NOAA Technical Memorandum NMFS-AFSC-484

Midwater Trawl Comparison
Study for Acoustic Surveys
of Walleye Pollock (Gadus
chalcogrammus) in Alaska
K. Williams and S. Kotwicki

April 2024

U.S.
U.S.DEPARTMENT
DEPARTMENT
OF COMMERCE
OF COMMERCE
National Oceanic
National
Oceanicand
andAtmospheric
Atmospheric
Administration
Administration
National Marine
National
MarineFisheries
FisheriesService
Service
Alaska Fisheries
AlaskaFisheriesScience
ScienceCenter
Center

The National Marine Fisheries Service's Alaska Fisheries Science Center uses the NOAA Technical
Memorandum series to issue informal scientific and technical publications when complete formal
review and editorial processing are not appropriate or feasible. Documents within this series reflect
sound professional work and may be referenced in the formal scientific and technical literature.
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the NMFS-F/NWC series established in 1970 by the Northwest Fisheries Center. The NMFSNWFSC series is currently used by the Northwest Fisheries Science Center.

This document should be cited as follows:
Williams, K., and Kotwicki, S. 2024. Midwater trawl comparison study for acoustic surveys of walleye
pollock (Gadus chalcogrammus) in Alaska. U.S. Department of Commerce, NOAA Technical Memorandum NMFS-AFSC-484, 40 p.

This document is available online at:Document available: https://repository.library.noaa.gov

Reference in this document to trade names does not imply endorsementby the National Marine Fisheries Service, NOAA.

Midwater Trawl Comparison
Study for Acoustic Surveys
of Walleye Pollock (Gadus
chalcogrammus) in Alaska
K. Williams1 and S. Kotwicki2

Midwater Assessment and Conservation Engineering Program
Resource Assessment and Conservation Engineering Division
Alaska Fisheries Science Center
National Marine Fisheries Service
National Oceanic and Atmospheric Administration
7600 Sand Point Way NE
Seattle, WA 98115
1

Groundfish Assessment Program
Resource Assessment and Conservation Engineering Division
Alaska Fisheries Science Center
National Marine Fisheries Service
National Oceanic and Atmospheric Administration
7600 Sand Point Way NE
Seattle, WA 98115

2

U.S. DEPARTMENT OF COMMERCE
National Oceanic and Atmospheric Administration
National Marine Fisheries Service
Alaska Fisheries Science Center
NOAA Technical Memorandum NMFS-TM-AFSC-484
April 2024

ii

ABSTRACT

Midwater trawling is a critical component of acoustic-trawl fisheries surveys, and it isused to determine the species and size composition of acoustically sampled fish schools.
Changes in midwater trawl gear can influence the catch, and therefore potentially bias thesurvey data. The Alaska Fisheries Science Center conducts acoustic-trawl surveys of walleye
pollock (Gadus chalcogrammus) in Alaska waters and recently switched to a new midwater
LFS1421 trawl (LFS) from an older Aleutian Wing Trawl (AWT). A series of field trials wereconducted to compare the performance of the two midwater trawls during three separate
surveys in 2019-2020. For two of the surveys, both trawls were outfitted with recapture nets toassess escapement from the trawl. An analysis of the comparative pollock catch-at-length
showed that the size distribution of pollock was similar between the two trawls, although the
AWT had a higher catch-per-unit-effort. The escapement of pollock from the trawl was alsosimilar, although relatively low numbers of juvenile fish in 2020 made this comparison lessrigorous. The LFS trawl was more efficient at catching several smaller non-pollock fish species,
as well as non-fish organisms such as euphausiids. Overall, findings in this study do not indicate
substantive differences between the trawls that would constitute a dis-continuity in the
acoustic-trawl survey abundance time series for pollock.

iii

iv

CONTENTS

Abstract ............................................................................................................................... iii
Introduction ........................................................................................................................ 1
Methods ………………………………………………………………………………………………………………………. 2
Results …………………………………………………………………………………………………………………………. 9
Summary ……………………………………………………………………………………………………………………. 20
Acknowledgments ……………………..………………………………………………………………………………. 25
Citations …………………………………………………………………………………………………………………….. 27
Appendices ………………………………………………………………………………………………………………… 31v

vi

INTRODUCTION

Midwater trawls are an essential tool for performing acoustic-trawl (AT) fisheries
surveys. Trawl catch is used to identify the size and species composition of targeted fish
aggregations, allowing for correct interpretation and scaling of acoustic backscatter into fishabundance (MacLennan and Simmonds, 2013). In Alaska, AT fisheries surveys are a primarydata source for assessing the population status of walleye pollock (Gadus chalcogrammus,
hereafter pollock), which supports the largest fishery in the United States, and one of thelargest fisheries in the world (FAO, 2020). The NOAA Fisheries Alaska Fisheries Science Center
regularly conducts acoustic-trawl surveys in the eastern Bering Sea (McCarthy et al., 2020), theGulf of Alaska (Jones et al., 2022), and pollock spawning areas (McKelvey and Levine, 2023,
McCarthy et al., 2022).
For surveys to accurately track populations shifts over time, standardization of
methodology and gear are essential. For AT surveys, this relates to acoustic instrumentation,
the survey vessel used, and trawling gear employed. However, on occasion, it becomes
necessary to change one of these to replace obsolete equipment or to change survey platforms.
These events require a process of inter-calibration to decouple methodological changes fromthe time series of survey estimates. The Alaska AT survey program changed survey vessels in2007 (NOAA ship Miller Freeman replaced by the noise-quieted NOAA ship Oscar Dyson), and in
2019 the survey upgraded the acoustic equipment (the Simrad EK60 upgraded to the Simrad
EK80 system), as well as introduced a new midwater trawl. The former two changes were
investigated extensively (De Robertis et al. 2008, De Robertis et al. 2019) via inter-calibration
analysis. This report represents a similar effort for examining the potential survey effects
resulting from the change in trawling gear.
The role of trawling during AT surveys differs from trawl-based fisheries surveys. For
example, bottom trawl surveys use bottom trawls to directly assess density of fish based on thearea “swept” by the trawl (Gunderson, 1993). In Alaska, trawl-based surveys operate bysampling predetermined stations, or locations, with fixed duration tows and a high degree ofattention paid to standardization of net performance, such as bottom contact and net
spread/opening (e.g., Kotwicki et al. 2011). In AT surveys, the location and duration of the trawl
are not standardized, but are rather determined opportunistically to allow sampling of highdensity fish aggregations detected by the acoustics (Karp and Walters 1994). The critical role oftrawl samples for these surveys is to accurately determine the species and size composition of
acoustically sampled fish aggregations in order to correctly interpret acoustic backscatter andderive estimates of fish abundance and biomass (MacLennan and Simmonds 2013).
While many studies have been conducted on comparing survey bottom trawls (e.g.,
Bagley et al. 2015, Miller et al. 2010, Lewy et al. 2004), relatively few comparative studies of1

survey midwater trawls have been conducted (Kotwicki et al. 2017, Bethke et al. 1999), in part
because the trawls are not the primary basis for abundance assessment. Thus, this study
describes a unique approach to trawl comparison, utilizing both trawl catch and acoustic
information to evaluate the effect of using different trawls in the context of AT surveys.

