish were among the most impor-
tant prey species for a number of individual seals, es-
pecially males, but they were absent from the diets of
other seals. Whether differences between individual
seals could be explained by unmeasured covariates or
are attributable to individual preference or specializa-
tion is unknown. In either case, this heterogeneity with
respect to rockfish predation is an intriguing aspect of
the results of this study.

Our estimates of mean diet composition are not
thought to provide an accurate assessment of harbor
seal diets on an annual basis. Most seals were sam-
pled in the spring (Table 1), and no seals were sampled
from late May through late October. One would expect
season to be an important covariate that could explain
differences in diets, especially given the large changes
in the relative abundance of prey during the spring

spawning migration of Pacific Herring and the summer
availability of migrating adult salmon species (Stasko
et ah, 1976; Willson and Womble, 2006; Therriault et
al., 2009; Thomas et al., 2011). We surmise that such
temporal heterogeneity exists, but that evidence of
these seasonally available prey species in harbor seal
blubber was diminished by late October. The lack of
summer seal samples may partially explain the differ-
ence between these results and assessments of harbor
seal diet based on scats, in which salmon species and
Pacific Herring are prevalent (Luxa, 2008; Lance et al.,
2012). A complete assessment of seasonal variation in
harbor seal diets would require a somewhat expanded
investigation, in which the distribution of sampling ef-
fort would be designed to investigate potential changes
in diet expected on the basis of seasonally predictable
shifts in the availability of prey species. The expected
deposition and turnover rates of fatty acid compounds
in adipose tissue (Nordstrom et al., 2008) also would
contribute importantly to an optimized sample design.
On the basis of the results of this investigation, an ex-
panded effort to more fully explore spatial, temporal,
and demographic patterns in harbor seal diets likely
would be successful.

Two estimates of mean diet composition, one unad-
justed and one adjusted for differential fat mass of prey,
were provided for all seals combined (Fig. 2). However,
no adjustment for differential fat mass was made for
the estimates stratified by location and sex. The large
differences in fat composition among the prey classes
(Table 2) and, to a lesser extent, the lack of total mass
data for mature Chinook, Sockeye, and Pink Salmon,
all of which have high fat content, somewhat reduce
our confidence in the fat-adjusted estimates. The es-
timates unadjusted for differential fat mass are infor-
mative ecologically, providing information on the likely
sources of adipose tissue ingested by harbor seals. Fat-
adjusted estimates may be of greater interest from the
perspective of prey population demographics because
rescaling the estimates with mean fat per prey con-
verts the units to the relative numbers (proportions) of
prey animals consumed. Given an estimate of the num-
ber of fish consumed per unit of time, the fat-adjusted
estimates would facilitate the investigation of preda-
tion rates by prey class.

Although QFASA is a powerful method for investi-
gation of predator diets, it is important to recognize
potential problems with its use. With respect to marine
mammals, logistical constraints and permit require-
ments may limit sample sizes and preclude comprehen-
sive investigations of free-ranging populations. From a
statistical perspective, it is important to acknowledge
that estimates of diet composition are conditioned on
the calibration coefficients, the suitability of which in
any particular application cannot be verified. In the in-
stance of this investigation, the calibration coefficients
were estimated during a controlled feeding study of
captive harbor seals (Nordstrom et al., 2008), the spe-
cies of interest. Even so, the degree to which the coef-

Bromaghin et a!: Diets of Phoca vitulina in the Salish Sea revealed by analysis of fatty acid signatures

ficients are applicable to wild seals with a more diverse
diet is unknown, and use of previously published co-
efficients is a potential source of bias. To conduct an
independent feeding trial in association with every
field investigation obviously is infeasible and therefore
reliance on published calibration coefficients may be
unavoidable. However, some investigators have noted
that diet composition estimates are sensitive to the
values of calibration coefficients (Meynier et ah, 2010),
and such sensitivity may also be the case for the suite
of fatty acid compounds used in mixture modeling.
Achievement of adequate sample sizes of all potential
prey species, including representatives of the same spe-
cies at various life history stages and seasons, such as
immature and mature species of salmon, is obviously
an important precursor to implementation of QFASA.
Although such considerations do not negate the util-
ity of QFASA as a tool to estimate diet composition,
researchers need to be cognizant of these issues, and
therefore the development of analytical procedures to
assess sensitivity may be helpful.

Conclusions

Several fish stocks of historic commercial importance
within the Salish Sea are considered to be depressed
and their recovery is a high management priority.
Whether abundant pinniped populations may be im-
peding management actions intended to stimulate re-
covery is an open question in this region. Our findings
confirmed the importance of salmon species and Pacific
Herring in harbor seal diets, but they also revealed that
other species, including rockfish species, may contrib-
ute more substantially to harbor seal diets than had
been realized previously. Although estimates of harbor
seal diet composition varied spatially, demographically,
and among individual seals, species of rockfish were
estimated to compose a large proportion of the diets
of several individual seals. These results, in combina-
tion with the current high abundance of harbor seals,
indicate that predation may be an important ecologi-
cal factor in the regulation of the local and regional
abundance of rockfish populations — a possibility that
warrants additional investigation.

Acknowledgments

We thank B. Applegate, R. Tee, and S. Ali for their
assistance in the ASET Laboratory; B. Hagedorn for
logistical support and direction; D. Lambourn, B. Mur-
phie, J. Gould, T. Cyra, J. Gaydos, K. Reuland, S. Peter-
son, P. Olesiuk, and many others for their help captur-
ing seals; R. Sweeting (Fisheries and Oceans Canada
and RV Ricker), S. O’Neill (NOAA), and G. Williams
(NOAA) for providing fish samples; A. Default (NOAA),
and Western Washington University students for assis-
tance processing fish samples; and A. Thomas for creat-

ing Figure 1. We also thank K. Oakley (U.S. Geological
Survey) for providing helpful comments that greatly
improved the manuscript. This study was supported
by National Science Foundation Award No. 0550443
to A. Acevedo-Gutierrez, the University of Alaska An-
chorage, Washington Department of Fish & Wildlife,
Olympia, Washington, U. S. Geological Survey, and the
Alaska Science Center. Harbor seal research activities
were conducted under Marine Mammal Protection Act
Research Permit 782-1702-00.

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Fish consumption by harbor seals (Phoca
vitulina) in the San Juan Islands, Washington

Email address for contact author: sarah_howard@nps gov

Abstract — The harbor seal ( Phoca
vitulina) is a large-bodied and abun-
dant predator in the Salish Sea
ecosystem, and its population has
recovered since the 1970s after pas-
sage of the Marine Mammal Protec-
tion Act and the cessation of boun-
ties. Little is known about how this
large predator population may affect
the recovery of fish stocks in the
Salish Sea, where candidate marine
protected areas are being proposed.
We used a bioenergetics model to
calculate baseline consumption rates
in the San Juan Islands, Washing-
ton. Salmonids ( Oncorhynchus spp.)
and herring (Clupeidae) were the 2
most energetically important prey
groups for biomass consumed by
harbor seals. Estimated consumption
of salmonids was 783 (±380 standard
deviation [SD ] ) metric tons (t) in
the breeding season and 675 (±388
SD t in the nonbreeding season.
Estimated consumption of herring
was 646 (±303 SD) t in the breeding
season and 2151 (±706 SD) t in the
nonbreeding season. Rockfish, a de-
pressed fish stock currently in need
of population recovery, composed one
of the minor prey groups consumed
by harbor seals (84 [±26 SD| t in the
nonbreeding season). The variables
of seal body mass and proportion of
prey in seal diet explained >80% of
the total variation in model outputs.
Prey groups, such as rockfish, that
are targeted for recovery may still
be affected by even low levels of
predation. This study highlights the
importance of salmonids and herring
for the seal population and provides
a framework for refining consump-
tion estimates and their confidence
intervals with future data.

Manuscript submitted: 4 November 2011.
Manuscript accepted 31 October 2012.
Fish. Bull. 111:27-41 (2013).
doi: 10. 7755/FB. 111.1.3

The views and opinions expressed
or implied in this article are those of the
author (or authors) and do not necessar-
ily reflect the position of the National
Marine Fisheries Service, NOAA.

Sarah M. S. Howard (contact author)1
Monique M. Lance2
Steven J. Jeffries2
Alejandro Acevedo-Gutierrez1

1 Biology Department
Western Washington University
516 High Street

Bellingham, Washington 98225
Present address: National Park Service
10 Organ Pipe Drive
A|o, Arizona 85321

2 Washington Department of Fish & Wildlife
7801 Phillips Road SW

Lakewood, Washington 98498

Overfishing and habitat change have
affected fish populations heavily
in the inland waters of the Pacific
Northwest. Many formerly abundant
fish species are now species of con-
servation concern, including ground-
fish stocks, such as rockfish species
( Sebastes spp.) and Pacific Hake
(Merluccius productus), forage fish
stocks such as Pacific Herring (Clu-
pea pallasii), and several salmonid
species ( Oncorhynchus spp.) (Musick
et ah, 2000; Mills and Rawson, 2004).
Most recently, 3 rockfish species (S.
ruberrimus, S. pinniger, S. paucispi-
nis) were listed under the Endan-
gered Species Act as threatened or
endangered in Puget Sound, Wash-
ington State (Federal Register, 2010).

The decline of all these popula-
tions, which perform a critical func-
tion in regional food webs (Simenstad
et al., 1979; Schindler et al., 2003)
and have commercial and recre-
ational value, has created a need for
recovery strategies at the ecosystem
level. Fish recovery efforts currently
rely on traditional fisheries manage-
ment approaches, such as reduction
of fishing pressure and creation of
no-take refuges or marine reserves,
and on habitat restoration (Allison et

al., 1998; Roni et al., 2002). Marine
reserves in particular are more like-
ly to be successful for species, such
as rockfish, that have small home
ranges and high site fidelity (Love
et al., 2002), and reserves are impor-
tant management tools for recovery
of rockfish in the Pacific (Murray et
al., 1999). More reserves have been
proposed recently for the San Juan
Islands,1 an island group that is part
of the Salish Sea marine ecosystem
that spans U.S. and Canadian waters
(Fig. 1). For pelagic species, such as
salmonids and forage fishes, recovery
efforts call for habitat protection and
mitigation of water-pollution issues,
among other factors, as management
tools (Fluharty, 2000; Schindler et
al., 2003).

The restoration of predators in ma-
rine ecosystems can reestablish tro-
phic relations and restructure habi-

1 McConnell, M. L., and P. A. Dinnel. 2002.
Rocky reef bottomfish recovery in Skagit
County. Phase II final report: assessment
of eight potential marine reserve sites
& final site recommendations. Skagit
County Marine Resources Committee,
Mount Vernon, WA, 43 p. [Available
from http://www.nwstraits.org/Archives/
Library.aspx.]

Fishery Bulletin 1 1 1 (1)

Figure 1

Map of the study area, the San Juan Islands and eastern bays, where seal
scat collections were made for a bioenergetics model to examine the quan-
tity of fish consumption by the harbor seal ( Phoca uitulina ) population dur-
ing 2007-08. Black circles indicate harbor seal scat collection sites.

tat with usually positive results (Shears
and Babcock, 2002; Shears et ah, 2006);
however, predators also can cause declines
in the size distributions and abundance of
prey species inside marine reserves (Sala
and Zabala, 1996; Fanshawe et ah, 2003).
Large-bodied and abundant predators can
contribute significantly to fish mortality,
especially when prey species are already
low in abundance, and may theoretically
influence prey population recovery (Mohn
and Bowen, 1996; Bundy, 2001; DeMaster
et ah, 2001; Fu et al., 2001; Trzcinski et ah,

2006). Therefore, there is a need to under-
stand the prey requirements of predators
that consume fish species of conservation
concern to evaluate if such requirements
conflict with regional management goals.

In the Salish Sea, the harbor seal ( Phoca
vitulina ) is an abundant, generalist marine
predator whose population has steadily in-
creased since gaining protected status in the
1970s. The harbor seal population in Wash-
ington State experienced logistic growth
from the 1970s to the 1990s, increased 7- to
10-fold in size in different regions, and now
appears to be at carrying capacity (Jeffries
et ah, 2003). Estimates of the regional popu-
lation in the San Juan Islands and eastern
bays in the early 1970s were approximately
1000 animals; currently, there are approxi-
mately 8000. 2 The age structure of the har-
bor seal population in British Columbia was
documented in Bigg (1969), on the basis of
seals collected and aged in the 1960s. After
exponential population increases, this popu-
lation was heavily weighted toward juvenile age classes
by the 1980s (Olesiuk, 1993). Given the population in-
crease in all regions of the Salish Sea, the current age
structure of the harbor seal population in the San Juan
Islands is unknown.

As with other harbor seal populations in the east-
ern Pacific, harbor seals in the San Juan Islands take
advantage of the large influx of adult salmonids in
late summer and fall and increase the diversity of
their diet at other times of the year when salmonids
are less available (Hauser et al., 2008; Lance et al.,
2012). Salmonids, Pacific Herring, Pacific Sand Lance
(Ammodytes hexapterus), Northern Anchovy (Engraulis
mordax ), Walleye Pollock (Theragra chalcogramma),
and estuarine species, such as Shiner Perch ( Cymato -
gaster aggregata), also form significant proportions of
their diet in the San Juan Islands and nearby estua-
rine ecosystems (Lance et al., 2012).

2 Washington Department of Fish & Wildlife. Unpubl. data.
Washington Department of Fish & Wildlife, 7801 Phillips
Road SW, Lakewood, WA 98498.

To calculate population-level consumption of fish
species of conservation concern and other common har-
bor seal prey in the San Juan Islands, a bioenergetics
model was used to determine energetic requirements.
The model incorporated seasonal changes in seal diet
and life history parameters during breeding and non-
breeding seasons. We also used simulated data and
sensitivity analyses to address uncertainty in the over-
all model and in 2 specific components that may have
a strong influence on predicted consumption of prey: 1)
uncertainty in age structure of the harbor seal popu-
lation and 2) seasonal changes in energy intake (e.g.,
fasting during breeding season).

Methods

Area and timeframe of study

The region of the San Juan Islands and eastern bays
is an area where many fish species of conservation
concern occur and also an area where the majority of
the harbor seal population resides in the inland waters

Howard et ai.: Fish consumption by harbor seals ( Phoca vitulina ) in the San Juan Islands, Washington

of Washington State. The San Juan Islands (48°35'N,
122°55'W) are characterized by tidally influenced rocky
reefs and isolated rocks surrounded by deep water
where harbor seals often congregate at haul-outs (loca-
tions where seals come ashore). The adjacent eastern
bays, in contrast, consist of large, soft-bottomed, shal-
low bays (48°33'N, 122°30'W) (Fig. 1).

The consumption model was constructed for a sin-
gle annual cycle for the harbor seal population dur-
ing 2007-08. The model included 2 seasons: breeding
(15 June-15 September) and nonbreeding (16 Septem-
ber-14 June) determined on the basis of seal pupping
phenology in the San Juan Islands (Huber et al., 2001;
Patterson and Acevedo-Gutierrez, 2008). The 2 sea-
sons were delineated to reflect known behavioral shifts
(more time spent ashore to nurse pups, shallow-water
breeding displays by males) related to pupping and
breeding activities and subsequent changes in ener-
getic expenditures (Coltman et al., 1998; Bowen et al.,
1999).

The model was programmed in R software, vers.
2.7.1 (R Development Core Team, 2008) and used re-
gional activity, abundance, and diet data, as well as
physiological data from the literature. Model param-
eters were grouped into 3 categories: bioenergetics,
population, and diet (Lavigne et al., 1982; Winship et
al., 2002) (Table 1).

Model structure

Bioenergetics Energetic requirements were calculated
with a bioenergetics approach that described the en-
ergy budget of an individual seal, which is a function
of body size, activity budgets, growth, and reproductive
costs. Sex- and age-specific gross energy requirements
were calculated with Equation 5 in Boyd (2002):

EG, = [l(""‘-(rf9Ai)86400] + ft

I“‘ ’ U)

where EGt = energy requirements in a particular stage
i of the annual cycle;

y, = the power (watts) generated under activity
/"within stage i of the annual cycle;

= proportion of time spent in activity f\
g: - the cost of growth in stage i of the annual
cycle; and

dl - the digestive efficiencies of food being
eaten.

The model had 6 sex-and-age classes: 1) adult fe-
males (>6 years), 2) adult males (>8 years), 3) subadult
females (1-6 years), 4) subadult males (1-8 years), 5)
female pups (<1 year), and 6) male pups (<1 year). The
subadult to adult division was made at the age(s) har-
bor seals reach their predicted maximum weight (ap-
proximately 66 kg and 89 kg for females and males,
respectively) on the basis of the growth curve in Ole-

siuk (1993). Daily growth increments for each sex-and-
age class were calculated from the same growth curve.
Activity budgets were estimated from free-living har-
bor seals tagged with data recorders that recorded 3
behavioral periods: haul-out, diving, and shallow-water
activity (Table 1).

Population abundance and age structure Aerial popula-
tion surveys of harbor seals have been conducted an-
nually by the Washington Department of Fish & Wild-
life with fixed-wing aircraft to estimate the number of
animals hauled-out during the lowest tide of the day
since 1978 (Jeffries et al., 2003). Results from these
surveys were used to estimate the abundance of harbor
seals in the study area in 2007-08. The breeding sea-
son (July) correction factor of 1.53 (to account for seals
not hauled-out at the time of the survey) was used to
estimate the size of the breeding season population
(Huber et al., 2001). Age-dependent mortality rates in
Olesiuk (1993) were used to estimate the age structure
(number of seals in each sex and age class) of the har-
bor seal population:

^s(x+l)=Ns(x,e~rt ’ (2)

where NS(x) = number of seals in sex class S and age
class x;

-r = the age-dependent mortality rate; and
t = time interval between age classes.

The breeding season population vector was adjusted
by iteration to sum to the total population estimate
from aerial surveys. Seal abundance in the nonbreed-
ing season was calculated by estimating the numbers
still alive in each sex and age class, by using the same
age-dependent mortality rates calculated per day (in-
stead of annually) and by multiplying the number of
days in the breeding cycle.

Population energetic requirements were calculated by
multiplying individual requirements by the population
abundance vectors to estimate energetic requirements
for each sex and age class. Reproductive costs were then
calculated for the entire population on the basis of val-
ues from the literature for gestation and lactation costs
and fertility rates (Bigg, 1969; Olesiuk, 1993).

Digestive efficiency Data from the literature were used
to translate net energy requirements of the harbor
seal population into gross energy requirements and
prey consumption by first taking into account assimi-
lation efficiency and the heat increment of feeding (the
increase in metabolism or heat produced during di-
gestion) for harbor seals. We used the minimum and
maximum values reported in the literature to account
for differences in digestive efficiencies related to pro-
tein and fat content of prey (Markussen et al., 1994;
Trumble et al., 2003).

Table 1

Data sets used in the consumption model in a study of the harbor seal ( Phoca vitulina ) population in the San Juan Islands and eastern bays during breeding and
nonbreeding seasons, 2007-08. Model parameter symbols refer to Equations 1-3 in text. All energy units were converted to watts. H=haul-out; d=dive; s=surface.
NA= not applicable.

Fishery Bulletin 1 1 1 (1)

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Howard et at: Fish consumption by harbor seals (Phoca vitulina) in the San Juan Islands, Washington

Diet

Collection of scat samples Scat samples were collect-
ed at 23 sites that represented regional variation in
habitat in the San Juan Islands from 2005 to 2008 as
part of a larger harbor seal diet study conducted in
the northern Puget Sound (Fig. 1) (Lance et al., 2012).
Samples collected during seal breeding and nonbreed-
ing seasons in 2007-08 were used in our study. De-
tailed scat sample processing, collection information,
and analysis of frequency occurrence of prey items in
harbor seal diet are summarized in Lance et al. (2012).
Briefly, samples for the diet study were collected from
harbor seal haul-out locations during daytime low
tides, placed in plastic bags, and then frozen until they
were processed. Scat samples were processed following
Lance et al.3 and Orr et al. (2003). Otoliths were mea-
sured and graded according to the methods of Tollit et
al. (2007). On otoliths that were graded as good (no or
minimal erosion) and fair (small amount of erosion),
the width and length were measured with an ocular
micrometer. For our study, scat samples were pooled
by seal breeding and nonbreeding seasons for further
analyses.

Reconstruction of wet biomass To choose appropriate
input values for diet in the model, a wet biomass re-
construction technique (Laake et al., 2002) was used to
estimate the proportion by wet weight of prey items in
harbor seal diet. This technique focuses on energetic
content of seal diet, rather than on frequency of items
in diet, by accounting for the number and size of prey
consumed in a diet sample. The proportion of wet bio-
mass of a prey item (jt() in harbor seal diet was calcu-
lated by (Laake et al., 2002):

where nt = the corrected number of items of prey item /;
and

wt = the average weight (in grams) of all prey
items i.

The corrected number of “items” (n,, number of in-
dividuals in the sample) was calculated by applying
a species-specific (or closest proxy) correction factor
to account for otolith loss during digestion. We used
otoliths to enumerate all species except Shiner Perch,
for which we used the number of pharyngeal plates to
derive a more reliable passage rate. We lacked otolith-
loss correction factors for herring (Clupeidae) and Wall-
eye Pollock; therefore, we considered the correction fac-
tors for Pacific Sardine (Sardinops sagax) and Pacific
Hake in Phillips and Harvey (2009), respectively, to

Lance, M. M., Orr A. J., Riemer S. D., Weise M. J., and Laake
J. L. 2001. Pinniped food habits and prey identification
techniques protocol. AFSC Processed Report 2001-04, 41
p. Alaska Fisheries Science Center, Seattle, WA. [Available
from http://access.afsc.noaa.gov/pubs/search.cfm.!

be reasonable proxies because these species are simi-
lar in size and structure (M. M. Lance, personal com-
mun.l. We used a Pink Salmon ( Oncorhynchus gorbus-
cha) otolith-loss correction factor for all salmonids, a
Shortbelly Rockfish ( Sebastes jordani) correction factor
for all rockfish species, and species-specific correction
factors for Shiner Perch and Pacific Staghorn Sculpin
( Leptocottus armatus) (Harvey, 1989; Phillips and Har-
vey, 2009).

Length correction factors were applied to measure-
ments from otoliths scored as being in good or fair con-
dition to account for otolith erosion during digestion.
Corrected otolith lengths then were used to calculate
the fish size with species-specific length-weight regres-
sions (Harvey et al., 2000). When we lacked species-
specific correction factors or length-weight regressions,
we used estimated body sizes of prey items.

Otoliths of juvenile and adult salmonids were distin-
guished on the basis of otolith and bone sizes. Otoliths
that were graded in good enough condition to measure
and reconstruct salmonid size were uncommon in scat
samples; therefore, for salmonid adults that were not
identified to species, we used an approximate average
size (1589 g) for Pink Salmon, the species most com-
monly consumed by harbor seals (Lance et al., 2012).
An average estimated size of 35 g was used for all sal-
monid juveniles. We also lacked otolith-length correc-
tion factors for herring and Walleye Pollock; therefore,
we used Pacific Sardine and Pacific Hake as proxies.
The remaining length correction factors that we used
were a Shortbelly Rockfish correction factor for all
rockfish species, and species-specific correction factors
for Shiner Perch and Pacific Staghorn Sculpin.

It should be noted that reconstruction was not pos-
sible for all species in the diet samples because of the
diversity of harbor seal diet and lack of appropriate
correction factors as noted previously and in Table 2.
Given the complexity of harbor seal diet and lack of
reconstruction techniques for several species, we recon-
structed the proportion in the sample only for prey spe-
cies of conservation concern or for prey species whose
frequency of occurrence was >5.0 in the broader study
of harbor seal diet (Lance et al., 2012). Our goal was
to set a reasonable range of values for model input in
addition to describing diet composition; therefore, we
make here a distinction between diet sample results
and the parameter values used in the model to calcu-
late consumption. When there was great uncertainty
in percent contribution by wet weight to harbor seal
diet because of the use of proxy correction factors or
omission of some species from biomass reconstruction,
confidence intervals were increased (see Model uncer-
tainty and parameter estimation section).

Consumption rates

We calculated consumption (as biomass) for 5 key
prey species or groups that are species of conserva-
tion concern or most common in harbor seal diet: her-

Table 2

Wet biomass construction results for the most common (frequency of occurrence >5.0) prey species or groups in diet of harbor seals ( Phoca vitulina ) during
breeding and nonbreeding seasons, 2007-08. 1 All prey with frequency of occurrence >5.0 are listed to illustrate which common species or groups were not recon-

Fishery Bulletin 1 1 1 (1)

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;Average and ranges reported are between sampling months,
includes all unidentified clupeids.

•^No otolith length or otolith loss correction factor was available; these estimates should be treated with caution.

Howard et al Fish consumption by harbor seals ( Phoca vituiina ) in the San Juan Islands, Washington

ring, salmonids, rockfish, Walleye Pollock, and Shiner
Perch. Gross energy requirements were translated to
consumption rates by applying the energetic density of
prey to the proportion by wet weight of prey items in
seal diet (Perez, 1994; Van Pelt et ah, 1997; Paul et ah,
1998; Payne et ah, 1999; Anthony et al., 2000; Roby
et al., 2003). After biomass reconstruction, all species
of adult and juvenile salmonids were combined into a
“salmonid” complex. A “herring” complex represented
Clupea pallasii and unidentified clupeid species. There
are 2 other clupeid species in the study area, but, be-
cause of their rareness, we assumed most species were
C. pallasii (M.M. Lance, personal commun.). When prey
were placed into broader taxonomic groups, we used
the minimum and maximum values for energetic densi-
ty reported for all prey sizes and ages in the literature
to represent the prey group.

Model uncertainty and parameter estimation

Model variables described in Table 1 were randomly
chosen during 1000 simulations from probability dis-
tributions to estimate uncertainty in all model outputs.
Where estimation of distribution parameters was not
straightforward (e.g., lognormal), a maximum likeli-
hood technique with the MASS package in R was used;
this technique estimates the joint likelihood for dis-
tribution parameter values, given the seal body mass
values for each sex-and-age class (Venables and Ripley,
2002). We also made the following changes to diet re-
sults to adjust the uniform distribution parameters for
percentage by wet weight of prey in diet. If we had
set the minimum and maximum values for a uniform
distribution for proportion in diet exactly as found in
diet samples, it would have been uninformative (i.e.,
a range of 0-100 often occurred but would imply no
prior knowledge of diet composition; Table 2). There-
fore, zero values from diet samples were discarded and
minimum values for herring and salmonids were set as
calculated from the remaining diet samples. For Shiner
Perch and Walleye Pollock, zero values also were dis-
carded. The minimum possible value was assumed to
be 1%, and the maximum value was set near the aver-
age calculated from diet samples. Harbor seal diet is
diverse; therefore at least 20-30% of harbor seal diet
was assumed to be made up of other species, and the
maximum value possible for any prey species was set
at 70-80% (the maximum value for nonbreeding season
was set slightly lower because of increased diversity of
diet). All model outputs are reported as means ^stan-
dard deviation).

Sensitivity analyses also were used to identify pa-
rameters with the most influence on model outputs by
systematically allowing one parameter at a time to be
chosen randomly while other variables were fixed at
their mean value(s). In this manner, any variation in
the model outputs should be the direct result of varia-
tion in the parameter of interest (Shelton et al., 1997;
Stenson et al., 1997; Winship et al., 2002). The percent-

age of variance explained by a single variable was cal-
culated as the variance of model outputs when single
random variables were used and divided by the total
variance when all variables were randomly chosen.

To estimate the effect of age structure on total prey
consumption, we used different ratios of adults to sub-
adults in 3 alternate model scenarios. We increased the
number of adults in the population by 25%, 50%, and
100% and kept the total population size stable.

During the breeding season, adult harbor seals fast
or reduce consumption (Bowen et al., 1992; Coltman
et al., 1998); therefore, there may be a discrepancy
between predicted energy requirements and timing
of consumption during an annual cycle. Rather than
use direct consumption, we addressed the effect of this
discrepancy with a correction factor that accounted for
energy obtained from burning body fat stores in the
breeding season. We estimated the amount of energy
consumed, stored as body fat, and later metabolized by
adult seals with the same estimates of digestive effi-
ciency and energy density of prey that were used in the
overall consumption model.

Results

Fish consumption

There were 196 and 361 scat samples collected dur-
ing the breeding and nonbreeding seasons, respective-
ly. In these samples, 23 and 29 prey taxa were iden-
tified during the breeding and nonbreeding seasons.
Ten prey taxa were selected for reconstruction in this
study; they had a frequency of occurrence >5.0 in the
broader harbor seal diet study (Lance et al., 2012) or
were species of conservation concern. Of these 10 taxa,
3 prey groups (unidentified gadid, skate species, and
American Shad [Alosa sapidissima ]) could not be used
because we had insufficient methods (e.g., lack of cor-
rection factors) to reconstruct their presence in seal
diet. Of the remaining prey, herring comprised the vast
majority of reconstructed samples: >80% of wet weight
in both breeding and nonbreeding seasons. Salmonids
composed 15% and 9% in the breeding and nonbreed-
ing seasons, respectively (Table 2). We were not able to
identify rockfish otoliths to species in either season. In
the breeding season, rockfish frequency of occurrence
was 0.5% and therefore was assumed to contribute
little in energetic terms to diet and was not further
considered for calculation of consumption rates. Mea-
surable otoliths were not found for rockfish species in
the nonbreeding season; therefore, we were unable to
determine species or size. During the nonbreeding sea-
son, rockfish frequency of occurrence was 1.4% (Lance
et al., 2012); we set a hypothetical range for proportion
of wet weight of rockfish in diet at 1. 0-2.0%. Walleye
Pollock and Shiner Perch constituted a relatively mi-
nor portion (averages 0.5-2. 8%) of reconstructed diet
(Table 2).

Fishery Bulletin 1 1 1 (1)

During the seal breeding season, the average con-
sumption for prey species calculated over 1000 simu-
lations was 783 (±380) metric tons (t) of salmonids,
646 (±303) t of herring, 50 (±17) t of Walleye Pollock,
and 22 (±4) t of Shiner Perch (Fig. 2). Subadult seals
of both sexes consumed the greatest proportion of the
total biomass (approximately 30-40% each), followed
by adult females (27%). Adult males consumed a rela-
tively small proportion of total biomass compared with
adult females and subadults, and their consumption
was only slightly higher than the biomass consumed
by pups of both sexes (each <10%).

During the nonbreeding season, consumption of
herring and salmonids had the widest range of val-
ues; rockfish, Shiner Perch, and Walleye Pollock were
less variable. The average consumption for prey spe-
cies calculated over 1000 simulations was 84 (±26)
t of rockfish, 675 (±388) t of salmonids, 2151 (±706)
t of herring, 66 (±13) t of Walleye Pollock, and 86 (±22)
t of Shiner Perch (Fig. 2).

The per capita fish consumption rate predicted

by the model was 2.1 kg day-1
seal-1 (annual average 2.9, 2.8,
2.0, 2.2, and 1.0 kg for adult
females, adult males, subadult
females, subadult males, and
pups, respectively). As was
evident during the breeding sea-
son, subadults (which included
pups from the previous breed-
ing season) of both sexes con-
sumed the greatest proportion of
the total biomass (approximately
30-45% each), followed by adult
females (19%). Adult female
consumption dropped slightly in
the nonbreeding season. Adult
males consumed the smallest
proportion in the population
(5%).

Sensitivity analyses and assessment
of model uncertainty

Variation in seal body mass had
the largest effect on energy use
of the population and account-
ed for >80% of model variance
in both seasons. Taken togeth-
er, all bioenergetics variables
(mass, growth rates, and activity)
accounted for the majority of the
variance in the simulation mod-
el. Fertility rates accounted for
the next-greatest variance
(7.3%) after body mass during
the breeding season while pop-
ulation size contributed least
(1.3%) to overall model variabil-
ity (Fig. 3).