METHODS
Trawl Gear Description
From 1995 to 2019, Alaska Fisheries Science Center’s (AFSC) Midwater Assessment andConservation Engineering (MACE) program conducted pollock AT surveys using an Aleutian
wing trawl (AWT, Nor’eastern trawl systems; Fig. 1) as its primary survey midwater trawl. The
AWT is a commercial midwater trawl specifically designed for use in the pollock fishery, and it
was modified for survey use by placing a small mesh liner (19 – 13 mm) in the codend. Having
reached the end of its use period, it was replaced by the Lummi Fisheries Supply LFS1421(hereafter LFS) trawl (Lummi Fisheries Supply; Fig. 2), which was designed as a survey trawl. In
identifying the replacement trawl, it was sought to improve on certain aspects of the AWT, suchas the retention of smaller pollock and other small fishes, ease of deployment, and reduced
catch quantities in high-density fish aggregations. To accomplish these goals, the standard LFS
trawl design was further modified by reducing mesh size in the section leading to the codend. A
3.2-mm liner was placed in the codend to aid in retaining small organisms.

2

Figure 1. -- Aleutian Wing Trawl (AWT).
The LFS has a smaller headrope length, a more gradual taper, and is outfitted withsynthetic rigging and weighted line for the front bottom panel (the trawl “belly”). For the AWT
and LFS trawls, performance was evaluated using a Simrad FS70 netsounder, which provided
measurements of headrope depth as well as estimates of the vertical and horizontal trawl
opening. A comparison of trawl dimensions is provided in Table 1.
Table 1. -- Basic trawl dimensions and specified accessories for two midwater trawls.
Trawl gear
model
headrope length
largest mesh size
smallest body mesh sizecodend liner size
rigging
doors
tom weights for typical towing

AWT
30/26
268' (81.7 m)
128" (3.25 m)
4" (100 m)
1/2" (12 mm)
wire rope
Nets Fishbuster 5 m2
250 - 500 lb (113 - 227 kg)

3

LFS
1421
337.37' (102.8 m)
256" (6.5 m)
1.5" (38 mm)
1/8" (3")
composite
Nets Fishbuster 5 m2
500 – 1,000 lb (227 – 554 kg

TOP PANEL

4

SIDE PANEL

Figure 2. -- LFS1421 midwater trawl.
5

Trawl Comparison Experiments
To evaluate the trawl performance and to determine how using the new trawl might
impact pollock survey results, a series of comparison experiments were conducted in 2019 and2020. Paired tows were taken concurrently with regular survey activities, with the locations
and times chosen opportunistically to identify areas of observed high backscatter, with the LFS
trawl catch also used for purposes of survey backscatter classification. For each pair, the firsttrawl to be fished was determined randomly, and the follow-up trawl was performed as soon as
possible. Pairs were taken when certain conditions were present, including 1) sufficient
backscatter suspected to contain pollock, 2) sufficient time available to collect both trawls
during daytime hours, and 3) overall survey time availability. Pairs were conducted during theJune-August 2019 summer Gulf of Alaska ATsurvey (DY1906; Jones et al., 2022), the FebruaryMarch 2020 Bogoslof Island AT survey (DY2002; McKelvey and Levine, 2023), and the March
2020 Shelikof Strait AT survey (DY2003; McCarthy et al., 2022).
Trawl Selectivity
The MACE program has conducted trawl selectivity experiments with the AWT trawl
since 2007 (e.g., SH1904; Lauffenburger et al. 2019, DY2002; McKelvey and Levine 2023) andthe LFS trawl since 2019 (DY1906; Jones et al. 2022, DY2003; McCarthy et al. 2022; DY2102;
Honkalehto et al. In review), where selectivity is defined as the species- and size-dependent
probability that a fish entering the trawl opening will be retained in the codend. The MACE
program has developed a method for estimating midwater trawl mesh escapement by using
small recapture or “pocket” nets mounted on the outside of the trawl that sample fish as they
pass through the trawl During the trawl comparison experiments, a total of nine pocket nets
were used on the LFS trawl; one each on the top, bottom, and side panels of the trawl in threedifferent sections of the trawl from the main trawl body to the codend. The AWT was outfittedwith 8 nets, placed on top, bottom, port, and starboard panels of the trawl in two sections
along the net. Samples from the pocket nets were used to estimate total size- and speciesdependent escapement from the trawl. For the DY1906 and DY2003 surveys, pocket nets wereplaced on both the AWT and LFS trawls, with the AWT outfitted with 1/4-inch mesh pocket nets
and the LFS outfitted with 1/8-inch mesh pocket nets, each matching the corresponding codend
liners used in the trawls. The difference in mesh size between the gears, while not ideal, wasnecessary because the historical time-series used 1/4-inch liner with the AWT, and correctinterpretation of codend selectivity requires that the same mesh size is used for the pocket nets
and the codend liner to reduce any additional effects of organisms passing though the liner orpocket net.
For the DY2002 survey, pocket nets were only placed on the LFS trawl, as the AWT had
not historically been outfitted with pocket nets for this survey. Pocket net catches were used toestimate selection curves for juvenile pollock escapement from both trawls in DY1906 and
DY2003 surveys. Trawl selectivity curves were computed using an analysis that is based on
6Williams et al. (2011), but replacing the hierarchical Bayesian approach with a general linear
mixed-effects model fitted using a binomial family with a logit link function and specifying eachhaul event as a random effect (GLMM), fish length as the fixed effect, with the response
variable being whether or not a measured fish was retained in the codend (coded as 1) or
escaped from the trawl before reaching the codend (coded as 0). For this model, total
escapement Nesc at length l was estimated by scaling the catch in each pocket net (Np,l) by theratio of the total meshes in the trawl section represented by a pocket net to meshes covered by
the pocket net itself (Fp) as
𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑙𝑙 = ∑𝑝𝑝 𝑁𝑁𝑝𝑝,𝑙𝑙 ∗ 𝐹𝐹𝑝𝑝 .

Eq.1

Due to the low abundance of age-1 fish in 2020, a separate cross-year comparison wasmade between the selectivity estimates for the 2021 Shelikof Strait AT survey (DY2102;
Honkalehto et al. in review), which was dominated by age-1 fish, and the 2013 Shelikof Strait
survey (DY1303; Jones et al. 2014) where a similar size distribution was observed. In 2021, theLFS trawl was used in the same configuration as in 2020, and in 2013, the AWT trawl was used,with pocket nets placed on the trawl in different randomly chosen locations for each trawl
event, as described in Williams et al (2011).