Consumption estimates of salmonids and herring
were most sensitive to estimates of proportion of prey
in the diet and energy density of prey. Variation in con-
sumption estimates was low when the heat increment
of feeding and assimilation efficiency parameters were
varied within their estimated ranges. The variance in
the nonbreeding season seen in the overall simulation
model for both salmonids and herring was not well ex-
plained by any single prey variable (Fig. 4).

We estimated that adult seals used approximately
1,100,000 MJ of fat stores during the breeding season.
Assuming an average prey energy density of 4000 J
g1, this use of energy was equivalent to consumption
of 300 t or approximately 6% and 21% of annual and
breeding-season energy use, respectively. Increasing
the number of adult seals in the population led to a
positive increase in population energy use, although at
a relatively slow rate of increase: even when we dou-
bled the number of adults in the population, energy
use increased only by 7% (Fig. 5).

Howard et al.: Fish consumption by harbor seals ( Phoca vitulma ) in the San Juan Islands, Washington

1.4

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Breeding

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Figure 3

Effect of bioenergetics and population variables, relative to season (breeding or
nonbreeding), on net population energy use (in megawatts) of harbor seals ( Phoca
vitulina) in the San Juan Islands and eastern bays during 2007-08. Distribution
of model outputs after running 1000 simulations with all variables (“Full”), single
(individual variables), or “groups of variables” (“Bioenergetics” [mass, activity,
and growth rates]” or “Population” [fertility and abundance!) selected randomly.
Solid circles indicate medians, boxes enclose the interquartiles, vertical dashed
lines represent 1.5* the interquartile range, and open circles indicate outliers.

Discussion

The prey consumption model
was quite sensitive to body
mass: when body mass was
varied +10% around the aver-
age, there was a corresponding
+ 10% change in the energy use
outcome. Body mass controls
many physiological functions in
organisms, and because mass-
based predictive relationships
were used for metabolic rate,
the sensitivity of the model to
body mass was not entirely un-
expected. By simply account-
ing for body size and number
of harbor seals, the model cap-
tured the bulk of energy use in
the population. In fact, omission
of reproduction costs (lactation
and gestation costs) did not af-
fect estimates of nonbreeding
season energy use and lowered
breeding season estimates by
approximately 10%.

Predicted per capita fish con-
sumption of 2.1 kg day-1 seaP1
fell within the range estimated
for the harbor seal populations
in British Columbia, Canada,
and Norway: 1.9 kg and 4 kg,
respectively (Harkbnen and
Heide-Jprgensen, 1991; Ole-
siuk, 1993; Bjprge et al., 2002).

Despite their large body size,
adult males were the least nu-
merous sex-and-age class in the
population — information that
explained their low proportion of total population con-
sumption when the population was considered as a
unit. Consumption was for the most part proportional
to the biomass of the total seal population; therefore,
any change in total population size would correspond
to a roughly equal percent change in estimated con-
sumption. With this prediction, all other model vari-
ables were assumed to be similar among years, and
this assumption seems reasonable given that the total
population size has stabilized during the last decade2
(Jeffries et al., 2003). Nevertheless, at dramatically
different population sizes, there may be different be-
havioral or population changes that would need to be
taken into account (e.g., individual prey preferences,
intraspecific competition, fertility rates, and mortality
rates) to predict population consumption.

In contrast to the other population variables, only
point estimates were used for mortality rates. The age
structure of the harbor seal population used in the ba-
sic consumption model was heavily dominated by sub-

adults, and the population structure was based on data
from a time period when the harbor seal population
was depressed. However, changing the age structure in
our alternative model (see Appendix) caused relatively
minor changes in the energy budget, especially com-
pared with the sensitivity of the model to body mass.
If the increase in population size since the 1970s has
led to decreased juvenile survival rates, as is predicted
to be the case for marine mammals (Fowler, 1981; Hiby
and Harwood, 1985), and adult seals are now more
dominant in the population, overall consumption rates
still should be similar to those that we predicted, at
least at the adult to subadult ratios that were tested
in alternate model versions.

For species, such as harbor seals, that use fat stores
during fasting periods, inferring consumption directly
from energetic requirements may be somewhat mis-
leading. Harbor seals fast or reduce feeding rates for
2-6 weeks and can lose up to 33% of body mass during
the breeding season (Bowen et al., 1992; Coltman et

Fishery Bulletin 1 1 1 (1)

4000 -

g 3000

2000

1000 -

Breeding

Nonbreeding

•

<<^

X ,/ ✓

o°

Figure 4

Effect of prey variables on herring consumption of harbor seals (Phoca vi-
tulina ) relative to season (breeding or nonbreeding), in the San Juan Islands
and eastern bays during 2007-08. Distribution of model outputs after run-
ning 1000 simulations with all (“Full”) or single variables selected randomly.
Proportion=percent of total biomass in seal diet composed of herring (%). En-
ergy density=energy contained in prey items (J g-1). Efficiency=percent of gross
energy available in prey item that is metabolizable (%). HIF=heat increment
of feeding (%). Solid circles indicate medians, boxes enclose the interquartiles,
vertical dashed lines represent 1.5* the interquartile range, and open circles in-
dicate outliers. All simulations allowed variance in seal energetic requirements.

al., 1998). Pinnipeds increase feeding rates either im-
mediately after the breeding season or before the next
breeding season to regain fat stores (Beck et al., 2003).
In addition, there are seasonal changes in energy in-
take that occur in harbor seals and other pinnipeds
(Schusterman and Gentry, 1971; Rosen and Renouf,
1998). We addressed this discrepancy in timing of pre-
dicted energetic requirements and feeding through as-
sessment of how much prey may be consumed by adult
seals in the winter and spring and later used as fat
stores. We found the amount to be a minor proportion
of annual consumption but a more significant portion
of the breeding season estimates. Therefore, the effect
of consumption in the breeding season may be reduced,
and consumption during the winter may be higher than
we predicted.

Bioenergetic variables (especially body mass) con-
tributed most to sensitivity in calculations of energy

requirements in this study. Other
pinniped consumption models
similarly have identified body
mass and body-mass predicted
energetic requirements as a sig-
nificant source of model variation
(Mecenero et al., 2006; Chassot
et al., 2009). When the full con-
sumption model was examined,
the assumed proportion of each
prey species in the diet had
the largest effect on consump-
tion outputs — a result that was
also similar to other pinniped
consumption models (Mohn and
Bowen, 1996; Shelton et al., 1997;
Mecenero et al., 2006; Overholtz
and Link, 2007), suggesting that
future effort should be focused on
refining the contribution of differ-
ent prey to harbor seal diet. Ge-
netic and molecular techniques
increasingly are used to identify
diet composition (Casper et al.,
2007; Deagle and Tollit, 2007).
It is likely necessary to evalu-
ate the diet of generalist marine
predators with a combination
of techniques, given that these
techniques often yield different
results and can answer different
questions (Tollit et al., 2006). The
model described here can be used
to test assumptions about the
relative importance of salmonids
and herring compared with other
species in harbor seal diet as oth-
er data become available.

Estimates indicate that rock-
fish species constituted a rela-
tively minor proportion of total
consumption by harbor seals. There are more than 26
species of rockfish that occur in the inland waters of
Washington State, and many species are listed as endan-
gered by the state. Under the federal Endangered Spe-
cies Act, 2 species are listed as threatened and 1 species
is listed as endangered. The 2 most dominant species,
Copper ( Sebastes caurinus ) and Quillback (S. maliger)
Rockfish, for which abundance data are well document-
ed, have both undergone serious declines and are consid-
ered vulnerable to extinction (Mills and Rawson, 2004).
For depressed species such as these, even small amounts
of predation may be significant. If we assume an average
size of 1 kg for a rockfish in harbor seal diet (ignoring
age- or species-size differences), harbor seals hypotheti-
cally consumed 84,000 rockfish individuals in 2007-08
in the San Juan Islands and eastern bays. However, to
illustrate the importance of age or species preference by
harbor seals, if we assume that harbor seals eat only

Howard et al Fish consumption by harbor seals ( Phoca vitulina) in the San Juan Islands, Washington

12 -

1.0 -

0 8 -

0.6 -

Figure 5

Effect of altering age structure on the net population energy use (in megawatts)
of the harbor seal ( Phoca vitulina ) population in the San Juan Islands and
eastern bays during 2007-08. Base=basic model with age structure from 1970s;
for the other graph lines, 25, 50, and 100 correspond to percent increases in
numbers of adults in population. Solid circles indicate medians, boxes enclose
the interquartiles, vertical dashed lines represent 1.5* the interquartile range,
and open circles indicate outliers.

Puget Sound Rockfish (S. empha-
eus ; the smallest of the rockfish at
~40 g), they could have consumed
more than 2 million individuals,
a number that presumably can
affect the rockfish population. It
seems clear that prey that consti-
tute even a minor proportion of
harbor seal diet may be affected
by predation, if such predation
increases their natural mortality
rates. Therefore, harbor seal inter-
actions with prey species of man-
agement concern merit further at-
tention, and modeling prey vulner-
ability to predation will require a
multidisciplinary approach.

Consumption estimates calcu-
lated in this study illustrate the
energetic importance of herring
and salmonids to harbor seals in
the San Juan Islands and the im-
portance of considering predation
effects on prey groups from mul-
tiple perspectives. In this study,
we contrasted high consumption
rates of prey species (salmonids
and herring) with less commonly
consumed prey groups, such as
rockfish, to illustrate the capacity
of models to test assumptions in
situations with high uncertainty
in input values, such as percent-
age by wet weight of rockfish in
seal diet. We provided evidence
that the apparently minor con-
tribution of rockfish biomass to
harbor seal diet may neverthe-
less indicate that large numbers
of individuals are being consumed, but the number con-
sumed is highly dependent on the species and age of
prey. Harbor seals consumed large amounts of the more
commonly consumed species, such as herring, even at
the lower estimated limits of consumption rates calcu-
lated in this study. Many herring stocks have under-
gone critical declines, and there is concern that pinni-
ped predation may have increased the natural mortal-
ity rate of herring in some areas (Musick et al., 2000),
although it is acknowledged that there are likely many
factors that contributed to the decline of herring (Stout
et al., 2001). Spawner biomass of herring for the north-
ern Puget Sound, an index of population abundance,
remained low through the study period,4 yet herring
has been identified as one of the top prey species of

4 Stick, K. C., and A. Lundquist. 2009. 2008 Washington

State herring stock status report. Stock Status Report FPA
09-05, 111 p. Washington Department of Fish & Wildlife,
Fish Program, Fish Management Division. [Available from
http://wdfw.wa.gov/publications.]

harbor seals in a San Juan Islands diet study since
2005 (Lance et al., 2012).

Like herring populations, salmonid populations have
undergone serious declines, and there is also concern
that pinnipeds may affect salmonid recovery (NMFS,
1997; Wright et al., 2007). Five species of salmonid oc-
cur in the study area and all have been documented
in harbor seal diet. Chinook Salmon (Oncorhynchus
tshawytscha ) was the only salmonid species confirmed
by the scat samples of our study; however, Pink Salm-
on are the salmonid species most commonly consumed
by harbor seals in the San Juan Islands (Lance et al.,
2012). Pink Salmon runs in the northern Puget Sound
were relatively abundant during the study period, but
abundance indices indicate Chinook Salmon remained
at critically depressed levels through 2008. 5 Salmonid

5 Salmonid stock inventory (SaSi). Washington Department
of Fish & Wildlife. [Available from http://wdfw.wa.gov/
mapping/salmonscape/index.html.]

Fishery Bulletin 111(1)

abundance along the west coast of North America is
linked to cooler than average ocean water tempera-
tures. The high salmonid consumption values in our
study may reflect higher than average salmonid abun-
dance driven by changes (warm phase through 2005,
neutral-to-cold phase after 2005) caused by the Pacific
Decadal Oscillation since approximately 2006 (Mantua
et ah, 1997). We suggest that the overall high consump-
tion rates of herring and salmonids (along with great
uncertainty in these consumption rates) by harbor
seals found in this study indicate that harbor seal con-
sumption should be examined on broader spatial and
historical scales to further explore the potential effect
of harbor seal consumption on prey groups.

Conclusions

Harbor seals are a large-bodied and abundant predator
whose consumption of depressed fish populations may
conflict with regional fish recovery goals. This study
established baseline consumption estimates for major
prey groups and highlighted the potential range of
consumption for the most common minor prey groups
in the San Juan Islands region. Although there was
great uncertainty in quantitative diet composition of
harbor seals, salmonids and herring clearly constitut-
ed the majority of biomass consumed during the study
period. Rockfish, one of the fish groups for which ma-
rine reserves are being planned, were among the minor
prey groups consumed. The relative importance of prey
items in harbor seal diet can be tested with future diet
data in a model framework that incorporates estimates
of uncertainty, similar to the one used in this study. Re-
lation of consumption rates to mortality rates for any
of the depressed fish species will require a multidisci-
plinary approach because of the complexity of harbor
seal diet.

In this study, we explored how changes in the age
structure of the harbor seal population influenced con-
sumption values and found age structure to have rela-
tively little influence. However, more work is needed to
establish the current age structure of the harbor seal
population because it may have significant implications
for prediction of harbor seal body size, which strongly
controlled model predictions. In further modeling exer-
cises, the variables that most heavily influenced con-
sumption values (body size of seals and quantitative
diet composition) should be considered as some of the
most important factors for prediction of consumption
and food requirements of harbor seals in the study area.

Acknowledgments

We would like to thank N. Schwarck, G. McKeen,
and members of the Marine Behavior and Ecology
Laboratory of the Western Washington University for
logistical support in field work. The lead author was

supported through National Science Foundation Grant
No. 0550443 awarded to A. Acevedo-Gutierrez, a re-
search assistantship from Padilla Bay National Es-
tuarine Research Reserve, and the Office of Research
and Sponsored Programs and the Biology Department
at Western Washington University. Suggestions from 3
anonymous reviewers substantially improved previous
versions of this manuscript.

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Appendix

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tion. Pup numbers did not change from the basic age
structure. +25%, 50%, and 100% correspond to percent
increases in numbers of adults in the population.

Seal age class

Basic +25%

Basic +50% structure

Basic +100% structure

Adult female

1485-1673

1782-2007

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Adult male

339-393

407-471

542-628

Subadult female

1997-2572

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Subadult male

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2316-3200

2170-3054

Quantification and reduction of unobserved
mortality rates for snow, southern Tanner, and
red king crabs (Chionoecetes opilio, G bairdi,
and Paralithodes camtschaticus ) after
encounters with trawls on the seafloor

Craig S. Rose (contact author)1
Carwyn F. Hammond1
Allan W. Stoner2
J. Eric Munk3
John R. Gauvin4

Email address for contact author: craig. rose@noaa gov

Abstract — Unobserved mortalities
of nontarget species are among the
most troubling and difficult issues
associated with fishing, especially
when those species are targeted
by other fisheries. Of such concern
are mortalities of crab species of
the Bering Sea, which are exposed
to bottom trawling from groundfish
fisheries. Uncertainty in the man-
agement of these fisheries has been
exacerbated by unknown mortality
rates for crabs struck by trawls. In
this study, the mortality rates for 3
species of commercially important
crabs — red king crab, ( Paralithodes
camtschaticus), snow crab ( Chion-
oecetes opilio ) and southern Tanner
crab (C. bairdi) — that encounter dif-
ferent components of bottom trawls
were estimated through capture of
crabs behind the bottom trawl and
by evaluation of immediate and de-
layed mortalities. We used a reflex
action mortality predictor to predict
delayed mortalities. Estimated mor-
tality rates varied by species and by
the part of the trawl gear encoun-
tered. Red king crab were more vul-
nerable than snow or southern Tan-
ner crabs. Crabs were more likely
to die after encountering the foot-
rope than the sweeps of the trawl,
and higher death rates were noted
for the side sections of the footrope
than for the center footrope section.
Mortality rates were <16%, except
for red king crab that passed under
the trawl wings (32%). Herding de-
vices (sweeps) can expand greatly
the area of seafloor from which flat-
fishes are captured, and they subject
crabs in that additional area to low-
er (4-9%) mortality rates. Raising
sweep cables off of the seafloor re-
duced red king crab mortality rates
from 10% to 4%.

Manuscript submitted 7 March 2012.
Manuscript accepted 9 November 2012.
Fish. Bull. 111:42-53 (2013).
doi:10.7755/FB. 11 1.1.4

The views and opinions expressed
or implied in this article are those of the
author (or authors) and do not necessar-
ily reflect the position of the National
Marine Fisheries Service, NOAA.

’ Conservation Engineering Program
Alaska Fisheries Science Center
National Marine Fisheries Service. NOAA
7600 Sand Point Way NE
Seattle, Washington 98115
2 Fisheries Behavioral Ecology Program
Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
2030 Marine Science Drive
Newport, Oregon 97365

The potential for unobserved mor-
tality of crabs that encounter bot-
tom trawls but are not captured has
long been a concern for the manage-
ment of groundfish fisheries in the
Bering Sea (Witherell and Pautzke,
1997; Witherell and Woodby, 2005).
Fisheries on the crab and groundfish
stocks of the wide continental shelf
of the eastern Bering Sea have made
Dutch Harbor, the principal port for
that area, the highest port by ton-
nage in the United States and 1 of
the 2 highest ports by dollar value
for more than 20 years.1 Three ma-
jor crab species — red king crab ( Para-
lithodes camtschaticus), snow crab
( Chionoecetes opilio), and southern
Tanner crab (C. bairdi) — are targets
of large commercial fisheries (Otto,
1990). The 2 Chionoecetes species

1 U.S. Department of Commerce. 1995-
2011. Fisheries of the United States
1995 (1996, ...,2011). Current Fishery

Statistics 1995 ( 1996, ...,2011). U.S.
Dep. Commer., NOAA, Natl. Mar. Fish.

Serv., Fisheries Statistics Division, Silver
Spring, MD. [Available from http://

w w w. st.nmfs.noaa.gov/commercial-
fisheries/fus/index. ]

3 Shellfish Assessment Program
Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
301 Research Court
Kodiak, Alaska 99615

have similar low, flat body shapes
and inhabit deeper water with mud-
dier substrates than that of the red
king crab, which has a thicker body
and inhabits shallower, sandier areas
(Jadamec et al., 1999; Donaldson and
Byersdorfer, 2005). Groundfish spe-
cies, particularly gadids and flatfishes
are targeted with trawls. Overlaps be-
tween crab habitat and areas trawled
by groundfish fisheries can result in
some mortality for crabs that encoun-
ter groundfish trawls, either through
capture and discard (bycatch) or as
unobserved mortality of crabs that
remain on the seafloor (Witherell and
Pautzke, 1997).

The current management mea-
sures to control and reduce bycatch
of the major Bering Sea crab spe-
cies in Alaska groundfish fisheries
include extensive year-round trawl
closure areas (Fig. 1) and bycatch
limits outside these areas. The year-
round closure areas were established
to protect areas of known concentra-
tions of female and juvenile crabs.
Armstrong et al. (1993) and Witherell
and Pautzke (1997) cited unobserved
trawl-induced mortality, along with

4 Alaska Seafood Cooperative
4241 21s1 Avenue W, Suite 302
Seattle, Washington 98199

Rose et a! : Mortality rates for Chionoecetes opilio, C. bairdi, and Parahthodes camtschaticus after trawls on the seafloor

1 75°W 170°W 165°W 16CTW

Figure 1

Sampling locations for snow ( Chionoecetes opilio) (S) and southern Tanner (C. bairdi) (T) crabs in 2008 and
red king crab (Paralithodes camtschaticus) in 2009 (RK), during our study of unobserved mortality rates from
bottom trawling. Bottom trawl area closures (shaded) and depth contours are included for reference.

possible habitat degradation, as principal reasons for
the establishment of these closures. Crab bycatch lim-
its (on the basis of numbers caught) have also trig-
gered additional closures if seasonal, species-specific
(and sometimes area-specific) limits are reached. These
bycatch numbers are obtained from onboard fishery ob-
servers on an in-season basis (Withered et al., 2000).
The species-specific crab bycatch limits (in estimated
numbers of crabs brought aboard) are thought to have
a biologically insignificant effect on the different crab
populations because these limits have represented as
little as 0.113% of the abundance index for snow crab
and 0. 5-1.0% of abundance for southern Tanner crab
and red king crab (Withered and Pautzke, 1997).

Critics of the existing framework of measures for
crab bycatch management have from time to time as-
serted that, although bycatch limits appear to be suffi-
ciently conservative, bycatch represents only a fraction
of the actual mortality of different crab species caused
by groundfish fisheries. Citing an unpublished tech-
nical paper, Thompson (1990) estimated actual trawl
gear mortality for king crabs to be “10 to 15 times the
number of crabs that are caught in the net (and esti-

mated by [National Marine Fisheries Service] observ-
ers).” These concerns cannot be adequately evaluated
without addition of valid estimates of the unobserved
mortality rates for these crab species to the assess-
ments of bycatch and discard. Some crab researchers in
Alaska (Murphy et al., 1994) also have underscored the
need for additional research on injury rates and unob-
served or unaccounted for mortality from both direct-
ed crab fisheries and groundfish trawl fisheries. Dew
and McConnaughey (2005) concluded that excessively
high mortality rates on male Bristol Bay red king crab
from the directed fishery and unaccounted for mortal-
ity of females from the groundfish fisheries explain the
downward population trajectory of this crab species
through the late 1970s and early 1980s better than
does the more accepted scientific hypothesis that the
low population levels of red king crab were explained
by unfavorable climate conditions.

Worldwide, the recognition of unobserved mortali-
ties as a potentially significant element by the fishing
industry and by fishery managers has increased the
number of studies that have addressed such mortali-
ties and the range of methods used in their estimation.

Fishery Bulletin 1 1 1 (1)

Broadhurst et al. (2006) provided a thorough review
of such studies. Although a great number of studies
estimated mortalities of discarded catch, others dealt
with mortalities of escaping animals not brought
aboard the fishing vessel. Broadhurst et al. (2006)
noted that studies of escaping animals, almost exclu-
sively fishes, lately have emphasized methods where
escaping animals are recaptured in cages that are then
detached from the fishing gear while still at fishing
depths. Those cages then are moved slowly to shallow-
er depths, where they are maintained by divers long
enough to assess delayed mortalities. Earlier methods
involved capture of escaping animals in auxiliary nets
before they were brought aboard and held long enough
to evaluate mortality rates. However, stress and injury
from recapture and extended towing and holding times
could have easily masked or exacerbated the effects of
the escape process, particularly for animals vulnerable
to skin abrasion damage. More recent methods retain
the experimental subjects in an environment closer to
what they would experience after actual escape. The
cost of these gains is that each collection of affected
animals requires an extended series of activities that
are time consuming and labor and resource intensive.
These time and resource demands greatly restrict the
number of experimental samples that can be collected
and held and, hence, the number of experimental fac-
tors that can be addressed.

As an experimental subject, crab are significantly
different from fish for which the in situ capture, trans-
fer, and holding methods were developed. Exoskeletons
protect crabs from the type of abrasion to which fish
are particularly susceptible during net capture and
crowded holding. As a trawl net approaches, fish con-
tinue swimming, often to exhaustion, to avoid contact
with the net and other animals, but crab, being much
slower, can flee only briefly before being overrun (Rose,
1995).

Another difference is how crabs interact with fishing
gear. Broadhurst et al. (2006), describing research on
fishes, noted, “Because most experiments have quanti-
fied escape mortality at the codend, the potential for
mortalities as a result of collisions and escape through
other parts of the gear have largely been ignored.” Be-
cause of the sizes and behavior of Bering Sea crabs and
the configurations of Bering Sea bottom trawls, most
crabs escape under the forward parts of trawl systems,
and interactions typically last only a few seconds as
the crab passes the components of the net that directly
contact the seafloor. Rose (1999) studied crab mortali-
ties after such escapes under the forward sections of
bottom trawls through assessment of visible injuries to
red king crab that resulted from passes of crabs under
different trawl footrope designs. The crabs were recap-
tured in an auxiliary net fished behind the main foot-
ropes. A control footrope, suspended with floats to allow
crabs to pass beneath with minimal damage, also was
used. A low rate of injuries for control crabs indicated
that recapture of crabs to bring them aboard could be

done without greatly increasing injury to crabs. The
principal limitations of that study were the following:
1) crabs were not held beyond the initial assessment of
injuries to observe delayed mortality; and 2) observa-
tions were limited to crabs that passed under the cen-
ter section of the footrope, a small portion of the area
swept during trawling.

Studying mortality of crabs discarded from trawl
catches, Stevens (1990) effectively applied a strategy in
which all subject crabs were assessed for selected con-
dition attributes and a sample was held long enough to
relate those attributes to delayed mortality. Since that
study, such methods have been expanded and improved.
Davis and Ottmar (2006) used assessment of a range of
reflexes of Pacific Halibut ( Hippoglossus stenolepis) to
build a predictor of delayed mortality, the Reflex Action
Mortality Predictor (RAMP). In a pilot study for this
project, Stoner et al. (2008) found the RAMP technique
effective for estimation of delayed mortalities for snow
and southern Tanner crabs.

Our research addressed unobserved mortality rates
for 3 principal commercial crab species of the Bering
Sea: red king crab, southern Tanner crab, and snow
crab. We improved methods for collection of crabs im-
mediately after trawl encounters as used by Rose
(1999) and applied the RAMP technique as described
by Stoner et al. (2008) to assess the mortality prob-
abilities for crabs that passed under the sweeps, wings,
and central footrope of a commercial groundfish trawl.
Raised sweeps, which reduce seafloor contact yet main-
tain herding of flatfishes (Rose et al., 2010), also were
used at the red king crab sites to evaluate whether
they would reduce crab mortality rates. Observations of
control animals collected with identical recapture nets
but no trawl encounter were used to adjust observed
mortality rates for effects of capture and handling.

Materials and methods

A pilot study conducted in 2007 evaluated the RAMP
and developed and tested techniques for 1) recaptur-
ing crabs after encounters with trawl components, 2)
handling and assessing those crabs on deck, 3) holding
selected crabs to determine their survival over several
days, and 4) using the RAMP to estimate the mortal-
ity probability of each crab (Stoner et al., 2008). Our
study followed those methods closely, and the following
description summarizes them and highlights all modi-
fications made to the methods of the pilot study for our
later study.

Experimental tows for southern Tanner and snow
crabs were made in August of 2008 -111 km (-60 nmi)
east of Saint Paul Island (Fig. 1). All tows included a
mix of both species. Red king crab tows were made in
August of 2009 at 2 sites in Bristol Bay, about 22 km
(12 nmi) west of Amak Island and ~65 km ( —35 nmi)
northwest of Port Moller. Operations were conducted
aboard the FV Pacific Explorer, a 47-m, 1800-hp com-

Rose et al.: Mortality rates for Chionoecetes opilio, C. bairdi, and Parahthodes camtschaticus after trawls on the seafloor

mercial trawler equipped with a trawl configured simi-
larly to the one used by many of the bottom trawlers
that are used in Bering Sea groundfish fisheries. The
2-seam trawl net had a 36.0-m headrope and a 54.6-
m footrope, which was made of 19-mm-long link -t-steel
chain and equipped with bobbins 46 cm in diameter.
The ~70-cm sections between bobbins were covered
with 2 steel-chain toggles, weighing 6.4 kg each, rubber
disks of 4-20 cm, and one 5-kg circular weight. Wing
extensions, installed ahead of the forward ends of the
footrope, were made of 20-em disks strung over 19-mm-
long link chain. The cables (sweeps) that ran forward
from the trawl to the doors were made of 48-mm combi-

Figure 2

Diagram of the trawl net (not to scale) used in our
study of unobserved mortality rates for snow crab (Chi-
onoecetes opilio ), southern Tanner crab (C. bairdi), and
red king crab (Paralithodes camtschaticus), showing po-
sitions of recapture nets designed to retain crabs after
contact with various trawl components. No more than 2
of these nets were fished during the same tow, and the
control net always was fished separately. Illustration
by Kama McKinney.

nation rope, a product made of both steel and synthetic
materials and used by most Bering Sea flatfish trawl-
ers. The red king crab study included tests of sweeps
equipped with disk clusters spaced at 14-m intervals
and raised the combination rope 7.5 cm above the sea-
floor. Rose et al. (2010) found that such raised sweeps
reduced seafloor contact while still herding groundfish
effectively.

Crabs were captured immediately after contact with
the components of the main trawl by small recapture
nets fished behind these 3 gear regions: 1) at center of
the footrope, 2) at the footrope wings (including their
extensions), and 3) behind the sweeps (Fig. 2). These
recapture nets were small trawls designed to minimize
fish capture and maximize crab capture. The recapture
nets used behind the wings and sweeps had unequal
bridle lengths, which were adjusted until water passed
perpendicular to the center of the headrope of each net,
as observed with an underwater camera. An identical
recapture net was fished ahead of the trawl as a con-
trol to assess damage and mortality due to handling.
A rope between the sweeps ahead of the control net
was necessary to avoid overspreading. That rope was
raised 23 cm off the bottom of the seafloor to avoid
affecting crabs. Only 1 recapture net was used at a
time during every tow in 2008 to ensure that nets did
not tangle when launched. Experience allowed us to
expand to 2 nets (1 sweep and 1 footrope) at a time
during some tows in 2009; however the control net
was always fished alone because it would potentially
have damaged crabs before they reached the footrope.
The time required to change positions of the recapture
nets on the trawls precluded alternating them between
trawl components on a tow-by-tow basis; therefore, all
tows that addressed each gear component were done
in 1 or 2 blocks of sequential tows. To maximize hold-
ing times for crabs affected by the trawl, the control
tows were done last. The codend of the main trawl was
not closed because the tows were too short to represent
typical mortality due to capture by the trawl, and catch
volume was considered unlikely to significantly affect
sweep and footrope mortality.

Towing speeds were 3-3.5 kn. Tow lengths were kept
short to minimize damage to crabs from the recapture
process but varied from 7 to 25 min to capture suf-
ficient numbers of crabs. These speeds reflect industry
practice, and, although commercial tows last much lon-
ger, the shorter lengths of the tows in our study did not
change the relatively brief interactions between indi-
vidual crabs and the ground contact components of the
trawl. The main trawl was monitored with trawl sonar,
which would detect any significant net asymmetry, and
video observations of ground-gear components were
used to check for atypical contact with the seafloor.

Tow sites (Fig. 1) were selected to provide adequate
numbers of the targeted crab species during relatively
short tows. Both snow and southern Tanner crabs were
sufficiently abundant to be studied at a single site in
2008, but red king crab research in 2009 required an

additional site. Although one of the red king crab sites
was in a closed area, both such sites were similar in
depth and substrate to areas where Bering Sea ground-
fish fisheries encounter that species. If <7 individuals
of a species were captured in one of the nets, crab as-
sessments for that species were not used in the analy-
sis. Tow tracks were arranged to minimize crossing the
trawl tracks of previous tows and to keep such cross-
ings close to perpendicular, to limit areas of overlap.
Track crossings made up <1% of study tows. We also
maximized the time elapsed between such crossings
(always more than 1 day) so that immediate mortali-
ties from earlier exposure would be easily recognizable.

Upon recovery, the recapture codend was opened
and all Chionoecetes crabs in 2008, or red king crab
in 2009, were removed and sorted by species and sex
(Jadamec et ah, 1999). To use our project’s resources
most efficiently, we used a 2-stage sampling procedure
in which all of the subject animals were assessed im-
mediately for selected condition attributes and a small
sample of those subjects was held long enough to relate
those attributes to eventual mortality rates.