Pollock Length Composition Comparison
During AT surveys of pollock, pollock typically comprises > 90% of the catch by weight,
and the pollock length distribution is of primary importance for survey abundance estimates.
For catch processing, pollock are sorted and a subsample is measured to the nearest millimeter(for details on catch processing, see Jones et al. 2022). For a comparison pair, catch data werenormalized between trawl pairs by dividing the number caught by the fishing duration, resulting
in a catch (in numbers)-per-unit-effort (CPUE), where the effort is minutes fished. The fishingduration was measured from the time the trawl reached target depth until haulback was
initiated. To compare the CPUE at length for the two trawls, the Selectivity Ratio (Sr) was
computed (Kotwicki et al. 2017). This metric is a relative value of catch efficiency as a functionof fish length, where the absolute efficiency of either gear is not known. Several models forfitting Sr were described in Kotwicki et al. (2017), and for this analysis the GAM and Beta
regression were compared using a ten–fold cross validation procedure to select the best model.
The model fitting procedure was as follows: first, the relative ratio p_lfs estimated as
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶_𝑙𝑙𝑙𝑙𝑙𝑙

𝑙𝑙
𝑝𝑝_𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 = 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶_𝑙𝑙𝑙𝑙𝑙𝑙 +𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶_𝑎𝑎𝑎𝑎𝑎𝑎
,
𝑙𝑙

𝑙𝑙

Eq. 2

where l is fish length (2-cm bin size). The choice of a larger bin size was made to minimize thenumber of size classes that did not have any observations, improving the model performance.
As p_lfs is a continuously distributed variable on the interval [0,1], it is appropriate to use a7

Beta regression to model the dependency of this variable on fish length. The Beta regression
model requires that values do not exactly equal 0 or 1, therefore a transformation was
employed to slightly move 0 and 1 values away from the boundaries by computing
𝑝𝑝𝑝𝑝_𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 =𝑝𝑝_𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 ×(𝑛𝑛−1)+0.5
𝑛𝑛

,

Eq. 3

where n equals the number of data points in length bin l. This situation was infrequent and only
affected low abundance size classes. After fitting the model to 𝑝𝑝𝑝𝑝_𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 , this value wastransformed to Sr as
𝑝𝑝�_𝑙𝑙𝑙𝑙𝑙𝑙

𝑆𝑆𝑆𝑆_𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 = (1−𝑝𝑝�_𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 ) ,

Eq. 4

𝑙𝑙

where 𝑝𝑝̂ _𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 is the model estimate of the new trawl (LFS) ratio. For fitting a GAM model, the𝑝𝑝_𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 , was used instead of 𝑝𝑝𝑝𝑝_𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 , as this modeling approach was not constrained to values
not equaling 0 or 1. Variances for Sr were derived by applying a bootstrap approach where arandom sampling of trawl pairs were drawn with replacement for 1,000 iterations, and the 2.5
and 97.5 percentiles of the simulated results were used as proxies for the upper and lower
confidence bounds. These analyses of inter-net selectivity ratios were conducted for the catchin the trawl codends as well as for the estimated total catch, comprising the codend combinedwith estimated escapement from the pocket net samples.

Species Composition Comparison and Trawl Efficiency
We also compared the selectivity of the AWT and LFS trawls for a number of different
species and species groups across pairs, using a similar approach to the length analysis. These
species and species groups were selected based on frequency of occurrence (5% or more by
number in the overall survey catch) or ecological or survey importance (e.g. forage fish species).
For each species or species group, the catch by number and weight (including estimatedescapement from pocket net data) were normalized by tow duration, except for the DY2002
cruise, where only codend catch was available for the AWT. The ratio of catch in the new (LFS)
trawl over total catch was estimated as
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶_𝑙𝑙𝑙𝑙𝑙𝑙

𝑠𝑠,𝑖𝑖
𝑝𝑝_𝑙𝑙𝑙𝑙𝑠𝑠𝑠𝑠,𝑖𝑖 = 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶_𝑙𝑙𝑙𝑙𝑙𝑙 +𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶_𝑎𝑎𝑎𝑎𝑎𝑎
𝑠𝑠,𝑖𝑖

𝑠𝑠,𝑖𝑖

,

where s is the species or species group and i is the paired trawl number.
Species-specific selectivity parameters were estimated separately for each survey
region. Confidence bounds for 𝑝𝑝̅ _𝑙𝑙𝑙𝑙𝑙𝑙𝑠𝑠 were estimated using a bootstrap across trawl pairs.
8

Eq. 5

Acoustic Survey Application Comparison
The current practice for scaling acoustic backscatter is to assign acoustic measurements
taken along the trackline to the nearest trawl (Jones et al. 2022). Thus, each trawl has an
associated total backscatter that is then converted into abundance using standard acoustic
survey methodology (De Robertis et al. 2014).
As paired trawl comparisons were taken during regular survey operations, many of the
trawl samples from the LFS catches used in the comparisons were also used to scale backscatterfor survey abundance estimates. To estimate the potential effect of trawl choice on acoustic
backscatter scaling, backscatter associated with those LFS tows were also scaled using thepaired AWT haul. Acoustic backscatter was partitioned among species using the method
outlined in De Robertis et al. (2014) and Jones et al. (2022, Appendix III). Catch data included
estimated escapement from expanded pocket net catches. This analysis was limited to DY1906
and DY2003 surveys, as the DY2002 had too few hauls to make a reasonable comparison.
Backscatter was scaled using total catch (codend + estimated escapement) as computed foreach individual haul based on catches in the pocket nets (Jones et al. 2022, Appendix IV).

RESULTS
Trawl Comparison Experiments
Overall, 43 paired trawls were collected: 26 pairs during DY1906 (Fig. 3a), 6 during DY2002, and
11 during DY2003. While the paired trawl locations, depths, and durations were replicated as
closely as possible, changes in fish school location between the trawls operations often
required adjustments to reach an adequate sample for comparison. An effort was made tocollect paired tows throughout the survey area; however, the majority of the comparisonsoccurred where most of the pollock aggregations were encountered. Of the six pairs collectedduring the DY2002 survey (Fig. 3b), the last pair from this set occurred in Shelikof Strait during
the end-of-survey transit, and thus has been included in the analysis for DY2003 (Fig. 3c), which
occurred immediately after. An additional 11 pairs were collected during DY2003, bringing thetotal number of tows for this survey area to 12.

9Figure 3a. -- Comparison trawl locations (numbered black squares) taken during the 2019
summer GOA survey (DY1906)

Figure 3b. -- Comparison trawl locations (numbered black squares) taken during the 2020
winter pollock pre-spawning survey of the Bogoslof Island area (DY2002)

10

Figure 3c. -- Comparison trawl locations (numbered black squares) taken during the 2020 winterpollock pre-spawning survey of Shelikof Strait (DY2003)

The average time between trawl starts was 3.13 hours, with 90 % occurring within
4 hours (Fig. 4). The average distance between the starting locations of paired tows was 1.15km, with 75 % occurring within 1.5 km. The depth at which fish were caught varied somewhat
between pairs, likely due to diel vertical movement of fish schools. Table 2 shows the net
dimensions measured during paired trawling.

Figure 4. -- General paired trawl comparison performance and characteristics.