All Chionoecetes crabs were assessed for the pres-
ence of the 6 reflex responses described in Stoner et
al. (2008): leg flare, leg retractions, chela closure, eye
retraction, mouth closure, and kick. For red king crab,
the leg retraction reflex test was replaced with a test
of antennae movement response. Antennae, minuscule
in snow or southern Tanner crabs, were quite active
and responsive for red king crab, providing a more sen-
sitive reflex response. As in the Stoner et al. (2008)
eye and mouth tests, the antennae were manipulated
and responsive movements were recorded as a positive
response.

Assessments were limited to presence or absence
of reflexes, there was no evaluation of reflex strength.
This simplification allowed for rapid assessments and
reduced any ambiguity or observer variation (Stoner
et al., 2008). Initial scans separated unimpaired crabs
from those crabs with an injury or at least one reflex
missing. Missing reflexes and any injuries were record-
ed. Reflex scores indicated the number of impairments;
a score of 0 indicated an unimpaired crab, and a score
of 6 indicated a moribund crab with no reflexes pres-
ent. Sex and shell condition for all crabs and carapace
width for the 2 Chionoecetes spp. and carapace length
for red king crab were recorded. Shell conditions (Jada-
mec et ah, 1999) included soft shell (shell soft and pli-
able), new hard shell (firm to hard shell that lacked
wear or encrustment), old shell (wear and encrustment
present) and very old shell (extensive signs of shell
wear and encrustment). Catch processing generally
took less than 15 min, and crabs were held in seawater
when they were not being processed.

For each crab species, specimens representing each
reflex score were tagged and held to estimate the re-
lationship between reflex score and delayed mortality.
Collections of snow and Tanner crabs in 2008 supple-
mented the RAMP results of the 2007 pilot study. Selec-

Fishery Bulletin 1 1 1 (1)

tion of crabs for holding emphasized those with reflex
scores from 1 to 5, categories that had lower observed
numbers in the earlier study. Holding procedures were
identical to those of Stoner et al. (2008), with -900 L
on-deck tanks, supplied with seawater flow >20 L/min.
Crabs were assessed daily, and those crabs that died
were recorded and removed.

Early in the 2009 work, it became apparent that
many of the red king crabs with no reflex impairments
but apparent injuries were dying. This outcome indi-
cated that fatally injured red king crab were not as
likely to lose reflexes as were the Chionoecetes crabs
and led us to adapt the full RAMP approach so that
all red king crab that had either a missing reflex or an
apparent injury were held. To ascertain how commonly
fatal damage was completely hidden, 367 uninjured
crabs displaying all reflexes were held.

Our estimator of the probability of mortality for
crabs with each reflex score was the proportion of held
crabs with that score that died for each species. To
estimate overall mortalities, the proportions of crabs
in each reflex class were multiplied by the probability
mortality of that reflex class and summed (Eq. 1):

mc = Sr=0 to 6^r * (1)

where mc = the mortality estimate for a species in
catch c;

mr = the mortality probability from the RAMP
for that species for reflex score r ; and

prc = the proportion of that species from catch c
with reflex score r.

For red king crab, this formula was modified to use
the actual mortality outcomes of the injured and reflex-
impaired crabs, all of which were held for observation
(Eq. 2):

mc = (mu * puc) + mjNic)*pic), (2)

where DIC = the number of impaired or injured crabs
that died from catch c;

Nic = the number of injured or impaired crabs in
catch c; and

m and p have the same meaning as in Equation
1, except that i refers to injured or im-
paired crabs and u refers to those crabs
that were uninjured with all reflexes
present.

To estimate mortality for crabs that encountered a por-
tion of the trawl, mortalities (mc) for all catches from
recapture nets installed in that area were averaged
and weighted for the number of crabs in each catch.

To correct mortality estimates for handling dam-
age, we assumed that gear and handling mortalities
were independent and sequential. That is, where both
processes occurred together in the recapture catches
(mg+h)> the Sear mortality (mg) occurred first and only
those crabs not killed by the gear (1 - mg) were vulner-
able to handling mortality (mh, estimated as the mor-

Rose et a! : Mortality rates for Chionoecetes opilio, C. bairdi, and Paralithodes camtschaticus after trawls on the seafloor

tality rate from the control net), resulting in Equation
3:

mg+h = mg + ((1 - mg) * mh). (3)

This equation was solved for mg, resulting in Equa-
tion 4:

mg = (mg+h _ mh) / (1 - m\)- (4)

If the cumulative effects of gear impact and handling
caused additional mortalities, this estimator would at-
tribute those mortalities to gear effects, resulting in
overestimated gear-caused mortalities.

To account for variability due to the combination of
reflex score assessments, RAMP prediction of mortality,
and corrections for handling mortality, a randomization
approach was used for hypothesis testing and estima-
tion of confidence intervals. A model of the experiment
was implemented with the Resampling Stats add-in for
Microsoft Excel (Resampling Statistics, Inc., Arlington,
VA., http://www.resample.com).2 RAMP estimators were
regenerated for each trial by making random binary
draws for each reflex score category (Urn procedure) and
by using the sample size and mortality probability for
that score from the experiment. New probabilities, cal-
culated from that draw, were then used in the mortality
estimation procedure for that trial.

In resampling from the reflex assessments, we used
each catch as our sample unit, choosing not to assume
that individual crabs within a catch have independent
mortality probabilities. To test null hypotheses that 2
groups of catches (e.g., catches from recapture nets at
different trawl locations) actually came from the same
population, the groups were combined and random draws
were made from that combination, without replacement
(Shuffle procedure), filling 2 new samples corresponding
in number to the samples from the original experiment.
A mortality estimate was generated for each trial by
using the RAMP and assessment draws. For each test,
5000 trials were generated, and the proportion of those
trials with differences greater than the observed esti-
mate indicated the probability that our result occurred
from a random process in which the mortality rates for
both groups were equal.

Comparisons were made between catches from each
of the 3 gear areas (center footrope, footrope wings and
extension, and sweeps) and the control catches to deter-
mine whether those trawl encounters caused significant
mortality. Subsequent tests were made for differences
between the 2 footrope areas and between the sweeps
and the combined footrope areas.

Confidence intervals were generated by a similar pro-
cess, except that samples of the assessment catches for
each group, including control catches, were randomly
selected with replacement from the actual catches for
that group. Handling corrections were applied to mortal-

2 Mention of trade names or commercial companies is for
identification purposes only and does not imply endorsement
by the National Marine Fisheries Service, NOAA.

ity estimates generated for each gear component, on the
basis of the control estimate from each trial. Confidence
intervals (95%) were generated by identification of the
highest 2.5% and the lowest 2.5% of the estimates from
5000 trials.

Effects of sex, size, species, and shell condition on
mortality rates were examined with logistic regression
after the effects of each gear component were accounted
for. Mortality was initially regressed against gear com-
ponents, and the effects of these other factors were then
tested against the residual variation. Because logistic
regression requires binomial outcomes, specific RAMP
probabilities of death could not be directly applied.
Where direct observations from holding were not avail-
able, crab mortality outcomes were scored on the basis
of whether RAMP probabilities for their mortality were
less or greater than 50%. Significant effects also were
tested for interactions of each significant factor with
gear area.

Results

The 159 total tows included 17-21 tows for each spe-
cies at each recapture position. Between 154 and 991
crabs from each of the 6 combinations of species and
sex were assessed after their capture behind each gear
component and in the control position, and a substan-
tial range of crab sizes were recorded within each com-
bination (Table 1).

Augmentation of the Stoner et al. (2008) RAMP re-
lationships for the 2 Chionoecetes species by holding
additional crabs in 2008 had only minor effects on mor-
tality rate estimates (Table 2) other than to reduce un-
certainty due to larger sample sizes (Hammond, 2009).

For all 3 species, injuries varied widely in affected
body part, type of damage, and severity, and were cor-
related with both reflex score and mortality rate. Of
the red king crab with at least one missing reflex (re-
flex scores of 1 to 6), 96% also had observable inju-
ries, as opposed to only 5% of those crab with no miss-
ing reflexes (reflex score of 0). Crabs of all 3 species
never survived removal of their abdomen or carapace,
although autotomized legs (dropped off after injury)
rarely caused fatalities. Crabs with either leg damage
or carapace cracks normally survived, depending on
extent, severity, and combination with other injuries.

Of the 485 surviving red king crab released at the
end of this study, 482 had all reflexes present upon re-
lease, including all 14 that initially were missing at
least one reflex. The 3 crab that were missing a re-
flex upon release were all missing the eye reflex, had
been held for 9 or 10 days, and had significant injuries,
including carapace cracks. Although 25% (122) of the
surviving crab had detectable injuries, their survival
through the holding period and vigorous state condi-
tion upon release indicated a low likelihood of signifi-
cant later mortalities.

Fishery Bulletin 11 HI)

Table t

Number of crabs assessed and size ranges for each species and sex combination after they were captured behind 3 sections
of bottom trawl gear, or with a control net. Size ranges, carapace width for snow ( Chionoecetes opilio) and southern Tanner
crabs (C. bairdi) and carapace length for red king crab ( Paralithodes camtschaticus ) are given in millimeters. The three gear
components were the footrope wings or extensions, the center of the footrope, and the sweep. For red king crab only, a fourth
component was added, a sweep raised off of the seafloor (Rose et al., 2010).

Snow crab Southern Tanner crab Red king crab

Male

Female

Male

Female

Male

Female

No. Size range

Control

467

50-130

154

54-92

567

62-148

157

56-100

448

53-183

433

82-145

Sweep

407

47-126

218

52-93

281

60-147

518

59-98

370

64-188

226

63-150

Raised sweep

321

63-179

278

68-148

Footrope center

991

46-140

353

50-85

677

50-145

756

49-102

753

69-189

393

68-164

Footrope wing

696

48-130

540

50-110

288

51-143

494

52-97

203

61-167

263

70-156

Most southern Tanner and snow crabs captured be-
hind the main trawl components had all reflexes pres-
ent (76-93% reflex score of 0, Fig. 3), and the next
most frequent category was dead crabs (reflex score of
6, no reflexes present) upon capture (2-17%). Similarly,
a substantial majority (66-83%) of red king crab cap-
tured behind the trawl gear was uninjured and had all
reflexes present. Very few of these animals died during
holding. Of the red king crab, 6% were dead upon cap-
ture, making up 71% of mortalities. Therefore, nearly
all of the observed crabs were either extremely likely to
survive or moribund; relatively few crabs displayed an
intermediate condition where the holding and RAMP
results were critical to estimation of their probability
of mortality.

For both red king and southern Tanner crabs, the
control net yielded 97% uninjured crab with all reflexes
present and no crabs were dead upon capture. Snow
crab had more immediate mortalities in the control net
(2%) and only 88% had all reflexes present. Mortality
estimates for crabs from the control nets (snow crab
7.1%, southern Tanner crab 8.5%, and red king crab
2.9%) were significantly lower than the estimates for
crabs captured behind trawl components.

Estimates of the rates of mortality due to contact
with the trawl gear, adjusted for capture and handling,
were below 16% (Fig. 4), with the exception of red king
crab that encountered the wing section of the footrope,
for which mortality was estimated at 31%. Overall,
estimated mortality rates for all 3 species were sig-

Table 2

Number of crabs held to observe delayed mortality and resulting mortality rates by reflex score (number of
reflexes missing; 6 reflexes were assessed) and species for snow crab ( Chionoecetes opilio), southern Tanner
crab (C. bairdi), and red king crab (Paralithodes camtschaticus). Crabs from Stoner et al. (2008) were included
for both Chionoecetes species.

Number of reflexes missing

None

missing

None
missing +
injury *

All 6
missing

Snow crab

500

—

Southern Tanner Crab

375

—

Red king crab

367

145

Mortality rate (%)

Snow crab

1.4%

—

20.5%

30.0%

43.9%

75.9%

88.1%

100.0%

Southern Tanner Crab

7.2%

—

32.1%

51.4%

86.5%

91.5%

92.1%

100.0%

Red king crab

1.9%

23.4%

81.6%

94.5%

98.3%

100.0%

* This category was used only for red king crab.

Rose et al Mortality rates for Ch/onoecetes opiiio, C. bairdi, and Parahthodes camtschaticus after trawls on the seafloor

□ No reflexes missing

a No reflexes missing + injury (RKC)

□ Some reflexes missing (1-5)
m All 6 reflexes missing

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Snow crab
Control
Sweep
Footrope center
Footrope wing

Tanner crab
Control
Sweep
Footrope center
Footrope wing

Red king crab
Control
Raised sweep
Sweep
Footrope center
Footrope wing

t: .i it

n=m

Figure 3

Percentage of crabs that displayed a range of reflex states in our study of unobserved mortality rates
for snow crab (Chionoecetes opiiio), southern Tanner crab (C. bairdi), and red king crab (Paralithodes
camtschaticus) . Reflex states were assigned on the basis of the number of reflexes that were missing;
6 reflexes were assessed. Crabs were captured after they contacted 1 of the 3 components of a bottom
trawl representative of the gear used in Bering Sea bottom trawl fisheries — the center of the footrope,
the footrope wings or extensions, or the sweep — or, for red king crab only, a sweep raised off of the
seafloor (Rose et al., 2010). Crabs were captured with no gear contact during control tows. Injured red
king crab with no missing reflexes were categorized separately. RKC = red king crab.

nificantly lower for crabs that encountered the sweeps
than for those crabs that encountered the footrope and
were higher for those crabs that encountered the wing
portion of the footrope as opposed to the center foo-
trope. Although the mortality rates for the southern
Tanner and snow crabs were similar, both had lower
mortality rates than did the red king crab for all trawl
components. Raising the sweeps with widely spaced
disk clusters reduced red king crab mortality from 10%
to 4%.

Holding only samples of the large numbers of crabs
with no missing reflexes (no missing reflexes and unin-
jured for red king crab) greatly reduced the number of
held crabs and produced minimal effects on precision
of the mortality estimates. For example, the confidence
interval estimation process was run with a sample size
of 2581, representing all such red king crab observed,
instead of the 367 crabs actually held. The resulting

confidence range (high limit to low limit) for foot-
rope wing mortality was reduced only from 14.25% to
13.99% by holding 7 times as many crabs. Confidence
ranges for footrope center and sweep mortalities were
reduced even less (3.53% to 3.50% and 5.98% to 5.95%,
respectively).

Logistic regression was used to examine whether
mortality rates varied by species, sex, size, and shell
condition, after the effects of gear were removed. Near-
ly all crabs had either a new hard shell or old shell.
For southern Tanner and snow crabs, marginally signif-
icant effects were detected between species, sexes, and
sizes. When the mean effects across the combinations
of those factors were examined, it was apparent that
most of those effects were the result of higher mortali-
ties for snow crab with carapace widths >95 mm; those
large snow crab were nearly all males. Large snow crab
were approximately twice as likely to die as smaller

Fishery Bulletin 1 1 1 (1)

40%

35%

30%

25%

20%

15%

10%

□ Snow crab
■ Tanner crab
S Red king crab
0 Red king crab (raised sweep)

Footrope wing

Footrope center

Sweep

Figure 4

Estimates and 95% confidence intervals of rates of mortality for snow crab (Chionoecetes
opilio), southern Tanner crab (C. bairdi ), and red king crab ( Paralithodes camtschaticus
that resulted from contact with 1 of 3 different components of a bottom trawl represen-
tative of the gear used bottom trawl fisheries in the Bering Sea — the footrope wings or
extensions, the center of the footrope, or the sweep — and, for red king crab only, a sweep
raised off of the seafloor (Rose et al., 2010).

snow crab or as any size of southern Tanner crab, and
this difference persisted across all gear components
and control catches.

Large red king crab had higher mortality than
smaller king crabs (PcO.OOl), although this effect ex-
plained <1% of the variability in mortality, compared
with 12% for the difference between gear components.
The interaction between crab size and gear component
was not statistically significant; therefore, there was no
indication that this difference in vulnerability between
sizes varied between gear components. Mortality of red
king crab did not vary significantly between sexes or
between new-hard-shell and old-shell crab. Although
the percentage of mortalities was high for soft-shell
crab (4 of 5 died) and crab with very old shells (3 of 5
died), those shell types were too rare for a statistical
validation of difference.

Discussion

Our study provides the first reliable estimates of mor-
tality rates following noncapture (not bycatch or dis-
card) bottom trawl encounters for 3 commercially im-
portant crab species. Mortality rates varied by species
but depended mainly on that part of the trawl system
they encountered.

Crabs that passed under the trawl footrope, particu-
larly in the wing sections, died at higher rates than
those crab struck by the sweeps. Effective herding by
sweeps greatly expands the area of seafloor from which
flatfishes are captured. Mortality rates were substan-
tially lower for crabs that encountered these herding
devices in that expanded area than for crabs that en-
countered the trawl net itself, specifically the footrope.
Therefore, enhancement of fish capture rates through
effective herding can also reduce overall crab mor-
talities (i.e., capture of equivalent quantities of fishes
without herding would expose more crabs to footrope
components). The effective reduction of crab mortality
through use of sweeps was further augmented for red
king crab with modifications to raise sweeps a few cen-
timeters above the seafloor (Rose et al., 2010).

The lower rates of unobserved crab mortalities from
herding devices (i.e., sweeps), compared with mortality
rates from trawl footropes, only partially indicate the
potential of herding to reduce crab mortalities. Mortali-
ties of crabs that encounter the footrope also would in-
clude those crabs retained in the net (bycatch). Stevens
(1990) found that mortality rates were much higher for
both captured red king crab (79%) and captured south-
ern Tanner crab (78%) than for escaping crabs. Some
herding of crabs is conceivable, but their much slower

Rose et al Mortality rates for Chionoecetes opilio, C. bairdi, and Paralithodes camtschaticus after trawls on the seafloor

locomotion, compared with that of commercial fish spe-
cies, led us to assume that the number of crabs that
encountered each part of the trawl system is roughly
proportional to the area swept by each part.

Red king crab had higher mortalities (6-32%) than
2 species of Chionoecetes, snow and southern Tanner
crabs (4-15%) — a result that was expected given the
generally smaller size and flatter body shape of Chi-
onoecetes crabs. Overall mortality rates, weighted for
the approximate relative areas swept by each trawl
component for modern Bering Sea flatfish trawls (90%
sweeps, 6% footrope wings, 4% footrope center) were
6% for snow crab, 5% for southern Tanner crab, and
11% for red king crab. The raised sweeps reduce mor-
tality rate for red king crab to 6%. Such sweep modi-
fications were required by the North Pacific Fishery
Management Council for Bering Sea flatfish trawlers
beginning in January 2011.

The trawl gear and methods selected for our experi-
ment represented those gear and methods used in the
Bering Sea flatfish fisheries. The gear is characterized
by long, combination rope sweeps and footropes built
with large-diameter, rubber bobbins or disks to keep
the net mouth more than 20 cm above the seafloor.
This footrope selection by the fleet has been driven
partially by pressure to reduce crab bycatch. Decreas-
ing bycatch through changes to gear means that more
crabs pass under the trawl net. Although other Alas-
ka bottom trawl fisheries (e.g., for Pacific Cod [Gadus
macrocephalus ]) use similar footropes, they use much
shorter sweeps. Therefore, although cod trawls cover
less seafloor (and hence contact fewer crabs) per kilo-
meter towed than flatfish trawls, a higher proportion
of the crabs might die because more of them would
encounter the footrope components. The other major
trawl fishery that can affect Bering Sea crabs is the
fishery for Walleye Pollock { Theragra chalcogramma ).
Pollock trawls must meet a number of requirements
that allow them to be considered “pelagic” trawls, but
this fishery commonly has been fished with substantial
seafloor contact.

Because regulations disallow any protective bobbins,
none of the crab mortality estimates for gear compo-
nents examined in our study can be used to estimate
mortalities used for the pollock fishery, where chain foo-
tropes are used. The differences we found in mortality
rates between different gear components indicate that
changes in the specific gear configurations could im-
prove or worsen crab mortality rates. The rates found
here should not be applied to trawls with substantially
different ground gear (e.g., chain footropes used in the
Bering Sea pollock fishery). Component-specific mortal-
ity differences also present an opportunity to reduce
crab mortality through identification of less damaging
footrope configurations that sustain effective capture
of target species. A companion study where an alter-
native footrope was tested has been completed (Ham-
mond, 2009).

Because crabs were held for periods <14 days, our
results did not include mortalities delayed over longer
periods. The rapid drop of new mortalities after the
first few days and the presence of all reflexes at the
end of the study suggest that little additional mortality
would be expected unless some other mechanism, such
as infection or problems with molting, created a pulse
of mortalities outside of the time period observed (see
also Stoner et ah, 2008). Likewise, holding crabs in on-
deck tanks protected them from predation that would
have increased delayed mortality if vulnerability to
predation was enhanced by injury or stress after trawl
exposure. Predators and scavenger species have been
observed to move into areas recently swept by bottom
trawls (Prena et ah, 1999). Although this potential for
additional mortality was not addressed directly in this
study, the vast majority of the surviving crabs retained
their full suite of assessed reflexes, including mobility
of walking legs and defensive reactions. If predators
initially focused on the more severely impaired and in-
jured crabs that ended up as mortalities in our study,
less impaired crabs might have some respite, allowing
some time for recovery and reducing any difference be-
tween our results and the actual unobserved mortality
due to predation.

All retained red king crab were held until the end of
the study, 4 days after the control tows were complet-
ed. Because control crabs were held for only 4-6 days,
we examined the proportions of delayed mortalities of
crabs held for longer periods. For crabs held more than
10 days, 93% of the mortalities occurred in the first 4
days and 95% in the first 6 days. Because only 9 of the
881 red king crab caught in the control net died, the
possibility of missing one additional mortality because
of a shortened holding time was not considered to in-
troduce a significant potential bias. Short holding time
was even less of a concern for southern Tanner and
snow crab because all of those crabs were held 7 days
or longer and the low proportion of deaths after the
first days noted during the pilot project (Stoner et ah,
2008) continued during our 2008 observations.

In this study, the RAMP procedure (Stoner et ah,
2008) was successful in prediction of mortality rates
for many more crabs than we could have held to ob-
serve delayed mortality. Of all crabs assessed, 85% had
either all reflexes present ( Chionoecetes spp.) or were
uninjured with all reflexes present (red king crab).
Holding only one-eighth of these crabs provided gener-
ous samples (>350 crabs per species) for estimation of
their low mortality probabilities. If we had followed a
conventional study method and held all crabs regard-
less of reflex state, more than 4 times as many crabs
would have been held, with minimal reductions in
uncertainty.

Although only representing a small proportion of the
observed crabs, the RAMP procedure also allowed us
to efficiently account for crabs with intermediate reflex
assessments (reflex scores of 1 to 5). Because significant
mortalities occurred to injured red king crab with all

Fishery Bulletin 1 1 1 (1)

reflexes present, we held all those crabs, as well as all
crabs of any of the 3 species with any missing reflexes.
This procedure maintained the primary advantage of
our RAMP assessments, accounting for a large group
with high survival, and avoided the need to rely on
injury assessments to estimate mortality. Both Stevens
(1990) and Stoner et al. (2008) applied scoring systems
for injuries, but the variety of injury types makes in-
jury assessment more subjective and less likely to be
repeatable than the reflex assessments.

We provided specific estimates of the unobserved
mortality rates of crabs swept over by trawl gear com-
mon to bottom trawl fisheries in the Bering Sea. How-
ever, assessment of the effects of such mortalities on
the populations of those crabs will require estimation
of the portion of those populations exposed to trawling
each year. Although the distribution of trawling effort
is well documented by automated position monitoring
of vessels and onboard observers, the spatial distribu-
tion of crabs throughout the year is not well known. A
reliable estimate of the distribution of crabs, including
seasonal variability, would be needed to estimate their
exposure to trawling and allow for use of our mortality
rate estimates in order to estimate resulting mortali-
ties to the population. This approach would be subject
to error from interannual and seasonal variations in
crab distribution — variations that are not well under-
stood and would be difficult to monitor.

The number of crabs captured in bottom trawls
is monitored through catch sampling by onboard ob-
servers. Another way to estimate the number of crabs
encountering trawls would be to learn the proportion
of crabs that are caught in the path of a trawl. Crab
bycatch data could then be expanded to estimate the
number encountered, a value to which our mortality
rates could be applied to estimate overall, unobserved
mortality. One significant source of error for this ap-
proach is variability or changes in the specific foot-
ropes used across the fishery — differences that could
substantially alter the proportion of crabs retained by
the trawl. Also, should the trawl fishery approach its
goal of eliminating crab bycatch, the base bycatch data
could become sparse and even more variable.

Conclusions

Unobserved mortality is an important component of
bycatch that is both easily overlooked and difficult
to assess. Mortality rates for commercial crab species
overrun by bottom trawls used in the Bering Sea var-
ied substantially between the different components of
trawls, with lower mortality for crabs that encountered
sweeps than for crabs that encountered footropes. Re-
duction of mortality rates of red king crab from 10% to
4% by raising the sweeps off the seafloor showed that
gear modifications can mitigate unobserved mortality.

Acknowledgments

This study was primarily funded under a grant from
the North Pacific Research Board (project 711), with
additional support from the National Cooperative Re-
search and National Bycatch Reduction Engineering
Programs of the National Marine Fisheries Service,
NOAA. We gratefully acknowledge the substantial con-
tributions of Captain L. Perry and his crew on the FV
Pacific Explorer and the invaluable sampling efforts of
P. Iseri, S. Walters, D. Evans, and K. Lee, and particu-
larly D. Benjamin, who participated during all 3 sum-
mers of this study.

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Reactions of fishes to two underwater survey
tools, a manned submersible and a remotely
operated vehicle

Email for address for contact author: tom.laidig@noaa.gov

Abstract — We examined the reac-
tions of fishes to a manned submers-
ible and a remotely operated vehicle
(ROV) during surveys conducted in
habitats of rock and mud at depths
of 30-408 m off central California
in 2007. We observed 26 taxa for
10,550 fishes observed from the
submersible and for 16,158 fishes
observed from the ROV. A reaction
was defined as a distinct movement
of a fish that, for a benthic or hover-
ing individual, was greater than one
body length away from its initial po-
sition or, for a swimming individual,
was a change of course or speed. Of
the observed fishes, 57% reacted to
the ROV and 11% reacted to the
submersible. Aggregating species
and those species initially observed
off the seafloor reacted most often to
both vehicles. Fishes reacted more
often to each vehicle when they
were >1 m above the seafloor (22%
of all fishes >1 m above the seafloor
reacted to the submersible and 73%
to the ROV) than when they were
in contact with the seafloor (2% of
all reactions to the submersible and
18% to the ROV). Fishes reacted by
swimming away from both vehicles
rather than toward them. Consider-
ation of these reactions can inform
survey designs and selection of sur-
vey tools and can, thereby, increase
the reliability of fish assemblage
metrics (e.g., abundance, density,
and biomass) and assessments of
fish and habitat associations.

Manuscript submitted 16 February 2012.
Manuscript accepted 15 November 2012.
Fish. Bull. 111:54-67 (2013).
doi: 10. 7755/FB. 111.1.5

The views and opinions expressed
or implied in this article are those of the
author (or authors) and do not necessar-
ily reflect the position of the National
Marine Fisheries Service, NOAA.

Thomas E. Laidig (contact author)
Lisa M. Krigsman
Mary M. Yoklavich

Fisheries Ecology Division
Southwest Fisheries Science Center
National Marine Fisheries Service, NOAA
110 Shaffer Road
Santa Cruz, California 95060

Visual surveys of fishes in deep wa-
ter and untrawlable areas have been
conducted more frequently in re-
cent years than in the past largely
because of increased availability of
underwater vehicles and the need
for nonextractive assessments, par-
ticularly in no-take areas. These
vehicles have provided researchers
with the opportunity to gather valu-
able information on species composi-
tion, habitat associations, population
density, and various behavioral traits
that was previously unattainable
in these deep (>30 m), structurally
complex areas (Carlson and Straty,
1981; Pearcy et ah, 1989; Yoklavich
et ah, 2007; Laidig et ah, 2009; Love
et ah, 2009). Visual surveys present
advantages over traditional sampling
methods (e.g., trawling, hook and
line, traps) through the use of non-
destructive, in situ observations of
fishes in their natural habitats.

One concern in counting fishes is
their reaction to an observer (e.g.,
in scuba or snorkel surveys) or un-
derwater vehicle (e.g., submersibles,
remotely operated vehicles [ROVs],
and camera sleds; Stoner et ah,
2008). The vehicles, in particular, can
produce a number of electronic and
mechanical stimuli (e.g., lights, mo-
tion, and noise) that could alter be-
havior (Krieger, 1993; Uiblein et ah,

2003; Ryer et ah, 2009). Accounting
for these reactions is an important
aspect of accurate population assess-
ments. To this end, Yoklavich et ah
(2007) quantified the reactions of
fishes to a manned submersible dur-
ing a survey of Cowcod ( Sebastes le-
uis). Cowcod were found to react very
little to the submersible, and that low
level of reaction strengthened the ac-
curacy of the survey results and as-
sociated stock assessment. Other
studies have reported fish reactions
to both ROVs (Johnson et ah, 2003;
Trenkel et ah, 2004a; Lorance and
Trenkel, 2006) and manned submers-
ibles (Murie et ah, 1994; Krieger and
Sigler, 1996; Gibbons et ah, 2002).
However, most of these studies were
qualitative, simply noting that fishes
moved out of the way of the vehicles.
More quantitative studies are needed
to improve our understanding of the
nature and magnitude of reactions
of various fish species to a variety of
underwater survey vehicles.

The goal of our study was to char-
acterize the reactions of a wide range
of marine fish species to 2 commonly
used underwater vehicles (a manned
submersible and an ROV) during
surveys conducted along the seafloor.
We quantified the degree of species-
and size-specific reactions of fishes
living both on and above the seafloor.

Laidig et al Reactions of fishes to a manned submersible and a remotely operated vehicle

122’0’0-W

Figure t

Map of the area inside and outside of 3 marine protected areas (MPAs)
off central California that was surveyed in 2007 for our study of the reac-
tions of fishes to the manned Delta submersible and a remotely operated
vehicle (ROV). Polygon shapes outline the MPAs, and triangles and circles
indicate dive locations for the submersible and ROV. Bathymetry is in
given meters.

Materials and methods

Fish surveys were conducted off central
California (Fig. 1) inside and outside of 3
recently created marine protected areas
(MPAs) — Point Lobos, Portuguese Ledge,
and Soquel Canyon — with the 2-person
Delta submersible (Delta Oceanographies,

Torrance, CA) and a Phantom DS41 ROV
(Deep Ocean Engineering, San Jose, CA).

The manned submersible surveys occurred
during the period of 20 September-5 No-
vember, 2007, at depths of 30-365 m, and
the ROV surveys were conducted during
the period of 18-23 November, 2007, at
depths of 71-408 m. All surveys were con-
ducted during daylight hours from 0800
to 1700. Each submersible dive comprised
2-6 transects, each of a 10-min duration.

The ROV dives were 1-3 h in duration.

The ROV surveys were conducted along
the same path of only a subset of the sub-
mersible transects; in other words, not all
submersible transects were paired with an
ROV dive (Fig. 1).

The Delta submersible (Fig. 2A) was
launched from the FV Velero IV and op-
erated by experienced pilots from Delta
Oceanographies. An experienced scientific
observer accompanied the pilot inside
the untethered submersible. This yellow-
orange submersible was 1.8 m tall, 4.6 m
long, and from 0.4 m wide at its forward-
most part to 1.1 m wide at mid-vehicle.

The submersible was equipped with 2 vid-
eo cameras: 1) a forward-facing, low-light,
wide-angle, monochrome camera (Super
SeaCam 5000, DeepSea Power and Light,

San Diego, CA), and 2) a starboard-mount-
ed, custom-built, color zoom camera with
400 iines of resolution and an illumina-
tion range of 2-100,000 lux (Yoklavich and
O’Connell, 2008). The position of the Delta
submersible was tracked from the support
vessel with WinFrog integrated navigation software
(Fugro Pelagos, San Diego, CA) and an ORE Track-
point-II ultra-short baseline (USBL) acoustic system
(EdgeTech, West Wareham, MA). The distance traveled
was estimated with a ring laser gyro and Doppler ve-
locity log attached to the outside of the submersible.
A single 24-volt propeller provided thrust. During sur-
veys, the Delta traveled at an average speed of 0.5 m/s,
~1 m above the seafloor, following a directional heading
given to the pilot by scientists aboard the support ves-
sel. The submersible was equipped with ten 150-watt

1 Mention of trade names or commercial companies is for
identification purposes only and does not imply endorsement
by the National Marine Fisheries Service, NOAA.

halogen bulbs; only 3 of the starboard lights and 1 of
the front-mounted forward-facing lights were used to
illuminate the transect area.

We also used an unmanned Phantom DS4 ROV
launched from and tethered to the NOAA Ship Da-
vid Starr Jordan and operated by experienced pilots
from the National Marine Fisheries Service, South-
west Fisheries Science Center, in La Jolla, California
(Fig. 2B). The ROV had a yellow body and black frame
and was 1 m tall, 2 m long, and 1.4 m wide. The ROV
was equipped with a forward-facing, color video cam-
era (Sony FCB-IX47C, Sony Corp., Tokyo, Japan) with
470 lines of horizontal resolution and an 18x optical
zoom. Like the position of the submersible, the position
of the ROV was tracked with WinFrog software and

Fishery Bulletin 1 1 1 (1)

Figure 2

(A) Photos of the front and port side of the Delta submersible and (B) views of the front and port side of the Phan-
tom DS4 remotely operated vehicle (ROV), the 2 survey tools that were used in 2007 off central California in our
study of the reactions of fishes to underwater vehicles. The Delta measures 1.8 m tall, 1.1m wide (tapering to 0.4
m at front port), and 4.6 m long. The ROV is 1.0 m tall, 1.4 m wide, and 2 m long.

an ORE Trackpoint-II system. The ROV was propelled
by 6 electric thrusters (2 angled and 4 perpendicular
to the seafloor). Surveys were conducted at a target
speed of 0.5 m/s and a target height of 1 m above the
seafloor. Illumination was provided by two 250-watt
Multi-SeaLite halogen lights from DeepSea Power and
Light.

The forward-facing video cameras on each vehicle
were used to document fish reactions because these
cameras had similar orientations and captured fish
reactions in front of both vehicles. Both vehicles also
were equipped with lasers to help the observers esti-
mate size of fishes and their distance from the vehicle.
The Delta submersible had a pair of parallel lasers

Laidig et al Reactions of fishes to a manned submersible and a remotely operated vehicle

mounted 20 cm apart on either side of the color vid-
eo camera and were visible to the observer inside the
submersible. For both vehicles, fishes were measured
to the nearest 5 cm. Five lasers were mounted on the
front of the ROV; these lasers included 2 pairs of par-
allel lasers (20 and 60 cm apart) and a single crossing
laser used to determine depth of field. The laser spots
on the video footage were used in postsurvey analysis
to estimate both the size (total length) of fishes and the
distance ahead of the ROV at which a fish reaction oc-
curred. An effort was made to measure all fishes; how-
ever, some fishes were either too far away or partially
obscured, and, therefore, they could not be measured.

In an important distinction in survey methodology
between the 2 vehicles, the scientific observer inside
the submersible identified, counted, and estimated
length of fishes (as annotated on the audio channel of
the video camera), but these tasks were performed only
with video footage from the ROV surveys. Video foot-
age from both vehicles was reviewed after completion
of the surveys. Fishes in both surveys were identified
to the lowest possible taxon with taxonomic keys (Love
et al. [2002] for rockfishes, and Miller and Lea [1972]
and Eschmeyer et al. [1983] for the remaining fishes).

All fish reactions were determined solely from video
footage of the forward-facing cameras on both vehicles
in order for the methods to be similar between survey
vehicles. A reaction was defined as a distinct movement
of a fish if that movement was greater than one body
length away from the initial position of the fish. Some
fishes that were hovering off the seafloor would turn
and face the vehicle as it passed by, but this movement
was not considered a reaction unless a fish actively
swam at least one body length in any direction. If a
fish was swimming in a particular direction when first
observed and continued swimming in the same direc-
tion at the same speed during the entire time on video,
that fish was considered to have no reaction. However,
a reaction was noted if a fish changed course or swim-
ming speed.

The initial position of a fish was recorded as 1 of
3 categories: resting on the seafloor, <1 m above the
seafloor (but not touching the seafloor), or >1 m above
the seafloor. Direction of fish reaction was recorded as
swimming 1) toward the vehicle, 2) parallel, forward,
and away from the vehicle, 3) perpendicular to the left,
4) perpendicular to the right, or 5) down toward the
seafloor. No fishes were ever recorded moving upward.
We used time and an average vehicle speed of 0.5 m/s to
estimate the distance between a reacting fish and the
front of the Delta submersible. The distance between a
reacting fish at first sighting and the front of the ROV
was estimated with the laser array. This distance was
binned to <3 m or 3-6 m. A 20-cm fish could be seen at
a maximum distance of about 6 m in front of the ROV
and about 9 m in front of the submersible (because im-
ages could be distinguished farther with the low-light,
monochrome camera on the submersible compared with
the color camera on the ROV). To ensure that results

from the ROV and submersible were comparable, we
used data only from fishes that occurred at a distance
of at most 6 m from the submersible.

Hagfishes ( Eptatretus spp. ), thornyheads ( Sebastolo -
bus spp.), and young-of-the-year (YOY) rockfishes ( Se -
bastes spp.) were included as taxonomic groups in our
analyses. Hagfishes often were seen hiding in holes or
under structure and could not be identified to species.
However, all the hagfishes that could be identified were
Pacific Hagfish (Eptatretus stoutii). The thornyhead
group comprised Shortspine Thornyhead ( Sebastolobus
alascanus), a few Longspine Thornyhead (S. altivelis ; 1
observed from the submersible and 4 from the ROV),
and mostly unidentified thornyheads. YOY rockfishes
were a mix of many species, and each was recorded as
5 cm in total length.

We determined fish reactions only while the vehi-
cles traveled forward in survey mode. No fish reactions
were counted if the seafloor, which we used as a sta-
tionary reference for fish movement, was not observed
in the video footage for >5 s (as when either vehicle
transited over narrow ravines or when the ROV was
pulled off transect by the ship). A number of species
were not considered in our analyses. For instance, pe-
lagic schooling fishes, such as Northern Anchovy (En-
graulis mordax). Jack Mackerel ( Trachurus symmetri-
cus ), and Pacific Chub Mackerel ( Scomber japonicus),
swam around the vehicles for extended periods of time
(possibly because they were attracted to the vehicles,
but this idea was not verified), and these long periods
of time increased the possibility that fishes would be
double counted. These species also darted in and out of
the view of the cameras, making it difficult to assess
individual reactions to the vehicles. Only species that
accounted for >1% of the total number of fish observed
from either vehicle were included in the analyses of
reactions to the vehicles. A chi-square test was used to
evaluate reactions relative to initial fish position.

Results

A total of 223 transects (56 h) were surveyed with
the Delta submersible in hard (70% rock, boulder, and
cobble) and soft (30%) mud and sand) seafloor habitat,
and 10,550 fishes were observed (Table 1). A total of
10 ROV dives (21 h) were conducted, and 16,158 fishes
were observed. Although the ROV covered only a subset
of all submersible dives, the type of habitats surveyed
with the ROV (60% hard and 40% soft) were similar to
those habitats surveyed with the submersible. Water
visibility during submersible dives ranged from 4 to 13
m (as estimated by the submersible pilot during each
dive), averaged 8 m, and was greatest at depths >100
m. Observations made from the submersible were lim-
ited more by light penetration from the submersible (9
m) than by water visibility. Observations made from
the ROV video footage were confined to ~6 m, because

Table 1

The number and percentage of reactions of various fish taxa observed during visual surveys conducted from a manned submersible and remotely operated vehicle

Fishery Bulletin 1 1 1 (1)

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Laidig et al.: Reactions of fishes to a manned submersible and a remotely operated vehicle

of the type of lighting and camera (see Materials and
methods section).

We used 26 taxa of fishes in the analyses of fish
reactions to the submersible and ROV (Table 1). Half-
banded ( Sebastes semicinctus; 25%), Blue (S. mystinus;
24%), and Pygmy (S. wilsonr, 12%) Rockfishes were
the most abundant species observed from the Delta
submersible, and Halfbanded (56%) and Pygmy (22%)
Rockfishes were most abundant in the ROV survey. In
total, observations of 1161 fishes for the Delta sub-
mersible and 9206 fishes for the ROV were used in the
analyses of directional movements and distance of re-
action from each vehicle.

Fewer fishes reacted to the manned submersible
(11% of all fishes; Table 1) than to the ROV (57% of all
fishes). The minimum distance of a fish reaction was
0.5 m from the submersible (96% of reactions were at
a distance >1 m) and 1 m from the ROV. The percent
reaction varied from 0% for several species to 54% for
the Squarespot Rockfish (S. hopkinsi) observed from
the submersible and from 0% for some species to 84%
for Pink Seaperch, (Z alembius rosaceus) for fishes ob-
served from the ROV. Of those taxa observed from the
submersible, only Squarespot Rockfish had a reaction
rate of at least 50%. Six taxa observed with the ROV
had a reaction rate of at least 50%: Pink Seaperch,
Pacific Hake ( Merluccius productus), Spotted Ratfish
(Hydrolagus colliei), and Yellowtail (S. flauidus), Ca-
nary (S. pinniger), and Halfbanded Rockfishes. Cow-
cod, Bocaccio (S. paucispinis), and Canary Rockfish are
of particular concern to fishery managers and in need
of improved assessments (Hilborn et al., 2011; PFMC,
2011). The reaction rate of these 3 species to the sub-
mersible ranged from 8% to 19%; their reactions to the
ROV varied from 20% to 56%. Thornyheads, YOY rock-
fishes, and hagfishes had reaction rates <10% to either
vehicle. Fishes of 5 taxa did not react at all to the sub-
mersible, and 1 group of taxa (YOY rockfishes) that did
not react to the ROV.

Fish reactions to both vehicles increased significant-
ly as fish distance above the seafloor increased, and
this trend in reaction was greater for the ROV than for
the submersible (all fishes combined, P<0.001; Table 2;
Fig. 3). Only 2% of the fishes observed on the seafloor
during submersible surveys (i.e., 27 of 1261 fishes) and
7% observed near the seafloor (i.e., 410 of 6009) reacted
to this vehicle. However, 18% of fishes on the seafloor
(i.e., 512 of 2895) reacted to the ROV, with Halfbanded
Rockfish and Blackeye Goby ( Rhinogobiops nicholsii )
accounting for 71% of these reactions (361 out of 512
fishes that reacted; Table 2). During the ROV surveys,
fishes near the seafloor reacted more than fishes in
contact with the seafloor (59% versus 18%, respective-
ly), with Halfbanded and Pygmy Rockfishes represent-
ing 93% of these reactions (3800 out of 4083 fishes that
reacted). Fishes in the midwater, a region defined as >1
m above the seafloor, reacted the most to either vehicle
(22% to the submersible and 73% to the ROV). Squares-
pot and Blue Rockfishes represented 80% of the midwa-

ter reactions to the submersible, and Halfbanded and
Pygmy Rockfishes accounted for 90% of the reactions
of midwater fishes to the ROV. This pattern of greater
percentage of reactions with increased height off the
seafloor was observed for most individual taxa. Even
those species that are primarily demersal, like Cowcod
and Greenstriped (S. elongatus) and Greenspotted (S.
chlorostictus) Rockfishes, exhibited this pattern in ob-
servations from both the submersible and ROV.

The fishes that demonstrated any type of reaction
to each vehicle primarily swam away rather than to-
ward the vehicles (Fig. 4; Table 3, A and B). Only a
small percentage (0-8%) of fishes swam toward ei-
ther vehicle; most of these fishes were Bocaccio near
the seafloor, and 19 of 50 of those Bocaccio reacted by
swimming toward the submersible. Most fishes either
moved away (forward, ahead of the vehicle) or sideways
(to the left or right). However, 37% of all fishes in the
midwater reacted by swimming downward when ini-
tially encountered by the submersible (Table 3A). This
group was dominated by Blue, Widow (S. entomelas),
and Splitnose ( S . diploproa) Rockfishes (representing
96% of those midwater fishes that reacted by swim-
ming down). Only 13% of all fishes near the seafloor
moved downward as the submersible approached; Bo-
caccio and Widow Rockfish reacted the most in this
category (20% and 25% of all fish that reacted, respec-
tively). Only 1% of fishes in the midwater or near the
seafloor reacted to the ROV by swimming downward
(Table 3B).

The distance at which a fish reaction occurred var-
ied between vehicles (Table 4; Fig. 5). Blue, Halfband-
ed, Widow, Bank (S. rufus), and Splitnose Rockfishes
moved at distances >3 m in front of the submersible.
These species often were located in the midwater or
near the seafloor. However, some species located most
often near the seafloor (e.g., Bocaccio and Canary and
Squarespot Rockfishes) reacted more often when the
vehicle came closer to them (<3 m). Seafloor-dwelling
species did not react often to the submersible, and,
when they did, there was no clear pattern in reactions
related to distance in front of the vehicle. The species
that reacted farthest in front of the ROV were Half-
banded, Widow, and Yellowtail Rockfishes, all of which
were found near the seafloor or in the midwater. Spe-
cies that reacted closer (<3 m) to the ROV included
fishes living almost entirely on the seafloor (e.g.. Black-
eye Goby, Shortspine Combfish [ Zaniolepis frenata],
and Greenstriped Rockfish), as well as some near the
seafloor and in the midwater (e.g., Bocaccio and Ca-
nary, Greenspotted, Rosy [S. rosaceus], Splitnose, and
Squarespot Rockfishes).

Body length was determined for all fishes that were
observed during the submersible surveys (n = 10,550),
but only 9177 fishes (57%) of all fishes observed in
video footage from the ROV surveys were measured.
Total length ranged from 5 to 100 cm for fishes ob-
served from the submersible and from 5 to 70 cm for
fishes seen during the ROV surveys. Most fishes were

Table 2

Number and percentage of fishes that reacted to the manned submersible and the remotely operated vehicle (ROV) that were used in our surveys in 2007 off
central California, relative to the initial position of those fishes: on the seafloor, near (<1 m above) the seafloor, or in the midwater (>1 m above the seafloor).
YOY=young-of-the-year, s=submersible, r=ROV. Significance levels: *=0.05, **=0.01, ***=0.0001.

Fishery Bulletin 111(1)

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Laidig et al Reactions of fishes to a manned submersible and a remotely operated vehicle

20 cm or less in length (68% of all fish-
es in the submersible surveys and 89%
in the ROV surveys). The fishes that
were <20 cm in total length accounted
for 75% of all reactions observed from
the submersible and 94% of all reac-
tions observed in video footage from
the ROV surveys.

= 50

30 -

10 -

I Submersible (n = 10,550) □ ROV (n = 1 6, 1 58)

(n= 6976)

(n= 6287)

(n= 2895)

(n=6009)

(n=3280)

On seafloor

Near seafloor

Midwater

Figure 3

Percentages of fishes that reacted to the manned submersible or the re-
motely operated vehicle (ROV) that were used in 2007 off central Cali-
fornia in our study of the reactions of fishes to underwater vehicles rela-
tive to the initial position of those fishes: on the seafloor, near (<1 m
above) the seafloor, or in the midwater (>1 m above the seafloor). The
total number of reactions is indicated for each vehicle. Numbers above
bars indicate the total number of fishes (i.e., sample size) in each cat-
egory for each vehicle.

Discussion

Although fishes reacted to both sur-
vey vehicles, there were proportionally
greater numbers of reactions to the
ROV than to the submersible. The ROV
and submersible traveled at similar
speeds and maintained similar heights
off the seafloor, yet substantial differ-
ences were observed in fish reactions
to the 2 vehicles. Possible reasons for
these differences in reactions include
the presence of a tether that attach-
es the ROV to the support ship (the
manned submersible is autonomous
and untethered), forward lighting on
the ROV compared with lighting large-
ly on the starboard side of the sub-
mersible, differences in vehicle noise,
and disparity in vehicle dimensions.

Both vehicles were much larger than
common predators (e.g., large fishes and pinnipeds) of
most of these species, and we, therefore, surmise that
size alone was not the factor that caused fishes to re-
act. It is possible that the smaller ROV, which was
about one-half the height and length of the submers-
ible, appeared to be more like a large predator to the
fishes than did the submersible, but this idea is dif-
ficult to establish.

The magnitude of pressure waves generated in front
of each vehicle could have differed because the submers-
ible was of solid construction and the ROV comprised a
frame with attached instruments and a trailing tether.
Indeed, pressure waves generated from a deepwater
drop-camera system that operated about 130 m above a
midwater aggregation of Orange Roughy ( Hoplostethus
atlanticus) off Tasmania caused those fishes to disperse
rapidly up to 40 m (Koslow et al. 1995).

Fish reactions to vehicles can also depend on envi-
ronmental conditions (e.g., type of seafloor sediments,
relief, ambient light levels, and water currents) and
some attributes of the survey itself (e.g., vehicle speed
and height off the seafloor). To reduce the effects of
some of these conditions, we surveyed only during day-
light hours, in similar habitats, during the same time
of the same year, at similar speeds, and at similar
heights off the seafloor.

Whatever the reasons that fishes react to survey ve-
hicles, the reaction of the target species must be con-

sidered in selection of underwater vehicles to conduct
surveys on fish abundance. Population abundance can
be either over-or under-estimated if fish reactions to
the survey vehicles are not quantified. Once the reac-
tion rates are determined, correction factors can be
developed to account for species-specific differences in
reaction to the survey vehicles and to adjust resultant
abundance estimates. Knowledge of fish reactions as-
sociated with each survey tool can help ascertain the
most appropriate survey method for target species.

Clear description and quantification of fish reactions
to underwater survey vehicles are not common in the
literature. From a review of the literature, fish reac-
tions were defined in only 2 of 37 published papers that
reported on the reactions of fishes to underwater vehi-
cles (see review in Stoner et al. 2008; Davis et a!., 1997;
Krieger and Ito, 1999; Else et al., 2002; Moore et al.,
2002; Uiblein et al., 2003; Costello et al., 2005; Gartner
et al., 2008; Luck and Pietsch, 2008; Benefield et al.,
2009; Trenkel and Lorance, 2011; Baker et al., 2012;
O’Connell et al.2). A fish reaction was defined in one of
these 2 articles as a “disturbed” behavior or “differenc-

2 O’Connell, V., D. Carlile, and C. Brylinsky. 2001. Demersal
shelf rockfish stock assessment and fishery evaluation
report for 2002. Regional Information Report 1J01-35,
42 p. Alaska Dept. Fish Game, Division of Commercial
Fisheries, Juneau, AK.

Fishery Bulletin 1 1 1 (1)

On seafloor

Near seafloor

■ Submersible (410 fishes, 8%) □ ROV (4083 fishes, 59%)

50 -
45 -
40 -

Toward Away Left Right Down

Midwater

Submersible (724 fishes, 22%) □ ROV (461 1 fishes, 73%)

50 -

Toward Away Left Right Down

Figure 4

Percentage of fishes that reacted in a particular direction
to the manned submersible or the remotely operated vehicle
(ROV) that were used in 2007 off central California in our
study of the reactions of fishes to underwater vehicles rela-
tive to the initial position of those fishes: on the seafloor, near
(<1 m above) the seafloor, or in the midwater (>1 m above the
seafloor). Total number of fishes that reacted to each vehicle,
and the percentage of the total number of fishes in the survey
that reacted, are shown in parentheses for each initial position.

es in natural behavior” (Lorance and Trenkel,
2006) and as “a marked change in activity level
and/or locomotion behavior” in the other article
(Uiblein et al., 2003). General categories of re-
actions (such as a fish avoided or was attracted
to a vehicle, or a fish had no reaction) were
used in 6 studies (Adams et al., 1995; Trenkel
et al., 2004a; Trenkel et al., 2004b; Costello et
al., 2005; Trenkel and Lorance, 2011, Baker et
al., 2012), but specific definitions of the reac-
tions (in contrast to natural movements) were
not reported for these studies.

In our surveys, reaction of a nonmoving fish
was defined as a distinct movement greater
than one body length. We used this proportional
measure instead of a specific distance because
the total length of observed fishes varied from
5 to 100 cm. The use of our definition of a reac-
tion as at least one body length could be prob-
lematic, especially for quantification of relative-
ly small movements. However, in our study, the
minimum distance that any fish traveled was
0.5 m in reaction to the submersible (with 96%
of these fishes moving 1 m or greater) and 1.0
m in reaction to the ROV. Therefore, the reac-
tions of even the smallest fishes could be read-
ily discerned.

It can be argued that a fish in motion when
first seen in a video footage was already mov-
ing in reaction to the survey vehicles (Uiblein
et al., 2003; Lorance and Trenkel, 2006). In our
study, we surveyed numerous benthopelagic
species that were slowly moving when first
observed in the video footage. Such movement
was not considered a reaction unless a fish ob-
viously changed course or speed. Because a fish
could not be seen before it came into view on a
video footage, it could not be determined if that
fish was initially motionless and then reacted
as the vehicle approached. This type of behav-
ior could be indicated by signs like a dust cloud
where a fish had contact with the seafloor, a
fish quickly darting into the video footage, or
loose aggregations of fishes moving in many dif-
ferent directions. In our study, these types of
behavior were rarely, if ever, observed.

Few quantitative studies have been con-
ducted on fish reactions to a submersible or an
ROV, and no direct comparisons between the
reactions of specific fish species to a submers-
ible and ROV have been found in the literature.
General reactions to an ROV (fishes moving
into and out of a video frame) were quantified
during surveys on mud habitats off central Cal-
ifornia (Adams et al., 1995). In that study, most
fishes that occurred on the seafloor did not re-
act to a relatively large working-class ROV, al-
though 2 species typically observed off the sea-
floor exhibited avoidance behavior: 44% of all

Table 3 A

Number of fishes that reacted in a particular direction (toward, away, etc.) to a manned submersible in our surveys in 2007 off central California, relative to the
initial position of those fishes: on the seafloor, near (<1 m above) the seafloor, or in the midwater (>1 m above the seafloor). YOY=young-of-the-year.

Laidig et al Reactions of fishes to a manned submersible and a remotely operated vehicle

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Table 3B

Number of fishes that reacted in a particular direction to a remotely operated vehicle (ROV) in our surveys in 2007 off central California, relative to the initial
position of those fishes: on the seafloor, near (<1 m above) the seafloor, or in the midwater (>1 m above the seafloor). YOY=young-of-the-year.

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Laidig et at. : Reactions of fishes to a manned submersible and a remotely operated vehicle

Table 4

Number of fishes reacting within 3 m or >3 m from the front of the manned submersible and the remotely operated
vehicle (ROV). “Position” refers to the location where each fish taxon was most frequently observed. S=on the seafloor,
N=near the seafloor, M=in midwater (>1 m above seafloor). The total number of fishes (n) observed is indicated for
each vehicle.

Position

Submersible (n = 10,550)

ROV ( «= 16, 158 )

Number of reacting fishes

<3 m

>3 m

Total

<3 m

>3 m

Total

Bank Rockfish

Blackeye Goby

Blue Rockfish

179

181

Bocaccio

Canary Rockfish

Cowcod

Dover Sole

Greenblotched Rockfish

Greenspotted Rockfish

S, N

Greenstriped Rockfish

Hagfishes

Halfbanded Rockfish

N, M

134

218

1258

5173

6431

Pacific Hake

Pink Seaperch

N, M

211

219

Pygmy Rockfish

1201

581

1782

Rosethorn Rockfish

Rosy Rockfish

Shortspine Combfish

Splitnose Rockfish

S, N, M

Spotted Ratfish

Squarespot Rockfish

N, M

301

111

412

112

Stripetail Rockfish

Thornyheads

Widow Rockfish

N, M

Yellowtail Rockfish

N, M

119

YOY Rockfishes

S, N

Total

571

590

1161

3159

6047

9206

Percentage of fish reactions

Percentage of all fishes

Sablefish ( Anoplopoma fimbria) and 39% of all Pacific
Hake. Lorance and Trenkel (2006) observed that all
8 taxa seen in the Bay of Biscay, in habitat types rang-
ing from flat to gentle slopes and from fine sediments
to boulders, reacted to a large working-class ROV
with rates from 10% to 90%. Uiblein et al. (2003), also
in the Bay of Biscay, worked with a 3-person submers-
ible to study fish behavior and found that most of
the 7 more abundant taxa reacted to the vehicle by
markedly changing their activity level. Two species
observed in both of these studies (Roundnose Grena-
dier [ Coryphaenoides rupestris] and Orange Roughy)
reacted more often to the ROV than to the submers-
ible.

In our study, fishes that lived in the midwater above
the seafloor reacted to both the Delta submersible and
the Phantom ROV at a higher rate than did fishes

on the seafloor. Similar results have been reported in
other studies. Krieger and Ito (1999) observed that
all Shortraker ( Sebastes borealis) and Rougheye (S.
aleutianus) Rockfishes that occurred above the sea-
floor reacted by swimming toward the seafloor as the
Delta submersible approached, but only 5 out of the
531 recorded fishes of these 2 species moved when
initially seen on the seafloor. Lorance and Trenkel
(2006) examined the reactions of 8 fish taxa in the
Bay of Biscay and observed that most species reacted
to the working-class ROV; only the seafloor-dwelling,
deep-sea Atlantic Thornyhead ( Trachyscorpia cristula-
ta echinata) had little reaction to the vehicle. In that
study, 2 of the 3 taxa that had the greatest reactions
(shark species of the order Squaliformes and the fami-
ly Scyliorhinidae) were commonly encountered as they
swam high in the water column. Adams et al. (1995)

Fishery Bulletin 1 1 1 (1)

Distance in front of vehicle

Figure 5

Percentage of fishes that reacted at a specific distance in front
of the manned submersible and the remotely operated vehicle
(ROV). These percentages were used in 2007 off central Califor-
nia in our study of the reactions of fishes to underwater vehicles.
The total number of reactions in) is indicated for each vehicle.

hide for target species and environmental
conditions. Through such efforts, researchers
will gain a better understanding of the effec-
tiveness and limitations of potential survey
vehicles.

Acknowledgments

We thank R. Starr, co-principal investigator of
the Delta submersible cruise; J. Butler for the
use and operation of the ROV; S. Mau for pi-
loting the ROV; Delta Oceanographies; and the
crews of the FV Velero IV and the David Starr
Jordan. We thank M. Love, M. Nishimoto,
T. O’Connell, and D. Watters for help with data
collection. D. Watters also created the map
of our study site. We also thank C. Rooper,
S. Sogard, K. Stierhoff, R. Starr, and L. Wed-
ding for their helpful comments on early
versions of this manuscript. This study was
funded in part by a grant from the California
Ocean Protection Council to R. Starr and M.
Yoklavich.

used a working-class ROV and Starr et al. (1996) used
the Delta submersible to estimate fish abundance; both
studies determined that these vehicles were not re-
liable in assessment of the abundance of fishes well
above the seafloor.

Conclusions

What are the implications of the reaction of a fish to a
survey vehicle? If the reaction occurs over a small dis-
tance and the fish remains inside the survey transect,
then the fish would be counted and its reaction would
not affect the outcome of the survey. However, some
reactions (both large and small in magnitude) could
cause a fish to move out of the survey transect or out of
view (e.g., into a hole or behind a rock) — behavior that
would, thereby, bias the resultant abundance estimate.
Similarly, overestimates of abundance could be made if
a fish moves into a transect because of its reaction to
a survey vehicle.

Reactions of the target species need to be considered
in selection of a survey vehicle, and the limitations
of vehicles need to be evaluated relevant to the goals
of a study. For instance, a comparative study can be
undertaken to estimate abundance and reaction rates
of fish species with various underwater vehicles (e.g.,
a submersible, ROV, camera sled, an autonomous
underwater vehicle, or drop camera) within a specific
survey area or over particular transects. From this
type of study, the reaction of fishes and abundance es-
timates can be ascertained for each vehicle, thereby
aiding in the selection of an appropriate survey ve-

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Abstract — Rockfishes ( Sebastes
spp.) tend to aggregate near rocky,
cobble, or generally rugged areas
that are difficult to survey with
bottom trawls, and evidence indi-
cates that assemblages of rockfish
species may differ between areas
accessible to trawling and those ar-
eas that are not. Consequently, it
is important to determine grounds
that are trawlable or untrawlable
so that the areas where trawl sur-
vey results should be applied are ac-
curately identified. To this end, we
used multibeam echosounder data
to generate metrics that describe
the seafloor: backscatter strength at
normal and oblique incidence angles,
the variation of the angle-dependent
backscatter strength within 10° of
normal incidence, the scintillation of
the acoustic intensity scattered from
the seafloor, and the seafloor rugos-
ity. We used these metrics to develop
a binary classification scheme to
estimate where the seafloor is ex-
pected to be trawlable. The multi-
beam echosounder data were verified
through analyses of video and still
images collected with a stereo drop
camera and a remotely operated ve-
hicle in a study at Snakehead Bank,
-100 km south of Kodiak Island in
the Gulf of Alaska. Comparisons of
different combinations of metrics
derived from the multibeam data
indicated that the oblique-incidence
backscatter strength was the most
accurate estimator of trawlability at
Snakehead Bank and that the addi-
tion of other metrics provided only
marginal improvements. If success-
ful on a wider scale in the Gulf of
Alaska, this acoustic remote-sensing
technique, or a similar one, could
help improve the accuracy of rock-
fish stock assessments.

Manuscript accepted 21 November 2012.
Fish. Bull. 111:68-77 (2013).
doi:10.7755/FB. 11 1.1.6

The views and opinions expressed
or implied in this article are those of the
author (or authors) and do not necessar-
ily reflect the position of the National
Marine Fisheries Service, NOAA.

Seabed classification for trawlability determined
with a multibeam echo sounder on Snakehead
Bank in the Gulf of Alaska

Thomas C. Weber (contact author)1

Christopher Rooper2

John Butler3

Darin Jones2

Chris Wilson2

Email address for contact author weber@ccom.unh.edu

1 Center for Coastal and Ocean Mapping
University of New Hampshire

24 Colovos Road

Durham, New Hampshire 03824

2 Alaska Fisheries Science Center
National Marine Fisheries Service, NOAA
7600 Sand Point Way NE

Seattle, Washington 98115

3 Southwest Fisheries Science Center
National Marine Fisheries Service, NOAA
8604 La Jolla Shores Drive

La Jolla, California 92037

Rockfish ( Sebastes spp.) stocks are
difficult to assess because of their
propensity to aggregate near the
seafloor in areas that are difficult to
trawl, such as rocky, cobble, or gener-
ally rugged areas. Consequently, data
from bottom-trawl surveys conducted
in trawlable areas typically are ex-
trapolated to all areas within the
boundaries of a survey, regardless of
whether the seafloor is trawlable or
not (Wakabayashi et ah, 1985). Such
extrapolation may result in biased
biomass indices if, for example, there
is a shift in biomass between strata
with variable but unknown amounts
of untrawlable seafloor (Cordue,
2006). Evidence also indicates that
species assemblages differ between
trawlable and untrawlable areas
(Matthews and Richards, 1991; Ja-
gielo et al., 2003; Rooper et al., 2010),
and remote-sensing techniques with
acoustic or optical sensors may be
able to help identify these differ-
ences. Equally important is the need
to have a quantitative assessment of
those grounds that are trawlable or
untrawlable to more accurately esti-
mate the areas where the results of

different stock assessment methods
are valid.