11

Table 2. -- A comparison of trawl opening and depth measurements of two midwater trawls(distances in m, area in m2)
net height

net widthmean

surveyDY1906

gear
AWT

range
18.0 – 27.0

mean
22.5

range
23.0 - 42.0

mean
33.3

depth
108.4

area
2451

DY1906LFS

13.5 - 20.0

17.1

31.5 - 44.9

38.3

108.5

2409

DY2002AWT

24.0 - 36.0

30.6

40.0 - 47.0

43.6

317.4

4329

DY2002LFS

15.9 - 21.6

19.7

34.0 - 44.5

40.6

309.9

2860

DY2003AWT

21.0 - 29.6

25.0

20.0 - 40.7

31.4

190.1

2504

DY2003

LFS

12.5 - 24.5

19.6

26.0 - 42.0

34.0

193.9

2258

mouth

During the DY2002 survey, pollock schools occurred in deeper water, which required moreweight to be added to the trawl to assist in rapid descent to fishing depth. The LFS was fishedwith 500 lb tom weights for DY1906 and DY2003 surveys, for DY2002 this was increased to
750 – 1,000 lb. This change could have influenced the trawl opening (net height) estimates, as
the geometry of the trawl opening was likely affected by the extra weight. The AWT tom
weights were also increased from 250 lb for DY1906 and DY2003 surveys to 500 – 750 lb for
DY2002, and displayed an even greater change in vertical opening than observed in the LFS
trawl.

Trawl Selectivity
Trawl selectivity was estimated for pollock catches in the DY1906 and DY2003 surveys
using the pocket net samples to estimate total escapement from the trawl. Overall, the catches
in the pocket nets were relatively low in both surveys (4.6% and 5.7% of codend catch,
respectively), and the corresponding selectivity curves indicated that the pollock of nearly all
sizes were well-retained (Fig. 5). While the LFS trawl appeared less selective for pollock (e.g.,
retaining more) in the size range of 15 - 25 cm in DY1906, in the winter survey (DY2003)
retention of the smaller sized age-1 pollock (11 – 17 cm) appeared comparable; the AWT
retained 67% of this size group, while the LFS retained 66%. Overall, age-1 pollock were notvery abundant in this survey, thus the data in this study are not strongly informative on theirretention properties in the trawls, as seen in the overlapping selectivity curve confidence
intervals in Fig. 5. The L50 (length at which 50% of fish are retained) estimates were also
substantially higher (more escapement) in the winter survey compared with the summer.

12

Figure 5. -- Trawl selectivity estimates for pollock for the AWT and LFS trawls. Bottom panelreflects a comparison of two past surveys with similar age structure, while the upper
panels are same survey comparisons.

The multi-year comparison between 2021 (LFS) and 2013 (AWT) is more appropriate as
the AWT data is based on substantially higher amounts of catch in the pocket nets, and thus
may represent a better comparison for selectivity than either the 2019 or 2020 data, assuming
there aren’t strong annual effects on selectivity. This comparison shows that the LFS trawl isslightly less selective, retaining 96% of age-1 fish (8-16 cm), while the AWT retained 84%.

Comparison of Pollock Length Data
A comparison of relative pollock length composition for each trawl pair in general
showed good agreement among the trawl samples in all surveys (Appendix Fig. 1). However,13

there were several substantial mismatches in targeted fish distributions; for example, the thirdpair from DY2002 likely encountered different fish schools as the composition differed
substantially compared to the other pairs in this survey (Appendix Fig. 1). This pair was
therefore excluded from further analyses. In the DY1906 survey, two AWT trawl catches were
extremely low (pair 17, with 31 pollock captured and pair 26, with 4 pollock captured), andthese pairs were also excluded from analysis. To facilitate comparison, the length composition
was aggregated on for each survey, where each haul sample was equally weighted. For thiscomparison, the proportion p at length l is derived as
𝑝𝑝𝑙𝑙 =𝑐𝑐∑ℎ � ℎ,𝑙𝑙�∑�𝑙𝑙 𝑐𝑐ℎ �

𝑛𝑛 ,

Eq. 6

where c is the catch in haul h at length l and n is the total number of hauls. The normalized
length distributions show very minor differences between gears (Fig. 6).

Figure 6. -- Comparison of aggregated pollock length frequencies by survey, normalized by haul.

Two models were compared in fitting 𝑝𝑝𝑝𝑝𝑛𝑛𝑛𝑛𝑛𝑛 using a cross validation procedure, a GAM
model (without a beta transformed response) and a Beta regression. While the latter is similar
to a binomial generalized linear model (GLM), it is fit using the betareg package in R statisticalsoftware (Cribari-Neto and Zeileis 2010). Both models resulted in similar RMSE values, with the
Beta regression showing a slightly better fit (RMSEGAM = 0.339, RMSEBETA = 0.337). As theinterest was to evaluate a simple relationship between 𝑝𝑝𝑝𝑝𝑛𝑛𝑛𝑛𝑛𝑛 and fish length, the Beta
regression was chosen for further modeling.
The model was fit to two datasets, the first one representing the catch in the codend
only, or retained catch, and the second representing the estimate of the total fish that haveentered the mouth of the trawl, e.g. retained + escaped catch (Fig. 7). The model was fit
independently to each survey area, with the escaped catch unavailable for the DY2002 survey.
The resulting Sr value was < 1 for the DY1906 and DY2003 surveys, although this value was notstatistically different from 1 due to the high level of uncertainty. The DY2002 survey shows adifferent pattern although it was also not different than 1 statistically and was based on very14

few samples. Modeling full catch (retained + escaped components) did not seem to influence
the outcome. In general, these models would be expected to show a stronger slope if one of
the gears was more efficiently sampling a different size component of the population (seeKotwicki et al. 2017 for an example). The lack of a strong slope indicated that the lengthcompositions associated with the two trawls are not significantly different given the data
available.

15

16

Figure 7. -- Beta regression model fits of pair-wise differences in pollock CPUE using AWT and
LFS trawls. Surveys DY1906 and DY2003 were compared using codend only andselectivity corrected catch; this option was not available for the DY2002 survey. The
left panels represent the relative catch ratio (LFS/(AWT+LFS)), and the right
represents the selectivity ratio where 1 = equal selectivity at length.
Species Composition
Overall, the LFS trawl with the 1/8-inch codend liner retained smaller organisms(eulachon, Thaleichthys pacificus; herring, Clupea pallasii; krill, Euphausiidae) than the AWT(Fig. 8). The proportion of pollock in the catch was similar (Table 3). The equivalent statistics fornumbers caught are different, with pollock being less represented in the catch numerically inthe last two surveys.
Table 3. -- Average percent of pollock by weight and number for different trawls and including
correction for escapement.