In many bottom-trawl surveys,
trawlability has been assessed
through the subjective interpreta-
tion of normal-incidence backscatter
(echoes) from downward-looking sin-
gle-beam echo sounders. These back-
scatter echoes are examined by vessel
captains with different levels of ex-
perience, with different echo sound-
ers, and with different echosounder
settings. Multibeam echo sounders
(MBES), which have been successful
previously for characterizion of the
seafloor for the purposes of mapping
habitat and surficial geology (e.g.,
Kostylev et al., 2001; Goff et ah,
2004; Brown and Blondel, 2009), may
offer an alternative solution for as-
sessment of trawlability. In addition
to the wider, high-precision coverage
of the seafloor that results from the
use of multiple beams, MBES offer
the potential for more accurate dis-
crimination between different types
of seafloor substrate (e.g., silt, sand,
cobble, and rock) than does the use
of downward-looking single beams
because of the angle-dependent na-

Weber et al: Seabed classification for trawlability determined with a multibeam echo sounder

rough rock

Figure 1

A prediction of the angle-dependent seafloor backscatter strength, Sb (dB), ac-
cording to APL [1994], for the beam configuration used for the Simrad ME70
multibeam echo sounder at Snakehead Bank in the Gulf of Alaska during a
cruise of the NOAA Ship Oscar Dyson in October 2009. The areas over which the
oblique-incidence Sb and the slope of the angle-dependent backscatter within 10°
of normal incidence (S^-slope) were calculated are shown. Normal-incidence Sb
was calculated at 0° incidence angle.

ture of the seafloor backscatter
strength, Sb. For example, the
normal-incidence (i.e., 0° inci-
dence angle) Sb that would typi-
cally be expected for both cobble
and fine sand are predicted to be
very similar but are appreciably
different at increased incidence
angles (Fig. 1). Angle-dependent
metrics that describe the back-
scatter from the seafloor have
been extracted from MBES data
in previous studies to determine
the nature of seafloor sediments
(e.g., Fonseca and Mayer, 2007).

Seafloor backscatter collected
with an MBES, as are the pre-
dictions shown in Figure 1, are
often treated as the ensemble
average of a large number of
random realizations of scattered
acoustic intensity. Higher order
statistics that describe the scat-
tered intensity may also provide
information that can be used to
characterize the seafloor. Often,
the amplitude of the backscat-
ter echoes is expected to follow
a Rayleigh distribution, with the
underlying assumption that there are a large number
of contributors to the backscatter from the seafloor at
any instant in time (Jackson and Richardson, 2007).
Abraham and Lyons (2002) have linked heavy-tailed,
non-Rayleigh distributions of backscatter to a model
with a relatively small number of objects on the sea-
floor that have high levels of backscatter strength. In
other words, the details of the probability density func-
tion that describe the amplitude of the acoustic echoes
are likely to be related to the size and density of the
scattering objects and their relative role in the overall
scattering response. Measures that indicate non-Ray-
leigh backscatter may give an indication of distributed
cobble or rock that would render a seafloor untrawlable.

In this study, we examined the angle-dependent na-
ture of Sb, as well as measures of non-Rayleigh dis-
tribution of the backscatter and the seafloor rugos-
ity (roughness) derived from bathymetric soundings,
in an attempt to discriminate between trawlable and
untrawlable seafloors. The data were collected with
a Simrad1 ME70 MBES (Kongsberg AS, Horten, Nor-
way) at a study area on Snakehead Bank in the Gulf
of Alaska, -100 km south of Kodiak Island (Fig. 2). To
test the efficacy of the acoustic measures as classifiers
of the seafloor as either trawlable or untrawlable, we
compared metrics derived from a MBES with observa-

1 Mention of trade names or commercial companies is for
identification purposes only and does not imply endorsement
by the National Marine Fisheries Service, NOAA.

tions collected with a stereo drop camera (SDC) system
(Williams et ah, 2010) along with cameras mounted on
a remotely operated vehicle (ROV) (Rooper et ah, 2012).
The results of this comparison were then extracted to
the entire multibeam data set that was collected with
the Simrad ME70 during our Snakehead Bank surveys.

Methods

MBES data were collected with a Simrad ME70 MBES
mounted on the hull of the NOAA ship Oscar Dyson.
The Simrad ME70 was developed specifically for fish-
eries applications (Trenkel et ah, 2008), although it
also has been used for bathymetric mapping (e.g., Cut-
ter et ah, 2010). The Simrad ME70 is configurable in
terms of 1) the number of beams generated, 2) acoustic
frequency for each beam, and 3) direction and open-
ing angle of the beams. For our surveys at Snakehead
Bank, the Simrad ME70 was configured to generate 31
beams at frequencies ranging from 73 to 117 kHz and
at beam opening angles that ranged from 2.8° to 11.0°.
The 31 beams were steered to 0° in the alongship di-
rection and from -66° to +66° in the athwartship direc-
tion, with the lowest frequencies steered to the high-
est beam steering angles to mimimize the possibility
of ambiguities associated with grating lobes (angular
regions within a beam pattern of a transducer array
that have equal sensitivity to the main angular region,
or lobe, and cause ambiguities in the determination of

Fishery Bulletin 111(1)

56 10°N

56 05°N

56.00°N

55 95“N

55 90 N

1 54. 2° W 154 1“W 154 0°W 153 9°W 1538°W 153 7°W 1536°W 153 5°W

Figure 2

The study area at Snakehead Bank in the Gulf of Alaska, south of Kodiak Island. Bathymetric
contours are drawn at 50-m intervals. The locations where data were collected in 2009 with a Sim-
rad ME70 multibeam echo sounder from the large-scale trackline and during focused surveys are
shown in red (classified as untrawlable) and blue (classified as trawlable). Camera data collected
in 2009 and 2010 with a stereo drop camera and a remotely operated vehicle are shown as green
squares (untrawlable) and cyan circles (trawlable).

target angle direction; the occurrence of grating lobes
is specific to the design of the transducer array that
generates beams). A pulse duration of 1.5 ms was used
for each beam. During transmission and reception, the
beam-pointing directions were compensated for pitch
and roll of the ship with a GPS-aided inertial motion
unit (IMU). The IMU was also used to georeference
the data collected with the MBES. The standard target
method was used to calibrate the combined transmit-
receive sensitivity of each beam (Foote et al., 1987).

In comparison with the Simrad ME70, most hydro-
graphic MBES are capable of generating an order of
magnitude more beams with beam opening angles of a
fraction of a degree and, therefore, produce a relatively
high density of bathymetric soundings and measure-
ments of seafloor backscatter. To achieve a similarly
high density of data with fewer beams, we processed
the Simrad ME70 data with a hybrid multibeam and
phase-differencing technique (Lurton, 2010) that pro-
vided hundreds of independent seafloor soundings
(each of which was associated with a measure of Sb)
over a swath that nominally covered ±60°. At beam
angles away from normal incidence, the insonified por-
tion of the seafloor (the area on the seafloor defined
by the intersection of the sonar pulse within the beam
pattern of the transducer array) acts as a discrete tar-
get; therefore, each beam was processed as if it were
a phase-measuring bathymetric sonar (Lurton, 2010,
section 8.2.3). Because this approach is more accu-
rate at higher incidence angles (Jin and Tang, 1996), a
weighted mean amplitude detection (Lurton, 2010, sec-

tion 8.3.3) was used for beams with incidence angles
of only a few degrees. For our data, the transition be-
tween these 2 bottom detection approaches correspond-
ed to an incidence angle of approximately 15°. The raw
soundings were then merged with vessel position and
attitude data and corrected for refraction through the
water column. The georeferenced soundings were used
to extract the rugosity in a grid of 25-m squares, or
cells, by computing the ratio of the observed surface
area within each grid cell to the area of a plane fitted
to the same data.

A measure of the acoustic power was associated
with each bottom detection and was converted to Sb
by accounting for system gains and calibration offsets,
spherical spreading and absorption in the water col-
umn, and area insonified. Area insonified was estimat-
ed with the assumption that the seafloor was flat and
with the method described by Lurton (2010, section
3.4.3). Applications of these radiometric corrections
provided a realization of the angle-dependent seafloor
backscatter, which was used to help characterize the
seafloor, on each ping. Figure 1 shows predictions of
the angle-dependent Sb for different substrate types
that range from very fine silt to rough rock, on the
basis of a scattering model that includes estimates for
acoustic impedance, seafloor roughness, and sediment
volume scattering strength (APL, 1994). In general, it
can be difficult to disambiguate between the different
factors that underlie these scattering curves (Fonseca
and Mayer, 2007), but they do offer some separation
between different substrate types. On the basis of an

Weber et al: Seabed classification for trawlabiiity determined with a multibeam echo sounder

examination of the predictions of Sb shown in Figure 1,
3 different metrics that describe Sb were used, similar
to those of Fonseca and Mayer (2007): the normal-inci-
dence Sb, the slope of the angle-dependent backscatter
within 10°of normal incidence (S6-slope), and the aver-
age oblique-incidence Sb (30° <0< 60°).

The acoustic power associated with each bottom de-
tection also was converted to acoustic backscatter in-
tensity and used to derive an estimate of the scintilla-
tion index, SI, which is defined here as

S/ = -H, (1)

P-i

2 2

where O/ and Ui = the variance and mean of the
backscatter intensity, respectively.

The SI is a measure of how the backscatter inten-
sity fluctuates: for Rayleigh-distributed backscatter,
the SI is equal to 1; for heavier tailed distributions
that are a potential indicator of a relatively few strong
scatterers contributing to the backscattered echo, the
SI would be >1. The SI was calculated independently
for each beam with a minimum of 50 samples (pings)
and then averaged across beams. One important caveat
to such SI estimation is that it is dependent on the
sonar footprint on the seafloor (Abraham and Lyons,
2004), which changes as a function of incident angle
and seafloor depth for MBES. To reduce changes in SI
that were associated with the sonar footprint rather
than the substrate type, we used only the beam angles
between 34° and 50° to generate this parameter. This
restriction of angles essentially reduced the resolution
to that of a single multibeam swath.

The MBES data were compared with image data
(both video and still images) from an SDC and a ROV.
The SDC contained identical Sony TRD-900 camcorder
units (Sony Corp., Tokyo, Japan) capable of collecting
progressive scan video images at a pixel resolution of
1280x720. Both SDC camcorder units were mounted
on a sled in an aluminum frame and lowered to the
seafloor with a dedicated winch, and illumination was
provided by 2 lights mounted above the camera hous-
ings inside the aluminum frame (Williams et ah, 2010).
MBES data also were compared with data collected
with a Phantom DS4 ROV (Deep Ocean Engineering,
Inc., San Jose, CA). Video footage was recorded from
the ROV with a forward-looking color camera (Sony
FCB-IX47C module with 470 lines of horizontal resolu-
tion and 18x optical zoom). Two pairs of parallel lasers
on the ROV were used to estimate substrate size and
horizontal field of view.

Data were collected during 3 cruises conducted at
Snakehead Bank, south of Kodiak Island in the Gulf of
Alaska (Fig. 2). During the first cruise, the Oscar Dys-
on and the FV Epic Explorer, a commercial fishing ves-
sel, visited the study site on 4-12 October 2009. Data
were collected aboard the Oscar Dyson with the Simrad
ME70 and ROV, and data were collected with the stereo
drop camera aboard the Epic Explorer. Several repeat

large-scale surveys were conducted with The Oscar Dy-
son along a series of parallel transect lines spaced 2.2
km (1.2 nmi) apart and 9.3-14.8 km (5-8 nmi) long.
Three of these surveys were used for this analysis. In
addition to the large-scale surveys, 4 small-scale, fo-
cused surveys were conducted in the same area dur-
ing the first of the 3 cruises. The focused surveys were
designed to achieve “full coverage” (i.e., no unsampled
regions of the seafloor) of the seafloor with the Simrad
ME70 in areas where a relatively strong indication of
fish had been observed in the acoustic data. For the
small-scale surveys, transects were 1.9-3. 7 km (1-2
nmi) long and spaced 0.2-0. 4 km (0. 1-0.2 nmi) apart
(depending on the water depth).

The drop camera was deployed 9 times during the
October 2009 cruise, and locations were chosen where
the acoustic data indicated that rockfishes were most
abundant. During each of the drop-camera deploy-
ments, the camera sled moved over the bottom at
speeds of <1.5 kn as the Epic Explorer drifted along
transects that lasted up to 1 h and, as a result, col-
lected relatively dense data in 9 small regions. The
horizontal field of view of the drop camera averaged
2.43 m (standard error of the mean [SE] =0 . 14).

The ROV was deployed in 5 different areas where
the acoustic data indicated that rockfishes were most
abundant. Each deployment lasted for a few hours. The
horizontal field of view for the ROV averaged 2.61 m
(SE=0.20).

During the other 2 cruises in March and June of
2010, the study site was revisited and the SDC de-
ployed 51 times aboard the Oscar Dyson. During these
additional deployments, the seafloor was recorded in
only 1 of the 2 available stereo cameras, preventing
collection of stereographic images. Each of these de-
ployments was short: the drop camera was deployed
to the bottom for a couple of minutes before it was re-
trieved to the surface. The resulting images were all
from single, small patches ( <25 m radius) of seafloor,
rather than from the drift transects described for the
first cruise.

The seafloor substrate observed during the under-
water video transects was classified with a commonly
used scheme (Stein et ah, 1992; Yoklavich et ah, 2000).
The classification consisted of 2-letter codes for sub-
strate types that denoted a primary substrate with
>50% coverage of the seafloor bottom and a second-
ary substrate with 20-49% coverage of the seafloor.
There were 7 identified substrate types: mud (M), sand
(S), pebble (P, diameter <6.5 cm), cobble (C, diameter
6.5-25.5 cm), boulder (B, diameter >25.5 cm), exposed
low-relief bedrock (R), and exposed high-relief bedrock
and rock ridges (K). The size of substrate particles was
measured or estimated from a known horizontal field
of view (~2.4 m) for the SDC and estimated with a
paired laser system for the ROV. With this classifica-
tion scheme, a section of seafloor covered primarily in
cobble but with boulders over more than 20% of the
surface would receive the substrate-type code cobble-

Fishery Bulletin 1 1 1 (1)

boulder (Cb), with the secondary substrate indicated
by the lower-case letter. Because the video collected
with the SDC and ROV provided a continuous display
of substrata, the substrate-type code was changed only
if a substrate type encompassed more than 10 consecu-
tive seconds of video.

For this study, the substrate observed in the under-
water video transects was further classified as either
untrawlable or trawlable with reference to the stan-
dard Poly-Nor’eastern 4-seam bottom trawl used in
biennial bottom-trawl surveys of the Gulf of Alaska
and Aleutian Islands by the Alaska Fisheries Science
Center (Stauffer, 2004). The Poly-Nor’eastern bottom-
trawl footrope comprised 10-cm disks interspersed
with bobbins 36 cm in diameter. The untrawlable ar-
eas were defined as any substrate containing boulders
that reached >20 cm off the bottom of the seafloor or
any substrate with exposed bedrock that was so rough
that the standard bottom-trawl footrope would not eas-
ily pass over it. Therefore, the trawlable grounds were
those areas mostly composed of small cobble, gravel,
sand, and mud without interspersed boulders or jagged
rocks. The untrawlable grounds were those areas that
contained any boulder or high-relief rock substrates.
The same experienced observer classified the substrate
for both the ROV and SDC video transects.

The video data thus classified were partitioned in
a grid of 25-m squares, or cells — a length scale that
is a rough estimate for the accuracy of the position-
ing systems associated with both video systems. The
primary and secondary substrate types were given a
numeric value based on a nominal substrate size, and
each grid cell was assigned substrate types associated
with the median values for all data within the cell
boundaries. Grid cells also were assigned as trawlable
or untrawlable if all data within a cell supported such
a classification; otherwise, the grid cell was assigned a
“mixed” classification. The gridded video classifications
were then compared with the seafloor parameters (e.g.,
rugosity or normal-incidence Sb) derived from data col-
lected with the Simrad ME70, where both types of data
existed at the same position, to provide an indication of
how each acoustically derived seafloor parameter was
able to discriminate between trawlable and untraw-
lable areas. This comparison was done for each param-
eter separately and then done for various combinations
of parameters to find a combination of parameters that
best discriminated between trawlable and untrawlable
substrate. For each parameter, a f-test was used to de-
termine whether it was able to distinguish between
trawlable and untrawlable seafloor at the significance
level of a=0.05 (i.e. , where erroneous rejection of the
null hypothesis is expected 5% of the time), and val-
ues of standard difference (the difference between the
sample means divided by the pooled standard devia-
tion) were computed. When combinations of parameters
were tested, a best-fit separation (for the goal of mini-
mizing the classification error rate) within the multidi-
mensional parameter space was found through exami-

nation of the entire parameter space. To maintain a
clear link back to the underlying data distribution, the
separation between trawlable and untrawlable was as-
sumed to be a line, plane, or hyperplane (a generaliza-
tion of a plane into more than 2 dimensions), depend-
ing on the dimension of the parameter space.

Results

The data showed a wide range of values and, presum-
ably, associated substrate types. The shallowest (<100-
m) portion of Snakehead Bank contained the highest
oblique-incidence Sb (approximately -12 dB). This re-
gion contained similar values for the normal-incidence
Sb, and small S6-slope (<0.75 dB/°). Taken together,
these data indicate a cobble seafloor on the top of the
bank. On the northeastern side of the bank at depths
-200 m, the oblique-incidence Sh reached its lowest
value of approximately -30 dB with a normal-incidence
Sh of -15 dB and S6-slope of -1.1 dB/° — values consis-
tent with a substrate composed of very fine silt.

The region with the highest normal-incidence Sb
(-10 to -7 dB) occurred between 154°W and 153. 9°W
and near 56.07°N in the northwest region of the bank.
The S6-slope was also high in this region, reaching up
to 1.5 dB/°, and the oblique-incidence Sb was between
-18 dB and -15 dB. These results for the seafloor pa-
rameters are confounding, given that the S6-slope was
large enough to indicate a fine sand or silt, but the
normal-incidence and oblique-incidence Sb both indi-
cated a coarser sediment or a higher-than-anticipated
volume scatter contribution due to heterogeneities or
gas (Jones et ah, 2012) within the sediment.

The SI shows a complicated pattern that did not
appear to be well correlated with any certain sub-
strate type, although there were large (hundreds of
meters) contiguous regions that exhibited high SI val-
ues (i.e., the data did not appear to be simply random
noise). The rugosity levels show the bank to be rela-
tively smooth along the top, except at a sharp transi-
tion along its northeastern edge between the 100- and
150-m contours. The rugosity analysis also indicates
the appearance of what may be large (wavelength
-150 m) sand waves in the extreme southeastern por-
tion of the study area and smaller pockmarks in the
southwestern portion of the study area.

The results of a comparison of the seafloor param-
eters derived from the backscatter data that was col-
lected with the Simrad ME70 and the substrate types
derived from the data collected with the SDC and ROV
are shown in Figure 3. These data show that, although
substrate types Bb, Cb, and Gb are difficult to distin-
guish with backscatter parameters, these 3 types are
clearly separate from substrate type Ss. The oblique-
incidence Sb values for substrate type Ss appeared to
be bimodal, with the majority of the values residing be-
tween -17 and -15 dB and a substantial number of val-
ues between -29 and -26 dB. According to the notional

Weber et al: Seabed classification for trawlability determined with a multibeam echo sounder

20:

Figure 3

The frequencies of occurrence for major and minor substrate combinations, classified from the data collected in 2009 and
2010 with a stereo drop camera and a remotely operated vehicle as a function of different seafloor characteristics derived
from the data collected with a Simrad ME70 multibeam echo sounder. Major (capital letter) and minor (lowercase letter)
substrate types included Bb=boulder; C=cobble; Gg=gravel; and Ss=sand.

values shown in Figure 1, these 2 regions would cor-
respond to sandy gravel and very fine silt, respectively.
The lower set of oblique-incidence Sh values were found
in the deepwater off the northern side of the bank at
depths of 200-250 m and also on the south side of the
bank at depths of 120-150 m. On average, the larg-
est Sfc-slope and the widest range of normal-incidence
Sb were observed on sandy substrate. The normal-in-
cidence Sb for areas classified as sandy substrate ex-
tended to ranges higher than would be expected, a find-
ing that could be a result of unusually high volume-
backscatter caused by gas or heterogeneities within the
sediment volume. The harder substrates (Bb and Cb)
all had small S6-slope, as expected, and on average had
higher SI than the sandy sediments.

To determine how each parameter discriminated
between trawlable or untrawlable seafloor, using clas-
sified SDC and ROV video data as verification, the
frequencies of occurrence for each parameter were ex-
tracted for each substrate type (Fig. 4). T-tests indicat-
ed that the distributions of trawlable and untrawlable
areas of seafloor were distinguishable at the oc=0.05
significance level (Table 1), although each parameter
did not perform equally when discriminating between
the 2 classifications. The 3 best individual discrimina-
tors were the normal-incidence Sb, Sb- slope, and the

oblique-incidence Sb with standard differences of 0.74,
1.12, and 1.89, respectively. Of these 3 parameters, the
oblique-incidence Sb demonstrated the clearest separa-
tion between trawlable and untrawlable seafloor, with
a boundary at -13.4 dB. According to modeled data
(Fig. 1), this Sb level discriminates cobble and rock
from gravel, sand, and silt. The SI and rugosity were
separated less well with standard differences of 0.25
for each.

With the oblique-incidence Sb considered alone, the
combined error rate (erroneous classifications of both
trawlable and untrawlable seafloor) reached a mini-
mum of 5.6% (n=303) with a boundary set at S6=-13.4
dB. To determine whether this error rate could be
lowered, additional parameters derived from the data
collected with the Simrad ME70 were linearly com-
bined with the oblique-incidence Sb. Figure 5 shows
the combination of the oblique- incidence Sb with each
of these other parameters, along with a line that best
discriminated between the trawlable and untrawlable
classifications. The largest reduction in classification
error rate was achieved when the oblique-incidence Sb
was combined with either the normal-incidence Sb or
the SI, both of which had a marginally improved er-
ror rate of 5.0%. When 3 parameters were combined to
discriminate between trawlable and untrawlable sea-

Fishery Bulletin 111 (1)

Table 1

Results of a 2-sample t-test and the standard difference in a
comparison of trawlable and untrawlable populations for differ-
ent parameters derived from the data collected with the Simrad
ME70 multibeam echo sounder during a cruise in 2009 aboard the
NOAA Ship Oscar Dyson. These parameters are normal-incidence
seafloor backscatter strength (Sb), oblique-incidence Sb, the slope
of the angle-dependent backscatter within 10° of normal incidence
(S^-slope), scintillation index (SI), and rugosity (roughness).

Degrees of Standard

t-statistic freedom P -value difference

Normal-incidence Sb

6.6

260

2xlO-10

0.74

Oblique-incidence Sb

17.2

170

4xl0-39

1.89

S6-slope (0-10°)

9.9

287

5xlO-20

1.12

2.1

216

0.04

0.25

Rugosity

3.6

418

0.0004

0.25

floor, the error rate did not change apprecia-
bly except in the case of a combination of the
oblique-incidence Sb, the normal-incidence Sb,
and the SI, in which case the class error rate
was reduced to 3.8%; similar error rates were
found with 4 classes separated by a best-fit
hyperplane.

Because only marginal improvements in
class error rate were achieved when multiple
parameters were combined and maintenance
of simplicity in the interpretation of the re-
sults was desired, the oblique-incidence Sb
was chosen as the sole discriminator between
the trawlable and untrawlable seafloor at the
study site. The classifications of trawlable
and untrawlable seafloor classifications area
shown in Figure 2 for both the from the Sim-
rad ME70 and the data from the SDC and
ROV. The classification based on the data from
the Simrad ME70 is accurate throughout most

Weber et al: Seabed classification for trawlability determined with a multibeam echo sounder

of the study site, and the most obvious error occurred
on the north-south transect intersected 153. 9°W in an
area with high oblique-incidence Sb.

Discussion

The oblique-incidence Sb and the S6-slope followed the
expected trends when separated into trawlable and un-
trawlable classes and these trends were verified from
video data collected with the SDC and ROV. Untraw-
lable areas were expected to have a larger oblique in-
cidence Sb and Sfe-slope than trawlable areas on the
basis of backscatter models (e.g., Fig. 1). The normal-
incidence Sb did not appear to discriminate very well
between trawlable and untrawlable seafloor and tended
to have a wider distribution of backscatter values than
would have been expected on the basis of consideration
of the oblique-incidence Sb and the modeled values
shown in Figure 1. There are several possible reasons
for the lack of discrimination with normal-incidence Sb,
including higher-than-expected normal-incidence Sb in

the sands and silts caused by gas or heterogeneities
within the sediment volume in some trawlable areas
and higher-than-expected roughness in the areas of
cobble and rock that caused a larger-than-anticipated
reduction in the normal-incidence Sb for some untraw-
lable areas.

Although quite variable throughout the study area,
the mode of the SI was slightly higher for the untraw-
lable seafloor than it was for the trawlable seafloor.
This difference seems plausible when we consider the
SI to be a metric for how many scatterers are contrib-
uting to the sonar return within a beam footprint. A SI
value near 1 suggests that there are a large number of
scatterers (i.e., the central limit theorem applies, and
the backscatter amplitude is Rayleigh distributed), as
might be expected from a sand or silt seafloor. On the
other hand, a larger SI indicates that there are only a
few dominant scatterers within the beam footprint, as
might be expected from a seafloor of cobbles or boul-
ders. Although the data indicate a trend in the correct
direction, SI alone has not provided a clear separation
between trawlable and untrawlable seafloor (e.g., a

Fishery Bulletin 111(1)

threshold of 1.2 would result in a high classification
error rate).

Rugosity derived from the data collected with the
Simrad ME70 was a poor discriminator of trawlable
versus untrawlable seafloor, generally with lower val-
ues (e.g., smoother seafloor) in areas where the valida-
tion data from the SDC and ROV surveys indicate that
the seafloor is untrawlable. The areas that contained
high values of rugosity generally were dominated by
larger scale features: the ridgeline on the northern
edge of the bank, the sand waves in the southeast, or
the pockmarks in the southwest. It is likely that the
spatial resolution of the MBES was insufficient to pro-
vide a useful estimate of the rugosity level and that an
MBES with higher frequencies and higher resolution
might provide more useful results.

The oblique-incidence Sb alone provided a low er-
ror rate as a discriminator between trawlable and un-
trawlable seafloor. When combined with the other met-
rics, it was possible to slightly lower the error rate,
but an examination of the scatter plots in Figure 5 in-
dicates that the error rates were not been lowered in
any meaningful way. For example, the best-fit line that
discriminates between the combination of oblique-inci-
dence Sb and normal-incidence Sb shows that a com-
bination of high oblique-incidence Sb and low normal-
incidence Sh gives a better indication of untrawlable
seafloor than high oblique-incidence Sb on its own.
This finding is contrary to what the modeled seafloor
return (Fig. 2) would predict: high oblique-incidence Sb
and high normal-incidence Sb are a better predictor of
an untrawlable seafloor. Therefore, it is likely that the
marginal improvement in classification error rate with
these extra parameters combined is simply a result of
variations in the tails of the underlying data distribu-
tions. With only marginal improvements (5. 6-3. 8%) in
classification error rate when up to 4 parameters are
combined, with a hyperplane separating the 2 classes,
it is reasonable to choose the simpler approach of using
only the oblique-incidence Sb as a predictor of traw-
lable or untrawlable seafloor.

Conclusions

The results described here indicate that acoustic re-
mote sensing of substrate type with an MBES, and
oblique-incidence acoustic Sb in particular, offer useful
insight into whether the seafloor is untrawlable. This
conclusion is in qualitative agreement with the work
of Jagielo et al. (2003), who used seafloor backscatter
collected with a sidescan sonar as part of an a priori
assessment of trawlability (note that much of the sid-
escan record was collected at oblique incidence angles).
Whether these types of acoustic metrics can provide a
similar level of confidence regarding the distribution
of untrawlable seafloor in areas throughout the entire
Gulf of Alaska needs to be determined. If successful on
a wider scale, this type of acoustic remote sensing can

help refine the interpretation of bottom-trawl surveys.
In particular, techniques such as those described here
could increase the accuracy in identification of areas
with seafloor characteristics similar to areas where
bottom-trawl surveys of rockfish were conducted (i.e.,
areas where results frojm the trawl surveys can be ap-
plied). As a result, the precision and accuracy of bio-
mass estimates from bottom-trawl surveys and their
resultant stock assessments would be improved.

Acknowledgments

Support for this work was provided by the North Pa-
cific Research Board (contribution no. 373). Additional
support for T. Weber was provided by NOAA (grant
NA05N0S4001153). We would like to acknowledge the
crews of the NOAA Ship Oscar Dyson and FV Epic Ex-
plorer for their help during data collection. We would
also like to thank M. Martin, D. Somerton, and W. Pal-
sson for their thoughtful reviews of this manuscript.

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Abstract — Jumbo squid (Dosidicus
gigas) and purpleback squid ( Sthe -
noteuthis oualaniensis) (Teuthida:
Ommastrephidae) are thought to
spawn in the eastern tropical Pa-
cific. We used 10 years of plankton
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samples from surface and oblique
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the eastern tropical Pacific over the
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vae were far more abundant in sur-
face tows (maximum: 1588 individu-
als) than in oblique tows (maximum:
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presence in both surface and oblique
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Manuscript submitted 18 April 2012.
Manuscript accepted 27 November 2012.
Fish. Bull. 111:78-89 (2013).
doi:10.7755/FB. 11 1.1.7

The views and opinions expressed
or implied in this article are those of the
author (or authors) and do not necessar-
ily reflect the position of the National
Marine Fisheries Service, NOAA.

Distribution of ommastrephid paralarvae in the
eastern tropical Pacific

Danna J. Staaf (contact author)1
Jessica V. Redfern2
William F. Gilly 1
William Watson2
Lisa T. Ballance2

Email address for contact author: danna|oy@gmail

1 Hopkins Marine Station of Stanford University
120 Oceanview Blvd

Pacific Grove, California 93950

2 Southwest Fisheries Science Center
National Marine Fisheries Service, NOAA
8901 La Jolla Shores Dr.

La Jolla. California 92037

Adult squid of the oceanic family
Ommastrephidae are active general-
ist predators and key prey for a wide
variety of marine fishes, birds, and
mammals. They are also the primary
targets of the world’s larger squid
fisheries (Nigmatullin et al., 2001;
Markaida et ah, 2005; FAO, 2011).
Many questions remain unanswered
about the reproduction and early life
history of these oceanic squid (Young
et ah, 1985; Boletzky, 2003). Logisti-
cal challenges impede direct obser-
vation of reproduction and develop-
ment in the wild, but the collection
of paralarvae in net tows often can
be used to elucidate ommastrephid
spawning grounds and the habitat
needs of early life stages (e.g., Oku-
tani and McGowan, 1969; Zeidberg
and Hamner, 2002).

Two ommastrephid species that
reproduce in the eastern Pacific are
Dosidicus gigas, the jumbo or Hum-
boldt squid, and Sthenoteuthis oual-
aniensis, the purpleback squid (Vec-
chione, 1999). The jumbo squid is
currently the target of the world’s
largest squid fishery (628,579 t in
2009 [FAO, 2011]), and commercial
interest in purpleback squid is grow-
ing (Zuyev et ah, 2002; Xinjun et ah,
2007). The adult ranges of these 2
species overlap in the eastern tropi-
cal and subtropical Pacific (Roper et

com

ah, 1984), but the location and ex-
tent of spawning grounds of either
species over this large region are
not well established. Paralarvae of
these species cannot be reliably dis-
tinguished morphologically; molecu-
lar techniques must be used (Gilly
et ah, 2006; Ramos-Castillejos et ah,
2010). When molecular identification
is not possible because of formalin
preservation or other limitations,
paralarvae in this broad geographic
region are generally assigned to the
“SD complex” IS. oualaniensis and D.
gigas [Vecchione, 1999]).

Ommastrephid paralarvae are
relatively rare off California (e.g.,
Okutani and McGowan, 1969; Wat-
son and Manion, 2011), and none
have been attributed to jumbo squid
or purpleback squid. Both species,
however, have been identified off the
Pacific coast of the Baja California
Peninsula (Hernandez-Rivas et ah1;
Ramos-Castillejos et ah, 2010). With-

1 Hernandez-Rivas, M. E., R. De Silva-
Davila, S. Camarillo-Coop, J. Grana-

dores-Amores, and R. Durazo. 2007.
Ommastrephid paralarvae during 1997-
1999 IMECOCAL cruises. Abstract in
California Cooperative Oceanic Fisheries
Investigations Annual Conference 2007,
Program and Abstracts; San Diego, CA,
2-28 November, p. 41. Calif. Coop.
Oceanic Fish. Invest., La Jolla, CA.

Staaf et at: Distribution of ommastrephid paralarvae in the eastern tropical Pacific

in the Gulf of California only the jumbo squid has been
reported to spawn (Gilly et ah, 2006; Staaf et ah, 2008;
Camarillo-Coop et ah, 2011), and, to our knowledge,
no other adult ommastrephid has been described from
this region, although adults of purpleback squid have
been reported from the area near the mouth of this
gulf (Olson and Galvan-Magana, 2002). In the south-
ern hemisphere, the Peru Current System has yielded
only jumbo squid paralarvae (Sakai et ah, 2008). In the
large intervening equatorial region, paralarvae of both
purpleback squid and jumbo squid are present (Oku-
tani, 1974; Ueynagi and Nonaka, 1993).

The data that form the basis of this knowledge were
collected through a variety of methods. Samples from
both the Pacific and Gulf coasts of the Baja California
Peninsula and from the Peru Current were collected
primarily during subsurface oblique tows with bongo
nets (Ramos-Castillejos et ah, 2010; Camarillo-Coop et
ah, 2011; Sakai et ah, 2008). By contrast, the central
region of the eastern tropical Pacific (ETP) has been
sampled extensively during surface tows with neuston
nets, yielding higher densities of paralarvae (Ueynagi
and Nonaka, 1993; Vecchione, 1999). In the ETP, densi-
ties can be extremely high, as in the case of more than
10,000 very small paralarvae of the SD complex from
a single surface tow conducted during the 1986-87 El
Nino (Vecchione, 1999). By contrast, the greatest num-
ber of SD-complex paralarvae reported from the Baja
California Peninsula is 20, collected with a bongo net
(Camarillo-Coop et ah, 2011).

Surface tows effectively sample only the top 10-20
cm of the water column, but subsurface oblique tows
typically sample from the surface to depths of about
200 m. Because oblique tows sample a broader, deeper
range of habitats than surface tows, discrepancies in
paralarval abundance and size between the 2 types
of tows may reflect different vertical habitat prefer-
ences at different stages of development. For example,
if recently hatched paralarvae exhibit a preference for
surface waters, surface tows would be far more effec-
tive at capturing these animals because oblique tows
spend very little time at the surface (10-20 cm). And
if paralarvae begin to occupy greater depths as they
grow, while their numbers decrease because of natu-
ral mortality, oblique tows would be likely to capture
fewer, larger individuals than would surface tows, as
has been seen for the ommastrephid Todarodes pacifi-
cus (Yamamoto et ah, 2002; 2007).

Although high surface abundances can be represen-
tatively sampled by surface tows, any narrow subsur-
face band of high abundance, as might occur at a pyc-
nocline, would be undersampled by oblique tows. How-
ever, a strong association of paralarvae with a subsur-
face feature in preference to the surface could still be
detected by a greater likelihood of capture in oblique
rather than in surface tows, as has been found for
the northern shortfin squid ( Illex illecebrosus ), which
shows a relationship with the subsurface interface be-

tween slope water and the Gulf Stream in the Atlantic
(Vecchione, 1979; Vecchione et ah, 2001).

Diel vertical migrations, typical of adult ommas-
trephids, also could drive different abundances in sur-
face and oblique tows. This result was found in loliginid
paralarvae (Zeidberg and Hamner, 2002), but the situa-
tion is less clear for ommastrephids (Piatkowski et ah,
1993; Young and Hirota, 1990). The few surface tows
during which paralarvae of northern shortfin squid
were collected in the Middle Atlantic Bight were con-
ducted at night (Vecchione, 1979) — a finding that could
indicate a nighttime migration to the surface, but the
numbers are too small to strongly support this idea. No
significant differences in paralarval abundance of pur-
pleback squid have been found between daytime and
nighttime tows in Hawaii (oblique and horizontal tows
from the surface to a depth of 200 m; [Harman and
Young, 1985]) or Japan (horizontal tows from the sur-
face to a depth of 200 m; [Saito and Kubodera, 1993]).

On cruises conducted by NOAA in the ETP, ecosys-
tem data (including plankton samples) from a large
geographic area have been collected regularly and ar-
chived for many years. In this study, we present the
first analysis of planktonic squid from this data set,
focusing on the ommastrephids jumbo squid and pur-
pleback squid. Our aims are 1) to compare surface and
oblique tows conducted at the same location and time
to determine differences in paralarval distribution and
abundance due to sampling method, 2) to address ques-
tions of species-specific depth preference and vertical
migration, 3) to uncover relationships between paralar-
val abundance and oceanographic features, and 4) to
use molecular techniques on a subset of samples to de-
termine whether the 2 species have distinct spawning
areas or habitat preferences within their range overlap.
Paralarval distribution is also contrasted with adult
distribution data, collected during the 2006 cruise, to
confirm that the study region is within the adult range
of both species and to enhance our understanding of
the ETP as a feeding and spawning area.

Materials and methods
Study area and data collection

The ETP, where the ranges of jumbo squid and purple-
back squid overlap, is defined by 3 large surface cur-
rents and 2 water masses (Fiedler and Talley, 2006;
Fig. 1A). The westward-flowing North and South Equa-
torial Currents derive from the temperate California
and Peru Currents, respectively. The Equatorial Coun-
tercurrent flows eastward from the western Pacific to
the coast of Central America. These currents define
2 water masses: Tropical Surface Water and Equato-
rial Surface Water, the latter cooler and fresher than
the former. Two smaller-scale oceanographic features
are prominent: 1) a distinct thermocline ridge at the
interface between the North Equatorial Current and

Fishery Bulletin 111(1)

Figure 1

Map of study area in our examination of the distribution of ommastrephid
paralarvae in the eastern tropical Pacific with (A) oceanography (after
Fiedler and Talley, 2006) and (B) sampling stations from cetacean and eco-
system assessment surveys conducted by the Southwest Fisheries Sci-
ence Center (NOAA) from 1998 to 2006. Two plankton tows, one each with
a manta and a bongo net, were conducted each evening approximately 2 h
after sunset. STSW=Subtropical Surface Water. TSW=Tropical Surface Water.
ESW=Equatorial Surface Water.

the Equatorial Countercurrent, nominally along 10°N
latitude (although the exact location varies season-
ally) and 2) the Costa Rica Dome, an area of thermo-
cline doming, nominally at 9°N latitude, 90°W longi-
tude, although this feature too varies in location and
degree of development through time, seasonally and
interannually.

The study area for this research
forms a polygon that circumscribes the
oceanic waters from the U.S. -Mexico
border west to Hawaii, and south to
central Peru. Cetacean and ecosystem
assessment cruises were conducted in
this region by the Southwest Fisheries
Science Center (NOAA Fisheries) from
late July to early December of 1998,
1999, 2000, 2003, and 2006 (Fig. IB),
with the University-National Oceano-
graphic Laboratory System (UNOLS)
research vessel Endeavor (1998), and
the NOAA Ships David Starr Jordan
(all years), McArthur (1998, 1999,
2000), and McArthur II (2003, 2006).
Plankton were sampled with 2 types
of net tows, conducted ~2 h after sun-
set each day, for a total of 979 manta
(surface) tows and 762 bongo (oblique)
tows over the 8-year period. On the
McArthur II in 2006, during one leg of
the cruise, medium-size jigs and rods
were used to fish for adult squid from
1 to 2 h after sunset.

Manta nets (Brown and Cheng,
1981) with 0.505-mm mesh were towed
for 15 min at a ship speed of 1. 0-2.0
kn, with all deck lights off. Bongo nets
(McGowan and Brown2; Smith and
Richardson, 1977), consisting of a pair
of circular net frames with 0.505-mm
or 0.333-mm mesh, were towed for a
15-min double oblique haul to a depth
of -200 m at a ship speed of 1. 5-2.0
kn. The net was lowered continuously
at about 35 m/min, held at -200 m for
30 s, and then was retrieved at about
14 m/min, with the angle of stray al-
ways maintained at -45°.

Volume of water filtered during
manta and bongo tows was estimated
with a flowmeter suspended across the
center of the net. Contents of the co-
dends were preserved in 5% formalin
buffered with sodium borate. In 2003
and 2006, the contents of one codend
of each bongo tow were frozen in sea-
water at -20° C, and the contents of
the other were preserved in 5% forma-
lin. Also in 2006, the contents of one
codend of every fourth bongo tow (38
samples total) were preserved in 70%
ethanol instead of formalin.

2 McGowan, J. A., and D. M. Brown. 1966. A new opening-
closed paired zooplankton net. Univ. Calif. Scripps Inst.
Oceanogr. Ref. 66-23, 56 p. Scripps. Inst. Oceanogr., Univ.
Calif, San Diego, CA.

Staaf et at: Distribution of ommastrephid paralarvae in the eastern tropical Pacific

Water column data were collected with conductivity-
temperature-depth (CTD) profilers 1 h before sunrise
and 1 h after sunset on each survey day and with ex-
pendable bathythermographs (XBTs) during daylight
hours at intervals of ~55 km. Samples of surface water
were collected in bottles during the CTD casts and in
buckets concurrent with XBT casts at depths from 1
to 3 m. Precruise calibration factors (fluorometer cali-
bration factor, F, and acid ratio of pure chlorophyll, x)
were used to calculate chlorophyll-a and phaeophytin
values from digital fluorometer readings of these sur-
face water samples. Sea-surface temperature (SST) and
salinity (SSS) were measured continuously (around the
clock) with a thermosalinograph while the ship was un-
derway. Details of the complete data set are available
in NOAA data reports (Philbrick et al., 2001, a-c; Am-
brose et al., 2002, a and b; Watson et al., 2002; Jackson
et al., 2004; 2008).

Sample processing

Cephalopods were removed manually from 654 bongo
(1998, 2000, 2003, 2006) and 784 manta (1998, 1999,
2003, 2006) samples. Bongo samples with >25 mL of
plankton were fractioned to -50% of the original sam-
ple volume before they were sorted. The absolute count
from each tow was divided by the volume of water
filtered during that tow, as computed from flowmeter
readings, to give paralarvae densities per cubic meter
(following techniques described in Kramer et al., 1972).

Adult and paralarva! specimens were identified by
morphological characteristics (Wormuth et al., 1992).
Adults were identified to species by the presence of
a fused funnel-locking cartilage in purpleback squid
and the absence of the fused structure in jumbo squid.
Ommastrephid paralarvae are known as rhynchoteu-
thions; their distinctive form is recognized easily by
the presence of a proboscis. For individuals missing
the proboscis or in which the proboscis already had
separated into tentacles, identification was based on
the characteristic inverted-T funnel-locking cartilage
of this family. When proboscis suckers were visible,
they were checked to separate individuals of the gen-
era Hyaloteuthis, Eucleoteuthis, and Ommastrephes
(enlarged, lateral suckers on proboscis) from individu-
als of the genera Dosidicus and Sthenoteuthis (equal-
size suckers on proboscis). Hyaloteuthis, Eucleoteuthis
and Ommastrephes are relatively rare in the ETP (all
the molecularly identified ommastrephids in this study
were Sthenoteuthis or Dosidicus', see also Yatsu3), and

3 Yatsu, A. 1999. Morphological and distribution of rhyncho-
teuthion paralarvae of two ommastrephid squids, Dosidicus
gigas and Sthenoteuthis oualaniensis, collected from eastern
tropical Pacific Ocean during 1997-preliminary report. In
Report of the Kaiyo Maru cruise for study on the resources of
two ommastrephid squids, Dosidicus gigas and Ommastrephes
bartramii, in the Pacific Ocean, during September 11-
December 24, 1997 (A. Yatsu, and C. Yamashiro, eds.), p.
193-206. Fisheries Agency of Japan, Tokyo.

only 9 specimens were tentatively identified as Eucleo-
teuthis and 2 specimens were tentatively identified as
Ommastrephes by proboscis suckers and photophores
(6 others were excluded from Dosidicus or Sthenoteuthis
but were too small to be assignable to the other 3 gen-
era). Therefore, any specimens damaged such that the
terminal suckers were not preserved were assigned to
the SD complex. The presence of paralarvae from other
cephalopod families was recorded, but these specimens
were not identified to genus or species, or counted.

Morphological techniques for reliable differentiation
between paralarvae of jumbo squid and purpleback
squid are not available. Wormuth et al. (1992) and
Yatsu3 used proboscis length and photophores as dis-
tinguishing characters, but the muscular proboscis can
extend and retract (Staaf et al., 2008), and reactions to
fixatives have not been quantified. Additionally, there
may be variability in ontogenetic timing of photophore
formation (Gilly et al., 2006). Ramos-Castillejos et al.
(2010) suggested several distinguishing indices that
used morphometric ratios; however, samples in this
study were prepared in different fixatives (ethanol
for jumbo squid and formalin for purpleback squid)
that can distort or shrink specimen proportions.
The efficacy of indices for diagnoses of individual speci-
mens of unknown species also were not tested. There-
fore, we attempted no species-level identification of SD-
complex specimens that were preserved in formalin.

Molecular identification of SD-complex ommas-
trephids from ethanol-preserved samples followed pro-
tocols described in Gilly et al. (2006). Two frozen bongo
samples were also sent to Hopkins Marine Station for
sorting and molecular identification. The frozen sam-
ples were selected on the basis of a high abundance
of ommastrephid paralarvae in the matching codend,
and they were sorted primarily to test whether it is
possible to reliably identify paralarvae from a frozen
plankton sample.

Mantle lengths (ML) of ommastrephid paralarvae
from 1998 manta and bongo tows were measured with
an ocular micrometer. For tows with 10 or fewer om-
mastrephids, all individuals were measured. For tows
with more than 10 ommastrephids, 10 individuals were
selected for measurement. Selection was arbitrary and
aimed to be representative; e.g., the largest (or small-
est) specimens were not always included.

Data analysis and modeling

We constructed a data set of ommastrephid paralarval
abundance and 5 in situ oceanographic variables: SST,
SSS, mixed-layer depth (MLD), temperature at thermo-
cline (TT), and surface concentration of chlorophyll-a
(CHL). MLD is defined as the depth at which tempera-
ture is 0.5°C less than SST (Fiedler, 2010). TT is tem-
perature at the depth of the thermocline as determined
by the “maximum slope by difference” method (Fiedler,
2010). MLD, TT, and CHL values were collected from
the station nearest the net tow; these data were used

Fishery Bulletin 11 1 (1)

only if the station was located within 18.5 km (10 nau-
tical miles) and was sampled within 12 h of the net
tow. SST and SSS were averaged over a 2-h window
centered on the time of the net tow. In total, 137 bongo
and 164 manta samples were discarded according to
these criteria, leaving 517 bongo and 620 manta sam-
ples. Many of the discards (56 bongo and 57 manta)
were collected aboard the McArthur in 2003, when the
thermosalinograph malfunctioned. Three outlier points
were also removed: an abnormally low value for each of
CHL and SST, and an abnormally high value for MLD.

Relationships between ommastrephid abundance
and oceanographic variables were explored with gener-
alized linear models in the R statistics package, vers.
2.1.1 (R Development Core Team, 2005). We used gen-
eralized linear models because of their utility in model-
ing relationships between cetaceans and oceanographic
habitat (Redfern et ah, 2006) and between cephalopod
paralarvae and oceanographic habitat off western Ibe-
ria (Moreno et al., 2009). Typical of marine survey
counts, our paralarval abundance data were overdis-
persed, with a high proportion of zeros and a few very
large samples. Therefore, we followed Aitchison (1955)
and Pennington (1983) in performance of a 2-step anal-
ysis, in which we separated the data into a binomial
presence and absence data set (hereafter referred to as
paralarval presence ) and an abundance data set that
included only stations at which paralarvae were pres-
ent (hereafter referred to as paralarval abundance). To
analyze paralarval presence, we used a binomial distri-
bution with a logit link; for paralarval abundance we
used a lognormal distribution. We used an automated
forward/backward stepwise approach based on Akaike’s
information criterion (AIC) to select the variables for
inclusion in the model.

Results

Abundance of paralarvae

Paralarvae of the SD complex were found in 781 of the
1438 formalin-preserved plankton samples. By type of
tow, 355 of 656 oblique bongo tows (54.28%) and 426
of 784 surface manta tows (54.34%) contained SD-com-
plex paralarvae. The greatest abundance in a single
manta tow was 1588 paralarvae versus 64 paralarvae
in a single bongo tow. SD-complex paralarvae taken in
bongo tows were distributed over a somewhat broader
geographical area than were those paralarvae captured
in manta tows (Fig. 2), but density of captured paralar-
vae was typically at least an order of magnitude great-
er in manta tows.

Size of paralarvae

Average mantle length in manta tows was 1.94 ±1.29
mm fn=779; range 0.7-15 mm ML) versus 1.86 ±1.0
mm (ra = 148; range 0.6—7 mm ML) in bongo tows. No

significant difference was found between these distri-
butions (1-way analysis of variance [ANOVA], P= 0.44).

Relationship of presence and abundance of paralarvae to
environmental variables and modeling

The stepwise approach for the presence models select-
ed SST, SSS, and TT as predictor variables for manta
data, and SST and MLD for bongo data (Table 1). The
decrease in the AIC values for these models and the
increase in the percentage of explained deviance came
primarily from SST for both bongo and manta tows,
with minimal contribution from MLD, SSS, and TT.
Therefore, SST emerged as the strongest predictor for
presence of SD-complex paralarvae, and the probability
of capture increased monotonically as SST increased
from 15°C to 32°C (Fig. 3).

Analysis of paralarval abundance, rather than pres-
ence, revealed no strong predictors (Table 2). For bongo
tows, the stepwise approach selected CHL, TT, and SST
in the final model (7.5% explained deviance). For manta
tows, CHL, SST, MLD, and TT were all selected (12.1%
explained deviance). There appears to be little relation-
ship between these variables and nonzero paralarval
abundance, which varied over a wide range of each en-
vironmental variable for both manta and bongo tows.

Species identification

In total, 97 SD-complex paralarvae were found in 12
of the 38 ethanol-preserved samples. Of these paralar-
vae, 81 were identified genetically as Sthenoteuthis
oualaniensis and 16 as Dosidicus gigas. Paralarvae of
purpleback squid were found over a much greater area
than paralarvae of jumbo squid (Fig. 4A). Eight om-
mastrephid paralarvae were removed from the 2 frozen
samples and identified genetically as purpleback squid.

Non-ommastrephid cephalopods were identified in
many of the tows, most commonly as taxa in the teu-
thid families Enoploteuthidae, Onychoteuthidae, Gona-
tidae, Chtenopterygidae, Cranchiidae, and Brachioteu-
thidae and in the octopod genera Argonauta and Tre-
moctopus; all have previously been reported from the
ETP (Ueyanagi and Nonaka, 1993; Vecchione, 1999).

Of the 129 adult squid captured in jigging sessions,
118 were jumbo squid and 11 were purpleback squid.
Jumbo squid adults were found primarily in the south-
ernmost sampling sites off Peru, but the few purple-
back squid adults were more evenly distributed (Fig.
4B).

Discussion

This study represents the most extensive sampling to
date in the ETP of paralarvae of jumbo squid and pur-
pleback squid, covering most of their broad equatorial
and subtropical region of range overlap in the Pacific
during a period of 8 years.

Staaf et a!. : Distribution of ommastrephid paralarvae in the eastern tropical Pacific

Paralarvae/m3
I 1 0—0. 1 6
I 1 0.16-0.25
| 1 0.25—0.3

[ I 0.3-0. 4
Dr: 0.4-0.55
r "I 0.55 -0.82
I 0 82-1 3
SI 1.3-2. 1

20 N

Figure 2

Abundance of paralarval purpleback squid ( Sthenoteuthis oualaniensis) and jumbo squid ( Dosidicus gigas) from ail
study years (1998-2006) for (A) manta (surface) and (B) bongo (oblique) tows conducted in the eastern tropical Pa-
cific. Paralarval abundance was interpolated by using inverse distance weighting with a cell size of 1° and a fixed
search radius of 5°.

Table 1

Generalized linear models used to relate the presence and absence of ommastrephid paralarvae in manta
(surface) and bongo (oblique) tows conducted in the eastern tropical Pacific in 1998-2006 to 5 in situ oceano-
graphic variables: sea-surface temperature (SST), sea-surface salinity (SSS), mixed-layer depth (MLD), tem-
perature at thermocline (TT), and surface-concentration of chlorophyll-a (CHL). A stepwise approach selected
SST, SSS, and TT for the final manta model; SST and MLD were selected for the final bongo model. Better-
fitting models have a higher percentage of explained deviance and a lower Akaike’s information criterion
(AIC) value.

Manta

Model

Deviance (%)

AIC

Null

913

SST x SSS x TT

18.8

748.1

SST x TT

18.5

748.5

SST x SSS

18.4

749.6

SSS x TT

12.7

801.6

SST

18.1

750.2

SSS

4.6

873.1

814.9

Bongo

Model

Deviance (%)

AIC

Null

710.3

SST x MLD

12.2

627.7

SST

10.6

637.1

MLD

0.2

711.1

Fishery Bulletin 1 1 1 (1)

</)

SST (°C) SST (°C)

Figure 3

Probability of finding paralarval purplebaek squid ( Sthenoteuthis oualaniensis ) and jumbo squid ( Dosidicus
gigas ) as a function of sea-surface temperature in samples from (A) manta (surface) and (B) bongo (oblique)
tows conducted in 1998-2006 in the eastern tropical Pacifc. All other variables were set to their median val-
ues. Dashed lines indicate standard error of the regression. Tick marks indicate raw binomial data.

both), abundance of paralarvae was much greater in
surface tows. High abundance in surface tows also has
been reported for other ommastrephids (Ueynagi and
Nonaka, 1993), and extremely high numbers of SD-
complex paralarvae have been captured in single sur-
face tows: 819 off Jalisco, Mexico4 and >10,000 in the

4 Palomares-Garci'a, R., R. De Silva-Davila, and R. Avendano-
Ibarra. 2007. Predation of the copepod Oncaea mediter-
ranea upon ommastrephid paralarvae in the mouth of the
Gulf of California. Abstract in Proceedings of the 1st inter-
national CLIOTOP symposium; La Paz, Mexico, 3-7 December.

Table 2

Generalized linear models used to relate nonzero abundance of ommastrephid paralarvae in manta (surface)
and bongo (oblique) tows conducted in the eastern tropical Pacific in 1998-2006 to 5 in situ oceanographic
variables: sea-surface temperature (SST), sea-surface salinity (SSS), mixed-layer depth (MLD), temperature
at thermocline (TT), and surface-concentration of chlorophyll-a (CHL). A stepwise approach selected SST,
MLD, TT, and CHL for the final manta model and SST, MLD, and CHL for the final bongo model. The re-
sulting percentage of explained deviance and the Akaike’s information criteria (AIC) value for these models
indicate that none of the oceanographic variables is a strong predictor of nonzero abundance.

Manta Bongo

Model

Deviance (%)

AIC

Model

Deviance (%)

AIC

Null

1341

Null

782

SST x MLD xTTx CHL

12.1

1303.8

SST x MLD x CHL

7.5

764.6

MLD x TT x CHL

11.3

1305

SST x CHL

6.9

764.8

SST x MLD x TT

11.1

1306

MLD x CHL

6.6

765.6

SST x TT x CHL

9.8

1310.9

SST x MLD

4.5

772.2

SST x MLD x CHL

9.5

1312.2

Vertical distribution of paralarvae

We found no difference in the size of paralarvae be-
tween surface (manta) and oblique (bongo) tows, in
agreement with Yatsu.3 These observations are not
consistent with an ontogenetic vertical migration to in-
creasing depths within the paralarval stage of develop-
ment, as proposed for Todarodes pacificus (Yamamoto
et al., 2002; 2007). This feature, therefore, may not be
common to all ommastrephids.

Although incidence of capture in surface and oblique
tows was nearly identical (54% positive samples in

Staaf et al Distribution of ommastrephid paralarvae in the eastern tropical Pacific

Figure 4

Geographic distribution and abundance of (A) genetically identified paralarvae and (B) morphologically
identified adult ommastrephids caught in the eastern tropical Pacific during surveys conducted in 2006.
The numbers at each station (small dot) represent the total number of individuals of purpleback squid
( Sthenoteuthis oualaniensis) (outlined in black) and jumbo squid ( Dosidicus gigas) (solid black) captured
at that station. At stations where numbers do not appear, no squid were caught.

ETP (Vecchione, 1999). The consistency of this result
seems surprising, because ommastrephid egg masses
are thought to occur near the pycnocline, typically
tens of meters deep, and not at the surface (O’Dor and
Balch, 1985). The only reported observation of an in
situ egg mass of jumbo squid was in the Gulf of Cali-
fornia at a depth of 16 m near the pycnocline (Staaf et
al., 2008). Presumably, this characteristic is common to
purpleback squid, but we are unaware of descriptions
of natural egg masses for this species.

Not only are egg masses of jumbo squid found at
depth, but paralarvae are negatively buoyant. Paralar-
vae in the laboratory can swim to the surface but sink
as soon as they stop swimming (Staaf et al., 2008); this
negative buoyancy indicates that surface tension is in-
sufficient for passive retention. We can only assume
that purpleback squid paralarvae share this trait, and
that tissue density of wild paralaravae is similar to
laboratory-reared animals.

A preferred surface habitat, in which maintenance
of position requires significant energy expenditure,
strongly indicates that some benefit is derived from
this behavior; the benefit may be access to increased

food quantity or to food of higher nutritional value
(Yamamoto et al., 2007). Nothing is known of the diet
of jumbo squid paralarvae, but amphipods, copepods,
and crab zoeae have been found in the digestive tracts
of purpleback squid paralarvae (Vecchione, 1991);
these and other zooplankton, as well as phytoplank-
ton, also have been found in paralarvae of another
ommastrephid, lllex argentinus (Vidal and Haimovici,
1998). Furthermore, a case has been made for the use
of dissolved and particulate organic material by om-
mastrephid paralarvae (O’Dor et al., 1985). At certain
times and in certain regions, oceanic surface waters
may have high concentrations of these foods. The depth
of the chlorophyll-# maximum in the ETP ranges from
60 to 90 m in open-ocean regions to near the surface
in coastal boundary regions (Pennington et al., 2006).

It would be valuable to examine the vertical distri-
bution of paralarvae with systematic oblique or hori-
zontal tows at a series of discrete depths through the
upper 100-200 m of the water column at a variety of
times in a given area. This approach would give a more
accurate picture of habitat use and of any association
with the subsurface chlorophyll-a maximum or acoustic

Fishery Bulletin 1 1 1 (1)

scattering layers. To our knowledge, such a dedicated
effort to address this problem has not been reported.

Oceanography

The number of both bongo- and manta-net tows that
contained paralarvae increased as SST increased from
15°C to 32°C (Table 1, Fig. 3). This increased paralarval
occurrence is consistent with the literature. Paralar-
vae of purpleback squid exhibit a preference for warm
temperatures (28-31°C) in waters off Japan (Saito and
Kubodera, 1993), and extremely large numbers of SD-
complex paralarvae in the ETP were captured in in-
dividual tows coincident with the 29°C SST isotherm
(Vecchione, 1999). In the Gulf of California, paralarvae
of jumbo squid are more abundant during the warm
months of June and September (SST of 27.7-29.4°C)
than during the cooler season of February and April
(SST of 15.3-18. 1°C) (Camarillo-Coop et ah, 2011). Be-
cause our surveys were conducted only between late
July and early December, we were unable to assess
seasonal variability in paralarval distribution.

We found no evidence for a decrease in paralarval
occurrence at the highest SST values, despite the fact
that embryonic development in vitro is optimal in the
range of 17-25°C and fails to proceed at 30°C (Staaf et
ah, 2011). The idea that paralarvae may be better able
than developing embryos to withstand warmer tem-
peratures would be consistent with a upward vertical
migration after hatching. If hatchlings promptly swim
from near the pycnocline up to warmer near-surface
water, where food may be more readily available, an
ontogenetic increase in temperature optima would be
advantageous. It also is possible that the upper ther-
mal limit for successful development of wild embryos
could be higher than the limit observed in laboratory
studies. Embryos studied in the laboratory, particularly
those embryos obtained through in vitro fertilization,
may perish at high temperatures because of microbial
infection, which could be inhibited in the wild by the
presence of natural egg jelly (Staaf et ah, 2011).

Peak abundances of SD-complex paralarvae ob-
served in our study were an order of magnitude lower
than the abundance levels reported during the 1986-87
El Nino (Vecchione, 1999). This discrepancy could be
due to chance in sampling or a real difference in abun-
dance. Among our study years, only in 2006 was an
El Nino observed, and it was weaker than the one in
1986-87. The other years of our sampling were either
in La Nina (1998, 1999, 2000) or neutral (2003) con-
ditions (http://ggweather.com/enso/oni.htm). Year was
included in our models as a potential explanatory dis-
crete variable, but it was determined not to be an infor-
mative predictor of paralarval abundance or presence,
indicating no difference between El Nino, La Nina, and
neutral years. However, the strong positive relation-
ship between paralarval occurrence and temperature
found in our study is consistent with Vecchione’s (1999)
hypothesis that the extraordinarily high paralarval

abundances in 1987 were related to the 3.5°C increase
in SST during El Nino.

Reduced upwelling during the 1986-87 El Nino led
to a 50% decline in chlorophyll-a in the region of high-
est paralarval abundance (Vecchione, 1999). Similarly,
in our study, ommastrephid paralarvae were not as-
sociated with upwelling zones or their resultant high
primary productivity. In general, zooplankton biomass
in the ETP tends to be greatest in the 4 major up-
welling regions — the Gulf of Tehuantepec, Costa Rica
Dome, Equatorial Cold Tongue, and coast of Peru (Fer-
nandez-Alamo and Farber-Lorda, 2006) — but ommas-
trephid paralarvae were not especially abundant in
any of these regions (Fig. 2). Indeed, we found no rela-
tionship between SD-complex paralarvae and primary
productivity, as measured by CHL or MLD (where the
thermocline is shallow, primary productivity tends to
be higher [Pennington et ah, 2006]).

Species-specific spawning area

Molecularly identified jumbo squid paralarvae have
been reported from the Gulf of California (Gilly et
ah, 2006), off the Baja California Peninsula (Ramos-
Castillejos et ah, 2010), off Peru (Wakayabashi et ah,
2008), and now, in this study, from the ETP. We found
that most molecularly identified paralarvae from the
ETP were purpleback squid (Fig. 4A), but most adult
squid captured by jigging were jumbo squid (Fig. 4B).
Although jigging capture rates may have been biased,
adult jumbo squid have also been found to outnum-
ber purpleback squid as prey items of the Dolphinfish
( Coryphaena hippurus) in the ETP (Olson and Galvan-
Magana, 2002). Despite this abundance of adult jum-
bo squid, we found jumbo squid paralarvae in only 2
samples, and these samples also contained paralarval
purpleback squid in appreciable numbers (Fig. 4A).
Neither the geographic locations nor oceanographic
features of these 2 sampling sites were distinct from
sites where only purpleback squid was found. There-
fore, we can say only that purpleback squid paralarvae
appear to be far more abundant than paralarvae of
jumbo squid because we have no way of assessing bias
in the capture rates of the 2 species during plankton
tows.