CodendCodend +escaped% pollock byweight% pollock by
number% pollock byweight% pollock by
number

DY1906AWT
LFS

DY2002AWT
LFS

DY2003
AWT
LFS

74.9

78.3

98.0

97.3

79.5

81.2

82.0

82.5

81.5

68.9

39.4

34.3

75.4

70.8

-

82.6

74.8

73.5

72.3

58.7

-

37.1

23.9

18.0

The current practice in MACE abundance estimation analyses is to correct forescapement from the trawl; thus, the following comparisons were based on estimates ofretained and escaped catch. A comparison of only the most numerous species caught by
number and weight in the summer data (DY1906) shows a higher Sr (> 1) for herring andeulachon, and substantially higher Sr for krill, which were not very effectively retained by the
AWT 1/2-inch liner. This is in contrast to juvenile pollock (< 20 cm, age-1 and age-0), whichindicated that pollock may have different behaviors in the trawl when compared with otherforage fishes. The number of jellyfish (broadly defined as medusae and ctenophores of various
species in this study), capelin (Mallotus catervarius), and pollock young-of-the-year (age-0)
caught by the LFS appeared similar on a CPUE basis. For the DY2002 survey, values were moresimilar between gears across all species groups except for shrimp (Malacostraca). Interestingly,
the average size of myctophids (Myctophidae) captured by the LFS was substantially smaller,
which is reflected in the lower Sr by weight compared to the AWT. Pacific Ocean perch (POP,
Sebastes alutus) CPUE appeared similar, but relatively few POP were encountered, with 259
17individuals caught in three AWT trawls, and 262 cough tin 7 LFS trawls. The minimum fork
length observed was approximately 29 cm, at which size a substantial portion of these fish areretained. No POP were encountered in pocket net catches. The winter DY2003 survey did notencounter krill, but the rest of the species groups showed higher CPUE, with the exception of
capelin. As with the DY1906, LFS catch of non-pollock was proportionally higher for all
categories except for capelin. The overall catch of capelin was very low in the survey, consistingof a total of 4.3 kg, compared with 70.6 kg of northern smoothtongue (Leuroglossus schmidti)
and 2,852 kg of eulachon, which may have influenced this result.

Figure 8. -- Comparison of the selectivity ratio (Sr) between the AWT and LFS trawls, fordifferent species/species groups. Not the Sr values are plotted on a log scale. Data
are presented by weight and by individual organism numbers. Data from DY2002 arebased on codend catch only, while the other two surveys are based on escapement
corrected data.

18

Acoustic Survey Application Comparison
In both surveys, the estimates of pollock numerical abundance were similar with a slightincrease in numbers in the LFS analysis (Fig. 9). Biomass estimates for the LFS analysis werelower in both surveys, with the difference being a substantial 6.44% reduction for the DY2003
survey. The proportion of backscatter that was attributed to pollock was similar for the two
trawls in both surveys, which indicated that while the LFS trawl retains more smaller organisms
than the AWT, this greater sampling scope does not influence the attribution of backscatter topollock. The differences in biomass estimates are therefore due to the differences in length
frequency of pollock between the gears, rather than improved retention of non-pollock
organisms.
While many of the LFS trawl events used for the paired comparison experiment werealso used in the survey analyses, not all of them were, particularly in the winter DY2003 survey.
In this survey, only six of the hauls used in the survey analysis had a paired AWT trawl, and thisconstituted only half of the total pairs taken (the remainder consisted of dedicated comparison
trawls not used for survey). The number of pairs from the summer DY1906 survey used in theanalysis was higher (all 23 paired trawl events), as expected given the larger scale of thatsurvey, but this still represents a small share (27%) of the total number of hauls in the survey
analysis. Thus, the abundance and biomass estimates derived in this component of the gearcomparison analysis are a fragment of the total survey analysis and are useful only for assessing
the approximate scale of variability that could be attributed to the gear.

19

Figure 9. -- Comparison of partial acoustic-based estimates of abundance and biomass, scaledby using escapement-corrected data for two surveys. The difference refers to %change in abundance and biomass relative to the AWT. The DY1906 re-analysis isbased on 26 paired trawls, while the DY2003 survey is based on six paired trawls.
Lower panels show proportion of backscatter assumed to be due to non-pollock
organisms.

SUMMARY

The results from this analysis present a range of comparison metrics that can be used togauge the potential impacts of different midwater trawls on survey estimates, as well as thecontinuity of survey estimates of abundance if trawls are changed. The AWT was more efficientin terms of the number of pollock caught per unit time, with the exception of the DY2002 data.
20

Higher efficiency of the AWT would be expected given its larger mouth opening (Table 1);
however, the greatest difference in mouth opening was seen in DY2002. During that survey
only four haul pairs were collected (after exclusion of one pair from the analysis), which may
partly explain this anomalous result. The observed efficiency patterns may also be explained by
the larger mesh size in the front section of the LFS, or different propensity of pollock to avoid
entering the mouth of each net (trawl avoidance, as opposed to trawl escapement through themeshes). Trawl avoidance is likely important, however, it is more difficult to measure andshould be further investigated using alternative sensing equipment such as imaging sonars or
underwater cameras.
Selectivity estimates for the two trawls were made using all available trawl data, andnot just those hauls used for the trawl comparison. These estimates showed a lot of uncertainty
due to the small number of age-1 fish in both summer and winter surveys. A comparison of the
LFS from DY2102 (2021) and AWT from DY1303 (2013) Shelikof Strait surveys, although not as
useful as the within-survey work, show that in independent assessments of selectivity with alarge age-1 presence, the LFS performed marginally better (96% retention of age-1 fish vs 84%).
For the pairwise size-dependent efficiency modeling, the differences were subtle with theselectivity ratio (Sr) showing only a slight inclining pattern which could be interpreted as aslightly lesser efficiency of the LFS for smaller sizes. However, uncertainty in the beta regression
model was high at the edges of the size distribution. Overall, the slope of the Beta regression
indicates that there is not a strong influence of fish length on Sr, especially relative to overall
efficiency difference and the substantial uncertainty in the estimate at the extremes of thelength ranges. In an overall assessment of selectivity and efficiency, we conclude there is little
evidence for a consistent difference in pollock size data between the two trawls, however
recognize that sample sizes were relatively small and there was substantial variability between
pairs and surveys. The lack of substantial improvement in pollock selectivity was not expected,
as there were several modifications made to the design of the LFS trawl to specifically improve
retention of age-1 pollock.
The LFS trawl was more efficient at catching non-pollock organisms, including someforage fish species, and, most notably krill. These efficiency increases did not translate into
differences in the quantity of backscatter that was attributed to pollock in the DY1906 survey.
In the winter DY2003 survey, more backscatter was attributed to pollock, albeit based on asubstantially smaller sample size. Improved retention of non-pollock species can be assumed to
improve the overall survey results as it represents a less biased sample of the true species
compositions in the survey area.
Past summer GOA surveys, most notably the 2017 survey, encountered substantial
numbers of young-of-the-year (age-0) pollock, which were not well retained by the AWT
equipped with an 1/2-inch codend liner. This acoustic backscatter classification of age-1+
pollock difficult due to co-occurrence of age-0 and age-1+ pollock in the water column (Jones etal. 2019). The DY1906 survey found only a modest amount of age-0 pollock, and this data21