Species-level molecular identification of paralarvae
was possible in this study only with material from
oblique tows. If future work on material from surface
tows were to find a similar predominance of purple-
back squid, it would support the hypothesis that the
purpleback squid is the primary ommastrephid that
spawns in the ETR Although jumbo squid can spawn
in the ETP or subtropical fringes, its primary spawning
grounds may actually lie farther to the north, off the
Baja California Peninsula in both the Pacific (Ramos-
Catellejos et ah, 2010) and Gulf of California (Staaf
et ah, 2008; Camarillo-Coop et ah, 2011), and farther
to the south off Peru (Tafur et ah, 2001; Sakai et ah,
2008; Anderson and Rodhouse, 2001).

Staaf et al Distribution of ommastrephid paralarvae in the eastern tropical Pacific

This view clearly contrasts with the one originally
proposed by Nesis (1983) in which the jumbo squid
spawns in the ETP and then migrates to feed at higher
latitudes in both hemispheres. Available genetic analy-
sis instead indicates 2 separate breeding populations,

1 in the northern hemisphere and 1 in the southern
hemisphere (Staaf et al., 2010). If the preferred spawn-
ing habitat of jumbo squid is indeed subtropical to tem-
perate, rather than tropical, it could explain the divi-
sion into 2 populations, 1 breeding off Mexico and 1
breeding off Peru.

For future collections, we recommend preservation of
material from both oblique and surface tows in ethanol.
Although we were able to extract and identify paralar-
vae from frozen plankton samples, the technique has

2 drawbacks: 1) the difficulty of visual identification
of individual specimens in the thawed slurry and 2),
if the samples are to be sorted in more than one ses-
sion, the damage done to the entire sample by repeated
freeze-thaw cycles.

Conclusions

We found paralarvae in surface and oblique tows to be
of equal size, indicating that paralarvae of the 2 om-
mastrephid species jumbo squid and purpleback squid
do not engage in ontogenetic vertical migration at the
paralarval stage. Ommastrephid paralarvae were much
more abundant in surface tows than in oblique tows;
this finding may indicate an ecological advantage of
surface waters — perhaps, related to feeding. Models
selected SST as the strongest predictor of paralarval
presence in both surface and oblique tows; presence
was more likely at higher temperatures. Therefore,
warm surface waters appear to be the preferred habi-
tat of ommastrephid paralarvae in the ETP. Molecu-
lar identification of specimens from a small subset of
oblique tows showed that paralarvae of purpleback
squid far outnumbered those of jumbo squid in this
region. Adults of purpleback squid are broadly dis-
tributed in the tropics, whereas adult jumbo squid are
abundant in tropical, subtropical, and temperate wa-
ters and occasionally present in boreal waters. Results
from this study are consistent with the possibility that
the purpleback squid spawns primarily in the tropics,
and the jumbo squid spawns preferentially in subtropi-
cal or, perhaps, even temperate regions.

Acknowledgments

To the cruise coordinators, the net-towing oceanogra-
phers, the plankton-sorting students and contractors,
and the commanding officers and crew of the research
vessels, we offer our boundless gratitude. We also thank
P. Fiedler and staff at the Southwest Fisheries Science
Center for processing oceanographic data, M. Ohman
for providing ethanol-preserved samples and advice, A.

Townsend for oversight of sample processing, L. Loren-
zo for sample sorting, C. Elliger and Z. Lebaric for DNA
sequencing, G. Watters for project guidance. We are
also grateful for support from the Nancy Foster Schol-
arship Program of NOAA (to DJS) and the National
Science Foundation (OCE0526640 and OCE0850839 to
WFG).

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71:1019-1060.

Staging ovaries of Haddock (Melanogrammus
aeglefinus ): implications for maturity indices
and field sampling practices

Email address for contact author: katie burchard@noaa.gov

Department of Natural Resources Conservation
University of Massachusetts-Amherst
Amherst, Massachusetts 01003
Present address: Narragansett Laboratory

Northeast Fisheries Science Center
National Marine Fisheries Service, NOAA
28 Tarzwell Drive
Narragansett, Rhode Island 02882

Department of Biology

University of Victoria

Victoria, BC, Canada V8W 3N5

Marine Ecology and Technology Applications, Inc

23 Joshua Lane

Waquoit, Massachusetts 02536

4 Marine Resources Research Institute
South Carolina Department of Natural
Resources
217 Ft Johnson Rd
Charleston, South Carolina 29412

Abstract — We build on recent efforts
to standardize maturation staging
methods through the development
of a field-proof macroscopic ovarian
maturity index for Haddock (Me-
lanogrammus aeglefinus) for stud-
ies on diel spawning periodicity. A
comparison of field and histological
observations helped us to improve
the field index and methods, and
provided useful insight into the re-
productive biology of Haddock and
other boreal determinate fecundity
species. We found reasonable agree-
ment between field and histological
methods, except for the regressing
and regenerating stages (however,
differentiation of these 2 stages is
the least important distinction for
determination of maturity or repro-
ductive dynamics). The staging of
developing ovaries was problematic
for both methods partly because of
asynchronous oocyte hydration dur-
ing the early stage of oocyte matura-
tion. Although staging on the basis
of histology in a laboratory is gen-
erally more accurate than macro-
scopic staging methods in the field,
we found that field observations can
uncover errors in laboratory staging
that result from bias in sampling
unrepresentative portions of ovaries.
For 2 specimens, immature ovaries
observed during histological exami-
nation were incorrectly assigned as
regenerating during macroscopic
staging. This type of error can lead
to miscalculation of length at matu-
rity and of spawning stock biomass,
metrics that are used to characterize
the state of a fish population. The
revised field index includes 3 new
macroscopic stages that represent
final oocyte maturation in a batch
of oocytes and were found to be reli-
able for staging spawning readiness
in the field. The index was found to
be suitable for studies of diel spawn-
ing periodicity and conforms to re-
cent standardization guidelines.

Manuscript submitted 6 February 2012.
Manuscript accepted 30 November 2012.
Fish. Bull. 111:90-106 (2013).

The views and opinions expressed
or implied in this article are those of the
author (or authors) and do not necessar-
ily reflect the position of the National
Marine Fisheries Service, NOAA.

Katie A. Burchard (contact author)1
Francis Juanes2
Rodney A, Rountree3
William A. Roumillat4

An important component of the as-
sessment and management of any
fish stock is quantification of the
stock’s productivity, which is a func-
tion of survival, individual growth,
and reproductive success of a fish
population (Wootton, 1998; Morgan,
2008). There are several factors that
can be used to estimate the annual
reproductive potential of a fish stock,
including but not limited to sex ratio,
age and size at maturity, spawning
stock biomass, fecundity, and stock
recruitment estimates where egg
and larval viability are taken into
consideration (Jennings et ah, 2001;
Morgan, 2008). Regular monitoring
and data collection on reproduc-
tive potential, including estimation
of spawning stock biomass, age and
size at maturity, and fecundity, are
dependent upon the use of reproduc-
tive maturity indices from a sample
of the population (Tomkiewicz et ah,
2003).

Because the ability to accurately
determine reproductive maturity by
macroscopic examination of the go-
nads alone is fallible, the validity of
field reproductive indices has been

questioned (Hilge, 1977; Templeman
et al., 1978; Saborido-Rey and Jun-
quera, 1998; Vitale et ah, 2006). De-
termination of maturation stages in
the field has been criticized as not be-
ing dependable because different re-
productive phases may appear simi-
lar during gross staging of the gonad.
For example, estimates of spawning
stock biomass or mean length at ma-
turity will depend upon an accurate
distinction between adult fishes with
regenerating gonads and immature
fishes (Forberg, 1982; West, 1990).
Similarly, estimates of fecundity in
determinate-spawning species, such
as Atlantic Cod ( Gadus morhua ) and
Haddock, require accurate identifica-
tion of ovaries in prespawning stages
(Murua et al., 2003). Therefore, it is
important that the system used for
determination of maturity stage is
accurate and unambiguous (Brown-
Peterson et al., 2011; Lowerre-Barb-
ieri et al., 2011).

There have been considerable in-
consistencies in the definitions of
maturity stages of fishes among the
existing indices in the literature. For
example, O’Brien et al. (1993) defined

Burchard et ai.: Maturity indices and field sampling practices for staging Melanogrammus aeglefmus

a female developing ovary as “a mixture of less than
50% yolked eggs and hydrated eggs”; however, accord-
ing to Murua et al. (2003), the presence of hydrated
oocytes indicate that the spawning process has begun
and the gonad is in a “spawning” stage, where “oocytes
are either in migratory nucleus stage or hydration
stage.” This discrepancy between indices in the defini-
tion of a developing ovary could result in different esti-
mates of fecundity in determinate-spawning species for
which prespawnmg, when the most advanced oocytes
in an ovary are in the late vitellogenesis stage, is the
optimal phase in reproductive maturity for the collec-
tion of samples for accurate estimation of fecundity. If
sampling is conducted before this stage, all oocytes des-
tined to be spawned may not be developed and would
be left out, and, as a result fecundity would be under-
estimated. If samples are taken from females that have
already spawned, the number of eggs that have already
been released cannot be detected, an outcome that also
would result in an underestimation of fecundity.

Another important difference between the matura-
tion indices of Murua et al. (2003) and O’Brien (1993)
is the description of a resting ovary. The definition
of O’Brien (1993) was based on a description by the
NMFS (1989) and Kesteven (1960) and was similarly
defined by Waiwood and Buzeta (1989), Tomkiewicz et
al. (2003), and Vitale et al. (2006). All these authors
described the resting maturity stage as occurring af-
ter the spent maturity stage. Conversely, Murua et al.
(2003) described the resting stage as an in-between
batch state occurring before the spent stage, when
some hydrated oocytes from the previous batch may
remain and further batches of hydrated oocytes are
still to be produced. Therefore, there was a need for
greater consistency in definitions and standardization
in terminology of reproductive maturity stages of fish-
es. In a recent work by Brown-Peterson et al. (2011),
a great deal of effort was invested in providing such
standardization.

Although certain reproductive traits, such as ma-
turity phases, are universal among teleost fishes, the
temporal patterns of these traits vary among species
(Lowerre-Barbieri et al., 2011). Incorporation of tem-
poral components into standardized indices potentially
could produce more accurate staging results for each
species studied, as well as provide additional informa-
tion on the reproductive success of a species. A recent
study by Tobin et al. (2010), published after our sam-
pling was completed in 2006-07, identified the tim-
ing and microscopic changes in maturation events of
female Haddock as they transition from immaturity
to maturity between summer and winter. That study
provided evidence that Haddock commit to maturation
by October or November with the existence of corti-
cal-alveolar-stage oocytes in the ovaries. Knowledge
of this maturation commitment can allow research-
ers to confidently identify females as either immature,
skipped-spawner, or mature after November, improving
estimations of spawning stock biomass.

Haddock is a batch-spawning species with group-
synchronous ovary organization and determinate fecun-
dity (Clay 1989; Murua and Saborido-Rey, 2003). This
collection of reproductive traits is common in demersal
Northwest Atlantic fishes, including but not limited
to Atlantic Cod, Yellowtail Flounder ( Limanda ferru-
ginea), and Atlantic Halibut ( Hippoglossus hippoglos-
sus; see Murua and Saborido-Rey, 2003). The standard
number of yolked oocytes immediately before the onset
of spawning in a determinate-fecundity spawner can
be considered equivalent to the potential annual fecun-
dity of that fish (Murua et al., 2003). After the onset of
spawning, the individual will hydrate several batches
of yolked oocytes throughout the spawning season.

The purpose of our study was to develop a standard
field-proof, macroscopic ovarian maturity index for Had-
dock that is suitable for use in studies of diel spawn-
ing periodicity (Anderson, 2011) and conforms to the
recent standardization guidelines of Brown-Peterson et
al. (2011). Diel spawning periodicity has been widely
studied in marine fishes (e.g., Ferraro 1980; Walsh and
Johnstone, 1992; Wakefield, 2010) and provides details
on the chronology of reproductive processes in species.
It has been suggested that diel spawning periodic-
ity maximizes fish survival and reproductive success
(Ferraro, 1980; Lowerre-Barbieri, 2011). In addition to
support for the collection of field data on reproductive
stages, we also wanted the index to provide guidance
on sampling techniques for the collection of samples
for laboratory analysis. First, a staging method devel-
oped from unpublished observations and a review of
data published before our sampling in 2006-07 was
used to stage female Haddock ovaries in the field. The
resulting maturity index was then revised compared
with a laboratory histological staging method similar
to that of Tomkiewicz et al. (2003) for Atlantic Cod in
the Baltic Sea. New stages were assessed to determine
whether they could be used in future studies to exam-
ine diel patterns in spawning (Anderson, 2011). Finally,
the relative strengths and weaknesses of both the field
and laboratory approaches were assessed.

Materials and methods
Initial field and laboratory indices

A new field macroscopic ovarian maturity index for fe-
male Haddock was developed by building on previous
published indices (Homans and Vladykoy, 1954; Robb,
1982; Murua et al., 2003; Brown-Peterson et al., 2011)
and unpublished observations made in the field (Table
1). The index consists of 8 stages, progressing from im-
mature to regressing. To move toward use of standard
phraseology, the terminology follows Brown-Peterson
et al. (2011). It differs from previously published indi-
ces with the addition of 3 stages that represent early
to late progression of oocyte maturation (OM; Brown-

Fishery Bulletin 1 1 1 (1)

Table 1

Field index developed and used to stage the reproductive maturity of female Haddock (Melanogrammus aeglefinus ) caught in
the Gulf of Maine in 2006-07 during this study in which macroscopic methods in the field were compared with histological
methods in the laboratory. OM=oocyte maturation.

Stage

Abbreviation Description

Immature

Ovaries small and firm, about 1/8 the volume of the body cavity. Membrane thin and trans-
parent, gray to pink in color. Contents microscopic: Individual oocytes not visible to the
naked eye.

Developing

Ovaries larger and plump, about 1/3 to 1/2 the volume of the body cavity. Membrane red-
dish-yellow with numerous blood vessels. Contents visible to the naked eye and consist of
opaque eggs that give the ovaries a granular appearance.

Hydration stage 1

Ovaries well developed, reddish-yellow in color, at least 2/3 volume of body cavity. Mem-
brane opaque with blood vessels conspicuous. Contents consist mostly of yellow-looking
oocytes with <25% of the ovary containing larger translucent oocytes. A batch of oocytes in
the early stages of OM where oocytes start to hydrate.

Hydration stage 2

Ovaries well developed, reddish-yellow in color, at least 2/3 volume of body cavity. Mem-
brane opaque with blood vessels conspicuous. Visible surface of the ovary consists of 25-
50% larger translucent oocytes. Further progression of a batch of eggs in OM.

Hydration stage 3

Ovaries well developed, reddish yellow in color, at least 2/3 the volume of body cavity.
Membrane opaque with blood vessels conspicuous. Visible surface of the ovary consists
of 50-75% larger translucent oocytes. Ovaries may appear a little flabby, indicating the
previous release of batch! es) of eggs. Final stages of the maturation of a batch of oocytes
before a spawning event.

Ripe and running

Ovaries very large, over 2/3 the volume of the body cavity. Contents consist of mostly large,
translucent eggs. Eggs running freely with little to no pressure on the abdomen.

Regressing

Ovaries soft, and flabby, about 1/4 the volume of the body cavity. Membrane thick and
tough, purplish in color, and bloodshot. Contents empty, few eggs remain, giving the gonad
a patchy appearance.

Regenerating

Ovaries small and firm. 1/6 the volume of the body cavity. Membrane thin but less trans-
parent than an immature ovary, yellowish-gray in color. Contents microscopic, opaque.

Peterson et al., 2011) on the basis of the percentage of
hydrated oocytes present (HI, H2, H3; Table 1, Fig. 1).

During observations of mature female Haddock
ovaries, we noticed that many of them had varying
numbers of hydrated oocytes. We did not find an ovar-
ian maturity index in the literature that categorized
the progression in percentage of hydrated oocytes in
a gonad. We were interested in whether the increase
in percentage of hydrated oocytes was detectable over
time and whether these stages may aid in examination
of diel reproductive periodicity (Anderson, 2011).
Hydration stage 1 (HI) is an ovary where a batch of
oocytes is in the early phase of OM and when <25%
of that ovary’s visible surface contains translucent,
hydrated oocytes (Table 1).

Hydration stage 2 (H2) is an ovary where a batch of
oocytes is in the middle phase of OM and when 25-
50% of that ovary’s visible surface contains translu-
cent, hydrated oocytes (Table 1).

Hydration stage 3 (H3) is an ovary with a batch of
oocytes in a late phase of OM and when 50-75% of
the visible surface of that ovary contains translu-
cent, hydrated oocytes (Table 1).

We hypothesized that HI, H2, and H3 occur with
each batch of oocytes before it is spawned (Fig. 1). The

index also includes for each stage: 1) a macroscopically
derived ratio of ovary volume to body cavity volume,
similar to the ratio of gonad cavity length to body cav-
ity length that Robb (1982) included for some stages;
2) a physical description of the ovary membrane, as
Homans and Vladykoy (1954) included for some of the
stages; and 3) a grossly assessed oocyte development
description, included by Homans and Vladykoy (1954),
Robb (1982), and Murua et al. (2003) (Table 1).

The histological staging method was derived inde-
pendently of the macroscopic ovarian maturity index
(i.e., during analysis, field-based stages were not used
by laboratory personnel in development of histological
stages and vice versa), and it was based on previous
work of Tomkiewicz et al. (2003), Roumillat and Brou-
wer (2004), and Brown-Peterson et al. (2011) (Table 2).
To differentiate the processes of early versus later vitel-
logenic activity, 2 histological index stages (2.1 or 2.2)
were used to define developing ovaries (Table 2). Be-
cause Haddock are classified as possessing determinate
fecundity (Murua et al., 2003), all oocytes that will be
spawned during the upcoming season develop during
these 2 stages, leaving a group of primary oocytes as a
reserve for the successive spawning season. However,
the developing stages in the histological index (2.1 and

Burchard et al. : Maturity indices and field sampling practices for staging Melanogrammus aeglefmus

Immature

Regenerating

Regressing

Oocyte maturation
(OM)

Batch 2 J
* H3-_ H2

Interbatch period

OM re-occurs with
every batch before

a spawning event = Spawning event

Figure 1

The maturation cycle of the female Haddock ( Melanogrammus aeglefinus), including 3
hydration stages and an interbatch period, introduced and used during this study of meth-
ods for staging the reproductive maturity of Haddock sampled in the southwestern region
of the Gulf of Maine in the spring of 2006 and 2007. Hydration stage 1 (HI), hydration
stage 2 (H2), and hydration stage 3 (H3) represent early-to-late progression of final oocyte
maturation (OM) of a batch of oocytes, based on the percentage of hydrated oocytes pres-
ent. *=spawning event.

2.2) were grouped together as one developing stage
(2.0) when the histology results were compared with
the field results because those stages could not be dif-
ferentiated by macroscopic examination. Three phases
of spawning-capable (SC) ovaries were assigned in the
histological index as 3.1, 3.2, and 3.3 to differentiate
the process of early, middle, and late phases of OM:
early germinal vesicle migration (GVM) and germinal
vesicle breakdown (GVBD) (Table 2). The gross assess-
ments of HI, H2, and H3 are based on morphologically
distinct criteria that are corroborated by the histologi-
cal sections that effectively separate these stages from
each other (Table 2). Two histological index stages (4.1
and 4.2) were defined to categorize SC ovaries that
showed evidence of recent ovulation with the presence
of recent (4.1) or old (4.2) postovulatory follicles (POFs;
Alekseyeva and Tormosova, 1979; Saborido-Rey and
Junquera, 1998). POFs are ruptured empty oocyte cas-
ings left in the ovary after a spawning event (Table 2;
Alday et al., 2010; Saborido-Rey and Junquera, 1998).
If a sample contained POFs but also exhibited char-
acteristics of another stage, the alternative stage was
assigned with a note that the sample contained POFs
(e.g., if a sample primarily contained oocytes in stage

3.1 but also contained POFs, it was assigned to the 3.1
stage).

Field sampling

Commercial fishing vessels were chartered for 25 dedi-
cated survey trips in the spring of 2006 (15) and 2007
(10) to collect biological samples of Haddock in the
southwestern Gulf of Maine (National Marine Fisher-
ies Service Statistical area 514; Fig. 2). Surveys were
based on a fixed station design with sampling where
Haddock aggregations were known to previously exist.
Sampling was conducted during the known spawning
season of Haddock in the Gulf of Maine, between Janu-
ary and June (Brown, 1998). Haddock were identified
in the manner used bj' Collette and Klein-MacPhee
(2002).

Longlining was the preferred collection method
for samples because few discards would result. Ap-
proximately 19 m of longline was set and retrieved
3 times at each sampling location over a 12-h period
with the objective of having 2 consecutive trips repre-
sent sampling over a 24-h period (0100-0000 h; Table
3). Sets were conducted within specific 4-h time bins

Fishery Bulletin 1 1 1 (1)

Table 2

The reproductive maturity index developed and used in this study of staging methods for female Haddock (Melanogrammus
aeglefinus ) during histological analysis with analogous stages from the macroscopic field index. Histological definitions were
based on criteria of Brown-Peterson et al. (Table 2 in 2011) CA=cortical alveolar; GVM=germinal vesicle migration; GVBD=
germinal vesicle breakdown; NA=not applicable; OM=oocyte maturation; POF=postovulatory follicle; SC*=spawning capable,
actively spawning subphase; Vtgl=primary vitellogenic; Vtg2=secondary vitellogenic; Vtg3=tertiary vitellogenic.

Histology

Stage

Macroscopic

Histological description

Immature
Developing (early

1.0

Small ovaries, only oogonia and primary growth oocytes present. Ovary wall
thin, no muscle bundles evident.

developing subphase)

2.1

Only primary and cortical alveolar oocytes present.

Developing

2.2

Primary growth, CA, Vtgl and Vtg 2 oocytes present.

SC* early GVM

3.1

Predominance of Vtg3 and early OM and beginning of GVM, yolk coalescence
beginning. Few germinal GVBD oocytes observed, although some hydrated
oocytes present.

SC* GVM

3.2

Both early and late stages of GVM oocytes, obvious yolk coalescence occurring.
Greater abundance of GVBD oocytes seen. Increased number of hydrated oo-
cytes present.

SC* GVBD

3.3

Predominance of GVBD oocytes, many with complete yolk coalescence. Many
hydrated oocytes present — immediately before ovulation.

SC recent POF

4.1

Many recent POFs present, showing few signs of degeneration. Otherwise ad-
vanced oocytes consist most noticeably of Vtgl-Vgt3 oocytes.

SC older POF

4.2

Only older POFs present with advanced structural degeneration. Advanced
oocytes consist of Vtgl-Vgt3 oocytes.

Regressing

5.0

Only spawning residue (old POFs) and primary growth oocytes remain in the
ovary. Spawning effort for season ceased.

Regenerating

6.0

Only primary oocytes remain in small ovary. Ovarian wall thickened, muscle
bundles present.

(0100-0500 h, 0500-0900 h, 0900-1300 h, 1300-1700
h, 1700-2100 h, 2100-0000 h EST) to examine diel
periodicity in reproductive maturity (Anderson, 2011).
Each longline was fished with 150 to 400 circle hooks
set 2 m apart for an average soak time of 2 h. The
number of hooks fished per line on each trip was de-
pendent on the success of catching Haddock that day.
With the intent of sampling at least 50 Haddock from
each longline set, the number of hooks was increased if
the sample size was not reached or decreased if more
fish than were needed were caught.

All Haddock were measured by fork length (FL,
±1 mm) and examined externally for signs that indi-
cated if they were in the ripe and running maturity
stage (classified RR; Table 1). Ovaries were classified
as RR when eggs were observed to be running freely
from females with little pressure applied to the abdo-
men. The first 50 Haddock in each set were sacrificed
to determine the stage of development of the gonads. If
a fish ovary was observed to be ripe and running, its
sex and maturation stage could be determined with-
out excisions, and it was automatically classified as RR
in the field. A subsample of the 50 sacrificed female
Haddock that represented all reproductive stages from
each longline set was labeled and reserved on ice. Fish
from each of the following length bins were collected
from each set if possible to have representation from as

many cohorts as possible: 30-40 cm, 40-50 cm, 50-60
cm, and >60 cm FL.

Laboratory methods

Samples were processed in the laboratory within 24
h of the end of each trip. Total weight (±0.1 kg) and
ovary weight (±0.01 kg) of each individual were re-
corded. Macroscopic maturity stage of all samples was
re-examined by the same field examiner. Digital pho-
tographs of whole ovaries were taken from a random
subsample of each stage in the field index. To deter-
mine the accuracy of macroscopic maturity staging per-
formed with our maturation index, histological analysis
was conducted on tissue samples of a subsample of 169
ovaries from 1706 macroscopically classified fish repre-
sentative of all 8 stages.

All histological tissue samples were taken from
the forward right lobe of each ovary. It was assumed
that this approach was appropriate because, according
to Robb (1982), Haddock ovaries are homogeneous in
structure throughout both lobes with oocytes present in
various stages from the walls to the center of the ovary.
Samples of 10-g tissue sections were fixed for at least
14 days in 10% neutral buffered formalin before they
were transferred to 50% isopropyl alcohol. Samples
were processed with standard histological procedures

Burchard et al Maturity indices and field sampling practices for staging Melanogrammus aeglefinus

70°12'W

! ! Western Gulf of Maine Closure

□ Stellwagen Bank National Marine Sanctuary

Figure 2

Map of the locations where mature female Haddock (Melanogrammus aeglefinus) were
sampled in the southwestern region of the Gulf of Maine in the spring of 2006 and
2007 for for staging reproductive maturity.

(Humason, 1972) through a graded ethanol series, em-
bedded in paraffin, and sectioned at 6 p. Tissues were
stained with Gill’s hematoxylin and counterstained
with eosin-Y. Ovary samples were classified by the oc-
currence of specific histological features that represent
progressive oocyte maturation stages (Brown-Peterson
et ah, 2011) (Table 2). The most progressive feature ob-
served in each sample was used to assign the appropri-
ate stage. Photomicrographs were taken of a random
subsample of stained tissue for each field index stage.

Statistical analysis

A contingency table was used to compare the results
between the macroscopic staging methods used in the

field and the histological staging methods used in the
laboratory (Table 4). The table cell where the 2 equiv-
alent stages cross shows the number of samples for
which the data from the 2 methods agreed. Because
the 2 indices were developed independently, 2 differ-
ent types of percent agreement were calculated. One
type was derived by dividing the number of samples
for which the 2 methods agreed by the field stage
sample size (last row in Table 4). The second type
of percent agreement was calculated by dividing the
number of samples for which the 2 methods agreed
by the histological stage sample size (last column
in Table 4). We did not have enough observed frequen-
cies in each cell to perform a chi-square statistical
analysis.

Fishery Bulletin 111(1)

Table 3

Dates of trips during which longlines were set and re-
trieved in the southwestern region of the Gulf of Maine
in the spring of 2006 and 2007 to collect samples of fe-
male Haddock (Melanogrammus aeglefinus) over a 12-h
period with the objective of having 2 consecutive trips
represent sampling over a 24-h period.

24-h period

Year

Sampling dates

2006

3/12, 3/28, 3/31

2006

4/7, 4/10, 4/28

2006

4/30, 5/4, 5/8

2006

5/8, 5/16

2007

3/26,3/31,4/10

2007

4/10, 4/21, 4/24

2007

5/1, 5/22

2007

5/24, 5/30

Results

The results of each stage are formatted to explain both
types of percent agreement as a function of each of the
two staging methods. For each stage, the results of the

macroscopic field staging method are presented first,
followed by the results of the histological laboratory
staging method.

All 6 ovaries classified as immature (I) with the field
index were also classified as the equivalent histological
stage (1.0) in the laboratory. In contrast, all but 2 of
the 8 samples classified as I (1.0) with the laboratory
staging method were also classified as I with the field
index (Table 4). Two samples classified as 1.0 in the
laboratory were classified as regenerating (RE) with
the field index.

Only 4 of the 9 ovaries classified as developing (D)
with the field index were also classified as developing
(2.0) with the laboratory staging method (Table 4). Two
of the remaining ovaries classified as D with the field
index were classified as the adjacent histological stage
3.1, and 2 samples contained early POFs (stage 4.1)
and 1 sample contained late POFs (stage 4.2). In con-
trast, 7 of the 12 ovaries classified as 2.0 in the labora-
tory were classified as the adjacent HI with the field
index, and 1 sample was classified as RE.

Twelve of the 32 ovaries classified as HI with the
field index were also classified as the equivalent his-
tological stage 3.1 (Table 4) in the laboratory. Seven of
the ovaries classified as HI with the field index were

Table 4

Contingency table showing the results from the cross classification between the histological maturity stag-
es (columns) and the field maturity stages (rows) in the indices used in this study of methods for staging
the reproductive maturity of female Haddock ( Melanogrammus aeglefinus). The gray squares represent
where the cross classification is expected to have the highest frequencies of agreement. n=sample size;
PA=percent agreement; NA=not applicable. If NA was used in place of PA, then that stage was not expected
to agree with any of the opposing index stages.

Maturity-index stages based on field examination

'&)

-C

1.0

75%

2.0

31%

3.1

75%

3.2

72%

3.3

39%

4.1

4.2

5.0

19%

6.0

92%

100%

44%

38%

64%

88%

33%

36%

-a

Burchard et at: Maturity indices and field sampling practices for staging Melanogrammus aeglefmus

classified as the adjacent histological stage 2.0, 2 ova-
ries were classified as 3.2, and 5 ovaries were assigned
as 3.3. One Hl-classified ovary contained early POFs,
and 5 HI ovaries contained late POFs. In contrast, 2 of
the 16 samples classified as 3.1 in the laboratory were
classified as the adjacent D stage with the field index,
1 sample was classified as H3, and 1 sample was as-
signed as regressing (S).

Twenty-one of the 33 ovaries classified as H2 with
the field index were also classified as the equivalent
histological stage 3.2 in the laboratory (Table 4). Nine
H2-classified ovaries were classified as the adjacent
histological stage 3.3. One ovary contained early POFs,
and 2 ovaries contained late POFs. In contrast, 4 of
the 29 ovaries classified as the 3.2 stage in the labo-
ratory were classified as the adjacent field stages (HI
and H3), and 4 of those ovaries were classified as S.

The H3-classified samples were most frequently
classified as the equivalent histological stage 3.3 (n- 22;
Table 4). Two H3-classified ovaries were classified as
the adjacent histological stage 3.2, and 1 ovary was
classified as 3.1. In contrast, 35 of the 57 ovaries classi-
fied as the histological stage 3.3 were classified differ-
ently with the field index, with most ovaries classified
as H2 (n=9) or RR (n= 17).

All but 2 of the ovaries classified as RR («=17) in
the field were classified as the histological stage 3.3
(Table 4). The 2 remaining ovaries were classified as
the histological stages 4.2 and 5.0.

Four of the 12 ovaries classified as S with the field
index were assigned the equivalent histological stage

5.0 (Table 4). Four additional ovaries classified as S
with the field index were classified as the histological
stage 3.2, and 2 ovaries were assigned as 3.3, 2 ova-
ries as 3.1, and 1 ovary as 6.0. In contrast, most of
the 21 ovaries assigned to the histological stage 5.0
in the laboratory were classified as RE with the field
index (/? = 16, 76%); however, 1 ovary was assigned as
H3 (Table 4).

Twelve of the ovary samples classified as RE with
the field index were classified as the equivalent histo-
logical stage 6.0 (Table 4). Sixteen samples classified as
RE with the field index were classified as the adjacent
histological stage 5.0 in the laboratory. Two additional
samples classified as RE in the field were classified as
histological stage 3.3, and 2 samples were classified as
1.0, and 1 sample was assigned as 2.0. In contrast, all
but 1 of the 13 ovaries classified as histological stage

6.0 in the laboratory were also classified as RE with
the field index.

A final composite ovarian maturity index was cre-
ated on the basis of the findings from this study (Table
5). Visual characteristics for both the whole ovary and
tissue sample were emphasized as was similarly done
by Tomkiewicz et al. (2003) for Altantic Cod in the Bal-
tic Sea. The final index consists of 7 stages of ovary
reproductive maturity distinguishable at sea. Table 5
includes for each maturity stage an image of the whole
ovary, a photomicrograph of equivalent histological tis-

sue, and both a macroscopic and microscopic physical
description of the ovary. Notes are included to aid the
user in correct macroscopic identification of each stage.
Sampling techniques for collection of tissue samples
are also included for problematic stages. On the basis
of comparison with the histological data, we concluded
that H3 and RR field stages are identical and grouped
them together as a single stage (H3). When we used
this revised H3 field stage, 39 of the 44 ovaries as-
signed as H3 were assigned the equivalent 3.3 histo-
logical stage.

Discussion

The utility of the field-based staging method for the
classification of fish reproductive maturity for fisher-
ies management is dependent on its biological accuracy.
The findings from this study highlight the problems of
development of an accurate error-proof field ovarian
maturity index on the basis of macroscopic observation.
However, a comparison of field-based and histology-
based staging methods of Haddock ovaries presented in
this study revealed the need to revise the field staging
methods to increase the accuracy of both staging meth-
ods. Although laboratory staging done on the basis of
histology is inherently more accurate than any macro-
scopic field staging method, there was indication that
field observations can reveal weaknesses in the labora-
tory approach because samples of the ovary taken for
histology are not always going to be representative of
the whole ovary. The strengths and weaknesses of both
approaches for each maturation stage are discussed
in the next sections, followed by recommendations for
correct identification of each stage and a description
of helpful sampling techniques for collection of tissue
samples of problematic stages.

Immature stage

The I stage in the field index was equivalent to the

1.0 histological stage (Tables 1 and 2). The only stage
mistaken for immature in the field was RE (Table 1).
In both stages, the ovary was small and firm. The RE
ovary appeared to be a little larger, less transparent,
and grayer in color in comparison with the pink color
of an immature ovary. However, in a young mature
fish or late immature fish, these differences were less
detectable. The imprecision in separation of immature
and regenerating mature females also has been en-
countered in staging Atlantic Cod ovaries (Tomkiewicz
et al., 2003). Comparison of the current mean length
at maturity for Haddock with the size of the specimen
may help support either maturity stage in the field, but
this criterion should not be relied on because length
at maturity can change over time (Saborido-Rey and
Junquera, 1998; Tobin et al., 2010).

In this study, the smallest Haddock caught was 35.5
cm FL, larger than the mean length at maturity re-

Fishery Bulletin 111(1)

corded for this species in the Gulf of Maine (34.5 cm;
Collette and Klein-MacPhee, 2002). The gear type used
in this study selected for larger fish, and we suspect
that smaller fish avoided the longline hooks. Although
to our knowledge skipped spawning (when a mature
individual skips a year of spawning) has not been ob-
served in Haddock, it is not uncommon in long-lived
iteroparous fishes, including Atlantic Cod (Jorgensen
et ah, 2006; Rideout et ah, 2006; Fig. 1). Therefore, we
could not have assumed that a female was immature
if it lacked signs of sexual maturity during the spawn-
ing season, as was assumed by Waiwood and Buzeta
(1989) because there is the possibility that the fish had
skipped spawning that year.

The use of microscopic analysis or histological ex-
amination of a tissue sample of the ovary was a reli-
able way to determine whether the ovary was imma-
ture or regenerating. Immature ovaries could be dis-
tinguished histologically from regenerating ovaries by
the diameter of the primary oocytes (W. Roumillat, per-
sonal commun.). Immature ovaries contained primary
oocytes that were equal in diameter, but regenerating
ovaries had primary oocytes that varied in diameter.
Additionally, the RE phase can be differentiated from
the I phase by the following features: RE ovaries 1)
have a thicker ovarian wall, 2) have more space, inter-
stitial tissue, and capillaries around primary oocytes,
and 3) have the presence of late-phase atresia and
muscle bundles (blood vessels surrounded by connec-
tive and muscle tissue) (Brown-Peterson et ah, 2011).
Because of the selectivity of the fishing gear for larger-
size fish and our limited sampling period, our study did
not provide adequate data to fully resolve macroscopic
differences between the RE and I stages. Further work
should focus on differentiation of a regenerating ova-
ry from an immature ovary with sampling conducted
further into the summer with less size-selective gear.
Proper identification of immature ovaries would great-
ly reduce the error in calculation of spawning biomass
estimates and improve accuracy of estimates of length
at maturity.

Developing stage

There was disagreement between D and early OM
phase, HI (Table 1). We observed that when a Had-
dock ovary began OM, some oocytes in the initial batch
completed the process before others within the same
ovulating batch. Although Haddock ovaries have been
reported to be homogeneous in structure throughout
all phases of maturity (Templeman et ah, 1978; Robb,
1982), our observations indicate that it is not homoge-
neous in structure during this very early phase of OM
(HI). This result is supported by Alekseyeva and Tor-
mosova (1979), who reported that formation of batches
occurs through asynchronous maturation of individu-
al groups of oocytes. The histological staging method
sometimes resulted in HI ovaries being misclassified
as D, likely because they were sampled during initial

OM of the first batch of oocytes for the season, when
there were no histological characteristics present to
indicate that prior batches had been spawned. Initial
spawning HI ovaries had so few fully hydrated oocytes
(because of the asynchronous maturation of the batch)
that collection of a small tissue sample from a central
location was sometimes unsuccessful in representing
all phases of oocytes present. As a single batch pro-
gresses through OM, evidence that spawning has been
initiated becomes more pbvious with GVM and yolk co-
alescence beginning in oocytes (Table 2; Lowerre-Bar-
bieri et ah, 2011). As the season progresses and the
ovary initiates OM in later batches of oocytes, a HI
tissue sample could be distinguished from a D tissue
sample by the presence of POFs.

The agreement between macroscopic and histologi-
cal staging for D and HI ovaries could be improved if
the method used to take tissue samples from the ovary
were modified. When ovaries are classified as HI in
the field, a larger tissue sample or samples should be
taken from multiple places in the ovary to improve the
accuracy of the histological results. Our observations
demonstrate that determination of the maturation of
an ovary based on histological examination alone may
not always be accurate. To reduce staging errors based
on histological analysis in future studies, it is recom-
mended that each tissue sample be documented with
a photograph of the whole ovary from which it was
extracted and with an estimate of the percentage of
hydrated oocytes observed on the visible surface of the
ovary.

Three ovaries classified as D in the field contained
POFs when analyzed histologically, and, by our defini-
tion, a D ovary could not have previously spawned that
season (Table 1; Fig. 1). Therefore, those specimens had
spawned at least one batch of eggs but had not yet
hydrated oocytes for the next batch, and the decrease
in volume of the ovary after spawning a prior batch of
eggs was not evident in field observations. A closely re-
lated species, Atlantic Cod, begins to hydrate a batch of
oocytes 1-2 days before spawning (Kjesbu, 1991). Final
oocyte maturation in cold-water marine fishes with pe-
lagic eggs generally lasts 1-2 days (Thorsen and Fyhn,
1996). Trippel and Neil (2004) reported that Haddock
had a mean interval of 5.4 days between batches of re-
leased eggs, and Hawkins et al. (1967) and Alekseyeva
and Tormosova (1979) reported an interval of 26-40 h.
These findings combined indicate that there is an in-
terbatch period between the spawning of a batch and
the next batch that is beginning to hydrate, a period
described by Murua et al. (2003) as the resting stage
(Fig. 1).

Consequently, there was the possibility that a ma-
ture ovary could be incorrectly classified as D in the
field if it was between ovulation events during this in-
terbatch period. Therefore, we concluded that it is not
always possible to be certain that an individual has
begun spawning for the season on the basis of macro-
scopic observation alone and this uncertainty can pose

Burchard et at: Maturity indices and field sampling practices for staging Melanogrammus aeglefinus

a problem for fecundity studies where ovary weight is
used as a factor in determining fecundity. For the same
reason, we also concluded that it is not possible to ac-
curately stage an ovary as D by macroscopic observa-
tion alone. This issue poses a problem for studies that
use gravimetric counting of vitellogenic oocytes and
oocyte density to determine fecundity. The D stage,
when the most advanced oocytes in the ovary are in
the late vitellogenesis phase, is the optimal stage from
which samples should be taken to determine fecundity.
Therefore, we recommend that ovary samples be col-
lected from fishes classified as D on the basis of mac-
roscopic observations to confirm through microscopic or
histological analysis that the ovary is in a prespawning
state.

Hydration stages

A challenge in the use of the field index was the subjec-
tive evaluation of the percentage of hydrated oocytes
in an ovary that was used to assign the consecutive
HI, H2, and H3 stages. Therefore, histological samples
were often assigned to a stage adjacent to the stage
that was reported in the field. There were 5 instances
where an ovary was macroscopically classified as HI
with the field index but microscopically classified as
the histological stage 3.3. This difference in staging
was likely due to some variation in individual and tem-
poral batch fecundity (Trippel et al., 1998). However,
this error was rare and the hydration stages were cor-
rectly staged consistently enough that we do not con-
sider this misclassification problematic in identification
of the correct hydration stage for the purpose of assess-
ing diel reproductive patterns.

The histology-based laboratory staging method un-
derestimated the HI stage because the ovary typi-
cally appears to be heterogeneous during this stage
and, therefore, was not adequately represented in the
tissue samples. An Hl-classified ovary could be incor-
rectly identified as D based on histological examination
under these conditions. However, as an ovary matured
further, the oocytes appeared to hydrate in unison and
evenly throughout the ovary and nuclear migration
and globule yolk coalescence became more evident.
These criteria reduced the bias in the sampling method
in later phases of HI and eliminated it in later stages
H2 and H3.

Histological analysis verified that H3-stage ova-
ries were in a state where the next batch of oocytes
to be spawned were in final OM phase (GVBD), with
most oocytes fully hydrated. This consistent result is
important because both the field H3 and histological
3.3 stages can be confidently used to identify spawning
readiness, and, therefore, we concluded that they will
be well suited for use in studies of diel spawning peri-
odicity in Haddock (Anderson, 2011) and other fishes.

Ripe and running stage

When the ovaries of RR females were examined mac-
roscopically, they exhibited characteristics of the H3
stage. Furthermore, the tissue samples from these ova-
ries were classified as 3.3 (SC GVBD; Table 2) with
histology-based methods. On the basis of results from
the histological analysis conducted on ovaries classified
as RR in the field and from the portion of the RR ovary
full of hydrated oocytes during macroscopic observa-
tion, we decided to combine the RR and H3 field stages
into a single stage in the final index (H3; Table 5).

Use of the RR field stage proved problematic be-
cause of the sampling method, and we recommend cau-
tion in its use in future studies. Homans and Vladykoy
(1954) reported that female Haddock stop feeding dur-
ing spawning — behavior that would make it difficult
to catch actively spawning fish with baited gear and
possibly result in an underestimation of RR females in
the population. In addition, RR may be overestimated
because of premature ovulation induced by stress or
barotrauma. It is hypothesized that the barotrauma
caused by forcing specimens to ascend to the surface
from an average depth of 90 m during sampling can
cause premature ovulation of hydrated oocytes. An
increased level of cortisol in fishes is an indication of
severe stress, but it is also involved in the natural pro-
cess of ovulation (Billard et al., 1981; Wendelaar Bon-
ga, 1997). The 2-h average soak time of the hooks in
this study could have been enough time for the stress
response to induce ovulation in an H3-stage fish before
it landed on board the fishing vessel.

For the same reason, histological stage 4.1 may be
overestimated, because the premature ovulation caused
by barotrauma results in POFs appearing before they
normally would. We concluded that it is difficult to
catch a Haddock in the act of spawning, especially with
baited hooks; therefore, use of H3-stage fish to estimate
spawning readiness would be more accurate. However,
the practice of macroscopically staging a RR Haddock
through application of pressure to the abdomen and
observation of the excretion of hydrated oocytes is a
method that can be used to classify a female as spawn-
ing ready without need to sacrifice the fish.

Regressing stage

The S ovary stage was the most problematic for macro-
scopic identification. The regressing condition is partic-
ularly difficult to detect in a species such as Haddock
with asynchronous development, where batches of eggs
are spawned multiple times over a prolonged season
(Hickling and Rutenberg, 1936; West, 1990). Species
with determinate fecundity complete a spawning sea-
son by the maturation and spawning of the entire co-
hort of oocytes developed that year. When only a single
batch of oocytes was left in the ovary to be spawned, it
was termed “last spawn.” This stage was evident only
during histological analysis. Of the ovaries classified

100

Fishery Bulletin 1 1 1 (1)

Table 5

The final female reproductive maturity index developed from findings with the macroscopic and microscopic method for
staging the maturity of female Haddock ( Melanogrammus aegleftnus).

,t jv.ii ^ Sij

Immature (I)

Macroscopic: The ovary is small and firm, and approximately 1/8 the volume of the body
cavity. The membrane is thin, transparent, and gray to pink in color. Individual oocytes
are not visible to the naked eye.

*Note: This stage can look similar to a resting-stage ovary. Use of microscopic analysis
or histology on a tissue sample of the ovary may be the only way to determine that the
ovary is immature and not resting.

Microscopic: The ovary contains germ cells, oogonia, and primary oocytes. The ovary
wall is thin and the primary oocytes vary little in diameter. No muscle bundles can be
seen. The nucleus is relatively large with the most advanced oocytes having peripheral
nucleoli (magnification lOOx).

Developing (D)

Macroscopic: The ovary is plump and approximately 1/3 to 1/2 the volume of the body
cavity. The membrane is reddish-yellow and has numerous blood vessels. The contents
are visible to the naked eye and consist of opaque eggs, giving the ovaries a granular
appearance.

*Note: If hydrated oocytes are visible, the ovary should be classified as HI (see the next
stage below). Hydrated oocytes will be large in diameter and translucent in color. A large
tissue sample should be taken from all ovaries macroscopically classified as developing
and analyzed microscopically to confirm that postovulatory follicles are not present and
that the ovaries are in a prespawning state. It may be helpful to document the tissue
sample with a photograph of the whole ovary.

Microscopic: Primary and cortical alveoli oocytes, and primary and secondary vitellogenic
oocytes are present. There is no evidence of postovulatory follicles (magnification 40x).

in the field as S, 58% (N= 7) were classified as being in
1 of the 3 OM histological phases. The most plausible
explanation for this result, other than observational er-
ror, is that these particular specimens were maturing
the last batch of eggs to be spawned that season (last
spawn) and the ovary at this point had lost its rigid-
ness and, therefore, looked as though it was in the S
stage. Last spawn was observed in 8 (5%) of the his-
tological samples, 5 of which were classified as S in
the field. Last spawn also was observed in Haddock in
the North Sea (Alekseyeva and Tormosova, 1979). Near
the end of the spawning season, the ovary can lose its

rigidness, although it still has 1-2 batches of oocytes to
spawn and appears as S. The outside membrane thick-
ens, which increases the difficulty of staging the ovary
through examination of just the outside (Templeman et
ah, 1978). Staging on the basis of the flabbiness of the
ovary alone is not recommended, and the inside of the
ovary should be examined for hydrated oocytes. If any
oocytes during final oocyte maturation (OM) remain,
the ovary is most likely not in the S stage and could
be in last spawn. Histological examination of a sample
of an ovary can be an effective way to determine if an
ovary is regressing.

Burchard et al Maturity indices and field sampling practices for staging Melanogrammus oeg/efinus

101

Table 5 continued

Hydration stage 1 (HI)

Macroscopic: The ovary is well developed, reddish-yellow in color, and approximately 2/3
the volume of the body cavity. The membrane is opaque and has prominent blood vessels.
The contents consist mostly of yellow-looking oocytes and <25% of the ovary contains
large translucent (hydrated) oocytes.

*Note: In the early phase of the HI stage, the ovary is not visually homogeneous and
hydrated oocytes can be unevenly scattered throughout. If microscopic analysis will be
conducted on a subsample, take care to obtain a representative tissue sample that in-
cludes translucent, hydrated oocytes. Document with a photograph of the whole ovary if
possible.

Microscopic: There is a predominance of tertiary vitellogenic oocytes, with many oocytes
showing oocyte maturation, germinal vesicle migration and germinal vesicle breakdown.
A small percentage of oocytes (<25%) will have completed oocyte maturation and are hy-
drated. Postovulatory follicles may be present (magnification 100x).

Hydration stage 2 (H2)

Macroscopic: The ovary is well developed, reddish-yellow in color, and approximately 2/3
the volume of the body cavity. The membrane is opaque with blood vessels conspicuous.
The visible surface of the ovary consists of 25-50% of large translucent oocytes.

*Note: There are gradients between the consecutive HI and H2 stages as well as the H2
and H3 stages, where it is difficult to assign one or the other stage. In these cases, the
ovary is at a state where it is either close to entering the H2 stage or close to advanc-
ing to H3. In both cases the ovary is near if not in an intermediate phase of final oocyte
maturation and may be accurately classified as H2.

Microscopic: There is a predominance of oocytes showing germinal vesicle migration and
germinal vesicle breakdown. Approximately 50% of the advanced oocytes are hydrated.
Postovulatory follicles may be present (magnification 40x).

Regenerating stage

The histological results for RE stage ovaries reflected
the difficulty in distinguishing between a regenerating
and regressing ovary in the field, with 46% of the ova-
ries classified as RE in the field assigned as S during
histological analysis. The plausible explanation for this
result is observational error. As the ovary progressed
into the RE stage, it became easier to differentiate
from the S stage, but, because of the short sampling
period, it was difficult to differentiate between the 2
stages during the time when regenerating fish were
captured. For future studies, we recommend that sam-
pling be conducted from well before to well after the

known spawning season and that a photograph of each
ovary be taken for comparison with histology-based
staging results. Such documentation of the changes
observed in different phases, from spent to regressing,
could improve the ability to distinguish between these
2 stages. However, extension of the sampling period too
far into the fall and winter may make it more difficult
to distinguish the D and RE stages from spawning stag-
es (Tomkiewicz et al., 2003). Histological examination of
a sample of an ovary was an effective way to determine
if an ovary was in the RE stage.

If a regenerating ovary was observed from a fish
near or larger in size than the mean length at maturity
during the peak spawning period, it is possible that

102

Fishery Bulletin 111(1)

Tabie 5 continued

Hydration stage 3 (H3)

Macroscopic: The ovary is well developed, reddish-yellow in color, and approximately
2/3 the volume of the body cavity. The membrane is opaque with blood vessels conspicu-
ous. Greater than 50% of the visible surface of the ovary consists of large translucent
oocytes.

Microscopic: There is a predominance of oocytes showing germinal vesicle migration and
germinal vesicle breakdown. Greater than 50% of the advanced oocytes are hydrated.
Postovulatory follicles may be present (magnification 40x).

Regressing (S)

Macroscopic: The ovary is soft and flabby and approximately 1/4 the volume of the
body cavity. The membrane is thick and tough, purplish in color, and bloodshot. The
inside of the ovary is almost empty and few oocytes remain, giving the gonad a patchy
appearance.

*Note: Toward the end of the spawning season, the ovary loses its rigidness although it
still has 1-2 batch(es) of oocytes to spawn. Staging should not be based only on the flab-
biness of the ovary, and the ovary should be inspected internally. The ovary is likely not
yet spent if any hydrated oocytes remain.

Microscopic: An abundance of postovulatory follicles are present. Oogonia and primary
oocytes are evident. The ovary wall is thick, and muscle bundles are visible (magnifica-
tion 40x).

vM o A&i&L

§gr

Iff! ♦, ' w

it spawned much earlier that season or skipped that
year’s spawning season (Fig. 1). One mature regenerat-
ing female was observed during the peak of the spawn-
ing season. Skipped spawning is a response to various
physiological and ecological conditions (Jorgensen et
al., 2006) and often a trade-off between present re-
production and survival for future reproduction (Bull
and Shine, 1979; Rideout et ah, 2005). Because it is
not possible to determine the existence and frequency
of skipped spawning and its effect on recruitment, it
is difficult to determine spawning stock biomass and,
hence, difficult to conduct stock assessments and man-
age such species (i.e., stock-recruitment models may
overestimate recruitment and underestimate survival;
Rideout et ah, 2005).

Postovulatory follicles

POFs were commonly found in ovary samples classified
as HI, H2, H3, and S in the field, but these POFs of-
ten were in various phases of atrophy. The observation
of early and late phases of POFs in the same ovary
indicated that POFs from the 2 previous batches still
existed during the OM of the next batch to be spawned
(Table 2). Evidence indicates that the complete atro-
phy of a POF in Haddock could take up to 10 days,
considering that Haddock have an average interval of
5.4 days between spawned batches (Trippel and Neil,
2004), and that final oocyte maturation in marine fish-
es with pelagic eggs generally lasts 1-2 days and ends
with ovulation (Thorsen and Fyhn, 1996). The atrophy

Burchard et al.: Maturity indices and field sampling practices for staging Melanogrammus aeglefinus

103

Table 5 continued

Macroscopic: The ovary is small and firm, and approximately 1/6 the volume of the body
cavity. The membrane is thin but less transparent, yellowish-gray. Contents are micro-
scopic, opaque.

Microscopic: The ovary wall is thick. There is often indication of past spawning with rem-
nants of unabsorbed material. The ovary contains primary oocytes that vary largely in
diameter (magnification 100x).

Regenerating (RE)

*Note: If a resting ovary is observed from a fish greater in size than the mean length at
maturity during the peak spawning period, then it is probable that the fish skipped that

year’s spawning season.

of POFs occurs for the Spotted Seatrout (Cynoscion
nebulosus) in 24-36 h in water temperatures >2°C
(Roumillat and Brouwer, 2004) and for the Northern
Anchovy ( Engraulis mordax) in 48 h at 19°C (Hunter
and Macewicz, 1985). The atrophy of Haddock POFs
may take much longer because this species prefers to
spawn in cold temperatures (4-7°C; Overholtz, 1987) —
an actuality that may be widespread in boreal fishes.
The slow degeneration of POFs in cold-water species is
supported by Brown-Peterson et al. (2011) and noted
by Saborido-Rey and Junquera (1998).

Aging of POFs has been used in other species to de-
termine spawning frequency or duration of time since
the female last spawned a batch of eggs (Hunter and
Macewicz, 1985; Roumillat and Brouwer, 2004). No de-
finitive information on diurnal timing of spawning was
clear from our inspection of Haddock POFs because
none of them appeared to have been very recently cre-
ated. Fish collections were concentrated in an area
where active spawning took place, and those Had-
dock that had finished spawning may not have been
available for capture. Observation of many ovaries in
spawning condition that also showed many phases of
POF atrophy indicated that these residual tissues had
a very slow rate of atrophy and were of little use in
making accurate assessments of diel timing of ovula-
tion. A more advanced study of aging POFs in cold-wa-
ter species similar to the studies done for clupeiforms
by Alday et al. (2010) and Haslob et al. (2012) is need-
ed and would increase our knowledge on the timing of
spawning in cold waters.

There were no equivalent field index stages for the
histological stages 4.1 and 4.2. Samples classified as
4.1 or 4.2 were typically assigned to an ovary in a state

between the last batch of oocytes spawned and the next
batch to be spawned, a state that we did not attempt
to identify in the field. In ovaries of this state, no oo-
cytes for the next batch had yet progressed to OM and
the only oocytes present were in a vitellogenic devel-
oped phase equivalent to the resting stage described by
Murua et al. (2003). We found that this stage was not
easily or accurately ascertainable through macroscopic
observation of the ovary. A trained eye may be able to
recognize a degree of flaccidity of an ovary that has
spawned already. Many of the ovaries assigned as 4.1
or 4.2 exhibited characteristics of an ovary that was
classified as the D stage in the field. The overestima-
tion of the D stage in this study indicates the need to
conduct histology on a subsample of ovaries classified
as D stage in the field to assure there is no indication,
on the basis of the presence of POFs, that females thus
classified have started spawning that season.

Conclusions

Working independently, we came to the same conclu-
sion as Brown-Peterson et al. (2011): standardization of
maturation staging methods and terminology are need-
ed. Our study confirms the importance of these efforts
but extends them with the development of a new ovar-
ian maturity index specifically for examination of diel
spawning periodicity while using the maturation ter-
minology established by Brown-Peterson et al. (2011).

Comparison of macroscopic and microscopic observa-
tions of ovaries helped us to improve the initial field
index and sampling methods, as well as to provide use-
ful insight into the reproductive biology of Haddock.

104

Fishery Bulletin 111(1)

Noting the apparent longevity of POFs helped us un-
derstand the duration and cyclical process of OM in
this species and potentially other boreal or cold-water
fishes. Because reproductive maturation occurred over
a prolonged period of time, OM occurred throughout
3 distinct field stages (HI, H2, and H3) and histol-
ogy stages (3.1, 3.2, and 3.3). This finding supports
the conclusion of Alekseyeva and Tormosova (1979)
that Haddock exhibits asynchronous maturation of in-
dividual groups of oocytes. We believe that the asyn-
chronous maturation of oocytes in a batch results in
heterogeneous ovaries during early phases of OM and
can lead to misclassification of HI ovaries as D stage
in the field. However, Robb (1982) and Templeman et
al. (1978) previously reported that Haddock ovaries
are homogeneous in structure throughout all phases of
maturity. Studies of follicle size-frequency distributions
throughout OM are needed to confirm our observation
of apparent heterogeneity of ovaries during early matu-
ration to clarify how future studies should be modified
to ensure accurate staging in the field and laboratory.

Additional work should be focused on differentiation
of a regenerating ovary from an immature ovary. This
differentiation is the most important distinction in de-
termination of maturity or reproductive dynamics of a
stock because of the use of these numbers in estima-
tion of spawning stock biomass.

The timing of the sampling in this study, although
restricted, was focused around the known spawning
season of Haddock in the Gulf of Maine. This focus
likely increased the reliability of staging SC fish be-
cause the closer in time to the spawning season the
more developed the ovary becomes, as was observed
by Tomkiewicz et al. (2003). Alternatively, reliability
in staging SC fish in the fall and winter is tenuous
because ovary development is just beginning (Tomkie-
wicz et ah, 2003). Therefore, the optimal time to collect
data to be used to estimate spawning stock biomass
should span across the spawning season, and we cau-
tion against the use of SC data collected off season in
estimation of spawning stock biomass.

It is anticipated that the revised ovarian maturity
index (Table 5) presented in our study will be useful
to Haddock resource managers. The H2 and H3 stages
appear to be useful indicators of spawning readiness
for Haddock ovaries in the field. We suspect that the
progression of OM is detectable in other boreal spe-
cies with the same reproductive traits as Haddock and
that the later stages could also be used to examine diel
periodicity in these species. Although this index was
developed for studies on diel reproductive periodicity,
we feel it would also be useful for study of other short-
term temporal reproductive patterns related to tidal,
lunar, or solar zenith cycles. The revised field index in-
cludes pointers to help users stage ovaries and take ap-
propriate samples (Table 5). Although this revised field
index will improve accuracy in the determination of the
maturity stage of Haddock in the field, evidence has
shown that field indices alone may not be enough to

correctly classify a fish in problematic stages. However,
the observations in our study also demonstrate that de-
termining the maturation of an ovary by histological
examination alone may not always be accurate, high-
lighting the importance of field staging. In addition to
field staging with the index presented here, appropri-
ate tissue samples should be collected and analyzed
microscopically or histologically to verify problematic
stages, especially when field data are used in assess-
ment and management of ^a fish stock.

Acknowledgments

This publication is the result of research spon-
sored by The Massachusetts Institute of Technol-
ogy Sea Grant College Program, under National Oce-
anic and Atmospheric Administration grant number
NA060AR4170019 and project number 2005-R/RD-29.
The authors thank the cooperative work and generos-
ity of fishermen T. Hill, P. Powell, and J. Montgomery.
We also thank C. Goudey, S. Cadrin, and R. McBride
for project advice and support. The assistance of vari-
ous volunteers in the field and laboratory work is
appreciated.

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Fishery Bulletin 111(1)

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Errata

Page 355: Figure 4 should read as follows:

Fishery Bulletin tt0:344-360 (2012).
Barlow, Paige F., and Jim Berkson

Evaluating methods for estimating rare
events with zero-heavy data: a simulation
model estimating sea turtle bycatch in the
pelagic longlme fishery

Corrections:

Page 354. The last paragraph in the
right column should read as follows:

The GLMs only outperformed the
delta-lognormal methods in the
fully uniform scenario ( Turtles ,

J uniform7

Sets , ). In this spatial scenario, the

GLMs were the most accurate esti-
mation method, but they produced
more positive outliers. The co-occur-
rence clumping scenario (Turtles clump,
Sets . , „ ) was the only spa-

tial scenario in which the GLMs
did not produce more outliers than
the delta-lognormal methods. The
GLMs were biased lower than
the delta-lognormal methods in
the co-occurrence clumping scenario
( Turtle , , Sets . , ) and sets-

only clumping scenario (Turtles , ,

u r ° unilorm7

Sets . . ). No substantial differ-

clump-sets

ence was seen between GLM-P and
GLM-NB performance in any spatial
scenario.

Page 357. The third paragraph in the
right column should read as follows:

The GLMs were more accurate than
the delta-lognormal methods in the
fully uniform scenario (Turtles ,
Sets uniform^ because this spatial sce-
nario was the only one that did not
violate the GLM-P assumption that
counts are independent and randomly
distributed in space (McCracken 2004,
Sileshi 2006).

■'3-

-JU

-J

t~ —

D-s D-p P-p NB-p

C 4 L 4

r T I

D-s

D-p

rLrL

o 9

-L 4-

D-s D-p P-p NB-p

D-s D-p

Figure 4

Comparison of bycatch estimates to the total amount of bycatch simulated
to evaluate performance of estimation methods. The stratum-level delta-
lognormal method (D-s), delta-lognormal method for all sets pooled (D-p),
generalized linear model with Poisson error distribution for all sets pooled
(P-p), and generalized linear model with negative binomial error distri-
bution for all sets pooled (NB-p) were evaluated. Each of the 5 panels
corresponds to one of the spatial scenarios: ( A)=co-occurrence clumping
(Turtles , , Sets . , ), (B)=sets-only clumping (Turtles , , Sets ,

clump’ clump-turtles 7 J r- o uniform7 clump-

sets), (C ^independent clumping (Turtles c| , Setsdump sels), (D)=turtles-only
clumping (Turtles , , Sets , ), and (E)=fully uniform (Turtles , , Set-

sumform). Each of the plots within a panel corresponds to an estimation
method. The scale of the y-axes varies by rows of panels for display pur-
poses. The horizontal line at a relative error of zero marks where the
median of an unbiased estimation method should fall. Notches are placed
around the medians, and if the notches of 2 plots do not overlap, there is
strong evidence that those medians differ. The box of each plot includes
the first through third quartile. Whiskers extend to the most extreme
data point that is no more than 1.5 times the interquartile range from the
box. Small circles represent outliers. For purposes of display, in the panel
for the sets-only clumping scenario (Turtles , , Sets , , ), one outlier

was removed from each of the P-p and NB-p box plots.

108

Fishery Bulletin 111(1)

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