showed that the relative catch efficiency of age-0 pollock with the LFS was approximately thesame as that of the AWT. This result was not expected, and therefore requires more data fromfuture surveys to understand the retention properties of the LFS trawl for age-0 pollock.
Another potential challenge for pollock assessment in the GOA summer surveys is thepresence of Pacific Ocean perch (POP), which can occasionally mix with pollock in schools,
making interpretation of the relative abundance of these two species dependent on theirvulnerability to the trawl gear. Unfortunately, the trawl pairs in this study did not encounter
POP in significant quantities (but see Figure 8, DY2002), and those that were encountered werelarge enough that escapement through the trawl mesh was not expected. For POP, strong
diving behavior in front of the trawl has been observed during AT surveys, which may indicate astrong pre-trawl avoidance component that may make catch comparisons between the two
trawls more challenging.
The application of the LFS or AWT catches from a paired trawling event to compare
survey biomass estimates (Section 3.5 above) provided some useful insights. Using the AWT
and LFS trawls in turn to scale the acoustic backscatter associated with each trawl pair gave asingle realization of the potential differences in survey outcomes that could result fromchanging the trawl gear. The outcome was heavily dependent on the amount of acoustic
backscatter associated with each trawl, and thus not all paired trawl sets were equally
influential. In the case of the DY2003 survey, only a few paired trawl location-acoustics strata
were available for this comparison. Therefore, the biomass reduction seen in the surveys using
this analysis method, especially in DY2003, is likely not representative of the expected surveylevel impacts of using the LFS trawl. While improved selectivity of age-1 pollock with the LFS is
expected to result in higher abundance and lower biomass, the differences in this comparison
are more likely related to the small sample size of trawls that could have encountered slightly
different fish aggregations during the paired sampling process, with the AWT encounteringlarger fish than the LFS.
In conclusion, this analysis shows some expected outcomes, such as lower CPUE andincreased retention of small non-pollock organisms by the LFS relative to the AWT. Lengthselectivity for all sizes of pollock was similar between the two trawls. We suspect age-0
retention would be improved with the LFS trawl due to the finer codend liner, however, thesedata didn’t support that due to the low abundance of these fishes in the catches in 2019. The
LFS was shown to retain more smaller organisms overall. These differences resulted in minimal
differences in proportion of backscatter allocated to pollock when each gear was used toindependently analyze a subset of the survey area, and while some difference in pollock
biomass were observed in this analysis, it was probably due to a change in pollock sizedistribution encountered by each trawl.
There was substantial variability in the trawl comparison data presented here, but
overall there was no evidence of major differences in retention between the two trawls,
especially when it comes to results for pollock. In terms of the survey time-series, it would be
22difficult to fully adjust historic AWT survey results to match LFS results for the differences
observed here because the smallest organisms were probably not retained at all in the AWT.
Based on these findings, we don’t recommend making any adjustments to the acoustic-trawl
survey time series for the change in gear, but the change in gear should be considered whenusing the data. Past survey data can be adjusted for trawl-specific selectivity depending on theapplication and the data available.
The LFS provides improvements in many other trawling aspects of AT survey work,
including lighter, color-coded rope materials, ease of deployment and maintenance, and more
appropriate catch sizes. The differences in catches between these gears does not appear torequire a substantial difference in treatment of the AT survey time series for pollock.

23

24

ACKNOWLEDGMENTS

This project was made possible by the leadership of Chris Wilson, and the assistance ofmany individuals, including gear preparation, repairs, and modification by the AFSC Net Loftand the NOAA ship Oscar Dyson deck department. Analytical help and advice were critical to
the successful interpretation of the data, and for that we thank Alex De Robertis and Mike
Levine. We are also indebted to the science field parties for all three surveys that worked hardon collecting this comparison data.

25

26

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Jones, D. T., S. C. Steinessen, and A. L. McCarthy. 2014. Results of the acoustic-trawl surveys ofwalleye pollock (Gadus chalcogrammus) in the Gulf of Alaska, February-March 2013
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NOAA, Natl. Mar. Fish. Serv., 7600 Sand Point Way NE, Seattle WA 98115.
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AFSC Processed Rep. 2019-10, 76 p. Alaska Fish. Sci. Cent., NOAA, Natl. Mar. Fish. Serv.,
7600 Sand Point Way NE, Seattle WA 98115.
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Science 68(1): 119-129.

29

30

APPENDICES

31

32

Appendix Table 1. -- Critical towing parameters for paired trawl events.

9.4

headrope
depth
(m)
92.7

net
height
(m)
18.0

net
width
(m)
36.7

Avg
wireout
260.0

mean
trawlpath
Sv-57.0-162.49

40.6

102.6

17.0

42.0

232.7

-68.7

58.52

-153.02

32.5

84.9

23.0

32.6

172.0

-75.5

6/26/19 21:48

58.54-153.02

26.0

80.6

13.5

32.5

192.5

-66.5

-154.85

6/28/19 23:45

57.40-154.87

20.6

100.4

N/A

N/A

N/A

-67.6

57.42

-154.85

6/29/19 6:10

57.39

-154.88

37.9

103.1

17.7

38.6

211.1

-73.7

6/29/19 21:10

57.27-155.13

6/29/19 21:35

57.26-155.17

24.3

119.4

21.0

33.5

272.5

-67.9

4

6/29/19 16:33

57.26-155.15

6/29/19 17:00

57.26-155.20

27.1

101.8

N/A

N/A

N/A

-70.4

AWT

5

7/1/19 22:06

56.57-155.73

7/1/19 22:16

56.57-155.74

10.3

138.3

N/A

N/A

N/A

-70.5

77

LFS

5

7/1/19 18:11

56.58-155.72

7/1/19 18:36

56.58-155.76

25.0

134.9

17.0

34.0

290.0

-61.9

81

AWT

6

7/2/19 17:44

56.41-156.10

7/2/19 18:28

56.39-156.16

43.7

157.0

N/A

N/A

N/A

-73.0

DY190680

LFS

67/2/19 14:58

56.40-156.12

7/2/19 15:05

56.40-156.13

7.3

144.5

N/A

N/A

N/A

-67.7

DY190683AWT

7

7/3/19 23:59

55.85-156.04

7/4/19 0:02

55.85

-156.05

2.6

65.4

N/A

N/A

N/A

-58.0

DY190684

LFS

7

7/4/19 2:07

55.85

-156.05

7/4/19 2:10

55.84

-156.06

3.9

59.8

16.0

39.0

180.0

-65.3

DY190687AWT

8

7/5/19 21:31

55.01-157.27

7/5/19 21:48

55.00-157.26

17.1

73.4

27.0

23.0

145.0

-70.3

DY190688

LFS

8

7/6/19 0:37

55.04

-157.29

7/6/19 0:52

55.03

-157.28

15.2

52.2

15.4

35.8

129.8

-60.1

DY190694AWT

9

7/6/19 23:28

55.63-156.31

7/6/19 23:29

55.63-156.31

1.3

91.6

26.5

31.5

225.0

-83.6

DY190695

LFS

97/7/19 1:40

55.63

-156.27

7/7/19 2:04

55.62

-156.23

23.5

119.1

18.7

41.2

222.5

-71.1

DY1906

100

AWT

10

7/7/19 16:08

55.63-156.26

7/7/19 16:08

55.63-156.26

0.6

116.7

N/A

N/A

N/A

-87.8

survey

haul

gear

pair
numbereq timeeq
latitudeeq
longitude

hb timehb
latitudehb
longitude

duration(min)

DY190615AWT1

6/9/19 17:23

54.50-162.53

6/9/19 17:33

54.50-162.51

DY190616LFS1

6/9/19 20:17

54.49-162.55

6/9/19 20:58

54.50

DY190655

AWT

2

6/27/19 2:55

58.55

-152.99

6/27/19 3:28

DY190654

LFS

2

6/26/19 21:22

58.56-152.99

DY190663

AWT

3

6/28/19 23:25

57.42

DY190664

LFS

3

6/29/19 5:32

DY190670

AWT

4DY190669

LFS

DY190678

DY1906
DY1906

DY1906

101

LFS

10

7/7/19 19:02

55.61-156.24

7/7/19 19:28

55.58-156.22

26.2

136.1

N/A

N/A

N/A

-69.0

DY1906

103

AWT

11

7/8/19 4:58

55.53

-155.79

7/8/19 5:18

55.52

-155.78

19.3

163.8

22.5

36.3

387.9

-69.6

DY1906

102

LFS

11

7/8/19 1:23

55.53

-155.79

7/8/19 1:48

55.51

-155.78

25.3

129.4

17.3

40.5

387.9

-72.4

DY1906

116

AWT

12

7/10/19 22:56

56.52-152.60

7/10/19 23:04

56.52-152.59

8.2

72.2

23.3

29.0

175.0

-65.9

DY1906

115

LFS

12

7/10/19 20:48

56.52-152.59

7/10/19 20:52

56.52-152.58

3.8

74.0

14.5

31.5

180.0

-64.2

DY1906

117

AWT

13

7/11/19 2:11

56.55

-152.43

7/11/19 2:18

56.55

-152.44

7.3

70.9

21.9

28.4

140.0

-68.1

DY1906

118

LFS

13

7/11/19 4:11

56.56

-152.41

7/11/19 4:14

56.56

-152.42

2.7

68.1

17.6

33.2

125.0

-67.2

33

DY1906

127

AWT

14

7/11/19 18:10

56.75-152.49

7/11/19 18:25

56.74-152.50

15.5

89.9

N/A

N/A

N/A

-63.1

DY1906

126

LFS

14

7/11/19 15:31

56.76-152.47

7/11/19 15:44

56.75-152.49

13.0

77.0

N/A

N/A

N/A

-65.9

DY1906

129

AWT

15

7/12/19 2:29

56.89

-152.38

7/12/19 2:39

56.88

-152.39

9.8

75.6

22.2

32.3

197.1

-65.0

DY1906

128

LFS

15

7/11/19 23:43

56.88-152.41

7/11/19 23:50

56.88-152.42

7.0

80.3

N/A

N/A

N/A

-58.7

DY1906

138

AWT

16

7/13/19 3:01

57.11

-152.37

7/13/19 3:09

57.10

-152.38

7.9

55.9

21.0

29.8

142.5

-66.4

DY1906

137

LFS

16

7/13/19 0:44

57.10

-152.38

7/13/19 0:44

57.10

-152.38

0.4

62.4

16.0

38.0

160.0

-83.5

DY1906

143

AWT

17

7/13/19 15:28

57.29-152.53

7/13/19 15:39

57.29-152.51

10.6

56.5

N/A

N/A

N/A

-62.5

DY1906

144

LFS

17

7/13/19 18:06

57.29-152.49

7/13/19 18:16

57.29-152.48

10.1

63.7

N/A

N/A

N/A

-52.8

DY1906

151

AWT

18

7/15/19 0:39

57.43

-151.47

7/15/19 0:44

57.43

-151.46

4.9

58.2

23.4

30.1

130.0

-65.5

DY1906

150

LFS

18

7/14/19 22:17

57.44-151.51

7/14/19 22:31

57.44-151.49

13.8

59.3

15.3

32.3

140.0

-74.3

DY1906

156

AWT

19

7/15/19 15:17

57.63-151.83

7/15/19 15:28

57.64-151.82

11.2

70.5

N/A

N/A

N/A

-63.8

DY1906

158

LFS

19

7/15/19 22:27

57.63-151.87

7/15/19 22:31

57.62-151.87

4.1

101.7

16.5

33.0

240.0

-57.9

DY1906

176

AWT

20

7/23/19 17:04

58.53-151.80

7/23/19 17:08

58.52-151.79

4.0

104.0

23.3

35.3

280.0

-50.8

DY1906

177

LFS

20

7/23/19 19:24

58.52-151.79

7/23/19 20:04

58.48-151.75

40.0

N/A

17.4

40.7

303.9

N/A

DY1906

201

AWT

21

7/26/19 19:21

59.01-149.50

7/26/19 19:52

58.99-149.54

31.2

168.4

20.1

38.5

421.3

-64.0

DY1906

200

LFS

21

7/26/19 16:09

59.02-149.47

7/26/19 16:50

58.99-149.52

40.7

158.5

17.1

42.0

361.9

-68.7

DY1906

206

AWT

22

7/27/19 22:11

59.02-148.50

7/27/19 22:21

59.02-148.51

9.9

170.9

24.1

38.6

398.3

-72.8

DY1906

205

LFS

22

7/27/19 19:16

59.03-148.50

7/27/19 19:41

59.01-148.51

24.9

180.0

20.0

43.2

385.9

-64.6

DY1906

225

AWT

23

7/29/19 21:59

59.65-148.36

7/29/19 22:40

59.61-148.38

40.7

139.7

24.0

35.0

279.5

-70.4

DY1906

224

LFS

23

7/29/19 18:48

59.66-148.35

7/29/19 19:29

59.62-148.37

40.7

129.1

20.0

41.0

277.4

-75.3

DY1906

232

AWT

24

7/30/19 18:22

59.42-146.92

7/30/19 18:42

59.41-146.92

20.5

116.3

22.9

33.5

262.5

-79.8

DY1906

233

LFS

24

7/30/19 20:42

59.43-146.91

7/30/19 20:48

59.43-146.91

6.0

118.8

19.0

42.0

282.7

-68.7

DY1906

236

AWT

25

7/31/19 4:32

59.53

-146.92

7/31/19 4:44

59.53

-146.94

11.3

129.7

23.7

33.7

320.0

-67.2

DY1906

235

LFS

25

7/31/19 2:07

59.54

-146.91

7/31/19 2:18

59.54

-146.93

10.8

130.8

19.0

40.4

280.0

-65.1

DY1906

262

AWT

26

8/4/19 2:25

59.65

-142.82

8/4/19 2:42

59.64

-142.85

16.4

236.7

18.0

42.0

664.1

-65.7

DY1906

261

LFS

26

8/3/19 23:00

59.66-142.79

8/3/19 23:16

59.65-142.82

16.4

245.7

17.3

44.9

539.4

-65.2

DY2003

1

AWT

1

3/6/20 15:38

58.23-153.30

3/6/20 15:56

58.24-153.28

18.0

164.7

29.6

36.0

321.8

-69.2

DY20032

LFS

1

3/6/20 19:24

58.22-153.313/6/20 19:44

58.23-153.28

20.0

181.0

18.5

36.7

378.0

-69.6

DY2003

3

AWT

2

3/7/20 1:30

58.19

-154.07

3/7/20 1:35

58.19

-154.06

5.1

194.4

28.0

33.5

435.0

-65.3

34

DY2003

4

LFS

2

3/7/20 3:58

58.19

-154.07

3/7/20 4:13

58.20

-154.05

15.0

214.3

16.8

31.3

405.0

-65.3

DY2003

5

AWT

3

3/7/20 9:18

57.94

-153.80

3/7/20 9:23

57.95

-153.79

5.2

145.2

26.0

32.0

285.0

-71.6

DY20036LFS

3

3/7/20 12:03

57.94-153.813/7/20 12:11

57.94-153.80

7.1

151.3

19.5

30.0

255.0

-68.1

DY20038

AWT

4

3/7/20 19:13

58.10-154.16

3/7/20 19:18

58.11-154.15

5.2

211.3

25.3

40.7

535.3

-57.6

DY20037LFS

4

3/7/20 15:45

58.10-154.17

3/7/20 15:50

58.10-154.16

4.7

225.3

20.0

38.0

510.0

-60.1

DY2003

10AWT

5

3/8/20 3:14

57.88

-154.01

3/8/20 3:24

57.87

-154.01

9.7

159.2

26.3

26.1

362.3

-61.9

DY20039LFS

5

3/8/20 0:46

57.88

-154.01

3/8/20 0:55

57.87

-154.01

9.0

160.3

20.2

39.6

318.5

-66.1

DY2003

11AWT

6

3/8/20 7:50

57.94

-154.55

3/8/20 7:55

57.93

-154.56

5.3

175.0

29.5

33.0

400.0

-63.6

DY200312LFS

6

3/8/20 10:12

57.93-154.56

3/8/20 10:19

57.93-154.57

6.9

164.7

19.5

31.3

355.0

-63.1

DY200318

AWT

7

3/11/20 5:36

57.99

-154.37

3/11/20 5:38

57.99

-154.36

2.2

223.3

N/A

N/A

N/A

-56.0

DY200319

LFS

7

3/11/20 8:24

57.99

-154.37

3/11/20 8:27

57.99

-154.37

3.5

230.2

24.5

32.0

410.0

-62.7

DY200321

AWT

8

3/11/20 13:59

57.99-154.38

3/11/20 14:09

57.99-154.37

10.2

228.1

21.0

30.0

463.7

-63.7

DY200320

LFS

8

3/11/20 11:11

57.99-154.36

3/11/20 11:25

58.00-154.35

14.0

222.4

23.0

32.0

399.0

-61.7

DY200322

AWT

9

3/11/20 19:38

57.92-154.53

3/11/20 19:49

57.93-154.55

11.1

219.9

21.0

30.0

489.1

-62.9

DY200323

LFS

9

3/11/20 22:27

57.92-154.53

3/11/20 22:39

57.93-154.55

11.5

225.7

17.0

38.1

530.8

-60.1

DY2003

25

AWT

10

3/12/20 3:21

57.91

-154.59

3/12/20 3:30

57.92

-154.58

9.1

N/A

23.0

25.0

450.0

-61.4

DY2003

24

LFS

10

3/12/20 0:31

57.92

-154.57

3/12/20 0:41

57.92

-154.56

10.0

N/A

19.6

31.4

428.2

-60.4

DY2003

27

AWT

11

3/12/20 9:55

57.87

-154.813/12/20 10:01

57.87-154.81

6.0

207.5

24.0

20.0

395.0

-59.9

DY2003

26

LFS

11

3/12/20 6:39

57.86

-154.813/12/20 6:54

57.87

-154.81

15.0

N/A

24.0

26.0

420.0

-61.1

DY2003

15

AWT

12

2/27/20 17:38

57.86-153.96

2/27/20 17:43

57.86-153.97

5.0

162.4

21.5

39.5

430.0

-63.7

DY2003

16

LFS

12

2/27/20 20:29

57.87-153.95

2/27/20 20:39

57.86-153.96

9.8

163.5

12.5

42.0

495.2

-68.3

DY2002

4

AWT

1

2/21/20 4:31

53.58

-167.80

2/21/20 4:33

53.58

-167.80

1.8

347.3

28.5

47.0

660.0

-53.9

DY20025LFS

1

2/21/20 7:51

53.58

-167.81

2/21/20 7:54

53.58

-167.81

2.2

261.1

15.9

43.6

625.4

-48.2

DY2002

7AWT

2

2/21/20 14:22

53.58-167.88

2/21/20 14:26

53.58-167.88

4.0

259.9

24.0

45.0

540.0

-51.3

DY20026LFS

2

2/21/20 11:18

53.58-167.88

2/21/20 11:20

53.58-167.88

1.8

256.1

20.9

44.5

539.5

-54.1

DY20028

AWT

3

2/22/20 9:30

53.08

-169.04

2/22/20 9:38

53.09

-169.04

8.0

266.1

30.7

44.5

481.5

-65.0

DY20029LFS

3

2/22/20 12:42

53.09-169.04

2/22/20 13:15

53.12-169.05

33.7

308.3

21.6

41.5

562.5

-65.0

DY2002

11

AWT

4

2/22/20 23:59

53.14-169.13

2/23/20 0:04

53.13

-169.12

5.0

367.6

36.0

40.0

710.0

-57.7

DY200210LFS

42/22/20 20:43

53.14-169.13

2/22/20 20:44

53.14-169.13

0.8

345.6

20.0

34.0

800.0

-48.4

35

DY2002

12

AWT

5

2/23/20 3:41

53.13

-169.12

2/23/20 3:45

53.12

-169.12

4.3

346.2

34.0

41.5

740.0

-64.8

DY200213

LFS

5

2/23/20 7:01

53.13

-169.13

2/23/20 7:19

53.11

-169.11

18.3

378.5

20.0

39.5

743.5

N/A

36

37

38

39

Appendix Figure 1. -- Individual haul paired comparisons of pollock length proportions from the
DY1906 summer OA survey (a1-2), the DY2002 Bogoslof Island wintersurvey (b), and the DY20003 Shelikof Strait winter survey (c).
40

41

U.S. Secretary of Commerce

Gina M. Raimondo

Under Secretary of Commerce for
Oceans and Atmosphere

Dr. Richard W. Spinrad

Assistant Administrator, National Marine
Fisheries Service.

Janet Coit

April 2024
www.nmfs.noaa.gov
OFFICIAL BUSINESSNational Marine
Fisheries Service

Alaska Fisheries Science Center
7600 Sand Point Way N.E.
Seattle, WA 98115-6349